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

Oddities

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?