analysis of the high-energy emission of the bl lac pks ...843045/fulltext01.pdf · pks 2155-304, an...

Degree project

Analysis of the high-energy

emission of the BL Lac

PKS 2155-304 with

Fermi-LAT-data

Author: Tobias Möllerström

Supervisor: Yvonne Becherini

Examiner: Arvid Pohl

Date: 2015-06-02

Course Code: 2FY80E

Subject: Physics

Level: Bachelor degree

Department Of Physics and electrical

Engineering

Abstract

Some of the most interesting objects in the Universe are Active Galactic Nuclei. In the centreof an active galaxy is a supermassive black hole that accretes matter from the surroundinggalaxy. In the process, not yet fully understood, some of the matter is ejected in two jets,perpendicular to the plane of the galaxy. The energy of the particles in the jets are extremelyhigh, sometimes over 1019 eV. The features of an active galaxy can be very different dependingon from which angle it is viewed. This means that some astronomical objects that earlierseemed to be very heterogeneous might be only different manifestations of the same type ofobject, namely active galactic nuclei. This thesis introduces some of these different objects.The unifying theory is described. Ways of detecting the high-energy radiation and twoimportant instruments, H.E.S.S. and Fermi-LAT are described. Three studies of the BL LacPKS 2155-304, an active galactic nucleus that points its jet almost straight at Earth, aremade using Fermi-LAT data. The conclusion of the studies is that the source is variable atleast in the time scale of days and that in order to gather further information about theseobjects simultaneous multi-wavelength surveys have to be done.

Acknowledgements

I would like to thank my supervisor Yvonne Becherini who opened up my eyes to the worldof Very High Energy Gamma radiation and Active Galactic Nuclei. Without her help ingiving me access and introducing me to vastly data sets and large computational resourcesthis thesis couldn’t be made. Her expertise and fantastic eye for details are impressive.

I would also like to thank all persons posing and answering questions at forums and alsowriting and recording tutorials concerning LATEX, LYX and Linux.

Last but not least, I am very grateful for the support from my partner and my childrenduring the last three years of studies.

Contents

Abstract i

Acknowledgements ii

Introduction 1

1 Active galactic nuclei 3

1.1 Different types of AGN . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31.1.1 Quasars . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31.1.2 BL Lac object . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51.1.3 Blazars . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61.1.4 Radio galaxies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61.1.5 Seyfert galaxies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

1.2 A unifying model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71.2.1 The accretion disk . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81.2.2 The jet . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

1.3 Radiation production . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91.3.1 Synchrotron radiation . . . . . . . . . . . . . . . . . . . . . . . . . . 91.3.2 Inverse Compton radiation . . . . . . . . . . . . . . . . . . . . . . . . 10

1.3.2.1 Compton radiation . . . . . . . . . . . . . . . . . . . . . . . 101.3.2.2 Inverse Compton radiation . . . . . . . . . . . . . . . . . . . 11

1.3.3 Synchrotron Self Compton . . . . . . . . . . . . . . . . . . . . . . . . 11

2 Cosmic radiation in the atmosphere 13

2.1 Cosmic radiation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 132.2 Atmospheric showers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14

2.2.1 Electromagnetic shower . . . . . . . . . . . . . . . . . . . . . . . . . 142.2.2 Hadronic shower . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15

2.2.2.1 Hadrons . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 152.2.2.2 Interaction in the Hadronic shower . . . . . . . . . . . . . . 16

2.3 Cherenkov radiation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 172.3.1 Faster than light . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 172.3.2 Cherenkov light . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 172.3.3 Cherenkov angle and the speed of the particle . . . . . . . . . . . . . 18

iii

CONTENTS iv

3 Detection of high-energy gamma-rays 21

3.1 The Cherenkov cone in the atmosphere . . . . . . . . . . . . . . . . . . . . . 213.1.1 Dependency of the Cherenkov angle from height . . . . . . . . . . . . 213.1.2 The Cherenkov light when reaching the ground . . . . . . . . . . . . 21

3.2 Factors affecting the light output in the atmosphere . . . . . . . . . . . . . . 223.3 Detection of gamma-rays with IACT . . . . . . . . . . . . . . . . . . . . . . 243.4 The H.E.S.S. observatory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26

3.4.1 The telescope structure and mirrors . . . . . . . . . . . . . . . . . . . 263.4.1.1 CT1-CT4 . . . . . . . . . . . . . . . . . . . . . . . . . . . . 263.4.1.2 The new large-area telescope . . . . . . . . . . . . . . . . . 27

3.4.2 The cameras . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 273.4.3 Progress in the field thanks to H.E.S.S. . . . . . . . . . . . . . . . . . 28

3.5 The Fermi Large Area Telescope . . . . . . . . . . . . . . . . . . . . . . . . . 283.5.1 The detector . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29

4 PKS 2155-304 and already published results 31

4.1 Early observations from H.E.S.S . . . . . . . . . . . . . . . . . . . . . . . . . 314.2 Multi-wavelength observations in 2003 . . . . . . . . . . . . . . . . . . . . . 324.3 Exceptional flares in 2006 . . . . . . . . . . . . . . . . . . . . . . . . . . . . 324.4 Meta data from ASDC database . . . . . . . . . . . . . . . . . . . . . . . . . 33

5 Methods and accuracy of results 35

5.1 Three studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 355.2 Computer processing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 355.3 Models of fitting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36

5.3.1 PowerLaw2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 365.3.2 LogParabola . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37

5.4 Accuracy of the results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 375.4.1 Test statistics and likelihood-ratio test . . . . . . . . . . . . . . . . . 375.4.2 Residuals plot . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 385.4.3 Counts Plot . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 395.4.4 Accuracy for the light curve . . . . . . . . . . . . . . . . . . . . . . . 39

5.5 MET - Mission Elapsed Time . . . . . . . . . . . . . . . . . . . . . . . . . . 40

6 Results of the analysis of PKS 2155-304 41

6.1 Analysis of PKS 2155-304, first study . . . . . . . . . . . . . . . . . . . . . 416.1.1 Results for the different intervals . . . . . . . . . . . . . . . . . . . . 41

6.1.1.1 Interval 1a: High-flux state . . . . . . . . . . . . . . . . . . 436.1.1.2 Interval 1b: Low-flux state . . . . . . . . . . . . . . . . . . . 436.1.1.3 Interval 1c: High-flux state . . . . . . . . . . . . . . . . . . 436.1.1.4 Interval 1d: Low-flux state . . . . . . . . . . . . . . . . . . . 436.1.1.5 Interval 1e: High flux-state . . . . . . . . . . . . . . . . . . 43

6.2 Analysis of PKS 2155-304, second study . . . . . . . . . . . . . . . . . . . . 436.2.0.6 Interval 2a High-flux state . . . . . . . . . . . . . . . . . . . 496.2.0.7 Interval 2b Low-flux state . . . . . . . . . . . . . . . . . . . 49

6.3 Analysis of PKS 2155-304, third study . . . . . . . . . . . . . . . . . . . . . 496.3.1 Light curve for the interval 3a . . . . . . . . . . . . . . . . . . . . . . 52

CONTENTS v

6.3.2 Light curve for the interval 3b . . . . . . . . . . . . . . . . . . . . . . 526.3.3 Spectral analysis of the interval 3c . . . . . . . . . . . . . . . . . . . 55

7 Discussion 57

7.1 Model of best fit . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 577.2 Variability of a high-flux state . . . . . . . . . . . . . . . . . . . . . . . . . . 577.3 Spectral Energy Distribution . . . . . . . . . . . . . . . . . . . . . . . . . . . 58

8 Conclusions 60

Bibliography 61

Supplement 64

Details on the computer analysis . . . . . . . . . . . . . . . . . . . . . . . . 65Example of configuration file . . . . . . . . . . . . . . . . . . . . . . . . . . 67

Introduction

The cosmos and the space that encircles the life of humans has always been stimulating to theimagination. Fascinatingly, it is often the reality that is pushing our imagination further. Toimagine a place where some things disappear and never come back is possible, but imagininga black hole that has the power to swallow the whole earth, the sun and even galaxies isastonishing. It is a privilege to be working with these thoughts and to further investigateour outermost environment. The aim of this thesis is getting a closer look to somethingeven more wondrous than black holes - the active galactic nuclei, AGN. At the centre of anactive galaxy is the nucleus. It consists of a black hole, but it is more to it than that. Theblack hole is accreting matter from the inner parts of the surrounding galactic disk. Andeven more things happen. We are not able to fully understand all the processes involved,but by tangled magnetic fields, gravity, and rapidly moving particles there is matter ejectedfrom the nucleus. Some of the particles are accelerated to ultra-relativistic speeds. Photonsare created during the acceleration of particles with mass. Some of those photons reach us.They can be very energetic. Other photons, still in the jet, are pushed into even higherenergies by the particles with mass and also reach us. The model currently explaining theVery High Energy gamma-ray emission from AGNs is called the Synchrotron Self Comptonmodel, which has two bumps on its Spectral Energy Distribution. Not all of the jets of AGNsare pointed towards us. Some of them we see from the side or in other angles. This meansthat a lot of extragalactic objects that before were believed to be very different has a lot incommon. The most energetic particles accelerated in the jets are so energetic that even ourstrongest particle accelerator on Earth just reaches a small fraction of it 1.

The different gamma-ray energies from AGNs span over several orders of magnitude. Weuse different instruments to detect the radiation. The rays with the highest energies is bestdetected on Earth. They are not very common so a small telescope would not catch a lotof them. Instead we use our whole atmosphere as a collector. When the gamma-rays enterthe atmosphere they interact with the particles in the air. It is then possible to measure theCherenkov light they give rise to. This kind of data collection is made, for example, by theHigh Energy Stereoscopic System (H.E.S.S.), an array of telescopes in Namibia. This thesiscontains a lot of information about the H.E.S.S. and the effects of the cosmic radiation inthe atmosphere. Telescopes like H.E.S.S. are crucial to be able to learn more about AGNs.These telescopes are able to detect the highest-energy gamma-rays (E > 50GeV) with highaccuracy. For gamma-ray energies in the range 100MeV−100GeV we have satellites circlingthe Earth. In this thesis, data from the Fermi-Large Area Telescope have been used. In orderto analyse these data, a lot of computing power has to be used. This computing power isprovided for us by Alarik, a computer with over 3000 processors. The communication with

1The highest energy reached on Earth is 13TeV, while, as mentioned earlier, there could be protonsaccelerated up to 1019 eV = 107 TeV.

1

CONTENTS 2

Alarik is done via Linux commands.The thesis treats AGN in general and one of them, PKS 2155-304, in particular. PKS 2155-304

has shown some really interesting features especially in the fact that it is a variable source.It has lower flux states and higher flux states. This is investigated further in the thesis in twodifferent ways. Finally a comparison with data from a vast collection of telescopes is beingmade, in order to see how my fits compare to the other observations.

Chapter 1

Active galactic nuclei

During the last decades a unifying theory has brought together seemingly different kindsof radiative objects outside our galaxy. These objects are for example radio-loud galaxies,radio-quiet galaxies, objects with broad line spectrum, objects with narrow line spectrum,quasars, blazars, BL Lac objects and Seyfert galaxies with or without polarization. Theircommon properties are being understood through a unifying theory, saying that they aregalaxies with an active nucleus, a black hole that accretes matter from the accretion disc inthe inner part of the galaxy. Perpendicular to the galactic plane and centered are two jetswhere particles emanate with extreme energies, see Fig. 1.1.

The reason the objects look so different from each other only depends on the angle inwhich we observe them, see [36], and also Fig. 1.2. There are differences between the objects,but it is now believed that they are just a different manifestation of the same type of object.In this chapter some of these different objects will be described and the unifying model willbe explained. The current best model for explaining their radiation will also be introduced.

1.1 Different types of AGN

1.1.1 Quasars

The name quasar is an abbreviation for the name quasi-stellar radio source, see [49], meaning“almost like a star”. Since not all quasars emit radio radiation it is also possible to use thename QSO (quasi-stellar object). From here only the name quasar will be used.

Emission lines plays an important role in astrophysics. When an electron changes itsenergy state from a higher to a lower, a photon is emitted. Since the energy states arequantized but differ from element to element, each element has its “fingerprint” that can bedetected by looking at the wavelengths of the emitted photons. Of the full spectrum onlysome wavelengths are detected. These lines in the spectrum are the spectral emission lines.The characteristic emission lines in the optical spectrum from hydrogen are called the Balmerlines.

