Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “LSST”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Cosmology from weak lensing, galaxy clustering, CMB lensing, and tSZ – I. 10 × 2pt modelling methodology

ABSTRACT The overlap of galaxy surveys and cosmic microwave background (CMB) experiments presents an ideal opportunity for joint cosmological data set analyses. In this paper we develop a halo model-based method for the first joint analysis combining these two experiments using 10 correlated two-point functions (10 × 2pt) derived from galaxy position, galaxy shear, CMB lensing convergence, and Compton-y fields. We explore this method using the Vera Rubin Observatory Legacy Survey of Space and Time (LSST) and the Simons Observatory (SO) as examples. We find such LSS × CMB joint analyses lead to significant improvement in Figure-of-Merit of Ωm and S8 over the constraints from using LSS-only probes within Λ cold dark matter (ΛCDM) model. We identify that the shear–y and y–y correlations are the most valuable additions when thermal Sunyaev–Zel’dolvich (tSZ) is included. We further identify the dominant sources of halo model uncertainties in the small-scale modelling, and investigate the impact of halo self-calibration due to the inclusion of small-scale tSZ information.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Emission line predictions for mock galaxy catalogues: a new differentiable and empirical mapping from DESI

ABSTRACT We present a simple, differentiable method for predicting emission line strengths from rest-frame optical continua using an empirically determined mapping. Extensive work has been done to develop mock galaxy catalogues that include robust predictions for galaxy photometry, but reliably predicting the strengths of emission lines has remained challenging. Our new mapping is a simple neural network implemented using the JAX Python automatic differentiation library. It is trained on Dark Energy Spectroscopic Instrument Early Release data to predict the equivalent widths (EWs) of the eight brightest optical emission lines (including H α, H β, [O ii], and [O iii]) from a galaxy’s rest-frame optical continuum. The predicted EW distributions are consistent with the observed ones when noise is accounted for, and we find Spearman’s rank correlation coefficient ρs > 0.87 between predictions and observations for most lines. Using a non-linear dimensionality reduction technique, we show that this is true for galaxies across the full range of observed spectral energy distributions. In addition, we find that adding measurement uncertainties to the predicted line strengths is essential for reproducing the distribution of observed line-ratios in the BPT diagram. Our trained network can easily be incorporated into a differentiable stellar population synthesis pipeline without hindering differentiability or scalability with GPUs. A synthetic catalogue generated with such a pipeline can be used to characterize and account for biases in the spectroscopic training sets used for training and calibration of photo-z’s, improving the modelling of systematic incompleteness for the Rubin Observatory LSST and other surveys.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

DESI complete calibration of the colour–redshift relation (DC3R2): results from early DESI data

We present initial results from the Dark Energy Spectroscopic Instrument (DESI) complete calibration of the colour–redshift relation (DC3R2) secondary target survey. Our analysis uses 230 k galaxies that overlap with KiDS-VIKING ugriZYJHK s photometry to calibrate the colour–redshift relation and to inform photometric redshift (photo-z) inference methods of future weak lensing surveys. Together with emission line galaxies (ELGs), luminous red galaxies (LRGs), and the Bright Galaxy Survey (BGS) that provide samples of complementary colour, the DC3R2 targets help DESI to span 56 percent of the colour space visible to Euclid and LSST with high confidence spectroscopic redshifts. The effects of spectroscopic completeness and quality are explored, as well as systematic uncertainties introduced with the use of common Self-Organizing Maps trained on different photometry than the analysis sample. We further examine the dependence of redshift on magnitude at fixed colour, important for the use of bright galaxy spectra to calibrate redshifts in a fainter photometric galaxy sample. We find that noise in the KiDS-VIKING photometry introduces a dominant, apparent magnitude dependence of redshift at fixed colour, which indicates a need for carefully chosen deep drilling fields, and survey simulation to model this effect for future weak lensing surveys.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Simulating image coaddition with the Nancy Grace Roman Space Telescope – I. Simulation methodology and general results

