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Photometric Monitoring of the Field Photometric Monitoring of the Field ofof
Open Star Cluster M23Open Star Cluster M23
Jeff WilkersonJeff WilkersonLuther CollegeLuther College
Iowa Academy of ScienceIowa Academy of Science
April 21, 2012April 21, 2012
Image M23 field every clear night every year and occasional other fields
Image durations: 2 to 12 seconds, unfiltered; use individually or summedFOV: ~1/2○ squareM23 campaign durations: Late February to early October>1600 stars appear consistently in M23 field
BVRI photometry occasionally for color correction to magnitude conversion and knowledge of variable star colors
Result: tens of thousands of images per field per year
Equipment: 12” Meade Schmidt-Cassegrain; Apogee AP6E or SBIG STL-1001E camera
What We Do
From http://rst.gsfc.nasa.gov/Sect20/sun_mw+.jpg
OUR DATA SETS
Cluster Dur. (s) # Nights Total Images
Date Range
NGC 6531 (M21) 3.5 21 30,000 26 June 2002 – 8 Sept 2002
NGC 6514 (M23) 3.5 25 45,000 19 June 2003 – 8 Sep. 2003
NGC 129 10.5 9 15,000 11 Aug. 2003 – 8 Sep. 2003
NGC 2682 (M67) 2.0 14 35,000 25 Feb. 2004 – 26 April 2004
NGC 6694 (M26) 9.0 20 28,000 24 June 2004 – 9 Sep. 2004
NGC 6514 (M23) 2.5 20 45,000 23 June 2005 – 30 Aug. 2005
NGC 2286 7.5 22 28,000 24 Jan. 2006 – 10 April 2006
NGC 6514 (M23) 5.0 37 49,000 28 Mar. 2006 – 25 Sep. 2006
NGC 7380 10.0 40 44,000 12 Jul. 2006 – 9 Jan. 2007
NGC 2286 7.5 29 44,000 31 Oct. 2006 – 5 Apr. 2007
NGC 6514 (M23) 2.8 49 91,000 9 Mar. 2007 – 27 Sep. 2007
NGC 7380 10.0 42 48,000 5 Jul. 2007 – 14 Jan. 2008
NGC 2286 5.0 35 65,000 3 Oct. 2007 – 12 Apr. 2008
NGC 6514 (M23) 3.5 53 82,000 3 Mar. 2008 – 16 Sep. 2008
NGC 6514 (M23) 3.5 45 50,000 11 Mar. 2009 – 17 Sep. 2009
NGC 6514 (M23) 3.5 63 59,000 27 Feb. 2010 – 8 Oct. 2010
NGC 6514 (M23) 3.5 57 46,000 1 Mar. 2011 – 11 Oct. 2011
NGC 6514 (M23) 7.0 ? ? 11 Feb. 2012 – present
Because we can!
Why Do We Do This?
http://www.hawaiimagazine.com/images/content/Mauna_Kea_wins_biggest_telescope/thirtymetertelescope.jpg
Sensitive to Variability on a Wide Range of Timescales:
I. Tenths of seconds to seconds Occultation and microlensing events Brief flares
II. Tenths of hours to a few days Flares in long period variables Delta Scuti stars Traditional flare stars Eclipsing binaries Transiting planets
III. Days to hundreds of days Long period pulsating variable stars Eclipsing binary stars Cataclysmic variable stars Cepheid variables Period-to-period variability in long
period variables Rotating variable stars in young clusters
IV. Years to decades Luminosity stability Solar-like cycles Period-to-period variability in long
period variables
Student Participation:
Ujjwal Joshi
Nathan Rengstorf
Andrea SchiefelbeinTodd BrownBrajesh Lacoul
Kari Frank
Alex Nugent
Drew Doescher
Alex Sperry
Jennifer Schulz
Clara Olson
Robyn Siedschlag
Siri Thompson
Matt Fitzgerald
Heather Lehmann
Amalia Anderson
Hilary Teslow
Steve Dignan
Kirsten Strandjord
Donald Lee-Brown
Andrew Becklin
Zebadiah HowesBuena Vista Univ.
