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Rachel Mandelbaum

Publications and source records attributed to Rachel Mandelbaum.

At least 73 records · Page 4Linked to original sources

Report of the Topical Group on Dark Energy and Cosmic Acceleration: Complementarity of Probes and New Facilities for Snowmass 2021

The mechanism(s) driving the early- and late-time accelerated expansion of the Universe represent one of the most compelling mysteries in fundamental physics today. The path to understanding the causes of early- and late-time acceleration depends on fully leveraging ongoing surveys, developing and demonstrating new technologies, and constructing and operating new instruments. This report presents a multi-faceted vision for the cosmic survey program in the 2030s and beyond that derives from these considerations. Cosmic surveys address a wide range of fundamental physics questions, and are thus a unique and powerful component of the HEP experimental portfolio.

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Weak Gravitational Lensing Shear Estimation with Metacalibration for the Roman High-Latitude Imaging Survey

We investigate the performance of the Metacalibration shear calibration framework using simulated imaging data for the Nancy Grace Roman Space Telescope (Roman) reference High-Latitude Imaging Survey (HLIS). The weak lensing program of the Roman mission requires the mean weak lensing shear estimate to be calibrated within about 0.03%. To reach this goal, we can test our calibration process with various simulations and ultimately isolate the sources of residual shear biases in order to improve our methods. In this work, we build on the Roman HLIS image simulation pipeline in Troxel et al. 2021 to incorporate several new realistic processing-pipeline updates necessary to more accurately process the imaging data and calibrate the shear. We show the first results of this calibration for six deg$^2$ of the simulated reference HLIS using Metacalibration and compare these results to measurements on more simple, faster Roman-like image simulations. In both cases, we neglect the impact of blending of objects. We find that in the simplified simulations, Metacalibration can calibrate shapes to be within $m=(-0.01\pm 0.10)$%. When applied to the current most-realistic version of the simulations, the precision is much lower, with estimates of $m=(-1.34\pm 0.67)$% for joint multi-band single-epoch measurements and $m=(-1.13\pm 0.60)$% for multi-band coadd measurements. These results are all consistent with zero within 1-2$σ$, indicating we are currently limited by our simulated survey volume. Further work on testing the shear calibration methodology is necessary at higher precision to reach the level of the Roman requirements, in particular in the presence of blending. Current results demonstrate, however, that the Metacalibration method can work on undersampled space-based Roman imaging data at levels comparable to the requirements of current weak lensing surveys.

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A Unified Catalog-level Reanalysis of Stage-III Cosmic Shear Surveys

Cosmological parameter constraints from recent galaxy imaging surveys are reaching $2-3\%$-level accuracy. The upcoming Legacy Survey of Space and Time (LSST) of the Vera C. Rubin Observatory will produce sub-percent level measurements of cosmological parameters, providing a milestone test of the $Λ$CDM model. To supply guidance to the upcoming LSST analysis, it is important to understand thoroughly the results from different recent galaxy imaging surveys and assess their consistencies. In this work we perform a unified catalog-level reanalysis of three cosmic shear datasets: the first year data from the Dark Energy Survey (DES-Y1), the 1,000 deg$^{2}$ dataset from the Kilo-Degree Survey (KiDS-1000), and the first year data from the Hyper Suprime-Cam Subaru Strategic Program (HSC-Y1). We utilize a pipeline developed and rigorously tested by the LSST Dark Energy Science Collaboration to perform the reanalysis and assess the robustness of the results to analysis choices. We find the $S_{8}$ constraint to be robust to two different small-scale modeling approaches, and varying choices of cosmological priors. Our unified analysis allows the consistency of the surveys to be rigorously tested and we find the three surveys to be statistically consistent. Due to the partially overlapping footprint, we model the cross-covariance between KiDS-1000 and HSC-Y1 approximately when combining all three datasets, resulting in a $1.6-1.9\%$ constraint on $S_8$ given different assumptions on the cross-covariance.

