Emerging Areas of Research: Computational Astrophysics and the Formation of Structure in the Universe. Personnel

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1 Emerging Areas of Research: Computational Astrophysics and the Formation of Structure in the Universe Personnel PI: Liese van Zee, Professor, Department of Astronomy. Prof. van Zee will lead one of the project initiatives related to investigating the structure of nearby galaxies and will coordinate the overall science program. Her expertise is in multi-wavelength astronomy, from ultraviolet to radio, and the study of galaxy formation and evolution. During the past decade, she has been awarded telescope time on numerous national and international facilities. She was previously awarded a CAREER grant from the NSF and was PI of an Exploration Science program on the Spitzer Space Telescope, which is the basis for one of the precursor studies described in this proposal. Co-PI: Enrico Vesperini, Assistant Professor, Department of Astronomy. Prof. Vesperini will lead one of the project initiatives related to investigating the dynamical evolution of star clusters in the Milky Way. His expertise is in computational astrophysics, with an emphasis on Galactic dynamics and evolution of star clusters. His current research program is supported by numerous grants from NASA and makes use of Big Red II and other high performance computing resources at IUB. Co-PI: Catherine Pilachowski, Daniel Kirkwood Chair, Professor, Department of Astronomy. Prof. Pilachowski will lead one of the project initiatives related to investigating the stellar population of our Galaxy. Her expertise is in spectroscopic analysis of stars in the Milky Way and the study of stellar chemical abundances and chemical enrichment history of our Galaxy. Her research program is currently funded by a collaborative NSF grant that includes an initiative to develop the science portal for the Blanco DECam Bulge Survey (BDBS). Co-PI: Katherine Rhode, Associate Professor, Department of Astronomy. Prof. Rhode will lead one of the project initiatives related to investigating the structure and evolution of nearby galaxies. Her expertise is in studying the stellar populations of nearby galaxies and star clusters, both from integrated light and individual stars. She was integral to the development of the ODI- PPA, a data processing pipeline for data acquired with the One Degree Imager (ODI) camera on the WIYN 3.5m telescope. She was previously awarded a CAREER grant from the NSF and is currently PI on an NSF grant to identify and study the stellar populations of the faintest dwarf galaxies in the nearby Universe. Co-PI: Andrew Womack, Assistant Professor, Department of Statistics. Prof. Womack will lead the development of statistical analysis tools for the large survey projects. His expertise is theoretical and applied Bayesian analysis. His theoretical research focuses on regression and clustering modeling for big data with an emphasis on objective Bayesian methodologies. His applied collaborations include work on complex models in the biological, ecological, and social sciences. Coupled with this work is an expertise in Bayesian computation using Markov Chain Monte Carlo and associated methodologies. Contributing team member: Robert Henschel, Manager, Scientific Applications and Performance Tuning. Robert Henschel is the manager of the Scientific Applications and Performance Tuning group with the Research Technologies division of the University 5 of 65 1

2 Information Technology Service. He has extensive experience in high-performance computing and the application of high-performance computing techniques and benchmarking to multiple disciplines including astronomy and biology. He is part of the team who developed the WIYN One-Degree-Imager-Portal, Pipeline, and Archive and the Blanco DECam Bulge Survey data portal. He is co-i on projects funded by the National Science Foundation and the National Institutes of Health. He will contribute 5% FTE effort to this initiative. Contributing team member: Scott Michael, Manager, Research Analytics. Scott Michael is the manager of the Research Analytics group within the Research Technologies division of the University Information Technology Service. His areas of expertise include high performance computational systems, workflow development for supercomputers, and application parallelization. His current research focuses on distributed computing and parallelization of data intensive scientific workflows. Scott also has domain expertise in computational simulations of astrophysical disks. He completed his PhD studies in numerical simulations of gravitational instabilities in protoplanetary disks in He will contribute 5% FTE effort to this initiative. Contributing team member: Michael Young, Sr. Developer/Analyst, UITS/Research Technologies. His expertise is in systems integration, specifically the development and deployment of scientific pipelines on large-scale compute clusters. He also has expertise in maintaining long-term archives of scientific data and developing web portals to enable community access to data products. He will contribute 5% FTE effort to this initiative. 6 of 65 2

3 Education: Liese van Zee Haverford College Astronomy and Chemistry, with High Honors B.S Cornell University Astronomy M.S Cornell University Astronomy Ph.D Professional Employment: Professor Indiana University 2016 present Associate Professor Indiana University Assistant Professor Indiana University Research Associate Herzberg Institute of Astrophysics Jansky Fellow National Radio Astronomy Observatory Products: Related publications: Neutral Hydrogen and magnetic fields in M83 observed with the SKA Pathfinder KAT-7, G. Heald, W. J. G. de Blok, D. Lucero, C. Carignan, T. Jarrett, E. Elson, N. Oozeer, T.H. Randriamampandry, & L. van Zee 2016, MNRAS, in press Baryonic Distributions in Galaxy Dark Matter Halos I: New Observations of Neutral and Ionized Gas Kinematics, E. E. Richards, L. van Zee, K. L. Barnes, S. Staudaher, D. A. Dale, and 5 co-authors, 2016, MNRAS, 460, 689 The stellar halo and tidal streams of Messier 63, S. Staudaher, D. A. Dale, L. van Zee, K. L. Barnes, & D. O. Cook, 2015, MNRAS, 454, 3613 Baryonic Distributions in the Dark Matter Halo of NGC5005, E. E. Richards, L. van Zee, K. L. Barnes, S. Staudaher, D. A. Dale, and 6 co-authors, 2015, MNRAS, 449, 3981 New Insights on the Formation and Assembly of M83 from Deep Near-infrared Imaging, K. L. Barnes, L. van Zee, D. A. Dale, S. Staudaher, J. S. Bullock, D. Calzetti, R. Chandar, J. J. Dalcanton, 2014, ApJ, 789, 126 Other publications: Oxygen and Nitrogen in Isolated Dwarf Irregular Galaxies, L. van Zee, & M. P. Haynes, 2006, ApJ, 636, 214 Spectroscopy of Outlying HII Regions in Spiral Galaxies: Abundances and Radial Gradients, L. van Zee, J. J. Salzer, M. P. Haynes, A. A. O Donoghue, & T. J. Balonek, 1998, AJ, 116, Neutral Gas Distributions and Kinematics of Five Blue Compact Dwarf Galaxies, L. van Zee, E. D. Skillman, & J. J. Salzer, 1998, AJ, 116, The Effects of Episodic Star Formation on the FUV-NUV Colors of Star Forming Regions in Outer Disks, K. L. Barnes, L. van Zee, & J. D. Dowell, 2013, ApJ, 775, 40 Modeling the Effects of Star Formation Histories on Hα and Ultraviolet Fluxes in Nearby Dwarf Galaxies, D. R. Weisz, and 11 co-authors, 2012, ApJ, 744, 44 Synergistic Activities: I am vice-chair of the Committee on Radio Frequencies, a standing committee of the National Academy of Sciences which represents the interests of US scientists who use radio frequencies for research. 7 of 65

4 Recent collaborators (98): Armus, L. (IPAC) Gouliermis, D. A. (Heidelberg) Mills, E. A. (Cal State, San Jose) Barnes, K. L. (Indiana) Grebel, E. K. (Heidelberg) Momjian, E. (NRAO) Beltz-Mohrmann, G. D. (Wellesley) Hatlestad, A. J. (Wyoming) Moravec, P. L. (Indiana) Berg, D. (Minnesota) Heald, G. (CSIRO) Murphy, E. J. (IPAC) Blackwell, W. (MIT) Herzog, L. J. (Minnesota St) Oozeer, N., (SKA South Africa) Boquien, M. (Cambridge) Hinz, J. L. (Arizona) Ott, J. (NRAO) Bothwell, M. S. (Cambridge) Hunter, D. A. (Lowell) Owen, F. (NRAO) Braun, T. T. (New Mexico) Hunter, T. (NRAO) Pearson, T. J. (Caltech) Brogan, C. (NRAO) Jarrett, T. (Cape Town) Phenicie, C. (Minnesota) Bullock, J. S. (Irvine) Jezek, K. (Ohio St) Randriamampandry, T. H. Cales, S. (U. de Concepcion) Johnson, B. D. (IAP) (Cape Town) Calzetti, D. (UMass) Johnson, K. (UVa) Reid, M. (CfA) Carignan, C (Cape Town) Johnson, L. C. (Washington) Reising, S. C. (Colorado State) Chandar, R. (Toledo) Judge, J. (Florida) Richards, E. E. (Indiana) Cook, D. O. (Wyoming) Kellerman, K. I. (NRAO) Roberts, J. S. (Wyoming) Côté, S. (HIA) Kennicutt, R. C. (Cambridge) Rogers, A. E. E. (MIT) Cruz-Pol, S. L. (NSF) Kobulnicky, H. A. (Wyoming) Rosolowsky, E. (Alberta) Dalcanton, J. J. (Washington) Koda, J. (Stony Brook) Sabbi, E. (STScI) Dale, D. A. (Wyoming) Le Vine, D. (Goddard) Schade, D. (HIA) Davis, M. M. (Cornell) Lee, J. C. (STScI) Schinnerer, E. (MPIA) de Block, W. J. G. (ASTRON) Leroy, A. K. (Ohio St) Scoville, N. (CalTech) DeBoer, D. R. (Berkeley) Leung, A. S. (Rutgers) Siqueira, P. (UMass) Donovan Meyer, J. (NRAO) Long, D. G. (BYU) Skillman, E. (Minnesota) Dowell, J. D. (New Mexico) Lovell, A. (Agnes Scott) Spekkens, K. (RMC of Canada) Egan, A. A. (Northern Michigan) Lucero, D. (Groningen) Staudaher, S. (Wyoming) Elmegreen, B. G. (IBM Watson) Magnani, L. (Georgia) Taylor, G. (New Mexico) Elson, E., (Cape Town) Marble, A. R. (Arizona) Thilker, D. A. (Johns Hopkins) Emerson, D. (NRAO) McKague, D. S. (Michigan) Thompson, A. R. (NRAO) Engelbracht, C. W. (deceased) McLane, J. N. (NAU) Wavle, D. (Illinois) Evans, A. (NRAO) McQuinn, K. B. (Texas) Weisz, D. R. (Berkeley) Feldman, P. (FH&H) Meidt, S. E., (MPIA) Williams, B. F. (Washington) Ferguson, A. M. N. (Edinburgh) Meier, D. S. (NMIMT) Wison, T. (NSF) Gaier, T. (JPL) Menten, K. (MPIfR) Wong, T. (Illinois) Graduate Advisor (1): Martha P. Haynes (Cornell University) Postdoc Advisees (2): Mansie Iyer ( ), Kate L. Barnes ( ) Graduate Student Advisees (7): Heidi Tebbe (MA 03), Janet Casperson (MA 03), Prasanth Nair (MA 07), Kevin V. Croxall (PhD 10), Jayce D. Dowell (PhD 10), Kate L. Barnes (PhD 12), Emily Richards (current) Recent Undergraduate Advisees (14): Miriam Musco (IU 09), Todd Smith (IU 12), Sarah Friberg (UMass 11), Elaine Snyder (IU 12), Bryce Shackleford (IU 13), Cody Minns (IU 12), Katee Koskie (IU 13), Patricia Moravec (IU 14), Daniel Wavle (IU 15), Timothy Braun (IU 15), Grace Haza (IU 17), Miranda Barnett (IU 18), Tasman Payne (IU 18), Stetson Reger (IU 17) 8 of 65

