rocket / iou-na optics research workshop 2015 ”workshop 1” : excel spreadsheets and data...
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ROCKET / IOU-NAOptics Research Workshop 2015
”Workshop 1” : Excel Spreadsheets and Data Analysis
Dr. Mike Nofziger
Professor
College of Optical Sciences
University of Arizona
Dr. Mike Nofziger 2015Workshop 1-1
Optics Research Workshop (ORW) Curriculum
“These Optics Research Workshops are designed to teach participants basic opto-electronic laboratory techniques, through hands-on measurements and experiments with:
• data analysis• electronics• lasers• laser beam alignment• spectroscopy• optical detectors (solar cells)
Topics and hardware have been chosen to provide a background to common lab practices that participants will (likely) see and use during their summer research experiences!
Emphasis will be placed on the practical vs. theoretical aspects of lab practices and techniques. Whenever possible, we will stress applications of hardware to real-world laboratory situations.” In the process, participants will gain hands-on experience with some of the basic and most useful lab techniques most important in an optics lab.
Dr. Mike Nofziger 2015Workshop 1-2
OPTICS IS…
OPTICS IS…BIG
The UofA Steward Observatory Mirror Lab casts mirrors up to 8.5 meters in diameter.
OPTICS IS…SMALL
Micro-lenses are now made with diameters as small as ≈ 10 μm. Arrays of micro-lenses are used on the CCD sensors of many digital cameras.
OPTICS IS…HOT
National Ignition Facility at Lawrence Livermore will
deposit 1.8MJ in 2 nanosec onto a 2 mm diameter tritium target,
heating it to 100,000,000K
OPTICS IS…COOL
Laser cooling and trapping at OSC can
capture and slow down individual atoms until
their effective temperature is <1 μK.
OPTICS IS…FAST
A 9 micron fiber can carry data at a rate of 10 Gbit/sec. Using dense wavelength-division multiplexing (DWDM, 16 wavelengths), 2,000,000
simultaneous phone conversations can be transmitted
through a single fiber.
OPTICS IS…SLOW
Using a new process, it now takes “only” 27 days to grow KDP crystals to this size for frequency
multiplication (It used to take 1 year!)
OPTICS IS…NEAR
Scanning tunneling microscopy (STM) at OSC
can resolve individual molucules (like these three
C-60 “buckyballs”).
OPTICS IS…FAR
UofA NICMOS on Hubble Space Telescope found
this galaxy 12 billion light years distant. OSC contributions to HST
include discovery of the original out-of-focus
problems.
OPTICS IS…NIGHT
A Gen III image intensifier can produce a useful
image under starlight. You can see a 6’ tall man at a
distance of 580 yards.
OPTICS IS…DAY
The sulfur lamp, the size of a golf ball, produces nearly 100 times as much light as a conventional HID lamp,
nearly 1000 times as much as a 40 watt tungsten
lamp.
OPTICS IS…NEW
LED’s are now available in three primary colors (great
for displays) and in white for illumination.
A violet laser diode (406nm) is a recent introduction;
expect smaller spot sizes and denser data storage.
OPTICS IS…OLD
In 1609, Galileo built a telescope based on an
earlier design and used it to discover four of Jupiter’s
moons.
▪ Communications▪ Medical Equipment/Procedures and Life Sciences ▪ Computers and Data Storage ▪ Military ▪ Telescopes and Satellites ▪ Cameras and Image Capture Devices ▪ Custom Illumination ▪ Industrial Manufacturing ▪ Metrology ▪ Nanotechnology and MEMS ▪ Research and Education
… EVERYWHERE!!!
OPTICS IS…
“The Nature of Light” Quantum Mechanics Physical Optics Geometrical Optics
EXAMPLE: Young’s Double Slit
Dr. Mike Nofziger 2015Workshop 1-17
Light is energy, transported from one locationto another via electromagnetic (EM) waves…
… or photons?!
Dr. Mike Nofziger 2015Workshop 1-18
Characteristics of an EM wave:
• EM waves are transverse waves (the electric field oscillates in a plane perpendicular to the direction of
travel).
• speed c (speed of light in vacuum, universally-accepted symbol)• frequency ν “nu”• wavelength λ “lambda”• amplitude• polarization• phase
Dr. Mike Nofziger 2015Workshop 1-19
EM wave—Speed, Frequency, and Wavelength
c = ν λ
Electromagnetic Spectrum
81 0 71 0 61 0 51 0 41 0 31 0 21 0 1 0 11 0 - 21 0 - 31 0 - 41 0 - 51 0 - 61 0 - 71 0 - 81 0 - 91 0 - 101 0 - 1 11 0 - 121 0 - 1 31 0 - 141 0 - 151 0 - 1 61 0 -1
700 600 500 400
W a v e le n g th ( in n a n o m e te r s )
V is ib l e s p e c tru m
W a v e le n g th (m )
F req u e n c y (H z )
1 0 21 0 31 0 41 0 51 0 61 0 71 0 810 91 0 1010 111 0 121 0 131 0141 0 151 0 161 0 1710 1810 191 0 201 0 211 0 221 0 231 0 2410
R a d io w a v e s X ra y s G a m m a ra y s
c = 299,792,458 m/sec. in vacuumc ≈ 300,000,000 m/sec. = 3x108 m/sc ≈ 186,000 miles/s
Dr. Mike Nofziger 2015Workshop 1-20
► NYC to LA ≈ 1/62 sec. (62 trips in one second!!)► sun-to-earth ≈ 8 min.► Earth-to-Mars = 9-16 min. (depending on where Mars is)► Proxima Centauri-to-earth = 4.3 years
(Proxima Centauri is the closest star to our own sun, 4.3 light-years away)► A light-year is defined as the distance light travels (in the vacuum of outer space)
in one year:
EM wave—Speed of Light in vacuum (or ≈ in air)
Hubble eXtreme Deep Field (XDF) image shows:
▪ galaxies 13.2 billion light years distant
(galaxies that are 13.2 billion years old)
Dr. Mike Nofziger 2015Workshop 1-21
EM wave—Speed of Light in glass
► Light traveling through a media like glass has a slower velocity than in air. The frequency is the same (constant) but the velocity is slower.