Travis DeJongDordt College
Forrest BishopDecorah High School
Support: Roy J. Carver Charitable Trust (Grant #00-50)Luther CollegeR.J. McElroy Trust/Iowa College FoundationAmerican Astronomical Society
DATA PROCESSING1. CALIBRATION
• Dark Noise Correction
• Flat Fielding
2. ALIGNMENT
• Use a single frame for entire data set
3. STAR ID & EXTRACTION
• Aperture photometry for signal determination
• 256 Background regions
4. INTRA-NIGHT NORMALIZATION
5. INTER-NIGHT NORMALIZATION
6. MAGNITUDE CONVERSION
Frame Normalization
1. Identify four reference images from throughout the night
2. Calculate average flux for each star in all four frames – this is the reference signal
3. Determine the signal of each star in the frame to be normalized – this is the sample signal
4. Calculate (ref. signal/sample signal) for each star
5. Normalization factor = median of all ratios in (4)
Define Short-term Photometric Resolution (STPR) as for a Gaussian fit to a histogram of several hundred signal measurements for a given star and Long-term Photometric Resolution (LTPR) as for the nightly average signal measure of a given star over an entire campaign.
0.01
0.1
100 1000 104
105
M23 Data
Stellar Signal (ADU)
At large signal values STPR approaches a constant (plateau) value determined by our frame normalization, itself limited by scintillation. For faint stars STPR increases as signal-1. In between STPR increases as signal-
1/2. Counting statistics of the stellar signal measurement dominate STPR in this region.
Functional fits shown of form: STPR=[(C1)² + (C2signal-1/2)² + (C3signal)2]1/2
0.01
0.1
1
100 1000 104
105
106
107
LTPR vs Mean Stellar Signal (M23)
Mean Signal (ADU)
0
2
4
6
8
10
12
14
16
0 0.05 0.1 0.15
M23 Summer 2011
Standard deviation of nightly signal over mean signal
-1.5
-1
-0.5
0
0.5
0 0.5 1 1.5 2 2.5
Magnitude Error Vs. Color Index
Catalogued B-V Color Index
0
2
4
6
8
10
12
-0.5 -0.4 -0.3 -0.2 -0.1 0 0.1 0.2 0.3
V Error After Color Correction
V Error (mag)
Standard deviation of fit = 0.08 mag
Use Web Version of the BDA catalog for magnitudes (Mermilliod and Paunzen , http://www.univie.ac.at/webda//). Find an empirical color equation for the system and apply it.
The Shortest (I) and Longest (IV) Timescales:
200
250
300
350
400
450
500
0 0.5 1 1.5 2
Test of Hot Pixels
Time (Hrs)
1
1.1
1.2
1.3
1.4
1.5
1.6
1.7
1.8
0 1 2 3 4 5 6 7 8
M23 -3.4 to -4.5 sigma fluctuations
ratio
of o
bser
ved t
o exp
ected
even
ts
flux resolution (%)
13.5
14
14.5
15
15.50 500 1000 1500 2000 2500 3000 3500
Star 2136
ma
gn
itud
e
CJD-2452800
Short (II) Timescales: (tenths of hours to a few days)
Primarily two types of objects here:
(a)Flare stars
(a)Eclipsing binaries
From Contemporary Activities in Astronomy, by Hoff and Wilkerson
14
14.1
14.2
14.3
14.4
14.52450 2500 2550 2600 2650 2700
Star 723 Summer 2010 Lightcurve
ma
gn
itud
e
CJD-2452800
12.8
12.9
13
13.1
13.2
13.3
13.4
13.50 50 100 150 200 250 300
Star 924 Lightcurve May24, 2010
ma
gn
itud
e
Time (minutes)
How do we find these? WSVI-statistic test
1. Fit a second-order polynomial to flux as a function of normalization factor
2. Define the WSVI* statistic to measure the deviation of a star’s flux from the polynomial fit using paired observations
3. Find the mean WSVI for a subset of stars
4. Measure each star’s WSVI deviation from the mean of its subset
* Based on a variability index developed by Welch and Stetson (AJ, 105, 1993)
0.92
0.94
0.96
0.98
1
1.02
1.04
1.06
1.08
0 20 40 60 80 100 120 140
NGC 129 August 26, 2003
Image Number
95000
100000
105000
110000
115000
120000
125000
0.92 0.94 0.96 0.98 1 1.02 1.04 1.06 1.08
NGC 129 Star 35 8/26/03
Normalization Factor
Eclipsing Binaries
Period = 0.32866 days Period = 0.54550 days Period = 0.20730 days
10.15
10.2
10.25
10.3
10.35
10.40 0.5 1 1.5 2 2.5 3 3.5 4
Star 16 July 5, 2007
ma
gn
itu
de
Time After Start (Hrs)
Period = 5.5 days Period = 0.91475 days
15.3
15.4
15.5
15.6
15.7
15.8
15.9
16
16.10 50 100 150 200 250 300
Star 1267 Lightcurve June 1, 2006
ma
gn
itud
e
Time (minutes)
Period Analysis
-0.1
0
0.1
0.2
0.3
0.4
0 200 400 600 800
Star 1267, P = 0.94131341 d; 2009 through 2011
y = -0.030939 + 0.00043604x R= 0.98371
O-C
(da
ys)
Minimum
-0.08
-0.06
-0.04
-0.02
0
0.02
0.04
0.06
0.08
0 200 400 600 800
Star 1267, P = 0.94174945 d; 2009 through 2011
O-C
(d
ays
)
Minimum
All 4 of our short-period EBs show O-C variations consistent with cyclic.