5 Past, Current, and Pending Support for Liese van Zee Pending External Grants: Project Title: An Extension of the EDGES Survey: Stellar Populations in Dark Matter Halos Source of Support: NASA Total Award Amount Requested: $299,976 Total Award Period Covered: 1/1/17-12/31/19 Location of Project: Indiana University Person-Months Per Year Committed to the Project: Cal: 0.0 Acad: 0.0 Sumr: 1.0 External Grants From the Past Five Years: Project Title: Stellar Distributions in Dark Matter Halos: Looking Over the Edge Source of Support: Spitzer Space Telescope Total Award Amount: $613,180 Total Award Period Covered: 10/1/11-9/30/14 Location of Project: Indiana University, University of Wyoming, University of Massachusetts Person-Months Per Year Committed to the Project: Cal: 0.0 Acad: 0.0 Sumr: 0.5 Project Title: Faint Stellar Distributions in Extended HI Disks Source of Support: Spitzer Space Telescope Total Award Amount: $98,520 Total Award Period Covered: 5/15/09-9/30/12 Location of Project: Indiana University Person-Months Per Year Committed to the Project: Cal: 0.0 Acad: 0.0 Sumr: 0.5 Project Title: Extended Stellar Distributions in M83 Source of Support: Spitzer Space Telescope Total Award Amount: $45,000 Total Award Period Covered: 5/15/09-9/30/12 Location of Project: Indiana University Person-Months Per Year Committed to the Project: Cal: 0.0 Acad: 0.0 Sumr: of 65

6 Biographical Sketch: Enrico Vesperini Professional Preparation 1990 Jun Degree of DOTTORE IN FISICA, cum laude. University of Rome Dec Ph.D. in Physics, cum laude. (Scuola Normale Superiore, Pisa) 1995 Jan-1996 March Research fellow at Scuola Normale Superiore Apr-Dec Post-doc fellowship at the Department of Mathematics and Statistics of the University of Edinburgh Post-doc fellowship at the Department of Physics and Astronomy of University of Massachusetts (Amherst) Five College Astronomy Department (University of Massachusetts, Amherst College, Smith College, Hampshire College, Mount Holyoke College) Science Education post-doc fellowship. Appointments August 2012-present Assistant Professor in the Department of Astronomy of Indiana University, Bloomington Nov July 2012 Research Associate Professor in the Department of Physics of Drexel University 2001-Oct Research Associate in the Department of Physics and Astronomy of Michigan State University. Products most closely related to the proposed project 1) Bellini, A.; Vesperini, E.; Piotto, G.; et al. The Hubble Space Telescope UV Legacy Survey of Galactic Globular Clusters: The Internal Kinematics of the Multiple Stellar Populations in NGC 2808, 2015, ApJ, 810, L13 2) Hong, J.; Vesperini, E.; Sollima, A.; McMillan, S. L. W.; D Antona, F.; D Ercole, A., Evolution of binary stars in multiple-population globular clusters, 2015, MNRAS, 449, 629 3) Vesperini, E., McMillan S.L.W.,D Antona F.,D Ercole A., Dynamical Evolution and spatial mixing of multiple population globular clusters, 2013, MNRAS, 416, 355 4) Vesperini,E., McMillan S.L.W.,D Antona F.,D Ercole A., The Fraction of Globular Cluster Second-generation Stars in the Galactic Halo, 2010, ApJ, 718, L112 5) D Ercole A., Vesperini E., D Antona F., McMillan S. L. W., Recchi S., Formation and dynamical evolution of multiple stellar generations in globular clusters, 2008, MNRAS, 391, 825 Other products 1) D Antona, F.; Vesperini, E.; D Ercole, A.; Ventura, P.; Milone, A. P.; Marino, A. F.; Tailo, M. A single model for the variety of multiple-population formation(s) in globular clusters: a temporal sequence, 2016, MNRAS, 458, ) Lucatello, S.; Sollima, A.; Gratton, R.; Vesperini, E.; D Orazi, V.; Carretta, E.; Bragaglia, A. The incidence of binaries in Globular Cluster stellar populations, 2015, A&A, 584, A52 3) Vesperini, E., Varri, A.L., McMillan, S.L.W., Zepf, S.E., Kinematical fingerprints of star cluster early dynamical evolution, 2014, MNRAS, 443, L79 4) Vesperini, E., McMillan S.L.W.,D Antona F.,D Ercole A., Binary star disruption in globular 1 10 of 65

7 clusters with multiple stellar populations, 2011, MNRAS, 416, 355 5) Vesperini,E., McMillan S.L.W.,D Ercole A., D Antona F., Intermediate-mass Black Holes in Early Globular Clusters, 2010, ApJ, 713, L41 Synergistic Activities -co-chair of the SOC of a 3-day IAU Special Session on Origin and Complexity of Massive Star Clusters held during the IAU General Assembly in August Director of the course on Dynamical Evolution of Globular Clusters held in May 2011 (Bertinoro- Italy) within the International School of Astrophysics for graduate students Francesco Lucchin. -Member of the SOC of the Multiple populations in globular clusters workshop held in Asiago (Italy) in September co-organizer of the KITP program Formation and Evolution of Globular Clusters (January- April 2009) -Chair of the SOC for International IAU Symposium 246 Dynamical Evolution of Dense Stellar Systems (September 2007) 2 11 of 65

8 Past, Current, and Pending Support for Enrico Vesperini HST-GO-cycle 21 (current): The HST legacy survey of Galactic globular clusters: shedding UV light on their populations and formation (co-i) Total amount (funds for co-i Vesperini): $ 45,898 Period: 12/ /2016 HST-Theory-Cycle 21 (current): E ects of dynamical evolution on the stellar mass function of multiple population globular clusters (PI) Total amount: $ 115,107 Period: 10/ /2016 HST-Theory-Cycle 20 (current): Dynamics of Binary Stars in Multiple Population Globular Clusters (PI) Total Amount: $ 94,715 Period: 10/ /2016 HST-Theory-Cycle 18 (past): Dynamical Evolution of Multiple Stellar Populations in Globular Clusters (PI) Total Amount: $ 86,298 Period: 10/ /2014 NASA-ATP (past): Multiple Stellar Populations in Globular Clusters (PI) Total Amount: $ 289,155. Period: 01/ /2016 NASA-ATP (pending): Dynamics of Multiple Stellar Populations in Globular Clusters (PI) Total amount requested: $ 371,043 Period: 04/ /2020 NSF-CAREER (pending): CAREER: Building a Theoretical Framework for the Formation and Dynamical Evolution of Multiple Stellar Populations in Globular Clusters (pending) (PI) Total amount requested: $ 732,638 Period: 04/ /2022 HST-GO-Cycle 24 (phase I-approved; phase II-pending): Multiple Stellar Populations in Young Magellanic Cloud Clusters (co-i) Total amount (phase II-pending requested by co-i Vesperini): $ 14,237 Period: 11/ / of 65

