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As an essential attribute of organic compounds, polarity has a profound influence on many molecular properties such as solubility and phase transition temperature. Thin layer chromatography (TLC) represents a commonly used technique for…

We describe a new method to compute general cubature formulae. The problem is initially transformed into the computation of truncated Hankel operators with flat extensions. We then analyse the algebraic properties associated to flat…

Algebraic Geometry · Mathematics 2015-06-10 Marta Abril Bucero , Chandrajit Bajaj , Bernard Mourrain

We consider a Canonical Polyadic (CP) decomposition approach to low-rank tensor completion (LRTC) by incorporating external pairwise similarity relations through graph Laplacian regularization on the CP factor matrices. The usage of graph…

Numerical Analysis · Mathematics 2023-11-14 Yu Guan , Shuyu Dong , Bin Gao , P. -A. Absil , François Glineur

Symplectic quantization is a functional approach to quantum field theory that allows sampling of quantum fluctuations directly in Minkowski space-time by means of a generalized microcanonical ensemble similar to the one of the standard…

High Energy Physics - Theory · Physics 2026-05-26 Martina Giachello , Francesco Scardino , Giacomo Gradenigo

Here we propose a novel searching scheme for a tuning parameter in high-dimensional penalized regression methods to address variable selection and modeling when sample sizes are limited compared to the data dimensions. Our method is…

Quantitative Methods · Quantitative Biology 2020-02-11 Tao Jiang , Stephanie J. London , Mi Kyeong Lee , Josyf C. Mychaleckyj , Alison A. Motsinger-Reif

In recent years, quaternion matrix completion (QMC) based on low-rank regularization has been gradually used in image de-noising and de-blurring.Unlike low-rank matrix completion (LRMC) which handles RGB images by recovering each color…

Image and Video Processing · Electrical Eng. & Systems 2021-01-08 Liqiao Yang , Kit Ian Kou , Jifei Miao

For high dimensional sparse linear regression problems, we propose a sequential convex relaxation algorithm (iSCRA-TL1) by solving inexactly a sequence of truncated $\ell_1$-norm regularized minimization problems, in which the working index…

Statistics Theory · Mathematics 2024-11-05 Shujun Bi , Yonghua Yang , Shaohua Pan

The unitary coupled cluster (UCC) approximation is one of the more promising wave-function ans\"atze for electronic structure calculations on quantum computers via the variational quantum eigensolver algorithm. However, for large systems…

Quantum Physics · Physics 2021-09-30 Jia Chen , Hai-Ping Cheng , James K. Freericks

In this paper, we consider the generalized low rank approximation of the correlation matrices problem which arises in the asset portfolio. We first characterize the feasible set by using the Gramian representation together with a special…

Numerical Analysis · Mathematics 2018-12-12 Xuefeng Duan , Jianchao Bai , Maojun Zhang , Xinjun Zhang

This paper presents an efficient parallel direct algorithm with near-optimal complexity for the compact fourth and sixth-order approximation of the three-dimensional Helmholtz equations [1] with the problem coefficient depending on only one…

Numerical Analysis · Mathematics 2020-03-13 Ronald Gonzales , Yury Gryazin , Yun Teck Lee

We propose herein an extension of truncated spectrum methodologies (TSMs), a non-perturbative numerical approach able to elucidate the low energy properties of quantum field theories. TSMs, in their various flavors, involve a division of a…

High Energy Physics - Theory · Physics 2023-08-02 Márton K. Lájer , Robert M. Konik

In this paper, we present a method for the Hamiltonian simulation in the context of eigenvalue estimation problems which improves earlier results dealing with Hamiltonian simulation through the truncated Taylor series. In particular, we…

Quantum Physics · Physics 2018-11-01 Ammar Daskin , Sabre Kais

Current spectral compressed sensing methods via Hankel matrix completion employ symmetric factorization to demonstrate the low-rank property of the Hankel matrix. However, previous non-convex gradient methods only utilize asymmetric…

Information Retrieval · Computer Science 2024-09-25 Jinsheng Li , Wei Cui , Xu Zhang

A highly anticipated use of quantum computers is the simulation of complex quantum systems including molecules and other many-body systems. One promising method involves directly applying a linear combination of unitaries (LCU) to…

Quantum Physics · Physics 2022-02-02 Richard Meister , Simon C. Benjamin , Earl T. Campbell

Temporal difference (TD) methods constitute a class of methods for learning predictions in multi-step prediction problems, parameterized by a recency factor lambda. Currently the most important application of these methods is to temporal…

Artificial Intelligence · Computer Science 2008-02-03 P. Cichosz

We are interested in the properties and relations of entanglement measures. Especially, we focus on the squashed entanglement and relative entropy of entanglement, as well as their analogues and variants. Our first result is a monogamy-like…

Quantum Physics · Physics 2014-02-19 Ke Li , Andreas Winter

In this article we solve four special cases of the truncated Hamburger moment problem (THMP) of degree $2k$ with one or two missing moments in the sequence. As corollaries we obtain, by using appropriate substitutions, the solutions to…

Functional Analysis · Mathematics 2022-05-17 Aljaž Zalar

The Theory of Functional Connections (TFC) is a general methodology for functional interpolation that can embed a set of user-specified linear constraints. The functionals derived from this method, called \emph{constrained expressions},…

Optimization and Control · Mathematics 2021-05-18 Hunter Johnston

We consider the problem of recovering the superposition of $R$ distinct complex exponential functions from compressed non-uniform time-domain samples. Total Variation (TV) minimization or atomic norm minimization was proposed in the…

Information Theory · Computer Science 2017-11-07 Weiyu Xu , Jirong Yi , Soura Dasgupta , Jian-Feng Cai , Mathews Jacob , Myung Cho

Eigenvector continuation is a computational method that finds the extremal eigenvalues and eigenvectors of a Hamiltonian matrix with one or more control parameters. It does this by projection onto a subspace of eigenvectors corresponding to…

Nuclear Theory · Physics 2021-01-22 Avik Sarkar , Dean Lee