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Adam S. Bolton

Publications and source records attributed to Adam S. Bolton.

At least 19 recordsLinked to original sources
arXiv2026

The Carousel Lens II: Cosmological Constraints with GIGA-Lens

The nature of dark matter and dark energy are among the central questions in cosmology. Strong gravitational lenses with multiple source planes provide a geometric probe of cosmology: the ratio of deflection angles at different redshifts depends only on angular-diameter distances, constraining the matter density $\Omega_m$ and the dark energy equation of state $w$. However, constraints from this technique have historically lagged behind those from the CMB, SNe Ia, and BAO. In this work, we present new cosmological constraints from the Carousel Lens, a cluster-scale lens with more than 40 extended images from 11 spectroscopically confirmed sources. Its relaxed core and rich set of extended images behind the main halo make it particularly suitable for cosmological inference. Using the GIGA-Lens pipeline, we construct a pixel-level lens model including six HST-detected sources and four mass components. From this model, we obtain $w$CDM constraints of $\Omega_m = 0.34^{+0.16}_{-0.13}$ and $w = -1.31^{+0.35}_{-0.32}$ from the Carousel Lens alone, accounting for both statistical and systematic uncertainties. We further project that including four additional known higher-redshift sources, assuming similar fractional uncertainties, could improve the constraining power by ~80%, bringing the precision close to that of the CMB and SNe Ia. For an evolving dark energy model ($w_0w_a$CDM), the Carousel Lens alone yields constraints comparable to the CMB, providing an independent and complementary probe alongside SN Ia and BAO. While currently systematic uncertainties dominate, which we quantify through simulations, our results demonstrate that relaxed multi-source-plane cluster lenses can deliver competitive cosmological constraints. Further improvements are expected from reductions in systematics and from incorporating higher-redshift sources (known and new) with high-resolution imaging.

astro-ph.CO↗
arXiv2026

Opportunities in AI/ML for the Rubin LSST Dark Energy Science Collaboration

The Vera C. Rubin Observatory's Legacy Survey of Space and Time (LSST) will produce unprecedented volumes of heterogeneous astronomical data (images, catalogs, and alerts) that challenge traditional analysis pipelines. The LSST Dark Energy Science Collaboration (DESC) aims to derive robust constraints on dark energy and dark matter from these data, requiring methods that are statistically powerful, scalable, and operationally reliable. Artificial intelligence and machine learning (AI/ML) are already embedded across DESC science workflows, from photometric redshifts and transient classification to weak lensing inference and cosmological simulations. Yet their utility for precision cosmology hinges on trustworthy uncertainty quantification, robustness to covariate shift and model misspecification, and reproducible integration within scientific pipelines. This white paper surveys the current landscape of AI/ML across DESC's primary cosmological probes and cross-cutting analyses, revealing that the same core methodologies and fundamental challenges recur across disparate science cases. Since progress on these cross-cutting challenges would benefit multiple probes simultaneously, we identify key methodological research priorities, including Bayesian inference at scale, physics-informed methods, validation frameworks, and active learning for discovery. With an eye on emerging techniques, we also explore the potential of the latest foundation model methodologies and LLM-driven agentic AI systems to reshape DESC workflows, provided their deployment is coupled with rigorous evaluation and governance. Finally, we discuss critical software, computing, data infrastructure, and human capital requirements for the successful deployment of these new methodologies, and consider associated risks and opportunities for broader coordination with external actors.

astro-ph.IM↗
arXiv2025

The DESI Single Fiber Lens Search. I. Four Thousand Spectroscopically Selected Galaxy-Galaxy Gravitational Lens Candidates