In 1963 the optical emission lines of the radio source 3C273, one of our nearest quasars,was interpreted by astronomer Maarten Schmidt. Assuming the emission lines were redshiftedby 16 % they coincided with the hydrogen Balmer lines, see [49]. The conclusion was thatthe source carried hydrogen and was at a very large distance (z = 0.16). For that time, itwas the largest redshift ever detected and thus the most distant object found. Later, even

3

CHAPTER 1. ACTIVE GALACTIC NUCLEI 4

Figure 1.1: Scheme explaining the powerful central engine of an AGN. See text for details.Credit: [33]

Figure 1.2: A sketch showing how different observing angles affect which kind of ActiveGalactic Nucleus we see.


Figure 1.3: An example of the spectrumfrom a BL Lac. DIB stands for Diffuse In-terstellar Band and ISM is the InterstellarMedium. The dips where ⊕ is positionedare caused by the Earth. Credit: [19]

Figure 1.4: An example of the spectrumfrom a quasar as comparison to the spec-trum of the BL Lac to the left. Credit:[22]

larger redshifts have been measured from other quasars. The largest measured redshift for aquasar is 6.3.

This means that the oldest quasars are objects from the early Universe, when the Universewas not much more than about a billion years old, see [49]. This makes them importantsources in the history of galaxies and of the Universe. Since quasars can be very far awaybut still observable, this means that their luminosity has to be very large. The radiation isvery strong and the source looks almost point-like, but with today’s improved observationalmethods it is often possible to see that the quasar is at the centre of a galaxy. The quasaris in comparison to its intensity very small and outshines its galaxy. Some quasars have avariable brightness, variability in quasars can be as fast as few days. This means they can’tbe more than 100AU across, see [49]. In the spectrum of the quasars there are both emissionand absorption lines. The emitting region is moving and spinning with high velocities, thusemission lines are broadened by the Doppler effect. The absorption lines suggest there aregas clouds in the proximity of the quasar traversed by the radiation emitted.

1.1.2 BL Lac object

The name BL Lac object means an object with the same properties as the BL Lacertae,see [49]. BL Lacertae was first discovered in 1929 and was then thought to be a variablestar in the Milky way. In 1968 radio analyses showed that it was a radio source and it wasalso possible to detect a galaxy around it. It was clear that BL Lacertae was the centre of agalaxy, not a star and not at all in the Milky way. Some years later the redshift was measuredto be 0.07. The main properties of a BL Lac object are the highly variable flux amplitudeand the optical polarization. There are almost no emission lines in the optical spectra, whichmakes it difficult to measure the distance to these objects, see [54], since it is displacementof the emission lines that reveals the magnitude of the redshift. An example of the flat andalmost featureless spectrum from a BL Lac is seen in Fig. 1.3.

Comparing this to a quasar spectrum makes the difference between them clear, see Fig.1.4.

BL Lacs are radio loud and have a relativistic jet, see Sec. 1.2 that almost points straight


Figure 1.5: Left: The radio-galaxy Centaurus A, the closest AGN to Earth, seen at variouswavelengths: radio, optical and X-rays. The two bipolar jets and inner lobes propagate oneither side of the active nucleus, perpendicular to the galactic disk. Centaurus A has alsotwo giant radio lobes which extend over 10 deg (not visible in the picture). Credit: [4] Right:the radio-galaxy M87 seen with the VLA and with HALCA + VLBI (in the inset) at 1.6GHz. Credit: M. Reid, CfA.

to the observer. Since the absence or the very weak emission lines makes it hard to measurethe distance to the object, it is possible to use the optical spectra of the surrounding galaxyinstead, see [54]. The radiation from the surrounding galaxy is thermal emission and fromthe jet non-thermal.

Many observations from new very-high-energy (VHE: E > 100GeV) observatories likethe H.E.S.S. (see also Sec. 3.4) and the MAGIC, see [9], have been and are currently beingmade of BL Lac objects. One can thus expect to learn more about BL Lacs in the next fewyears, and of course it is expected that the VHE BL Lac catalogue will be increased.

1.1.3 Blazars

The name blazar is a mix of the BL Lac object and quasar. It is a subgroup of quasars withthe relativistic jet pointed straight at the observer. This means that Blazars are the mostenergetic objects we can detect, maybe also the most energetic objects in the Universe.

Both the brightness and the polarization vary extremely. The emission lines are as in BLlac objects very weak or even invisible, see [49]. The jet is pushing the matter outward inrelativistic speeds that in some cases can be seen as a superluminal motion. The matter isactually not superluminal but can appear to be so depending on in which narrow angle thejet is pointing towards the observer.

1.1.4 Radio galaxies

A radio galaxy is an active galaxy characterized by a very strong emission in the radiowavelength. The total amount of emitted energy from an average galaxy is between 1033 Wand 1038 W. This is about the same energy that an average radio galaxy emits only in theradio wavelengths, see [49]. A radio galaxy has typically two large radio emitting regions(called "lobes") which are often symmetrical, roughly ellipsoidal structures placed on eitherside of the active nucleus, see Fig. 1.5 for the case of Cen A and M87. In radio-galaxiesthere is an angle between the observer and the jet, and this allows observatories to see thestructure of the object. The radio emission is concentrated in the lobes forming at the end


of the bipolar jets, which emit also in X-rays, while the bulk optical emission is from thestars composing the host galaxy. The formation of the radio lobes is probably due to the jetsexpanding from the position of the active galactic nucleus. The radio emission is due to theacceleration of highly-relativistic electrons in the jet, which produce synchrotron radiationin the presence of a magnetic field. In the jets there are often visible point-like hot spots,which are strong emitters in the X-ray region. These spots are probably due to a shock wavecreated by the jet. The other important emitting process is the inverse Compton radiation,see Sec. 1.3.2.

1.1.5 Seyfert galaxies

The emission lines from Seyfert galaxies are broad and there is a non-thermal componentbest seen in the ultraviolet wavelengths. It is believed that the emission lines come from a gascloud with a large internal movement, surrounding the galaxy nucleus. When the particlesin the highly-ionized gas cloud move fast and spin around, their emission lines broaden, dueto the Doppler effect. Seyfert galaxies are divided into type I and type II, depending on theirspectrum.

Both allowed and forbidden lines 1 are seen in the spectrum from Seyfert I galaxies. Theemission of a forbidden line indicates a very low gas density, in order for the electrons tosurvive in higher orbits without collisions and thus emission of rare wavelengths. In SeyfertI galaxies the width of the allowed lines are much broader than for the forbidden lines. Theallowed lines originate from dense gas-clouds close to the start of the jet, see [5]. The widthof the allowed lines suggests that the emitting matter has a speed up to 106 m/s, see [5].

In the Seyfert galaxies of type II, emission lines are less broad than in type I. Allowedand forbidden lines have the same line width, suggesting velocities less than 103 m/s, see [49].Since forbidden lines only can occur in low-density gas, the difference between type I andtype II Seyfert galaxies can be explained with the absence of denser clouds in type II. Morelikely, the denser cloud is obscured, so that the broadening of the emission lines is disfavored.A possible scenario is that the dense cloud with large internal movement is closer to thegalactic nucleus, and that a torus-shaped low-density cloud surrounds it. Depending on theline of sight the inner cloud is either seen together with the outer torus or it is obscured,resulting in that only the lesser dense torus is seen.

1.2 A unifying model

All these apparently different sources of radiation are likely to be of the same kind - anactive galactic nucleus with an accretion disk in one plane, see Fig. 1.6. The nucleus and thedisk are spherically surrounded by a rather dense gas cloud, ρ > 108 cm−3. Outside this gascloud, in the same plane as the disk, we find a torus-shaped gas cloud with lower density,103 < ρ < 106 cm−3. Perpendicular to the disk plane are two jets that beam out particles atrelativistic speeds. If one of those jets is pointed towards the observer, we see a blazar. If thejet is almost pointed to the observer, we see a quasar or a BL Lac object. When angling theAGN further the observer sees the inner dense gas cloud with its broad line spectrum thus aSeyfert I galaxy. Turning even more the inner gas cloud is obscured by the outer torus and

1A forbidden line is a spectral line which is very improbable, not really forbidden


Figure 1.6: A schematic view of the AGN Unified model. Notice the arrows indicating theline of sight for the observation. Credit: [53]

we see a Seyfert II galaxy. The strong radio lobes are situated at a great distance from thenucleus and are seen when not looking at the nucleus itself.

1.2.1 The accretion disk

When observing and formulating theories about the accretion disk in an AGN, it is possibleto compare it to the accretion disk in a micro-quasar or a X-ray binary. These objects aremuch smaller in scale and are much closer to us. Many of them are in the Milky way. Amicro-quasar is a black hole from a dead star accreting matter from a nearby less denserobject, as for example a normal star. Because the black hole spins, the accreting materialsurrounds it like a disk perpendicular to the rotational axis. The disk is not the only similaritybetween the quasar and the micro-quasar. What makes them interesting to study, from aquasar perspective, is their jet. Just as the AGNs, the micro-quasars have two relativistic,bipolar jets perpendicular to the disk. The underlying physics in the process is not clear, itis a unresolved problem. What is clear is that the only way to create such energetic radiationas in the jets of AGNs is connected to gravity.

The most efficient nuclear fusion process is the proton-proton chain, where the energyreleased , related to the mass involved is, see [53]

∆Enuc

m= 0.007c2 ⇡ 6 · 1018 erg/g (1.1)

The energy released from a neutron star can not be calculated exactly but a good estimatefor a neutron star with a radius R = 10 km, with mass m = M$, that accretes a mass mfrom its accretion disk can be given by

∆Eacc

m=

GM

R⇡ 1020 erg/g (1.2)


This means that the accretion process is up to a hundred times more efficient than thenuclear process.

One problem to take into account when dealing with the accretion disk is that it circlesaround a black hole and in the case of an AGN, the black hole is supermassive, i.e. the massis equal to 106 − 109 M$, see [50]. This means that the space-time is extremely curved andthat so close to the event horizon it is hard to say what is really happening. Nevertheless,broadly what is taking place in the accretion disk is that particles are circling the black holeat various distances. Every particle has an angular momentum. Some particles circles instable orbits and some in unstable ones. Particles at a distance given by rmin = 6GM/c2,and with an unstable orbit, will fall into the black hole faster than they can radiate anyenergy.

But if particles are in a stable orbit, they will slowly change orbit getting closer to theblack hole, due to viscose torques acting on the particles. With every new closer orbit theparticle loses angular momentum. This will continue till the point particles reach the lastpossible stable orbit at rmin then they will fall into the black hole. So every particle in astable orbit has an energy loss in angular momentum every time it changes orbit. Somehow,in ways that are not yet fully understood, this energy is transferred into the jet, see [53].There seems to be an intrinsic relationship between an accretion disk and a jet, since where ajet is found an accretion disk is also found. On the other hand, no direct correlation betweenhow fast matter is accreted and the luminosity of the jet seems to exist, see [50].

1.2.2 The jet

The jet seen perpendicular to the accretion disk consists of highly energetic particles andmagnetic fields. These particles are beamed out from the position of the black hole athighly relativistic speeds. When modeling the jet charged particles are often considered tobe electrons, see [50], but presumably there are also other leptons and protons, see [48]. Oneway of explaining the jet’s direction is that when orbiting matter is moving inwards it bringsalso the magnetic field lines. This is possible since both the accretion disk and the black holeare spinning. Close to the black hole the magnetic field lines become close and tangled. Thesetangling magnetic field lines give rise to a voltage inducing a current, see [50], and this mightbe why the jets are created, but there are also other theories explaining the mechanism.

1.3 Radiation production

In the jets there are electrically charged particles traveling at relativistic speeds and thereis a strong magnetic field. The radiation we observe from AGN spans from radio waves togamma-rays. The process driving the emission is most probably due to Synchrotron radiationand Inverse Compton Scattering. Both these processes are described below.

1.3.1 Synchrotron radiation

Synchrotron radiation occurs when electrically charged particles with high speed are accel-erated in a curved path in a magnetic field. It consists of photons of various energies, fromradio wavelengths to X-rays. Example of electron synchrotrons on earth was the LEP (Large


Figure 1.7: Left: Synchrotron radiation emitted by an electron moving in a magnetic field.Credit: Pearson Education. Right: scheme of an AGN. The magnetic field structure in thejet is also shown. Credit: [18]

Electron-Positron Collider) at CERN and will be the MAX IV in Lund. The radiation cre-ated can be used in different research fields. The radiation emitted from the particle is inthe tangent of the particle’s curved path, see Fig. 1.7.

