intermediate observations and analysis progress report · in “handbook of cosmic hazards and...

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 640351.

NEOShield-2 Science and Technology for Near-Earth Object Impact Prevention

Grant agreement no: 640351 Project Start: 1 March 2015

Project Coordinator Airbus Defence and Space DE Project Duration: 31 Months

WP 10

Deliverable D10.2

Intermediate observations and analysis progress report

WP Leader OBSPM Task Leader OBSPM

Due date M13, 31 Mar 2016

Delivery date 30.03.2016

Issue 1.0

Editor (authors) D. Perna, M.A. Barucci, S. Eggl, M. Birlan, E. Dotto, S. Ieva, M. Delbo, V. Ali-Lagoa

Contributors A. Di Paola, R. Speziali, E. Mazzotta Epifani, M. Lazzarin, S. Magrin, I. Bertini J. Hanus, M. Popescu, E. Perozzi

Verified by

Document Type R

Dissemination Level PU

The NEOShield-2 Consortium consists of:

Airbus DS GmbH (Project Coordinator) ADS-DE Germany Deutsches Zentrum für Luft- und Raumfahrt e.V. DLR Germany Airbus Defence and Space SAS ADS-FR France Airbus Defence and Space Ltd ADS-UK United Kingdom Centre National de la Recherche Scientifique CNRS France DEIMOS Space Sociedad Limitada Unipersonal DMS Spain Fraunhofer-Gesellschaft zur Förderung der angewandten Forschung e.V. EMI Germany GMV Aerospace and Defence SA Unipersonal GMV Spain Istituto Nazionale di Astrofisica INAF Italy Observatoire de Paris OBSPM France The Queen’s University of Belfast QUB United Kingdom

NEOShield-2 D10.2 Title: Intermediate observations and analysis progress report Issue, Date i1.0, 30.03.2016 /31

Change Record

Issue Date Section, Page Description of Change

0.1 15/3/2016 First Draft ; Distributed to Consortium

1.0 30/3/2016 Incorporating comments from Consortium


Table of Contents

1 Introduction ............................................................................................................................................. 4

1.1 Scope and objective ...................................................................................................................... 4

1.2 List of Abbreviations .................................................................................................................... 4

1.3 Applicable Documents ................................................................................................................ 5

1.4 Reference Documents ................................................................................................................. 5

2 Photometric observations ................................................................................................................... 8

2.1 Colours and phase functions (INAF) ...................................................................................... 8

2.2 Lightcurves and rotational properties (OBSPM-IMCCE).............................................. 11

2.2.1 French facilities ..................................................................................................................................... 11

2.2.2 International Facilities, the characterization of 2004 BL86 ............................................... 12

2.2.3 The YELP campaign ............................................................................................................................. 13

2.2.4 Space based photometry using NASA's Kepler spacecraft .................................................. 14

2.3 Precovery of NEOs and discovery apparition photometry (QUB) ............................ 17

3 Spectroscopic observations (OBSPM-LESIA) ............................................................................. 18

3.1 A literature study of the Potentially Hazardous Asteroid (PHA) population ....... 18

3.2 Guaranteed Time Observations at ESO-NTT .................................................................... 20

3.3 Further ESO observations ....................................................................................................... 23

4 Thermal IR observations (CNRS) ................................................................................................... 24

4.1 Modeling techniques ................................................................................................................. 24

4.1.1 Determination of sizes and albedos of NEAs from simple thermal models ................. 24

4.1.2 Thermal inertia ...................................................................................................................................... 25

4.1.3 Thermophysical modelling of near-Earth Asteroids .............................................................. 25

4.1.4 Asteroid 3D shapes as input for thermophysical models .................................................... 26

4.1.5 Hybrid thermal model ........................................................................................................................ 27

4.2 Results ............................................................................................................................................ 27

4.2.1 TPM of (3200) Phaethon ................................................................................................................... 27

4.2.2 TPM of (1685) Toro ............................................................................................................................. 28

4.2.3 Hybrid thermal model of (1685) Toro ......................................................................................... 29

4.2.4 Comparison with other thermal inertias found in the literature...................................... 29

4.3 Conclusions and Perspectives ............................................................................................... 30

5 Summary ................................................................................................................................................. 31


1 Introduction

1.1 Scope and objective

At the moment of this writing the number of known NEOs exceeds 14000 and new objects are currently being discovered at the rate of 3 per day. However less than 10% of NEOs have been investigated to retrieve their physical properties. The lack of data is particularly evident for the smaller sizes, those of interest for NEOShield-2. For example, less than 100 NEOs in the size range 50-300 m had been taxonomically characterized prior of our observations.

The present/near future NEO discovery rate is mostly due to the detection of small objects approaching the Earth. They represent a significant source of potential targets for physical characterization satisfying the PROTEC-2 requirements on size and accessibility, thus complementing the observation of already known objects. As discussed in Section 3.1 of the NEOShield-2 Deliverable 11.1 “Report on a Future NEO physical properties database” [AD3], more than 2/3 of NEOs which had a close approach with the Earth in 2012, hence an observational opportunity, were discovered within the same year, and among them almost the totality are small (< 300 m). Hence the possibility of a quick (~weeks) physical follow-up of newly discovered objects could provide a significant contribution to the characterization of the NEO population, especially in the size range of our interest. As the discoveries peak sharply around V=20, in order to exploit this opportunity at best, large telescopes (4-m class) available on short notice are needed. That’s why, as reported in [AD2], an agreement with the European Southern Observatory (ESO) was signed on 1/3/2015 to obtain Guaranteed Time Observations (GTO) at the 3.6-meter New Technology Telescope (NTT). Further observing time has been obtained via the standard biannual proposals at large telescopes, as well as with our small guaranteed-access telescopes.

In this document, we report about all observations and data analysis carried out so far (M13) by all NEOShield-2 participating observers.

Section 2 deals with photometric observations and data analysis (INAF, OBSPM-IMCCE, QUB).

Section 3 deals with spectroscopic observations and data analysis (OBSPM-LESIA).

Section 4 deals with thermal infrared observations and data analysis (CNRS).

1.2 List of Abbreviations

AD Applicable Document

AU Astronomical Unit

EARN European Asteroid Research Node

EPIC Ecliptic Plane Input Catalog

ESO European Southern Observatory

GA Grant Agreement

GTO Guaranteed Time Observations

IRTF InfraRed Telescope Facility

LBT Large Binocular Telescope

MOID Minimum Orbit Intersection Distance

NEA Near Earth Asteroid

NEATM Near-Earth Asteroid Thermal Model

NEO Near Earth Object


NTT New Technology Telescope

OHP Observatoire Haute Provence

PDM Pic du Midi

PHA Potentially Hazardous Asteroid

PHO PHA Potentially Hazardous Object

RD Reference Document

SSO Solar System Object

TIR Thermal InfraRed

TNG Telescopio Nazionale Galileo

TPM Thermo-Physical Model

WISE Wide-field Infrared Survey Explorer

WP Work Package

1.3 Applicable Documents

[AD1] NEOShield-2: “Science and Technology for Near-Earth Object Impact Prevention”, Grant Agreement no. 640351, 28.10.2014.

[AD2] NEOShield-2 Deliverable 10.1 “Report on observation procedures and tools”, v1.0, 7.9.2015.

[AD3] NEOShield-2 Deliverable 11.1 “Report on a Future NEO physical properties database”, v0.1, 14.3.2016.

1.4 Reference Documents

[RD1] Alí-Lagoa V., et al. (2014) Astron. Astrophys., 561, A45.

[RD2] Altmann, M., A. H. Andrei, U. Bastian, Sebastien Bouquillon, F. Mignard, R. Smart, I. Steele, Paolo Tanga, and Francois Taris (2010). "Ground Based Optical Tracking of Gaia." In Workshop Gaia Fun-SSO: follow-up network for the Solar System Objects, vol. 1, p. 149.

[RD3] Berthier, J., Carry, B., Vachier, F., Eggl, S., Santerne, A. (2016) ,Prediction of transits of solar system objects in Kepler/K2 images: An extension of the Virtual Observatory service SkyBoT, MNRAS (accepted), ArXiv e-prints, arXiv:1602.07153.

