About

Douglas Finkbeiner is a Professor of Astronomy and of Physics at Harvard University. He holds a Ph.D. in Physics from Berkeley, obtained in 1999, and has a background that includes a double major in Physics and German from the University of Michigan in 1994. His professional experience includes being a Hubble Fellow and Russell Fellow at Princeton Astronomy from 2001 to 2006. Since 2006, he has been a faculty member in the Harvard Astronomy Department, and since 2009, also in the Harvard Physics Department. He is currently the Director of the SIAG since 2022. His research interests involve astrophysics and astronomy, with a focus on dust mapping, H-alpha observations, and related topics, as indicated by his association with resources such as skymaps.info. Finkbeiner has also been involved in academic collaborations and has supervised numerous graduate students, including Tracy R. Slatyer, Sui Ann Mao, Edward F. Schlafly, Tongyan Lin, Meng Su, Aaron Meisner, Gregory Green, Stephen K. N. Portillo, Tansu Daylan, Albert Lee, Catherine S. Zucker, Joshua S. Speagle, Ioana Zelko, Jun Yin, Andrew Saydjari, Nayantara Mudur, Justina Yang, and Ana Sofia Uzsoy. His contact information includes a phone number, fax, and email at the Harvard-Smithsonian Center for Astrophysics.

Research topics

• Computer Science
• Astronomy
• Physics
• Remote sensing
• Astrophysics
• Geography
• Environmental science
• Geology

Selected publications

• Effect of local environment on Ly$α$ line profile in DESI/ODIN LAEs

  HAL (Le Centre pour la Communication Scientifique Directe) · 2026-01-21

  preprint

  International audience

  Publisher

• A Deep, High-angular-resolution 3D Dust Map of the Southern Galactic Plane

  The Astrophysical Journal · 2025-10-03 · 7 citations

  articleOpen accessSenior author

  Abstract We present a deep, high-angular-resolution 3D dust map of the southern Galactic plane over 239° &lt; l &lt; 6° and ∣ b ∣ &lt; 10° built on photometry from the DECaPS2 survey, in combination with photometry from VISTA Variables in the Via Lactea, the Two Micron All Sky Survey, and “Unofficial” Wide-field Infrared Survey Explorer and parallaxes from Gaia Data Release 3 where available. To construct the map, we first infer the distance, extinction, and stellar types of over 700 million stars using the brutus stellar inference framework with a set of theoretical MESA Isochrone and Stellar Tracks ( MIST ) stellar models. Our resultant 3D dust map has an angular resolution of <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mn>1</mml:mn> <mml:mo accent="false">′</mml:mo> <mml:mtext/> <mml:mspace width="0.1em"/> <mml:mtext/> <mml:mspace width="0.1em"/> </mml:math> , roughly an order of magnitude finer than existing 3D dust maps and comparable to the angular resolution of the Herschel 2D dust emission maps. We detect complexes at the range of distances associated with the Sagittarius-Carina and Scutum-Centaurus arms in the fourth quadrant, as well as more distant structures out to a maximum reliable distance of d ≈ 10 kpc from the Sun. The map is sensitive up to a maximum extinction of roughly A V ≈ 12 mag. We publicly release both the stellar catalog and the 3D dust map, the latter of which can easily be queried via the Python package dustmaps . When combined with the existing Bayestar19 3D dust map of the northern sky, the DECaPS 3D dust map fills in the missing piece of the Galactic plane, enabling extinction corrections over the entire disk ∣ b ∣ &lt; 10°. Our map serves as a pathfinder for the future of 3D dust mapping in the era of LSST and Roman, targeting regimes accessible with deep optical and near-infrared photometry but often inaccessible with Gaia.

  PublisherDOI

• Deriving Stellar Properties, Distances, and Reddenings using Photometry and Astrometry with BRUTUS

  ArXiv.org · 2025-03-03

  articleOpen access

  We present brutus, an open source Python package for quickly deriving stellar properties, distances, and reddenings to stars based on grids of stellar models constrained by photometric and astrometric data. We outline the statistical framework for deriving these quantities, its implementation, and various Galactic priors over the 3-D distribution of stars, stellar properties, and dust extinction (including $R_V$ variation). We establish a procedure to empirically calibrate MIST v1.2 isochrones by using open clusters to derive corrections to the effective temperatures and radii of the isochrones, which reduces systematic errors on the lower main sequence. We also describe and apply a method to estimate photometric offsets between stellar models and observed data using nearby, low-reddening field stars. We perform a series of tests on mock and real data to examine parameter recovery with MIST under different modeling assumptions, illustrating that brutus is able to recover distances and other stellar properties using optical to near-infrared photometry and astrometry. The code is publicly available at https://github.com/joshspeagle/brutus.