1.3.2 Inverse Compton radiation

1.3.2.1 Compton radiation

In order to understand Inverse Compton radiation a brief review of Compton radiation followshere. Compton radiation is named after the american physicist Arthur Compton who in 1921looked in to the wavelength shift of X-rays when scattered by a scattering material, see [47].

He found that the shift in wavelength depended on the angle of scattering, see Fig. 1.8.The model of explaining this was to treat the electron as a quasi-free particle and the X-raynot as a wave but also a particle. What was new in this time was the idea of treating theX-rays as particles with a momentum. However, by doing this, the scattering effect could beexplained treating it as an elastic collision. The collision taking place is between an electronat rest and a massless photon with momentum. The consequence of the collision is thatthe photon passes over some of its momentum to the electron. The law of conservation ofmomentum is valid and since the electron in the model goes from being at rest to a speed in acertain direction, the electron momentum comes from the photon. Depending at which angle(θ) the photon is collected after the collision it has different wavelength (λ0). The greater theangle the more momentum is transferred to the electron, following the formula

λ0 − λ =h

moc(1− cos θ) (1.3)

where mo is the mass of the electron, c is the speed of light and h is Planck’s constant. Themaximum difference in wavelength occurs when the scattering angle (θ) is 180°.


Figure 1.8: An elastic collision between a photon and an electron. The direction of thephoton is changed.

1.3.2.2 Inverse Compton radiation

In the jet from an AGN, electrons and other charged particles travel with very high speeds.If one of those particles collide with a photon with low energy the photon will increase

its momentum. Energy and thus also wavelength of the photon will change. This meansthat for example a photon with a wavelength in the X-ray spectra can be up scattered togamma-ray energies. This is a very probable cause of the high-energy and very-high-energygamma-ray radiation in AGNs, and under this assumption this constitutes the second humpin their Spectral Energy Distribution (SED), see Fig. 1.9. Almost all of the photons thatare up scattered have their origin from the synchrotron radiation. There might be photonsfrom other sources as well, for example the accretion disk or nearby molecular clouds, see[53]. These can be neglected since the predominant source is the jet.

1.3.3 Synchrotron Self Compton

The photons created in the jet lie in the energy spectrum from radio to X-rays, see Fig. 1.9.These photons can be boosted in energy by the inverse Compton scattering mechanism. Thisexplains why the blazar emission consists of both a component at low energy and a componentat higher energies. This mechanism is called the Synchrotron Self Compton model.


Figure 1.9: The SSC model proposing the origin of the low and high energy emission seen inblazar jets. Credit: [53]

Chapter 2

Cosmic radiation in the atmosphere

2.1 Cosmic radiation

In the beginning of the twentieth century, 1912, Victor Hess, detected some kind of radiationof unknown source, see [35]. During experiments with balloons he noticed that the radiationincreased further up in the atmosphere. To rule out that the radiation came from the sunhe also carried out balloon flights at night time. He concluded that Earth receives radiationfrom space and a new field of research was born, cosmic rays physics. The energy of cosmicrays span over a wide range of energies, from about 107 eV to about 1020 eV, see [35]. Theflux of cosmic rays at low energy is higher than the flux at higher energies. As seen in Fig.2.1, the spectrum is steep as a function of energy, at 1019 eV for example there is only aboutone event per km², per year, so this means that one needs very large detectors in order tocatch these extremely-high-energy particles.

For most astronomical observations the atmosphere creates a disturbance, as weather canbe cloudy or there can be turbulence in the air. For observations of high-energy cosmic rays,it is possible to make use of the atmosphere as a calorimeter, and thus reconstruct the arrivaldirection and energy of the incoming cosmic ray. When a primary cosmic ray particle, asfor instance a proton, collides with an atomic nucleus composing the atmosphere, a cascadeof secondary particles are created. These secondary particles create new particles throughnew collisions or decays. This process generates a "particle cascade" or a "Extensive AirShower" (EAS) in the atmosphere, see [35]. The particle shower content can be detecteddirectly or indirectly. The indirect detection is based on the fact that the particles created inthe cascade process are relativistic, and thus their passage in atmosphere can generate lightthrough the Cherenkov effect, see Sec. 2.3.

About 99 %, of the cosmic radiation consists of electrically charged particles such asprotons, α-particles and other ionized nuclei. Electrons constitute about 1 % of the flux,see [53]. The cosmic radiation also consists of neutrinos and photons. The neutrino do notcreate an EAS in atmosphere since it is a weakly interacting particle, and thus can traversethe atmosphere and the Earth undisturbed. The electrically charged portion of the cosmicradiation has a main drawback: since this flux is electrically charged, it can be deflected bymagnetic fields, especially at low energies. The Earth has a magnetic field, and even duringtheir journey from the point in which they were created, they might have been diverted fromtheir original path by inter-galactic and extra-galactic magnetic fields. This means that, forlow-energy cosmic rays, it is not possible to determine their origin. Luckily, cosmic radiationalso consists of photons. Allthough the photon flux constitutes only about 0, 1% of the

13

CHAPTER 2. COSMIC RADIATION IN THE ATMOSPHERE 14

Figure 2.1: The flux of cosmic rays at different energies at the top of the atmosphere. Theflux changes over 31 orders of magnitude, while the energy range spans over 12 decades.Credit: Swordy, S.

cosmic radiation, photons at all energies are the perfect messengers for astronomy.

2.2 Atmospheric showers

Cosmic-rays hit the Earth’s atmosphere at all times. They interact with the atmospheregiving rise to a cascade of particles which then can decay into other particles. This is calledan atmospheric shower because of the resemblance of an ordinary shower with a small nozzlein the top and then a widening area of water further down. We can distinguish between twotypes of atmospheric showers depending on whether the incident particle is of electromagneticnature, i.e. a gamma-ray, an electron or a positron, or if it is a proton or heavier nucleus.

2.2.1 Electromagnetic shower

An electromagnetic shower develops as an iterated interaction between gamma-rays andelectrons/positrons. There are two main parts of the interaction. The first part is whena very-high-energy gamma-ray photon (γHE) enters the atmosphere and comes close to anucleus. If the γHE has enough energy it can create a electron-positron pair, with thefollowing electromagnetic interaction

γHE + γ⇤ ! e+ + e− (2.1)

where γ⇤ can be a real photon or a virtual photon of the nuclear Coulomb force.


Figure 2.2: Simplified model of an electromagnetic shower. Credit: [53]

The second part happens when the electron and/or the positron are being deflected in theproximity of a nucleus. In the deflection, kinetic energy is loss in the form of a Bremsstrahlungphoton. The Bremsstrahlung emission also takes place in a synchrotron where an electron isconstantly accelerated. In an electromagnetic shower the electron and the positron travel atvery high speeds. This means that the Bremsstrahlung photon emitted can be of very highenergy too. The photon emitted can in turn interact with a nucleus producing an other e+e−

pair and so the process is repeated, see Fig. 2.2. The process continues as long as there isenough energy in Bremsstrahlung photons to create new e+e− pairs. Electron with energybelow that threshold can still interact with nuclei. There will then not be a photon emissionbut rather an ionization of the nucleus. The electromagnetic shower development ends. Inthis description of the whole process, the shower development started with a γHE enteringthe atmosphere. It can of course also start with an electron or a positron, since the processis repetitive.

2.2.2 Hadronic shower

2.2.2.1 Hadrons

An EAS can also be produced by a hadronic particle. A hadron is a particle made up ofquarks glued together by the strong force. There are two subgroups among the hadrons.Firstly there are the baryons, made up of three quarks. Example of baryons are protons andneutrons. The other subgroup is composed by mesons. They consist of one quark and oneantiquark. Example of mesons are kaons and pions, see [32]. Examples of particles that arenot hadrons are electrons and muons, they are leptons.


Figure 2.3: A schematic picture that interprets the fact that the core of the EAS is dominatedby hadronic particle interactions. Credit: [30]

2.2.2.2 Interaction in the Hadronic shower

The hadronic EAS starts with a hadronic particle entering the atmosphere and interactingwith a atomic nucleus in the atmosphere. In the processes that follow after that first interac-tion we will see both other hadrons, and leptons and photons. It is called a hadronic showerbecause it starts with a hadron.

The first collision between the hadron and the atmospheric atomic nucleus producesmostly pions (about 90%), see [53], partly other nuclei with smaller masses and kaons. Theshower has a core where these hadronic decays continue. The decays in the core continueuntil there is no longer enough energy to create any new meson, see [53]. A schematic pictureof this is seen in Fig. 2.3.

Among the created pions, about 1/3 of these are neutral π0. They are very short-livedwith a mean life time of 8, 4 · 10−17 s, in the pion’s rest frame, see [16]. The likelihood forthe π0 to decay into two photons is 98, 8%, see [16]. This means that a lot of the hadronicshower goes into electromagnetic sub showers which in their turn develop as told in theprevious section. About 1/3 of the first hadrons energy is transformed into electromagneticenergy [53].

The electrically charged pions, π+ and π−, decay into muons, µ+ and µ− where also anaccompanying neutrino is created, νµ or ν̄µ, see [16].

π± ! µ± + νµ(ν̄µ) (2.2)

The k-meson produced can also decay into muons and neutrinos. They can also decayinto pions that in turn decays as introduced above. This means that a lot of muons arecreated. Muons has an mean lifetime of 2, 2µs, see [16], in their rest frame. Because of theirhigh speed they are subject to special relativistic effects, and most of them reach the ground.


Figure 2.4: Simulated electromagnetic and hadronic shower. To the left an electromagnetic,to the right a hadronic. Credit: [51]

If a muon decays, it does so into an electron, an electron antineutrino and a muon neutrino,see [32]:

µ− ! e− + ν̄e + νµ (2.3)

Because of the lateral spread of the decay products the hadronic shower is much widerthan the electromagnetic, see Fig. 2.4.

2.3 Cherenkov radiation

2.3.1 Faster than light

Nothing can travel faster than the speed of light in vacuum, c = 2, 99792458 · 108 m/s. Onthe other hand light does not always travel that fast. In a medium with a refractive indexn the speed is v = c

n. In air, the refractive index depends on pressure, temperature and

the wavelength of the light. For example, yellow light, λ = 600 nm, when temperature isT = 15 °C and air pressure is P = 0, 1MPa gives the refractive index n = 1, 0002763, see[32]. In vacuum n = 1. This means that with the figures given the speed is 0, 028% less thanin vacuum. It is thus possible for a particle to exceed this speed.

2.3.2 Cherenkov light

When a charged particle travels through a dielectric medium, the dipoles of the mediumalter their direction close to the particle. It is like a spherical wave that propagates throughthe medium together with the particle, see [52]. This can be compared to the more easilyunderstood concept in Fig. 2.5 and 2.6. When the speed of the wave producing element, aduck in water or a particle in a dielectric medium, exceeds the speed of the waves produced,


Figure 2.5: A little duck swimming in wa-ter. The circular waves propagate fasterthan the speed of the duck. Credit: [20].

Figure 2.6: A duck swimming faster thanthe propagation speed of the waves. Atriangular coherent front wave occurs.Credit: [23]

we instead see a triangular coherent front wave. When this happens to a charged particle ina dielectric medium, Cherenkov light is emitted by the medium itself. In the cooling waterto a nuclear reactor it is possible to see this characteristic blue light. The charged particlesthere are electrons. Water is a dielectric medium with a refractive index of about n = 1, 3[32].

2.3.3 Cherenkov angle and the speed of the particle

The triangular front wave generated when the charged particle is traveling through the di-electric material can be seen in Fig. 2.7. The angle θ is called the Cherenkov angle. θ isdependent on the refractive index of the medium n. The distance travelled for the particlein a certain time is v · t. When using the relation β = v

cthe distance travelled by the particle

is βct, see Fig. 2.7. The speed of the light in the medium is cn, thus the distance light can

travel in the same time t is cnt. Using this we can obtain the relationship between θ, β and

n, since

cos θ =

βctcnt

!

