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In this work, we report on a detailed simulation of the Bullet Cluster (1E0657-56) merger, including magnetohydrodynamics, plasma cooling, and adaptive mesh refinement. We constrain the simulation with data from gravitational lensing…

Cosmology and Nongalactic Astrophysics · Physics 2014-05-21 Craig Lage , Glennys Farrar

Lieb-Robinson bounds are powerful analytical tools for constraining the dynamic and static properties of non-relativistic quantum systems. Recently, a complete picture for closed systems that evolve unitarily in time has been achieved. In…

Quantum Physics · Physics 2021-11-01 Andrew Y. Guo , Simon Lieu , Minh C. Tran , Alexey V. Gorshkov

We introduce a range-separation approximation to coupled cluster doubles (CCD) theory that successfully overcomes limitations of regular CCD when applied to the uniform electron gas. We combine the short-range ladder channel with the…

Chemical Physics · Physics 2014-05-07 James J. Shepherd , Thomas M. Henderson , Gustavo E. Scuseria

Long-range interacting many-body systems exhibit a number of peculiar and intriguing properties. One of those is the scaling of relaxation times with the number $N$ of particles in a system. In this paper I give a survey of results on…

Statistical Mechanics · Physics 2017-02-14 Michael Kastner

It is shown that random quantum spin systems with centered disorder satisfy correlation inequalities previously proved (arXiv:cond-mat/0612371) in the classical case. Consequences include monotone approach of pressure and ground state…

Statistical Mechanics · Physics 2015-05-13 Pierluigi Contucci , Joel L. Lebowitz

Numerical linked-cluster expansions allow one to calculate finite-temperature properties of quantum lattice models directly in the thermodynamic limit through exact solutions of small clusters. However, full diagonalization is often the…

Strongly Correlated Electrons · Physics 2019-07-17 Krishnakumar Bhattaram , Ehsan Khatami

A numerically implementable Multi-scale Many-Body approach to strongly correlated electron systems is introduced. An extension to quantum cluster methods, it approximates correlations on any given length-scale commensurate with the strength…

Strongly Correlated Electrons · Physics 2012-01-04 C. Slezak , M. Jarrell , Th. Maier , J. Deisz

We provide a complete asymptotic distribution theory for clustered data with a large number of independent groups, generalizing the classic laws of large numbers, uniform laws, central limit theory, and clustered covariance matrix…

Econometrics · Economics 2026-02-03 Bruce E. Hansen , Seojeong Lee

Linked cluster expansions provide a useful tool both for analytical and numerical investigations of lattice field theories. The expansion parameter is the interaction strength fields at neighboured lattice sites are coupled. They result…

High Energy Physics - Lattice · Physics 2009-10-28 T. Reisz

In the context of clustering, we consider a generative model in a Euclidean ambient space with clusters of different shapes, dimensions, sizes and densities. In an asymptotic setting where the number of points becomes large, we obtain…

Machine Learning · Statistics 2009-09-15 Ery Arias-Castro

Quantum periodic cluster methods for strongly correlated electron systems are reformulated and developed. The reformulation and development are based on a canonical transformation which periodizes the fermions in the cluster space. The…

Strongly Correlated Electrons · Physics 2007-05-23 Tran Minh-Tien

We prove bounds on operator growth and infinite temperature out-of-time-ordered correlators in many-body systems with $N$ spin-$\frac{1}{2}$ degrees of freedom which interact via two-body all-to-all interactions. Our results parametrically…

Quantum Physics · Physics 2020-08-12 Chao Yin , Andrew Lucas

The cactus approximation in the cluster variation method is applied to the spin ice system with nearest neighbor ferromagnetic coupling. The temperature dependences of the entropy and the specific heat show qualitatively good agreement with…

Statistical Mechanics · Physics 2009-11-07 S. Yoshida , K. Nemoto , K. Wada

Entanglement between individual spins can be detected by using thermodynamics quantities as entanglement witnesses. This applies to collective spins also, provided that their internal degrees of freedom are frozen, as in the limit of…

Mesoscale and Nanoscale Physics · Physics 2013-11-21 F. Troiani , S. Carretta , P. Santini

We calculate the Lyapunov exponents for particles suspended in a random three-dimensional flow, concentrating on the limit where the viscous damping rate is small compared to the inverse correlation time. In this limit Lyapunov exponents…

Disordered Systems and Neural Networks · Physics 2009-11-11 K. Duncan , B. Mehlig , S. Ostlund , M. Wilkinson

In this paper, we discuss a possibility to improve constraints on spin-dependent short-range interactions in the range of 1 - 200 micrometer significantly. For such interactions, our constraints are without competition at the moment. They…

Nuclear Experiment · Physics 2010-03-04 S. Baeßler , V. V. Nesvizhevsky , G. Pignol , K. V. Protasov , A. Yu. Voronin

In this paper we investigate some particular spin lattice (a higher dimensional generalization of a spin chain) related to Zamolodchikov model, in the limit when both sizes of the lattice tend to infinity. An infinite set of bilinear…

Exactly Solvable and Integrable Systems · Physics 2007-05-23 S. Sergeev

The coupled cluster method has been applied to the eigenvalue problem lattice Hamiltonian QCD (without quarks) for SU(2) gauge fields in two space dimensions. Using a recently presented new formulation and the truncation prescription of Guo…

High Energy Physics - Lattice · Physics 2007-05-23 D. Schuette , A. Wichmann , C. Weichmann

We investigate the self-organization of point-particles with short-range interactions modeled via simple 1D and 2D Hubbard-like models. We show how various properties emerge such as, boson-like ordering leading to topological structures in…

Strongly Correlated Electrons · Physics 2020-09-08 Ioannis Kleftogiannis , Ilias Amanatidis

Clustering under pairwise constraints is an important knowledge discovery tool that enables the learning of appropriate kernels or distance metrics to improve clustering performance. These pairwise constraints, which come in the form of…

Machine Learning · Computer Science 2022-03-24 Benedikt Boecking , Vincent Jeanselme , Artur Dubrawski