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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Selection of high-redshift Lyman-Break Galaxies from broadband and wide photometric surveys

In this paper, we investigate the possibility of selecting high-redshift Lyman-Break Galaxies (LBG) using current and future broadband wide photometric surveys, such as the Ultraviolet Near Infrared Optical Northern Survey (UNIONS) or the Vera C. Rubin Legacy Survey of Space and Time (LSST), using a Random Forest algorithm. This work is conducted in the context of future large-scale structure spectroscopic surveys like DESI-II, the next phase of the Dark Energy Spectroscopic Instrument (DESI), which will start around 2029.We use deep imaging data from the Hyper Suprime Camera (HSC) and the Canada-France-Hawaii Telescope Large Area U-band Deep Survey (CLAUDS) on the COSMOS and XMM-LSS fields. To predict the selection performance of LBGs with image quality similar to UNIONS, we degrade the u,g,r,i and z bands to UNIONS depth.The Random Forest algorithm is trained with the u,g,r,i and z bands to classify LBGs in the 2.5 < z < 3.5 range.We find that fixing a target density budget of 1,100 deg$^{-2}$, the Random Forest approach gives a density of z > 2 targets of 873 deg$^{-2}$, and a density of 493 deg$^{-2}$ of confirmed LBGs after spectroscopic confirmation with DESI. This UNIONS-like selection was tested in a dedicated spectroscopic observation campaign of 1,000 targets with DESI on the COSMOS field, providing a safe spectroscopic sample with a mean redshift of 3. This sample is used to derive forecasts for DESI-II, assuming a sky coverage of 5,000 deg$^{2}$. We predict uncertainties on Alcock-Paczynski parameters α$_{⊥}$ and α$_{∥}$ to be 0.7% and 1% for 2.6 < z < 3.2, resulting in a potential 2% measurement of the dark energy fraction at high redshift. Additionally, we estimate the uncertainty in local non-Gaussianity and predict σ$_{fNL}$ ≈ 7, which would be comparable to the current best precision achieved by Planck. The latter forecast suggests that achieving the precision required to place stringent constraints on inflationary models (σ$_{fNL}$ ≈ 1) using spectroscopic galaxy surveys necessitates the development of a next-generation (Stage V) spectroscopic survey.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Selection of high-redshift Lyman-Break Galaxies from broadband and wide photometric surveys

Here, in this paper, we investigate the possibility of selecting high-redshift Lyman-Break Galaxies (LBG) using current and future broadband wide photometric surveys, such as the Ultraviolet Near Infrared Optical Northern Survey (UNIONS) or the Vera C. Rubin Legacy Survey of Space and Time (LSST), using a Random Forest algorithm. This work is conducted in the context of future large-scale structure spectroscopic surveys like DESI-II, the next phase of the Dark Energy Spectroscopic Instrument (DESI), which will start around 2029. We use deep imaging data from the Hyper Suprime Camera (HSC) and the Canada-France-Hawaii Telescope Large Area U-band Deep Survey (CLAUDS) on the COSMOS and XMM-LSS fields. To predict the selection performance of LBGs with image quality similar to UNIONS, we degrade the u,g,r,i and z bands to UNIONS depth. The Random Forest algorithm is trained with the u,g,r,i and z bands to classify LBGs in the 2.5 < z < 3.5 range. We find that fixing a target density budget of 1,100 deg -2 , the Random Forest approach gives a density of z > 2 targets of 873 deg -2 , and a density of 493 deg -2 of confirmed LBGs after spectroscopic confirmation with DESI. This UNIONS-like selection was tested in a dedicated spectroscopic observation campaign of 1,000 targets with DESI on the COSMOS field, providing a safe spectroscopic sample with a mean redshift of 3. This sample is used to derive forecasts for DESI-II, assuming a sky coverage of 5,000 deg 2 . We predict uncertainties on Alcock-Paczynski parameters α ⊥ and α ∥ to be 0.7% and 1% for 2.6 < z < 3.2, resulting in a potential 2% measurement of the dark energy fraction at high redshift. Additionally, we estimate the uncertainty in local non-Gaussianity and predict σ fNL ≈ 7, which would be comparable to the current best precision achieved by Planck. The latter forecast suggests that achieving the precision required to place stringent constraints on inflationary models (σ fNL ≈ 1) using spectroscopic galaxy surveys necessitates the development of a next-generation (Stage V) spectroscopic survey.

