coronagraph; direct imaging; exoplanet; optimization; scheduling; validation; Coronagraphic instruments; Exoplanet detection; Infra-red survey telescope; Mission constraints; Mission simulation; Nonlinear combination; Optimal integration time; Optimal scheduling; Electronic, Optical and Magnetic Materials; Control and Systems Engineering; Instrumentation; Astronomy and Astrophysics; Mechanical Engineering; Space and Planetary Science
Abstract :
[en] We present an algorithm, effective over a broad range of planet populations and instruments, for optimizing integration times of an exoplanet direct imaging observation schedule, to maximize the number of unique exoplanet detections under realistic mission constraints. Our planning process uses "completeness"as a reward metric and the nonlinear combination of optimal integration time per target and constant overhead time per target as a cost metric constrained by a total mission time. We validate our planned target list and integration times for a specific telescope by running a Monte Carlo of full mission simulations using EXOSIMS, a code base for simulating telescope survey missions. These simulations encapsulate dynamic details such as time-varying local zodiacal light for each star, planet keep-out regions, exoplanet positions, and strict enforcement of observatory use over time. We test our methods on the Wide-Field Infrared Survey Telescope (WFIRST) coronagraphic instrument (CGI). We find that planet, Sun, and solar panel keep-out regions limit some target per-annum visibility to <28 % and that the mean local zodiacal light flux for optimally scheduled observations is 22.79 mag arcsec - 2. Both these values are more pessimistic than previous approximations and impact the simulated mission yield. We find that the WFIRST CGI detects 5.48 ± 0.17 and 16.26 ± 0.51 exoplanets, on average, when observing two different planet populations based on Kepler Q1-Q6 data and the full Kepler data release, respectively. Optimizing our planned observations using completeness derived from the more pessimistic planet population (in terms of overall planet occurrence rates) results in a more robust yield than optimization based on the more optimistic planet population. We also find optimization based on the more pessimistic population results in more small planet detections than optimization with the more optimistic population.
Disciplines :
Space science, astronomy & astrophysics
Author, co-author :
Keithly, Dean R. ; Cornell University, Ithaca, United States ; Cornell University, Carl Sagan Institute, Ithaca, United States
Savransky, Dmitry ; Cornell University, Ithaca, United States ; Cornell University, Carl Sagan Institute, Ithaca, United States
Garrett, Daniel ; Cornell University, Ithaca, United States ; Cornell University, Carl Sagan Institute, Ithaca, United States
Delacroix, Christian ; Université de Liège - ULiège > Département d'astrophysique, géophysique et océanographie (AGO) > Planetary & Stellar systems Imaging Laboratory
Soto, Gabriel ; Cornell University, Ithaca, United States ; Cornell University, Carl Sagan Institute, Ithaca, United States
Language :
English
Title :
Optimal scheduling of exoplanet direct imaging single-visit observations of a blind search survey
Publication date :
April 2020
Journal title :
Journal of Astronomical Telescopes, Instruments, and Systems
This research has made use of NASA’s NAIF planetary data system kernels. This research has made use of the Washington Double Star Catalog maintained at the U.S. Naval Observatory. This work was supported by the NASA Space Grant Graduate Fellowship from the New York Space Grant Consortium, NASA Grant Nos. NNX14AD99G (GSFC), NNX15AJ67G (WFIRST Preparatory Science), and NNG16PJ24C (WFIRST Science Investigation Teams). This research made use of astropy, a community-developed core Python package for Astronomy (Astropy Collaboration, 2018) and OR-Tools, an optimization utility package made by Google Inc. with community support. This research has made use of the Imaging Mission Database, which is operated by the Space Imaging and Optical Systems Lab at Cornell University. The database includes content from the NASA Exoplanet Archive, which is operated by the California Institute of Technology, under contract with the National Aeronautics and Space Administration under the Exoplanet Exploration Program, and from the SIMBAD database, operated at CDS, Strasbourg, France.This research has made use of NASA's NAIF planetary data system kernels. This research has made use of theWashington Double Star Catalog maintained at the U.S. Naval Observatory. This work was supported by the NASA Space Grant Graduate Fellowship from the New York Space Grant Consortium, NASA Grant Nos. NNX14AD99G (GSFC), NNX15AJ67G (WFIRST Preparatory Science), and NNG16PJ24C (WFIRST Science Investigation Teams). This research made use of astropy, a community-developed core Python package for Astronomy (Astropy Collaboration, 2018) and OR-Tools, an optimization utility package made by Google Inc. with community support. This research has made use of the Imaging Mission Database, which is operated by the Space Imaging and Optical Systems Lab at Cornell University. The database includes content from the NASA Exoplanet Archive, which is operated by the California Institute of Technology, under contract with the National Aeronautics and Space Administration under the Exoplanet Exploration Program, and from the SIMBAD database, operated at CDS, Strasbourg, France.