We present 4,110 strong gravitational lens candidates, 3,887 of which are new discoveries, selected from a sample of 5,837,154 luminous red galaxies (LRGs) observed with the Dark Energy Spectroscopic Instrument (DESI). Candidates are identified via the presence of background ionized oxygen [O II] nebular emission lines in the foreground LRG spectra which may originate from the lensing of higher redshift star-forming galaxies. Using the measured foreground redshift, background redshift, and integrated flux of the background [O II] doublet, we integrate over impact parameters to compute the probability that each candidate is a lens. We expect 53% of candidates to be true lenses with Einstein radii ranging from 0.1'' to 4'', which can be confirmed with high-resolution imaging. Confirmed strong lenses from this sample will form a valuable cosmological dataset, as strong gravitational lensing is the only method to directly measure dark matter halo substructure at cosmological distances. We independently recover the host of the multiply imaged gravitationally lensed type Ia supernova iPTF16geu. Monitoring these lenses for future multiply lensed transients will enable (a) H0 measurements via time-delay cosmography and (b) substructure measurements via flux ratios.

astro-ph.GA↗
arXiv2025

AstroVisBench: A Code Benchmark for Scientific Computing and Visualization in Astronomy

Large Language Models (LLMs) are being explored for applications in scientific research, including their capabilities to synthesize literature, answer research questions, generate research ideas, and even conduct computational experiments. Ultimately, our goal is for these to help scientists derive novel scientific insights. In many areas of science, such insights often arise from processing and visualizing data to understand its patterns. However, evaluating whether an LLM-mediated scientific workflow produces outputs conveying the correct scientific insights is challenging to evaluate and has not been addressed in past work. We introduce AstroVisBench, the first benchmark for both scientific computing and visualization in the astronomy domain. AstroVisBench judges a language model's ability to both (1) create astronomy-specific workflows to process and analyze data and (2) visualize the results of these workflows through complex plots. Our evaluation of visualizations uses a novel LLM-as-a-judge workflow, which is validated against annotation by five professional astronomers. Using AstroVisBench we present an evaluation of state-of-the-art language models, showing a significant gap in their ability to engage in astronomy research as useful assistants. This evaluation provides a strong end-to-end evaluation for AI scientists that offers a path forward for the development of visualization-based workflows, which are central to a broad range of domains from physics to biology.

cs.CL↗
arXiv2024

SPARCL: SPectra Analysis and Retrievable Catalog Lab

SPectra Analysis and Retrievable Catalog Lab (SPARCL) at NOIRLab's Astro Data Lab was created to efficiently serve large optical and infrared spectroscopic datasets. It consists of services, tools, example workflows and currently contains spectra for over 7.5 million stars, galaxies and quasars from the Sloan Digital Sky Survey (SDSS) and the Dark Energy Spectroscopic Instrument (DESI) survey. We aim to eventually support the broad range of spectroscopic datasets that will be hosted at NOIRLab and beyond. Major elements of SPARCL include capabilities to discover and query for spectra based on parameters of interest, a fast web service that delivers desired spectra either individually or in bulk as well as documentation and example Jupyter Notebooks to empower users in their research. More information is available on the SPARCL website (https://astrosparcl.datalab.noirlab.edu).

astro-ph.IM↗
arXiv2023

Astro Data Lab Spectral Viewer Requirements for Wide-Area Spectroscopic Surveys

The Astro Data Lab is preparing to host large spectroscopic datasets such as a copy of the Dark Energy Spectroscopic Instrument (DESI) survey, which is projected to include approximately 40 million spectra of galaxies and quasars as well as over 10 million spectra of stars by 2026. Currently, we serve DR16 spectra from the Sloan Digital Sky Survey (SDSS), including Baryon Oscillation Spectroscopic Survey (BOSS), and Extended BOSS (eBOSS) spectra. A spectral viewer tool allows users to visually and interactively inspect spectra. Given the large size of these spectroscopic datasets, a typical use case might consist of a selection or query for a subset of objects of interest (e.g., a subsample of stars or galaxies or quasars), followed by visual inspection of the selected spectra. It is anticipated that in some cases, users will want to go through a long list of spectra (e.g., thousands) quickly while looking for specific features. This document contains a description of the requirements for such a spectral viewer tool to be incorporated within the Astro Data Lab environment at NSF's NOIRLab. For each object, the spectral viewer will display the observed spectrum and, if available, the noise spectrum, sky spectrum, and best-fit template spectrum. Users will be able to control the display interactively after they launch the tool as part of their Data Lab workflow. The primary objective will be to support the visualization of spectroscopic datasets hosted at the Astro Data Lab but this requirements document could be a useful reference or inspiration for other applications and/or other datasets in the astronomy community.