=1

βn(2.4)

To have any Cherenkov radiation 1βn

has to be less than 1:

βn > 1v

cn > 1

v >c

n(2.5)

thus particle speed has to be larger than the speed of light in that medium.The explanation so far has used a two-dimensional plane but the particle travels in a

three-dimensional space. The Cherenkov angle is the angle in the tip of a cone. When the


Figure 2.7: Cherenkov radiation. The blue (many) arrows shows the direction of theCherenkov radiation, perpendicular to the wave front. The particle has travelled from left toright. Credit:[27]

Figure 2.8: A cone of Cherenkov light. The Cherenkov angle is marked θ.


particle comes from above, the tip of the cone is up and the base of the cone eventually meetsthe ground, see Fig. 2.8.

When detecting such a cone on the ground it is possible to calculate the Cherenkov angle.Knowing this and the refractive index makes it possible to calculate the speed of the particle.If the detection has information about the amount of photons it is also possible to calculatethe energy of the particle and also find out what kind of particle was enabling the mediumto produce light.

Chapter 3

Detection of high-energy gamma-rays

In order to detect the very-high-energy radiation from astrophysical sources, two methodsare used. The Imaging Atmospheric Cherenkov Technique (IACT) and the detection of theprimary particles outside the atmosphere (satellite experiments). In this chapter the methodsand the way of analysing the data are presented: first the detection technique of ground-basedtelescopes and then the detection technique of telescopes installed on satellites.

3.1 The Cherenkov cone in the atmosphere

In the previous chapter, the Cherenkov cone was described for a particle traveling througha ideal medium with constant density and temperature. The atmosphere is not like an idealgas, but by using good approximations it is possible to predict how the Cherenkov light willbehave in the atmosphere.

3.1.1 Dependency of the Cherenkov angle from height

The Cherenkov light spreads out like a cone in the atmosphere. As mentioned before, inEq. 2.4 the cosine value of the Cherenkov angle is inversely proportional to the refractiveindex n. The refractive index on the other hand is dependent, besides the wavelength ofthe light, also on the temperature and on pressure of the air. In the atmosphere neither thetemperature nor the pressure is constant. Using a common approximation, the isothermal-barotropic approximation, see [53], temperature is assumed to be constant while pressurechanges due to height. For the wavelengths concerning Cherenkov light also the dependenceof wavelength can be neglected [53]. The pressure and density of air follows each other. Agood approximation of the refractive index in the atmosphere is then only dependent of thedensity of the air that in turn is dependent of height. An exponential function describeswell the variation of refractive index due to height. So the Cherenkov angle is dependent onheight. This means that the Cherenkov cone does not have the same shape all the way for aparticle traveling down through the atmosphere.

3.1.2 The Cherenkov light when reaching the ground

A larger refractive index means a larger Cherenkov angle. On the way towards the groundthe refractive index is getting larger all the way and thus the Cherenkov angle also gets larger.

21

CHAPTER 3. DETECTION OF HIGH-ENERGY GAMMA-RAYS 22

This suggests that the radius of the cone would grow all the way down too. This is not thecase. Fig. 3.1 schematically explains why.

The radius of the circle on the ground, Rc, is usually about 150m. A radius of 150m cor-responds to an area of 0, 07 km2. This means that from a single electron creating Cherenkovradiation we have a large area to detect that. On the other hand the photon density is notvery high since the area is large.

The light in the outer part of the circle has been produced at a height of 10− 20 km, see[53]. The density of photons in the circle on the ground varies depending on the distancefrom the shower axis. As suggested in the schematic view in Fig. 3.1, there is an increase ofphotons in the outer part of the circle.

This is also what the detection of Cherenkov photons on the ground measures. Photonsare found outside this maximum too, but the density of them rapidly decreases with larger Rc.When the shower axis is aligned with zenith this is the shortest way through the atmosphereto the ground. When the zenith angle of the shower axis increases, photons has to traversemore air and thus there is a larger Rc. A larger Rc with the same amount of photons givesa lesser photon density on the ground.

3.2 Factors affecting the light output in the atmosphere

Visible light in the atmosphere is reduced mainly by dispersion, diffusion and absorption, see[53]. This is something that we see everyday the sun shines. Light with longer wavelengths(red) is not affected by dispersion as much as light with shorter wavelengths (blue). Thisdispersion in the atmosphere is called Rayleigh dispersion and explains why the sky look bluein the day and red in the sunset. In the evening the light has to traverse more atmospherethan when the sun shines from above. Rayleigh dispersion is the main decreasing factor. Thesecond factor is the diffusion, or Mie-diffusion, but this only stands for some percent of thedecrease in output, compared to the dispersion. It is caused mainly by particles of dust andsoot in the atmosphere. More soot diffuses the blue light more and makes for example a redsunset even more red. This is because the diffusion particles is about the same size as thewavelength of the blue light. The red light has a larger wavelength and is not affected asmuch.

An absorption process takes place when the incident light has the same energy as thebond energy in the gas that it traverses [31]. The ozone layer for example absorbs most ofthe the ultraviolet light from the sun.

Cherenkov radiation is emitted in different wavelengths. The relative intensity of a wave-length emitted is inversely proportional the wavelength i.e. the smaller the wavelength, thehigher the relative intensity.1 This suggests that the best wavelength to detect Cherenkovradiation should be as short as possible, but as seen above the factors that decrease thelight in the atmosphere are mainly for the smaller wavelengths. This means that the best

1Variation of Frank-Tamm formula. Number of photons radiated per unit path length in a wavelengthinterval dλ.

N(λ)dλ = 2πα

✓

1−1

β2n2

◆

dλ

λ2

[32]


Figure 3.1: Although the Cherenkov angle increases with lower altitude the radius of theCherenkov cone on the ground is not getting larger since light that spreads out close to theground has a smaller height available. The angles in the figure are exaggerated. Normallythey are about 0-1,5°.


Figure 3.2: In figure (a) the incident light is aligned with the normal of the directrix (notseen) and the light focuses in the parabola focus and thus on the middle spot of the camera,on the photographic pixels located there. In (b) the light comes a bit from the side with anangle β to the normal. This means that the light is focused on another spot on the camerapixels. Credit: [53]

wavelength range for detecting Cherenkov radiation in the atmosphere is 300− 400 nm [53].

3.3 Detection of gamma-rays with IACT

Cherenkov light from a particle in the atmosphere is detected by using mirrors and anda special camera. These mirrors can be parabolic or have a Davies-Cotton mounting orsome other rotational symmetric focusing optics, see [28] or [56]. When incident light isperpendicular to the optical axis, all the light is focused in the focus. The camera is placedat this point. When the incident light is with an angle from the normal of the directrix, thefocus of the light is moved, see Fig.3.2.

The angle β is most often very small, leading to this proportional approximation

ρ / sin βf ⇡ βf (3.1)

where f is the distance focal length of the parabola.Since Cherenkov light in the atmosphere is emitted by an object (the shower) with a

spatial extent, see Fig. 3.1, this gives an image on the camera, see Fig. 3.3.A large problem using this technique is to discriminate the Cherenkov images from showers

initiated by gamma-rays from the Cherenkov images from showers induced by other particles.This is hard partly because only about one of ten thousand cosmic rays are induced by gammarays. Hadrons are the most common cosmic rays. With the imaging technique it is possible


Figure 3.3: The Cherenkov light and the picture on the camera. Credit: [9]

though. Fig. 3.4 shows how the different particles are imaged. The small six-cornered pixelsin the picture are the enhanced signals from photomultipliers, see also 3.4.

Another major problem is the noise from Night Sky Background (NSB). There are dif-ferent types of NSB. There is for example human made light on Earth. To avoid this, thetelescopes are placed in areas far from larger cities and other major light polluters. Tele-scopes are also often placed at high altitudes because this also makes the disturbance fromlight less. The NSB in these places mainly consists of light from stars and galaxies, and ofcourse the Moon. The telescopes have to be directed away from the moonlight.

Figure 3.4: How different particles are imaged. The elliptic shape of the Cherenkov lightfrom the original gamma ray is seen to the right. Credit: [24]


Figure 3.5: One of the H.E.S.S. 12-m telescopes. Notice man on the right to compare size.Credit: [7]

3.4 The H.E.S.S. observatory

H.E.S.S. is the abbreviation for High Energy Stereoscopic System and is an array of telescopesmeasuring and detecting very-high-energy gamma rays (1010−1013 eV). The name is also anallusion to Victor Hess who discovered cosmic radiation, see also Sec. 2.1. The observatorysite is in Namibia, Africa, about 100 km south-west of the Namibian capital Windhoek. Theplace has very good weather conditions, is 1800m above sea level where the air is dry andwhere there is almost no human-made light pollution. The height also makes the absorptionof light in air less, since there is less air to travel compared to an observatory at sea level forexample. The first of the original four telescope was taken in use summer 2002 and all fourwas running in December 2003. A major enhancement was made in summer of 2012 when afifth, much larger telescope, was taken in use together with the other four. A collaborationof more than 170 scientist from 12 different countries operate the observatory, see [6].

In this thesis only already published results from H.E.S.S will be used, but since thetelescope plays such an important role in learning more about AGNs a description of H.E.S.S.follows here.

3.4.1 The telescope structure and mirrors

3.4.1.1 CT1-CT4

The four initial 12 m-telescopes, called CT1, CT2, CT3 and CT4, are placed as corners in asquare with a side of 120m, with the diagonal in the north-south direction see [7] and Sec.3.5 for an overview.

Each telescope consists of a Davies-Cotton dish mounted on to a stand consisting of twotowers. The telescope is controlled by motors that can move it to point at different directions,in an alt-azimuthal mount.

The diameter of the dish of each telescope is almost 12m giving an area of 107m2 per


Figure 3.6: Each mirror is attached to a triangular support with one fixed and two adjustablesupport points. Credit: [46]

telescope [51]. The mirrors in the dish, as every other details of the telescope, have beencarefully chosen to give very good observation data and in the same time to be cost efficient.Before the round glass mirrors were chosen, there were ideas of having for example aluminummirrors but tests showed that the glass mirrors were performing better, see [46]. The shapeof the mirrors has also been taken into account. Hexagonal mirrors have the benefit that itis possible to cover the whole dish, but since in the manufacturing process they should havebeen cut out from larger round ones, leading to bigger costs, it was better to keep the roundones. There is then a loss in 10% in the coverage but that is not affecting results too much,see [46]. Each mirror is attached to a support with three support points in order to makefurther fine adjustments, as shown in Fig. 3.6.

3.4.1.2 The new large-area telescope

The fifth telescope is placed in the middle of the square and resembles the other ones instructure and shape. The difference is in the size, and in the optics adopted (parabolicinstead of Davies-Cotton). Instead of an 12m dish diameter and 382 mirrors with 60 cmdiameter, the CT 5 has a dish diameter of 28m and 875 mirrors with 90 cm diameter. Thetotal mirror area is 614m2, almost six times the area of one of the smaller telescopes.

3.4.2 The cameras

The camera is placed in the focus of the dish. For CT 1-CT 4 the camera has a cylindricalshape where the diameter is about 1, 6m, the length 1, 5m and the weight about 800 kg.The CT 5 camera measures 2, 5m in diameter, has the length 2, 2m and the weight of about2800 kg, see [7].

The camera front consists of photon detector elements, also called photomultipliers. Theyare constructed to enhance the detection from a photon to a readable signal. It is also possibleto count the number of photons hitting it, often presented as different colours in 3.4. In thepicture that later is to be analysed, the different photo multipliers are seen as pixels, as inFig. 3.4. CT 1 to CT4 cameras consists of 960 pixels and the CT5 of 2048.


When observing an electromagnetic shower with all telescopes, these may give smalldifferences in where the shower is located. These differences make it possible to calculatethe direction of the shower and thus its origin. This is why H.E.S.S. is called a stereoscopicsystem. To be sure that the telescopes measure the same shower, a sophisticated triggersystem is active. The central trigger system waits for signals from any of the cameras. Ifonly one telescope is detecting something or if the time between two or more detections doesnot coincide, the electronics are reset within microseconds and thus making place for newcoincidental events very fast. If the calculations point to a coincidental detection, consideringthe time it takes for the signals to come to the central trigger, the event is stored and can beanalysed further afterwards.

It is possible to manually choose the level of what to count as a coincidence. If it isenough with two cameras noticing an event, or if there has to be more cameras involved. Thecamera combinations can also be chosen. It is also possible to count detections only fromCT5. The clear benefit of the trigger system is that the cameras can be ready very quicklyafter an event, or a mistaken event, and also that the energy threshold can be kept very low.