[RD4] Birlan, M., Barucci, M. A., Vernazza, P., Fulchignoni, M., Binzel, R. P., Bus, S. J., Belskaya, I., & Fornasier, S. (2004), New Astronomy, 9, 343.

[RD5] Birlan M., Popescu M., Nedelcu D. A., Turcu V., Pop A., Dumitru B., Stevance F., Vaduvescu O., Moldovan D., Rocher, P., Sonka A., Mircea, L. (2015), Characterization of (357439) 2004 BL86 on its close approach to Earth in 2015, Astronomy & Astrophysics vol 581, id.A3, 7pp.

[RD6] Birlan M., Nedelcu A., Sonka A., Popescu M., Dumitru B. (2016) Observations for secure and recovery Near-Earth Asteroids, Rom Astron. J., vol 26, n 1 (accepted).

[RD7] Bottke W. F. J., Vokrouhlický D., Rubincam D. P., et al. (2006) Annu. Rev. Earth Planet. Sci., 34, 157–191.

[RD8] Carry, B. (2012,) Planetary and Space Science, 73, 98.

[RD9] Carry, B., Solano, E., Eggl, S., & DeMeo, F. E. (2016). Spectral properties of near-Earth and Mars-crossing asteroids using Sloan photometry. Icarus.


[RD10] Delbo’ et al. (2015) In Asteroids IV (P. Michel. et al., eds.). Univ. of Arizona, Tucson.

[RD11] DeMeo, F. E., Binzel, R. P., Slivan, S. M., & Bus, S. J. (2009), Icarus, 202, 160.

[RD12] Drube L., Harris A. W., Hoerth, T., Michel, P., Perna, D., Schäfer, F. (2015). In “Handbook of Cosmic Hazards and Planetary Defense”, ed. Joe Pelton & Firooz Allahdadi, Springer.

[RD13] Durech et al. (2005) Earth Moon Planets, 97, 179–187.

[RD14] Durech et al. (2007) In Near Earth Objects, Our Celestial Neighbors: Opportunity and Risk (A. Milani et al., eds.), p. 191. Cambridge Univ., Cambridge.

[RD15] Durech et al. (2009) Astron. Astrophys., 493, 291–297.

[RD16] Eggl, S., Hestroffer, D., Cano, J. L., Avila, J. M., Drube, L., Harris, A. W., ... & Michel, P. (2016). Dealing with Uncertainties in Asteroid Deflection Demonstration Missions: NEOTwIST. IAU Symposium, 318, 231-238.

[RD17] Fulvio, D., Perna, D., Ieva, S., et al. (2016), MNRAS, 455, 584.

[RD18] Hanuš J., et al. (2011) Astron. Astrophys., 530, A134.

[RD19] Hanuš J., et al. (2013a). Icarus, 226, 1045–1057.

[RD20] Hanuš J., et al. (2013b) Astron. Astrophys., 551, A67.

[RD21] Hanuš J., et al. (2015) Icarus, 256, p. 101-116.

[RD22] Harris A. W. (1998), Icarus, 131, 291–301.

[RD23] Harris et al. (2013), Acta Aeronautica 90, 1, p. 80-84.

[RD24] Harris A. W. and Lagerros J. S. V. (2002) In Asteroids III (W. F. Bottke Jr. et al., eds.). Univ. of Arizona, Tucson.

[RD25] Ieva, S., Dotto, E., Lazzaro, D., et al. (2016), MNRAS, 455, 2871.

[RD26] Kaasalainen (2001) Astron. Astrophys., 376, 302–309.

[RD27] Kaasalainen & Torpa (2001) Icarus, 153, 24–36.

[RD28] Kaasalainen (2004) Astron. Astrophys., 422, L39–L42.

[RD29] Licandro et al. (2016), Astron. Astroph. 585, A10, 4pp.

[RD30] Mainzer et al. (2011) Astrophys. J., 743, 156.

[RD31] Masiero et al. (2011) Astrophys. J., 741, 68.

[RD32] Micheli, M., Tholen, D. J., Jenniskens, P. (2016). Icarus, 267, pp. 64-67.

[RD33] Moskovitz, N. et al. (2014), in AAS/Division for Planetary Sciences Meeting Abstracts, Vol. 46.

[RD34] Pal, A., Szabo, R., Szabo, G. M., Kiss, L. L., Molnar, L., Sarneczky, K., & Kiss, C. (2015), The Astrophysical Journal Letters, 804, L45.

[RD35] Perna, D., Dotto, E., Ieva, S., et al. (2016). Grasping the Nature of Potentially Hazardous Asteroids. The Astronomical Journal, 151, 11, 14 pp.

[RD36] Pravec, P. & Harris, A. W. (2000). Icarus, 148, pp. 12-20.

[RD37] Rozitis et al. (2014) Nature, 512, 174–176.

[RD38] Szabo, R. et al. (2015), The Astronomical Journal, 149, 112.

[RD39] Thuillot, W., Carry, B., Berthier, J., David, P., Hestroffer, D., & Rocher, P. (2014). Gaia-FUN-SSO: a network for ground-based follow-up observations of Solar System Objects. In SF2A-2014: Proceedings of the Annual meeting of the French Society of Astronomy and Astrophysics (Vol. 1, pp. 445-448).


[RD40] Thuillot, W., Bancelin, D., Ivantsov, A., Desmars, J., Assafin, M., Eggl, S., ... & Abe, L. (2015). The astrometric Gaia-FUN-SSO observation campaign of 99942 Apophis. Astronomy & Astrophysics, 583, A59.

[RD41] Wright et al. (2010) Astron. J., 140, 1868–1881.


2 Photometric observations

2.1 Colours and phase functions (INAF)

During this first year of activity, we have analyzed and interpreted photometric data acquired on July 2014 at Telescopio Nazionale Galileo (TNG) and we have prepared and submitted several proposals to TNG and the Large Binocular Telescope (LBT).

At TNG we have obtained a long-term program devoted to the characterization of surface color indexes (B-V-R-I) for a large number of NEAs. The program started in September 2015 and spans on 4 semesters (up to August 2017). For each semester, we have been awarded of 6 runs of 4 hours each one. So far we have acquired data on 58 targets: for 30 of them data have been already reduced and analysed and a preliminary taxonomy has been obtained. For further 28 targets, data are presently under reduction.

At LBT, we have obtained telescope time to observe NEAs in the B-V-R-I-g-r-z filters. 6 targets have been so far observed and data are presently under reduction.

In the framework of a collaboration with the Observatorio Nacional (Rio de Janeiro - Brasil, D. Lazzaro) for the use of the telescope OASI – Itacuruba, we have performed observations of NEAs at different phase angles, for phase curves characterization. Five targets have been so far observed: for 1 of them data are presently under reduction, for 4 of them phase curves have been obtained.

Table 2-1: runs, allocated time and comments.

Telescope run Allocated time Comments

TNG July 2014 4h 9 targets – data reduced

TNG October 2015 4h 6 targets – data reduced

TNG November 2015 4h No observations, bad

weather

TNG

December 2015

8h

15 targets – data reduced 13 targets – data under

reduction

TNG January 2016 4h No observations, bad

weather

TNG February 2016 4h 15 targets – data under

reduction

OASI – Itacuruba September 2015 8n 4 targets – data reduced

OASI – Itacuruba October 2015 --- No observations, bad

weather

OASI – Itacuruba November 2015 --- No observations, bad

weather

OASI – Itacuruba December 2015 1n 1 target – data under

reduction

OASI – Itacuruba January 2016 --- No observations, bad

weather

OASI - Itacuruba February 2016 --- No observations, bad

weather

LBT January 2016 2h 2 targets – data under

reduction

LBT February 2016 2h 4 targets – data under

reduction


For 4 objects observed at OASI – Itacuruba it was possible to compute the absolute magnitude H from the phase curve characterization.

Table 2-2: dates of observation and computed absolute magnitude (and albedo value from literature) of the 4 targets observed at OASI-Itacuruba.

Object Date H ρv

4055 Magellan 9-18/9/2015 14.43 ± 0.24 0.31(1)

333889 1998SV4 9-18/9/2015 17.62 ± 0.38 0.19 (2)

337118 1999TX2 9-18/9/2015 17.77 ± 0.47 0.11(3)

446833 2001RB12 9-18/9/2015 20.40 ± 0.35 --- References: (1) Thomas et al. 2014; (2) Harris et al. 2011; (3) Trilling et al. 2010.

