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Fault-tolerant quantum computation (FTQC) is expected to address a wide range of computational problems. To realize large-scale FTQC, it is essential to encode logical qubits using quantum error-correcting codes. High-rate concatenated…

Quantum Physics · Physics 2026-01-27 Takeshi Kakizaki

We study equal weight numerical integration, or Quasi Monte Carlo (QMC) rules, for functions in a Sobolev space $H^s(S^d)$ with smoothness parameter $s>d/2$ defined over the unit sphere $S^d$ in $R^{d+1}$. Focusing on $N$-point sets that…

Numerical Analysis · Mathematics 2015-12-24 Johann S. Brauchart , Edward B. Saff , Ian H. Sloan , Rob S. Womersley

The Cooperative Motion Algorithm is an efficient lattice method to simulate dense polymer systems and is often used with two different criteria to generate a Markov chain in the configuration space. While the first method is the…

Statistical Mechanics · Physics 2016-11-18 Piotr Knychala , Michal Banaszak

We present a new exact algorithm for estimating all elements of the quark propagator. The advantage of the method is that the exact all-to-all propagator is reproduced in a large but finite number of inversions. The efficacy of the…

High Energy Physics - Lattice · Physics 2007-05-23 Alan O Cais , K. Jimmy Juge , Mike J. Peardon , Sinead M. Ryan , Jon-Ivar Skullerud

We present the complete 1-loop perturbative computation of the renormalization constants and mixing coefficients of the operators that measure the first moment of deep inelastic scattering structure functions, employing the nearest neighbor…

High Energy Physics - Lattice · Physics 2009-10-22 Stefano Capitani , Giancarlo Rossi

This paper provides the theoretical foundation for the construction of lattice algorithms for multivariate $L_2$ approximation in the worst case setting, for functions in a periodic space with general weight parameters. Our construction…

Numerical Analysis · Mathematics 2026-03-04 Ronald Cools , Frances Y. Kuo , Dirk Nuyens , Ian H. Sloan

Reverse Monte Carlo (RMC) is an algorithm that incorporates stochastic modification of the action as part of the process that updates the fields in a Monte Carlo simulation. Such update moves have the potential of lowering or eliminating…

High Energy Physics - Lattice · Physics 2015-06-22 Arjun Singh Gambhir , Kostas Orginos

We discuss an algorithm for Tchakaloff-like compression of Quasi-MonteCarlo (QMC) volume/surface integration on union of balls (multibubbles). The key tools are Davis-Wilhelmsen theorem on the so-called Tchakaloff sets for positive linear…

Numerical Analysis · Mathematics 2023-03-03 Giacomo Elefante , Alvise Sommariva , Marco Vianello

The effect of different move sets on the folding kinetics of the Monte Carlo simulations is analysed based on the conformation-network and the temperature-dependent folding kinetics. A new scheme of implementing Metropolis algorithm is…

Soft Condensed Matter · Physics 2007-05-23 Yu-Pin Luo , Ming-Chang Huang , Yen-Liang Chou , Tsong-Ming Liaw

This article provides an overview of some interfaces between the theory of quasi-Monte Carlo (QMC) methods and applications. We summarize three QMC theoretical settings: first order QMC methods in the unit cube $[0,1]^s$ and in…

Numerical Analysis · Mathematics 2017-10-30 Frances Y. Kuo , Dirk Nuyens

The quantum Monte Carlo (QMC) is one of the most promising many-body electronic structure approaches. It employs stochastic techniques for solving the stationary Schr\" odinger equation and for evaluation of expectation values. The key…

Other Condensed Matter · Physics 2007-12-20 Michal Bajdich

In lattice field theory, the interactions of elementary particles can be computed via high-dimensional integrals. Markov-chain Monte Carlo (MCMC) methods based on importance sampling are normally efficient to solve most of these integrals.…

High Energy Physics - Lattice · Physics 2020-02-18 Tobias Hartung , Karl Jansen , Hernan Leövey , Julia Volmer

There is a class of statistical problems that arises in several contexts, the Lattice QCD problem of particle physics being one that has attracted the most attention. In essence, the problem boils down to the estimation of an infinite…

Methodology · Statistics 2012-01-06 Joshua Landon , Frank X. Lee , Nozer D. Singpurwalla

We analyze combined Quasi-Monte Carlo quadrature and Finite Element approximations in Bayesian estimation of solutions to countably-parametric operator equations with holomorphic dependence on the parameters as considered in [Cl.~Schillings…

Numerical Analysis · Mathematics 2016-02-25 Josef Dick , Robert N. Gantner , Quoc T. Le Gia , Christoph Schwab

The slow microstructural evolution of materials often plays a key role in determining material properties. When the unit steps of the evolution process are slow, direct simulation approaches such as molecular dynamics become prohibitive and…

In previous work (Kuo, Nuyens, Wilkes, 2023), we showed that a lattice rule with a pre-determined generating vector but random number of points can achieve the near optimal convergence of $O(n^{-\alpha-1/2+\epsilon})$, $\epsilon > 0$, for…

Numerical Analysis · Mathematics 2024-01-02 Dirk Nuyens , Laurence Wilkes

Large Momentum Effective Theory (LaMET) provides a general framework for computing the multi-dimensional partonic structure of the proton from first principles using lattice quantum chromodynamics (QCD). In this effective field theory…

High Energy Physics - Lattice · Physics 2026-03-04 Yong Zhao

Understanding the microscopic mechanism of coexisting long-range orders (such as lattice supersolidity) in strongly correlated systems is a subject of immense interest. We study the possible manifestations of long-range orders, including…

Strongly Correlated Electrons · Physics 2017-09-13 Amrita Ghosh , Sudhakar Yarlagadda

Higher order digital nets are special classes of point sets for quasi-Monte Carlo rules which achieve the optimal convergence rate for numerical integration of smooth functions. An explicit construction of higher order digital nets was…

Numerical Analysis · Mathematics 2019-12-09 Takashi Goda

The basic idea of fast Monte Carlo (MC) simulations is to perform particle-based MC simulations with the excluded-volume interactions modeled by "soft" repulsive potentials that allow particle overlapping. This gives much faster system…

Soft Condensed Matter · Physics 2012-01-24 Qiang Wang