astro-ph.IM↗
arXiv2022

The MegaMapper: A Stage-5 Spectroscopic Instrument Concept for the Study of Inflation and Dark Energy

In this white paper, we present the MegaMapper concept. The MegaMapper is a proposed ground-based experiment to measure Inflation parameters and Dark Energy from galaxy redshifts at $2<z<5$. In order to achieve path-breaking results with a mid-scale investment, the MegaMapper combines existing technologies for critical path elements and pushes innovative development in other design areas. To this aim, we envision a 6.5-m Magellan-like telescope, with a newly designed wide field, coupled with DESI spectrographs, and small-pitch robots to achieve multiplexing of at least 26,000. This will match the expected achievable target density in the redshift range of interest and provide a 10x capability over the existing state-of the art, without a 10x increase in project budget.

astro-ph.IM↗
arXiv2022

A Spectroscopic Road Map for Cosmic Frontier: DESI, DESI-II, Stage-5

In this white paper, we present an experimental road map for spectroscopic experiments beyond DESI. DESI will be a transformative cosmological survey in the 2020s, mapping 40 million galaxies and quasars and capturing a significant fraction of the available linear modes up to z=1.2. DESI-II will pilot observations of galaxies both at much higher densities and extending to higher redshifts. A Stage-5 experiment would build out those high-density and high-redshift observations, mapping hundreds of millions of stars and galaxies in three dimensions, to address the problems of inflation, dark energy, light relativistic species, and dark matter. These spectroscopic data will also complement the next generation of weak lensing, line intensity mapping and CMB experiments and allow them to reach their full potential.

astro-ph.CO↗
arXiv2021

The Seventeenth Data Release of the Sloan Digital Sky Surveys: Complete Release of MaNGA, MaStar and APOGEE-2 Data

This paper documents the seventeenth data release (DR17) from the Sloan Digital Sky Surveys; the fifth and final release from the fourth phase (SDSS-IV). DR17 contains the complete release of the Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey, which reached its goal of surveying over 10,000 nearby galaxies. The complete release of the MaNGA Stellar Library (MaStar) accompanies this data, providing observations of almost 30,000 stars through the MaNGA instrument during bright time. DR17 also contains the complete release of the Apache Point Observatory Galactic Evolution Experiment 2 (APOGEE-2) survey which publicly releases infra-red spectra of over 650,000 stars. The main sample from the Extended Baryon Oscillation Spectroscopic Survey (eBOSS), as well as the sub-survey Time Domain Spectroscopic Survey (TDSS) data were fully released in DR16. New single-fiber optical spectroscopy released in DR17 is from the SPectroscipic IDentification of ERosita Survey (SPIDERS) sub-survey and the eBOSS-RM program. Along with the primary data sets, DR17 includes 25 new or updated Value Added Catalogs (VACs). This paper concludes the release of SDSS-IV survey data. SDSS continues into its fifth phase with observations already underway for the Milky Way Mapper (MWM), Local Volume Mapper (LVM) and Black Hole Mapper (BHM) surveys.

astro-ph.GA↗
arXiv2021

The ANTARES Astronomical Time-Domain Event Broker

We describe the Arizona-NOIRLab Temporal Analysis and Response to Events System (ANTARES), a software instrument designed to process large-scale streams of astronomical time-domain alerts. With the advent of large-format CCDs on wide-field imaging telescopes, time-domain surveys now routinely discover tens of thousands of new events each night, more than can be evaluated by astronomers alone. The ANTARES event broker will process alerts, annotating them with catalog associations and filtering them to distinguish customizable subsets of events. We describe the data model of the system, the overall architecture, annotation, implementation of filters, system outputs, provenance tracking, system performance, and the user interface.

astro-ph.IM↗
arXiv2020

The Completed SDSS-IV extended Baryon Oscillation Spectroscopic Survey: Cosmological Implications from two Decades of Spectroscopic Surveys at the Apache Point observatory

