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Multivariate quantum signal processing (M-QSP) has recently been shown to be applicable for non-Hermitian Hamiltonian simulation, opening several problems regarding the optimization landscape, angle-finding, and constant-factor analysis. We…

Quantum Physics · Physics 2026-05-14 Joshua M. Courtney

We introduce a general scheme of many-particle interferometry in which two identical sources are used and "which-way information" is eliminated by making the paths of one or more particles identical (path identity). The scheme allows us to…

Quantum Physics · Physics 2018-09-24 Mayukh Lahiri

Path integral Monte Carlo (PIMC) simulations have become an important tool for the investigation of the statistical mechanics of quantum systems. I discuss some of the history of applying the Monte Carlo method to non-relativistic quantum…

History and Philosophy of Physics · Physics 2016-11-23 Tilman Sauer

Nuclear state densities are important inputs to statistical models of compound-nucleus reactions. State densities are often calculated with self-consistent mean-field approximations that do not include important correlations and have to be…

Nuclear Theory · Physics 2021-06-16 P. Fanto , Y. Alhassid

We have reformulated the quantum Monte Carlo (QMC) technique so that a large part of the calculation scales linearly with the number of atoms. The reformulation is related to a recent alternative proposal for achieving linear-scaling QMC,…

Other Condensed Matter · Physics 2016-08-31 D. Alfe` , M. J. Gillan

Nuclear level densities are crucial for estimating statistical nuclear reaction rates. The shell model Monte Carlo method is a powerful approach for microscopic calculation of state densities in very large model spaces. However, these state…

Nuclear Theory · Physics 2013-04-29 Y. Alhassid , M. Bonett-Matiz , S. Liu , H. Nakada

We present a microscopic description of nuclei in an intermediate-mass region, including the proximity to the proton drip line, based on a no-core shell model with a schematic many-nucleon long-range interaction with no parameter…

Nuclear Theory · Physics 2015-06-17 G. K. Tobin , M. C. Ferriss , K. D. Launey , T. Dytrych , J. P. Draayer , A. C. Dreyfuss , C. Bahri

We investigate the role of external constraints in quantum field theory using the path integral formalism. We begin by reviewing the quantization of constrained systems and extend the analysis to cases where constraints are added to the…

High Energy Physics - Theory · Physics 2025-04-14 Amin Akhavan

Quantum Monte Carlo (QMC) methods offer exact solutions for quantum many-body systems but face severe limitations in fermionic systems like atomic nuclei due to the sign problem. While sign-problem-free QMC algorithms exist and provide…

Nuclear Theory · Physics 2026-01-06 Zhong-Wang Niu , Bing-Nan Lu

Using the framework of the Covariant Spectator Theory (CST) [1] we are developing a covariant model formulated in Minkowski space to study mesonic structure and spectra. Treating mesons as effective $q\bar{q}$ states, we focused in [2] on…

High Energy Physics - Phenomenology · Physics 2014-11-18 S. Leitão , A. Stadler , M. T. Peña , E. P. Biernat

We propose using the wave function generated by the quantum selected configuration interaction (QSCI) method as the trial wave function in phaseless auxiliary-field quantum Monte Carlo (ph-AFQMC). In the QSCI framework, electronic…

We use quantum Monte Carlo methods in the framework of the interacting nuclear shell model to calculate the statistical properties of nuclei at finite temperature and/or excitation energies. With this approach we can carry out realistic…

Nuclear Theory · Physics 2009-11-11 Y. Alhassid

We present an exploratory study of chiral effective theories of nuclei with methods adopted from lattice quantum chromodynamics (QCD). We show that the simulations in the Euclidean path integral approach are feasible and that we can…

Nuclear Theory · Physics 2015-03-19 Istvan Montvay , Carsten Urbach

It has become increasingly feasible to use quantum Monte Carlo (QMC) methods to study correlated fermion systems for realistic Hamiltonians. We give a summary of these techniques targeted at researchers in the field of correlated electrons,…

Strongly Correlated Electrons · Physics 2016-08-24 Lucas K. Wagner , David M. Ceperley

A one-dimensional harmonic oscillator in a box is used to introduce the oblique-basis concept. The method is extended to the nuclear shell model by combining traditional spherical states, which yield a diagonal representation of the usual…

Nuclear Theory · Physics 2009-11-07 V. G. Gueorguiev , J. P. Draayer

We propose an efficient numerical method, which combines the advantages of recently developed tensor-network based methods and standard trial wave functions, to study the ground state properties of quantum many-body systems. In this…

Strongly Correlated Electrons · Physics 2015-05-22 Olga Sikora , Hsueh-Wen Chang , Chung-Pin Chou , Frank Pollmann , Ying-Jer Kao

Interacting spin systems are of fundamental relevance in different areas of physics, as well as in quantum information science, and biology. These spin models represent the simplest, yet not fully understood, manifestation of quantum…

Quantum Physics · Physics 2015-02-27 Johannes Schachenmayer , Alexander Pikovski , Ana Maria Rey

The discrete time path integral Monte Carlo (PIMC) with a one-particle density matrix approximation is applied to study the quantum phase transition in the coupled double-well chain. To improve the convergence properties, the exact action…

Statistical Mechanics · Physics 2015-06-25 Dong-Hee Kim , Yu-Cheng Lin , Heiko Rieger

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

This paper addresses the problem of filtering with a state-space model. Standard approaches for filtering assume that a probabilistic model for observations (i.e. the observation model) is given explicitly or at least parametrically. We…

Machine Learning · Statistics 2015-10-23 Motonobu Kanagawa , Yu Nishiyama , Arthur Gretton , Kenji Fukumizu