There is a good precision in the identification of photons from a real electromagneticshower, with respect to NSB or other cosmic radiation, see [7].

3.4.3 Progress in the field thanks to H.E.S.S.

The H.E.S.S. project is constantly making progress. From the beginning the telescopes havebeen detecting gamma-ray sources that before H.E.S.S. were too faint to be detected, andthis thanks to the good sensitivity of the experiment. The catalogue of known very-high-energy sources has been increased dramatically during 2003-2012. Every year many articlesare produced and the H.E.S.S collaboration has been awarded many international scientificawards like for example the Rossi Prize from the American Astronomical Society 2010, see[6].

3.5 The Fermi Large Area Telescope

The Fermi-LAT is an instrument placed on an Earth orbiting satellite. The name Fermiis after the Italian physicist Enrico Fermi who won the nobel prize in 1938 for his workconcerning neutrons and nuclear reactions [26]. During his late years he came up withtheories and started to engage in the research about cosmic rays.

LAT stands for Large Area Telescope and is a telescope for gamma rays in the rangebetween 20MeV and 300GeV. The large area is the area examined. It can see up to 20% ofthe sky. The satellite Fermi Gamma-ray Space Telescope who carries the Fermi-LAT and alsoanother instrument, was launched in summer of 2008. The other instrument is the GammaRay Burst Monitor (GBM) that detects Gamma Ray Bursts (GRB). Up to half of the GRBis also detected by the LAT.

The Fermi-LAT is not the first instrument mapping the gamma ray sky. Its precursorwas the gamma ray telescope EGRET, see [45]. But where the maximum energy for EGRETwas 30GeV, the LAT can measure ten times more energetic rays. It does this with betterresolution and thus making the map of the sky more accurate and pointing out the high-energetic sources instead of just noticing diffuse areas of high energy.


The satellite orbits the Earth at an altitude of 565 km. One round takes about 96minutes.The satellites orbital plane is inclined with respect to that of the Earth with 25, 5 °, see [45].When the LAT is in scanning mode, which it is most of the time, it is pointing in differentangles to make a scan where it has about the same exposure time to every different areaof the sky. This movement can be understood if one visualizes the satellite’s orbit as thecircumference of a sphere. The direction of the telescope is then pointing outwards to a zenithof the sphere. The satellite moves from the zenith direction, perpendicular to the plane ofthe orbit, towards the pole of the sphere until it makes an angle of 50 ° from the zenith. Thisis then repeated in the opposite direction. It is also possible to make the telescope pointingin a special direction for a longer time to make more exact observation of a particular area,see [45].

3.5.1 The detector

The LAT can determine the direction and the energy of an incident gamma ray. The con-struction of the instrument is schematically shown in Fig. 3.7, where one of the sixteenmodules is shown in more detail. In the upper part of each module is the tracking system.Close to the bottom is a calorimeter and in the bottom is the data acquisition system (DAQ).

Broadly what happens is that an incoming gamma-ray (single dashed line) hits a foil inthe upper part of the instrument and creates a electron-positron pair (two dashed lines). Thepath of the pair is detected. The energy of what is left of the primary gamma-ray when theseparticles reaches the bottom is measured.

The DAQ determines if it has detected the same particle all the way and tries to separateits data from background noise.

In more detail, what happen is that if the incoming ray has an energy E ≥ 2me there is apossibility that it will, in interaction with the electric field near an atomic nucleus, create aelectron-positron pair. To increase this possibility the thin foil at the top of the instrumentis made of tungsten that has a large atomic number. Passing near an atom with high atomicnumber increases the chances of an interaction. Just below the first tungsten-foil is a layerof two silicon strips oriented in x− and y−direction. These layers can detect if there is anelectron or positron passing, because the particles ionize the layer. After a certain distancethere is another layer of tungsten and silicon foil. The sequence of foils is repeated 12 timesand makes it possible to track lower energy photons in the top. The following four setscontain a thicker tungsten foil. A thicker foil means higher probability for pair-productionand this is for higher energy photons that otherwise could pass the instrument without beingdetected at all. The four layers in the bottom does not have a tungsten foil, just silicon.The detections from the different layers with their respective time are put together to trackthe path of the particles and can be extrapolated together with the information about thepointing of the telescope to calculate the origin of the gamma-ray.

The LAT is not receiving gamma-rays and other particles just from the top. From theside there are also incident particles. For the instrument these are background radiation thathas to be eliminated from the data. To be able to subtract these events the telescope issurrounded by anti-coincidence detectors (ACD).

These detectors are made of plastic scintillator tiles combined with photon multipliertubes. Whenever they get a signal this is compared to signals inside and if they coincidethey are quickly deleted from the data collection to make time for a proper signal as fast aspossible.


Figure 3.7: A simplified picture of the Fermi-LAT. One of the sixteen modules is seen indetail. Credit: [45]

The bottom part, the calorimeter, measures the energy of what is left of the incomingparticles from the top. This part also consists of layers, now eight layers of twelve CsI(Cesium Iodide) crystals. This material scintillates when exposed to ionizing radiation. Thisscintillation is then received and measured by photo detectors just beside every crystal layer.Depending on how much scintillation the particle gives rise to the energy can be calculated.This number has to be linked to the information about the particle’s path to calculate theenergy of the original gamma-ray. Some of the original energy is being transformed duringthe way down the telescope. Another scenario is that not all the energy is measured inthe calorimeter since there is a possibility that the particle has more energy than can betransferred into scintillation. The particle then continues out through the telescope. By usingdifferent kind of likelihood analyses it is possible to get very good data of both the originof the gamma-ray and its energy. These analyses are refined by Monte Carlo simulations onEarth and on previous data both from EGRET and from Fermi-LAT, see also [45].

It is interesting to note that there is a connection between the Fermi-LAT calorimeterand Linnaeus University. In 2004-2005 AMCRYS in Kharkov, Ukraine manufactured 1850CsI crystals for the Fermi-LAT calorimeter modules and sent them to Kalmar University,Sweden, for acceptance testing, see [11]. The crystals were then assembled into detectorelements (CDEs) at Swales Aerospace (USA).

Chapter 4

PKS 2155-304 and already published

results

PKS 2155-304 is an extremely well studied and very bright southern BL Lac and has beenchosen for this thesis to be studied in the full dataset of the Fermi-LAT data. The lettersPKS refer to the Parkes Radio catalog that compiled radio sources detected by the ParkesRadio Telescope, see [17]. Other catalogs has other names for it, see [15]. In the FermiGamma ray Lat-catalog is is called 3FGL J2158.8-3013. It was first discovered 1979 andis one of the brightest extragalactic X-ray sources we observe. Several satellites has beenobserving it during a long time. It has shown to have a strong flux variability. In 1996 and1997 the University of Durham Mark 6 Telescope detected energies greater than 300 GeV butPKS 2155-304 was not detected at all the year after by that instrument, see [42]. The distanceto this AGN is about 492 000 Mpc. It has a redshift z = 0, 116. Since 2002 its very-high-energy flux has been well observed by the H.E.S.S telescopes in Namibia. Observations of thesource have given and will give more information about active galactic nuclei in general andabout mechanisms at work in TeV blazars in particular. Observations of the source also giveimportant clues about the absorption of very-high-energy gamma-rays in the extragalacticbackground light, see [42].

4.1 Early observations from H.E.S.S

During the construction phase of H.E.S.S., 2002-2003, PKS 2155-304 was observed. Withhigh statistical significance (⇠ 45σ) energies greater than 160 GeV was detected [42]. Vari-ability in flux was detected in time scale of months, nights and hours. The quickest increasein flux took place when the flux was almost tripled (2, 7 ± 0, 7) under 30 minutes and thendecreased during the next 30 minutes to almost the same value as before the increase [42].The same survey looked for changes in spectral energy distribution over time. There was noevidence of this but it was not possible to say that there was none. The mathematical modelsthat fit the spectral energy distribution best, are a power law with an exponential cutoff ora broken power law. But these two model assumptions were not significantly better thana fit to a simple power law. Comparisons between PKS 2155-304 and other AGNs showssimilarities and differences. It is still too early to say if there is, for instance, a connectionbetween the distance and the behavior of the sources.

31

CHAPTER 4. PKS 2155-304 AND ALREADY PUBLISHED RESULTS 32

Figure 4.1: H.E.S.S. integral flux above 200 GeV observed from PKS 2155-304 in 2006 versustime. The data are binned in 1 minute intervals. Credit: [44]

4.2 Multi-wavelength observations in 2003

In a paper from 2005, see [41] a comparison between different wavelength areas for PKS 2155-304has been made.

The time period was from October 19 to November 26, 2003. During this period thesource was in a quiescent (resting, low activity) phase. The data for the investigation weretaken from H.E.S.S., the Rossi X-ray Timing Explorer satellite (RXTE), the Robotic OpticalTransient Search Experiment (ROTSE) and the Nançay decimetric radio telescope (NRT).They all cover different wavelengths, but also overlap to some extent. The aim for the surveywas to determine if there was any similarities in flux for the different energies.

The paper shows variability in all energy bands but can not establish a connection betweenX-ray and gamma ray fluxes, nor between any other of the wavebands. The spectral energydistribution from H.E.S.S.-data is best fitted to a power law in the VHE gamma ray-bandand a broken power law in the X-ray band, see [41].

4.3 Exceptional flares in 2006

An event that makes PKS 2155-304 a very interesting object is what happened in the summerof 2006. In July 28 that year, the very-high-energy flux increased to a value ten times higherthan the typical values detected from the source. Variability changes in the time span of200-600 seconds was measured, see [43] and Fig. 4.1. There were two distinct gamma flares,the second one 44h after the first one [44]. Different from the observations 2003 of a quiescentstate of PKS 2155-304, in this highly active state there is a strong correlation between theemission in the γ-ray and the X-ray band. The variations are correlated in time but notin amplitude. The greatest difference is in the very-high-energy gamma-ray band where thepeak is up to 22 times the lowest value. The same burst in the X-ray band shows only a


Figure 4.2: The homogeneous spherical emitting region thought to be the source of thenon-thermal emission from Active Galactic Nuclei. Credit: M. Weidinger

doubling, whereas in the optical band only a 15% increase is shown [44]. These correlationswere discovered by using multi-wavelength observations with data from several instruments.The long wavelength radiation in the radio band does not have this sudden increase, but stillhas an increase in the long term flux evolution. This increase starts after the event of thevery-high-energy flares, see [38].

The high energies are believed to be generated in the SSC process, see also 1.3.2.2. Theseexceptional flares are the first observed with such a rapidly evolving of the Compton domi-nated energy band [44].

Very fast changes in flux can help to determine the size of the emitting region. There isa relation between the minimal time of γ-ray variability (tvar), the Doppler factor (δ), theredshift (z) and the radius of the emitting region (R) [43].

R c · tvarδ1 + z

(4.1)

Using the best-determined rise time from the light curve in Fig. 4.1, for tvar = 173±28 s alimit on the size of the emitting region was estimated to be Rδ−1 4.65⇥1012 cm 0.31AU.In SSC models, the emitting region is a spherical, homogeneous "blob" of electrons displacingin the jet with a certain Lorentz factor, see Fig. 4.2.

4.4 Meta data from ASDC database

ASDC is an abbreviation for ASI data centre, where ASI stands for Italian Space Agency. Itis a centre storing data from high-energy astronomy/astroparticle satellites and telescopes.ASDC is also partly responsible for several of these satellites and develops data process-ing tools for those, see [1]. Data come from a lot of different telescopes and satellites. Byusing ASDC it is possible to receive all this data displayed in a plot. The number of dif-ferent catalogues that ASDC uses is vast. Some of the catalogues are directly connected to


Figure 4.3: SED-plot for PKS 2155-304 using meta data from ASDC. Every different colourrepresents a specified data catalog. Credit: [21]

ASDC and some of the data use only published material. The spectral energy distributionof PKS 2155-304 is shown in Fig. 4.3.

Chapter 5

Methods and accuracy of results

In this chapter the methods used in the analysis will be presented together with informationabout how the accuracy of the results presented in Chapter 6.

5.1 Three studies

In this project, three different studies have been done.The first starts with generating the light curve for the full time of Fermi-LAT’s observa-

tion, divided into 82 bins. The plot shows active and less active phases of the AGN. In orderto study the behavior of the AGN more closely, different periods are chosen. Then a spectralanalysis is done for phases with relatively low activity and phases with high activity. Foreach of these periods spectral analysis are made and then two different models are tested tosee which one gives the best fit.