We present the cosmological implications from final measurements of clustering using galaxies, quasars, and Ly$\alpha$ forests from the completed Sloan Digital Sky Survey (SDSS) lineage of experiments in large-scale structure. These experiments, composed of data from SDSS, SDSS-II, BOSS, and eBOSS, offer independent measurements of baryon acoustic oscillation (BAO) measurements of angular-diameter distances and Hubble distances relative to the sound horizon, $r_d$, from eight different samples and six measurements of the growth rate parameter, $f\sigma_8$, from redshift-space distortions (RSD). This composite sample is the most constraining of its kind and allows us to perform a comprehensive assessment of the cosmological model after two decades of dedicated spectroscopic observation. We show that the BAO data alone are able to rule out dark-energy-free models at more than eight standard deviations in an extension to the flat, $\Lambda$CDM model that allows for curvature. When combined with Planck Cosmic Microwave Background (CMB) measurements of temperature and polarization the BAO data provide nearly an order of magnitude improvement on curvature constraints. The RSD measurements indicate a growth rate that is consistent with predictions from Planck primary data and with General Relativity. When combining the results of SDSS BAO and RSD with external data, all multiple-parameter extensions remain consistent with a $\Lambda$CDM model. Regardless of cosmological model, the precision on $\Omega_\Lambda$, $H_0$, and $\sigma_8$, remains at roughly 1\%, showing changes of less than 0.6\% in the central values between models. The inverse distance ladder measurement under a o$w_0w_a$CDM yields $H_0= 68.20 \pm 0.81 \, \rm km\, s^{-1} Mpc^{-1}$, remaining in tension with several direct determination methods. (abridged)

astro-ph.CO↗
arXiv2019

Petabytes to Science

A Kavli foundation sponsored workshop on the theme \emph{Petabytes to Science} was held 12$^{th}$ to 14$^{th}$ of February 2019 in Las Vegas. The aim of the this workshop was to discuss important trends and technologies which may support astronomy. We also tackled how to better shape the workforce for the new trends and how we should approach education and public outreach. This document was coauthored during the workshop and edited in the weeks after. It comprises the discussions and highlights many recommendations which came out of the workshop. We shall distill parts of this document and formulate potential white papers for the decadal survey.

astro-ph.IM↗
arXiv2019

A Full Implementation of Spectro-Perfectionism for Precise Radial Velocity Exoplanet Detection: A Test Case With the MINERVA Reduction Pipeline

We present a computationally tractable implementation of spectro-perfectionism, a method which minimizes error imparted by spectral extraction. We develop our method in conjunction with a full raw reduction pipeline for the MINiature Exoplanet Radial Velocity Array (MINERVA), capable of performing both optimal extraction and spectro-perfectionism. Although spectro-perfectionism remains computationally expensive, our implementation can extract a MINERVA exposure in approximately $30\,\text{min}$. We describe our localized extraction procedure and our approach to point spread function fitting. We compare the performance of both extraction methods on a set of 119 exposures on HD122064, an RV standard star. Both the optimal extraction and spectro-perfectionism pipelines achieve nearly identical RV precision under a six-exposure chronological binning. We discuss the importance of reliable calibration data for point spread function fitting and the potential of spectro-perfectionism for future precise radial velocity exoplanet studies.

astro-ph.IM↗
arXiv2019

First radial velocity results from the MINiature Exoplanet Radial Velocity Array (MINERVA)

The MINiature Exoplanet Radial Velocity Array (MINERVA) is a dedicated observatory of four 0.7m robotic telescopes fiber-fed to a KiwiSpec spectrograph. The MINERVA mission is to discover super-Earths in the habitable zones of nearby stars. This can be accomplished with MINERVA's unique combination of high precision and high cadence over long time periods. In this work, we detail changes to the MINERVA facility that have occurred since our previous paper. We then describe MINERVA's robotic control software, the process by which we perform 1D spectral extraction, and our forward modeling Doppler pipeline. In the process of improving our forward modeling procedure, we found that our spectrograph's intrinsic instrumental profile is stable for at least nine months. Because of that, we characterized our instrumental profile with a time-independent, cubic spline function based on the profile in the cross dispersion direction, with which we achieved a radial velocity precision similar to using a conventional "sum-of-Gaussians" instrumental profile: 1.8 m s$^{-1}$ over 1.5 months on the RV standard star HD 122064. Therefore, we conclude that the instrumental profile need not be perfectly accurate as long as it is stable. In addition, we observed 51 Peg and our results are consistent with the literature, confirming our spectrograph and Doppler pipeline are producing accurate and precise radial velocities.