9 Biographical Sketch Catherine A. Pilachowski Indiana University Bloomington Telephone: (812) Astronomy Dept., Swain West 319 Fax: (812) E. 3 rd Street cpilacho@indiana.edu Bloomington, IN Professional Preparation Harvey Mudd College Physics B.S., 1971 University of Hawaii Manoa Astronomy M.S., 1973 University of Hawaii Manoa Astronomy Ph.D., 1975 University of Washington Astronomy Post-doctoral Appointment, Appointments Daniel Kirkwood Chair in Astronomy, Indiana University present Associate Dean for Graduate Education, IU College of Arts and Sciences Interim Dean for Women s Affairs, Indiana University Astronomy Department Chair, Indiana University Astronomer with Tenure, National Optical Astronomy Observatory Associate Astronomer, National Optical Astronomy Observatory Associate Support Scientist, Kitt Peak National Observatory 1982 Assistant Support Scientist, Kitt Peak National Observatory Postdoctoral Research Assoc., University of Washington Recent Refereed Publications: C. I. Johnson, N. Caldwell, R. M, Rich, C. A. Pilachowski, Hsyu, T. (2016), The Chemical Composition of Red Giant Branch Stars in the Galactic Globular Clusters NGC 6342 and NGC 6366, ApJ, 152, 21J. Johnson, C. I.; Rich, R. M.; Pilachowski, C A.; Caldwell, N.; Mateo, M.; Bailey, J. I., III; Crane, J. D. (2015), A Spectroscopic Analysis of the Galactic Globular Cluster NGC 6273 (M19); ApJ, 150, 63J C. A. Pilachowski & C. Pace (2015), The Abundance of Fluorine in Normal G and K Stars of the Galactic Thin Disk, Astron. J., 150, 66 C. I. Johnson and C. A. Pilachowski 2012, Oxygen and Sodium Abundances in M13 (NGC 6205) Giants:Linking Globular Cluster Formation Scenarios, Deep Mixing, and Post RGB Evolution;; ApJ, 754, L38. C. I. Johnson, C. A. Pilachowski (2010), Chemical Abundances for 853 Giants in the Globular Cluster Omega Centauri (NGC 5139), Astrophysical J., 722, M. Cordero, C. A. Pilachowski, C. I. Johnson, I. McDonald, A. Zijlstra, & J. Simmerer, ApJ, (in press);; Multi-Object Spectroscopy of Giants in the Globular Cluster 47 Tucanae (NGC 104) Synergistic Activities Chair, Time Allocation Committee, Hubble Space Telescope (2016) Chair, Keck Telescope Time Allocation Committee, NASA Exoplanet Science Institute ( ) Affiliate Member representing the Association of Universities for Research in Astronomy, Board of Governors, Thirty Meter Telescope International Observatory 13 of 65

10 Member, National Science Foundation, Advisory Committee for Math and Physical Sciences Observer: Kitt Peak National Observatory (WIYN telescope, Mayall 4-m telescope, Lynds 2.1-m telescope, 1.3-m telescope, coude feed telescope), WIYN 0.9-m telescope; Cerro Tololo Interamerican Observatory (Blanco 4-m telescope, 1.5m telescope);; MMT Observatory;; University of Hawaii 88 telescope, APO 3.5-m telescope; 3-m NASA Infrared Telescope Facility. Instrument Scientist, Mayall 4-m echelle spectrograph, Member, WIYN ODI Pipeline Advisory Committee Project Scientist, WIYN Telescope construction ( ) Collaborators during the past 48 Months J. Bailey (U. Mich) P. Blum (SAO intern) N. Caldwell (CFA) G. Carraro (ESO) W. Clarkson (UM Dearborn) M. Cordero (Heidelberg) J. D. Crane (OCIW) J. Cummings (STScI) R. de Propris (Turku) E. D. Friel (Indiana U) G. Fűrész (IvS, Belgium) D. Geisler (Concepcion) S. Gillam (IPFW) G. Hajdu (PUC Chile) C. J. Hansen (ZAH) K. Hinkle (NOAO) K. Honeycutt (Indiana U.) H. Jacobson (MIT) J. Jurcsik (Konkoly Obs) C. Johnson (Harvard/CFA) C. Kobayashi (Hertfordshire) A. Koch (ZAH) K. Kolenberg (SAO) Kun, E. (Szeged) A. Kunder (Leibniz) Z. Maas (Indiana U.) M. Mateo (U Mich) I. McDonald (Manchester) S. Meszaros (CEU) S. Michael (Indiana U.) A. Moór (Konkoly Obs) K. Nault (Indiana U.) E. Olzewski (U. Ariz) J. Overbeek (Indiana U.) C. Pace (Indiana U.) P. Prakesh (SAO intern) M. Rich (UCLA) A. Saha (NOAO) S. Shectman (OCIW) J. Simmerer (-) P. Smitola (Konkoly Obs) C. Sneden (UT Austin) Á. Sódor (Konkoly Obs) I. Thompson (OCIW) I. Toth (Konkoly Obs) E. Vesperini (Indiana U) S. Villanova (Conception) K. Vivas (NOAO/CTIO) R. Wilson (U. Florida) A Winans (Indiana U) M. Young (Indiana U.) A. Zijlstra (Manchester) Graduate and Postgraduate Advisors Dissertation advisor - Walter K. Bonsack, University of Hawaii (retired) Post-doctoral Sponsor - George Wallerstein, University of Washington (retired) Graduate & Postgraduate Advisees Total graduate student advisees 8. Total postgraduate advisees 0. M. J. Cordero, Ph. D 2014 (Heidelberg) H. R. Jacobson, Ph.D (MIT) C. I. Johnson, Ph.D (Harvard) K. Nault, MA 2014 (Indiana U.) D. Lamenti (deceased) T. Monroe, Ph.D (STScI) Zachary Maas (current student, Indiana University) Amanda Winans (current student, Indiana University) 14 of 65

11 Current Funding NSF DUE Building a Community in Science and Mathematics (S-STEM) (PI) 09/01/ /31/2018 $614,184 NSF AST Collaborative Research: A Panchromatic 08/01/ Imaging Survey of the Galactic Bulge (PI) 07/31/2017 $132,148 NSF DUE Indiana Noyce Scholars: Teachers for a 10/1/2012 New Decade (Co-PI; R. D. Sherwood, PI) 09/30/2017 $1,199,805 Other Funding in the Past Five Years INSGC Fellowship Program through Indiana Space Grant Consortium - Dennis Lamenti 05/17/ /16/2012 $12,500 INSGC View the Universe in 3D 05/17/ /16/2013 $10, of 65

12 Biographical Sketch for KATHERINE L. RHODE (a) Professional Preparation Sonoma State University, Rohnert Park, CA Physics B.A., 1989 Wesleyan University, Middletown, CT Astronomy M.A., 1997 Yale University, New Haven, CT Astronomy M.S., 1998 Yale University, New Haven, CT Astronomy Ph.D., 2003 Wesleyan & Yale NSF Astronomy & Astrophysics Postdoctoral Fellow, (b) Appointments Associate Professor, Indiana University 2013 present Assistant Professor, Indiana University NSF Astronomy & Astrophysics Postdoctoral Fellow, Wesleyan & Yale NASA Graduate Student Researchers Program (GSRP) Fellow, Yale University Graduate Teaching & Research Assistant, Yale University Graduate Teaching & Research Assistant, Wesleyan University Astronomer, Harvard Smithsonian Center for Astrophysics Programmer-Analyst, NASA-Goddard Space Flight Center , (c) Products (i) Five Publications Related to the Current Proposal 1. Janesh, W., Rhode, K., Salzer, J., Janowiecki, S., Adams, E., Haynes, M., Giovanelli, R., Cannon, J., & Muñoz, R. 2015, Searching for Optical Counterparts to Ultra-Compact High Velocity Clouds: Possible Detection of a Counterpart to AGC , ApJ, 811, Adams, E., Cannon, J., Rhode, K., Janesh, W., Janowiecki, S., Leisman, L., Giovanelli, R., Haynes, M., Oosterloo, T., Salzer, J., & Zaidi, T. 2015, AGC : A possible interacting low-mass system, A&A, 580, Janowiecki, S., Leisman, L., Jozsa, G., Salzer, J., Haynes, M., Giovanelli, R., Rhode, K., Cannon, J., Adams, E., & Janesh, W. 2015, (Almost) Dark HI Sources in the ALFALFA Survey: The Intriguing Case of HI , ApJ, 801, Rhode, K., Salzer, J., Haurberg, N., Van Sistine, A., Young, M., Haynes, M., Giovanelli, R., Cannon, J., Skillman, E., Adams, E., & McQuinn, K. 2013, ALFALFA Discovery of the Nearby Gas-Rich Dwarf Galaxy Leo P. II. Optical Imaging Observations, AJ, 145, Giovanelli, R., Haynes, M., Adams, E., Cannon, J., Rhode, K., Salzer, J., Skillman, E., Bernstein-Cooper, E., & McQuinn, K. 2013, ALFALFA Discovery of the Nearby Gas-Rich Dwarf Galaxy Leo P. I. HI Observations, AJ, 146, 15 (ii) Five Other Significant Publications 1. Rhode, K. 2012, Exploring the Correlations between Globular Cluster Populations and Supermassive Black Holes in Giant Galaxies, AJ, 144, Rhode, K., Zepf, S., & Santos, M. 2005, Metal-Poor Globular Clusters and the Formation of Their Host Galaxies, ApJ, 630, L21 3. Rhode, K. & Zepf, S. 2004, The Globular Cluster Systems of the Early-Type Galaxies NGC 3379, NGC 4406, and NGC 4594 and Implications for Galaxy Formation, AJ, 127, Rhode, K., Herbst, W., Mathieu, R. 2001, Rotational Velocities and Radii of Pre-Main- Sequence Stars in the Orion Nebula Cluster, AJ, 122, Rhode, K., Salzer, J.; Westpfahl, D.; Radice, L. 1999, A Test of the Standard Hypothesis for the Origin of the H I Holes in Holmberg II, AJ, 118, of 65

