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Abstract We infer the growth of large scale structure over the redshift range 0.4 ≲z≲ 1 from the cross-correlation of spectroscopically calibrated Luminous Red Galaxies (LRGs) selected from the Dark Energy Spectroscopic Instrument (DESI) legacy imaging survey with CMB lensing maps reconstructed from the latestPlanckand ACT data.We adopt a hybrid effective field theory (HEFT) model that robustly regulates the cosmological information obtainable from smaller scales, such that our cosmological constraints are reliably derived from the (predominantly) linear regime.We perform an extensive set of bandpower- and parameter-level systematics checks to ensure the robustness of our results and to characterize the uniformity of the LRG sample.We demonstrate that our results are stable to a wide range of modeling assumptions, finding excellent agreement with a linear theory analysis performed on a restricted range of scales.From a tomographic analysis of the four LRG photometric redshift bins we find that the rate of structure growth is consistent with ΛCDM with an overall amplitude that is ≃ 5-7% lower than predicted by primary CMB measurements with modest (∼ 2σ) statistical significance.From the combined analysis of all four bins and their cross-correlations withPlanckwe obtainS₈= 0.765 ± 0.023, which is less discrepant with primary CMB measurements than previous DESI LRG crossPlanckCMB lensing results.From the cross-correlation with ACT we obtainS₈= 0.790^+0.024_-0.027, while when jointly analyzingPlanckand ACT we findS₈= 0.775^+0.019_-0.022from our data alone andσ₈= 0.772^+0.020_-0.023with the addition of BAO data.These constraints are consistent with the latestPlanckprimary CMB analyses at the ≃ 1.6-2.2σlevel, and are in excellent agreement with galaxy lensing surveys. 

Many astrophysical analyses depend on estimates of redshifts (a proxy for distance) determined from photometric (i.e., imaging) data alone. Inaccurate estimates of photometric redshift uncertainties can result in large systematic errors. However, probability distribution outputs from many photometric redshift methods do not follow the frequentist definition of a Probability Density Function (PDF) for redshift — i.e., the fraction of times the true redshift falls between two limits z1 and z2 should be equal to the integral of the PDF between these limits. Previous works have used the global distribution of Probability Integral Transform (PIT) values to re-calibrate PDFs, but offsetting inaccuracies in different regions of feature space can conspire to limit the efficacy of the method. We leverage a recently developed regression technique that characterizes the local PIT distribution at any location in feature space to perform a local re-calibration of photometric redshift PDFs resulting in calibrated predictive distributions. Though we focus on an example from astrophysics, our method can produce predictive distributions which are calibrated at all locations in feature space for any use case. 

Abstract Poststarburst galaxies (PSBs) are young quiescent galaxies that have recently experienced a rapid decrease in star formation, allowing us to probe the fast-quenching period of galaxy evolution. In this work, we obtained Hubble Space Telescope (HST)/WFC3 F110W imaging to measure the sizes of 171 massive ( $\log (M_{*}/M_{\odot })\sim 11)$spectroscopically identified PSBs at 1 <z1.3 selected from the DESI Survey Validation luminous red galaxy sample. This statistical sample constitutes an order of magnitude increase from the ∼20 PSBs with space-based imaging and deep spectroscopy. We perform structural fitting of the target galaxies withpysersicand compare them to quiescent and star-forming galaxies in the 3D-HST survey. We find that these PSBs are more compact than the general population of quiescent galaxies, lying systematically ∼0.1 dex below the established size–mass relation. However, their central surface mass densities are similar to those of their quiescent counterparts ( $\log \left({\mathrm{\Sigma }}_{1\mathrm{kpc}}/\right(M_{\odot }{\mathrm{kpc}}^{-2}\left)\right)\sim 10.1$). These findings are easily reconciled by later ex situ growth via minor mergers or a slight progenitor bias. These PSBs are round in projection (b/a_median∼ 0.8), suggesting that they are primarily spheroids, not disks, in 3D. We find no correlation between the time since quenching and light-weighted PSB sizes or central densities. This disfavors apparent structural growth due to the fading of centralized starbursts in this galaxy population. Instead, we posit that the fast quenching of massive galaxies at this epoch occurs preferentially in galaxies with preexisting compact structures. 

