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The polar decomposition of a matrix is a key element in the quantum linear algebra toolbox. We show that the problem of quantum polar decomposition, recently studied in Lloyd et al. [LBP+20], has a simple and concise implementation via the…

Quantum Physics · Physics 2021-06-15 Yihui Quek , Patrick Rebentrost

In this work we detail the application of a fast convolution algorithm computing high dimensional integrals to the context of multiplicative noise stochastic processes. The algorithm provides a numerical solution to the problem of…

Computational Finance · Quantitative Finance 2015-03-19 Giacomo Bormetti , Sofia Cazzaniga

We introduce a fast algorithm for computing volume potentials - that is, the convolution of a translation invariant, free-space Green's function with a compactly supported source distribution defined on a uniform grid. The algorithm relies…

Numerical Analysis · Mathematics 2016-08-24 Felipe Vico , Leslie Greengard , Miguel Ferrando

We introduce a highly-parallelizable architecture for estimating parameters of compact binary coalescence using gravitational-wave data and waveform models. Using a spherical harmonic mode decomposition, the waveform is expressed as a sum…

General Relativity and Quantum Cosmology · Physics 2015-08-06 C. Pankow , P. Brady , E. Ochsner , R. O'Shaughnessy

We present a fast and accurate formulation for computing the nonlinear matter power spectrum at one-loop order based on Unified Lagrangian Perturbation Theory (ULPT). ULPT decomposes the density field into the Jacobian deviation, capturing…

Cosmology and Nongalactic Astrophysics · Physics 2025-10-23 Naonori Sugiyama

In the previous paper [arXiv:2210.10435], the nonlinear perturbation theory of cosmological density field is generalized to include the tensor-valued bias of astronomical objects, such as spins and shapes of galaxies and any other tensors…

Cosmology and Nongalactic Astrophysics · Physics 2024-09-23 Takahiko Matsubara

Over the last two decades, several fast, robust, and high-order accurate methods have been developed for solving the Poisson equation in complicated geometry using potential theory. In this approach, rather than discretizing the partial…

Numerical Analysis · Mathematics 2024-09-19 Fredrik Fryklund , Leslie Greengard , Shidong Jiang , Samuel Potter

Standard cosmological perturbation theory (SPT) for the Large Scale Structure (LSS) of the Universe fails at small scales (UV) due to strong nonlinearities and to multistreaming effects. In Pietroni et al. 2011 a new framework was proposed…

Cosmology and Nongalactic Astrophysics · Physics 2015-06-22 Alessandro Manzotti , Marco Peloso , Massimo Pietroni , Matteo Viel , Francisco Villaescusa-Navarro

We present quantum algorithms for the estimation of n-time correlation functions, the local and non-local density of states, and dynamical linear response functions. These algorithms are all based on block-encodings - a versatile technique…

Quantum Physics · Physics 2020-08-19 Patrick Rall

Bayesian inference, while foundational to probabilistic reasoning, is often hampered by the computational intractability of posterior distributions, particularly through the challenging evidence integral. Conventional approaches like Markov…

Machine Learning · Computer Science 2025-11-11 Di Zhang

We present a formulation of cosmological perturbation theory where the Boltzmann hierarchies that evolve the neutrino phase-space distributions are replaced by integrals that can be evaluated easily with fast Fourier transforms. The…

Cosmology and Nongalactic Astrophysics · Physics 2022-12-14 Lingyuan Ji , Marc Kamionkowski , Jose Luis Bernal

Image subtraction in astronomy is a tool for transient object discovery such as asteroids, extra-solar planets and supernovae. To match point spread functions (PSFs) between images of the same field taken at different times a convolution…

Instrumentation and Methods for Astrophysics · Physics 2013-05-30 Steven Hartung , Hemant Shukla , J. Patrick Miller , Carlton Pennypacker

Calculating perturbation response properties of materials from first principles provides a vital link between theory and experiment, but is bottlenecked by the high computational cost. Here a general framework is proposed to perform density…

Computational Physics · Physics 2024-03-01 He Li , Zechen Tang , Jingheng Fu , Wen-Han Dong , Nianlong Zou , Xiaoxun Gong , Wenhui Duan , Yong Xu

Modified gravity models with scale-dependent linear growth typically exhibit an enhancement in the power spectrum beyond a certain scale. The conventional methods for extracting cosmological information usually involve inferring modified…

A new approach to cosmological perturbation theory has been recently introduced by Bartelmann et al., relying on nonequilibrium statistical theory of classical particles, and treating the gravitational interaction perturbatively. They…

Cosmology and Nongalactic Astrophysics · Physics 2015-05-20 Yacine Ali-Haïmoud

Nonuniform Fourier data are routinely collected in applications such as magnetic resonance imaging, synthetic aperture radar, and synthetic imaging in radio astronomy. To acquire a fast reconstruction that does not require an online inverse…

Numerical Analysis · Mathematics 2016-10-05 Anne Gelb , Guohui Song

We propose two easy-to-implement fast algorithms based on moment-matching to compute the nonlocal potential $\varphi(\textbf{x})=(U\ast \rho)(\textbf{x})$ on bounded domain, where the kernel $U$ is singular at the origin and the density…

Numerical Analysis · Mathematics 2026-02-16 Xin Liu , Qinglin Tang , Yong Zhang

The nonlinear Fourier transform (NFT) has recently gained significant attention in fiber optic communications and other engineering fields. Although several numerical algorithms for computing the NFT have been published, the design of…

Signal Processing · Electrical Eng. & Systems 2019-10-17 Shrinivas Chimmalgi , Peter J. Prins , Sander Wahls

Optical imaging systems are inherently limited in their resolution due to the point spread function (PSF), which applies a static, yet spatially-varying, convolution to the image. This degradation can be addressed via Convolutional Neural…

Computer Vision and Pattern Recognition · Computer Science 2024-01-10 Sunny Howard , Peter Norreys , Andreas Döpp

The nonlinear mass is a characteristic scale in halo formation that has wide-ranging applications across cosmology. Naively, computing it requires repeated numerical integration to calculate the variance of the power spectrum on different…

Cosmology and Nongalactic Astrophysics · Physics 2019-11-04 Alex Krolewski , Zachary Slepian