13 (d) Synergistic Activities (1) Developed observational methods and data analysis techniques for systematic multi-color widefield CCD survey of extragalactic globular cluster systems (Rhode & Zepf 2001, 2003, 2004; Rhode et al. 2005, 2007, 2010; Rhode 2012). (2) Assisted sta at WIYN Observatory, NOAO, and Indiana University Information Technology Services to plan, design, and fund a data transfer, storage, reduction, and analysis system called the ODI Pipeline, Portal, & Archive (ODI-PPA) for WIYN One Degree Imager data. (3) Developed web-based lab exercises for intro astronomy courses that enable students to work with modern astronomical images (Education project for NSF Postdoctoral Fellowship). (4) Serves on the WIYN 3.5m Telescope Science Steering Committee and the WIYN Board of Directors; serves as the WIYN ODI-PPA Scientific Liaison, and served on the WIYN One Degree Imager Commissioning Working Group. (5) Serves as the only astronomer on the Maria Mitchell Association Board of Directors, a non-profit research, education, and outreach organization dedicated to promoting the legacy of America s first female professional astronomer. (e) Collaborators & Other A liations Collaborators (78): E. Adams (ASTRON), L. Allen (NOAO), J. Arnold (UCSC), E. Aver (Gonzaga), A. Benson (Carnegie), D. Berg (UW-Milwaukee), G. Bergond (Instituto de Astrofisica de Andalucia), E. Bernstein-Cooper (Wisconsin), C. Blom (Swinburne), A. Bolatto (Maryland), T. Bridges (Queens U.), J. Cannon (Macalester), J. Chengalur (TIFR), R. Ciardullo (PSU), A. Dolphin (Raytheon), J. Dowell (IU), E. Elson (Macalester), Y. Faerman (Tel Aviv U.), C. Foster (ESO), K. Freeman (Australian Nat l U.), K. Gebhardt (U Texas), R. Giovanelli (Cornell), L. Girardi (Padova), C. Gronwall (PSU), G. Hallenbeck (Union), C. Hamilton (Dickinson), J. Hargis (Haverford), N. Haurberg (Knox College), M. Haynes (Cornell), R. Herrera-Camus (Maryland), W. Janesh (IU), S. Janowiecki (IU), K. Jameson (Maryland), M. Jones (Cornell), R. Joyce (NOAO), G. Jozsa (Rhodes U.), J. Kirkpatrick (IPAC), R. Koopmann (Union), A. Kundu (Eureka Scientific), L. Leisman (Cornell), N. Loutrel (PSU), K. Luhman (PSU), T. Maccarone (Texas Tech), G. Mace (UCLA), C. Martinkus (Macalester), T. Matheson (NOAO), N. McCurdy (PSU), K. Mc- Quinn (UT-Austin), I. McLean (UCLA), N. Melso (PSU), E. Molter (Macalester), R. Munoz (U. Chile), N. Nichols (Hartwick), K. Olive (Minnesota), T. Oosterloo (ASTRON), M. Panetta (Harvard), E. Papastergis (Groningen), M. Peacock (MSU), R. Pogge (OSU), V. Pota (Swinburne), A. Romanowsky (UC Santa Cruz), J. Salzer (IU), E. Skillman (Minnesota), K. Star (PSU), M. Steele (MSU), D. Stern (JPL), A. Sternberg (Tel Aviv U.), R. Terrien (PSU), P. Troischt (Hartwick), C. Usher (UCSC), A. Van Sistine (IU), S. Warren (Maryland), C. Waters (IfA), M. West (Lowell), E. Wylie de Boer (ANU), M. Young (IU), T. Zaidi (Macalester), S. Zepf (MSU). Graduate Advisors (4): W. Herbst & R. Mathieu (M.A.); S. Zepf & C. Bailyn (PhD) Postdoc Advisors (2): NSF Fellowship sponsors were W. Herbst (Wesleyan), C. Bailyn (Yale) Advisees (13): A. Larner (Wesleyan), S. Nordhagen (Middlebury), T. Picard (Mt Holyoke), J. Dowell (IU PhD 2014), M. Young (IU PhD 2016), J. Hargis (IU PhD 2013), B. Fisher (IU B.S. 2013), W. Janesh (IU PhD candidate), R. Lambert (IU graduate student), H. Pagel (IU PhD candidate), M. Panetta (Maria Mitchell REU student), M. Smith (Maria Mitchell REU student), D. Carr (Maria Mitchell REU Student) 2 17 of 65

14 (f) Grant Funding During the Past Five Years ( ): NSF Astronomy & Astrophysics Research Grant, A Systematic Search for Stars in Almost- Dark Galaxies, August 2016 July 2019, $367,114 NSF Faculty Early Career Development (CAREER) Program Grant, CAREER: Using Globular Clusters to Unravel the Mysteries of Galaxy Formation, Galaxy Structure, and Black Holes, August 15, 2009 September 30, 2015 (no-cost extension for final 15 months), $681, of 65

15 Andrew J. Womack Contact Information Professional Preparation Department of Statistics 668 Ballantine Hall Indiana University 1020 E Kirkwood Ave ajwomack@indiana.edu Bloomington, IN University of Florida, Gainesville, FL Postdoctoral Researcher in the Department of Statistics. Supervised by George Casella and Linda Young. August 2011 May University of Southern California, Los Angeles, CA Visiting Postdoctoral Researcher in the Department of Molecular and Computational Biology. Supervised by Sergey Nuzhdin. August 2012 May Washington University in St. Louis, St. Louis, MO Ph.D., Department of Mathematics, May Thesis: Predictive Alternatives in Bayesian Model Selection. Advisor: Je Gill, Director of the Center for Applied Statistics. Qualifying Exam Fields: Algebra, Real Analysis, Complex Analysis, and Di erential Geometry. A.M., Mathematics, August University of Kansas, Lawrence, KS B.S., Mathematics, May B.S., Physics, May Appointments Publications Indiana University, Bloomington, IN Assistant Professor in the Department of Statistics. Taylor-Rodriguez, Daniel, Andrew Womack, Nikolay Bliznyuk, and Claudio Fuentes. Intrinsic Bayesian Analysis for Occupancy Models. Bayesian Analysis. Forthcoming. Taylor-Rodriguez, Daniel, Andrew Womack, and Nikolay Bliznyuk. Bayesian Variable Selection on Model Spaces Constrained by Heredity Conditions. Journal of Computational and Graphical Statistics 25.2 (2016): Womack, Andrew J., Luis Len-Novelo, and George Casella. Inference From Intrinsic Bayes Procedures Under Model Selection and Uncertainty. Journal of the American Statistical Association (2014): The Multilevel Model Framework, Je Gill and Andrew Womack The SAGE Handbook of Multilevel Modeling. Edited by Brian Marx, Marc Scott, and Je Simono. Thousand Oaks: SAGE Publications, Inc. 1 of 2 19 of 65

16 Synergistic Activities Collaborators Maintainer: R package varselectip Coauthors Daniel Taylor-Rodriguez, Research Associate, Department of Forestry, Michigan State University. Claudio Fuentes, Assistant Professor, Department of Statistics, Oregon State University. Nikolay Blyzniuk, Assistant Professor, Department of Agricultural and Biological Engineering, University of Florida. Luis Leon-Novelo, Department of Biostatistics, University of Texas School of Public Health. Diana O Brien, Assistant Professor, Department of Political Science, Indiana University. Amy Alexander, Assistant Professor, Department of Political Science, University of Gothenburg. Zikun Yang, PhD Candidate, Department of Statistics, Indiana University. Advisors Je Gill, Professor, Departments of Political Science, Biostatistics, and Surgery (Public Health Division), Washington University in St. Louis. George Casella, Distinguished Professor, Department of Statistics, University of Florida. Linda Young, Chief Mathematical Statistician and Director of Research and Development, United States Department of Agriculture, National Agricultural Statistics Service. Sergey Nuzhdin, Professor, Department of Biological Sciences, University of Southern California. 2 of 2 20 of 65