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From Data to Software to Science with the Rubin Observatory LSST

The Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) dataset will dramatically alter our understanding of the Universe, from the origins of the Solar System to the nature of dark matter and dark energy. Much of this research will depend on the existence of robust, tested, and scalable algorithms, software, and services. Identifying and developing such tools ahead of time has the potential to significantly accelerate the delivery of early science from LSST. Developing these collaboratively, and making them broadly available, can enable more inclusive and equitable collaboration on LSST science. To facilitate such opportunities, a community workshop entitled "From Data to Software to Science with the Rubin Observatory LSST" was organized by the LSST Interdisciplinary Network for Collaboration and Computing (LINCC) and partners, and held at the Flatiron Institute in New York, March 28-30th 2022. The workshop included over 50 in-person attendees invited from over 300 applications. It identified seven key software areas of need: (i) scalable cross-matching and distributed joining of catalogs, (ii) robust photometric redshift determination, (iii) software for determination of selection functions, (iv) frameworks for scalable time-series analyses, (v) services for image access and reprocessing at scale, (vi) object image access (cutouts) and analysis at scale, and (vii) scalable job execution systems. This white paper summarizes the discussions of this workshop. It considers the motivating science use cases, identified cross-cutting algorithms, software, and services, their high-level technical specifications, and the principles of inclusive collaborations needed to develop them. We provide it as a useful roadmap of needs, as well as to spur action and collaboration between groups and individuals looking to develop reusable software for early LSST science.

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Galaxies and Halos on Graph Neural Networks: Deep Generative Modeling Scalar and Vector Quantities for Intrinsic Alignment

In order to prepare for the upcoming wide-field cosmological surveys, large simulations of the Universe with realistic galaxy populations are required. In particular, the tendency of galaxies to naturally align towards overdensities, an effect called intrinsic alignments (IA), can be a major source of systematics in the weak lensing analysis. As the details of galaxy formation and evolution relevant to IA cannot be simulated in practice on such volumes, we propose as an alternative a Deep Generative Model. This model is trained on the IllustrisTNG-100 simulation and is capable of sampling the orientations of a population of galaxies so as to recover the correct alignments. In our approach, we model the cosmic web as a set of graphs, where the graphs are constructed for each halo, and galaxy orientations as a signal on those graphs. The generative model is implemented on a Generative Adversarial Network architecture and uses specifically designed Graph-Convolutional Networks sensitive to the relative 3D positions of the vertices. Given (sub)halo masses and tidal fields, the model is able to learn and predict scalar features such as galaxy and dark matter subhalo shapes; and more importantly, vector features such as the 3D orientation of the major axis of the ellipsoid and the complex 2D ellipticities. For correlations of 3D orientations the model is in good quantitative agreement with the measured values from the simulation, except for at very small and transition scales. For correlations of 2D ellipticities, the model is in good quantitative agreement with the measured values from the simulation on all scales. Additionally, the model is able to capture the dependence of IA on mass, morphological type and central/satellite type.

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Galaxy Distribution Incompleteness Testing Using Self-Organizing Maps

The calibration of redshift distributions for photometric samples using spectroscopic surveys is plagued by the difficulty in modelling the selection functions of spectroscopic surveys. In this work, we analyse how these selection functions impact redshift inference and quantify the induced biases using local calibration tests in photometry space. The study is carried out using simulations that mimic the radial selection function of a spectroscopic survey and an accompanying mock catalog of a photometric galaxy survey catalog. We use a self-organizing map to partition the photometry space and perform a local $χ^2$ test to study the probability calibration of redshift inferences that use the spectroscopic data for calibration. The goal of this work is to investigate the effect of uncorrected selection functions in the calibration data on redshift prediction accuracy and critically discuss mitigation methods. In particular we test culling-based bias correction techniques, that aim to remove redshift calibration biases by identifying regions in photometry with few spectroscopic calibration data, and propose avenues for future research. We found that removing regions in color-magnitude space that are underpopulated with spectroscopic calibration data does not remove all biases in redshift inference induced by the selection function.

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Intrinsic alignments of bulges and discs

Galaxies exhibit coherent alignments with local structure in the Universe. This effect, called Intrinsic Alignments (IA), is an important contributor to the systematic uncertainties for wide-field weak lensing surveys. On cosmological distance scales, intrinsic shape alignments have been observed in red galaxies, which are usually bulge-dominated; while blue galaxies, which are mostly disc-dominated, exhibit shape alignments consistent with a null detection. However, disc-dominated galaxies typically consist of two prominent structures: disc and bulge. Since the bulge component has similar properties as elliptical galaxies and is thought to have formed in a similar fashion, naturally one could ask whether the bulge components exhibit similar alignments as ellipticals? In this paper, we investigate how different components of galaxies exhibit IA in the TNG100-1 cosmological hydrodynamical simulation, as well as the dependence of IA on the fraction of stars in rotation-dominated structures at $z=0$. The measurements were controlled for mass differences between the samples. We find that the bulges exhibit significantly higher IA signals, with a nonlinear alignment model amplitude of $A_I = 2.98^{+0.36}_{-0.37}$ compared to the amplitude for the galaxies as a whole (both components), $A_I = 1.13^{+0.37}_{-0.35}$. The results for bulges are statistically consistent with those for elliptical galaxies, which have $A_I = 3.47^{+0.57}_{-0.57}$. These results highlight the importance of studying galaxy dynamics in order to understand galaxy alignments and their cosmological implications.