  PublisherOA PDF

• The Roman View of Strong Gravitational Lenses

  ArXiv.org · 2025-06-03

  preprintOpen access

  Galaxy-galaxy strong gravitational lenses can constrain dark matter models and the Lambda Cold Dark Matter cosmological paradigm at sub-galactic scales. Currently, there is a dearth of images of these rare systems with high signal-to-noise and angular resolution. The Nancy Grace Roman Space Telescope (hereafter, Roman), scheduled for launch in late 2026, will play a transformative role in strong lensing science with its planned wide-field surveys. With its remarkable 0.281 square degree field of view and diffraction-limited angular resolution of ~0.1 arcsec, Roman is uniquely suited to characterizing dark matter substructure from a robust population of strong lenses. We present a yield simulation of detectable strong lenses in Roman's planned High Latitude Wide Area Survey (HLWAS). We simulate a population of galaxy-galaxy strong lenses across cosmic time with Cold Dark Matter subhalo populations, select those detectable in the HLWAS, and generate simulated images accounting for realistic Wide Field Instrument detector effects. For a fiducial case of single 146-second exposures, we predict around 160,000 detectable strong lenses in the HLWAS, of which about 500 will have sufficient signal-to-noise to be amenable to detailed substructure characterization. We investigate the effect of the variation of the point-spread function across Roman's field of view on detecting individual subhalos and the suppression of the subhalo mass function at low masses. Our simulation products are available to support strong lens science with Roman, such as training neural networks and validating dark matter substructure analysis pipelines.

  PublisherOA PDFDOI

• The Roman View of Strong Gravitational Lenses

  The Astrophysical Journal · 2025-06-04 · 4 citations

  articleOpen accessCorresponding

  Abstract Galaxy–galaxy strong gravitational lenses can constrain dark matter models and the Lambda cold dark matter cosmological paradigm at subgalactic scales. Currently, there is a dearth of images of these rare systems with high signal-to-noise ratio (SNR) and angular resolution. The Nancy Grace Roman Space Telescope (hereafter Roman), scheduled for launch in late 2026, will play a transformative role in strong-lensing science with its planned wide-field surveys. With its remarkable 0.281 square degree field of view and diffraction-limited angular resolution of ~0 <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mover> <mml:mrow> <mml:mo>.</mml:mo> </mml:mrow> <mml:mrow> <mml:mtext>″</mml:mtext> </mml:mrow> </mml:mover> </mml:math> 1, Roman is uniquely suited to characterizing dark matter substructure from a robust population of strong lenses. We present a yield simulation of detectable strong lenses in Roman’s planned High Latitude Wide Area Survey (HLWAS). We simulate a population of galaxy–galaxy strong lenses across cosmic time with cold dark matter subhalo populations, select those detectable in the HLWAS, and generate simulated images accounting for realistic Wide Field Instrument detector effects. For a fiducial case of single 146 s exposures, we predict around 160,000 detectable strong lenses in the HLWAS, of which about 500 will have sufficient SNR to be amenable to detailed substructure characterization. We investigate the effect of variation of the point-spread function across Roman’s field of view on detecting individual subhalos and the suppression of the subhalo mass function at low masses. Our simulation products are available to support strong-lens science with Roman, such as training neural networks and validating dark matter substructure analysis pipelines.

  PublisherDOI

• A Fast Periodicity Detection Algorithm Sensitive to Arbitrary Waveforms

  ArXiv.org · 2025-02-01

  preprintOpen access1st authorCorresponding

  A reexamination of period finding algorithms is prompted by new large area astronomical sky surveys that can identify billions of individual sources having a thousand or more observations per source. This large increase in data necessitates fast and efficient period detection algorithms. In this paper, we provide an initial description of an algorithm that is being used for detection of periodic behavior in a sample of 1.5 billion objects using light curves generated from Zwicky Transient Facility (ZTF) data (Bellm et al. 2019; Masci et al. 2018). We call this algorithm "Fast Periodicity Weighting" (FPW), derived using a Gaussian Process (GP) formalism. A major advantage of the FPW algorithm for ZTF analysis is that it is agnostic to the details of the phase-folded waveform. Periodic sources in ZTF show a wide variety of waveforms, some quite complex, including eclipsing objects, sinusoidally varying objects also exhibiting eclipses, objects with cyclotron emission at various phases, and accreting objects with complex waveforms. We describe the FPW algorithm and its application to ZTF, and provide efficient code for both CPU and GPU.

