A5101916965- Galaxies: Formation, Evolution, Phenomena
- Astronomy and Astrophysical Research
- Gaussian Processes and Bayesian Inference
- Cosmology and Gravitation Theories
- Radio Astronomy Observations and Technology
- Computational Physics and Python Applications
- Scientific Research and Discoveries
- Markov Chains and Monte Carlo Methods
- Statistical Methods and Inference
- Gamma-ray bursts and supernovae
- Simulation Techniques and Applications
- Error Correcting Code Techniques
- Blind Source Separation Techniques
- Pulsars and Gravitational Waves Research
- Data Visualization and Analytics
- Advanced Clustering Algorithms Research
- Data Management and Algorithms
- Remote Sensing in Agriculture
- Data Analysis with R
- Model Reduction and Neural Networks
- Astrophysics and Cosmic Phenomena
- Forecasting Techniques and Applications
- Bayesian Methods and Mixture Models
- Climate variability and models
- Traffic Prediction and Management Techniques
Flatiron Health (United States)
2021-2024
Flatiron Institute
2021-2024
Mathematics Research Center
2023
Simons Foundation
2022
University of California, Berkeley
2015-2021
Lawrence Berkeley National Laboratory
2020
Indian Institute of Technology Bombay
2015
We investigate the anisotropic clustering of Baryon Oscillation Spectroscopic Survey (BOSS) Data Release 12 (DR12) sample, which consists $1\,198\,006$ galaxies in redshift range $0.2 < z 0.75$ and a sky coverage $10\,252\,$deg$^2$. analyse this dataset Fourier space, using power spectrum multipoles to measure Redshift-Space Distortions (RSD) simultaneously with Alcock-Paczynski (AP) effect Acoustic (BAO) scale. include monopole, quadrupole hexadecapole our analysis compare measurements...
We present nbodykit, an open-source, massively parallel Python toolkit for analyzing large-scale structure (LSS) data. Using bindings of the Message Passing Interface (MPI), we provide implementations many commonly used algorithms in LSS. nbodykit is both interactive and scalable piece scientific software, performing well a supercomputing environment while still taking advantage tools provided by ecosystem. Existing functionality includes estimators power spectrum, 2 3-point correlation...
We analyse the baryon acoustic oscillation (BAO) signal of final Baryon Oscillation Spectroscopic Survey (BOSS) data release (DR12). Our analysis is performed in Fourier space, using power spectrum monopole and quadrupole. The set includes 1198 006 galaxies over redshift range 0.2 < z 0.75. divide this into three (overlapping) bins with effective redshifts zeff = 0.38, 0.51 0.61. demonstrate reliability our pipeline N-body simulations as well ∼1000 MultiDark-Patchy mock catalogues that mimic...
One of the main unsolved problems cosmology is how to maximize extraction information from nonlinear data. If data are usual approach employ a sequence statistics (N-point statistics, counting clusters, density peaks or voids etc.), along with corresponding covariance matrices. However, this computationally prohibitive and has not been shown be exhaustive in terms content. Here we instead develop hierarchical Bayesian approach, expanding likelihood around maximum posterior linear modes,...
Estimating rates of COVID-19 infection and associated mortality is challenging due to uncertainties in case ascertainment. We perform a counterfactual time series analysis on overall data from towns Italy, comparing the population 2020 with previous years, estimate COVID-19. find that number deaths Italy until September 9 was 59,000-62,000, compared official 36,000. The proportion died 0.29% most affected region, Lombardia, 0.57% province, Bergamo. Combining reported test positive estimates...
ABSTRACT We perform a counterfactual time series analysis on 2020 mortality data from towns in Italy using the previous five years as control. find an excess that is correlated with official COVID-19 death rate, but exceeds it by factor of at least 1.5. Our suggests there large population predominantly older people are missing fatality statistics. estimate number cOvID-19 deaths 49,000-53,000 May 9 2020, compared to 33,000. The Population Fatality Rate (PFR) has reached 0.26% most affected...
Abstract Simulation-Based Inference of Galaxies ( SimBIG ) is a forward modeling framework for analyzing galaxy clustering using simulation-based inference. In this work, we present the model, which designed to match observed SDSS-III BOSS CMASS sample. The model based on high-resolution Quijote N -body simulations and flexible halo occupation model. It includes full survey realism models observational systematics such as angular masking fiber collisions. We “mock challenge” validating...
Abstract Rapid advances in deep learning have brought not only a myriad of powerful neural networks, but also breakthroughs that benefit established scientific research. In particular, automatic differentiation (AD) tools and computational accelerators like GPUs facilitated forward modeling the Universe with differentiable simulations. Based on analytic or backpropagation, current cosmological simulations are limited by memory, thus subject to trade-off between time space/mass resolution,...
We present the cosmological constraints from analyzing higher-order galaxy clustering on small nonlinear scales. use SimBIG, a forward modeling framework for analyses that employs simulation-based inference to perform highly efficient using normalizing flows. It leverages predictive power of high-fidelity simulations and robustly extracts information regimes inaccessible with current standard analyses. In this work, we apply SimBIG subset BOSS sample analyze redshift-space bispectrum...
The non-Gaussian spatial distribution of galaxies traces the large-scale structure Universe and therefore constitutes a prime observable to constrain cosmological parameters. We conduct Bayesian inference <a:math xmlns:a="http://www.w3.org/1998/Math/MathML" display="inline"><a:mi mathvariant="normal">Λ</a:mi><a:mi>CDM</a:mi></a:math> parameters <d:math xmlns:d="http://www.w3.org/1998/Math/MathML" display="inline"><d:msub><d:mi mathvariant="normal">Ω</d:mi><d:mi>m</d:mi></d:msub></d:math>,...