The upcoming Nancy Grace Roman Space Telescope will carry out a wide-area survey in the near-infrared. A key science objective is the measurement of cosmic structure via weak gravitational lensing. Roman data will be undersampled, which introduces new challenges in the measurement of source galaxy shapes; a potential solution is to use linear algebra-based coaddition techniques such as imcom that combine multiple undersampled images to produce a single oversampled output mosaic with a desired ‘target’ point spread function (PSF). We present here an initial application of imcom to 0.64 square degrees of simulated Roman data, based on the Roman branch of the Legacy Survey of Space and Time (LSST) Dark Energy Science Collaboration (DESC) Data Challenge 2 (DC2) simulation. We show that imcom runs successfully on simulated data that includes features such as plate scale distortions, chip gaps, detector defects, and cosmic ray masks. We simultaneously propagate grids of injected sources and simulated noise fields as well as the full simulation. We quantify the residual deviations of the PSF from the target (the ‘leakage’), as well as noise properties of the output images; we discuss how the overall tiling pattern as well as Moiré patterns appear in the final leakage and noise maps. We include appendices on interpolation algorithms and the interaction of undersampling with image processing operations that may be of broader applicability. The companion paper (‘Paper II’) explores the implications for weak lensing analyses.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

The Dark Energy Survey 5-yr photometrically classified type Ia supernovae without host-galaxy redshifts

ABSTRACT Current and future Type Ia Supernova (SN Ia) surveys will need to adopt new approaches to classifying SNe and obtaining their redshifts without spectra if they wish to reach their full potential. We present here a novel approach that uses only photometry to identify SNe Ia in the 5-yr Dark Energy Survey (DES) data set using the SuperNNova classifier. Our approach, which does not rely on any information from the SN host-galaxy, recovers SNe Ia that might otherwise be lost due to a lack of an identifiable host. We select $2{,}298$ high-quality SNe Ia from the DES 5-yr data set an almost complete sample of detected SNe Ia. More than 700 of these have no spectroscopic host redshift and are potentially new SNIa compared to the DES-SN5YR cosmology analysis. To analyse these SNe Ia, we derive their redshifts and properties using only their light curves with a modified version of the SALT2 light-curve fitter. Compared to other DES SN Ia samples with spectroscopic redshifts, our new sample has in average higher redshift, bluer and broader light curves, and fainter host-galaxies. Future surveys such as LSST will also face an additional challenge, the scarcity of spectroscopic resources for follow-up. When applying our novel method to DES data, we reduce the need for follow-up by a factor of four and three for host-galaxy and live SN, respectively, compared to earlier approaches. Our novel method thus leads to better optimization of spectroscopic resources for follow-up.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Gravitational waves and galaxies cross-correlations: a forecast on GW biases for future detectors

ABSTRACT Gravitational waves (GWs) have rapidly become important cosmological probes since their first detection in 2015. As the number of detected events continues to rise, upcoming instruments like Einstein Telescope (ET) and Cosmic Explorer (CE) will observe millions of compact binary mergers. These detections, coupled with galaxy surveys by instruments such as the Dark Spectroscopic Energy Instrument (DESI), Euclid, and the Vera Rubin Observatory, will provide unique information on the large-scale structure of the universe by cross-correlating GWs with the distribution of galaxies hosting them. In this paper, we focus on how cross-correlations constrain the clustering bias of GWs emitted by the coalescence of binary black holes (BBHs). This parameter links BBHs to the underlying dark matter distribution, hence informing us how they populate galaxies. Using a multitracer approach, we forecast the precision of these measurements under different survey combinations. Our results indicate that current GW detectors will have limited precision, with measurement errors as high as $\displaystyle \sim 50~{{\ \rm per\ cent}}$. However, third-generation detectors like ET, when cross-correlated with Legacy Survey of Space and Time (LSST) data, can improve clustering bias measurements to within 2.5 per cent. Furthermore, we demonstrate that these cross-correlations can enable a per cent-level measurement of the magnification lensing effect on GWs. Despite this, there is a degeneracy between magnification and evolution biases, which hinders the precision of both. This degeneracy is most effectively addressed by assuming knowledge of one bias or targeting an optimal redshift range of $\displaystyle 1 \lt z \lt 2.5$. Our analysis opens new avenues for studying the distribution of BBHs and testing the nature of gravity through large-scale structure.