Table 2-3: date of observation, color indexes and the obtained taxonomy of the 30 objects observed at TNG.

Object

date V

B-V

V-R

V-I

Preliminary Taxonomy

2014ER49 1/07/2014 18.61 ± 0.03 0.88 0.52 1.04 S-complex

2005UK1 1/07/2014 18.94 ± 0.03 0.51 0.58 0.82 S-complex

2010NY65 1/07/2014 18.63 ± 0.02 0.77 0.56 1.11 S-complex

2004LJ1 1/07/2014 18.53 ± 0.02 0.6 0.49 0.9 Sv

2008LV16 1/07/2014 18.54 ± 0.01 0.8 0.46 0.83 S-complex

1994CJ1 1/07/2014 18.54 ± 0.01 0.94 0.61 1.01 A

2002SR41 1/07/2014 18.77 ± 0.02 0.76 0.44 0.94 D, S-complex

2010LE15 1/07/2014 19.23 ± 0.03 0.86 0.67 0.88 S-complex, A

1995SA 1/07/2014

18.24 ± 0.02 0.74 0.33 0.81 C-complex, X-

complex

65690 13/10/2015 20.33 ± 0.06 0.68 0.46 0.43 Xc

423709 13/10/2015 21.74 ± 0.15 0.61 0.59 1.25 A/V

2006BE55 13/10/2015 21.17 ± 0.05 0.5 0.53 1.4 S-complex

2011AK5 13/10/2015 19.57 ± 0.05 0.81 0.65 0.88 S-complex

445974 13/10/2015 21.78 ±0.14 0.62 0.58 0.85 S-complex

2013QJ10 13/10/2015 20.25 ± 0.04 0.89 0.3 0.79 S-complex

2013UG5 10/12/2015 20.17 ± 0.04 0.43 0.33 0.73 C-complex

2015RT83 10/12/2015 19.51 ± 0.03 0.66 0.45 0.86 D/X

155110 10/12/2015 19.13 ± 0.03 0.74 0.34 0.92 X-complex

138852 10/12/2015 19.77 ± 0.05 0.7 0.4 0.85 X-complex

442243 10/12/2015 19.95 ± 0.04 0.8 0.38 0.88 S-complex

2012XA133 10/12/2015 19.97 ± 0.04 0.56 0.49 0.64 Q

142563 10/12/2015 19.92 ± 0.04 0.78 0.42 0.57 O,B

162273 10/12/2015 19.52 ± 0.04 1.02 0.58 0.77 S-complex

2008VQ4 10/12/2015 19.78 ± 0.04 0.64 0.37 0.51 C-complex

443880 10/12/2015 20.05 ± 0.07 0.61 0.28 0.46 B, C-complex

2011YH6 10/12/2015

19.96 ± 0.06 0.7 0.25 0.84 X-complex, S-

complex

174806 10/12/2015 19.94 ± 0.03 0.72 0.43 0.87 T, S-complex


2000YK4 10/12/2015 20.33 ± 0.05 0.69 0.29 0.77 C-complex

194126 10/12/2015 19.87 ± 0.04 0.79 0.39 0.78 X-complex

2012XD112 10/12/2015 19.67 ± 0.03 0.79 0.28 0.55 C-complex

The whole sample of objects observed at TNG were divided in four classes according to their composition: carbonaceous (C), siliceous (S), basaltic (V) and miscellaneous (X).

The distribution of different taxa was then analyzed according to NEAs orbital parameters.

In Fig. 2-1 we show, as an example, the Minimum Orbital Intersection Distance (MOID) with our planet as a function of the orbital inclination of the observed NEAs. In our sample, siliceous objects seem to have the lowest MOID, while C and X-complex objects seem to have higher inclination. Two carbonaceous objects show low MOID and very high inclination, representing the most dangerous objects in the present set of bodies.

Fig. 2-1 Minimum Orbital Intersection Distance (MOID) of compositional groups (Carbonaceous, Silicaceous, Basaltic and Miscellaneous) of our sample of NEAs, plotted vs their orbital inclination.

As above mentioned, data acquired in the temporal range December 2015 - February 2016 are presently under reduction; new observations will be soon available. Thus will allow us to implement the number of objects analyzed and upgrade our statistical work.

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0 5 10 15 20 25 30 35

MO

ID (

au

)

i (deg)

V

C

X

S


2.2 Lightcurves and rotational properties (OBSPM-IMCCE)

2.2.1 French facilities

The IMCCE partakes in the data collection and analysis endeavor making use of international as well as French facilities like the Observatoire Haute Provence (OHP) and the Pic du Midi (PDM) observatories. The telescopes at those sites available for asteroid research are in the one-meter class supporting a relatively large fieldview (FOV) which makes the excellent tools for and astrometric follow up of newly discovered asteroids. However, only a few relatively bright objects can be studied spectroscopically and photometrically at reasonable signal-to-noise ratios. The observatories that are available to the IMCCE for astrometric and photometric observations of NEOs are the Observatoire Haute Provence (OHP, MPC Code 511) and Pic du Midi (PDM, MPC Code 586). The accessible telescopes at both sites have apertures of 120cm and 106cm, respectively. While both telescopes are used to generate robust ground based astrometry for fainter sources on a regular basis, only relatively bright NEOs (around apparent magnitude 17-18) can be targeted with respect to photometry, if a signal-to-noise ratio around 50 is aimed for. Pic du Midi is accessible throughout the year. However, the observation program has to be funded through the NEOShield-2 travel and/or IMCCE team budget. A shared campaign was organized at PDM from September, 4th-9th, 2015. Unfortunately, the weather and shared time was allowing only for one target to be observed, namely 2001 RB12. In contrast, time at the OHP site was more plentiful as it could be shared with Gaia-FUN-SSO (Thuillot et al. 2014, 2015) and GBOT (Altmann et al. 2010) programs. In total we were able to conduct four campaigns at the OHP in 2015 yielding 13 objects where light curves could be measured fully or at least in part. Table 2-4 summarizes the preselected NEOShield-2 targets compatible with the brightness limits of OHP and PDM which were observed so far. The data and calibration frames are currently saved at IMCCE servers but will be made available for NEOShield-2 consortium members as soon as the corresponding facilities are online. Since the GBOT astrometric pipeline has become available astrometric data reduction is currently tested on a semiautomated basis. The current GBOT pipeline does extract photometric data. However, it has not been designed to provide high precision photometric results. While some work has been done in this respect, the GBOT photometric pipeline sill needs to be worked on in this respect to allow for a proper re-reduction of the acquired data. We foresee a re-reduction of all data by mid 2016. The Gaia-FUN-SSO campaign continues through 2016. Shared NEOShield-2 observation time at the OHP has already been allocated for April 4th-8th 2016. One observing run (PI M. Birlan) is also scheduled for April 2016 at Pic du Midi for observing colors of NEAs.


Table 2-4. Targets observed at French observatories so far. Astrometric (AM) and photometric light curve (LC) observations are shown. The corresponding program name is also given. One can see that time sharing with Gaia FUN-SSO (GFSSO) has resulted in a substantial increase in observed targets. YELP is a program speficially dedicated to detect changes in the rotation of NEOs with a measured astrometric orbit drift.

