arXiv subjects

Gregory Green

Publications and source records attributed to Gregory Green.

9 recordsLinked to original sources

arXiv2026

Enabling Metallicity Measurements of Microlensing Lenses through Multi-band Lens Photometry

We present the photometric--microlensing metallicity method, which enables metallicity measurements of M-dwarf lenses out to bulge distances by combining their multi-band photometry with the angular Einstein radius. The cool atmospheres of M dwarfs contain abundant molecules, whose broad absorption bands make their positions in an optical--NIR color--absolute magnitude diagram sensitive to metallicity. The angular Einstein radius provides the mass--distance constraint needed to infer the lens absolute magnitude, while the intrinsic M-dwarf locus and reddening vector are non-parallel in color--color space, allowing the lens extinction and intrinsic color to be inferred simultaneously from its multi-band photometry, thereby recovering the lens intrinsic position in the metallicity-sensitive color--absolute magnitude diagram. The method requires three-band lens photometry spanning roughly the R, Z, and K bands, making it particularly well suited to Roman through its high-resolution F062, F087, and F213 imaging. With the planned Roman Galactic Bulge Time-Domain Survey (GBTDS) observations plus an additional $\sim$8 hr of F062 imaging per field ($\sim$40 hr in total) roughly a decade after Roman launch, host metallicities could be measured for $\sim$150 planetary systems under the GBTDS yield forecast, with a typical $1\sigma$ precision of $\sim$0.25 dex from our mock-recovery analysis. Applied homogeneously to GBTDS microlensing events with and without detected planets, the method would enable the first measurement of the occurrence--metallicity relation for cold low-mass planets beyond the snow line, constrain the low-metallicity cutoff for their formation, and extend occurrence--metallicity studies into the inner Galaxy.

astro-ph.EP↗

arXiv2026

Deep Learning for Astrophysics: An Open Textbook from the NASA Cosmic Origins AI/ML Science and Technology Interest Group

Recent community assessments identify education as a principal barrier to adopting modern machine learning in astronomy. We present Deep Learning for Astrophysics, a freely available textbook at https://deeplearning4astro.com, curated from the NASA Cosmic Origins Artificial Intelligence and Machine Learning Science and Technology Interest Group (AI/ML STIG) lecture series. The book collects 23 chapters by 17 lecturers across six parts, moving from computational foundations and deep-learning architectures through generative modeling, simulation-based inference, reinforcement learning, and large-language-model agents to the practice of AI-laden science. Many include executable notebooks using astronomical data.

astro-ph.IM↗

arXiv2025

Determining the Milky Way gravitational potential without selection functions

Selection effects, such as interstellar extinction and varying survey depth, complicate efforts to determine the gravitational potential - and thus the distribution of baryonic and dark matter - throughout the Milky Way galaxy using stellar kinematics. We present a new variant of the "Deep Potential" method of determining the gravitational potential from a snapshot of stellar positions and velocities that does not require any modeling of spatial selection functions. Instead of modeling the full six-dimensional phase-space distribution function $f\left(\vec{x},\vec{v}\right)$ of observed kinematic tracers, we model the conditional velocity distribution $p\left(\vec{v}\mid\vec{x}\right)$, which is unaffected by a purely spatial selection function. We simultaneously learn the gravitational potential $\Phi\left(\vec{x}\right)$ and the underlying spatial density of the entire tracer population $n\left(\vec{x}\right)$ - including unobserved stars - using the collisionless Boltzmann equation under the stationarity assumption. The advantage of this method is that unlike the spatial selection function, all of the quantities we model, $p\left(\vec{v}\mid\vec{x}\right)$, $\Phi\left(\vec{x}\right)$, and $n\left(\vec{x}\right)$, typically vary smoothly in both position and velocity. We demonstrate that this "conditional" Deep Potential method is able to accurately recover the gravitational potential in a mock dataset with a complex three-dimensional dust distribution that imprints fine angular structure on the selection function. Because we do not need to model the spatial selection function, our new method can effectively scale to large, complex datasets while using relatively few parameters, and is thus well suited to Gaia data.

astro-ph.GA↗

arXiv2024

Unveiling the Milky Way dust extinction curve in 3D

Interstellar dust is a major foreground contaminant for many observations and a key component in the chemistry of the interstellar medium, yet its properties remain highly uncertain. Using low-resolution spectra, we accurately measure the extinction curve - a diagnostic of the grain properties - for 130 million stars, orders of magnitude more than previously available, allowing us to map its variation in the Milky Way and Magellanic Clouds in 3D in unprecedented detail. We find evidence that accretion is the dominant mechanism of grain growth in moderately dense regions, with coagulation dominating at higher densities. Moreover, we find that the extinction curve flattens in star-forming regions, possibly caused by cycling of large grains formed in molecular clouds, or by preferential destruction of small grains by supernova shocks.

astro-ph.GA↗

arXiv2023

Roman Early-Definition Astrophysics Survey Opportunity: Galactic Roman Infrared Plane Survey (GRIPS)

A wide-field near-infrared survey of the Galactic disk and bulge/bar(s) is supported by a large representation of the community of Galactic astronomers. The combination of sensitivity, angular resolution and large field of view make Roman uniquely able to study the crowded and highly extincted lines of sight in the Galactic plane. A ~1000 deg2 survey of the bulge and inner Galactic disk would yield an impressive dataset of ~120 billion sources and map the structure of our Galaxy. The effort would foster subsequent expansions in numerous dimensions (spatial, depth, wavelengths, epochs). Importantly, the survey would benefit from early defintion by the community, namely because the Galactic disk is a complex environment, and different science goals will require trade offs.

