Diss defense

Stellar Variability:
A Broad and Narrow Perspective

Monnier et al. 2007

J. Robert Parks

Georgia State University

Advisor: Russel White

Committee: Peter Plavchan (IPAC) John Monnier (Umich) Fabien Baron Doug Gies Gary Hastings Hal McAlister

Credit: NASA/JPL-Caltech/T. Pyle

Here's hoping nobody gets beheaded during or after this talk...

Types of Stellar Variability

Era of High Precision Astronomy

Photometry to parts per million, RV to m/s

Complicates detection and characterization of exoplanets

Complicates determination of fundamental parameters of stars

Explores stellar interiors

Explores stellar environments

Dumusque et al. 2012

http://astro.phys.au.dk/KASC/seismology/measurements.html

www.crh.noaa.gov

The Broad

Long temporal baseline, daily cadence photometric survey of a group of coeval stars.

The Narrow

High spatial resolution of a starspots on a stellar surface.

Young stellar objects often found in chaotic environments

Many different variability mechanism can be working concurrently

Temporal behavior along with changes in stellar brightness and color point to variability mechanism

Photometric Monitoring of Young Stars

Isella (2006)

Ophiuchi

Well studied low mass star forming region

D ~ 125 pc, Age ~ 1 Myr

Observations2MASS Cal-PSWDB, 8 x 1 FOV

1678 star, 1582 obs. per star (JHKs)~ 8 million data points

B ~ 2.5 yrs, cadence of ~ 1 day

Heavy visual extinction (Av ~ 5 to 25 mag)

Cool Starspots

Magnetic in origin

Stellar photosphere

Stellar colors not correlated with single band variability

PeriodicP < 14 days (Rebull 2001)

Hot Starspots

Accretion shock or magnetic flare

Stellar photosphere

Star becomes bluer as star brightens

Periodic or aperiodicP < 14 days (Rebull 2001)

TS ~ days

Variable Extinction

Circumstellar environment or intra-cloud material

Inner disk (~1 3 AU) or beyond

Star becomes redder as star dims

Periodic or aperiodicP < 250 days

TS > 50 days

Variable Mass Accretion

Circumstellar disk heats via mass transfer

Inner Disk (~1 3 AU)

Star becomes bluer as star dims

AperiodicTS ~ days to years

Variability Mechanisms

Cool Starspots

Hot Starspots (Accretion)

Extinction

Accretion

7 point variability test

101 (6%) variable stars

72 known YSOs, 79% variableClass I: 92% (12 of 13)

Class II: 72% (34 of 47)

Class III: 92% (11 of 12)

22 new candidate members

Variable sub-categoriesPeriodicSinusoidal-like

Eclipse-like

Long time-scale

Irregular

25 stars

Periods: 0.49 to 25.55 days

Ks 0.06 to 1.64 mag, median 0.29 mag

3 Class I, 8 Class II, & 8 Class III

Dominant mechansim -> cool starspots

Sinusoidal-like Periodic Variables

6 stars; all Class II

Periods: 2.95 to 8.00 days


Dominant mechansim -> extinction

Eclipse-like Periodic Variables

31 stars


Time-scales: 64 to 790 days


Dominant mechansim -> extinction/accretion

Long Time-scale Variables

Irregular Variables

40 stars



Dominant mechansim -> extinction/accretion

ISO-Oph 126

Ps = 9.114 0.090 daysKs = 0.06 mag(H-Ks) = 0.10 magCool Starspots

TS = 349 daysKs = 0.1 mag(H-Ks) = 0.37 magExtinction

WL 15

Ps = 19.412 0.085 daysKs = 0.90 mag(H-Ks) = 0.40 magCool Starspots (?)

TS 47 daysKs ~ 1 mag(H-Ks) = 0.50 magExtinction

Ps = 5.7752 0.0085 days

Pe = 5.9514 0.0014 days

Phased to Sinusoidal Period

Phased to Eclipse-like Period

P ~ 4 hours

Distinct to 20 levelYLW 1C

Potential hot proto-Jupiter

AA Tau-like systems found in other surveys [citations]

Driven occultations over millions of dynamical timescales

Fundamental to understanding planet formation

Sinusoidal-like Variability: Cool Starspots

Eclipse-like Variability: Extinction from occulting body

Huelamo et al. 2008

Starspots are common

Inhibit determining stellar properties, finding planets

Effects can be better understood if starspots could bespatially resolved, and

temporally monitored

Transition Slide

Previous Starspot Studies

Light Curve Inversion

Doppler Imaging

Indirect methods

Rely heavily on initial assumptions

Direct method Long Baseline Interferometric Imaging!