2.2.2 International Facilities, the characterization of 2004 BL86

The potentially hazardous asteroid (PHA) (357439) 2004 BL86 grazed Earth on January 26, 2015 at a distance of about 1.2 million km. The favorable geometry during its closest approach to Earth in January-February 2015 allowed to derive its physical and dynamical parameters. (357439) 2004 BL86 was previously estimated to be a 500 m body. Spectral VNIR and photometry of asteroid binary asteroid (357439) 2004 BL86 was obtained. (357439) 2004 BL86 was classified as V-type asteroid, which are particularly rare among binary PHAs, see Figure 2-2. Near-infrared (NIR) spectral observations (0.8-2.5μm) were carried out using the upgraded SpeX instrument mounted on the InfraRed Telescope Facility (IRTF), located on Mauna Kea, Hawaii. The remote observing technique was used from CODAM-Paris Observatory (Birlan et al. 2004). The upgraded SpeX (uSpeX) instrument was used in low-resolution prism mode, with a 0.8×15” slit oriented north-south. Spectra of the asteroid and solar analogs were obtained alternatively in two distinct locations on the slit (A and B); this is referred to as the nodding procedure. The visible (V) spectrum (0.4-0.9 μm) was obtained using the IDS instrument mounted on Isaac Newton Telescope (INT), located at El Roque de Los Muchachos Observatory, Canary Islands. These observations were obtained remotely in a first remote observing run between th e ROC-Astronomical Institute, Romanian Academy and INT. The IDS instrument was used in low-resolution mode (R150 grating) with a slit width of 1.5” and the RED +2 CCD

TARGET PROGRAM TYPE DATE PERIOD (prel.) [h]

2000 LF6 GFSSO LC 11-15.06.2015 14.9

2010 EV45 GFSSO LC 11-15.06.2015 3.5

1998 AX4 GFSSO LC 15.06.2015 2.9

2003 NZ6 GFSSO AM 14.06.2015

2015 JH2 GFSSO AM 15.06.2015

2015 KJ7J GFSSO AM 15.06.2015

2015 KL122 GFSSO AM 15.06.2015

2006 WP127 GFSSO LC 22-23.07.2015 tbd

2015 NZ13 GFSSO AM 20.07.2015

2010 PR66 GFSSO LC 10.-13.08.2015 tbd

2012 NP GFSSO LC 10.-13.08.2015 19.6

2001 RB12 NEOShield 2 LC 9.-14.09.2015 5.3

2015 SA17 GFSSO AM 10.10.2015

2015 TE GFSSO LC 10.-15.10.2015 tbd

Geographos GFSSO LC 10.-15.10.2015 5.2

1998VW36 GFSSO AM 10.-15.10.2015

2000 NL10 GFSSO LC 10.-15.10.2015 6.9

2000 SU318 GFSSO AM 10.-15.10.2015

2003 XO15 GFSSO LC 10.-15.10.2015 tbd

1991 CS YELP LC 2.-5.03.2016 2.4

2016 CB138 YELP AM 2.-5.03.2016

2016 DV1 YELP LC 02.03.2016 tbd

A100hUP YELP AM 02.03.2016

2016 DN2 YELP AM 03.03.2016

2016 ED YELP AM 03.03.2016


detector. Based on an average value of the thermal albedo for a V-type object, its diameter was estimated to be 290 ± 30 m. The mineralogical analysis revealed similarities to HED meteorites. The band analysis revealed that the object is more similar to an eucritic and howarditic composition and that it originated from the crust of a large parent body. The analysis tends to a mineralogical solution with an errorbar of 4%. A dynamical analysis showed a chaotic behavior of (357439) 2004 BL86. The result of integrating backward in time for 500 000 yr showed that this object was part of the NEA population. However, even if its MOID is 0.007 au, no direct correlation with HED meteorite falls was found. The rotational period of the asteroid was estimated to be 2.637±0.024 h and 2.616±0.061 h, respectively. These observations were crucial since the next favorable geometry for ground-based observations of (357439) 2004 BL86 will not occur before January-February 2050. More details can be found in Birlan et al. (2015).

Figure 2-2: (Top) Composite VNIR spectrum of (357439) 2004 BL86 normalized to unity at 0.55 μm. (Bottom) Mineralogical parameters in a howardite–eucrite–diogenite (HED) diagram. The composition is more like eucritic and howarditic mineralogy.

2.2.3 The YELP campaign

Proposed to the OHP, YELP (Yarkovsky effect Estimation via Light-curve derived Physical modeling) is an observation campaign, initiated by a consortium of astronomers at the IMCCE, LESIA Observatoire de Paris and the OCA in Nice with the aim of improving the correspondence between model predictions and observations in order to allow for a more reliable long term impact monitoring of potentially hazardous objects. A brief summary of the project is given below. A proper physical characterization is important for an accurate prediction of the


influence of non-gravitational accelerations on asteroid orbits. Fortunately, nongravitational effects such as the Yarkovsky-effect – an acceleration due to emission of thermal radiation tend to cause only relatively small alterations in an asteroid’s orbit. However, in combination with close encounters with e.g. terrestrial planets, even small drift effects can lead to significant changes in predicted future positions. For near-Earth asteroids (NEAs) and especially for potentially hazardous objects (PHO), an accurate understanding of the nongravitational forces is, thus, vital in order to assess a potential impact threat. In fact, one of the main limitations of long term orbit prediction and impact monitoring for asteroids is our lack of knowledge of the physical and spin properties of asteroids. This becomes clear when looking at the drift rate in the asteroid’s semimajor axis caused by the Yarkovsky effect

where S, c, n, r, A, γ, P , Theta, T , Γ, σ are the solar flux at 1 au, the speed of light, the mean orbital motion, the heliocentric distance in au, the bolometric Bond albedo, and the spin axis obliquity, the rotational period, the emissivity, the subsolar temperature, the thermal inertia (see Section 4), and the Stefan-Boltzmann constant, respectively. From the above equation it becomes clear that the thermal properties and the spin state directly influence the non-gravitational orbit drift, even in the most simple models. It has been difficult so far to find a reliable link between first principle predictions and actually measured values. In fact, basically all detections of the Yarkovsky effect have been achieved via fitting a constant transversal acceleration to astrometric and radar data. It remains, however, unclear whether this transversal acceleration is indeed a manifestation of the Yarkovsky effect. This is partly due to the fact that the physical parameters for asteroids where the Yarkovsky effect was determined via astrometry alone remain largely unknown. Thus, no reasonable comparison between model predictions and observed drift rates can be performed. The observation program aims to collect vital physical data on a sample of asteroids with already detected Yarkovsky drift rates. The goal is to accumulate enough photometric and thermal data to compare realistic shape and thermal model predictions with the actually measured drifts. Observing time at the 120cm telescope at the OHP gives access to vital photometry and astrometry measurements that will be used to determine and improve current period as well as drift rate estimates. Additional thermal infrared observations would have been carried out at ESO. However, this proposal was unfortunately not selected. Nevertheless, the program should enhance our understanding of how the Yarkovsky effect works in detail and, thus, contribute to an improvement in the global asteroid impact risk assessment process. Two OHP observation runs in 2016 were attributed to the YELP campaign, one from March 1st-5th 2016 and the other one from March 31st to April 4th 2016. The first observation run featured the target 1991 CS, a kilometer sized asteroid with a period of roughly 2.4h with a detectable astrometric drift rate.

2.2.4 Space based photometry using NASA's Kepler spacecraft

Given the limited number of objects accessible via OHP and PDM, other options for asteroid photometry have been considered, in order to catch up with US based programs such as MANOS (Moskovitz et al. 2014). The basic idea was to use photometric data of asteroids acquired by NASA’s Kepler spacecraft during the K-2 mission. Kepler is known to produce high accuracy photometry for stars. The possibility of extracting photometry of Solar System Objects (SSOs) passing the FOV of Kepler has been discussed e.g. by Pal et al. (2015), Szabo et al. (2015). During the K-2 mission, the Kepler spacecraft enacts step and stare phases along the ecliptic, see Figure 2-3. However, not all of the SSOs in K-2’s FOV have actually been observed due to telemetry constraints. Only small areas around the stars, so called ”boxes” or ”imagettes” around the ecliptic plane input catalog (EPIC) target objects, are scanned on a regular basis. In contrast to the previous works, we are using Virtual Observatory tools such as SKYBOT and MIRIADE


developed at the IMCCE to scan K-2 FOVs for passing asteroids. As soon as FOV crossing asteroids have been identified, they are checked in more detail with regard to whether they have actually been recorded in the imagettes of EPIC targets. As examples for such events, we present Figures 2-4 and 2-5. Those show the crossing of EPIC image boxes by the asteroid 484 Pittsburghia. The results of this query are directly fed into an image reduction pipeline providing photometric data on those frames which contain the crossing asteroid. From those frames light-curve data can be extracted, such as presented in Figure 2-5. The SKYBOT query that identifies potential targets in Kepler’s FOV was previously only valid for Earth-based observations. As the parallax between the Earth and the Kepler S/C become non-negligible over the mission’s lifetime, however, FOV crossing predictions for NEOs was to be rather inaccurate. This may lead to a loss of possible targets. An update of the SKYBOT service was necessary in order to be able to predict all FOV crossings of NEOs from the viewpoint of the Kepler spacecraft. This update of the SKYBOT service has been performed. The results are published in Berthier et al. (2016). The quality of the extracted asteroid light-curves for the long cadence data (exposure time of 30mins) were unfortunately too sparse to produce reliable period estimates themselves. In fact from 10 bright objects with known periods only 3 could be recovered ab initio, i.e. using Kepler data alone. Linking single measurements to already existing light curves is also difficult, since the absolute photometric calibration for Kepler SSOs is not an easy task. Hence, we shall explore algorithms that may allow for a better prediction of rotation periods from sparse data on the one hand, and we shall look into short cadence data (exposure time in the order of one minute). While there are fewer and only relatively bright targets in short cadence data, the quantity of photometric measurements should allow for a better period determination.