ABSTRACT Studies of cosmology, galaxy evolution, and astronomical transients with current and next-generation wide-field imaging surveys like the Rubin Observatory Legacy Survey of Space and Time are all critically dependent on estimates of photometric redshifts. Capsule networks are a new type of neural network architecture that is better suited for identifying morphological features of the input images than traditional convolutional neural networks. We use a deep capsule network trained on ugriz images, spectroscopic redshifts, and Galaxy Zoo spiral/elliptical classifications of ∼400 000 Sloan Digital Sky Survey galaxies to do photometric redshift estimation. We achieve a photometric redshift prediction accuracy and a fraction of catastrophic outliers that are comparable to or better than current methods for SDSS main galaxy sample-like data sets (r ≤ 17.8 and zspec ≤ 0.4) while requiring less data and fewer trainable parameters. Furthermore, the decision-making of our capsule network is much more easily interpretable as capsules act as a low-dimensional encoding of the image. When the capsules are projected on a two-dimensional manifold, they form a single redshift sequence with the fraction of spirals in a region exhibiting a gradient roughly perpendicular to the redshift sequence. We perturb encodings of real galaxy images in this low-dimensional space to create synthetic galaxy images that demonstrate the image properties (e.g. size, orientation, and surface brightness) encoded by each dimension. We also measure correlations between galaxy properties (e.g. magnitudes, colours, and stellar mass) and each capsule dimension. We publicly release our code, estimated redshifts, and additional catalogues at https://biprateep.github.io/encapZulate-1. 

Abstract We measure the clustering of Lyman Alpha Emitting galaxies (LAEs) selected from the One-hundred-square-degree DECam Imaging in Narrowbands (ODIN) survey, with spectroscopic follow-up from Dark Energy Spectroscopic Instrument (DESI). We use DESI spectroscopy to optimize our selection and to constrain the interloper fraction and redshift distribution of our narrow-band selected sources. We select samples of 4000 LAEs atz= 2.45 and 3.1 in 9 sq.deg. centered on the COSMOS field with median Lyα fluxes of ≈ 10^-16erg s^-1cm^-2. Covariances and cosmological inferences are obtained from a series of mock catalogs built upon high-resolution N-body simulations that match the footprint, number density, redshift distribution and observed clustering of the sample. We find that both samples have a correlation length ofr₀= 3.0 ± 0.2 h^-1Mpc. Within our fiducial cosmology these correspond to 3D number densities of ≈ 10^-3h³Mpc^-3and, from our mock catalogs, biases of 1.7 and 2.0 atz= 2.45 and 3.1, respectively. We discuss the implications of these measurements for the use of LAEs as large-scale structure tracers for high-redshift cosmology. 

Many astrophysical analyses depend on estimates of redshifts (a proxy for distance) determined from photometric (i.e., imaging) data alone. Inaccurate estimates of photometric redshift uncertainties can result in large systematic errors. However, probability distribution outputs from many photometric redshift methods do not follow the frequentist definition of a Probability Density Function (PDF) for redshift -- i.e., the fraction of times the true redshift falls between two limits z1 and z2 should be equal to the integral of the PDF between these limits. Previous works have used the global distribution of Probability Integral Transform (PIT) values to re-calibrate PDFs, but offsetting inaccuracies in different regions of feature space can conspire to limit the efficacy of the method. We leverage a recently developed regression technique that characterizes the local PIT distribution at any location in feature space to perform a local re-calibration of photometric redshift PDFs. Though we focus on an example from astrophysics, our method can produce PDFs which are calibrated at all locations in feature space for any use case. 