astro-ph.GA↗

arXiv2022

The First 3$\pi$ 3D Map of ISM Dust Temperature

We present the first large-scale 3D map of interstellar dust temperature. We build upon existing 3D reddening maps derived from starlight absorption (Bayestar19), covering 3/4 of the sky. Starting with the column density for each of 500 million 3D voxels, we propose a temperature and emissivity power-law slope ($\beta$) for each of them, and integrate along the line of sight to synthesize an emission map in five frequency bands observed by \emph{Planck} and \emph{IRAS}. The reconstructed emission map is constrained to match observations on a $10'$ scale, and does so with good fidelity. We produce 3D temperature maps at resolutions of $110', 55', $and $27'$. We assess performance on Cepheus, a dust cloud with two distinct components along the line of sight, and find distinct temperatures for the two components. We thus show that this methodology has enough precision to constrain clouds with different temperature along the line of sight up to $1-\sigma$ error. This would be an important result for dust frequency decorrelation foreground analysis for cosmic microwave background experiments, which would be impacted by a line-of-sight with varying temperature and magnetic field components. In addition to $T$ and $\beta$, we constrain the conversion factor between emission optical depth and reddening. This conversion factor is assumed to be constant in commonly used emission-based reddening maps. However, this work shows a factor of two variation that may prove significant for some applications.

astro-ph.GA↗

arXiv2021

A classifier for spurious astrometric solutions in Gaia EDR3

The Gaia early Data Release 3 has delivered exquisite astrometric data for 1.47 billion sources, which is revolutionizing many fields in astronomy. For a small fraction of these sources, the astrometric solutions are poor, and the reported values and uncertainties may not apply. Before any analysis, it is important to recognize and excise these spurious results - this is commonly done by means of quality flags in the Gaia catalog. Here, we devise a means of separating 'good' from 'bad' astrometric solutions that is an order of magnitude cleaner than any single flag: 99.3% pure and 97.3% complete, as validated on our test data. We devise an extensive sample of manifestly bad astrometric solutions, with parallax that is negative at > 4.5 sigma; and a corresponding sample of presumably good solutions, including sources in HEALPix pixels on the sky that do not contain such negative parallaxes, and sources that fall on the main sequence in a color-absolute magnitude diagram. We then train a neural network that uses 17 pertinent Gaia catalog entries and information about nearby sources to discriminate between these two samples, captured in a single 'astrometric fidelity' parameter. A diverse set of verification tests shows that our approach works very cleanly, including for sources with positive parallaxes. The main limitations of our approach are in the very low-SNR and the crowded regime. Our astrometric fidelities for all of eDR3 can be queried via the Virtual Observatory, our code and data are public.

astro-ph.IM↗

arXiv2019

Overview of the DESI Legacy Imaging Surveys

The DESI Legacy Imaging Surveys are a combination of three public projects (the Dark Energy Camera Legacy Survey, the Beijing-Arizona Sky Survey, and the Mayall z-band Legacy Survey) that will jointly image approximately 14,000 deg^2 of the extragalactic sky visible from the northern hemisphere in three optical bands (g, r, and z) using telescopes at the Kitt Peak National Observatory and the Cerro Tololo Inter-American Observatory. The combined survey footprint is split into two contiguous areas by the Galactic plane. The optical imaging is conducted using a unique strategy of dynamically adjusting the exposure times and pointing selection during observing that results in a survey of nearly uniform depth. In addition to calibrated images, the project is delivering a catalog, constructed by using a probabilistic inference-based approach to estimate source shapes and brightnesses. The catalog includes photometry from the grz optical bands and from four mid-infrared bands (at 3.4, 4.6, 12 and 22 micorons) observed by the Wide-field Infrared Survey Explorer (WISE) satellite during its full operational lifetime. The project plans two public data releases each year. All the software used to generate the catalogs is also released with the data. This paper provides an overview of the Legacy Surveys project.

astro-ph.IM↗

arXiv2015

Kepler Eclipsing Binary Stars. VII. The Catalog of Eclipsing Binaries Found in the Entire Kepler Data-Set

The primary Kepler Mission provided nearly continuous monitoring of ~200,000 objects with unprecedented photometric precision. We present the final catalog of eclipsing binary systems within the 105 square degree Kepler field of view. This release incorporates the full extent of the data from the primary mission (Q0-Q17 Data Release). As a result, new systems have been added, additional false positives have been removed, ephemerides and principal parameters have been recomputed, classifications have been revised to rely on analytical models, and eclipse timing variations have been computed for each system. We identify several classes of systems including those that exhibit tertiary eclipse events, systems that show clear evidence of additional bodies, heartbeat systems, systems with changing eclipse depths, and systems exhibiting only one eclipse event over the duration of the mission. We have updated the period and galactic latitude distribution diagrams and included a catalog completeness evaluation. The total number of identified eclipsing and ellipsoidal binary systems in the Kepler field of view has increased to 2878, 1.3% of all observed Kepler targets. An online version of this catalog with downloadable content and visualization tools is maintained at http://keplerEBs.villanova.edu.

astro-ph.SR↗