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Peter Lawrence Capak
Alma materUniversity of Hawaii at Manoa
University of British Columbia
Known forCosmology, Structure Formation, Dark Matter, Dark Energy Galaxy Evolution
Scientific career
FieldsAstronomy, Machine Learning, Space Sciences
InstitutionsCalifornia Institute of Technology
Cosmic DAWN Center
Websitepetercapak.com

Peter Lawrence Capak is a staff scientist and member of the professional staff at the California Institute of Technology.[1] His research focuses on using physical modeling and advanced statistical methods including artificial intelligence and machine learning to extract information from very large multi-wavelength (hyper-spectral) data sets. He has primarily used this to study structure formation in the universe, cosmology, and the nature of dark matter[2] and dark energy.

Early life and education[edit]

Capak grew up in a rural area[3] in Smithers, British Columbia, Canada, where he graduated from Smithers Secondary School. He received his bachelor of science in physics and astronomy with honors from the University of British Columbia in 1999.[4] He then earned a masters in astronomy in 2002, and a Ph.D. in astronomy in 2004 both from the University of Hawaii.[5] In his Ph.D. thesis, he focused on measuring the growth of structure and history of star formation in the universe using several data sets including the GOODS survey.

Scientific career[edit]

Capak is currently science lead of the SPHEREx[6][7] science center at the Infrared Processing and Analysis Center (IPAC), Caltech and a member of the NASA Euclid Science Center at IPAC. He previously was a member of the Spitzer Science Center where he led the Spitzer Enhanced Imaging Products pipeline team and the Spitzer Frontiers Field Initiative.[8] He was also a principal investigator on the Spitzer Large Area Survey with Hyper-Suprime-Cam (SPLASH) project.[9] Before joining IPAC, he was a postdoctoral fellow on the Cosmic Evolution Survey (COSMOS) and a graduate student at the University of Hawaii at Manoa.

Capak joined Caltech, in 2004, to work on the COSMOS project where he led the multi-wavelength data processing and analysis effort.[10][11] As part of this work he developed a way of estimating redshifts from photometry (photometric redshifts) that accounted for the signal strength of weak lensing, enabling the first 3-dimensional map of dark matter. He subsequently led the development of new technique based on manifold learning that significantly reduced the number of observations required to calibrate photometric redshifts for dark energy measurements.[12][13] This made it practical to carry out the calibration observations in a reasonable amount of time on the Keck and VLT telescopes with the C3R2 survey.[14][15][16] Capak has also worked on improving galaxy modeling techniques using more advanced statistical methods and machine learning[17][18][19] including leading the development of the fitting pipeline for the SPHEREx mission.[20]

In 2010, Capak took over leadership of the COSMOS collaboration which he lead until 2018. The COSMOS data set helped to develop the concept behind several experiments to measure the properties of dark matter and dark energy including the Dark Universe Explorer (DUNE),[21] which was incorporated into the Euclid mission. Capak consulted[22] on the design of NASA's Wide Field Infrared Survey Telescope (WFIRST). He was also a co-investigator on the team that developed NASA's SPHEREx mission.

Capak's work has been featured in the media including his work on Abell 520, the Baby Boom Galaxy. He also discovered the most distant known cluster of galaxies[23][24] and carried out the first large study of the interstellar medium in the distant universe.[25][26] In 2017 and 2018, he was identified as one of the top 1% of cited researchers in space sciences.[27][28]

References[edit]

  1. ^ "Peter Capak". IPAC. Retrieved 7 Aug 2019.
  2. ^ "Big Unknowns: what is dark matter? – Science Weekly podcast". The Guardian. 22 Nov 2016.
  3. ^ "Meet the BUFFALO Collaboration - Peter Capak". BUFFALO Survey. 12 Nov 2018.
  4. ^ "PHYSICS 449/ ASTR 449 THESIS". Physics Astronomy, University of British Columbia. Retrieved 7 Aug 2019.
  5. ^ "Alumni (alphabetical listing)". Institute for Astronomy, University of Hawaii. Retrieved 7 Aug 2019.
  6. ^ "SPHEREx Science Team". SPHEREx. Retrieved 7 Aug 2019.
  7. ^ "IPAC Organization". IPAC. Retrieved 8 Aug 2019.
  8. ^ "The Frontier Fields: where primordial galaxies lurk". Astronomy Now. 29 Sep 2016.
  9. ^ "Spitzer's SPLASH Project Dives Deep for Galaxies". JPL NASA. 9 Sep 2014.
  10. ^ "Dark matter maps reveal cosmic scaffolding" (PDF). Hubble Space Telescope. 12 Nov 2006.
  11. ^ "First 3D map of the Universe's Dark Matter scaffolding". Hubble Space Telescope. 7 Jan 2007.
  12. ^ "Mapping the Galaxy Color-Redshift Relation: Optimal Photometric Redshift Calibration Strategies for Cosmology Surveys". The Astrophysical Journal. 28 Oct 2015.
  13. ^ "Photometric Redshift Calibration Requirements for WFIRST Weak Lensing Cosmology: Predictions from CANDELS". Retrieved 24 Apr 2019.
  14. ^ "The C3R2 Survey: Mapping the Galaxy Color-Redshift Relation for Weak Lensing Cosmology". Retrieved 12 Aug 2019.
  15. ^ "The Complete Calibration of the Color-Redshift Relation (C3R2) Survey: Survey Overview and Data Release 1". Retrieved 21 Apr 2017.
  16. ^ "The Complete Calibration of the Color-Redshift Relation (C3R2) Survey: Survey Overview and Data Release 1". Retrieved 21 Apr 2017.
  17. ^ "Exploring Photometric Redshifts as an Optimization Problem: An Ensemble MCMC and Simulated Annealing-Driven Template-Fitting Approach". Retrieved 11 Aug 2015.
  18. ^ "Bringing manifold learning and dimensionality reduction to SED fitters". Retrieved 24 May 2019.
  19. ^ "Horizon-AGN virtual observatory - 2: Template-free estimates of galaxy properties from colours". Retrieved 12 Aug 2019.
  20. ^ "An Empirical Approach to Cosmological Galaxy Survey Simulation: Application to SPHEREx Low-Resolution Spectroscopy". Retrieved 12 Aug 2019.
  21. ^ "The Dark UNiverse Explorer (DUNE): Proposal to ESA's Cosmic Vision" (PDF). Retrieved 7 Aug 2019.
  22. ^ "Wide-Field InfrarRed Survey Telescope-Astrophysics Focused Telescope Assets WFIRST-AFTA 2015 Report". 12 March 2015.
  23. ^ Clavin, Whitney (11 Jan 2011). "NASA Telescopes Help Identify Most Distant Galaxy Cluster". JPL NASA.
  24. ^ "A massive protocluster of galaxies at a redshift of z ≈ 5.3". Nature. 12 Jan 2011.
  25. ^ Choi, Charles (24 June 2015). "Ancient Carbon Haze Offers Clues to Galaxy Evolution". Space.com.
  26. ^ "Galaxies at redshifts 5 to 6 with systematically low dust content and high [C II] emission". Nature. 24 June 2015.
  27. ^ "2017 Highly Cited Researchers". Clarivate Analytics. Retrieved 9 Aug 2019.
  28. ^ "Highly Cited Researchers 2018". Web of Science Group. Retrieved 9 Aug 2019.


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