Extracting the non-Gaussian information of cosmic large-scale structure (LSS) is vital in unlocking full potential rich datasets from upcoming stage-IV galaxy surveys. Galaxy skew spectra serve as efficient beyond-two-point statistics, encapsulating essential bispectrum with computational efficiency akin to power spectrum analysis. This paper presents first cosmological constraints analyzing set redshift-space data SDSS-III BOSS, accessing down nonlinear scales. Employing forward modeling...
We present a method to reconstruct the initial conditions of universe using observed galaxy positions and luminosities under assumption that can be calibrated with weak lensing give mean halo mass. Our relies on following gradients forward model since standard way identify halos is non-differentiable results in discrete sample objects, we propose framework position mass field starting from non-linear matter Neural Networks. evaluate performance our multiple metrics. more than $95\%$...
Upcoming 21-cm intensity surveys will use the hyperfine transition in emission to map out neutral hydrogen large volumes of universe. Unfortunately, spatial scales are completely contaminated with spectrally smooth astrophysical foregrounds which orders magnitude brighter than signal. This contamination also leaks into smaller radial and angular modes form a foreground wedge, further limiting usefulness observations for different science cases, especially cross-correlations tracers that have...
We investigate the range of applicability a model for real-space power spectrum based on N-body dynamics and (quadratic) Lagrangian bias expansion. This combination uses highly accurate particle displacements that can be efficiently achieved by modern methods with symmetries-based expansion which describes clustering any tracer large scales. show at low redshifts, moderately biased tracers, substitution N-body-determined improves over an equivalent using perturbation theory more than factor...
We present cosmological constraints from a simulation-based inference (SBI) analysis of galaxy clustering the S im BIG forward modeling framework. leverages predictive power high-fidelity simulations and provides an framework that can extract information on small nonlinear scales. In this work, we apply to Baryon Oscillation Spectroscopic Survey (BOSS) CMASS sample analyze spectrum, <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline" overflow="scroll"> <mml:mrow>...
Abstract Neutron stars provide a unique opportunity to study strongly interacting matter under extreme density conditions. The intricacies of inside neutron and their equation state are not directly visible, but determine bulk properties, such as mass radius, which affect the star's thermal X-ray emissions. However, telescope spectra these emissions also affected by stellar distance, hydrogen column, effective surface temperature, always well-constrained. Uncertainties on nuisance parameters...
ABSTRACT Dark matter halo demographics and assembly histories are a manifestation of cosmological structure formation have profound implications for the evolution galaxies. In particular, merger trees provide fundamental input several modelling techniques, such as semi-analytic models (SAMs), sub-halo abundance matching (SHAM), decorated occupation distribution models. Motivated by new ultra-high-redshift (z ≳ 10) frontier enabled JWST, we present suite Gadget at Ultrahigh Redshift with...
We present several methods to accurately estimate Lagrangian bias parameters and substantiate them using simulations. In particular, we focus on the quadratic terms, both local non ones, show first clear evidence for latter in Using Fourier space correlations, also time, scale dependence of non-local coefficients. For linear bias, fit demonstrate validity a consistency relation between parameters. Furthermore employ real estimators, cross-correlations Peak-Background Split argument. This is...
A new generation of surveys will soon map large fractions sky to ever greater depths and their science goals can be enhanced by exploiting cross correlations between them. In this paper we study the lensing CMB biased tracers large-scale structure at high z. We motivate need for more sophisticated bias models modeling increasingly these redshifts propose use perturbation theories, specifically Convolution Lagrangian Effective Field Theory (CLEFT). Since such signals reside scales redshifts,...
ABSTRACT Simulation-based inference (SBI) is a promising approach to leverage high-fidelity cosmological simulations and extract information from the non-Gaussian, non-linear scales that cannot be modelled analytically. However, scaling SBI next generation of surveys faces computational challenge requiring large number accurate over wide range cosmologies, while simultaneously encompassing volumes at high resolution. This can potentially mitigated by balancing accuracy cost for different...
ABSTRACT Dark Energy Spectroscopic Instrument (DESI) will construct a large and precise three-dimensional map of our Universe. The survey effective volume reaches $\sim 20\, h^{-3}\, \mathrm{Gpc}^{3}$. It is great challenge to prepare high-resolution simulations with much larger for validating the DESI analysis pipelines. AbacusSummit suite dark-matter-only designed this purpose, $200\, \mathrm{Gpc}^{3}$ (10 times volume) base cosmology. However, further efforts need be done provide more...
Reconstructing the initial conditions of Universe from late-time observations has potential to optimally extract cosmological information. Due high dimensionality parameter space, a differentiable forward model is needed for convergence, and recent advances have made it possible perform reconstruction with nonlinear models based on galaxy (or halo) positions. In addition positions, future surveys will provide measurements galaxies' peculiar velocities through kinematic Sunyaev-Zel'dovich...
We present the first $\Lambda$CDM cosmological analysis performed on a galaxy survey using marked power spectra. The spectrum is two-point function of field, where galaxies are weighted by that depends their local density. presence mark leads these statistics to contain higher-order information original making them good candidate exploit non-Gaussian catalog. In this work we make use \simbig, forward modeling framework for clustering analyses, and perform simulation-based inference...