Figure 2-3: The FOVs of the K-2 mission campaigns C0-C3 are already public. SSOs that cross the FOV can happen to be recorded. Image credits: NASA.


Figure 2-4: Time series of K-2 Campaign 0 images of the target EPICID 202137697. The asteroid 484 Pittsburghia enters the field at the lower left corner and leaves it at the upper right corner. The cadence is 30 minutes. Photometry can be extracted when the asteroid is totally in the field of view.

Figure 2-5: Light-curve data extracted form images such as presented in Figure 3.4 for 484 Pittsburghia. The blue curve symbolizes the light-curve prediction based on the current shape model. The Grey dots represent the data extracted from K-2 image crossings (Berthier et al. 2016).


2.3 Precovery of NEOs and discovery apparition photometry (QUB)

Re-analysis of NEOs observed by Pan-STARRS identified from Physical Properties Priority Lists has been done.

Time for additional photometry with 2-m Liverpool Telescope has been allocated.


3 Spectroscopic observations (OBSPM-LESIA)

3.1 A literature study of the Potentially Hazardous Asteroid (PHA) population

On April 2015, we retrieved the European Asteroid Research Node (EARN)1 database of NEO physical properties, selecting those 255 PHAs with published taxonomic classifications. Combining the literature with our unpublished spectroscopic observations for further 7 PHAs, a total sample of 262 PHAs has been considered in our analysis. The full results have been published in Perna et al. (2016). Hereafter we summarize the main results.

We found that the taxonomic distribution of PHAs is similar to that of NEOs in general (i.e., dominated by the S/Q complex, though observational biases surely affect such distribution; Fig. 3-1). Given a number of uncertainties about their taxonomy and composition, we defined four “groupings” of objects: the “silicaceous” (types S, Q, A, and O – 184 objects in total), the “basaltic” (V-types – 12 objects), the “carbonaceous” (types B, C, D, P, T, and Xc – 40 objects in total), and the “miscellaneous” (types X, Xe, Xk, K, and L – 25 objects in total) PHAs. Then we analyzed the distribution of such groupings in terms of dynamical and physical properties (Tab. 3-1). The primitive, carbonaceous asteroids seem to pose a special danger to our planet: not only are the most mature techniques for deviating an asteroid from a hazardous orbit less efficient for such objects (e.g., Drube et al. 2015), but their low MOID and inclination values indicate that these PHAs will have close approaches with the Earth more frequently than those belonging to the other groupings. Based on their low albedo and Tisserand parameter with respect to Jupiter (we remind that Tj roughly distinguishes asteroids with typical Tj>3 from Jupiter-family comets, with typically 2<Tj<3), we also identified two candidate extinct cometary nuclei within the carbonaceous PHAs, which could present extremely low porosities: 2001 XP1 and 2002 BM26. The possible cometary origin of 2001 ME1 and (4015) Wilson–Harrington was already pointed out in previous works. The basaltic PHAs also deserve special attention, as the dynamical routes from Vesta to the near-Earth region seem to put them on orbits characterized by low MOID values and frequent close approaches with our planet, as also suggested by the latest findings about the lack of space weathering on the surfaces of V-type NEOs (Fulvio et al. 2016; Ieva et al. 2016). Because of their rapid rotations and elongated shapes, suggesting an important internal strength, additional objects that we identified as particularly hazardous are the silicaceous 2011 XA3, 2011 BT15, 1998 WB2, and 2002 NV16. The X-types (29075) 1950 DA and (367248) 2007 MK13 also deserve attention because of their possible metallic nature and extreme rotational properties (as well as the Xe-type (144898) 2004 VD17). Conversely, no fast rotators are found within the carbonaceous PHAs, suggesting low cohesions (Fig. 3-2).

Table 3-1: Orbital and physical parameters median values (Median Absolute Deviation in parentheses) for the four PHA compositional groupings defined in the text. From Perna et al. (2016).

1 http://earn.dlr.de

http://earn.dlr.de/


Figure 3-1: Distribution of PHAs within the different taxonomic classes. The color coding is relative to the grouping scheme introduced in the text (red for the “silicaceous” PHAs, magenta for the “basaltic” PHAs, black for the “carbonaceous” PHAs, green for the “miscellaneous” PHAs).

Figure 3-2: Distribution of PHA groupings in rotational period and light-curve amplitude. The rotational break-up limits for cohesionless bodies (e.g. Pravec & Harris 2000) are also reported for different densities.


3.2 Guaranteed Time Observations at ESO-NTT

As reported in [AD2], Guaranteed Time Observations (GTO) at the 3.6-meter ESO-NTT telescope are currently conducted by OBSPM-LESIA (programme “Characterizing the small near-Earth asteroid population in the framework of the NEOShield-2 EC project”, PI: D. Perna).

This GTO programme is mainly devoted to visible spectroscopic observations to derive the taxonomic type of the targets, hence some information on their surface composition. Our observing strategy is to prepare the target list for each run a few days before of the observations, in order to consider all of the small NEOs that are discovered near their close approaches with the Earth. We usually limit the observations to objects with absolute magnitude equal or fainter than H=20, which corresponds to a maximum diameter of 300 m assuming a value of 0.20 for the albedo. An exception has been the km-sized 2009 WN25, observed because of its low Tisserand parameter suggesting a cometary nature. Indeed, 2009 WN25 has been identified (Micheli et al. 2016) as the likely progenitor of the November i-Draconids, a recently detected weak annual meteoroid stream. The primitive nature of this body is confirmed by our spectroscopic observations (taxonomy: X/Xc/T type).

Up to present, 12 out of 30 nights have been carried out. The data acquired in April, June, July and November 2015 have been reduced and analysed (10 nights in total, though the observations in April 2015 have been strongly concerned by poor weather conditions, resulting in a very limited number of objects for which we could acquire useful data). The data acquired on 13-14 December 2015 for eleven additional small NEOs are currently under reduction. The next four runs of the GTO (3 nights for each run) are already scheduled for 29-31 March, 9-11 May, 28-30 June, 28-30 August 2016. The final 6 nights will be scheduled within the next months for execution in 2016-2017.

Figure 3-3 reports an example spectrum, obtained for 2009 FD. The taxonomic classification has been derived for 69 objects, which already almost double the available literature prior of NEOShield-2. Table 3-2 reports, for each object:

the type of the orbit (Aten/Apollo/Amor) if the object is a Potentially Hazardous Asteroid the necessary “change in velocity” Δv for a spacecraft rendezvous2 the Tisserand’s parameter with respect to Jupiter Tj3 the epoch of the observations the absolute magnitude H the derived taxonomic class

Figure 3-3: NTT spectrum of 2009 FD, one of the most hazardous NEOs currently known (0.29% impact probability in 2185-2196). Derived taxonomy: Xc-type.

2 http://echo.jpl.nasa.gov/~lance/delta_v/delta_v.rendezvous.html 3 http://echo.jpl.nasa.gov/~lance/tisserand/tisserand.html

http://echo.jpl.nasa.gov/~lance/delta_v/delta_v.rendezvous.html

http://echo.jpl.nasa.gov/~lance/tisserand/tisserand.html


Table 3-2: Preliminary results from the GTO programme at ESO-NTT telescope.