Zazzera, Stefano (ORCID:0000000158979221)↗
DOE OSTI2025

2D end-to-end modelling of kilonovae from binary neutron star merger remnants

We investigate the kilonova emission resulting from outflows produced in a 3D general-relativistic magnetohydrodynamic (GRMHD) simulation of a hypermassive neutron star (HMNS) remnant. We map the outflows into the flash hydrodynamics code to model their expansion in axisymmetry, and study the effects of employing different r-process heating rates. Except for the highest heating rate prescription, we find no significant differences with respect to overall ejecta dynamics and morphology compared to the simulation without heating. Once homologous expansion is attained, typically after ~2s for these ejecta, we map the outflows to the sedona radiative transfer code and compute the spectral evolution of the kilonova and broad-band light curves in various Legacy Survey of Space and Time (LSST) bands. The kilonova properties depend on the remnant lifetime, with peak luminosities and peak time-scales increasing for longer lived remnants that produce more massive ejecta. For all models, there is a strong dependence of both the bolometric and broad-band light curves on the viewing angle. While the short-lived (12 ms) remnant produces higher luminosities when viewed from angles closer to the pole, longer lived remnants (240 ms and 2.5 s) are more luminous when viewed from angles closer to the equator. Our results highlight the importance of self-consistent, long-term modelling of merger ejecta, and taking viewing-angle dependence into account when interpreting observed kilonova light curves. We find that magnetized outflows from an HMNS – if it survives long enough – could explain blue kilonovae, such as the blue emission seen in AT2017gfo.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Photometric classification of Hyper Suprime-Cam transients using machine learning

Abstract The advancement of technology has resulted in a rapid increase in supernova (SN) discoveries. The Subaru/Hyper Suprime-Cam (HSC) transient survey, conducted from fall 2016 through spring 2017, yielded 1824 SN candidates. This gave rise to the need for fast type classification for spectroscopic follow-up and prompted us to develop a machine learning algorithm using a deep neural network with highway layers. This algorithm is trained by actual observed cadence and filter combinations such that we can directly input the observed data array without any interpretation. We tested our model with a dataset from the LSST classification challenge (Deep Drilling Field). Our classifier scores an area under the curve (AUC) of 0.996 for binary classification (SN Ia or non-SN Ia) and 95.3% accuracy for three-class classification (SN Ia, SN Ibc, or SN II). Application of our binary classification to HSC transient data yields an AUC score of 0.925. With two weeks of HSC data since the first detection, this classifier achieves 78.1% accuracy for binary classification, and the accuracy increases to 84.2% with the full dataset. This paper discusses the potential use of machine learning for SN type classification purposes.

Takahashi, Ichiro↗
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↗
DOE OSTI2025

Dark energy survey year 3 results: Cosmological constraints from cluster abundances, weak lensing, and galaxy clustering

Galaxy clusters provide a unique probe of the late-time cosmic structure and serve as a powerful independent test of the Λ⁢CDM model. This work presents the first set of cosmological constraints derived with ∼16,000 optically selected redMaPPer clusters across nearly 5000 deg 2 using DES year 3 datasets. Our analysis leverages a consistent modeling framework for galaxy cluster cosmology and DES-Y3 joint analyses of galaxy clustering and weak lensing (3 × 2⁢pt), ensuring direct comparability with the DES-Y3 3 × 2⁢pt analysis. Here, we obtain constraints of 𝑆 8 = 0.864 ± 0.035 and Ω m = $0.26⁢5^{+0.019}_{−0.031}$ from the cluster-based data vector. We find that cluster constraints and 3 × 2⁢pt constraints are consistent under the Λ⁢CDM model with a posterior predictive distribution (PPD) value of 0.53. The consistency between clusters and 3 × 2⁢pt provides a stringent test of Λ⁢CDM across different mass and spatial scales. Jointly analyzing clusters with 3 × 2⁢pt further improves cosmological constraints, yielding 𝑆 8 = $0.81⁢1^{+0.022}_{−0.020}$ and Ω m = $0.29⁢4^{+0.022}_{−0.033}$, a 24% improvement in the Ω m − 𝑆 8 figure of merit over 3 × 2⁢pt alone. Moreover, we find no significant deviation from the Planck CMB constraints with a probability to exceed (PTE) value of 0.6, significantly reducing previous 𝑆 8 tension claims. Finally, combining DES 3 × 2⁢pt, DES clusters, and Planck CMB places an upper limit on the sum of neutrino masses of ∑𝑚 𝜈 < 0.26 eV at 95% confidence under the Λ⁢CDM model. These results establish optically selected clusters as a key cosmological probe and pave the way for cluster-based analyses in upcoming stage-IV surveys such as LSST, Euclid, and Roman.