17 Robert Henschel Manager Scientific Applications and Performance Tuning University Information Technology Services/Indiana University Professional Preparation Technische Universität Dresden, Germany Computer Science M.S Appointments 09/ / /2012 Manager Scientific Applications and Performance Tuning, Indiana University Manager High Performance Applications, Indiana University 06/ /2008 Researcher at Technische Universität Dresden, Germany 01/ /2007 Researcher at Max Planck Institute of Molecular Cell Biology and Genetics 11/ /2006 Researcher at Technische Universität Dresden, Germany 05/ /2006 Project Manager at 6PAC AG 12/ /2004 Senior Support Manager at Netsys GmbH Products Selected relevant products: 1. K. Nho, J.D. West, Huian Li, R. Henschel, M.C. Tavares, A. Bharthur, M.W. Weiner, R.C. Green, A.W. Toga, A.J. Saykin; Comparison of multi-sample variant calling methods for whole genome sequencing, 8th International Conference on Systems Biology (ISB), A. Gopu, S. Hayashi, M.D. Young, D.R. Harbeck, T. Boroson, W. Liu, R. Kotulla, R. Shaw, R. Henschel, J. Rajagopal, E. Stobie; ODI-Portal, Pipeline, and Archive (ODI-PPA): a web-based astronomical compute archive, visualization, and analysis service, SPIE Astronomical Telescopes+ Instrumentation (pp E-91520E). International Society for Optics and Photonics, B. Haas, A. Papanicolaou, M. Yassour, M. Grabherr, P. Blood, J. Bowden, M. Couger, D. Eccles, B. Li, M. Lieber, M. MacManes, M. Ott, J. Orvis, N. Pochet, F. Strozzi, N. Weeks, R. Westerman, T. William, C. Dewey, R. Henschel, R. LeDuc, N. Friedman, A. Regev. De novo transcript sequence reconstruction from RNA-seq using the Trinity platform for reference generation and analysis. Nature Protocols, Vol. 8, No. 8., pp , R. Henschel, S. Simms, D. Hancock, S. Michael, T. Johnson, N. Heald, T. William, D. Berry, M. Allen, R. Knepper, M. Davy, M. Link, and C. A. Stewart. Demonstrating Lustre over a 100Gbps wide area network of 3,500km. Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis (SC '12). IEEE Computer Society Press, Los Alamitos, CA, USA, Article 6, 8 pages R. Henschel, P. M. Nista, M. Lieber, B. J. Haas, L.-S. Wu and R. D. LeDuc. Trinity RNA-Seq assembler performance optimization. Proceedings of the 1st Conference of the Extreme Science and Engineering Discovery Environment: Bridging from the extreme to the campus and beyond. Article No R. Henschel, S. Michael and S. Simms. A distributed workflow for an astrophysical OpenMP application: using the Data Capacitor over WAN to enhance productivity. Proceedings of the 19th ACM International Symposium on High Performance Distributed Computing (HPDC '10). ACM, New York, NY, USA, C. Collinet, M. Stoter, C. R. Bradshaw, N. Samusik, J. C. Rink, D. Kenski, B. Habermann, F. Buchholz, R. Henschel, M. S. Mueller, W. E. Nagel, E. Fava, Y. Kalaidzidis, M. Zerial, Systems survey of endocytosis by multiparametric image analysis, Nature, Vol. 464, No. 7286, Mar Other selected products: 1. SPEC ACCEL version 1.0 benchmark for accelerated HPC systems of 65

18 Synergistic Activities 1. Secretary of HPG at SPEC. As the IU representative and secretary to the High Performance Group (HPG) at the Standard Performance Evaluation Corporation (SPEC) Henschel is leading the benchmarking efforts of Indiana University. 2. Treasurer of SPXXL Large Systems User Group. As the treasurer of the SPXXL Large Systems User Group, Henschel is responsible for running meetings in financial responsible manner. 3. Collaboration with Technische Universität Dresden, Germany. Henschel is playing a leading in the collaboration between Indiana University and the Center for Information Service and High Performance Computing at the Technische Universität Dresden, Germany. Performance analysis of scientific codes and trans-continental high speed networking are of particular interest to him. Collaborators & Other Affiliations Collaborators and Co-Editors: Blood, P. (Pittsburgh Supercomputer Center), Bradshaw C. (Max Planck Institute of Molecular Cell Biology and Genetics), Haas, B. (Broad Institute), Hahn, M. (Indiana University), Hancock, D. (Indiana University), Harbeck, D. (National Optical Astronomy Observatory), Hernandez, O. (Oak Ridge National Laboratory), Juckeland, G. (Helmholtz-Zentrum Dresden-Rossendorf), Kalaidzidis, Y. (Max Planck Institute of Molecular Cell Biology and Genetics), Kluge, M. (Technische Universitaet Dresden), Knüpfer, A. (Technische Universitaet Dresden), Kotulla, R. (University of Wisconsin Madison), Kumaran, K. (Argonne National Laboratory), Link, M. (Indiana University), Lumsdaine, A. (Indiana University), Lynch M. (Indiana University), Mueller M. (RWTH Aachen), Nagel W. (Technische Universitaet Dresden), Pierce, M. (Indiana University), Pilachowski, C. (Indiana University), Regev A. (Broad Institute), Saykin, A. (Indiana University), Simms, S. (Indiana University), Stewart, C. (Indiana University), Stobie, E. (National Optical Astronomy Observatory) Graduate and Post Doctoral Advisors: N/A Total number of graduate students supervised: N/A 22 of 65

19 Past, Current, and Pending Support for Robert Henschel Pending External Grants: Project Title: An Open Source Precision Medicine Platform for Cloud Operating Systems Source of Support: National Institutes of Health Total Award Amount Requested: $2,000,000 Total Award Period Covered: 3/1/16-2/28/18 Location of Project: Curoverse Inc. and Pennslyvania State University Person-Months Per Year Committed to the Project: Cal: 0.6 Acad: 0.0 Sumr: 0.0 Current External Grants: Project Title: ABI Development: CAFE for very large comparative genomic datasets Source of Support: National Science Foundation Total Award Amount: $796,715 Total Award Period Covered: 4/1/16-3/31/19 Location of Project: Indiana University Person-Months Per Year Committed to the Project: Cal: 1.2 Acad: 0.0 Sumr: 0.0 Project Title: EAGER: Open XD Metrics on Demand Value Analytics Source of Support: National Science Foundation Total Award Amount: $296,416 Total Award Period Covered: 4/1/16-3/31/18 Location of Project: Indiana University Person-Months Per Year Committed to the Project: Cal: 0.0 Acad: 0.0 Sumr: 0.0 Project Title: Trinity - Transcriptome assembly for genetic and functional analysis of cancer Source of Support: National Institutes of Health Total Award Amount: $2,500,000 Total Award Period Covered: 9/1/13-8/31/18 Location of Project: Broad Institute Person-Months Per Year Committed to the Project: Cal: 1.6 Acad: 0.0 Sumr: of 65

20 Scott A. Michael Manager, Research Analytics Indiana University Role in this proposal: Senior Personnel Professional Preparation Indiana University Indiana University Physics Applied Mathematics B.S B.S Indiana University Astronomy M.A Indiana University Astrophysics Ph.D Appointments Manager, Research Analytics, Indiana University Principal Analyst, Research Technologies, Indiana University Senior Analyst/Programmer, Research Technologies, Indiana University Research Assistant, Astronomy, Indiana University Publications Selected relevant publications: 1. Henschel, R., Simms, S., Hancock, D., Michael, S., Johnson, W., Heald, N., William, T., Allen, M., Knepper, R., Davy, M, Link, M., Stewart, C. (2012) Demonstrating Lustre over a 100Gbps Wide Area Network of 3500km. Proceedings of 2012 International Conference for High Performance Computing, Networking, Storage and Analysis; ACM, Accepted 2. Michael, S., Zhen, L., Henschel, R., Simms, S., Barton, E., Link, M. (2012) A Study of Lustre Networking Over a 100 Gigabit Wide Area Network with 50 milliseconds of Latency. Proceedings of the fifth international workshop on Data-Intensive Distributed Computing; ACM: Delft, The Netherlands 3. Michael, S., Knezek, P., Stobie, E., Henschel, R., Simms, S. (2010) A Revolutionary New Paradigm for the Reduction and Analysis of Astronomical Images. escience 2010; IEEE Computer Society Press, USA. 4. Henschel, R., Michael, S., Simms, S. (2010). A Distributed Workflow for an Astrophysical OpenMP Application. Challenges of Large Applications in Distributed Environments 2010; ACM: Chicago, IL Other selected publications: 1. Michael, S., Steiman-Cameron, T., Durisen, R. H., Boley, A. (2012) Convergence Studies of Mass Transport in Disks with Gravitational Instabilities I: The Constant Cooling Time Case. ApJ, 746, Michael, S., Durisen, R. H., Boley, A. (2011) Migration of Gas Giant Planets in Gravitationally Unstable Disks. ApJ, 737, L42 3. Michael, S., Durisen, R. H. (2010). Stellar Motion Induced by Gravitational Instabilities in Protoplanetary Discs. MNRAS, 406, 279 Synergistic Activities 1. A pioneer in the area of using wide area file systems (specifically Lustre) to facilitate geographically distributed workflows in a variety of scientific disciplines. Collaborators & Other Affiliations Collaborators and Co-Editors: Boley, Aaron (University of Florida), Pickett, Megan (Lawrence University), Hartquist, Thomas (Leeds University), Steiman-Cameron, Thomas (Indiana University), Link, Matthew (Indiana University), 24 of 65

21 Breckenridge, William (Mississippi State University), Simms, Stephen (Indiana University), Henschel, Robert (Indiana University), Durisen, Richard (Indiana University), Knezek, Patricia (WIYN), Stobie, Elizabeth (NOAO), Zhen, Li (Intel Inc.), Barton, Eric (Intel Inc.), Knepper, Richard (Indiana University), Stewart, Craig (Indiana University) Graduate and Post Doctoral Advisors: Durisen, Richard (Indiana University) Thesis Advisor and Postgraduate-Scholar Sponsor (for the following people in the last 5 years): None Total number of graduate students supervised: 0 25 of 65