The second study divides the full time light curve into 27 bins instead. This is made tosee if there are any clearer differences in high and low states of activity. Also here spectralanalysis are made, as above.

The third study chooses a flux peak and tries to see the shortest variability time and thenmakes a spectral comparison between two different flux states.

The spectrum from this peak is then compared to a spectrum from a period with lowactivity and they are put in a context with a multiwavelength study with meta data fromother surveys.

5.2 Computer processing

The data collected by the Fermi-LAT are available for download at a NASA-website. Everybin contains data from a week of observation. For this thesis the “reprocessed Pass7 photondata” have been used. During the first years of use of the telescope some adjustments hadto be made. In the reprocessed data these adjustments have been taken in to consideration,and thus changing some of the data that were released in the earlier years of the project,see [40]. In may 2015 data consist of detection of 438460535 photons, see [13] and, for thisproject, all data are stored in one account in Alarik. It is not necessary for every user tostore the data, it is easy accessible via a link that points to the files.

In order to process the data from the Fermi-LAT a lot of computing power is needed.For the analysis in this thesis the computing system Alarik at the Lunarc cluster in Lund

35

CHAPTER 5. METHODS AND ACCURACY OF RESULTS 36

Figure 5.1: An approximation of the energy range of the photons detected by Fermi-LATmarked with a dashed rectangle. See also Sec. 1.3.3 for more about the SSC model. Credit:[53].

(Sweden) has been used. Alarik has all in all 3328 processors, see [2] and is accessed throughinternet via SSH. SSH is an abbreviation for Secure Shell and is an internet protocol thatmakes a safe connection between computers possible. When communicating with the clusterthe user uses Linux commands. The analysis uses the Fermi science tools and the Enricosoftware distributed NASA (National Aeronautics and Space Administration), see [14]. Formore information about the computer analysis see Supplement.

5.3 Models of fitting

The Fermi software offers different models to adjust to the data. In this thesis the modelscalled PowerLaw2 and LogParabola has been used. In Fig. 5.1 is marked the approximateenergy range of the photons possible to detect with the Fermi-LAT.

If the model of best fit is the PowerLaw2, this indicates that the the photons detected areof less energy than in the inverse Compton peak. If the best model instead is the LogParabolathis would suggest that we actually see the inverse Compton peak in the data. If one modelis preferred for the low activity phases and another model for the high activity phases thismight suggest that the spectral energy distribution differs when in different activity states.

5.3.1 PowerLaw2

The PowerLaw2 is an improvement of a simple power-law function, and uses the integratedflux and the spectral index as free parameters:

dN

dE=

N(γ + 1)Eγ

Eγ+1max − Eγ+1

min

(5.1)

where

N =Integralγ =IndexEmin =Lower limitEmax =Upper limit


The upper and lower limits are treated as fixed. In the following surveys, see chapter 6,Emin = 300MeV and Emax = 300GeV. The flux given by the integral is over the range fromthe lower limit to the upper limit. The advantage of this model is that the errors on theintegrated flux can be evaluated by likelihood instead of taken into considerations afterwards,see [12].

5.3.2 LogParabola

The other model used is the LogParabola:

dN

dE= N0

✓

E

Eb

◆−(α+β ln(E/Eb))

(5.2)

where

N0 =normalizationα =alphaβ =betaEb =Eb

This model is often used for the blazar spectra. Eb is set to 904,028 in the followingsurveys, see chapter 6.

5.4 Accuracy of the results

When determining how accurate a result is, it is common to calculate the probability thatthe detection of an event happens to be a natural random variation. A commonly usedconfidence interval is that of 95%, see [57].

This means, given that our hypothesis is true, there is only 5 % chance that it wasrandom factors that gave us such a result. It could also be put as that the significanceis 2 standard deviations, 2σ. However, in some branches of science, as for example particle-and astrophysics the demands for accuracy is much higher, as there could also be systematiceffects in a detector, for example. An indication of an event is when the significance is 3σ andin order to claim a detection (or a discovery), the significance shall be 5σ. That correspondsto a probability of 0.000057 % that it was random factors giving the result, given that thehypothesis was true. That is a very low probability, as also seen in Fig. 5.2.

5.4.1 Test statistics and likelihood-ratio test

A test statistic is a single measure of some attribute of a sample that can be used to test ahypothesis. The Test Statistic is defined as

TS = −2 ln✓

H0

H1

◆

= −2 lnH0 + 2 lnH1 = 2(lnH1 − lnH0) (5.3)

where the value of H0 is the maximum likelihood value for a given hypothesis and H1 is themaximum likelihood value of an additional hypothesis.


Figure 5.2: The normal distribution with standard deviations σ.

For source detection, this corresponds to a H0 given by a model without the source (‘nullhypothesis’) and a H1 for a model with the source at a specified location, see [29]. Sourcedetection in Fermi-LAT is based on a threshold likelihood Test Statistic of 25, correspondingto a significance of roughly

p25 ⇠ 5, see [8] and below for an explanation of the TS in the

limit of large number of counts.Fermi science tools calculate the TS for the detection of the source in the given bin and

analysis, and the maximum likelihood of the spectral hypothesis made in the analysis. Thelatter is to be compared with an additional hypothesis, in order to decide which spectralmodel fits better the data.

In this thesis I used the two different models PowerLaw2 and LogParabola.In this case, lnH0 is the maximum likelihood value for the PowerLaw2 model and lnH1

the one for the LogParabola model. In the test the H0 shall be the model with the leastdegrees of freedom - in this case the PowerLaw2. There are two ways of using the TS. In thelimit of a large number of counts, Wilk’s Theorem, see [37], states that the TS can be treatedas a χ2 with degrees of freedom equal to the difference in dimensionality between the twohypotheses. Thus, if we treat the statistics as a χ2 , the value of TS is used to find the p-valueof the test. The p-value expresses the probability that it is only random factors that madethe alternative hypothesis (H1) to be favored over the null hypothesis (H0). If for examplethe p-value is 0.05, this can be interpreted as it is very likely that the alternative hypothesis(H1) is better than the null hypothesis (H0), but that there is a 5% chance, given that thenull hypothesis it true, that the results from the survey is only based on random factors. Inthis case that is not very likely and so the alternative hypothesis should be chosen. The lowerthe value of p, the greater the confidence in rejecting the null hypothesis. To achieve thep-value a table of the χ2 -distribution is used. The degrees of freedom play an important rolehere. Generally for this test form, the degrees of freedom is determined by subtracting thedegrees of freedom of the alternative hypothesis, df1, from the degrees of freedom of the nullhypothesis, df0. I.e df1 − df0. In this case the degrees of freedom for the test is 3 − 2 = 1.As a basic rule of thumb, the

pTS is approximately equal to the significance (in standard

deviations) of H1 (LogParabola) with respect to H0 (PowerLaw2).

5.4.2 Residuals plot

For each energy plot made by the Enrico software also plots of the analysis accuracy is made.In this thesis the plot of the residuals and the counts plot is taken into account. The plotof the residuals (see Fig. 5.3 for an example) shows the value of what is subtracted when


Figure 5.3: An example of a residual plot,see Sec. 5.4.2 for details.

Figure 5.4: An example of a counts plot,see Sec. 5.4.3 for details.

adjusting an hypothesis to the data, see [3]. If there is a “perfect” fit, the residual for thatenergy value is zero. Most often there are deviations.

residuals =γreal − γexpected

γexpected=

counts−model

model(5.4)

The closer γreal is to γexpected the closer to zero is the residual and the better the model isfitted.

5.4.3 Counts Plot

The counts plot (see Fig. 5.4 for an example) on the other hand graphically shows how thedifferent counts in each bin is summed up to the data, see [3]. The satellite is hit by a lotof photons, not just from the source that is analysed. By having control of other sourcesnearby in the field of view it is possible to subtract the photons from the nearby sources inorder to have the values for just PKS 2155-304. The solid line in the plot is the model forthe source. The dots represent the actual data. The dashed line, that lies between the solidand the dotted line are the photons from the other sources. The dotted line, the one that ison top of the others is the sum of the previous. As seen in the plot, the sum of separatedvalues add up to the data. Notice that the scales are logarithmical.

5.4.4 Accuracy for the light curve

For the accuracy of the light curve the Enrico software offers only one plot, the flux/dflux vsNpred/DNpred plot, where flux is the measured flux, dflux is the errors in the measurement,Npred is the predicted value from the chosen model and DNpred is the predicted error fromthe model, calculated as

pNpred, since it is treated as Poisson distributed. The plot has

been chosen because there might be some issues with the lightcurve, especially when it comesto calculating the errors. If the flux/dflux vs Npred/DNpred plot shows good correlationbetween the ratios, this means that the calculations of the errors has been successful, see forinstance Fig. 6.2.


5.5 MET - Mission Elapsed Time

A normal year in a normal calendar has 365 days, or 366 days in the leap years. Sometimes,in order to adjust the time to our position in our orbit around the sun, an extra leap secondis added. If this system of measuring time would be used in Fermi-LAT there would be severecomplications when handling the data.

An error of one second would make the satellite pointing in an other direction and thusreceiving photons from other sources then expected. To avoid these problems the time iscounted in seconds in MET - mission elapsed time, with a “time zero” at midnight the 1January 2001, in the UTC-system. UTC stands for Coordinated Universal Time, a moreexact and updated version of the commonly known Greenwich Mean Time. The start timefor Fermi-LAT in MET is thus 239557418 corresponding to August 4, year 2008, with thetime 15:43:37 in UTC. The last time used in this thesis is 450846434 corresponding to April16, this year 2015, with the time 03:07:11 in UTC. The difference is 211289016 seconds, a bitmore than six and a half years.

Chapter 6

Results of the analysis of PKS 2155-304

6.1 Analysis of PKS 2155-304, first study

The light curve from the PKS 2155-304 for the full time interval, see Tab. 6.1 (see alsoSec. 5.5) showed flux variations over the period. By examining the light-curve, the followingintervals were chosen: 1a, 1b, 1c, 1d and 1e, see Tab. 6.1, for further spectral investigation.The intervals are between 80 and 160 days long, see Fig. 6.1. The accuracy of the lightcurve is very high since the Npred plot (see Fig. 6.2) shows highly correlated values. Thevariability index, defined with the help of the fractional variance method, see [55], for thelight curve is Fvar = 0.414 +/- 0.014. Fvar is greater than 0, even with the lowest error.Fvar stays positive within errors, so this means we have a variable source.

6.1.1 Results for the different intervals

In this section, the spectral results for the different time intervals will be shown. On the leftside of the panels, the results for the PowerLaw2 model will be shown, while on the rightside of the panel the results for the LogParabola hypothesis will be found. First there is thespectrum of the source in the given interval, with the data points and their respective errors,and the bow-tie representing the result of the fit (in red). Each data point is calculated if thesignificance of the given energy bin is greater than 5 σ, (if TS < TSlimit = 25). When thesignificance of the energy bin is less than 5 σ, an upper limit is calculated (points with arrows).An upper limit is the largest probable value that the data point can have. Underneath theseplots there are the results of the fit. The model hypotheses (PowerLaw2 and LogParabola)were introduced in Sec. 5.3. Then the plots for residuals and count plots are shown. Finally

Period MET Date (UTC)

Full time 239557418-450846434 2008-08-04 15:43:37.000 UTC - 2015-04-16 03:07:11.000 UTC

1a 261000000-268000000 2009-04-09 19:59:58.000 UTC - 2009-06-29 20:26:38.000 UTC

1b 273000000-286000000 2009-08-26 17:19:58.000 UTC - 2010-01-24 04:26:38.000 UTC

1c 308000000-315000000 2010-10-05 19:33:18.000 UTC - 2010-12-25 19:59:58.000 UTC

1d 344000000-358000000 2011-11-26 11:33:18.000 UTC - 2012-05-06 12:26:38.000 UTC

1e 419000000-426000000 2014-04-12 12:53:17.000 UTC - 2014-07-02 13:19:57.000 UTC

Table 6.1: The different time intervals converted to calendar time format.

