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The prediction of the effective elastic properties of polymer bonded explosives using direct numerical simulations is computationally expensive because of the high volume fraction of particles in these particulate composites ($\sim$0.90)…

Materials Science · Physics 2012-01-13 Biswajit Banerjee , Daniel O. Adams

We develop a quantum Monte Carlo method for many fermions that allows the use of any one-particle basis. It projects out the ground state by random walks in the space of Slater determinants. An approximate approach is formulated to control…

Condensed Matter · Physics 2009-02-20 Shiwei Zhang , Henry Krakauer

The optimized gradient method (OGM) provides a factor-$\sqrt{2}$ speedup upon Nesterov's celebrated accelerated gradient method in the convex (but non-strongly convex) setup. However, this improved acceleration mechanism has not been well…

Optimization and Control · Mathematics 2021-05-25 Chanwoo Park , Jisun Park , Ernest K. Ryu

We propose a novel optimal transport-based version of the Generalized Method of Moment (GMM). Instead of handling overidentification by reweighting the data to satisfy the moment conditions (as in Generalized Empirical Likelihood methods),…

Econometrics · Economics 2025-11-11 Susanne Schennach , Vincent Starck

A general quantum many-body theory in configuration space is developed by extending the traditional coupled cluter method (CCM) to a variational formalism. Two independent sets of distribution functions are introduced to evaluate the…

Strongly Correlated Electrons · Physics 2009-11-07 Y. Xian

A new method of deriving comparative statics information using generalized compensated derivatives is presented which yields constraint-free semidefiniteness results for any differentiable, constrained optimization problem. More generally,…

Optimization and Control · Mathematics 2013-10-29 M. Hossein Partovi , Michael R. Caputo

We propose and study kernel conjugate gradient methods (KCGM) with random projections for least-squares regression over a separable Hilbert space. Considering two types of random projections generated by randomized sketches and Nystr\"{o}m…

Machine Learning · Statistics 2022-07-18 Junhong Lin , Volkan Cevher

Multi-reference calculations along the lines of the Generator Coordinate Method or the restoration of broken symmetries within the nuclear Energy Density Functional (EDF) framework are becoming a standard tool in nuclear structure physics.…

Nuclear Theory · Physics 2011-08-17 D. Lacroix , T. Duguet , M. Bender

NOTE: this is a shortened version of the abstract of the paper. Multigrid methods for propagators in gauge fields are investigated. Gauge fields are incorporated in algorithms in a covariant way. This avoids the necessity for gauge fixing…

High Energy Physics - Lattice · Physics 2015-06-25 Thomas Kalkreuter

We propose a quantum-assisted solution for the maximum likelihood detection (MLD) of generalized spatial modulation (GSM) signals. Specifically, the MLD of GSM is first formulated as a novel polynomial optimization problem, followed by the…

Signal Processing · Electrical Eng. & Systems 2024-08-27 Kein Yukiyoshi , Taku Mikuriya , Hyeon Seok Rou , Giuseppe Thadeu Freitas de Abreu , Naoki Ishikawa

The Principle of Maximum Conformality (PMC) provides scale-fixed perturbative QCD predictions which are independent of the choice of the renormalization scheme, as well as the choice of the initial renormalization scale. In this article, we…

High Energy Physics - Phenomenology · Physics 2017-08-22 Alexandre Deur , Jian-Ming Shen , Xing-Gang Wu , Stanley J. Brodsky , Guy F. de Teramond

We develop an encompassing framework for matching, covariate balancing, and doubly-robust methods for causal inference from observational data called generalized optimal matching (GOM). The framework is given by generalizing a new…

Machine Learning · Statistics 2017-10-30 Nathan Kallus

Grammar-Guided Genetic Programming (GGGP) employs a variety of insights from evolutionary theory to autonomously design solutions for a given task. Recent insights from evolutionary biology can lead to further improvements in GGGP…

Neural and Evolutionary Computing · Computer Science 2023-07-13 Stefano Tiso , Pedro Carvalho , Nuno Lourenço , Penousal Machado

Generative Bayesian Computation (GBC) methods are developed for Casual Inference. Generative methods are simulation-based methods that use a large training dataset to represent posterior distributions as a map (a.k.a. optimal transport) to…

Methodology · Statistics 2024-12-25 Maria Nareklishvili , Nicholas Polson , Vadim Sokolov

Quantum tomography is a fundamental technique for characterizing, benchmarking, and verifying quantum states and devices. It plays a crucial role in advancing quantum technologies and deepening our understanding of quantum mechanics.…

While quantum machine learning (ML) has been proposed to be one of the most promising applications of quantum computing, how to build quantum ML models that outperform classical ML remains a major open question. Here, we demonstrate a…

Quantum Physics · Physics 2023-03-10 Elham Torabian , Roman V. Krems

Background: The isospin mixing is an interesting feature of atomic nuclei. It plays a crucial role in astrophysical nuclear reactions. However, it is not straightforward for variational nuclear structure models to describe it. Purpose: We…

Nuclear Theory · Physics 2022-02-02 M. Kimura , Y. Suzuki , T. Baba , Y. Taniguchi

In this letter, we demonstrate that previously proposed improved state parameterizations for soft and continuum robots are specific cases of Clarke coordinates. By explicitly deriving these improved parameterizations from a generalized…

Robotics · Computer Science 2025-03-18 Reinhard M. Grassmann , Jessica Burgner-Kahrs

The Particle Number Projected Generator Coordinate Method is formulated for the pairing Hamiltonian in a detailed way in the projection after variation and the variation after projection methods. The dependence of the wave functions on the…

Superconductivity · Physics 2009-11-11 M. A. Fernandez , J. L. Egido

In this paper, we study supersymmetry in quantum mechanics using the generalized uncertainty principle (GUP), or in other words, generalized supersymmetry in quantum mechanics. We construct supersymmetry in the generalized form of the…

Quantum Physics · Physics 2024-09-06 Meysam Hassandoust