  PublisherOA PDFDOI

• Improving Radial Velocities by Marginalizing over Stars and Sky: Achieving 30 m s⁻¹ RV Precision for APOGEE in the Plate Era

  The Astronomical Journal · 2025-02-25 · 2 citations

  articleOpen access

  Abstract The radial velocity catalog from the Apache Point Observatory Galactic Evolution Experiment (APOGEE) is unique in its simultaneously large volume and high precision as a result of its decade-long survey duration, multiplexing (600 fibers), and spectral resolution of R ∼ 22,500. However, previous data reductions of APOGEE have not fully realized the potential radial velocity (RV) precision of the instrument. Here we present an RV catalog based on a new reduction of all 2.6 million visits of APOGEE DR17 and validate it against improved estimates for the theoretical RV performance. The core ideas of the new reduction are the simultaneous modeling of all components in the spectra, rather than a separate subtraction of point estimates for the sky, and a marginalization over stellar types, rather than a grid search for an optimum. We show that this catalog, when restricted to RVs measured with the same fiber, achieves noise-limited precision down to 30 m s −1 and delivers well-calibrated uncertainties. We also introduce a general method for calibrating fiber-to-fiber constant RV offsets and demonstrate its importance for high RV precision work in multifiber spectrographs. After calibration, we achieve 47 m s −1 RV precision on the combined catalog with RVs measured with different fibers. This degradation in precision relative to measurements with only a single fiber suggests that refining line spread function models should be a focus in the Sloan Digital Sky Survey V to improve the fiber-unified RV catalog.

  PublisherDOI

• The Nineteenth Data Release of the Sloan Digital Sky Survey

  ArXiv.org · 2025-07-09 · 4 citations

  preprintOpen access

  Mapping the local and distant Universe is key to our understanding of it. For decades, the Sloan Digital Sky Survey (SDSS) has made a concerted effort to map millions of celestial objects to constrain the physical processes that govern our Universe. The most recent and fifth generation of SDSS (SDSS-V) is organized into three scientific ``mappers". Milky Way Mapper (MWM) that aims to chart the various components of the Milky Way and constrain its formation and assembly, Black Hole Mapper (BHM), which focuses on understanding supermassive black holes in distant galaxies across the Universe, and Local Volume Mapper (LVM), which uses integral field spectroscopy to map the ionized interstellar medium in the local group. This paper describes and outlines the scope and content for the nineteenth data release (DR19) of SDSS and the most substantial to date in SDSS-V. DR19 is the first to contain data from all three mappers. Additionally, we also describe nine value added catalogs (VACs) that enhance the science that can be conducted with the SDSS-V data. Finally, we discuss how to access SDSS DR19 and provide illustrative examples and tutorials.

  PublisherOA PDFDOI

• Deep Learning for Clouds and Cloud Shadow Segmentation in Methane Satellite and Airborne Imaging Spectroscopy

  SSRN Electronic Journal · 2025-01-01 · 1 citations

  preprintOpen access
  PublisherDOI

• A Fast Periodicity Detection Algorithm Sensitive to Arbitrary Waveforms

  Publications of the Astronomical Society of the Pacific · 2025-05-01 · 2 citations

  articleOpen access1st authorCorresponding

  Abstract A reexamination of period-finding algorithms is prompted by new large-area astronomical sky surveys that can identify billions of individual sources having a thousand or more observations per source. This large increase in data necessitates fast and efficient period detection algorithms. In this paper, we provide an initial description of an algorithm that is being used for the detection of periodic behavior in a sample of 1.5 billion objects using light curves generated from Zwicky Transient Facility (ZTF) data. We call this algorithm “Fast Periodicity Weighting” (FPW), derived using a Gaussian Process formalism. Periodic sources in ZTF show a wide variety of waveforms, some quite complex, including eclipsing objects, sinusoidally varying objects also exhibiting eclipses, objects with cyclotron emission at various phases, and accreting objects with complex waveforms. A major advantage of the FPW algorithm is that it is sensitive to a broad range of waveforms. We describe the FPW algorithm and its application to ZTF, and provide efficient code for both CPU and GPU.

  PublisherDOI

Recent grants

• Exploring the Galaxy: 3-Dimensional Structure and Stellar Streams

  NSF · $337k · 2016–2021

• Mapping Dust in 3-D with Pan-STARRS

  NSF · $317k · 2013–2017

Frequent coauthors

• David J. Schlegel

  103 shared

• Edward F. Schlafly

  Space Telescope Science Institute

  73 shared

• Nicolas F. Martin

  Centre National de la Recherche Scientifique

  61 shared

• G. R. Knapp

  60 shared

• Gregory Green

  55 shared

• Robert H. Lupton

  52 shared

• Nikhil Padmanabhan

  51 shared

• M. Fukugita

  Kavli Institute for the Physics and Mathematics of the Universe

  47 shared

Education

• Ph.D., Astronomy

  Harvard University

  1994

• B.A., Physics

  University of California, Berkeley

  1989