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We discuss recently introduced numerical linked-cluster (NLC) algorithms that allow one to obtain temperature-dependent properties of quantum lattice models, in the thermodynamic limit, from exact diagonalization of finite clusters. We…

Statistical Mechanics · Physics 2007-06-25 Marcos Rigol , Tyler Bryant , Rajiv R. P. Singh

Many spin systems affected by critical slowing down can be efficiently simulated using cluster algorithms. Where such systems have long-range interactions, suitable formulations can additionally bring down the computational effort for each…

Statistical Mechanics · Physics 2017-04-07 Emilio Flores-Sola , Martin Weigel , Ralph Kenna , Bertrand Berche

Machine learning interatomic potentials are revolutionizing large-scale, accurate atomistic modelling in material science and chemistry. Many potentials use atomic cluster expansion or equivariant message passing frameworks. Such frameworks…

Computational Physics · Physics 2024-07-31 Bingqing Cheng

The quantum jump approach, where pairs of state vectors follow Stochastic Schroedinger Equation (SSE) in order to treat the exact quantum dynamics of two interacting systems, is first described. In this work the non-uniqueness of such…

Quantum Physics · Physics 2009-02-05 Denis Lacroix

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 work we propose a series-expansion thermal tensor network (SETTN) approach for efficient simulations of quantum lattice models. This continuous-time SETTN method is based on the numerically exact Taylor series expansion of…

Strongly Correlated Electrons · Physics 2017-04-12 Bin-Bin Chen , Yun-Jing Liu , Ziyu Chen , Wei Li

This paper proposes a new method for constructing multidimensional signal constellations (SC), referred to as SCOPT, for high-speed communication systems with enhanced energy efficiency (EE). In contrast to conventional approaches, the…

Information Theory · Computer Science 2026-04-02 Mark Bykhovskiy

Classical stochastic processes can be generated by quantum simulators instead of the more standard classical ones, such as hidden Markov models. One reason for using quantum simulators is that they generally require less memory than their…

Quantum Physics · Physics 2016-09-19 C. Aghamohammadi , J. R. Mahoney , J. P. Crutchfield

Linked cluster expansions provide a useful tool for both analytical and numerical investigations of lattice field theories. The expansion parameter(s) being the interaction strength(s) fields at neighboured lattice sites are coupled, they…

High Energy Physics - Lattice · Physics 2009-10-28 Thomas Reisz

The coupled cluster method (CCM) is a powerful and widely applied technique of modern-day quantum many-body theory. It has been used with great success in order to understand the properties of quantum magnets at zero temperature. This is…

Strongly Correlated Electrons · Physics 2009-09-11 D. J. J. Farnell

We consider the sampling of the coupled cluster expansion within stochastic coupled cluster theory. Observing the limitations of previous approaches due to the inherently non-linear behaviour of a coupled cluster wavefunction representation…

Chemical Physics · Physics 2018-08-14 Charles J. C. Scott , Alex J. W. Thom

We prove clustering estimates for the truncated correlations, i.e., cumulants of an unbounded spin system on the lattice. We provide a unified treatment, based on cluster expansion techniques, of four different regimes: large mass, small…

Mathematical Physics · Physics 2015-05-13 Abdelmalek Abdesselam , Aldo Procacci , Benedetto Scoppola

The linked-cluster expansion technique for the high-temperature expansion of spin model is reviewed. A new algorithm for the computation of three-point and higher Green's functions is presented. Series are computed for all components of…

Statistical Mechanics · Physics 2008-11-26 Massimo Campostrini

The many-body expansion (MBE) is an efficient tool which has a long history of use for calculating interaction energies, binding energies, lattice energies, and so on. In the past, applications of MBE to correlation energy have been…

Strongly Correlated Electrons · Physics 2021-08-11 Vibin Abraham , Nicholas Mayhall

The stochastic block model (SBM) is a flexible probabilistic tool that can be used to model interactions between clusters of nodes in a network. However, it does not account for interactions of time varying intensity between clusters. The…

Machine Learning · Statistics 2017-07-11 Marco Corneli , Pierre Latouche , Fabrice Rossi

An improved version of a recently developed stochastic cluster dynamics (SCD) method {[}Marian, J. and Bulatov, V. V., {\it J. Nucl. Mater.} \textbf{415} (2014) 84-95{]} is introduced as an alternative to rate theory (RT) methods for…

Data Structures and Algorithms · Computer Science 2016-05-04 Tuan L. Hoang , Jaime Marian , Vasily V. Bulatov , Peter Hosemann

We propose a generalization of the linked-cluster expansions to study driven-dissipative quantum lattice models, directly accessing the thermodynamic limit of the system. Our method leads to the evaluation of the desired extensive property…

Statistical Mechanics · Physics 2018-01-10 Alberto Biella , Jiasen Jin , Oscar Viyuela , Cristiano Ciuti , Rosario Fazio , Davide Rossini

We review efficient Monte Carlo methods for simulating quantum systems which couple to a dissipative environment. A brief introduction of the Caldeira-Leggett model and the Monte Carlo method will be followed by a detailed discussion of…

Statistical Mechanics · Physics 2009-11-11 Philipp Werner , Matthias Troyer

We introduce the stochastic Zassenhaus expansions (SZEs), a class of ancilla-free quantum algorithms for Hamiltonian simulation. These algorithms map nested Zassenhaus formulas onto quantum gates and then employ randomized sampling to…

Quantum Physics · Physics 2025-01-24 Joseph Peetz , Prineha Narang

Clustering is a fundamental task for analyzing unlabeled data based solely on its underlying distribution. Spectral clustering is a clustering method that represents a dataset as a graph and uses the relationships between data points.…

Quantum Physics · Physics 2025-04-01 Hyeong-Gyu Kim , Siheon Park , June-Koo Kevin Rhee