cosmological parameters from LSS↗
DOE OSTI2023

Applied Machine-Learning Models to Identify Spectral Sub-Types of M Dwarfs from Photometric Surveys

M dwarfs are the most abundant stars in the Solar Neighborhood and they are prime targets for searching for rocky planets in habitable zones. Consequently, a detailed characterization of these stars is in demand. The spectral sub-type is one of the parameters that is used for the characterization and it is traditionally derived from the observed spectra. However, obtaining the spectra of M dwarfs is expensive in terms of observation time and resources due to their intrinsic faintness. We study the performance of four machine-learning (ML) models—K-Nearest Neighbor (KNN), Random Forest (RF), Probabilistic Random Forest (PRF), and Multilayer Perceptron (MLP)—in identifying the spectral sub-types of M dwarfs at a grand scale by deploying broadband photometry in the optical and near-infrared. We trained the ML models by using the spectroscopically identified M dwarfs from the Sloan Digital Sky Survey (SDSS) Data Release (DR) 7, together with their photometric colors that were derived from the SDSS, Two-Micron All-Sky Survey, and Wide-field Infrared Survey Explorer. We found that the RF, PRF, and MLP give a comparable prediction accuracy, 74%, while the KNN provides slightly lower accuracy, 71%. We also found that these models can predict the spectral sub-type of M dwarfs with ~99% accuracy within ±1 sub-type. The five most useful features for the prediction are r - z, r - i, r - J, r - H , and g - z, and hence lacking data in all SDSS bands substantially reduces the prediction accuracy. However, we can achieve an accuracy of over 70% when the r and i magnitudes are available. Since the stars in this study are nearby (d ≲ 1300 pc for 95% of the stars), the dust extinction can reduce the prediction accuracy by only 3%. Finally, we used our optimized RF models to predict the spectral sub-types of M dwarfs from the Catalog of Cool Dwarf Targets for the Transiting Exoplanet Survey Satellite, and we provide the optimized RF models for public use.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

The PAU Survey: Photometric redshifts using transfer learning from simulations

In this paper, we introduce the DEEPZ deep learning photometric redshift (photo-z) code. As a test case, we apply the code to the PAU survey (PAUS) data in the COSMOS field. DEEPZ reduces the σ68 scatter statistic by 50 percent at iAB = 22.5 compared to existing algorithms. This improvement is achieved through various methods, including transfer learning from simulations where the training set consists of simulations as well as observations, which reduces the need for training data. The redshift probability distribution is estimated with a mixture density network (MDN), which produces accurate redshift distributions. Our code includes an autoencoder to reduce noise and extract features from the galaxy SEDs. It also benefits from combining multiple networks, which lowers the photo-z scatter by 10 percent. Furthermore, training with randomly constructed coadded fluxes adds information about individual exposures, reducing the impact of photometric outliers. In addition to opening up the route for higher redshift precision with narrow bands, these machine learning techniques can also be valuable for broad-band surveys.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Mind the gap: the power of combining photometric surveys with intensity mapping

The long wavelength modes lost to bright foregrounds in the interferometric 21-cm surveys can partially be recovered using a forward modeling approach that exploits the non-linear coupling between small and large scales induced by gravitational evolution. In this work, we build upon this approach by considering how adding external galaxy distribution data can help to fill in these modes. We consider supplementing the 21-cm data at two different redshifts with a spectroscopic sample (good radial resolution but low number density) loosely modeled on DESI-ELG at z=1 and a photometric sample (high number density but poor radial resolution) similar to LSST sample at z=1 and z=4 respectively. We find that both the galaxy samples are able to reconstruct the largest modes better than only using 21-cm data, with the spectroscopic sample performing significantly better than the photometric sample despite much lower number density. Here, we demonstrate the synergies between surveys by showing that the primordial initial density field is reconstructed better with the combination of surveys than using either of them individually. Methodologically, we also explore the importance of smoothing the density field when using bias models to forward model these tracers for reconstruction.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Using machine learning to identify extragalactic globular cluster candidates from ground-based photometric surveys of M87