22 Michael D. Young Senior Developer, Pervasive Technology Institute Indiana University Role in this proposal: Senior Personnel Professional Preparation University of Hawai i, Hilo Astronomy B.S., 2007 Indiana University Indiana University Astronomy Astronomy M.A., 2009 Ph.D., 2016 Appointments Senior Developer, PTI, Indiana University Research Assistant, Astronomy Dept., Indiana University Associate Instructor, Astronomy Dept., Indiana University Products Selected relevant products: 1. Young, M. D.; Kotulla, R.; Gopu, A.; Liu, W Integrating the ODI-PPA scientific gateway with the QuickReduce pipeline for on-demand processing. Proc. SPIE 9152, Software and CyberInfrastructure for Astronomy III, 91522U (July 18, 2014); doi: / Young, M. D.; Gopu, A.; Hayashi, S.; StarDock: shipping customized computing environments to the data. Proc. SPIE 9913, Software and CyberInfrastructure for Astronomy III, (August 8, 2016); doi: / Young, M. D.; Michael, S.; Big Data Challenges in the Blanco DECam Bulge Survey. In ASP Conference Series TBD. Astronomical Data Analysis Software and Systems XXV. 4. Young, M. D.; Gopu, A.; Hayashi, S.; Cox, J. A FRIAA: A FRamework for Web-based Interactive Astronomy Analysis using AMQP Messaging. In ASP Conference Series Volume 475, Astronomical Data Analysis Software and Systems XXII 5. Young, M. D.; Gopu, A.; Hayashi, S Source Explorer: Towards web-browser based tools for astronomical source visualization and analysis. In ASP Conference Series Volume 485, Page 269, Astronomical Data Analysis Software and Systems XXIII. Other relevant products: 1. Young, M. D., Dowell, J. L., & Rhode, K. L. Globular Cluster Systems of Spiral and S0 Galaxies: Results from WIYN Imaging of NGC 1023, NGC 1055, NGC 7332, and NGC 7339 The Astronomical Journal, Volume 144, pp , (2012). 2. Rhode, K. L., Windschitl, J. L., & Young, M. D. WIYN Imaging of the Globular Cluster Systems of the Spiral Galaxies NGC 891 and NGC 4013 The Astronomical Journal, Volume 140, Issue 2, pp (2010) 3. Gopu, A.; Hayashi, S.; Young, M. D.; Harbeck, D.; Boroson, T.; Liu, W.; Kotulla, R.; Shaw, R.; Henschel, R.; Rajagopal, J.; Stobie, E.; Knezek, P.; Martin, P.; Archbold, K ODI - Portal, Pipeline, and Archive (ODI-PPA): a web-based astronomical compute archive, visualization, and analysis service. Proc. SPIE 9152, Software and CyberInfrastructure for Astronomy III, 91520E (July 18, 2014); doi: / of 65

23 4. Gopu, A.; Hayashi, S.; Young, M. D Image Explorer: Astronomical Image Analysis on an HTML5-based Web Application. In ASP Conference Series Volume 485, Page 417, Astronomical Data Analysis Software and Systems XXIII. Synergistic Activities 1. Developed archival database and data transfer system to store the raw and reduced data products of the WIYN-ODI instrument and pipeline securely and redundantly in multiple physical locations. 2. Developed and maintained portal front-end for access to archive and interactive analysis tools running on Indiana University s Big Red II supercomputer. 3. Refactored code from the ODI-PPA project into the offshoot EMC-PPA project for electron microscopy data. 4. Constructed portal, database, and data querying service for Blanco DECam Bulge Survey dataset, processing billions of astronomical observations and hundreds of millions of objects. 5. Constructed customized portal for Spectral Archive (SpArc) project at Indiana University to preserve and disperse decades of legacy astronomical data. Collaborators & Other Affiliations Collaborators and Co-Editors: Cox, Jeffrey (Indiana University); Dowell, Jessica (Indiana University); Gopu, Arvind Indiana University); Harbeck, Daniel (WIYN, Inc.); Hayashi, Soichi (Indiana University & Open Science Grid); Henschel, Robert (Indiana University); Knezek, Patricia (National Science Foundation); Kotulla, Ralf (University of Wisconsin Milwaukee); Liu, Wilson (WIYN, Inc.); Rajagopal, Jayadev (WIYN, Inc.); Rhode, Kathy (Indiana University); Shaw, Richard (National Optical Astronomy Observatory); Catherine Pilachoswki (Indiana University); Michael Rich (UCLA); Christian Johnson (Harvard-Smithsonian Center for Astrophysics); Will Clarkson (University of Michigan - Dearborn) Graduate and Post Doctoral Advisors: Rhode, Kathy (Master s and Doctoral Thesis advisor), Astronomy, Indiana University 27 of 65

24 Emerging Areas of Research: Computational Astrophysics and the Formation of Structure in the Universe 1. Introduction Is it possible to create an accurate model universe with a simple push of a button? Can we correlate the positions and motions of billions of stars to build a living model of the Milky Way galaxy? With high performance computing and applications of big data science, these goals will be achievable in the era of exascale computing (10 18 flops per second). Our proposed Emerging Area of Research program will set the stage for Indiana University to be a leading player in the application of high performance computing to astronomical research problems, with a particular focus on understanding the formation and evolution of structure on all size scales (from planets to the cosmic web). This initiative will engage researchers from a variety of fields, including astronomy, statistics, math, physics, and informatics, to work on transformative research programs that utilize high performance computing and applications of big data science to address the biggest questions of all: How did we get here and where are we going? With large data sets and complex numerical models, astronomers have always pushed the forefront of computational science. The field is now poised to make the next big step in computational astrophysics. During the next decade, high performance computing at the level of exascale computations will be required for analysis of data acquired with new observational facilities, such as the Square Kilometer Array, and for the computation of the most accurate numerical models to compare with observational data. Of key import is the ability of such models to incorporate astrophysical phenomena on a diverse range of physical scales (Figure 1), which is particularly challenging since it requires either immense models with finely spaced grids or an ability to adapt the grid size during the evolution of the model to adjust to the spatial scale of interest at any particular time step or location. Indeed, the time resolution of each step in the grid also adds to the computational cost associated with the numerical model. Thus, even with current supercomputers, numerical simulations often require months of computer time to complete. However, the next generation of supercomputers exascale computing will enable astronomers to probe the full dynamic range of spatial scales and time resolution in their models. With better sampling (both spatial and temporal), these models will also be able to better incorporate the complex physical processes associated with star formation, gas accretion, feedback, and galaxygalaxy interactions. On the observational side, astronomers have a long history of surveying the sky and creating astronomical catalogs, which are then used to identify sources for additional study. With the advent of sensitive digital detectors and the use of dedicated telescopes to implement such surveys, recent sky surveys have resulted in an explosion of data (see Figure 2) from which diverse studies are now possible. During the next decade, the Large Synoptic Survey Telescope (LSST), currently under construction in Chile, will be dedicated to obtaining multi-filter images of the night sky twice per week and is expected to yield a final catalog of 37 billion stars and galaxies. In addition to identifying new astronomical objects, the survey will be used to identify transient and variable sources (objects that appear in only a few observations or whose intensity varies significantly as a function of time) and is expected to generate 15 Terabytes of data each night. The computational challenge posed by such large data volumes, and the desire to cross-correlate the LSST data with 28 of 65 1

25 Figure 1: Astronomical phenomena occur on a wide variety of spatial scales. Shown here are images of star formation in our Galaxy (Pillars of Creation, diameter ~4 light years); a star cluster (M3, diameter ~160 light years); nearby galaxies (M51, diameter ~100,000 light years); a galaxy cluster (Abel 1689, diameter ~1.3 million light years); and an illustration of the cosmic web from the BOSS Survey (6 billion light years 4.5 billion light years and 500 million light years thick). Accurate numerical simulations of the universe need to include physical processes on all of these spatial scales in order to model the transformative processes associated with galaxy formation and evolution. Image sources include: other datasets, will require both high performance computing and applications of big data approaches to data analysis. In combination with other large survey projects, such as Gaia, a European initiative to measure the location, proper motion, and intensity of a least a billion stars in our Galaxy, it will be possible to map the structure of our Galaxy in exquisite detail, which will enable studies of the formation and evolution of structural features such as the bulge, the bar, and spiral arms. While driven by astronomical research questions, these projects require access to, and development of, high performance computing techniques, which is a research area in its own right. IU s superb cyber infrastructure will enable us to pursue these initiatives while also providing the impetus to develop the next generation of supercomputers and associated software. Indeed, designing and developing software that can make full use of existing computational resources, and can rapidly scale to future systems, remains an extant challenge for the high performance computing community. Thus, these astronomical initiatives will build on IU s current strengths in high performance computing and set the stage for IU to be recognized as a leader in computational astrophysics research. In this proposal, we describe current efforts to investigate the formation and evolution of structure in the Universe and how the addition of graduate students, postdoctoral scholars, and three additional faculty lines two numerical modelers with expertise in galaxy formation and star formation, respectively, and a survey scientist with interest in structures in our Galaxy will make IU a major center for computational astrophysics research. As part of the Emerging Areas of Research initiative, we will further highlight IU s new expertise in computational astrophysics by sponsoring both a workshop and an international conference in Bloomington. Our plan to host internationally recognized experts as part of a visiting researcher program will provide further networking opportunities for our students and raise the profile of our department and IU. Overall, the opportunities provided by the Emerging Areas of Research initiative will enable an innovative science program that will provide the groundwork to drive astronomy into the era of exascale computing and applications of big data science of 65

