Near Infrared Monitoring of Ultra Cool Dwarfs: Transiting Companions

1. Near Infrared Monitoring of Ultra Cool Dwarfs: Transiting Companions May 16, 2006 Cullen Blake

2. Outline • Planets around Ultra Cool Dwarfs (UCDs) • Near Infrared (NIR) Photometry • Transit detection • Conclusions

3. Ultra Cool Dwarfs • Small stars and brown dwarfs, M, L, T spectral types • Roughly spectral types from M7 and later • Some Ms are BDs, some Ls are not BDs • Masses from 13MJ to ~100 MJ • Cool temperatures of <1000K to 2500K • Partially degenerate EOS leads to size similar to Jupiter • Complex atmospheres with molecules, precipitates (dust) • Few thousand known from multi-color surveys like 2MASS, DENIS, SDSS

4. Luminosity-age relation from Burrows (2001) Gold dots are deuterium burning, Magenta dots are lithium burning. Red lines are giant planets, green lines are UCDs, blue lines are small stars

5. Radius-age relation from Burrows (2001)

6. Transit Searches • Currently 9 (maybe 10?) known transiting planets • Allow for direct investigation of properties of planets • Requires monitoring many, many stars • Transits are relatively improbable • Many stars are giants, main-sequence is preferable • Requires high photometric accuracy • Control of non-Gaussian noise • Extensive phase coverage • Most sensitive to giant, short-period planets

7. Mass-Radius Relation Charbonneau et al. (2006)

8. IR Detection Charbonneau et al. (2005)

9. Transmission Spectroscopy Charbonneau et al. (2002)

10. Small Star = Big Transit • With good photometric accuracy: • Small, terrestrial planets in short-period orbits can be found • Earth=0.008 mag • Neptune=0.12 mag • Cooler host mean “habitable zone” at very small separation • Transits of small stars may be the only viable method for finding Earth-like planets in habitable zone • Microlensing is possible exception • Improved brightness ratio makes planets susceptible to imaging

11. Do UCDs Have Planets? • Distant companions unlikely to be found through transits: • Smaller, close-in companions to early-M dwarfs do exist: • GJ 876: M4, 0.02MJ, P=1.9d • GJ 436: M2.5, 0.07MJ, P=2.6d • GJ 531: M3, 0.6 MJ, P=5.4d • Does a similar population exist for smaller, cooler hosts? • Is there a “hot Jupiter” type population • A transit search is sensitive to these types of companions

12. Do UCDs Have Planets? • RV studies suggest early-M dwarfs have few giant planets • Statistics not well known • Little known about small companions to smaller stars • Chauvin discovered a ~5MJ companion at 55 AU from a young UCD Chauvin et al. (2004)

13. Do UCDs Have Planets? • Young UCDs definitely have disks • Disk fraction seems to be comparable to larger stars (Luhman 2005b) • Process of dust formation/settling taking place • At least early stages of planet formation ongoing • Core accretion predicts few giant planets around small stars • Disk instability predicts giant companions to small stars • Some theoretical motivation for expecting planetary companions

14. Do UCDs Have Planets? • Ida and Lin (2005) simulate statistics for stars of 200MJ • Very few gas giant companions • A population of close-in Neptune-mass companions • 2-15ME planets at a<0.05AU • Planets as small as 2ME can undergo Type II migration • Can companions exist so far inward of the assumed 0.04AU “stall”? • Very Hot Jupiters extend inward to 2RR(Ford 2005) • Breaking process could very well scale with host mass • Companions at 2RR from UCD are at ~0.004AU

15. Grain Growth Apai (2005)

16. Luhman (2005a)

17. Do UCDs Have Planets? • Existence of close UCD binaries constrains formation mechanisms • What if UCDs form in a very different way from stars? • UCDs seem to be part of low-mass star (LMS) continuum • Similar velocity dispersion, IMF, spatial distribution • UCDs do tend to have lower binary fraction • New technologies may reveal new populations (Kelu-1) • Ejection scenario seems less likely today • UCDs probably have same formation mechanism as LMSs

18. Transit Search Strategy • Hours/night of PAIRITEL commissioning time • Observe sample of 20 objects for a few months • Observe objects for 30 minutes at a time • Observe objects once nightly or every other night • Select targets from 2MASS sample of bright UCDs • Focus on targets with comparison stars within 3’-4’ • Focus on targets with 10.5<J<13.0

19. Search Strategy • Bin individual 7.8s observations so photon noise <<1% • Produce differential photometry in all 3 bands • Search for transit signals and other variability • Find first Earth-like planet!