Abstract We present a multiband study of FRB 20180916B, a repeating source with a 16.3 day periodicity. We report the detection of four, one, and seven bursts from observations spanning 3 days using the upgraded Giant Metrewave Radio Telescope (300–500 MHz), the Canadian Hydrogen Intensity Mapping Experiment (400–800 MHz) and the Green Bank Telescope (600–1000 MHz), respectively. We report the first ever detection of the source in the 800–1000 MHz range along with one of the widest instantaneous bandwidth detections (200 MHz) at lower frequencies. We identify 30 μ s wide structures in one of the bursts at 800 MHz, making it the lowest frequency detection of such structures for this fast radio burst thus far. There is also a clear indication of high activity of the source at a higher frequency during earlier phases of the activity cycle. We identify a gradual decrease in the rotation measure over two years and no significant variations in the dispersion measure. We derive useful conclusions about progenitor scenarios, energy distribution, emission mechanisms, and variation of the downward drift rate of emission with frequency. Our results reinforce that multiband observations are an effective approach to study repeaters, and even one-off events, to better understand their varying activity and spectral anomalies. 

Abstract We utilize ∼17,000 bright luminous red galaxies (LRGs) from the novel Dark Energy Spectroscopic Instrument Survey Validation spectroscopic sample, leveraging its deep (∼2.5 hr galaxy⁻¹exposure time) spectra to characterize the contribution of recently quenched galaxies to the massive galaxy population at 0.4 <z< 1.3. We useProspectorto infer nonparametric star formation histories and identify a significant population of recently quenched galaxies that have joined the quiescent population within the past ∼1 Gyr. The highest-redshift subset (277 atz> 1) of our sample of recently quenched galaxies represents the largest spectroscopic sample of post-starburst galaxies at that epoch. At 0.4 <z< 0.8, we measure the number density of quiescent LRGs, finding that recently quenched galaxies constitute a growing fraction of the massive galaxy population with increasing look-back time. Finally, we quantify the importance of this population among massive ( $\log \left(M_{\star }/M_{\odot }\right)$> 11.2) LRGs by measuring the fraction of stellar mass each galaxy formed in the gigayear before observation,f_{1 Gyr}. Although galaxies withf_{1 Gyr}> 0.1 are rare atz∼ 0.4 (≲0.5% of the population), byz∼ 0.8, they constitute ∼3% of massive galaxies. Relaxing this threshold, we find that galaxies withf_{1 Gyr}> 5% constitute ∼10% of the massive galaxy population atz∼ 0.8. We also identify a small but significant sample of galaxies atz= 1.1–1.3 that formed withf_{1 Gyr}> 50%, implying that they may be analogs to high-redshift quiescent galaxies that formed on similar timescales. Future analysis of this unprecedented sample promises to illuminate the physical mechanisms that drive the quenching of massive galaxies after cosmic noon. 

Abstract Over the next 5 yr, the Dark Energy Spectroscopic Instrument (DESI) will use 10 spectrographs with 5000 fibers on the 4 m Mayall Telescope at Kitt Peak National Observatory to conduct the first Stage IV dark energy galaxy survey. Atz< 0.6, the DESI Bright Galaxy Survey (BGS) will produce the most detailed map of the universe during the dark-energy-dominated epoch with redshifts of >10 million galaxies spanning 14,000 deg². In this work, we present and validate the final BGS target selection and survey design. From the Legacy Surveys, BGS will target anr< 19.5 mag limited sample (BGS Bright), a fainter 19.5 <r< 20.175 color-selected sample (BGS Faint), and a smaller low-zquasar sample. BGS will observe these targets using exposure times scaled to achieve homogeneous completeness and cover the footprint three times. We use observations from the Survey Validation programs conducted prior to the main survey along with simulations to show that BGS can complete its strategy and make optimal use of “bright” time. BGS targets have stellar contamination <1%, and their densities do not depend strongly on imaging properties. BGS Bright will achieve >80% fiber assignment efficiency. Finally, BGS Bright and BGS Faint will achieve >95% redshift success over any observing condition. BGS meets the requirements for an extensive range of scientific applications. BGS will yield the most precise baryon acoustic oscillation and redshift-space distortion measurements atz< 0.4. It presents opportunities for new methods that require highly complete and dense samples (e.g.,N-point statistics, multitracers). BGS further provides a powerful tool to study galaxy populations and the relations between galaxies and dark matter.