Kim et al. found that ~50% of EBs in the Mt. Suhora catalog show detectable variation in the their O-C diagrams; half of those were cyclic variations1,5.
Could be light-time effect from the orbit of a third body. Only expect ~10-20% of systems to be triple2,4 but might expect much greater for short-period EBs since Kozai cycle is only known way to produce them3,4. Our apparent periods are short relative to most previously observed5.
1. Kim, C.-H., et al. 2003, in Stellar Astrophysics – a Tribute to Helmut A. Abt, Cheng, K.S., et al. (eds.), Kluwer Academic Publishers, 127-130.
2. Abt, H.A. 1983, Ann Rev A&A, 21, 343.3. Kozai, Y. 1962, AJ, 67, 591.4. Eggleton, P.P. and Kisseleva-Eggleton, L. 2006, Astrophys
Space Sci, 304, 73.5. Kreiner, J. M., et al. 2001, An Atlas of O-C Diagrams of
Eclipsing Binary Stars, Parts 1-6, Cracow: Pedagogical University Press.
To get F-Stat: Take ratio of consecutive night variance to full data set variance. Histogram these values in 100 star chunks; fit a Gaussian measure each star’s deviation from the mean in standard deviations.
F-Stat – Standard deviations from mean of set
F-Stat > 5.5
50 stars with standard deviations greater than 5.5
Long (IV) Timescales: An F-statistic test
Pulsating Variables in the M23 Field
Properties:
Period: DCDFTColor: R-IAmplitude: 4-96%Asymmetry: Risetime/PeriodMean Magnitude: (96+4)/2
15
16
17
18
19
200 500 1000 1500 2000 2500 3000
Star 1654
ma
gn
itud
e
MJD-2452800
15
16
17
18
19
200 0.2 0.4 0.6 0.8 1
Star 1654
20032005200620072008200920102011
mag
nitu
de
MJD/154.29 - X
Populations of Pulsating Stars
11
11.2
11.4
11.6
11.8
12
12.20 0.2 0.4 0.6 0.8 1
Star 82 Phase Diagram; 1 = 24.2
ma
gn
itud
e
MJD/118.03-X
0
1
2
3
4
5
6
7
8
0 20 40 60 80 100
Power Spectrum Lead Term Amplitude Histogram
# s
tars
DCDFT Theta One
13
13.5
14
14.5
15
15.5
16
16.50 0.2 0.4 0.6 0.8 1
Star 356 Phase Diagram; 1 = 96.3
ma
gn
itud
e
MJD/321.42 - X
14.5
14.6
14.7
14.8
14.9
15
15.1
15.2
15.30 0.2 0.4 0.6 0.8 1
Star 981 Phase Diagram; 1 = 42.3
mag
nitu
de
MJD/193.32 - X
Populations of Pulsating StarsWe see many more lower A stars than higher A stars.
Recognize that detection efficiency is lower for lower A stars as well.
Fit a power lower; extrapolate to threshold; use scatter to determine detection efficiency as a function of both magnitude and amplitude.