21. Observations • More than 106 seconds of integration • More than 4x105 images • Time baselines of ~125 days

22. Observations • Observations are dithered • Telescope is moved ~20” every three exposures • Averages out problems of bad pixels • Allows for sky estimation • Dither positions are randomly selected to fill 50” box • UCDs are bright enough to photometer individual 7.8s frames • Bright sky, dither sets, noise require specialized reduction

25. Data Reduction • Basic plan: • Use standard PAIRITEL reduction pipeline • Median-combine images in a time “window” • Estimates sky, removes point sources • Lots of details I will leave out, can come back to later

26. Photometry • Fix a set of reference stars for each target • Measure flux of target relative to average flux of comparison ensemble • Bright, isolated targets warrant aperture photometry • Optimal aperture, annulus matched to average PSF

27. Culling Observations • Raw flux of target very high or low • Every comparison star not present in frame • Bad pixel near target or comparison

28. Binning Data • Individual 7.8s observations combined into ~minute bins • Robust average of measurements in bin • Standard error on bin • Realistic errors estimates are very important • Binned J,H,K measurements combined into composite flux

29. Photometry Results • ~2% differential photometry in 180s bins over months • Systematics limited • Composite magnitude very Gaussian • Compares favorably with results in the literature • Not as precise as observations with well-sampled PSF

31. Transit Searching • Box Least-Squares is standard method for finding transits • Detection efficiency is simulated with actual PAIRITEL data • Transits with random phase, inclination injected into light curves • Transit shapes from Mandel and Agol (2002) • BLS method used to try to recover injected transit • Monte-Carlo simulation carried out for 50,000 combinations • Phase, inclination, host mass (13-100MJ) combinations • Planets of 3 ME to 10 ME and Neptune • Planet radii from models of Valencia (2006)

32. Simulations of detection efficiency

33. Monte-Carlo Results • Detection efficiencies fall below geometric expectation • Approximate probability of detecting four unique events • Increased phase coverage will increase detection probability • Objects as small as 3ME detectable, not limited by photometry • Improvements in photometry will allow detection of 1ME objects

34. Limits on Planet Fraction • Current sample is small: • Not sufficient to exclude every UCD having a close-in planet • At 2 Roche-radii the per-UCD detection efficiency is ~5% • Two years of observations of ~100 objects could place upper-limits • Gould (2006a) estimates rate of Very Hot Jupiters at 1/690 • Planets in orbits with a~2-4 RRoche • If UCD frequency is similar, probably impossible to detect • New evidence from microlensing that Neptunes are far more common • Gould (2006b) estimate Neptune frequency >1/6 for 1.6<a<4.3 AU

35. Conclusions • An extensive campaign to monitor UCDs could be sensitive to Earth-like planets in the Habitable zone • UCDs are photometrically stable over long periods of time in NIR • Simultaneous J,H,K data can be used to mitigate systematics due to atmosphere of Earth and UCD • We find no evidence for large (>20%), evolving cloud features in our cooler UCDs

36. Acknowledgements • Dave Latham, Josh Bloom • Gaspar Bakos, Dave Charbonneau, Scott Gaudi, Joe Hora, Mike Skrutskie • Michael Cushing, Dan Fabryky, Ken Jucks, Francis O’Donovan, Willie Torres • Dwarfarchives.org • The PAIRITEL project has been made possible by a grant from the Milton Fund (Harvard University). The camera is on long-term loan from Prof. Mike Skrutskie at the University of Virginia. Starting calendar year 2005 the project became funded by a grant from the Swift guest investigator program in collaboration with the Yale Astronomy GRB group

37. References Apai, D. et al. 2005, Science, 310, 834 Burrows, A. et al. 2001, RevMP, 73, 719 Charbonneau, D. et al. 2006, astro-ph/0603376 Charbonneau, D. et al. 2005, ApJ, 626, 523 Charbonneau, D. et al. 2002, ApJ, 568, 377 Chauvin, G. et al. 2004, A&A, 425, 29 Ford, E. 2005, astro-ph/0510198 Gould, A. et al. 2006a, astro-ph/0601001 Gould, A. et al. 2006b, astro-ph/0603276 Ida, S and Lin, D. 2005, ApJ, 626, 1045 Luhman, K. et al. 2005a, ApJ, 635, 93 Luhman, K. et al. 2005b, ApJ, 631, 69 Mandel, K. and Agol, E. 2002, ApJ, 580, 171 Valencia, et al. 2006, astro-ph/0511150