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Snowmass2021: Opportunities from Cross-survey Analyses of Static Probes

Cosmological data in the next decade will be characterized by high-precision, multi-wavelength measurements of thousands of square degrees of the same patches of sky. By performing multi-survey analyses that harness the correlated nature of these datasets, we will gain access to new science, and increase the precision and robustness of science being pursued by each individual survey. However, effective application of such analyses requires a qualitatively new level of investment in cross-survey infrastructure, including simulations, associated modeling, coordination of data sharing, and survey strategy. The scientific gains from this new level of investment are multiplicative, as the benefits can be reaped by even present-day instruments, and can be applied to new instruments as they come online.

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Snowmass2021 Cosmic Frontier White Paper: Enabling Flagship Dark Energy Experiments to Reach their Full Potential

A new generation of powerful dark energy experiments will open new vistas for cosmology in the next decade. However, these projects cannot reach their utmost potential without data from other telescopes. This white paper focuses in particular on the compelling benefits of ground-based spectroscopic and photometric observations to complement the Vera C. Rubin Observatory, as well as smaller programs in aid of a DESI-2 experiment and CMB-S4. These additional data sets will both improve dark energy constraints from these flagship projects beyond what would possible on their own and open completely new windows into fundamental physics. For example, additional photometry and single-object spectroscopy will provide necessary follow-up information for supernova and strong lensing cosmology, while highly-multiplexed spectroscopy both from smaller facilities over wide fields and from larger facilities over narrower regions of sky will yield more accurate photometric redshift estimates for weak lensing and galaxy clustering measurements from the Rubin Observatory, provide critical spectroscopic host galaxy redshifts for supernova Hubble diagrams, provide improved understanding of limiting astrophysical systematic effects, and enable new measurements that probe the nature of gravity. A common thread is that access to complementary data from a range of telescopes/instruments would have a substantial impact on the rate of advance of dark energy science in the coming years.

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Snowmass2021 Cosmic Frontier White Paper: Rubin Observatory after LSST

The Vera C. Rubin Observatory will begin the Legacy Survey of Space and Time (LSST) in 2024, spanning an area of 18,000 square degrees in six bands, with more than 800 observations of each field over ten years. The unprecedented data set will enable great advances in the study of the formation and evolution of structure and exploration of physics of the dark universe. The observations will hold clues about the cause for the accelerated expansion of the universe and possibly the nature of dark matter. During the next decade, LSST will be able to confirm or dispute if tensions seen today in cosmological data are due to new physics. New and unexpected phenomena could confirm or disrupt our current understanding of the universe. Findings from LSST will guide the path forward post-LSST. The Rubin Observatory will still be a uniquely powerful facility even then, capable of revealing further insights into the physics of the dark universe. These could be obtained via innovative observing strategies, e.g., targeting new probes at shorter timescales than with LSST, or via modest instrumental changes, e.g., new filters, or through an entirely new instrument for the focal plane. This White Paper highlights some of the opportunities in each scenario from Rubin observations after LSST.

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Snowmass2021: Vera C. Rubin Observatory as a Flagship Dark Matter Experiment

Establishing that Vera C. Rubin Observatory is a flagship dark matter experiment is an essential pathway toward understanding the physical nature of dark matter. In the past two decades, wide-field astronomical surveys and terrestrial laboratories have jointly created a phase transition in the ecosystem of dark matter models and probes. Going forward, any robust understanding of dark matter requires astronomical observations, which still provide the only empirical evidence for dark matter to date. We have a unique opportunity right now to create a dark matter experiment with Rubin Observatory Legacy Survey of Space and Time (LSST). This experiment will be a coordinated effort to perform dark matter research, and provide a large collaborative team of scientists with the necessary organizational and funding supports. This approach leverages existing investments in Rubin. Studies of dark matter with Rubin LSST will also guide the design of, and confirm the results from, other dark matter experiments. Supporting a collaborative team to carry out a dark matter experiment with Rubin LSST is the key to achieving the dark matter science goals that have already been identified as high priority by the high-energy physics and astronomy communities.

