Rachel Mandelbaum

Professor Carnegie Mellon University

  • Pittsburgh PA

Rachel Mandelbaum's research interests are predominantly in the areas of observational cosmology and galaxy studies.

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Biography

Rachel Mandelbaum's research interests are predominantly in the areas of observational cosmology and galaxy studies. This work includes the use of weak gravitational lensing and other analysis techniques, with projects that range from development of improved data analysis methods, to actual application of such methods to existing data. She has developed algorithms that are used by leading astronomical surveys, including the Hyper Suprime-Cam Survey and the upcoming Legacy Survey of Space and Time (LSST), Euclid and Roman Space Telescope projects and their associated scientific collaborations. She currently serves as CMU's PI for the LINCC Frameworks initiative, developing open-source software to enable the LSST science community's robust, scalable analyses of astronomical imaging data. She served as the spokesperson for the LSST’s Dark Energy Science Collaboration (DESC) from 2019-2021, and previously served as the DESC analysis coordinator and co-leader of the weak lensing working group.

Areas of Expertise

Galaxy Studies
Observational Cosmology
Astronomical Surveys
Space

Media Appearances

CMU now offers track in quantum physics, thanks to advocacy from a student

Pittsburgh Post-Gazette  online

2024-12-27

These tracks allow students to complete their general degree while gaining additional expertise in an area they’re interested in, said Rachel Mandelbaum, CMU professor and interim head of the physics department.

“It’s a way of providing additional educational opportunities to students with particular interests,” Ms. Mandelbaum said.

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CMU hosts first-ever Physics Slam

The Tartan  online

2022-02-21

Then, Professor Rachel Mandelbaum introduced the audience to weak gravitational lensing, a measurement using data gained from large sky surveys. Weak gravitational lensing can be used to measure masses, specifically of dark matter in the universe. Her lab uses data from the Sloan Digital Sky Survey (SDSS) and the Hyper-SuprimeCam (HSC), which capture detailed images of the galaxy. Professor Mandelbaum’s research asks questions like, “How is dark matter distributed in the universe?” and “What are the main components of the universe?”

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Jewish cosmologist is a star at CMU

The Pittsburgh Jewish Chronicle  online

2020-08-12

Rachel Mandelbaum has always asked why. “From when I was a pretty young child, I was interested in learning how stuff worked,” she said.

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Social

Industry Expertise

Aerospace

Accomplishments

DOE Early Career Award

2012

Kusaka Memorial Prize, Princeton University

2000

Hubble Fellow

2006

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Education

Princeton University

A.B.

Physics

2000

Princeton University

Ph.D.

Physics

2006

Event Appearances

Invited Talk,“New Frontier sin Cosmology with the Intrinsic Alignments of Galaxies”

(2022)  Kyoto (participated remotely)

Invited Talk on LINCC Frameworks

(2022) LSST Solar System Readiness Sprint  Virtual

Invited Review

(2022) EchoIA Kickoff Workshop  Virtual

Articles

A Joint Roman Space Telescope and Rubin Observatory synthetic wide-field imaging survey

Monthly Notices of the Royal Astronomical Society

2023

We present and validate 20 deg2 of overlapping synthetic imaging surveys representing the full depth of the Nancy Grace Roman Space Telescope High-Latitude Imaging Survey (HLIS) and five years of observations of the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST). The two synthetic surveys are summarized, with reference to the existing 300 deg2 of LSST simulated imaging produced as part of Dark Energy Science Collaboration (DESC) Data Challenge 2 (DC2). Both synthetic surveys observe the same simulated DESC DC2 universe. For the synthetic Roman survey, we simulate for the first time fully chromatic images along with the detailed physics of the Sensor Chip Assemblies derived from lab measurements using the flight detectors. The simulated imaging and resulting pixel-level measurements of photometric properties of objects span a wavelength range of ∼0.3 to 2.0 μm. We also describe updates to the Roman simulation pipeline, changes in how astrophysical objects are simulated relative to the original DC2 simulations, and the resulting simulated Roman data products. We use these simulations to explore the relative fraction of unrecognized blends in LSST images, finding that 20-30 per cent of objects identified in LSST images with i-band magnitudes brighter than 25 can be identified as multiple objects in Roman images. These simulations provide a unique testing ground for the development and validation of joint pixel-level analysis techniques of ground- and space-based imaging data sets in the second half of the 2020s – in particular the case of joint Roman–LSST analyses.

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Analytical weak-lensing shear responses of galaxy properties and galaxy detection

Monthly Notices of the Royal Astronomical Society

2023

Shear estimation bias from galaxy detection and blending identification is now recognized as an issue for ongoing and future weak-lensing surveys. Currently, the empirical approach to correcting for this bias involves numerically shearing every observed galaxy and rerunning the detection and selection process. In this work, we provide an analytical correction for this bias that is accurate to subpercent level and far simpler to use. With the interpretation that smoothed image pixel values and galaxy properties are projections of the image signal onto a set of basis functions, we analytically derive the linear shear responses of both the pixel values and the galaxy properties (i.e., magnitude, size and shape) using the shear responses of the basis functions. With these derived shear responses, we correct for biases from shear-dependent galaxy detection and galaxy sample selection. With the analytical covariance matrix of measurement errors caused by image noise on pixel values and galaxy properties, we correct for the noise biases in galaxy shape measurement and the detection/selection process to the second-order in noise. The code used for this paper can carry out the detection, selection, and shear measurement for ∼1000 galaxies per CPU second. The algorithm is tested with realistic image simulations, and we find, after the analytical correction (without relying on external image calibration) for the detection/selection bias of about $-4~{{\%}}$, the multiplicative shear bias is $-0.12 \pm 0.10~{{\%}}$ for isolated galaxies; and about $-0.3 \pm 0.1~{{\%}}$ for blended galaxies with Hyper Suprime-Cam observational condition.

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Weak lensing tomographic redshift distribution inference for the Hyper Suprime-Cam Subaru Strategic Program three-year shape catalogue

Monthly Notices of the Royal Astronomical Society

2023

We present posterior sample redshift distributions for the Hyper Suprime-Cam Subaru Strategic Program Weak Lensing three-year (HSC Y3) analysis. Using the galaxies’ photometry and spatial cross-correlations, we conduct a combined Bayesian Hierarchical Inference of the sample redshift distributions. The spatial cross-correlations are derived using a subsample of Luminous Red Galaxies (LRGs) with accurate redshift information available up to a photometric redshift of z < 1.2. We derive the photometry-based constraints using a combination of two empirical techniques calibrated on spectroscopic- and multiband photometric data that covers a spatial subset of the shear catalog. The limited spatial coverage induces a cosmic variance error budget that we include in the inference. Our cross-correlation analysis models the photometric redshift error of the LRGs to correct for systematic biases and statistical uncertainties. We demonstrate consistency between the sample redshift distributions derived using the spatial cross-correlations, the photometry, and the posterior of the combined analysis. Based on this assessment, we recommend conservative priors for sample redshift distributions of tomographic bins used in the three-year cosmological Weak Lensing analyses.

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