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A numerical algorithm for studying strongly correlated electron systems is proposed. The groundstate wavefunction is projected out after numerical renormalization procedure in the path integral formalism. The wavefunction is expressed from…

Strongly Correlated Electrons · Physics 2007-05-23 Masatoshi Imada , Tsuyoshi Kashima

We review a formulation of a renormalization-group scheme for Hamiltonian systems with two degrees of freedom. We discuss the renormalization flow on the basis of the continued fraction expansion of the frequency. The goal of this approach…

chao-dyn · Physics 2007-05-23 C. Chandre , H. R. Jauslin

Percolation refers to an interesting class of problems related to the properties of disordered systems, usually formulated in terms of objects randomly placed on an underlying lattice or continuum. Despite the simplicity of the setup, most…

Statistical Mechanics · Physics 2022-02-22 Abraham Levitan

A new scheme of first-principles computation for strongly correlated electron systems is proposed. This scheme starts from the local-density approximation (LDA) at high-energy band structure, while the low-energy effective Hamiltonian is…

Materials Science · Physics 2007-05-23 Yoshiki Imai , Igor V. Solovyev , Masatoshi Imada

The single-cluster Monte Carlo algorithm and the reweighting technique are used to simulate the 3D-ferromagnetic Ising model on three dimensional Voronoi-Delaunay lattices. It is assumed that the coupling factor $J$ varies with the distance…

Disordered Systems and Neural Networks · Physics 2007-05-23 F. W. S. Lima , U. M. S. Costa , R. N. Costa Filho

A block spin renormalization group approach is proposed for the dynamical triangulation formulation of two-dimensional quantum gravity. The idea is to update link flips on the block lattice in response to link flips on the original lattice.…

High Energy Physics - Lattice · Physics 2011-09-09 Ray Renken

False vacuum decay, a quantum mechanical first-order phase transition in scalar field theories, is an important phenomenon in early universe cosmology. Recently, real-time semi-classical techniques based on ensembles of lattice simulations…

High Energy Physics - Theory · Physics 2023-04-26 Jonathan Braden , Matthew C. Johnson , Hiranya V. Peiris , Andrew Pontzen , Silke Weinfurtner

We obtain an explicit expression for the multipoint energy correlations of a non solvable two-dimensional Ising models with nearest neighbor ferromagnetic interactions plus a weak finite range interaction of strength $\lambda$, in a scaling…

Mathematical Physics · Physics 2012-09-19 Alessandro Giuliani , Rafael L. Greenblatt , Vieri Mastropietro

The problem of structure estimation in graphical models with latent variables is considered. We characterize conditions for tractable graph estimation and develop efficient methods with provable guarantees. We consider models where the…

Machine Learning · Statistics 2013-04-23 Animashree Anandkumar , Ragupathyraj Valluvan

Recent work has shown that probabilistic models based on pairwise interactions-in the simplest case, the Ising model-provide surprisingly accurate descriptions of experiments on real biological networks ranging from neurons to genes.…

Quantitative Methods · Quantitative Biology 2007-12-18 Tamara Broderick , Miroslav Dudik , Gasper Tkacik , Robert E. Schapire , William Bialek

In lattice Hamiltonian systems with a quartic coupling $\gamma$, a critical value $\gamma^*$ may exist such that, when $\gamma=\gamma^*$, the leading irrelevant operator decouples from the Hamiltonian and the leading nonscaling contribution…

Statistical Mechanics · Physics 2009-11-07 Massimo Campostrini , Pietro Parruccini , Paolo Rossi

We demonstrate that a tight-binding Hamiltonian with nearest- and next-nearest-neighbor hopping integrals can be decomposed into bulk and boundary parts in a general lattice system. The Hamiltonian decomposition reveals that next…

Mesoscale and Nanoscale Physics · Physics 2009-04-16 Ken-ichi Sasaki , Yuji Shimomura , Yositake Takane , Katsunori Wakabayashi

Machine learning is becoming widely used in condensed matter physics. Inspired by the concept of image super-resolution, we propose a method to increase the size of lattice spin configurations using deep convolutional neural networks.…

Statistical Mechanics · Physics 2019-02-13 Stavros Efthymiou , Matthew J. S. Beach , Roger G. Melko

In planar lattice statistical mechanics models like coupled Ising with quartic interactions, vertex and dimer models, the exponents depend on all the Hamiltonian details. This corresponds, in the Renormalization Group language, to a line of…

Mathematical Physics · Physics 2020-11-19 Vieri Mastropietro

An ill-defined integral equation for modeling the mass-spectrum of mesons is regulated with an additional but unphysical parameter. This parameter dependance is removed by renormalization. Illustrative graphical examples are given.

High Energy Physics - Phenomenology · Physics 2009-11-07 Michael Frewer , Tobias Frederico , Hans-Christian Pauli

This paper discusses methods for the construction of approximate real space renormalization transformations in statistical mechanics. In particular, it compares two methods of transformation: the "potential-moving" approach most used in the…

Statistical Mechanics · Physics 2015-06-12 Efi Efrati , Zhe Wang , Amy Kolan , Leo P. Kadanoff

The accurate computational determination of chemical, materials, biological, and atmospheric properties has critical impact on a wide range of health and environmental problems, but is deeply limited by the computational scaling of…

Chemical Physics · Physics 2021-06-09 Debadrita Saha , Srinivasan S. Iyengar , Philip Richerme , Jeremy M. Smith , Amr Sabry

We present a new exact renormalization approach for quantum lattice models leading to long-range interactions. The renormalization scheme is based on wavelets with an infinite support in such a way that the excitation spectrum at the fixed…

High Energy Physics - Theory · Physics 2019-09-04 Pascal Fries , Ignacio Reyes , Johanna Erdmenger , Haye Hinrichsen

We prove that the generator of the renormalization group of Potts models on hierarchical lattices can be represented by a rational map acting on a finite-dimensional product of complex projective spaces. In this framework we can also…

Statistical Mechanics · Physics 2008-08-03 Jacopo De Simoi , Stefano Marmi

We report a real-space renormalization group (RSRG) algorithm, which is formulated through Baxter's corner transfer matrix (CTM), for two-dimensional (d = 2) classical lattice models. The new method performs the renormalization group…

Statistical Mechanics · Physics 2008-02-03 Tomotoshi Nishino , Kouichi Okunishi