Estimate the percentage of stars with A>0.22 mag. and P>10 days as : 5.2±2.1%. With cluster members removed the number is: 10.4±4.2%.
0
0.2
0.4
0.6
0.8
1
0.1 0.2 0.3 0.4 0.5
Variability Detection Efficiency Vs. Amplitude
Det
ect
ion
Eff
icie
ncy
Amplitude
15.5
<m
<17
.0
14.7
<m
<15
.5
13.8
5<m
<14
.7
m<
13.8
5
1
10
100
1000
0.1 1 10
f-stat Vs. Amplitude: 13.85<m<14.70
y = 67.173 * x (̂1.644) R= 0.9558
f-st
at
4-96 Amplitude (mag.)
0
50
100
150
200
250
0 0.5 1 1.5 2 2.5 3
Calculated Number of Variables per Magnitude of Amplitude
# V
aria
ble
s/m
ag
.
Amplitude
0
2
4
6
8
10
12
0 0.5 1 1.5 2 2.5 3
Histogram of measured amplitudes
# s
tars
Amplitude
Populations of Pulsating Stars
10
100
0.1 1
PS Lead Term Amplitude Vs. Varaibility Amplitude
y = 70.573 * x^(0.24606) R= 0.4897
y = 84.718 * x^(0.99436) R= 0.52016
DC
DF
T T
he
ta O
ne
Amplitude (mag)
0
0.5
1
1.5
2
2.5
3
0 1 2 3 4 5 6 7
Amplitude vs. Color
Am
plit
ude
R-I
0
0.5
1
1.5
2
2.5
3
0 100 200 300 400 500
Amplitude Vs. Best Period
Am
plitu
de
Period (days)
0
0.5
1
1.5
2
2.5
3
0 100 200 300 400 500
Amplitude Vs. Period
Am
plitu
de
Period (days)
Interesting Stars: The Yellow Stars
A likely Cepheid variable
A likely RV Tau variable
12.5
13
13.5
14
14.5
15
15.5
160 0.2 0.4 0.6 0.8 1
Star 338 Phase Diagram
ma
gn
itud
e
MJD-2452800/77.9
13.3
13.4
13.5
13.6
13.7
13.8
13.9
140 0.2 0.4 0.6 0.8 1
Star 357 Phase Diagram
ma
gn
itud
e
MJD/14.898-X
Interesting Stars: Plateau Stars12.5
13
13.5
14
14.5
150 0.2 0.4 0.6 0.8 1
Star 317 Phase Diagram
ma
gn
itud
e
MJD/367.64 - X
13
13.5
14
14.5
15
15.5
160 0.2 0.4 0.6 0.8 1
Star 1223 Phase Diagram
ma
gn
itud
e
MJD/389.61 - X
13.5
14
14.5
15
15.5
160 0.2 0.4 0.6 0.8 1
Star 1495 Phase Diagram
ma
gn
itud
e
MJD/394.73 - X
15
16
17
18
19
202500 2600 2700 2800 2900 3000
Star 1654 Lightcurve
ma
gn
itud
e
MJD-2452800
Interesting Stars: SAS Stars14.6
14.8
15
15.2
15.4
15.6
15.8
16
16.20 500 1000 1500 2000 2500 3000
Star 1007 Lightcurvem
ag
nitud
e
MJD-2452800
11
11.2
11.4
11.6
11.8
12
12.20 500 1000 1500 2000 2500 3000
Star 82 Lightcurve
ma
gn
itud
e
MJD-2452800
8
10
12
14
16
-1 0 1 2 3 4 5 6 7
M23 Color-Magnitude Diagram
Non-VariableHA Pulsating StarsLA Pulsating StarsEclipsing Binaries
I
R-I
CONCLUSION
We have a unique data set that offer unprecedented temporal coverage of >1600 stars down to 19th magnitude.
Estimate ≥ or ≈ 10% of field stars in the direction of the center of the Galaxy are variable, probably largely from the galactic bulge.
Strong evidence of two classes of stars (high and low amplitude) with different pulsation behavior
A few interesting individual stars might help us understand these systems better.
Groups of stars with interesting behavior can lead to a better understanding of how these systems work as stability of pulsations over years or decades.
Eclipsing binaries appear to have shorter period cyclic behavior than typical –
a clue to their formation?
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