Primer I: UV & Aperture Synthesis

van Cittert-Zernike

Primer II: Visibility and Closure Phase

Visibility Source Distributionranges from 0 to 1

Closure Phase Source AsymmetryRanges from -180 to 180

Asymmetry if non-zero or 180

Monnier 2003

Primer III: Effects of Starspots on Vis & CP

Starspots warp diffraction pattern

180 visibility ambiguity; CP necessary to resolve

Andromeda

G8 III-IV

SB1

= 38.74 0.68 mas

D ~ 25 pcvsini = 6.5 km/sPphot ~ 54 days

H = 1.501 mag V = 0.22 mag

~ 2.75 mas

Andromeda is a bright, large, essentially single star with high amplitude photometric variability attributed to starspots.

Fairborn Observatory

V 0.22 mag

Cool starspot driven variability with P ~ 54 days

11 years

Long Term Photometric Monitoring

6 x 1-m telescopes

Dense [u,v] coverage

MIRC combiner in H band8 spectral channels

2010 photometric channels

2011 6 telescope combination

~0.4 mas maximum resolution

27 epochs from 2007 to 2011

S1

S2

E1

E2

W2

W1

Outer Array, S1-E1-W1-W2

Inner Array, S2-E2-W1-W2

CHARA/MIRC

Periodic Photometric Observations

P1 = 26.978 0.032 daysP2 = 54.25 0.91 daysP3 = 55.0 1.1 daysP4 = 54.8 1.9 daysPavg = 54.5 2.4 days

2007

2008

2009

2010

Parametric Model

SQUEEZE Reconstruction

GA and AMOEBA minimization

Free parameters:Stellar angular diameter

Limb-darkening coefficient

Starspot size, latitude, longitude, and flux ratio

Baron et. al 2010

Monte-Carlo Markov Chain minimization

Minimizes flux gradients

Starspots

Artifact

Angular Resolution

2007 & 2008 Observing Strategy

Nov 17th, 2007

1 Inner Array snapshot

Aug 17th through 21st, 2008 &Sep 20th and Sep 27th,2008

1 to 3 Outer Array snapshots

[u,v] Coverage

48 to 144 points

Each Data Block

6 visibilities

4 closure phase & triple amplitudes

Inconclusive results based on limited [u,v] coverage

2007 & 2008 Data Sets

2009 & 2010 Observing Strategy

Aug 24th & Aug 25th, 2009

Bracketed obs. with Outer Array during night's first half

Bracketed obs. with Inner Array during night's second half

Combine both sets of data

Repeat on consecutive night

Combine nights together

Aug 2nd through Sep 10th, 2010

Same as 2009 except Sep 10th

[u,v] Coverage

624 to 1128 points (336 on Sep 10th)

Each Data Block

11 visibilities


Strategy provides nearly 8x improvement in [u,v] coverage and 2 additional closure phases

Indicates presence of starspots even at maximum brightness

2009 Data Set

ParameterModelRecon

14.1 4.13.6

b1-2.3 1.9-3.4

l1-13.4 5.3-26.8

Tr10.931 0.0240.922

22.2 2.22.0

b2-0.8 1.4-2.3

l222.9 2.021.1

Tr20.979 0.0100.924

2010 Data Set

2010 Light Curve

Points extracted from model images

Scaled to match level and amplitude of photometric light curve

2011 Observing Strategy

Sep 2nd & Sep 24th, 2011

Bracketed obs. with all 6 telescopes simultaneously

[u,v] Coverage

200 to 864 points

Each Data Block

11 visibilities


Reduction in [u,v] coverage, however gains 12 additional closure phases

2011 Data Set

2011 Light Curve

2010 Andromeda Rotation

Pspots = 60 13 days

Pphot = 54.8 1.9 days

2011 Andromeda Rotation

Pspots = 54.0 7.6 days

Pphot = 54.5 2.4 days

Still Don't Believe Me?

Andromeda Rotation Axis

2010

2011

=20 6.8i =78 1.5

=23 6.4i =77.98 0.18

Conducted a high cadence, long baseline variability of the molecular cloud Oph

Characterized the amplitude and timescales of variability

Discovered candidate Oph members

Discovered a number of stars with obvious evidence of multiple variability mechanisms

Summary of Results I

Established that cool spots can be resolved on stars besides the Sun.

Tentative evidence for motion of cool starspots across stellar disc.

Performed ~2.5 year variability survey with a cadence of ~1 day.

Identified 101 variables from 1678 target stars

Identified 32 periodic variable stars

Determined variability time-scales for 31 stars

Tentatively identified dominant variability mechanism for most variable stars

Summary of Results II

Acknowledgements

Bonus Slides

Plavchan-Parks Algorithm

Determination of Time-scales

Parameter Extraction from Reconstructions

Simulated Images for Artifact Identification

Ph.D. Dissertation Defense

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