38. UCD Variability • Question of UCD variability uncertain in the literature • Some reports of variability at a low (<1%) level in optical • Some reports of persistent periodic variation • Most recent NIR observations show no evidence for variability • Our data show that UCDs are not variable at >2% over months • Intrinsic variability does not preclude planet detection

40. Sources of Variability • Cool, magnetic spots: • Less favored, I band variability not related to H emission • Cloud features: • Areas with less dust, settled dust • Areas with more dust, fully circulated dust • Both types of features could be modulated by fast rotation • Features could evolve on timescales longer than rotation • Possible explanation for quasi-periodic variation in literature

41. Simple Models • Dusty and dust cleared models are calculated by France Alard • The expected signal of a cloud with 10% covering factor is estimated • Combination of spectra in a 9:1 ratio • Signals due to 10% clouds are calculated for bands and colors • Cloud features of given size has larger amplitude for cooler UCDs • Composite magnitude is relatively immune to clouds

42. Predicted signals from clouds with 10% covering factors

43. Detecting Quasi-periodic Variations • Cloud signatures inserted into real data • Rotation period of UCD assumes to be 3 hours, around ~3% • Cloud amplitude changes very 24 hours • Detected in both CLEAN and Lomb-Scargle periodograms

44. Periodograms • Lomb-Scargle • Statistical behavior in principle well defined • Not well understood for data “clustered” in time • CLEAN • Statistics not well understood • False alarm level estimated from Monte-Carlo simulation • Data randomly permuted • Highest peak in 100 periodograms taken as 99% level • CLEAN does a better job of identifying inserted cloud feature

45. Power Period(d) Top: Lomb-Scargle of ; Middle: CLEAN of ; Bottom: CLEAN of H-K

46. Variability Results • No evidence for increased variability with decreased temperature • Cooler UCDs could have smaller clouds • Only one case of marginal evidence for quasi-periodic variability • 2M0746+2000 J band data show periodicity at 2.5 hours • Similar period reported in literature • We place upper limits of ~30% covering factor of evolving clouds • Predicted cloud signal only detectable for coolest objects • Strong correlatoin between H and K bands

47. (K) (J) C Teff Cloud models and observed variability compared to UCD temperature

48. Conclusions • An extensive campaign to monitor UCDs could be sensitive to Earth-like planets in the Habitable zone • UCDs are photometrically stable over long periods of time in NIR • Simultaneous J,H,K data can be used to mitigate systematics due to atmosphere of Earth and UCD • We find no evidence for large (>20%), evolving cloud features in our cooler UCDs

49. Acknowledgements • Dave Latham, Josh Bloom • Gaspar Bakos, Dave Charbonneau, Scott Gaudi, Joe Hora, Mike Skrutskie • Michael Cushing, Dan Fabryky, Ken Jucks, Francis O’Donovan, Willie Torres • Dwarfarchives.org • The PAIRITEL project has been made possible by a grant from the Milton Fund (Harvard University). The camera is on long-term loan from Prof. Mike Skrutskie at the University of Virginia. Starting calendar year 2005 the project became funded by a grant from the Swift guest investigator program in collaboration with the Yale Astronomy GRB group

50. References Apai, D. et al. 2005, Science, 310, 834 Burrows, A. et al. 2001, RevMP, 73, 719 Charbonneau, D. et al. 2006, astro-ph/0603376 Charbonneau, D. et al. 2005, ApJ, 626, 523 Charbonneau, D. et al. 2002, ApJ, 568, 377 Chauvin, G. et al. 2004, A&A, 425, 29 Ford, E. 2005, astro-ph/0510198 Gould, A. et al. 2006a, astro-ph/0601001 Gould, A. et al. 2006b, astro-ph/0603276 Ida, S and Lin, D. 2005, ApJ, 626, 1045 Luhman, K. et al. 2005a, ApJ, 635, 93 Luhman, K. et al. 2005b, ApJ, 631, 69 Mandel, K. and Agol, E. 2002, ApJ, 580, 171 Valencia, et al. 2006, astro-ph/0511150