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We examine the generalized leading-logarithmic approximation (LLA) equations for compound states of n-reggeized gluons. It is shown that in multi-color QCD, when $N_c \rightarrow \infty$, these equations have a sufficient number of…

High Energy Physics - Phenomenology · Physics 2007-05-23 L. N. Lipatov , A. Berera

Cellular Automata (CA) are a class of discrete dynamical systems that have been widely used to model complex systems in which the dynamics is specified at local cell-scale. Classically, CA are run on a regular lattice and with perfect…

Cellular Automata and Lattice Gases · Physics 2007-05-23 Nazim A. Fates , Michel Morvan

We present second-order molecular cluster perturbation theory (MCPT(2)), a linear scaling methodology to calculate arbitrarily large systems with explicit calculation of individual wavefunctions in a coupled-cluster framework. This new…

In this short paper, we consider discrete-time Markov chains on lattices as approximations to continuous-time diffusion processes. The approximations can be interpreted as finite difference schemes for the generator of the process. We…

Probability · Mathematics 2016-11-08 Christoph Reisinger

For the treatment of interacting electrons in crystal lattices approximations based on the picture of effective sites, coupled in a self-consistent fashion, have proven very useful. Particularly in the presence of strong local correlations,…

Strongly Correlated Electrons · Physics 2008-09-19 Norbert Grewe , Sebastian Schmitt , Torben Jabben , Frithjof B. Anders

We study both static and transport properties of model quantum dots, employing density functional theory as well as (numerically) exact methods. For the lattice model under consideration the accuracy of the local-density approximation…

Mesoscale and Nanoscale Physics · Physics 2011-04-11 S. Schenk , P. Schwab , M. Dzierzawa , U. Eckern

Clustering multi-dimensional points is a fundamental task in many fields, and density-based clustering supports many applications as it can discover clusters of arbitrary shapes. This paper addresses the problem of Density-Peaks Clustering…

Databases · Computer Science 2022-12-01 Daichi Amagata , Takahiro Hara

Using Gaussian integral transform techniques borrowed from functional-integral field theory and the replica trick we derive a version of the coherent-potential approximation (CPA) suited for describing ($i$) the diffusive (hopping) motion…

Disordered Systems and Neural Networks · Physics 2015-06-15 S. Köhler , G. Ruocco , W. Schirmacher

Symplectic symmetry approach to clustering (SSAC) in atomic nuclei, recently proposed, is modified and further developed in more detail. It is firstly applied to the light two-cluster $^{20}$Ne + $\alpha$ system of $^{24}$Mg, the latter…

Nuclear Theory · Physics 2025-02-18 H. G. Ganev

We present a massively parallel quantum Monte Carlo based implementation of real-space dynamical mean-field theory for general inhomogeneous correlated fermionic lattice systems. As a first application, we study magnetic order in a binary…

Quantum Gases · Physics 2010-12-16 N. Blümer , E. V. Gorelik

Clustering is one of the most fundamental problem in Machine Learning. Researchers in the field often require a lower bound on the size of the clusters to maintain anonymity and upper bound for the ease of analysis. Specifying an optimal…

Data Structures and Algorithms · Computer Science 2022-03-29 Neelima Gupta , Sapna Grover , Rajni Dabas

We present massively parallel (MPC) algorithms and hardness of approximation results for computing Single-Linkage Clustering of $n$ input $d$-dimensional vectors under Hamming, $\ell_1, \ell_2$ and $\ell_\infty$ distances. All our…

Data Structures and Algorithms · Computer Science 2018-03-28 Grigory Yaroslavtsev , Adithya Vadapalli

In this paper we study from a numerical analysis perspective the Fractional Step Kinetic Monte Carlo (FS-KMC) algorithms proposed in [1] for the parallel simulation of spatially distributed particle systems on a lattice. FS-KMC are…

Numerical Analysis · Mathematics 2012-08-07 Giorgos Arampatzis , Markos A. Katsoulakis , Petr Plechac

D-theory provides an alternative lattice regularization of the (1+1)-d CP(N-1) quantum field theory. In this formulation the continuous classical CP(N-1) fields emerge from the dimensional reduction of discrete SU(N) quantum spins. In…

High Energy Physics - Lattice · Physics 2009-11-10 B. B. Beard , M. Pepe , S. Riederer , U. J. Wiese

Centered kernel alignment (CKA) is a popular metric for comparing representations, determining equivalence of networks, and neuroscience research. However, CKA does not account for the underlying manifold and relies on numerous heuristics…

Machine Learning · Computer Science 2025-10-28 Mohammad Tariqul Islam , Du Liu , Deblina Sarkar

Density functional theory (DFT) provides convenient electronic structure methods for the study of molecular systems and materials. Regular Kohn-Sham DFT calculations rely on unitary transformations to determine the ground-state electronic…

Chemical Physics · Physics 2022-10-10 Greta Jacobson , Juan M. Marmolejo-Tejada , Martín A. Mosquera

We present a numerically feasible semiclassical (SC) method to evaluate quantum fidelity decay (Loschmidt echo, FD) in a classically chaotic system. It was thought that such evaluation would be intractable, but instead we show that a…

Quantum Physics · Physics 2009-11-10 Jiri Vanicek , Eric J. Heller

Simulations in finite density, beta=0 lattice QCD by means of the Monomer-Dimer-Polymer algorithm show a signal of first order transition at finite temporal size. This behaviour agrees with predictions of the mean field approximation, but…

High Energy Physics - Lattice · Physics 2009-10-31 R. Aloisio , V. Azcoiti , G. Di Carlo , A. Galante , A. F. Grillo

We study domain growth properties of two species of particles executing biased diffusion on a half-filled square lattice, consisting of just two lanes. Driven in opposite directions by an external ``electric'' field, the particles form…

Statistical Mechanics · Physics 2009-11-07 J. T. Mettetal , B. Schmittmann , R. K. P. Zia

With the emergence of Artificial Intelligence, numerical algorithms are moving towards more approximate approaches. For methods such as PCA or diffusion maps, it is necessary to compute eigenvalues of a large matrix, which may also be dense…

Numerical Analysis · Mathematics 2023-11-17 Keerthi Gaddameedi , Severin Reiz , Tobias Neckel , Hans-Joachim Bungartz