26 Figure 2: Left: As an indication of the explosion in astronomical data available from modern sky surveys, we illustrate the approximate number of extragalactic sources known as a function of time, including a projection of the anticipated results from the next generation sky survey, LSST, which will identify ~37 billion stars and galaxies and be completed during the next 10 years. Note the logarithmic scaling. Right: The density of known sources as function of position on the sky as of 2015 January in the NASA Extragalactic Database (NED). The area in red (including the 3 stripes in the south) represents the area covered by the Sloan Digital Sky Survey (SDSS). Even higher source counts are expected from the Large Synoptic Survey Telescope (LSST), which will begin observing the southern sky starting in Source: 2. Specific Aims Our fundamental research aim is to understand the formation and evolution of structures on a diverse range of physical scales, from planetary systems to the largest structures in the Universe. On the time scale of this EAR initiative, we will focus our efforts on small and mid-size scales, including star formation and stellar populations in our Galaxy, the surrounding Local Group environment, and structural evolution of nearby galaxies. Future collaborations may enable us to expand our research directions to include the largest spatial scales, but our current focus on nearby systems is chosen to allow us to have the best observational data to compare with numerical models, since it is difficult to resolve stellar populations and kinematics in distant systems, even with modern space-based telescopes. Indeed, our own Galaxy, the Milky Way, is an ideal test case for models of galaxy evolution, since we can infer its complex star formation history based on a combination of kinematic and chemical tracers for individual stars. Observational studies of other nearby galaxies allow us to expand beyond a test-case of one in order to explore the diverse range of galaxy properties, including parameters such as mass, gas content, star formation history, and environment. Further, while not constrained by observational parameters, numerical models currently have similar subdivisions in terms of spatial scale in order to keep computational speeds within reason. With this EAR initiative, we will build the framework within which results from all spatial scales for both observational and computational data can be combined to yield accurate models of structures in the nearby universe. A critical aspect of our project will be the development of computational techniques and systems that will allow the analysis of large data volumes, complex data sets, and high precision numerical simulations. In addition to addressing the scalability of simulation codes to prepare them for exascale computing on standard architectures, we will evaluate the applicability of emerging computational technologies as they arise. Current examples include new accelerator architectures like the Knight s Landing version of the Xeon Phi accelerator, and new interconnect technologies like Intel s Omni Path interconnect. With these computational advances, we will be able to address several specific projects, which are described below. 30 of 65 3

27 3. Design and Methods The projects described below are the first steps towards our ultimate goals of using the next generation of supercomputers exascale computers to create accurate models of the Universe. These first projects are designed to build the requisite expertise, including observational parameters, computer code, and personnel, to make these goals achievable within the next decade. Our science themes naturally break into two main areas of research: (1) the Milky Way and its surroundings and (2) nearby galaxies. We emphasize, however, that these topics are interrelated, as studies of our Galaxy have the highest resolution (since we are embedded within), but lack the ability to explore the full diversity of galaxy properties found in the Universe, while studies of nearby galaxies are able to explore the full dynamic range of galaxy properties, but are limited in both spatial and time resolution. Fundamentally, we expect the synergy between observational and computational studies of the Milky Way and nearby galaxies to reveal the physical processes that drive the evolution of complex structures and lead to the development of a living model of our home, the Milky Way. 3.1 Structure of the Milky Way and its Surroundings One challenge of astronomical studies is to deduce the nature of a system while we are embedded within it. For centuries, astronomers have used a combination of observational data and numerical calculations to infer underlying structures, even as the Earth spins on its axis and the Solar System is in motion around the center of our Galaxy. Indeed, the first maps of the Milky Way were generated by counting the number of stars observed in deep photographic images; astronomers then created a model to match the star counts in different directions. Such star counts have revealed the presence of spiral arms, a central bulge, a diffuse halo, and a bar at the center of our Galaxy. While the first star catalogs only recorded position and an estimate of each star s apparent brightness, modern star catalogs include significantly more parameters, including information on kinematic motion, elemental abundances, and apparent brightness measured throughout the electromagnetic spectrum (from ultraviolet to infrared), which can be used to infer the temperature and age of each star. During the next decade, two major surveys, Gaia and LSST, will generate catalogs with complex records for billions of stars, providing the opportunity to identify structures based not only on position in the sky, but also on kinematic signatures, chemical signatures, and similar age groupings. It will be a major computational challenge to match the sources in these catalogs, and those identified by other surveys, in order to identify the disparate stellar populations that provide a time-history of the evolution of the Milky Way and the various structures within (Figure 3). The key transformative aspects of this research are the ability to cross-correlate large databases with billions of entries and the ability of cluster-identification algorithms to identify features based on common age, kinematics, or chemical signatures. Similar studies on more sparsely populated datasets revealed the remnant of a low mass galaxy that was accreted by the Milky Way billions of years ago (Ibata et al. 1994, Nature, 370, 194). More recently, a new class of low mass galaxies, known as the ultra-faint dwarfs, were identified in the Sloan Digital Sky Survey based on the apparent clustering of only a handful of individual stars (Willman et al. 2005, Astronomical Journal, 129, 2692). The wealth of data provided by Gaia and LSST will allow us to identify even smaller and fainter structures to compare with those predicted from hierarchical accretion models of galaxy formation (see Figure 3). 31 of 65 4

28 Figure 3: Examples of stellar streams in the Milky Way and nearby spiral galaxies. (left) Rendition of the multiple stellar streams expected in the Milky Way, as predicted by cold dark matter hierarchical accretion models. Each stream is color-coded by its progenitor galaxy (credit: P. Harding). (center) Distribution of spatially coherent streams currently known in the Milky Way (credit: B. Pila Diez). (right) Diffuse stellar streams identified in the outskirts of the nearby galaxy M63 (credit: L. van Zee). We will apply clusteridentification algorithms to discriminate between different stellar populations in order to find faint and diffuse stellar streams within the billions of stars in the catalogs generated by the Gaia and LSST surveys. Image sources include: Observational and theoretical approaches To prepare for these future large datasets, we have begun a pathfinder project, the Blanco DECam Bulge Survey (BDBS), to understand the stellar populations comprising the Milky Way s central bulge, the massive star-dense, spherical core of our Galaxy. Like most spiral galaxies, our own Milky Way s disk surrounds a central bulge of stars that includes about a quarter of all the stars in our Galaxy. Galaxy bulges are critical ingredients in models of structure formation and evolution in galaxies. Our own bulge is the one we can study in greatest detail, and provides insights needed to understand structure formation in other galaxies. The stars in the Bulge are mostly old, and the region contains very little gas or current star formation. After decades of detailed study, however, astronomers still do not know the origin of our bulge, whether it formed rapidly in the early history of the Milky Way, or more slowly, growing and evolving over longer time scales, as it fed from the Galactic disk. BDBS utilizes the 520 mega-pixel Dark Energy Camera on the Blanco 4-m telescope in Chile to image a 200-square-degree region of the Milky Way Bulge in six filters (ugrizy) ranging from the ultraviolet to the near infrared, and reaches a depth sufficient to measure the properties of old, lowmass stars like the sun, still burning hydrogen in their cores. Using multiple filters allows us to estimate ages, distances, and compositions for stars in the Bulge. Follow-up spectroscopy of the brightest targets identified using the survey and comparisons to earlier surveys will provide kinematic data to understand the stars motions. In collaboration with the Scientific Applications group at UITS Research Technologies division, we have extracted ~15 billion source detections from the more than 350 thousand images obtained as part of the BDBS survey. Given the wide and deep nature of the data, traditional approaches are unsuitable for all but the simplest of investigations of the data. To support BDBS data services, a Hadoop cluster consisting of five of the 16 Data Intensive nodes was implemented on Indiana University s Karst supercomputer cluster. The photometry and coordinates from the individual exposures have been parsed and combined into a full, combined catalog. The catalog includes ~365 million matched sources with photometric measurements in at least 2 filters. This number is 32 of 65 5

29 expected to rise with additional data processing. Reddening maps have been applied to the data to correct all photometric measurements for the dimming effects of intervening gas and dust. A prototype BDBS data portal is available to view and download data from the catalog. We can search by position and with any number of magnitude and color limits, and we are in the process of adding functionality to the portal, including the ability to generate color-magnitude and color-color plots from catalog data. The collaboration is now turning to science investigations using the BDBS catalog and science portal. With the BDBS source catalog we will be mapping large scale structures in the Bulge, exploring metallicity gradients, identifying special stellar populations, and examining multi-color, color magnitude diagrams of Bulge globular star clusters. The BDBS will allow us to resolve key questions about the origin and evolution of the Milky Way s bulge and, by extension, to better interpret the origin of structure in all galaxies. Of key importance in these stellar population studies is the correction for foreground and background contamination and for a proper statistical treatment of the cluster-finding algorithms used to identify special stellar populations within the dataset. Specifically, standard statistical clustering techniques are not as well suited to finding star clusters with non-standard spatial distributions, which are expected as a result of dynamical interactions within themselves and with the underlying Galactic background. However, a dynamic partition model, which accounts for star formation, evolution, and death, is more likely to identify these groupings successfully. Fitting these dynamical models requires the use of stochastic simulation models, since a dynamical partition model for the Milky Way will have billions of parameters whose distributions are not easily summarized. Modern Markov Chain Monte Carlo methods based on Hamiltonian dynamics on Reimannian manifolds provide a fruitful avenue for fitting these dynamic models and learning the underlying distributions of physical parameters. Nonetheless, further development is required for both the theoretical basis of these models and the computational algorithms that will enable efficient application of inherently sequential methods on high performance parallel computing platforms. When implemented, this statistical analysis of stars in the Milky Way will identify star clusters and star groupings that form the basis of structure in our Galaxy. Star clusters are also considered one of the prime tracers of the star formation history of the Galaxy. Originally thought to be simple systems with a single age and chemical enrichment history for all stars in the cluster, numerous spectroscopic and photometric observational studies now provide strong evidence that most globular clusters host multiple stellar populations characterized by different chemical properties. The discovery of multiple stellar populations represents a major paradigm shift in the field and raises many fundamental questions regarding the formation and dynamical history of star clusters and the role they may have played in the assembly of their host galaxies. Identifying sources of gas out of which multiple stellar populations formed and the structural properties required to trigger the formation of multiple stellar populations, understanding the role of the external galactic environment and tidal field in the formation of multiple-populations, and in turn, the possible contribution of dissolved clusters to the assembly of the host galaxy stellar content are just a few of the issues currently under investigation. To tackle these questions, it is crucial to combine expertise from many sub-areas of astronomy, including star formation, stellar evolution and nucleosynthesis, and the dynamical evolution of star clusters and galaxies. Numerical simulations are a key aspect of this research and current efforts utilize IU s existing supercomputer Big Red II to explore the dynamical evolution of star clusters. For these simulations, the GPU nodes are essential since the code used can leverage GPUs to speed up the most computationally expensive parts of the simulation. In addition, the availability of a large 33 of 65 6