astro-ph.IM↗
arXiv2019

Astrophysical Tests of Dark Matter with Maunakea Spectroscopic Explorer

We discuss how astrophysical observations with the Maunakea Spectroscopic Explorer (MSE), a high-multiplexity (about 4300 fibers), wide field-of-view (1.5 square degree), large telescope aperture (11.25 m) facility, can probe the particle nature of dark matter. MSE will conduct a suite of surveys that will provide critical input for determinations of the mass function, phase-space distribution, and internal density profiles of dark matter halos across all mass scales. N-body and hydrodynamical simulations of cold, warm, fuzzy and self-interacting dark matter suggest that non-trivial dynamics in the dark sector could have left an imprint on structure formation. Analysed within these frameworks, the extensive and unprecedented datasets produced by MSE will be used to search for deviations away from cold and collisionless dark matter model. MSE will provide an improved estimate of the local density of dark matter, critical for direct detection experiments, and will improve estimates of the J-factor for indirect searches through self-annihilation or decay into Standard Model particles. MSE will determine the impact of low mass substructures on the dynamics of Milky Way stellar streams in velocity space, and will allow for estimates of the density profiles of the dark matter halos of Milky Way dwarf galaxies using more than an order of magnitude more tracers. In the low redshift Universe, MSE will provide critical redshifts to pin down the luminosity functions of vast numbers of satellite systems, and MSE will be an essential component of future strong lensing measurements to constrain the halo mass function. Across nearly all mass scales, the improvements offered by MSE, in comparison to other facilities, are such that the relevant analyses are limited by systematics rather than statistics.

astro-ph.CO↗
arXiv2019

The Detailed Science Case for the Maunakea Spectroscopic Explorer, 2019 edition

(Abridged) The Maunakea Spectroscopic Explorer (MSE) is an end-to-end science platform for the design, execution and scientific exploitation of spectroscopic surveys. It will unveil the composition and dynamics of the faint Universe and impact nearly every field of astrophysics across all spatial scales, from individual stars to the largest scale structures in the Universe. Major pillars in the science program for MSE include (i) the ultimate Gaia follow-up facility for understanding the chemistry and dynamics of the distant Milky Way, including the outer disk and faint stellar halo at high spectral resolution (ii) galaxy formation and evolution at cosmic noon, via the type of revolutionary surveys that have occurred in the nearby Universe, but now conducted at the peak of the star formation history of the Universe (iii) derivation of the mass of the neutrino and insights into inflationary physics through a cosmological redshift survey that probes a large volume of the Universe with a high galaxy density. MSE is positioned to become a critical hub in the emerging international network of front-line astronomical facilities, with scientific capabilities that naturally complement and extend the scientific power of Gaia, the Large Synoptic Survey Telescope, the Square Kilometer Array, Euclid, WFIRST, the 30m telescopes and many more.

astro-ph.IM↗
arXiv2019

Inflation and Dark Energy from spectroscopy at $z > 2$

The expansion of the Universe is understood to have accelerated during two epochs: in its very first moments during a period of Inflation and much more recently, at $z < 1$, when Dark Energy is hypothesized to drive cosmic acceleration. The undiscovered mechanisms behind these two epochs represent some of the most important open problems in fundamental physics. The large cosmological volume at $2 < z < 5$, together with the ability to efficiently target high-$z$ galaxies with known techniques, enables large gains in the study of Inflation and Dark Energy. A future spectroscopic survey can test the Gaussianity of the initial conditions up to a factor of ~50 better than our current bounds, crossing the crucial theoretical threshold of $σ(f_{NL}^{\rm local})$ of order unity that separates single field and multi-field models. Simultaneously, it can measure the fraction of Dark Energy at the percent level up to $z = 5$, thus serving as an unprecedented test of the standard model and opening up a tremendous discovery space.

astro-ph.CO↗