NEO Orbit PHA Delta-V Tj Run H Taxonomy 2001 HY7 AT y 8.961 6.453 April 2015 20.5 Q,R (noisy) 2014 TF17 AP n 13.547 3.747 April 2015 20.7 Q,Sq,Sr 2014 WP365 AM n 9.327 4.656 April 2015 20.3 Sq, Sr 2015 KU121 AP n 9.08 5.6 June 2015 22.9 Q, Sq 2015 JY1 AM y 6.3 3.55 June 2015 20.8 R 2013 BO73 AP n 6.18 4.82 June 2015 20.1 L, C 2011 AM24 AM y 5.02 5.34 June 2015 20.5 L ? 2015 HP43 AM n 7.77 3.41 June 2015 21.1 Q 2015 HB117 AM n 5.24 4.68 June 2015 23.6 R, Sa Asclepius AP y 7.03 5.91 June 2015 20.7 Cg 2011 OL5 AM n 6.7 5.18 June 2015 20.2 C 2007 RQ17 AP n 4.89 4.32 June 2015 22.6 A 2015 GF AM n 7.35 4.76 June 2015 20.7 Q 2010 LN14 AP n 7.45 5.33 June 2015 21.1 Q 2015 BY310 AP y 5.32 4.29 June 2015 21.7 Q 2001 XP88 AM n 5.15 4.85 June 2015 20.7 Xk, Q 2015 HA1 AT n 8.91 6.19 June 2015 21.2 C, D, L? 2015 FD134 AM n 6.77 3.33 June 2015 20.4 V 2011 KD11 AP n 7 4.24 June 2015 20.1 R 2003 KZ18 AT n 10.83 6.22 June 2015 21.2 Xc, C 2015 JJ2 AM n 6.42 3.51 June 2015 21.9 Xc 2014 YS34 AP y 5.37 4.35 June 2015 20.8 A, Sv 2009 XO AP n 6.27 3.81 June 2015 20.5 X, Xc 2015 LH AP n 5.61 3.79 June 2015 27.2 A 2004 EW AT n 6.73 6.1 June 2015 20.8 X, Xe, Xc 2015 KS121 AM n 8.86 4.06 June 2015 22.8 C 2000 YJ11 AM y 4.767 4.932 July 2015 20.8 S,Sv 2001 XP88 AM n 5.148 4.854 July 2015 20.7 Cb, Cgh 2002 RB AM n 6.979 3.53 July 2015 20.8 Cb, C, Cgh 2007 WU3 AP n 5.45 6.008 July 2015 23.8 Sq, Q 2008 JV19 AT y 6.477 6.113 July 2015 20.8 Ch (noisy) 2010 NY65 AT y 9.242 6.01 July 2015 21.5 Sv, S 2012 NP AM n 6.393 3.6 July 2015 21.3 A,Sa 2012 PG6 AT n 13.029 6.844 July 2015 20.3 X, Xc 2012 RS16 AM n 6.539 3.617 July 2015 21.2 Q,V (noisy) 2014 OE338 AP n 11.329 5.79 July 2015 21 Cb (noisy) 2014 QK362 AP n 8.788 5.687 July 2015 21.6 C-complex (noisy) 2015 AY245 AM y 6.361 5.516 July 2015 21.2 C-complex (noisy) 2015 HM10 AM n 6.364 3.174 July 2015 23.6 Xk,Xc,X 2015 JJ2 AM n 6.419 3.514 July 2015 21.9 D,T; 2015 LH14 AM n 6.863 3.43 July 2015 20.1 Xe 2015 LN21 AM n 6.362 3.581 July 2015 23 Sv, S 2015 LU24 AM n 8.399 3.94 July 2015 20.4 V,R,Sa 2015 MN44 AM n 5.974 3.993 July 2015 22.4 O,Q (noisy) 1993 HA AM n 5.302 5.043 November 2015 20.0 T, D; 2000 WN10 AP n 9.742 5.976 November 2015 20.2 Sv, S; 2001 RV17 AT n 7.913 6.467 November 2015 20.5 S, Sv; 2002 VV17 AT n 9.744 6.927 November 2015 20.2 Q 2005 UO5 AP n 7.921 5.361 November 2015 20.7 Q 2005 XT77 AT y 9.607 6.927 November 2015 20.9 Sq, K 2007 WQ3 AM n 7.379 4.76 November 2015 21.1 Sq, Sr


2009 FD AP n 7.661 5.291 November 2015 22.10 X, C, Xc, Cb 2009 WN25 AM n 21.018 1.968 November 2015 18.4 X, Xc, T 2012 TS AT n 7.744 6.081 November 2015 20.8 T,D 2015 JD1 AP n 7.497 5.166 November 2015 20.6 -- (Too noisy) 2015 QQ3 AM n 6.942 3.342 November 2015 21.3 Q 2015 RD37 AM n 6.709 3.892 November 2015 20 V 2015 RG36 AM n 5.597 4.54 November 2015 20.3 Sr, Sq, R 2015 TA AM n 8.404 4.757 November 2015 21.6 Q,V (noisy) 2015 TA25 AP n 11.727 5.092 November 2015 20.0 Sv;S 2015 TB179 AM n 7.342 3.192 November 2015 20.3 A,L 2015 TG238 AM n 8.369 3.588 November 2015 22.7 Q (noisy) 2015 TK238 AP n 6.497 3.237 November 2015 21.9 Q,Sq 2015 TL143 AM n 6.544 3.135 November 2015 23 Sv, S; 2015 TM143 AP n 5.675 5.471 November 2015 23.6 Cb 2015 TW144 AM n 6.189 3.951 November 2015 21 A,Sv 2015 TY144 AM n 6.712 3.531 November 2015 21.2 Sr,R,Sq 2015 TZ237 AM n 5.647 3.96 November 2015 24 Xk,Xc,X 2015 UC AM n 6.181 3.43 November 2015 24.5 Sr,Sq 2015 UJ51 AP n 8.012 3.149 November 2015 21.2 O,Q

As for the literature data, rather than analyzing each taxon separately, we define four major groupings to increase the significance of our analysis (also in terms of impact risk mitigation purposes): the “silicaceous” asteroids, including the whole S-complex together with objects classified as Q-, A-, or O-type; the “basaltic” V-type asteroids; the “carbonaceous” asteroids, consisting of NEOs belonging to the B, C, D, P, T, and Xc classes; the remaining “miscellaneous” asteroids, i.e. those classified in the X, Xe, Xk, K, and L taxa (such a grouping will therefore include objects of either silicaceous, carbonaceous, enstatitic, or metallic nature).

While it is still too early to draw firm conclusions from our observations and data analysis, we can note that, in comparison with the available literature for NEOs of all sizes (from EARN), our sample of “small” NEOs seem to include a higher fraction of carbonaceous objects, possibly because of their greater fragility (Fig. 3-4).

Figure 3-4: Distribution of NEOs based on their compositions, for small (10-300 m, left) and all sizes (right). The carbonaceous asteroids seem more abundant at small sizes.


3.3 Further ESO observations

Besides the preparation and execution of GTO runs, and the reduction and analysis of the obtained data, we have also submitted in October 2015 a proposal to ESO (PI: D. Perna) to use the (UV-to-NIR) X-Shooter and (visible) FORS2 spectrographs for studying asteroid Ryugu. This potentially hazardous asteroid is the target of the sample return mission Hayabusa 2 by JAXA, which will reach Ryugu in July 2018, and will return samples of its surface back to Earth in December 2020. The Hayabusa 2 project will represent a breakthrough in our understanding of the nature of primitive asteroid material, with obvious consequences for the mitigation of the impact risk from this kind of objects. However, the physical properties of Ryugu are still somewhat puzzling, and the July 2016 observing opportunity is the only left before mission arrival. Our proposal has been accepted, and we have been assigned 5 hours of X-Shooter observing time and 1 night of FORS2 observing time (both runs will be carried out in July 2016) for solving the current uncertainties about the surface composition and possible heterogeneity of Ryugu, as well as to secure the determination of its rotational period and to help assessing the orientation of its rotation axis. Such detailed characterization will be fundamental to optimize the Hayabusa 2 mission operations and scientific return.