Goddard Space Flight Center, "LUVOIR interim report," Technical Report (2018).
D. Garrett and D. Savransky, "Analytical formulation of the single-visit completeness joint probability density function," Astrophys. J. 828, 20 (2016).
D. Garrett, D. Savransky, and B. Macintosh, "A simple depth-of-search metric for exoplanet imaging surveys," Astronom. J. 154(2), 47 (2017).
S. L. Hunyadi, S. B. Shaklan, and R. A. Brown, "The lighter side of TPF-C: evaluating the scientific gain from a smaller mission concept," Proc. SPIE 6693, 66930Q (2007).
R. A. Brown and R. Soummer, "New completeness methods for estimating exoplanet discoveries by direct detection," Astrophys. J. 715, 122-131 (2010).
D. Savransky, C. Delacroix, and D. Garrett, "EXOSIMS: Exoplanet open-source imaging mission simulator," Astrophysics Source Code Library, https://ui.adsabs.harvard.edu/abs/ 2017ascl.soft06010S/abstract (2017).
R. W. Farquhar, "The utilization of halo orbits in advanced lunar operations," NASA Technical Note, pp. 1-99 (1971).
R. Lougee-Heimer, "The common optimization interface for operations research: promoting open-source software in the operations research community," IBM J. Res. Dev. 47, 57-66 (2003).
P. T. Boggs and J.W. Tolle, "Sequential quadratic programming," Acta Numer. 4, 1-51 (1995).
D. Savransky, C. Delacroix, and D. Garrett, "Multi-mission modeling for space-based exoplanet imagers," Proc. SPIE 10400, 104001L (2017).
D. Savransky and D. Garrett, "WFIRST-AFTA coronagraph science yield modeling with EXOSIMS," J. Astron. Telesc. Instrum. Syst. 2, 011006 (2015).
D. Keithly et al., "Scheduling and target selection optimization for exoplanet imaging spacecraft," Proc. SPIE 10698, 106985I (2018).
J. Krist, B. Nemati, and B. Mennesson, "Numerical modeling of the proposed WFIRSTAFTA coronagraphs and their predicted performances," J. Astron. Telesc. Instrum. Syst. 2(1), 011003 (2015).
F. Fressin et al., "The false positive rate of Kepler and the occurrence of planets," Astrophys. J. 766, 81 (2013).
D. Savransky, "Space mission design for exoplanet imaging," Proc. SPIE 8864, 886403 (2013).
R. K. Kopparapu et al., "Exoplanet classification and yield estimates for direct imaging missions," Astrophys. J. 856, 122 (2018).
D. Garrett and D. Savransky, "Building better planet populations for EXOSIMS," in AAS Meeting #231, American Astronomical Society, id.#246.04, Vol. 231 (2018).
A. Cumming et al., "The Keck planet search: detectability and the minimum mass and orbital period distribution of extrasolar planets," Publ. Astron. Soc. Pac. 120, 531-554 (2008).
A. V. Moorhead et al., "The distribution of transit durations for Kepler planet candidates and implications for their orbital eccentricities," Astrophys. J. Suppl. Ser. 197, 1 (2011).
E. L. Nielsen et al., "The Gemini planet imager exoplanet survey: giant planet and brown dwarf demographics from 10 to 100 AU," Astronom. J. 158(1), 13 (2019).