Globular clusters (GCs) have been at the heart of many longstanding questions in many sub-fields of astronomy and, as such, systematic identification of GCs in external galaxies has immense impacts. In this study, we take advantage of M87’s well-studied GC system to implement supervised machine learning (ML) classification algorithms – specifically random forest and neural networks – to identify GCs from foreground stars and background galaxies, using ground-based photometry from the Canada–France–Hawaii Telescope (CFHT). We compare these two ML classification methods to studies of ‘human-selected’ GCs and find that the best-performing random forest model can reselect 61.2 per cent ± 8.0 per cent of GCs selected from HST data (ACSVCS) and the best-performing neural network model reselects 95.0 per cent ± 3.4 per cent. When compared to human-classified GCs and contaminants selected from CFHT data – independent of our training data – the best-performing random forest model can correctly classify 91.0 per cent ± 1.2 per cent and the best-performing neural network model can correctly classify 57.3 per cent ± 1.1 per cent. ML methods in astronomy have been receiving much interest as Vera C. Rubin Observatory prepares for first light. The observables in this study are selected to be directly comparable to early Rubin Observatory data and the prospects for running ML algorithms on the upcoming data set yields promising results.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Cluster Difference Imaging Photometric Survey. II. TOI 837: A Young Validated Planet in IC 2602

We report the discovery of TOI 837b and its validation as a transiting planet. We characterize the system using data from the NASA Transiting Exoplanet Survey Satellite mission, the ESA Gaia mission, ground-based photometry from El Sauce and ASTEP400, and spectroscopy from CHIRON, FEROS, and Veloce. We find that TOI 837 is a T = 9.9 mag G0/F9 dwarf in the southern open cluster IC 2602. The star and planet are therefore 35$_{-5}^{+11}$ million years old. Combining the transit photometry with a prior on the stellar parameters derived from the cluster color–magnitude diagram, we find that the planet has an orbital period of 8.3 days and is slightly smaller than Jupiter (R p =0.77$_{-0.07}^{+0.09}$ R Jup ). From radial velocity monitoring, we limit M p sin i to less than 1.20 M Jup (3σ). The transits either graze or nearly graze the stellar limb. Grazing transits are a cause for concern, as they are often indicative of astrophysical false-positive scenarios. Our follow-up data show that such scenarios are unlikely. Our combined multicolor photometry, high-resolution imaging, and radial velocities rule out hierarchical eclipsing binary scenarios. Background eclipsing binary scenarios, though limited by speckle imaging, remain a 0.2% possibility. TOI 837b is therefore a validated adolescent exoplanet. The planetary nature of the system can be confirmed or refuted through observations of the stellar obliquity and the planetary mass. Such observations may also improve our understanding of how the physical and orbital properties of exoplanets change in time.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1987

A spectroscopic and photometric survey of OB+ stars

Image-tube spectra (with dispersions of 40-90 A/mm) and UBV photometry of OB+ stars have been obtained at Cerro Tololo and Kitt Peak. The survey is complete to galactic latitudes of + or - 30 deg for galactic longitudes of between 300 and 60 deg. Most of the stars are found to be O-type and B-type supergiants, and 378 new O-type and B-type detections have been identified.

Drilling, J. S.↗
NASA NTRS1992

A photometric survey of outer belt asteroids

Since 1989, we have been conducting a research program devoted to the study of the Trojans and outer belt asteroids (Hilda and Cybele groups), in order to characterize their rotational properties and shapes. As an outcome of several observational campaigns, we determined rotational periods and lightcurve amplitudes for 23 distant asteroids, using both CCD and photoelectric photometry. In this paper, we compare the rotational properties of main belt asteroids and Trojans, based on the preliminary results of this survey.

Dimartino, M.↗
NASA NTRS2020

Cluster Difference Imaging Photometric Survey. II. TOI 837: A Young Validated Planet in IC 2602

