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The feasibility of shell-model calculations is radically extended by the Quantum Monte Carlo Diagonalization method with various essential improvements. The major improvements are made in the sampling for the generation of shell-model basis…

Nuclear Theory · Physics 2008-11-26 Michio Honma , Takahiro Mizusaki , Takaharu Otsuka

Monte-Carlo simulations are routinely used for estimating the scaling exponents of complex systems. However, due to finite-size effects, determining the exponent values is often difficult and not reliable. Here we present a novel technique…

Computational Physics · Physics 2013-03-05 Indrek Mandre , Jaan Kalda

We consider the problem of estimating the expected outcomes of Monte Carlo processes whose outputs are described by multidimensional random variables. We tightly characterize the quantum query complexity of this problem for various choices…

Quantum Physics · Physics 2021-07-09 Arjan Cornelissen , Sofiene Jerbi

Quantum Monte Carlo (QMC) techniques are widely used in a variety of scientific problems and much work has been dedicated to developing optimized algorithms that can accelerate QMC on standard processors (CPU). With the advent of various…

Quantum Physics · Physics 2023-04-28 Shuvro Chowdhury , Kerem Y. Camsari , Supriyo Datta

Non-global QCD observables are characterised by a sensitivity to the full angular distribution of soft radiation emitted coherently in hard scattering processes. This complexity poses a challenge to their all-order resummation, that was…

High Energy Physics - Phenomenology · Physics 2022-04-13 Andrea Banfi , Frédéric A. Dreyer , Pier Francesco Monni

In this paper we investigate the optimal partition approach for multiparametric conic linear optimization (mpCLO) problems in which the objective function depends linearly on vectors. We first establish more useful properties of the…

Optimization and Control · Mathematics 2022-09-29 Zizong Yan , Xiangjun Li , Jinhai Guo

Sampling minimum energy grain boundary (GB) structures in the five-dimensional crystallographic phase space can provide much-needed insight into how GB crystallography affects various interfacial properties. However, the complexity and…

Materials Science · Physics 2018-09-10 Arash Dehghan Banadaki , Mark A. Tschopp , Srikanth Patala

The past years have witnessed impressive advances in electronic structure calculation, especially in the complexity and size of the systems studied, as well as in computation time. Linear scaling methods based on empirical tight-binding…

Materials Science · Physics 2007-05-23 Abduxukur Abdurixit , Alexis Baratoff , Giulia Galli

Every numerical general relativistic investigation starts from the solution of the initial value equations at a given time. Astrophysically relevant initial values for different systems lead to distinct set of equations that obey specific…

General Relativity and Quantum Cosmology · Physics 2024-05-24 Lambros Boukas , Antonios Tsokaros , Koji Uryu

We calculated the total energy of a semiconductor quantum dot which is defined by the trench gate method. In our calculation we used a recently developed energy functional called ``orbital-free energy functional". We compared the total…

Mesoscale and Nanoscale Physics · Physics 2010-08-30 G. Bilgeç Akyüz , K. Akgüngör , S. Şakiroglu , A. Siddiki , İ. Sökmen

We measure electron localization in different materials by means of a ``localization tensor'', based on Berry phases and related quantities. We analyze its properties, and we actually compute such tensor from first principles for several…

Materials Science · Physics 2009-11-07 Claudia Sgiarovello , Maria Peressi , Raffaele Resta

Sequential Monte Carlo techniques are useful for state estimation in non-linear, non-Gaussian dynamic models. These methods allow us to approximate the joint posterior distribution using sequential importance sampling. In this framework,…

Computation · Statistics 2012-07-09 Mike Klaas , Nando de Freitas , Arnaud Doucet

Monte Carlo methods are widely used to estimate observables in many-body quantum systems. However, conventional sampling schemes often require a large number of samples to achieve sufficient accuracy. In this work we propose the…

Quantum Physics · Physics 2026-01-29 Wenxuan Zhang , Dingzu Wang , Dario Poletti

Quantum Monte Carlo (QMC) methods such as Variational Monte Carlo, Diffusion Monte Carlo or Path Integral Monte Carlo are the most accurate and general methods for computing total electronic energies. We will review methods we have…

Computational Physics · Physics 2007-05-23 David Ceperley , Mark Dewing , Carlo Pierleoni

We develop generalization of the fixed-phase diffusion Monte Carlo method for Hamiltonians which explicitly depend on particle spins such as for spin-orbit interactions. The method is formulated in zero variance manner and is similar to…

Strongly Correlated Electrons · Physics 2016-04-13 Cody A. Melton , Minyi Zhu , Shi Guo , Alberto Ambrosetti , Francesco Pederiva , Lubos Mitas

Orthogonal geometric constructions are the basis of many many quantum error-correcting codes (QEC), but strict orthogonality constraints limit design flexibility and resource efficiency. We introduce a quasi-orthogonal geometric framework…

H\"uckel molecular orbital (HMO) theory provides a semi-empirical treatment of the electronic structure in conjugated {\pi}-electronic systems. A scalable system-agnostic execution of HMO theory on a quantum computer is reported here based…

Quantum Physics · Physics 2024-05-22 Harshdeep Singh , Sonjoy Majumder , Sabyashachi Mishra

Optimizing a target function over the space of organic molecules is an important problem appearing in many fields of applied science, but also a very difficult one due to the vast number of possible molecular systems. We propose an…

Most of the novel energy materials contain multiple elements occupying a single site in their lattice. The exceedingly large configurational space of these materials imposes challenges in determining their ground-state structures. Coulomb…

Materials Science · Physics 2025-07-04 Konstantin Köster , Tobias Binninger , Payam Kaghazchi
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