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The three-year shear catalog of the Subaru Hyper Suprime-Cam SSP Survey

We present the galaxy shear catalog that will be used for the three-year cosmological weak gravitational lensing analyses using data from the Wide layer of the Hyper Suprime-Cam (HSC) Subaru Strategic Program (SSP) Survey. The galaxy shapes are measured from the $i$-band imaging data acquired from 2014 to 2019 and calibrated with image simulations that resemble the observing conditions of the survey based on training galaxy images from the Hubble Space Telescope in the COSMOS region. The catalog covers an area of 433.48 deg$^2$ of the northern sky, split into six fields. The mean $i$-band seeing is 0.59 arcsec. With conservative galaxy selection criteria (e.g., $i$-band magnitude brighter than 24.5), the observed raw galaxy number density is 22.9 arcmin$^{-2}$, and the effective galaxy number density is 19.9 arcmin$^{-2}$. The calibration removes the galaxy property-dependent shear estimation bias to a level: $|δm|<9\times 10^{-3}$. The bias residual $δm$ shows no dependence on redshift in the range $0 1$ degree scales and will require mitigation during the inference of cosmological parameters using cosmic shear measurements.

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Validating Synthetic Galaxy Catalogs for Dark Energy Science in the LSST Era

Large simulation efforts are required to provide synthetic galaxy catalogs for ongoing and upcoming cosmology surveys. These extragalactic catalogs are being used for many diverse purposes covering a wide range of scientific topics. In order to be useful, they must offer realistically complex information about the galaxies they contain. Hence, it is critical to implement a rigorous validation procedure that ensures that the simulated galaxy properties faithfully capture observations and delivers an assessment of the level of realism attained by the catalog. We present here a suite of validation tests that have been developed by the Rubin Observatory Legacy Survey of Space and Time (LSST) Dark Energy Science Collaboration (DESC). We discuss how the inclusion of each test is driven by the scientific targets for static ground-based dark energy science and by the availability of suitable validation data. The validation criteria that are used to assess the performance of a catalog are flexible and depend on the science goals. We illustrate the utility of this suite by showing examples for the validation of cosmoDC2, the extragalactic catalog recently released for the LSST DESC second Data Challenge.

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Impact of Point Spread Function Higher Moments Error on Weak Gravitational Lensing

Weak gravitational lensing is one of the most powerful tools for cosmology, while subject to challenges in quantifying subtle systematic biases. The Point Spread Function (PSF) can cause biases in weak lensing shear inference when the PSF model does not match the true PSF that is convolved with the galaxy light profile. Although the effect of PSF size and shape errors - i.e., errors in second moments - is well studied, weak lensing systematics associated with errors in higher moments of the PSF model require further investigation. The goal of our study is to estimate their potential impact for LSST weak lensing analysis. We go beyond second moments of the PSF by using image simulations to relate multiplicative bias in shear to errors in the higher moments of the PSF model. We find that the current level of errors in higher moments of the PSF model in data from the Hyper Suprime-Cam (HSC) survey can induce a $\sim 0.05 $ per cent shear bias, making this effect unimportant for ongoing surveys but relevant at the precision of upcoming surveys such as LSST.

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Cosmological inference from the emulator based halo model II: Joint analysis of galaxy-galaxy weak lensing and galaxy clustering from HSC-Y1 and SDSS