We report the discovery of TOI 837b and its validation as a transiting planet. We characterize the system using data from the NASA Transiting Exoplanet Survey Satellite mission, the ESA Gaia mission, ground-based photometry from El Sauce and ASTEP400, and spectroscopy from CHIRON, FEROS, and Veloce. We find that TOI 837 is a T = 9.9 mag G0/F9 dwarf in the southern open cluster IC 2602. The star and planet are therefore 35(sup +11)(sub -5) million years old. Combining the transit photometry with a prior on the stellar parameters derived from the cluster color–magnitude diagram, we find that the planet has an orbital period of 8.3 days and is slightly smaller than Jupiter (R(sub p) = 0.77(sup + 0.09)(sub -0.07) R(sub Jup)). From radial velocity monitoring, we limit M(sub p) sin i to less than 1.20 M(sub Jup) (3σ). The transits either graze or nearly graze the stellar limb. Grazing transits are a cause for concern, as they are often indicative of astrophysical false-positive scenarios. Our follow-up data show that such scenarios are unlikely. Our combined multicolor photometry, high-resolution imaging, and radial velocities rule out hierarchical eclipsing binary scenarios. Background eclipsing binary scenarios, though limited by speckle imaging, remain a 0.2% possibility. TOI 837b is therefore a validated adolescent exoplanet. The planetary nature of the system can be confirmed or refuted through observations of the stellar obliquity and the planetary mass. Such observations may also improve our understanding of how the physical and orbital properties of exoplanets change in time.

Exoplanets↗
DOE OSTI2022

Photometric Redshifts for Next-Generation Surveys

Photometric redshifts are essential in studies of both galaxy evolution and cosmology, as they enable analyses of objects too numerous or faint for spectroscopy. The Rubin Observatory, Euclid, and Roman Space Telescope will soon provide a new generation of imaging surveys with unprecedented area coverage, wavelength range, and depth. To take full advantage of these data sets, further progress in photometric redshift methods is needed. In this review, we focus on the greatest common challenges and prospects for improvement in applications of photometric redshifts to the next generation of surveys: ∙ Gains in performance (i.e., the precision of redshift estimates for individual galaxies) could greatly enhance studies of galaxy evolution and some probes of cosmology. ∙ Improvements in characterization (i.e., the accurate recovery of redshift distributions of galaxies in the presence of uncertainty on individual redshifts) are urgently needed for cosmological measurements with next-generation surveys. To achieve both of these goals, improvements in the scope and treatment of the samples of spectroscopic redshifts that make high-fidelity photometric redshifts possible will also be needed. For the full potential of the next generation of surveys to be reached, the characterization of redshift distributions must improve by roughly an order of magnitude compared with the current state of the art, requiring progress on a wide variety of fronts. We conclude by presenting a speculative evaluation of how photometric redshift methods and the collection of the necessary spectroscopic samples may improve by the time near-future surveys are completed.

Astronomy & Astrophysics↗
NASA NTRS1984

A Survey for Photometric Variability from Space

A survey for photometric variability in a wide variety of astronomical objects would produce much new information about their interiors and dynamics. Reasons for such a survey are given, as well as an example of the solar-constant variations that can be used as a guide to what may be expected from main-sequence stars. A concept for a satellite dedicated to a survey of photometric variability is proposed.

Hudson, H. S.↗
NASA NTRS1984

A survey for photometric variability from space

A survey for photometric variability in a wide variety of astronomical objects would produce much new information about their interiors and dynamics. Reasons for such a survey are given, as well as an example of the solar-constant variations that can be used as guide to what may be expected from main-sequence stars. A concept for a satellite dedicated to a survey of photometric variability is proposed.

Hudson, H. S.↗
DOE OSTI2024

Modeling neutrino-induced scale-dependent galaxy clustering for photometric galaxy surveys

Abstract The increasing statistical precision of photometric redshift surveys requires improved accuracy of theoretical predictions for large-scale structure observables to obtain unbiased cosmological constraints. In ΛCDM cosmologies, massive neutrinos stream freely at small cosmological scales, suppressing the small-scale power spectrum. In massive neutrino cosmologies, galaxy bias modeling needs to accurately relate the scale-dependent growth of the underlying matter field to observed galaxy clustering statistics. In this work, we implement a computationally efficient approximation of the neutrino-induced scale-dependent bias (NISDB). Through simulated likelihood analyses of Dark Energy Survey Year 3 (DESY3) and Legacy Survey of Space and Time Year 1 (LSSTY1) synthetic data that contain an appreciable NISDB, we examine the impact of linear galaxy bias and neutrino mass modeling choices on cosmological parameter inference. We find model misspecification of the NISDB approximation and neutrino mass models to decrease the constraining power of photometric galaxy surveys and cause parameter biases in the cosmological interpretation of future surveys. We quantify these biases and devise mitigation strategies.