41

CHAPTER 6. RESULTS OF THE ANALYSIS OF PKS 2155-304 42

Figure 6.1: The light curve for PKS 2155-304 for the full time interval, 2008-08-04 15:43:37.00- 2015-04-16 03:07:11.00, see Tab. 6.1. Variability of the source can clearly be seen. Thechosen intervals, 1a-d, for further spectral investigation, of high- respectively low-flux statesare marked. The grey line is the calculated flux assuming the source would not have fluxvariability. Time is given in MET.

Figure 6.2: Accuracy of the calculation of the errors for the light curve. Values are highlycorrelated and thus the light curve accuracy is high. See Sec. 5.4 for further information.


the models are compared to each other to determine which one represents the data best. Thecounts plot shows that the correct sources has been subtracted.

6.1.1.1 Interval 1a: High-flux state

During Period 1a PKS 2155-304 is in a high-flux state as can be seen from Fig. 6.1. Spectralresults for this period are shown in Tab. 6.2. The likelihood-ratio test gives a p-value ofsomewhere in between 0,025 and 0,01 or a significance of 2.4 σ that the LogParabola is themodel that fits better the data, with respect to the PowerLaw2.

6.1.1.2 Interval 1b: Low-flux state

The results for interval 1b, which is a low-flux state of the source are shown in Tab. 6.3. Thelikelihood-ratio test gives an answer that points out the PowerLaw2 model to be the best fit.Notice that the LogParabola model is adjusting towards a PowerLaw2 model by making theparameter β very small. This indicates that for that time interval the PowerLaw2 model isthe best among the two hypothesis. It could be that a broken power law (not studied herein this thesis) will fit the data of this period better. Notice that the LogParabola model isadjusting towards a PowerLaw2 model by making the parameter β very small.

6.1.1.3 Interval 1c: High-flux state

The results for interval 1c, which is a high-flux state of the source, are shown in Tab. 6.4. Thelikelihood-ratio test gives a p-value of somewhere in between 0,50 and 0,30 or the significanceof 0, 99σ that the LogParabola is the model that fits best. So this means that in this caseit is difficult to disentangle which model fits better the data, but that the LogParabola ispreferred at a 1 σ level.

6.1.1.4 Interval 1d: Low-flux state

The results for interval 1d are shown in Tab. 6.5. The likelihood-ratio test gives a p-value ofsomewhere in between 0,025 and 0,01 or a significance of 2, 4σ that the LogParabola is themodel that fits best. A clear advantage for that model.

6.1.1.5 Interval 1e: High flux-state

The results for interval 1e are shown in Tab. 6.6. The likelihood-ratio test gives a p-value of0,95 or the significance of 0, 02σ that the LogParabola is the model that fits best and thisis not very significant. The PowerLaw2 model thus fits the data quite well. Notice that theLogParabola model is adjusting towards a PowerLaw2 model by making the parameter βvery small, as seen already in the time interval named 1b.

6.2 Analysis of PKS 2155-304, second study

In this, the second study, the analysis is being made using less bins for the light curve. Only27 bins are generated instead of 82 bins in study I. In Fig. 6.3 the chosen intervals for thespectral analysis are shown. The time intervals are shown in Tab. 6.7.


PowerLaw2

Integral: 8.52 · 10−8 ± 4.6 · 10−9

Index: -1.84±0.042

TS = 1986.55Loglike: -60537.96

LogParabola

Norm: 3.20 · 10−11 ± 1.9 · 10−12

α: 1.702± 0.078β: 0.056±0.028TS = 1985.53

Loglike: -60535.02

Table 6.2: Results for the time interval 1a (April to June 2009), see Tab. 6.1. The PowerLaw2fit is found on the left, while the LogParabola hypothesis is on the right. Top: Energyspectrum. Below: fit values. Below: Residuals plot. Bottom: Counts plot.


PowerLaw2

Integral: 4.16 · 10−8 ± 2.8 · 10−9

Index: -1.804±0.048

TS = 1406.31Loglike: -97668.82

LogParabola

Norm: 1.53 · 10−11 ± 1.1 · 10−12

α: 1.803±0.049β: 0.0005000± 7.7 · 10−6

TS = 1406.17Loglike: -97668.83

Table 6.3: Results for the time interval 1b (August 2009 to January 2010), see Tab. 6.1. ThePowerLaw2 fit is found on the left, while the LogParabola hypothesis is on the right. Top:Energy spectrum. Below: fit values. Below: Residuals plot. Bottom: Counts plot.


PowerLaw2

Integral: 9.78 · 10−8 ± 4.8 · 10−9

Index: -1.869±0.039

TS = 2469.34Loglike: -61609.48

LogParabola

Norm: 3.66 · 10−11 ± 1.9 · 10−12

α: 1.81±0.067β: 0.023±0.024TS = 2468.22

Loglike: -61608.99

Table 6.4: Results for the time interval 1c (October to December 2010), see Tab. 6.1. ThePowerLaw2 fit is found on the left, while the LogParabola hypothesis is on the right. Top:Energy spectrum. Below: fit values. Below: Residuals plot. Bottom: Counts plot.


PowerLaw2

Integral: 3.81 · 10−8 ± 2.6 · 10−9

Index: -1.835±0.049

TS = 1283.35Loglike: -106735.67

LogParabola

Norm: 1.41 · 10−11 ± 1.1 · 10−12

α: 1.656±0.098β: 0.069±0.033TS = 1284.12

Loglike: -106733.38

Table 6.5: Results for the time interval 1d (November 2011 to May 2012), see Tab. 6.1. ThePowerLaw2 fit is found on the left, while the LogParabola hypothesis is on the right. Top:Energy spectrum. Below: fit values. Below: Residuals plot. Bottom: Counts plot.


PowerLaw2

Integral: 9.63 · 10−8 ± 5.4 · 10−9

Index: -1.822±0.042

TS = 2098.49Loglike: -52405.12

LogParabola

Norm: 3.55 · 10−11 ± 2.1 · 10−12

α: 1.821±0.059β: 0.00050±0.00035

TS = 2098.19Loglike: -52405.12

Table 6.6: Results for the time interval 1e (April to July 2014), see Tab. 6.1. The PowerLaw2fit is found on the left, while the LogParabola hypothesis is on the right. Top: Energyspectrum. Below: fit values. Below: Residuals plot. Bottom: Counts plot.


Full time 239557418-450846434 2008-08-04 15:43:37.000 UTC - 2015-04-16 03:07:11.000 UTC

2a 240000000-319000000 2008-08-09 18:39:59.000 UTC- 2011-02-10 03:06:38.000 UTC

2b 332000000-413000000 2011-07-10 14:13:18.000 UTC - 2014-02-02 02:13:17.000 UTC



Figure 6.3: The light curve for PKS 2155-304 for the full time interval, 2008-08-04 15:43:37.00- 2015-04-16 03:07:11.00, see Tab. 6.1. Variability of the source can clearly be seen. Thechosen intervals for further spectral investigation, of high- respectively low-flux states aremarked. The grey line is the calculated flux assuming the source would not have flux vari-ability. Time is given in MET.

The left interval is to represent an active state of PKS 2155-304 and the right one a morequiescent state. The intervals are named 2a and 2b. They both consist of ten bins i.e. theyrepresent approximately 30 months of data each. The accuracy of the light curve is very highsince the Npred plot, see Fig. 6.4 shows highly correlated values. The variability index forthe light curve is Fvar = 0.338 +/- 0.014. Thus, the source is variable also when consideringthis type of binning.

6.2.0.6 Interval 2a High-flux state

The results are shown in Tab. 6.8. The likelihood-ratio test gives a p-value of somewhere inbetween 0,001 and 0,0005 or the significance of 3, 3σ that the LogParabola is the model thatbest fits the data. A very clear advantage for that model.

6.2.0.7 Interval 2b Low-flux state

The results are shown in Tab. 6.9. The likelihood-ratio test gives a p-value of somwhere inbetween 0,001 and 0,0005 or the significance of 3, 4σ that the LogParabola is the model thatfits best. Again, a very clear advantage for that model.

6.3 Analysis of PKS 2155-304, third study

In the third study, a high activity phase is chosen and then zoomed in to, to see if it ispossible to see variability over shorter time span. The first interval is named 3a, see 6.10,


PowerLaw2

Integral: 6.81 · 10−8 ± 1.5 · 10−9

Index: -1.859±0.015

TS = 15530.38Loglike: -644585.03

LogParabola

Norm: 2.54 · 10−11 ± 5.3 · 10−13

α: 1.785±0.028β: 0.0305±0.0095TS = 15504.84

Loglike: -644579.48

Table 6.8: Results for the time interval 2a (August 2008 to February 2011), see Tab. 6.7.The PowerLaw2 fit is found on the left, while the LogParabola hypothesis is on the right.Top: Energy spectrum. Below: fit values. Below: Residuals plot. Bottom: Counts plot.


PowerLaw2

Integral: 4.05 · 10−8 ± 1.2 · 10−9

Index: -1.849±0.021

TS = 7253.58Loglike: -595104.43

LogParabola

Norm: 1.51 · 10−11 ± 4.6 · 10−13

α: 1.735±0.039β: 0.045±0.013TS = 7251.13

Loglike: -595098.51

Table 6.9: Results for the time interval 2b (July 2011 to February 2014), see Tab. 6.7. ThePowerLaw2 fit is found on the left, while the LogParabola hypothesis is on the right. Top:Energy spectrum. Below: fit values. Below: Residuals plot. Bottom: Counts plot.


Figure 6.4: Accuracy for the light curve from study II. As seen, the values are highly correlatedand thus the accuracy for the light curve is high.


3a 419544357-427369876 2014-04-18 20:05:54.000 UTC - 2014-07-18 09:51:13.000 UTC

3b 421400000-422600000 2014-05-10 07:33:17.000 UTC - 2014-05-24 04:53:17.000 UTC

3c 421000000-423000000 2014-05-05 16:26:37.000 UTC - 2014-05-28 19:59:57.000 UTC


from March to July 2014. The interval is divided into 78 bins where every bin is about 100000 seconds or 28 hours. A spectral analysis of interval is also done

6.3.1 Light curve for the interval 3a

A clear top is seen in Fig. 6.5. A lot of the bins are upper limits.The accuracy is seen in Fig. 6.6. Compared to the earlier results there is a larger deviation

here. That is because of the lower number of photons registered. The probability that thecurve actually is a constant function, given that our hypothesis is that it is variable, is verylow: 1, 89 · 10−9. The variability index is Fvar = 0.718 +/- 0.044.

6.3.2 Light curve for the interval 3b

From the light curve above, a new interval was chosen, with a focus on the peak of the lattercurve. The new interval is called 3b, see Tab. 6.10. It is obvious that there is to few photonsto make a good analysis. The light curve is shown in Fig. 6.7. The error margins are verybig and most of the bins shows an upper limit. The analysis was made by dividing the timeinto 100 bins but those shown are the only ones that were possible to calculate.

In the Npred plot there are large deviations, see Fig. 6.8.


Figure 6.5: Light curve for the interval 3a, from April 18 to July 18, 2014, see Tab. 6.10.

Figure 6.6: Accuracy for the first light curve from study III. Notice the deviations in the leftof the figure.


Figure 6.7: Light curve for the interval 3b, May 10 to May 24, see Tab. 6.10. The errormargins are very large.

Figure 6.8: Accuracy for the second light curve from study III. Notice the deviations and thevery few bins.


The calculated analysis results say that the probability that the curve actually is a con-stant function, given that our hypothesis is that it is variable, is very high: 0, 744, and thevariability index gives a negative value. Fvar = −9, 97 · 10−2 + / − 2, 2 · 10−3. The analysisis pushed too hard with too few photons and to many errors.

6.3.3 Spectral analysis of the interval 3c

The results of the spectral analysis of interval 3c, which is a high-flux state of the source,are shown in Tab. 6.11. The likelihood-ratio test gives a p-value of somewhere in between0,50 and 0,30 or the significance of 0, 91σ that the LogParabola is the model that fits best.So this means that in this case it is difficult to disentangle which model fits better the data,but that the LogParabola is preferred at a 1 σ level.


PowerLaw2

Integral: 1.90 · 10−7 ± 1.4 · 10−8

Index: -1.782±0.054

TS = 1354.55Loglike: -16749.67

LogParabola

Norm: 6.99 · 10−11 ± 5.4 · 10−12

α: 1.75± 0.10β: 0.012±0.032TS = 1357.14

Loglike: -16749.25

Table 6.11: Results for the time interval 3c (beginning to end of May 2014), see Tab. 6.10.The PowerLaw2 fit is found on the left, while the LogParabola hypothesis is on the right.Top: Energy spectrum. Below: fit values. Below: Residuals plot. Bottom: Counts plot.