30 number of GPU nodes enables the exploration of a large number of different initial conditions of star cluster structural parameters and thereby generates an extensive suite of simulations New Directions Star formation is one of the key transformative processes in galaxy evolution, as gaseous material is cycled through a stellar component, yielding a long-lived stellar population of low mass stars and releasing the products of stellar nucleosynthesis from high mass stars back into the gaseous component. Stellar formation, evolution, and interaction with the surrounding interstellar medium are some of the key processes in galaxy evolution. The study of stellar formation and evolution requires an approach that incorporates a multitude of physical processes over spatial and temporal scales spanning many orders of magnitude. Many of the physical processes, including magnetohydrodynamics, nucleosynthesis, chemical reactions, self-gravity, and thermodynamic processes, require much more research to understand their interplay in stellar evolution. Star formation is mediated and regulated by several feedback loops, which are still poorly understood. Progress requires highly detailed and sensitive numerical simulations that treat all of the relevant physical processes in a consistent manner. A variety of novel numerical techniques have been, or are in the process of being, developed to meet these challenges, including multi-point stenciling techniques, adaptive mesh refinement, and sub-grid physics/modeling. Many of these techniques have yet to be adapted to cutting-edge high performance computing hardware technologies, such as accelerators or many-core architectures. As described in Section 7, this important aspect of our project will require the addition of a new faculty member to provide the relevant expertise and technical skills. Finally, although our group is currently working on medium-sized pre-cursor surveys of stellar populations in the Milky Way, we desire an additional new faculty member whose expertise will include analysis of data from large surveys, with a particular interest in exploring the structure of the Milky Way galaxy and the Local Group. Specifically, this new faculty member will be able to apply big data science techniques, including deep learning neural networks for automated classification and discovery, to the next-generation astronomical surveys to identify stellar groups and streams within and near our Galaxy. Such stellar structures provide a record of the assembly history of our Galaxy and, in addition, can be used to trace the Galaxy s dark matter potential. The extent and number of stellar streams provide critical observational evidence with which to test models of galaxy formation and evolution within the current cold dark matter hierarchical galaxy formation paradigm. In conjunction with the state-of-the art numerical simulations of galaxy formation and evolution that will be produced as part of this project (see below), the observational evidence of structural features within our Galaxy will reveal the assembly history of the Milky Way and, by extension, the evolutionary process of massive spiral galaxies. The synthesis of the above projects will provide all of the pieces necessary to render survey data into a living model of the Milky Way. With this planned analysis, our group will be one of the national leaders in the visualization and analysis of large survey data. Furthermore, the novel software and analysis tools developed here will provide the platform for further advances in numerical simulation and big data science for the next generation of supercomputers, with potential applications well beyond those envisioned here. 34 of 65 7

31 3.2 Nearby Galaxies While observations of the Milky Way and Local Group galaxies have the advantage of exquisite spatial resolution, observations of other nearby galaxies are necessary to explore the full dynamic range of galaxy properties. In particular, the distinctly different structural features of gas-rich spiral galaxies and gas-poor elliptical galaxies are indicative of divergent evolutionary histories for these systems that are driven by a variety of physical processes, all of which must be understood in order to build a representative model Universe. Key transformative processes include star formation activity, feedback from active galactic nuclei, gas accretion, and galaxy interactions. At the present time, numerical simulations use prescriptive recipes to account for many of these processes, as the model grids do not have sufficient spatial resolution to warrant more accurate representations. However, in the era of exascale computing, it will be possible to build numerical models that sample the full spatial and temporal ranges of interest. We thus require measurements of galaxy properties that include sufficient spatial information on stellar populations, gas distribution and kinematics, and dust content to provide accurate constraints on the model results, and to yield sufficient insight into the physics behind these processes to provide input into the numerical simulations. During the next decade, major observational initiatives include the Large Synoptic Survey Telescope (LSST), the James Webb Space Telescope (JWST), and the Wide Field Infrared Survey Telescope (WFIRST), all of which will produce deep multi-wavelength (optical and/or infrared) images of nearby galaxies, among other data products. These surveys will be complemented by targeted observations of individual galaxies to trace the gaseous and dust distributions, using facilities such as the Atacama Large Millimeter/submillimeter Array (ALMA) and the Very Large Array (VLA), and moderate-aperture ground-based telescopes to image the ionized gas component. There are many computational challenges associated with analysis of data obtained with different telescopes and at different parts of the electromagnetic spectrum. In particular, generation of appropriately scaled and sampled images requires rapid computational speeds and the ability to store large volumes of data, as matched datasets. At the same time, numerical simulations of galaxy formation and evolution will require the speed and power of the next generation of supercomputers in order to include the detailed physics of the processes that drive galaxy evolution. The key transformative aspect of this research is the use of high performance computing to generate spatially matched multi-wavelength datasets from a variety of observational facilities and, also, to create accurate numerical simulations of galaxy evolution which include a large dynamic range in both spatial and temporal resolution. In addition, this program will require an effective means to share the large datasets created by these observational and computational projects with the international scientific community and the public Properties of Nearby Galaxies As a precursor to the more extensive datasets anticipated from the LSST and WFIRST surveys, we are currently investigating the stellar populations and gaseous content of a modest statistical sample of nearby galaxies. This precursor project is designed to investigate the growth and evolution of the stellar component in spiral galaxies by using observations that trace the dominant stellar population on different timescales and, also, by using the gas distributions and kinematics to search for evidence of recent interactions and accretion events. However, since the key signatures of star formation, gas distribution, and stellar content are traced by light emitted at very different wavelengths (from the ultraviolet to the radio, see Figure 4), the data required for this analysis have been collected on several different facilities. Thus, we must first address the fundamental problem 35 of 65 8

32 Figure 4: Multi-wavelength images of the nearby galaxy NGC 3344, illustrating the different structural features that are visible at different wavelengths. The plots on the right trace the galaxy color (top) and specific star formation rate (bottom) as a function of radius. NGC 3344 has an unusually strong color gradient (built over a time period of billions of years), which is not matched by a similar gradient in the specific star formation rate (measured over a time period of hundreds of millions of years). The mismatch between stellar population gradients on these two different time scales suggests that a recent event has enhanced the current star formation rate at all radii in this galaxy. Evidence of such a trigger may be gleaned from the extended neutral hydrogen distribution and kinematics. Results from numerical simulations of galaxy formation and evolution can be used to predict both the frequency of such triggering events and the impact on structural features in the gaseous and stellar components. The synergy between observational and computational research programs enables a more complete understanding of the physical processes that drive galaxy evolution. that every observation has a different sensitivity, spatial resolution, and field-of-view prior to the planned analysis. To overcome these issues, data taken with different facilities need to be registered, smoothed, and either mosaicked or cropped so that the final data products include the same sky area with the same spatial resolution. In addition, after re-projection, the sensitivity of each image must be re-measured, as the re-sampling process changes the noise characteristics. This computationally intensive process can be streamlined if the data are from astronomical surveys with uniform observational parameters, but often requires individual attention due to variations in data quality or observational parameters. Not unexpectedly, these data sets are large. For example, with technological advances in radio instrumentation, the raw data from radio telescopes for projects such as these are on the order of hundreds of Gbytes for each galaxy. Thus, the computational power required for processing are significant, as are the data storage requirements for the intermediate data products. The current project makes use of the Scholarly Data Archive (SDA) for data storage and local data servers for data processing, but the next generation of such multi-wavelength surveys, in the WFIRST and LSST era, will require correspondingly more data storage and computing power. Ultimately, such multi-wavelength studies of large samples of galaxies will reveal the properties of the underlying stellar populations and the frequency of star formation triggers in the nearby Universe, a critical component in hierarchical models and numerical simulations of galaxy evolution. One of the other current challenges in hierarchical models of galaxy evolution is the formation and retention of the smallest galaxies. Specifically, in a hierarchical model, where large galaxies are formed by accretion of small galaxies (a.k.a. dwarf galaxies), it is important to know what is the 36 of 65 9