Developing Performance Estimates for High Precision Astrometry with TMT Matthias Schoeck, Tuan Do, Brent Ellerbroek, Gilles Luc, Glen Herriot, Leo Meyer, Ryuji Suzuki, Lianqi Wang, Sylvana Yelda AO4ELT3 Conference, Florence, Italy May TMT.AOS.PRE REL01 AO4ELT3, Florence, 05/28/13

Presentation Outline TMT astrometry requirements Example astrometry science cases Astrometry error budget –Overview –Work to date –Error budget spreadsheet by category Summary 2 TMT.AOS.PRE REL01 AO4ELT3, Florence, 05/28/13

3 Current 8-10 m telescopes: ~ µas differential astrometry with adaptive optics –Some higher-precision special cases TMT requirement: –50 µas differential astrometry for 100s exposure on 30” FoV in H band –Error falling as t -1/2 to a systematic floor of 10 µas –50 µas is 10 cm at distance of Moon Challenging constraints on all parts of opto-mechanics Unique scientific opportunities enabled by astrometry at µas level –We need to make sure that TMT will be able to achieve this Astrometry with TMT TMT.AOS.PRE REL01 AO4ELT3, Florence, 05/28/13

Example Astrometry Science Cases 50 micro-arcsecs differential astrometry in densely populated fields: ­ General Relativity at the Galactic Center ­ Velocities in dwarf galaxies ­ Star forming regions: accurate determination of the Initial Mass Function with cluster membership 2 milli-arcsecs in sparse fields, i.e., where only wavefront sensor guide stars are available: – Magnetar proper motions to establish velocity imparted during progenitor explosion – Binary star/planet orbits to measure stellar, compact object and planet masses – Astrometric microlensing to measure accurate stellar masses – Gravitational lensing to probe dark matter substructures – Binary Kuiper Belt Objects TMT.AOS.PRE REL01 AO4ELT3, Florence, 05/28/13 4

5 Many error terms that are negligible for ~100 µas astrometry become important for ~10 µas astrometry We tried to identify all effects that might influence astrometry –Currently more than 30 error terms in 5 categories Many terms are correlated or interconnected –They cannot simply be added in quadrature Almost every error term depends on the details of the astrometry observations –Absolute vs. differential astrometry –Sparse vs. crowded fields –Short vs. long times scales –Differences can be qualitative, not just quantitative –We also need calibration, observing and data reduction sequences TMT.AOS.PRE REL01 AO4ELT3, Florence, 05/28/13 TMT Astrometry Error Budget Overview

Lots of work done has been done, for example: –Residual atmospheric turbulence –Multi-conjugate vs. single-conjugate adaptive optics –Telescope, NFIRAOS and IRIS distortions and aberrations –Atmospheric dispersion –Pinhole grid and optical surfaces requirements –Galactic Center simulations –Focal plane errors –Top-down astrometry error budget Analytical analyses, simulations and observations Data reduction sequences with error propagation 6 TMT Astrometry Error Budget Work to Date

Galactic Center Astrometry Simulations 7 Simulations of Galactic Center Astrometry ~100,000 stars, 3,000 of which are known GC stars second exposures Will be bench-marked by Keck simulations See talk by Sylvana Yelda

TMT Astrometry Error Budget 8 Zoomed-in versions on next slides Rows: error terms in 5 categories Columns: 8 generic science cases Right column: current status Words: Status Color: Reliability of error estimate Purple: value calculated from equation Blue: sum of error terms above Orange: input parameters Note: Work in Progress; values are very dependent on type of observation (by more than an order of magnitude)

By Comparison: One year Ago 9 Status of the error budget on May 1, 2012

TMT Astrometry Error Budget Reference Catalog Errors 10 Differences between real and assumed properties of reference sources –Pretty much “under control” –Color & variability errors taken care of in atmospheric dispersion analysis Note: Values are very dependent on type of observation TMT.AOS.PRE REL01 AO4ELT3, Florence, 05/28/13

TMT Astrometry Error Budget Atmospheric Refraction 11 –Achromatic differential refraction Due to differences between zenith angles of different objects –Chromatic differential refraction (dispersion) Due to wavelength dependence of index of refraction Requires atmospheric dispersion corrector (ADC), and possibly a different ADC for each wavelength band A posteriori corrections likely required for highest-precision astrometry –Refraction-caused errors can be one of the dominant terms –Currently under investigation in both simulations and measurements (Subaru) Note: Values are very dependent on type of observation

TMT Astrometry Error Budget Other Atmospheric Residuals 12 –Analysis of residual turbulence after NFIRAOS correction mostly done –Most terms depend on integration time as T -0.5 –Halo effect Seeing-limited halos of other stars cause background gradients –Variable atmospheric effects (during exposure, e.g. Strehl, transparency): Couple with image motion to cause astrometric uncertainties Unintuitively, this error term increases with integration time Note: Values are very dependent on type of observation

TMT Astrometry Error Budget Residual Turbulence Errors Simulations to study astrometry errors due to residual wavefront errors after MCAO compensation by NFIRAOS –Geometric tip/tilt effects (<30  arcsec) –Atmospheric “speckle noise” (10-12  arcsec) –Uncertainty in r 0 estimate (1-3 μarcsec) 2 x 15 sec exposures of a 30x30 arcsec field at 50 degrees zenith –Global tip/tilt and plate scale distortion removed using field stars (-> these are high-order residuals) All errors found to scale as T -0.5 (previous slide is for 100s) Errors are much larger for single-conjugate AO systems –MCAO is good for astrometry –Also: Distortions by DM11 are not a problem (see talk by Brent Ellerbroek) 13 TMT.AOS.PRE REL01 AO4ELT3, Florence, 05/28/13

TMT Astrometry Error Budget Opto-Mechanical Errors 14 –Stability of distortions and repeatability of configurations are crucial Observing sequences (incl. calibration methods) are critical input information –See Brent’s talk –No show stoppers found so far Note: Values are very dependent on type of observation

TMT Astrometry Error Budget Focal Plane Errors –Photon noise of 24 µas is for S/N = 200 ( 100 s exposure for K = 20 point source ) –Confusion not an issue for this generic science case (by definition), but can be a major contribution in other cases (Galactic Center, dwarf galaxies, globular clusters) Currently under investigation in Galactic Center simulations (see Sylvana’s talk) –Total error for differential astrometry with many reference sources: 37 µas (But note again: Values are very dependent on type of observation) 15

TMT Astrometry Error Budget Summary Lots of work done has been done, for example: –Analytical analyses –Simulations –Observations –Top-down astrometry error budget –Data reductions sequences with error propagation –Still lots to do … No show stoppers found so far for very high-precision astrometry –Work has resulted in a couple tweaks to NFIRAOS design Results depend very much on the science case –Need analysis and requirements for different science cases 16

Acknowledgements The TMT Project gratefully acknowledges the support of the TMT partner institutions. They are –the Association of Canadian Universities for Research in Astronomy (ACURA), –the California Institute of Technology –the University of California –the National Astronomical Observatory of Japan –the National Astronomical Observatories and their consortium partners –And the Department of Science and Technology of India and their supported institutes. This work was supported as well by –the Gordon and Betty Moore Foundation –the Canada Foundation for Innovation –the Ontario Ministry of Research and Innovation –the National Research Council of Canada –the Natural Sciences and Engineering Research Council of Canada –the British Columbia Knowledge Development Fund –the Association of Universities for Research in Astronomy (AURA) –and the U.S. National Science Foundation. 17 TMT.AOS.PRE REL01 AO4ELT3, Florence, 05/28/13