Astronomy & Astrophysics↗
DOE OSTI2024

Disentangling the Black Hole Mass Spectrum with Photometric Microlensing Surveys

Abstract From the formation mechanisms of stars and compact objects to nuclear physics, modern astronomy frequently leverages surveys to understand populations of objects to answer fundamental questions. The population of dark and isolated compact objects in the Galaxy contains critical information related to many of these topics, but is only practically accessible via gravitational microlensing. However, photometric microlensing observables are degenerate for different types of lenses, and one can seldom classify an event as involving either a compact object or stellar lens on its own. To address this difficulty, we apply a Bayesian framework that treats lens type probabilistically and jointly with a lens population model. This method allows lens population characteristics to be inferred despite intrinsic uncertainty in the lens class of any single event. We investigate this method’s effectiveness on a simulated ground-based photometric survey in the context of characterizing a hypothetical population of primordial black holes (PBHs) with an average mass of 30 M ⊙ . On simulated data, our method outperforms current black hole (BH) lens identification pipelines and characterizes different subpopulations of lenses while jointly constraining the PBH contribution to dark matter to ≈25%. Key to robust inference, our method can marginalize over population model uncertainty. We find the lower mass cutoff for stellar origin BHs, a key observable in understanding the BH mass gap, particularly difficult to infer in our simulations. This work lays the foundation for cutting-edge PBH abundance constraints to be extracted from current photometric microlensing surveys.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

First Detection of the GI-type of Intrinsic Alignments of Galaxies Using the Self-calibration Method in a Photometric Galaxy Survey

Weak gravitational lensing is one of the most promising cosmological probes to constrain dark matter, dark energy, and the nature of gravity at cosmic scales. Intrinsic alignments (IAs) of galaxies have been recognized as one of the most serious systematic effects facing gravitational lensing. Such alignments must be isolated and removed to obtain a pure lensing signal. Furthermore, the alignments are related to the processes of galaxy formation, so their extracted signal can help in understanding such formation processes and improving their theoretical modeling. We report in this Letter the first detection of the gravitational shear–intrinsic shape (GI) correlation and the intrinsic shape–galaxy density (Ig) correlation using the self-calibration method in a photometric redshift survey. These direct measurements are made from the KiDS-450 photometric galaxy survey with a significance of 3.65σ in the third bin for the Ig correlation, and 3.51σ for the GI cross-correlation between the third and fourth bins. The self-calibration method uses the information available from photometric surveys without needing to specify an IA model and will play an important role in validating IA models and IA mitigation in future surveys such as the Rubin Observatory Legacy Survey of Space and Time, Euclid, and WFIRST.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

StarDICE III: characterization of the photometric instrument with a collimated beam projector

The measurement of Type Ia supernovae magnitudes provides cosmological distances, which constrain dark energy parameters. Current and upcoming large photometric surveys require improved photometric calibration precision to reduce systematic uncertainties in cosmological constraints. The StarDICE experiment aims to establish accurate broad-band flux references for these surveys, targeting sub-percent precision in magnitude measurements. Achieving this requires precise filter bandpass measurements for both StarDICE and survey instruments with sub-nanometre accuracy. To this end, we developed the Collimated Beam Projector (CBP), an optical device for calibrating the throughput of astronomical telescopes and their filters. The CBP uses a tunable laser source and a reversed telescope to emit a parallel monochromatic light beam, continuously monitored in flux and wavelength. The CBP output flux is measured with a large-area photodiode calibrated relative to a NIST photodiode. Using CBP measurements, we derive the StarDICE telescope throughput and filter transmissions, anchoring them to NIST’s absolute calibration. After analysing systematic uncertainties, we achieved sub-nanometre accuracy for filter central wavelengths, measured filter transmission with ~0.5 per cent precision per 1 nm bin, and detected out-of-band leakages at a relative level of 10 –4 ⁠. Furthermore, we synthesized equivalent transmission for full pupil illumination from four sampled positions in the StarDICE telescope mirror, with ~0.2 nm accuracy for central wavelengths and 7 mmag for broad-band fluxes. This demonstrates our ability to characterize telescope throughput down to the millimagnitude, paving the way for future developments, such as the Rubin-CBP for measuring the LSST at Vera Rubin Observatory, and a portable CBP version for in-situ transmission monitoring.

Calibration↗