4 Thermal IR observations (CNRS)

Sizes and albedos are within the most fundamental physical properties of asteroids. Although some NEAs have been observed by radar, the majority of NEA sizes and corresponding albedos have been derived from the analysis of thermal infrared (TIR) fluxes (Delbo’ et al. 2015, and references therein). Thermal inertia is another extremely important parameter, not only because it gives us information about the physical nature of the surface material, but because it also modulates the Yarkovsky effect, a non-gravitational force susceptible of affecting the orbital evolution of asteroids < 40 km (for a review, see Bottke et al. 2006).

Obtaining TIR data is especially complicated, since we require the largest ground-based telescopes on Earth, but after the decommissioning of CanariCam at the GranTeCan (La Palma, Spain), VISIR at the VLT stands as the only thermal infrared instrument currently available to Europeans. Although we have successfully gained access to using these facilities until recently (Licandro et al. 2016), our two last ESO proposals, submitted in collaboration with other members of WP10 in April 2015 and in October 2015, have not been successful. Thus, we have had to resort to the literature, namely to the WISE catalog, in search for TIR data from which we can expand our knowledge of the properties of some NEAs. In particular, we have used TPM to constrain the thermal inertia of two bodies, and we illustrate an approach that can potentially be used to constrain the thermal inertia of objects that do not have determined shape.

In the next section, we lay out some concepts relevant to our modeling techniques, in Section 4.2 we present our results and a brief discussion, and in Section 4.3 we summarize our conclusions.

4.1 Modeling techniques

4.1.1 Determination of sizes and albedos of NEAs from simple thermal models

To better explain the thermophysical model, it is convenient to introduce a less sophisticated thermal model first. The near-Earth Asteroid Thermal Model (NEATM, Harris 1998) has been widely applied to infer asteroid sizes from TIR data in cases in which information about the shape and rotational state of the asteroids are not known, i.e., the vast majority of them. The model assumes that the asteroid has a spherical shape and does not rotate. In this sense, the computed sizes are the diameters of the spheres that produce the best-fitting values of TIR fluxes. The other fundamental assumption of NEATM is that the surface is always in instantaneous equilibrium with the fraction of the incident solar radiation that it absorbs, which allows one to calculate the temperature of each illuminated surface element of the surface. The amount of energy absorbed by each surface element of the sphere depends on the object’s heliocentric distance and Bond albedo (the ratio of total absorbed to incident energy), and on each element’s inclination with respect to the sunward direction.

Typically, the NEATM allows a robust estimation of asteroid diameter, but does not provide any direct information about other physical properties of the material (see Harris & Lagerros 2002 for a review). Nonetheless, knowledge of the object’s H-value allows one to estimate its visible geometric albedo (pV) given its diameter. This provides a very coarse idea of composition, since low-pV objects are usually associated with spectrally classified C- and/or X-complex asteroids, thought to be primitive bodies, whereas higher-pV ones usually fall in the S-complex asteroids, whose spectra indicate they have undergone igneous processing.

A large fraction of the currently known sizes and albedos of NEAs have been estimated from the use of NEATM to model WISE/NEOWISE data (Mainzer et al. 2011). WISE stands for Wide-field Infrared Survey Explorer, a survey carried out in 2010 that provided photometric observations of more than 150,000 asteroids (Wright et al. 2010; Masiero et al. 2011), i.e., two orders of magnitude more than its predecessor, the Infrared Astronomical Satellite (IRAS), the major source of asteroid diameter and albedos for over two decades.


4.1.2 Thermal inertia

A very important parameter that is largely unknown for near asteroids but highly relevant for the NEOShield-2 objectives is thermal inertia. It is related to the nature of the material constituting the regolith and governs the surface temperature over a rotational period. Therefore, it controls non-gravitational Yarkovsky effect, the modeling of which is necessary to accurately determine NEA orbits. In turn, accurate orbits are essential to adequately assess impact risks, which one of the major goals of NEOShield-2. Furthermore, the nature of regolith is essential parameter if one wants to estimate the restitution coefficient after a kinetic impact.

To give an intuitive notion of thermal inertia, consider that the temperature of any material capable of efficiently conducting incident solar energy towards its interior will not respond quickly to changes in illumination. Unlike the instantaneous equilibrium case, the surface will remain colder for a longer time in the morning, and warmer in the night. Thermal inertia increases with the conductivity of the material, its density, and its specific heat capacity, and thus is related to the material’s composition as well as physical structure, for example, its porosity. In Figure 4-1 we show two paradigmatic examples of terrains with different thermal inertias. For a recent review, see Delbo et al. (2015).

This parameter has been traditionally estimated for asteroids by means of thermophysical models (TPMs), which we briefly introduce in the following section.

4.1.3 Thermophysical modelling of near-Earth Asteroids

Asteroid thermophysical models (TPMs) are computer numerical codes that allow one to calculate the temperature of asteroids’ surface and immediate sub-surface. These temperatures depend on absorption of sunlight, multiple scattering of reflected and thermally emitted photons, and heat conduction. Physical parameters such as albedo (or reflectivity), thermal conductivity, heat capacity, emissivity, density and roughness, along with the shape (e.g., elevation model) of the body, its orientation in space, and its previous thermal history are taken into account. From the synthetic surface temperatures, thermally emitted fluxes (typically in the medium-infrared) can be calculated. Physical properties are constrained by fitting model fluxes to observational data. Typically TPMs produce the value of the thermal inertia averaged over the whole surface of the body.

Figure 4-1. (A) Close-up image of (433) Eros from the NEAR Shoemaker mission reveals coarse regolith with grain size in the mm-range Γ~150 J m-2 s-0.5 K-1 for Eros. (B) Image from the Hayabusa mission of the surface of (25143) Itokawa displaying gravel-like regolith and a correspondingly higher thermal inertia of Γ~700 J m-2 s-0.5 K-1.


4.1.4 Asteroid 3D shapes as input for thermophysical models

The lightcurve inversion method developed by Kaasalainen et al. (2001) and Kaasalainen and Torppa (2001) is a powerful tool that allows us to derive basic physical properties of asteroids (the sidereal rotation period, spin vector orientation and its shape) from their disk-integrated photometry. This photometry can be dense-in-time, sparse-in-time or combination of both. These shape models are used as inputs for the TPM.

To obtain a unique spin and shape solution, one needs a set of at least a few tens of dense lightcurves observed during three or more apparitions for an asteroid: this is the first/classical approach. Kaasalainen (2004) showed that one can also use only sparse data for the inversion technique. In such case, a unique model can be derived from more than about one hundred calibrated measurements observed during 3–5 years if the photometric accuracy is better than 5% (Durech et al. 2005, 2007). Sparse data available so far are not that accurate. Nevertheless, for many asteroids with high lightcurve amplitudes, it is possible to derive their shape models from contemporary sparse data (covering usually time of ~15 years). First results coming from this approach were shown by Durech et al. (2009), where sparse data from the US Naval Observatory in Flagstaff (USNO-Flagstaff station) were used. If one combines sparse and dense data together, the shape model can be already derived from few dense lightcurves and about 100 sparse data points. This approach led to a significant increase of derived shape models from ~100 to ~400 (Hanus et al. 2011, 2013a, 2013b).

Kaasalainen et al. (2001) validated the lightcurve inversion method on asteroids (243) Ida, (433) Eros, and (951) Gaspra and demonstrated that convex shape models well represents the convex hulls of the real shapes. Experience shows that shape models derived from only sparse data are much coarser than those based on dense data, and should be refined by additional dense lightcurves prior applying them for thermophysical modeling, for example.

Most of the asteroid models are publicly available in the Database of Asteroid Models from Inversion Techniques (DAMIT, http://astro.troja.mff.cuni.cz/projects/asteroids3D, Durech et al. 2010). In March 2015, models of almost 400 asteroids were included in DAMIT, about a hundred based only on dense data.

More recently, Hanus et al. (2015) have examined for the first time how uncertainties associated with the pole and shape determination affect the best-fitting values of thermal inertia. Their approach is based on bootstrapping the visible data from which the shapes are obtained, i.e., they randomly remove a portion of the data used in each case and recomputed a new shape. In turn, the new shape is used in the TPM to recalculate new best-fitting value of thermal inertia. Doing this procedure several times, one can estimate an average value and a more realistic interval of uncertainty than in previous works.