Abbott, T. M. C. [NSF’s National Optical-Infrared ↗
DOE OSTI2025

Evidence for large baryonic feedback at low and intermediate redshifts from kinematic Sunyaev-Zel’dovich observations with ACT and DESI photometric galaxies

Recent advances in cosmological observations have provided an unprecedented opportunity to investigate the distribution of baryons relative to the underlying matter. In this work, we show that the gas is more extended than the dark matter, and the amount of baryonic feedback at $z \lesssim 1$ disfavors low-feedback models such as that of state-of-the-art hydrodynamical simulation IllustrisTNG compared with high-feedback models such as that of the original Illustris simulation. This has important implications for bridging the gap between theory and observations and understanding galaxy formation and evolution. Furthermore, a better grasp of the baryon-dark matter link is critical to future cosmological analyses, which are currently impeded by our limited knowledge of baryonic feedback. Here, we measure the kinematic Sunyaev-Zel'dovich (kSZ) effect from the Atacama Cosmology Telescope (ACT), stacked on the luminous red galaxy (LRG) sample of the Dark Energy Spectroscopic Instrument (DESI) imaging survey. This is the first analysis to use photometric redshifts for reconstructing galaxy velocities. Due to the large number of galaxies comprising the DESI imaging survey, this is the highest signal-to-noise stacked kSZ measurement to date: we detect the signal at 13$σ$, finding strong evidence that the gas is more spread out than the dark matter, as well as a preference for larger feedback compared to some commonly used state-of-the-art hydrodynamical simulations. Here, our work opens up the possibility of recalibrating large hydrodynamical simulations using the kSZ effect. In addition, our findings highlight the importance of properly accounting for baryonic feedback with future surveys such as LSST through direct probes such as the kSZ, and shed light on long-standing enigmas in astrophysics, such as the “missing baryon” problem.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Optimal multifrequency weighting for CMB lensing

We report that extragalactic foregrounds in cosmic microwave background (CMB) temperature maps lead to significant biases in CMB lensing reconstruction if not properly accounted for. Combinations of multifrequency data have been used to minimize the overall map variance (internal linear combination, or ILC), or specifically null a given foreground, but these are not tailored to CMB lensing. In this paper, we derive an optimal multifrequency combination to jointly minimize CMB lensing noise and bias. We focus on the standard lensing quadratic estimator, as well as the "shear-only"and source-hardened estimators, whose responses to foregrounds differ. We show that an optimal multifrequency combination is a compromise between the ILC and joint deprojection, which nulls the thermal Sunyaev-Zel'dovich (tSZ) and cosmic infrared background (CIB) contributions. In particular, for a Simons Observatory-like experiment with ℓ max,T =3000, we find that profile hardening alone (with the standard ILC) reduces the bias to the lensing power amplitude by 40%, at a 20% cost in noise, while the bias to the cross-correlation with a LSST-like sample is reduced by nearly an order of magnitude at a 10% noise cost, relative to the standard quadratic estimator. With a small amount of joint deprojection the bias to the profile hardened estimator can be further reduced to less than half the statistical uncertainty on the respective amplitudes, at a 20% and 5% noise cost for the auto- and cross-correlation respectively, relative to the profile hardened estimator with the standard ILC weights. Finally, we explore possible improvements with more aggressive masking and varying ℓ max,T .