R. B. Fernandes et al., "Hints for a turnover at the snow line in the giant planet occurrence rate," Astrophys. J. 874, 81 (2019).
A. Howard et al., "The occurrence and mass distribution of close-in super-Earths, Neptunes, and Jupiters," Science 330(6004), 653-655 (2010).
R. Belikov et al., "Exoplanet occurrence rates and distributions," Technical Report (2017).
D. Garrett, D. Savransky, and R. Belikov, "Planet occurrence rate density models including stellar effective temperature," Publ. Astron. Soc. Pac. 130(993), 114403 (2018).
K. L. Cahoy, M. S. Marley, and J. J. Fortney, "Exoplanet albedo spectra and colors as a function of planet phase, separation, and metallicity," Astrophys. J. 724, 189-214 (2010).
D. Savransky, E. Cady, and N. J. Kasdin, "Parameter distributions of Keplerian orbits," Astrophys. J. 728(7), 66 (2011).
M. C. Turnbull, "ExoCat-1: the nearby stellar systems catalog for exoplanet imaging missions," arXiv:1510.01731 (2015).
M. J. Pecaut and E. E. Mamajek, "Intrinsic colors, temperatures, and bolometric corrections of pre-main-sequence stars," Astrophys. J. Suppl. Ser. 208(22), 9 (2013).
G. L. Wycoff, B. D. Mason, and S. E. Urban, "Data mining for double stars in astrometric catalogs," Astronom. J. 132(1), 50-60 (2006).
B. Nemati, "Detector selection for the WFIRST-AFTA coronagraph integral field spectrograph," Proc. SPIE 9143, 91430Q (2014).
W. A. Traub et al., "Science yield estimate with the wide-field infrared survey telescope coronagraph," J. Astron. Telesc. Instrum. Syst. 2, 011020 (2016).
C. Leinert et al., "The 1997 reference of diffuse night sky brightness," Astron. Astrophys. Suppl. Ser 127, 1-99 (1998).
G. Soto et al., "Parameterizing the search space of starshade fuel costs for optimal observation schedules," J. Guid. Control Dyn. 42(2), 1-6 (2018).
G. Soto et al., "Optimal starshade observation scheduling," Proc. SPIE 10698, 106984M (2018).
C. H. Acton, "Ancillary data services of NASA's navigation and ancillary information facility," Planet. Space Sci. 44, 65-70 (1996).
C. Acton et al., "A look towards the future in the handling of space science mission geometry," Planet. Space Sci. 150, 9-12 (2018).
E. Kolemen, N. J. Kasdin, and P. Gurfil, "Quasi-periodic orbits of the restricted three-body problem made easy," AIP Conf. Proc. 886, 68-77 (2007).
D. Keithly et al., "WFIRST: exoplanet target selection and scheduling with greedy optimization," in AAS Meeting #231, American Astronomical Society, id. 246.06, Vol. 231 (2018).
D. Keithly et al., "Blind search single-visit exoplanet direct imaging yield for space based telescopes," in AAS Meeting #233, American Astronomical Society, id.140.40, Vol. 233 (2019).
D. Savransky, N. J. Kasdin, and E. Cady, "Analyzing the designs of planet finding missions," Publ. Astron. Soc. Pac. 122(890), 401-419 (2010).
Lindler, personal communication (2008).
D. Savransky, "Sequential covariance calculation for exoplanet image processing," Astrophys. J. 800, 100-119 (2015).
N. S. Budden and P. D. Spudis, "Evaluating science return in space exploration initiative architectures," Technical Report, Houston (1993).
B. Nemati, J. E. Krist, and B. Mennesson, "Sensitivity of the WFIRST coronagraph performance to key instrument parameters," Proc. SPIE 10400, 1040007 (2017).
J. E. Krist, "End-to-end numerical modeling of AFTA coronagraphs," Proc. SPIE 9143, 91430V (2014).
G. Soto et al., "Optimization of high-inclination orbits using planetary flybys for a zodiacal light-imaging mission," Proc. SPIE 10400, 104001X (2017).
D. A. Vallado, Fundamentals of Astrodynamics and Applications, 4th ed., Microcosm Press, Hawthorne (2013).
