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Related papers: Extended Variational Cluster Approximation

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We show that short-range correlations have a dramatic impact on the steady-state phase diagram of quantum driven-dissipative systems. This effect, never observed in equilibrium, follows from the fact that ordering in the steady state is of…

Statistical Mechanics · Physics 2016-07-29 Jiasen Jin , Alberto Biella , Oscar Viyuela , Leonardo Mazza , Jonathan Keeling , Rosario Fazio , Davide Rossini

In this article, we study a class of lattice random variables in the domain of attraction of an $\alpha$-stable random variable with index $\alpha \in (0,2)$ which satisfy a truncated fractional Edgeworth expansion. Our results include…

Probability · Mathematics 2023-06-30 Leandro Chiarini , Milton Jara , Wioletta M. Ruszel

Variational and diffusion quantum Monte Carlo (VMC and DMC) methods with Slater-Jastrow-backflow trial wave functions are used to study the spin-polarized three-dimensional uniform electron fluid. We report ground state VMC and DMC energies…

Strongly Correlated Electrons · Physics 2025-11-11 Sam Azadi , N. D. Drummond , Sam. M. Vinko

We consider a new formulation of the stochastic coupled cluster method in terms of the similarity transformed Hamiltonian. We show that improvement in the granularity with which the wavefunction is represented results in a reduction in the…

Chemical Physics · Physics 2016-02-02 Ruth S. T. Franklin , James S. Spencer , Alberto Zoccante , Alex J. W. Thom

The Atomic Cluster Expansion (ACE) [R. Drautz, Phys. Rev. B, 99:014104 (2019)] provides a systematically improvable, universal descriptor for the environment of an atom that is invariant to permutation, translation and rotation. ACE is…

Computational Physics · Physics 2023-08-15 Christoph Ortner

The connections between the Random Phase Approximation (RPA) and Many-Body Perturbation Theory (MBPT) and its all order generalisation, the Coupled- Cluster Theory (CCT) have been explored. Explicit expressions have been derived for the…

A unitary coupled-cluster (UCC)-based self-consistent electron propagator theory (EPT) is proposed for the description of electron-detached and electron-attached states. Two practical schemes, termed IP/EA-UCC3 and IP/EA-qUCCSD, are…

Chemical Physics · Physics 2026-03-03 Yu Zhang , Junzi Liu

We explore different variants of the random phase approximation (RPA) to the correlation energy derived from closed-shell ring-diagram approximations to coupled cluster doubles theory. We implement these variants in range-separated…

Chemical Physics · Physics 2011-09-01 Julien Toulouse , Wuming Zhu , Andreas Savin , Georg Jansen , János G. Angyán

We consider the collective, long-wavelength charge excitations in correlated media in presence of short- and long-range forces. As an example for the case of a short-range interaction, we examine the two-dimensional Hubbard model within…

We present excitation energies for molecular doublets from a spin-adapted formulation of coupled cluster singles and doubles theory. The entanglement coupled cluster approach represents an unconventional take on the notorious problem of…

Chemical Physics · Physics 2025-04-08 Sarai Dery Folkestad , Kristine Lauvstad Kruken , Henrik Koch

New integrable variant of the one-dimensional Hubbard model with variable-range correlated hopping is studied. The Hamiltonian is constructed by applying the quantum inverse scattering method on the infinite interval at zero density to the…

Statistical Mechanics · Physics 2016-08-31 Shuichi Murakami

Exponential families are widely used in machine learning; they include many distributions in continuous and discrete domains (e.g., Gaussian, Dirichlet, Poisson, and categorical distributions via the softmax transformation). Distributions…

We present an unsupervised learning analysis of correlation hierarchies in the quarter-filled simple and extended Hubbard models by applying principal component analysis (PCA) to exact-diagonalization (ED) data on 3x4 and 4x4 cylindrical…

Strongly Correlated Electrons · Physics 2026-05-12 Md Fahad Equbal , S R Hassan , M. A. H. Ahsan

Diagrammatic expansions are a central tool for treating correlated electron systems. At thermal equilibrium, they are most naturally defined within the Matsubara formalism. However, extracting any dynamic response function from a Matsubara…

Strongly Correlated Electrons · Physics 2020-02-19 Jaksa Vucicevic , Michel Ferrero

The conditional extremes (CE) framework has proven useful for analysing the joint tail behaviour of random vectors. However, when applied across many locations or variables, it can be difficult to interpret or compare the resulting extremal…

Methodology · Statistics 2025-10-24 Patrick O'Toole , Christian Rohrbeck , Jordan Richards

We present a comprehensive numerical investigation of the cluster Truncated Wigner Approximation (cTWA) applied to quench dynamics in bond-disordered Heisenberg spin chains with power-law interactions. We find that cTWA yields highly…

Quantum Physics · Physics 2024-08-20 Adrian Braemer , Javad Vahedi , Martin Gärttner

We describe further details of the Stochastic Coupled Cluster method and a diagnostic of such calculations, the shoulder height, akin to the plateau found in Full Configuration Interaction Quantum Monte Carlo. We describe an initiator…

Chemical Physics · Physics 2016-03-23 James S. Spencer , Alex J. W. Thom

We investigate the properties of a two-orbital Hubbard model with unequal bandwidths on the square lattice in the framework of the dynamical cluster approximation (DCA) combined with a continuous-time quantum Monte Carlo (CT QMC) algorithm.…

Strongly Correlated Electrons · Physics 2010-01-25 Hunpyo Lee , Yu-Zhong Zhang , Harald O. Jeschke , Roser Valenti , Hartmut Monien

Optical responses in an excitonic insulating (EI) system with strong electron correlation are studied. We adopt the two-orbital Hubbard model with a finite energy difference between the two orbitals where the spin state degree of freedom…

Strongly Correlated Electrons · Physics 2020-03-25 Hengyue Li , Junya Otsuki , Makoto Naka , Sumio Ishihara

Variational autoencoders (VAEs) are popular likelihood-based generative models which can be efficiently trained by maximizing an Evidence Lower Bound (ELBO). There has been much progress in improving the expressiveness of the variational…

Machine Learning · Statistics 2023-08-29 Marcel Hirt , Vasileios Kreouzis , Petros Dellaportas
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