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Simons Observatory: Constraining inflationary gravitational waves with multitracer B-mode delensing

We introduce and validate a delensing framework for the Simons Observatory (SO), which will be used to improve constraints on inflationary gravitational waves by reducing the lensing noise in measurements of the B modes in CMB polarization. SO will initially observe CMB by using three small aperture telescopes and one large-aperture telescope. While polarization maps from small-aperture telescopes will be used to constrain inflationary gravitational waves, the internal CMB lensing maps used to delens will be reconstructed from data from the large-aperture telescope. Since lensing maps obtained from the SO data will be noise dominated on subdegree scales, the SO lensing framework constructs a template for lensing-induced B modes by combining internal CMB lensing maps with maps of the cosmic infrared background from Planck as well as galaxy density maps from the LSST survey. We construct a likelihood for constraining the tensor-to-scalar ratio r that contains auto and cross spectra between observed B modes and the lensing B-mode template. We test our delensing analysis pipeline on map-based simulations containing survey nonidealities, but that, for this initial exploration, does not include contamination from Galactic and extragalactic foregrounds. We find that the SO survey masking and inhomogeneous and atmospheric noise have very little impact on the delensing performance, and the r constraint becomes σ(r)≈0.0015 which is close to that obtained from the idealized forecasts in the absence of the Galactic foreground and is nearly a factor of 2 tighter than without delensing. We also find that uncertainties in the external large-scale structure tracers used in our multitracer delensing pipeline lead to bias much smaller than the 1σ statistical uncertainties.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

The Simons Observatory: Combining cross-spectral foreground cleaning with multitracer B -mode delensing for improved constraints on inflation

The Simons Observatory (SO), due to start full science operations in early 2025, aims to set tight constraints on inflationary physics by inferring the tensor-to-scalar ratio r from measurements of cosmic microwave background (CMB) polarization B-modes. Its nominal design including three small-aperture telescopes (SATs) targets a precision σ⁡(r = 0) ≤ 0.003 without delensing. Achieving this goal and further reducing uncertainties requires a thorough understanding and mitigation of other large-scale B-mode sources such as Galactic foregrounds and weak gravitational lensing. We present an analysis pipeline aiming to estimate r by including delensing within a cross-spectral likelihood, and demonstrate it for the first time on SO-like simulations accounting for various levels of foreground complexity, inhomogeneous noise and partial sky coverage. As introduced in an earlier SO delensing paper, lensing B-modes are synthesized using internal CMB lensing reconstructions as well as Planck-like cosmic infrared background maps and LSST-like galaxy density maps. We then extend SO’s power-spectrum-based foreground-cleaning algorithm to include all auto- and cross-spectra between the lensing template and the SAT B-modes in the likelihood function. This allows us to constrain r and the parameters of our foreground model simultaneously. Within this framework, we demonstrate the equivalence of map-based and cross-spectral delensing and use it to motivate an optimized pixel-weighting scheme for power spectrum estimation. We start by validating our pipeline in the simplistic case of uniform foreground spectral energy distributions. In the absence of primordial B-modes, we find that the 1⁢σ statistical uncertainty on r, σ⁡(r), decreases by 37% as a result of delensing. Tensor modes at the level of r = 0.01 are successfully detected by our pipeline. Even when using more realistic foreground models including spatial variations in the dust and synchrotron spectral properties, we obtain unbiased estimates of r both with and without delensing by employing the moment-expansion method. In this case, uncertainties are increased due to the higher number of model parameters, and delensing-related improvements range between 27% and 31%. These results constitute the first realistic assessment of the delensing performance at SO’s nominal sensitivity level.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Exploring Primordial Black Holes from the Multiverse with Optical Telescopes

Primordial black holes (PBHs) are a viable candidate for dark matter if the PBH masses are in the currently unconstrained “sublunar” mass range. We revisit the possibility that PBHs were produced by nucleation of false vacuum bubbles during inflation. We show that this scenario can produce a population of PBHs that simultaneously accounts for all dark matter, explains the candidate event in the Subaru Hyper Suprime-Cam (HSC) data, and contains both heavy black holes as observed by LIGO and very heavy seeds of supermassive black holes. Here, we demonstrate with numerical studies that future observations of HSC, as well as other optical surveys, such as LSST, will be able to provide a definitive test for this generic PBH formation mechanism if it is the dominant source of dark matter.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

gp_blendclass_singleband

The code used for the data preprocessing, image simulation, and model training and analysis reported in the paper "Gaussian Process Classification for Galaxy Blend Identification in LSST" (arXiv:2107.09246).

Buchanan, JamesJ.↗
DOE OSTI2021

slaclab/lsst-ac-filter-relay

This is the repository for "lsst-ac-filter-relay" developed by SLAC National Accelerator Laboratory.

Ruckman, Larry↗