We present high-fidelity cosmology results from a blinded joint analysis of galaxy-galaxy weak lensing ($Δ\!Σ$) and projected galaxy clustering ($w_{\rm p}$) measured from the Hyper Suprime-Cam Year-1 (HSC-Y1) data and spectroscopic Sloan Digital Sky Survey (SDSS) galaxy catalogs in the redshift range $0.15<z<0.7$. We define luminosity-limited samples of SDSS galaxies to serve as the tracers of $w_{\rm p}$ in three spectroscopic redshift bins, and as the lens samples for $Δ\!Σ$. For the $Δ\!Σ$ measurements, we select a single sample of 4 million source galaxies over 140 deg$^2$ from HSC-Y1 with photometric redshifts (photo-$z$) greater than 0.75, enabling a better handle of photo-$z$ errors by comparing the $Δ\!Σ$ amplitudes for the three lens redshift bins. For cosmological parameter inference, we use an input galaxy-halo connection model built on the {\tt Dark Emulator} package with a halo occupation distribution that includes nuisance parameters to marginalize over modeling uncertainties. We model the $Δ\!Σ$ and $w_{\rm p}$ measurements on scales from $R\simeq 3$ and $2\,h^{-1}{\rm Mpc}$, respectively, up to $30\,h^{-1}{\rm Mpc}$ assuming a flat $Λ$CDM cosmology. With various tests using mock catalogs described in Miyatake et al. (2021), we show that any bias in the clustering amplitude $S_8\equiv σ_8(Ω_{\rm m}/0.3)^{0.5}$ due to uncertainties in the galaxy-halo connection is less than $\sim50$\% of the statistical uncertainty of $S_8$, {\it unless} the assembly bias effect is unexpectedly large. Our best-fit models have $S_8=0.795^{+0.049}_{-0.042}$ (mode and 68\% credible interval) for the flat $Λ$CDM model; we find tighter constraints on the quantity $S_8(α=0.17)\equivσ_8(Ω_{\rm m}/0.3)^{0.17} =0.745^{+0.039}_{-0.031}$. (abriged)

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The LSST Dark Energy Science Collaboration (DESC) Science Requirements Document

The Large Synoptic Survey Telescope (LSST) Dark Energy Science Collaboration (DESC) will use five cosmological probes: galaxy clusters, large scale structure, supernovae, strong lensing, and weak lensing. This Science Requirements Document (SRD) quantifies the expected dark energy constraining power of these probes individually and together, with conservative assumptions about analysis methodology and follow-up observational resources based on our current understanding and the expected evolution within the field in the coming years. We then define requirements on analysis pipelines that will enable us to achieve our goal of carrying out a dark energy analysis consistent with the Dark Energy Task Force definition of a Stage IV dark energy experiment. This is achieved through a forecasting process that incorporates the flowdown to detailed requirements on multiple sources of systematic uncertainty. Future versions of this document will include evolution in our software capabilities and analysis plans along with updates to the LSST survey strategy.

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Optimization of the Observing Cadence for the Rubin Observatory Legacy Survey of Space and Time: a pioneering process of community-focused experimental design

Vera C. Rubin Observatory is a ground-based astronomical facility under construction, a joint project of the National Science Foundation and the U.S. Department of Energy, designed to conduct a multi-purpose 10-year optical survey of the southern hemisphere sky: the Legacy Survey of Space and Time. Significant flexibility in survey strategy remains within the constraints imposed by the core science goals of probing dark energy and dark matter, cataloging the Solar System, exploring the transient optical sky, and mapping the Milky Way. The survey's massive data throughput will be transformational for many other astrophysics domains and Rubin's data access policy sets the stage for a huge potential users' community. To ensure that the survey science potential is maximized while serving as broad a community as possible, Rubin Observatory has involved the scientific community at large in the process of setting and refining the details of the observing strategy. The motivation, history, and decision-making process of this strategy optimization are detailed in this paper, giving context to the science-driven proposals and recommendations for the survey strategy included in this Focus Issue.

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Impact of Image Persistence in the Roman Space Telescope High-Latitude Survey

The High Latitude Survey of the Nancy Grace Roman Space Telescope is expected to measure the positions and shapes of hundreds of millions of galaxies in an area of 2220 deg$^2$. This survey will provide high-quality weak lensing data with unprecedented systematics control. The Roman Space Telescope will survey the sky in near infrared (NIR) bands using Teledyne H4RG HgCdTe photodiode arrays. These NIR arrays exhibit an effect called persistence: charges that are trapped in the photodiodes during earlier exposures are gradually released into later exposures, leading to contamination of the images and potentially to errors in measured galaxy properties such as fluxes and shapes. In this work, we use image simulations that incorporate the persistence effect to study its impact on galaxy shape measurements and weak lensing signals. No significant spatial correlations are found between the galaxy shape changes induced by persistence. On the scales of interest for weak lensing cosmology, the effect of persistence on the weak lensing correlation function is about two orders of magnitude lower than the Roman Space Telescope additive shear error budget, indicating that the persistence effect is expected to be a subdominant contributor to the systematic error budget for weak lensing with the Roman Space Telescope given its current design.

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