Figure 4-2 (a) example of a triangulated 3D shape model as typically used in TPMs taken from Delbo’ et al. (2015). Temperatures are colour coded: white corresponds to the maximum and dark-grey corresponds to minimum temperature. Three different roughness models are sketched in the bottom of the figure: (b) hemispherical section craters; (c) Gaussian surface; (d) fractal surface. Adapted from Delbo et al. (2015).


4.1.5 Hybrid thermal model

The scarcity of both requisites for TPM, namely high-quality IR data and asteroid shapes and rotation states, is critically limiting our possibility to exploit WISE data with TPMs, as evidenced by the fact that only two works have been published so far (Alí-Lagoa et al. 2014, Rozitis et al. 2014).

Here, we also propose to combine the use of TPM with spherical shapes plus partial but potentially critical information about the rotational states of some objects. The idea is based on the notion that NEAs coming from the 6 secular resonance must be retrograde (Bottke et al. 2006). This makes a retrograde pole orientation for a sphere (i.e., any axis with a negative ecliptic latitude) a reasonable assumption. While this does not purely constitute a TPM, it is still an improvement over the near-Earth asteroid thermal model NEATM that may help constrain the thermal inertia and improve the size estimate. In addition, it has also been shown by Hanus et al. (2015) that, in some cases, changing the 3-D shapes within the uncertainties of the pole and shape determination increases the 2 of the best-fitting thermal inertia but does not change the best-fitting thermal inertia value itself. In these circumstances, ignorance of the shape may not be a limitation, but the feasibility of this approach still needs to be evaluated, which is our purpose here.

4.2 Results

4.2.1 TPM of (3200) Phaethon

We used combined newly acquired visible data to produce a 3D model of this object (Figure 4-3), with which we constrained its thermal inertia. The TIR data were collected from different works in the literature. In Figure 4-4 we show the reduced 2 of the fit versus different values of thermal inertia of the model (Hanus et al., in preparation). The large circle shows the minimum corresponding to the original shape, and the smaller circles those of the varied shapes, which inform about the uncertainty in the thermal inertia determination associated to the uncertainties in the 3D model.

Figure 4-3: shape model of (3200) Phaethon (Hanus et al., in preparation). Shape models that correspond to the first (top) and second (bottom) pole solutions derived from dense data only. Each panel shows the shape model at three different viewing geometries: the first two are equator-on views rotated by 90◦, the third one is a pole-on view.


4.2.2 TPM of (1685) Toro

We used a still unpublished shape model for this asteroid (Figure 4-5) and fitted its available WISE data. Preliminary analysis with TPM shows a minimum reduced 2 at a thermal inertia of 100−30

+40 SI units at the 1-sigma level (based on standard statistical analysis, Figure 4-6).

Figure 4-5: shape model of (1685) Toro (tri_model_02_1).

Figure 4-4: reduced 2 versus thermal inertia for (3200) Phaethon (Hanus et al., in preparation). The circles indicate the minima of the different models. The varied-shape models help quantify the uncertainty in the thermal inertia associated to the uncertainty in the shape and pole orientation.

Figure 4-6: Reduced 2 versus thermal inertia for NEA (1685) Toro


4.2.3 Hybrid thermal model of (1685) Toro

Dynamical models suggest Toro has >70% probability of having been delivered to NEA space through the 6 secular resonance. If this is the case, it should have a retrograde spin. To test this prediction, we applied TPM with a sphere to several prograde and retrograde spin orientations, changing both ecliptic latitude and longitude. TPMs have frequently helped constrain multiple solutions obtained from lightcurve inversion, and we find that this is the case for Toro and our hybrid thermal model. In Figure 4-7 we show the reduced 2 versus thermal inertia for three retrograde spheres, one with spin pole perpendicular to the ecliptic, one with the spin pole obtained from lightcurve inversion, one with the same ecliptic latitude but zero eclipctic longitude, and finally a prograde sphere rotating perpendicularly to the ecliptic. The fact that we obtain a maximum in 2 for a thermal inertia close to the TPM solution (see above) provides a strong basis to reject the prograde solution, as well as a good corroboration of the dynamical model’s prediction about the object’s spin axis orientation. The three other models give similar best-fitting values of thermal inertia at ~150 SI units, which are also consistent within the uncertainties with the value obtained from TPM.

4.2.4 Comparison with other thermal inertias found in the literature

Figure 4-8, adapted from Delbo’ et al. (2015), shows a plot of thermal inertia versus diameter for all objects with known thermal inertias. Different spectral types are indicated with different symbols. We have updated the figure to include our results. While the thermal inertia of (1685) Toro lies within the values spanned by other similarly-sized asteroids, (3200) Phaethon presents a higher thermal inertia. This may be an interesting clue about the different nature of the surface material on Phaethon, possibly containing very coarse-grained particles.

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Figure 4-7: Reduced 2 versus thermal inertia for NEA (1685) Toro using a sphere instead of a 3D shape. Three different retrograde spheres


4.3 Conclusions and Perspectives

We constrained the thermal inertia of NEAs (3200) Phaethon and (1685) Toro based on newly derived shapes obtained from light curve inversion and thermophysical modelling of WISE thermal infrared data. Our results for Toro are consistent with other asteroids with similar sizes, but the thermal inertia of Phaethon is high for its size, which may hint that the surface material on this object is. Motivated by the scarcity of available NEA shapes, we also proposed a strategy to constrain the thermal inertia of asteroids with known rotational periods for which no 3-D models are available by using a sphere. Our approach requires partial but potentially crucial knowledge of the object’s pole orientation, which is based on the fact that NEAs coming from the 6 secular resonance must be retrograde (Bottke et al. 2006). We explored this idea with (1685) Toro as a test case, which shows that prograde spheres cannot fit the thermal inertia (Figure 4-7) but retrograde spheres may succeed, albeit with some inaccuracy. In future work, we will survey the literature to find all NEAs for which this idea may be applied and discuss its feasibility further.

Figure 4-8: Thermal inertia versus diameter of all asteroids with estimated values. It is an update of Delbo’ et al. (2015) that includes our results for Phaethon (Hanus et al. in preparation) and Toro (this report).


5 Summary

While we are not yet at half of the NEOShield-2 project duration, within the WP10 activity we already acquired/analysed a good clump of data to characterize the small NEA population:

Eight observing runs have been carried out at TNG (6 runs) and LBT (2 runs) telescopes to acquire the photometric colors of a total of 64 targets. Data have been analysed for 30 of them, and the corresponding taxonomic type derived. A collaboration has been established with the Observatorio Nacional (Brazil) to make use of the OASI telescope, to acquire phase curves of NEAs. Five objects have been observed so far, with the data analysed and the corresponding absolute magnitude H derived for four of them.

Light-curves of 13 NEAs have been taken at OHP and PDM telescopes, where additional astrometric data have been also acquired for 12 asteroids (these data could help to enhance our understanding of the Yarkovsky effect). The light-curve and spectrum of 2004 BL86 have been also obtained at the IRTF telescope. Efforts are in progress to make use of the photometric data acquired by NASA’s Kepler space telescope to obtain further light-curves of asteroids and NEAs in particular.

Twelve out of the 30 observing nights of our GTO programme at the ESO-NTT telescope have been carried out: reflectance spectra of 80 small NEAs have been acquired. Data have been analysed for 69 of them, and the corresponding taxonomic type derived (suggesting that the primitive, carbonaceous objects are more common within the smaller NEA population). An analysis of the available literature of spectroscopic data of the PHA population has also been carried out, to identify those particularly hazardous objects requiring a special attention in the near future.

The thermal inertia of NEAs (3200) Phaethon and (1685) Toro has been constrained based on newly derived shape models and thermophysical modelling of WISE data. The results obtained for Phaeton suggest a very coarse-grained surface. A novel strategy is also proposed (and successfully tested on Toro) to constrain the thermal inertia of asteroids with retrograde rotations and no 3-D models, assuming a spherical shape (e.g., for objects coming from the 6 secular resonance).

In summary, NEOShield-2 new observations already more than doubled the available data for what concerns the surface composition (taxonomy) of small NEAs, and several objects of particular interest have been identified and/or studied. A number of observing runs are already foreseen for the next 1.5 years at several worldwide telescopes. Novel strategies are being developed by WP10 partners for the rotational and thermophysical modelling of extended samples of NEAs.