Chapter 7

Discussion

7.1 Model of best fit

The Fermi-LAT data used in this thesis cover a range 300MeV − 300GeV. The advantageof performing a detailed analysis in the thesis is that more exact and accurate values can beobtained and the significance of the results can be calculated. The tool that ASDC providesis very efficient but lacks the opportunity to go further with very detailed surveys.

From the results of first analysis, seen in Sec. 6.1 it is not possible to determine which ofthe two models LogParabola and PowerLaw2 that has the best fit in general. There seems tobe no difference between lower flux state and higher. For some of the intervals the PowerLaw2fits the best and for others the LogParabola model. This could be because of the many binsthe time interval is divided in. There might be an insufficiently amount of detected photonsto ensure which is the best fit.

From the results of the second analysis, seen in Sec. 6.2, where every bin is a longer timeinterval and thus consists of more detected photons the LogParabola model is clearly thebest model for both the higher flux state and the lower flux state. This suggests that wehave maybe captured the inverse Compton peak in our observations.

In Fig. 7.1 I show two of my spectra. The spectrum with the higher flux is case 3b, whilethe other lower-flux spectrum represents case 2b.

7.2 Variability of a high-flux state

The high-flux state chosen for study III showed variability. The aim for that study was tosay whether it was possible to claim variability also for small timer intervals. With highcertainty it is possible to say that there is variability in a day time binning. By dividing theinterval further it is not possible to say if there is variability on even smaller time intervals.The amount of photons is too small. When comparing these data to the exceptional flaresin 2006, see also Sec.4.3, where variability was shown in intervals of minutes it is seen thatthose flares really were exceptional, both in flux and in variability. Unfortunately these flarestook place before the Fermi-LAT had started so it is not possible to compare data from theseinstruments.

57

CHAPTER 7. DISCUSSION 58

Figure 7.1: Two Fermi-LAT spectra corresponding to period 3b (high-flux state) and period2b (low-flux state). Errors in 2b are smaller, due to the larger dataset. Both spectra all wellfit by a LogParabola, the only large change is represented by the flux level, which is higherin case 3b.

7.3 Spectral Energy Distribution

The energy range analysed in this thesis is only a small part of the energy spectrum of theradiation. It is important to compare these results with other instrument covering otherenergy ranges in order to understand the overall emission from sources. The plot in Fig.7.2 shows PKS 2155-304 data from instruments at all energy ranges taken from the ASDCdatabase. We added to the ASDC data the Fermi-LAT spectra from periods 3b and 2b, the3FGL spectrum see [10] (red squares), and the H.E.S.S. spectra from 2006 (flaring activity,green triangles), and from 2007, 2008 and 2009 (all observations, which integrate over lowand high-states), see [39]. It is clear that PKS 2155-304 is highly variable in X-rays, ingamma-rays and in very-high-energy gamma-rays, as found already in many publications. Inorder to understand the overall emission from the AGN and constrain the parameters of theemitting region, one would need to model the SED with an SSC hypothesis. But this goesbeyond the scope of this thesis.

CHAPTER 7. DISCUSSION 59

Figure 7.2: Plot of data collected with ASDC, [34], with Fermi-LAT spectra obtained in thisthesis and HESS spectra. See Sec. 7.3 for details.

Chapter 8

Conclusions

The aim for this thesis was to get a closer look at Active Galactic Nuclei in general andPKS 2155-304, using data from Fermi-LAT, in particular. This has been done, first bybriefly describing the different objects that probably can be brought together to being AGNs,secondly explaining some of the physics behind and thirdly how the radiation can be detected.

The analysis of the data shows the dependence of the amount of photons received. Itis not possible to divide the data in too short time intervals if one wants to have goodaccuracy. However it looks like a good model of fit for the energy range detected by Fermi-LAT is a LogParabola model. The source PKS 2155-304 is clearly variable. The time scaleof variability is at least as short as days. The analysis done here can not say whether thereis variability in shorter time ranges. In order to gather further knowledge on AGNs it isimportant to perform multi-wavelength observations both of states of high variability and ofmore quiescent states.

60

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Supplement

Details on the computer analysis

Fermi science tools

In order to perform the analysis of large datasets not only a large computer is needed, but alsodedicated software is necessary. For the analysis of the data from the Fermi-LAT experiment,NASA (National Aeronautics and Space Administration) distributes the Fermi science tools.It is programmed for a Linux-based system and is available for different Linux distributionsas well as some UNIX distributions as OS X 10.8 and 10.9, see [14]. This software is beingused on Alarik and has not to be installed in the computer of every user. Instead a muchsmaller application is being used by the end user. This application is called Enrico (the firstname of Enrico Fermi, see also Sec. 3.5).

The data from Fermi-LAT consist on one hand of event data from every photon detectedby the experiment, and on the other hand of spacecraft data. The analysis has to be able toaccess both of them. The information about the angle and the position of the satellite hasto be combined with the information of directions and energy of photons received.

Communicating with Linux commands

As mentioned above the communication between the computing system Alarik and the enduser is made via Linux commands. For this thesis an ordinary personal computer has beenused, a Macbook with a 1, 4GHz processor. The computing power is in Alarik. For a userthat is accustomed to using point and click with a mouse it is a readjustment of earliercomputer skills. An example of the interface is shown in Fig. 8.1.

The process of analysing

For performing the Fermi-LAT analysis in this thesis, firstly an account at the Alarik has tobe set up. Then links have to be generated. Links that both points to the files where theFermi science tools are and to the files where the data are stored.

The Enrico software has to be downloaded to the account, from reference. To makeEnrico be able to perform the analysis of the source a configuration file has to be set up. Inthis file, the coordinates for the source (the AGN) that is going to be analysed have to bespecified. The position of the source can be retrieved from the NED-catalogue. NED is shortfor NASA/IPAC Extragalactic Database which is operated by the Jet Propulsion Laboratory,California Institute of Technology, under contract with the National Aeronautics and SpaceAdministration, see [15].

65

Figure 8.1: The interface while communicating with the computing system Alarik. What isseen on the screen of the pc.

The configuration file also consists of the time interval chosen, the maximum and mini-mum energies, what type of likelihood analysis should be used, etc. See also the example ofa configuration file further down in the supplement.

With the data, the configuration file and the Fermi science tools it is possible to do theanalysis by “telling” Alarik what to do. Sending a job to Alarik is done using batch scripts.A batch script is a set of commands that a computer follows step by step. The batch scriptfor this project contains information about the maximum time for the computing. If a resultis not ready in the specified time, the computation will be aborted. The file has informationof which file to save the results in, where to look for the fermi science tools, which files tocopy and analyse and so on. To start the batch script the command "sbatch" is used, see[25]. Alarik gives the job a number and either starts direct or puts the job in queue. Aftera day or two the results are ready, depending on the amount of data being processed in thejob.

Looking at the results

The next step is to look at the results. For a spectral analysis first another batch script hasto be used. That file basically just collects the results in a file with a new name, that is easyto locate for the next step. The next step is to use the Enrico tools to plot the data. For theLight curve the approach is almost the same. The difference is that the batch script to usebefore the Enrico tool is slightly different.

Example of configuration file

# Default config and validation file for Enrico.

#

# Besides providing default options it is also used

# to check the user config file.

# Options without default options here must be

# specified in the user config file

# Folder where the output will be stored

out = /alarik/nobackup/q_z/tm222ca/fermi/PKS2155-304/unbinned

/PowerLaw2_300MeV_300GeV_239557418_450846434

verbose = yes

[target]

spectrum = PowerLaw2

dec = -30.2255883

name = PKS2155-304

ra = 329.7169379

[space]

yref = -30.2255883

rad = 10.0

xref = 329.7169379

srcpix = 120

nxpix = 200

nypix = 200

nlong = 120.0

nlat = 120.0

binsz = 0.1

coordsys = CEL

proj = AIT

## phibins = 0.0

[energy]

emax = 300000.0

emin = 300.0

enumbins_per_decade = 10

[file]

xml = /alarik/nobackup/q_z/tm222ca/fermi/PKS2155-304/unbinned/

PowerLaw2_300MeV_300GeV_239557418_450846434/

PKS2155-304_PowerLaw2_model.xml

spacecraft = /alarik/nobackup/q_z/tm222ca/fermi/PKS2155-304/

unbinned/PowerLaw2_300MeV_300GeV_239557418_

450846434/lat_spacecraft_merged.fits

tag = LAT_Analysis

event = /alarik/nobackup/q_z/tm222ca/fermi/PKS2155-304/unbinned/

PowerLaw2_300MeV_300GeV_239557418_

450846434/lat_photon.lis

[time]

tmax = 450846434

67

tmin = 239557418.0

[environ]

# Analysis environment configuration

# Can also be done via shell environment variables

FERMI_DATA_DIR = "/alarik/nobackup/q_z/tm222ca/fermi/PKS2155-304

/unbinned/PowerLaw2_300MeV_300GeV_239557418_450846434/"

FERMI_CATALOG_DIR = "/alarik/nobackup/q_z/tm222ca/fermi/PKS2155-304/

unbinned/PowerLaw2_300MeV_300GeV_239557418_450846434/"

FERMI_CATALOG = ""

FERMI_DIFFUSE_DIR = "/alarik/nobackup/q_z/tm222ca/fermi/PKS2155-304/


FERMI_PREPROCESSED_DIR = "/alarik/nobackup/q_z/tm222ca/fermi/PKS2155-304/


[analysis]

# General analysis options

likelihood = unbinned

evclass = 2

ComputeDiffrsp = yes

zmax = 100.0

roicut = no

filter = DATA_QUAL==1&&LAT_CONFIG==1&&ABS(ROCK_ANGLE)<52

irfs = P7REP_SOURCE_V15

# if convtype =0 or 1, an ::FRONT of ::BACK is happend at the

end of the irfs string automatically

convtype = -1

[fitting]

optimizer = MINUIT

ftol = 1e-06

[model]

# The following options determine the xml model

diffuse_gal_dir = "/alarik/nobackup/q_z/tm222ca/fermi/PKS2155-304/


diffuse_iso_dir = "/alarik/nobackup/q_z/tm222ca/fermi/PKS2155-304/


diffuse_gal = "gll_iem_v05_rev1.fits"

diffuse_iso = ""

# user points sources for diffuse catalog sources

# freeze spectral parameters for weak and far away sources:

min_significance = 4.0

max_radius = 3.0 # -1 means use ROI radius

[tool]

chatter = 2

clobber = no

debug = no

gui = no

mode = ql

[Spectrum]

#Generates fits files or not?

FitsGeneration = yes

#Generates plots (SED, model map)

ResultPlots = yes

#Freeze the spectral index of the source

FrozenSpectralIndex = 0.0 # no implication if 0

#Use the summed likelihood method

SummedLike = no

#Submit the job to a cluster?

Submit = no

[UpperLimit]

#Assumed Spectral index

SpectralIndex = 1.5

# UL method could be Profile or Integral (provided by the fermi collaboration)

Method = Profile

envelope = no

#Compute an UL if the TS of the sources is <TSlimit

TSlimit = 25.0

[LightCurve]



#Number of points for the LC

NLCbin =82

#Index for the power law

SpectralIndex = 2.0

MakeConfFile = yes

#Compute Variability index as in the 2FGL.

ComputeVarIndex = yes


Submit = no

#Compute an UL if the TS of the sources is <TSLightCurve

TSLightCurve = 9.0

#Generates control plots

DiagnosticPlots = yes

[AppLC]



#Spectral index for the exposure calculation

index = 1.5

#Number of bins

NLCbin = 10

#bin form data or frozen bin size

binsFromData = no

[Ebin]



NumEnergyBins = 5

#Compute an UL if the TS of the sources is <TSEnergyBins

TSEnergyBins = 9


Submit = no

[TSMap]

#Re-fit before computing the TS map

Re-Fit = no

#Numbers of pixel in x and y

npix = 10

#Remove or not the target from the model

RemoveTarget = yes


Submit = no

#Generate the TS map pixel by pixel or by grouping the pixels by row.

#(reduce the numbers of jobs but each job are longer)

method = row

Faculty of Technology

SE-391 82 Kalmar | SE-351 95 Växjö

Phone +46 (0)772-28 80 00

[email protected]

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