► vm < c
► n ≡ c/vm ; vm = c/n
where n ≡ Refractive Index and c = speed of light in air
► n ≥ 1 for any material; n = 1.5 for a typical type of optical glass
Dr. Mike Nofziger 2015Workshop 1-22
• water 1.33333• glass 1.46 to 1.76 (typically 1.5 is used)• plastic 1.4• air 1.0• Oil 1.6• Diamond 2.42• Germanium 4• Silicon 3.4
Refractive Index of Different Materials
► A graph of refractive index vs. wavelengthis called a dispersion curve:
Dr. Mike Nofziger 2015Workshop 1-23
Basics of Data Analysis:
● Mean (average) of a sample population Sample Mean
Example: (1,2,3,4,5,6,7,8,9,10)
1 2 3
1
...
1
N
N
ii
x x x xx
N
x xN
1 2 3 4 5 6 7 8 9 10 555.5
10 10x
Dr. Mike Nofziger 2015Workshop 1-24
Basics of Data Analysis: In Excel
● Sample Mean
=(A1+A2+A3+A4+A5+A6+A7+A8+A9+A10)/10
=SUM(A1:A10)/COUNT(A1:A10)
=AVERAGE(A1:A10)
A B1 12 23 34 45 56 67 78 89 9
10 1011 Average = 5.512 Average = 5.513 Average = 5.5
Dr. Mike Nofziger 2015Workshop 1-25
Basics of Data Analysis:
● Sample Variance
Example: (1,2,3,4,5,6,7,8,9,10)
(1)
(2)
1 2 3 4 5 6 7 8 9 10 555.5
10 10x
22
1
1
1
N
ii
x xN
2 2 2 2 2
2
2 2 2 2 2 2
1 5.5 2 5.5 3 5.5 4 5.5 5 5.51
10 1 6 5.5 7 5.5 8 5.5 9 5.5 10 5.5 1 5.5
2 9.167
Dr. Mike Nofziger 2015Workshop 1-26
Basics of Data Analysis:
● Sample Standard Deviation
Example: (1,2,3,4,5,6,7,8,9,10)
(1)
(2)
(3)
1 2 3 4 5 6 7 8 9 10 555.5
10 10x
2
1
1
1
N
ii
x xN
2 2 2 2 2
2
2 2 2 2 2 2
1 5.5 2 5.5 3 5.5 4 5.5 5 5.51
10 1 6 5.5 7 5.5 8 5.5 9 5.5 10 5.5 1 5.5
2 9.167 3.028
Dr. Mike Nofziger 2015Workshop 1-27
Plotting Data: In Excel
● Linear-Linear
(1) 0 ; " "y mx b x y x
0 10 20 30 40 50 60 70 80 90 1000
102030405060708090
100
y = x
x
y
0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 20
0.20.40.60.8
11.21.41.61.8
2f(x) = xR² = 1
log(y) vs. log(x)
log (x)
log (y)
● Log-Log 10 10log logy x
Dr. Mike Nofziger 2015Workshop 1-28
Plotting Data: In Excel
● Linear-Linear 2y x
0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 20
0.5
1
1.5
2
2.5
3
3.5
4f(x) = 2 xR² = 1
log (y) vs. log (x)
log (x)
log (y)
● Log-Log
0 10 20 30 40 50 60 70 80 90 1000
100020003000400050006000700080009000
10000
y = x2
x
y log 2logy x
Dr. Mike Nofziger 2015Workshop 1-29
Plotting Data: In Excel
● Linear-Linear 3y x
0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 20
1
2
3
4
5
6f(x) = 3 xR² = 1
log (y) vs. log (x)
log (x)
log (y)
● Log-Log
0 10 20 30 40 50 60 70 80 90 1000
100000200000300000400000500000600000700000800000900000
1000000
y = x3
x
y log 3logy x
Dr. Mike Nofziger 2015Workshop 1-30
Plotting Data: In Excel
● Linear-Linear 2 3and andy x y x y x
0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 20
1
2
3
4
5
6
log (y) vs. log (x)
log (x)
log (y)
0 10 20 30 40 50 60 70 80 90 1000
100000
200000300000
400000500000
600000
700000800000
9000001000000
y = x
x
y
Dr. Mike Nofziger 2015Workshop 1-31
Computer Exercises: In Excel
● Michelson’s “Speed of Light” Data Set (measured values of “c”)- Find the mean, variance, and standard deviation of his values- Plot histograms of his data- Plot a “best-fit” Gaussian distribution
=NORMDIST(x, mean, standard dev, FALSE)
Dr. Mike Nofziger 2015Workshop 1-32