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We describe how density-functional theory, well-known for its many uses in ab initio calculations of electronic structure, can be used to study the ground state of inhomogeneous model Hamiltonians. The basic ideas and concepts are discussed…

Materials Science · Physics 2007-05-23 Valter L. Libero , Klaus Capelle

A new efficient numerical algorithm for interacting fermion systems is proposed and examined in detail. The ground state is expressed approximately by a linear combination of numerically chosen basis states in a truncated Hilbert space. Two…

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

The highly influential two-group model in testing a large number of statistical hypotheses assumes that the test statistics are drawn independently from a mixture of a high probability null distribution and a low probability alternative.…

Methodology · Statistics 2020-12-08 Ruth Heller , Saharon Rosset

Using the Density Matrix Renormalization Group and two-leg ladders, we investigate an electronic two-orbital Hubbard model including plaquette diagonal hopping amplitudes. Our goal is to search for regimes where charges added to the undoped…

Strongly Correlated Electrons · Physics 2015-05-18 J. C. Xavier , G. Alvarez , A. Moreo , E. Dagotto

We present a class of Lie algebraic similarity transformations generated by exponentials of two-body on-site hermitian operators whose Hausdorff series can be summed exactly without truncation. The correlators are defined over the entire…

Strongly Correlated Electrons · Physics 2015-06-22 Jacob M. Wahlen-Strothman , Carlos A. Jimenez-Hoyos , Thomas M. Henderson , Gustavo E. Scuseria

A one-dimensional model of electrons locally coupled to spin-1/2 degrees of freedom is studied by numerical techniques. The model is one in the class of $dynamic$ $Hubbard$ $models$ that describe the relaxation of an atomic orbital upon…

Strongly Correlated Electrons · Physics 2009-11-07 J. E. Hirsch

We investigate the existence and the properties of fully separable (fully factorized) ground states in quantum spin systems. Exploiting techniques of quantum information and entanglement theory we extend a recently introduced method and…

Statistical Mechanics · Physics 2009-07-01 S. M. Giampaolo , G. Adesso , F. Illuminati

The standard Large Deviation Theory (LDT) is mathematically illustrated by the Boltzmann-Gibbs factor which describes the thermal equilibrium of short-range-interacting many-body Hamiltonian systems, the velocity distribution of which is…

Statistical Mechanics · Physics 2021-12-24 Ugur Tirnakli , Constantino Tsallis , Nihat Ay

Off-diagonal hypervirial relationships, combined with quantum mechanical sum rules of charge-current conservation, offer a way for testing electronic excited-state transition energies and moments, which does not need any external reference.…

Chemical Physics · Physics 2021-02-16 Francesco Ferdinando Summa , Guglielmo Monaco , Riccardo Zanasi , Paolo Lazzeretti

A fundamental assumption of the dynamical density functional theory (DDFT) of colloidal systems is that a grand-canonical free energy functional may be employed to generate the thermodynamic driving forces. Using one-dimensional hard-rods…

Soft Condensed Matter · Physics 2013-06-04 Johannes Reinhardt , Joseph Michael Brader

Using the Runge-Gross theorem that establishes the foundation of Time-dependent Density Functional Theory (TDDFT) we prove that for a given electronic Hamiltonian, choice of initial state, and choice of fragmentation, there is a unique…

Chemical Physics · Physics 2015-06-15 Martin A. Mosquera , Daniel Jensen , Adam Wasserman

We investigate the performance of a family of multiple comparison procedures for strong control of the False Discovery Rate ($\mathsf{FDR}$). The $\mathsf{FDR}$ is the expected False Discovery Proportion ($\mathsf{FDP}$), that is, the…

Statistics Theory · Mathematics 2008-11-21 Pierre Neuvial

We present a novel rationale-centric framework with human-in-the-loop -- Rationales-centric Double-robustness Learning (RDL) -- to boost model out-of-distribution performance in few-shot learning scenarios. By using static semi-factual…

Artificial Intelligence · Computer Science 2022-03-25 Jinghui Lu , Linyi Yang , Brian Mac Namee , Yue Zhang

As a prototype model of antiferromagnetism, we propose a repulsive Hubbard Hamiltonian defined on a graph $\L={\cal A}\cup{\cal B}$ with ${\cal A}\cap {\cal B}=\emptyset$ and bonds connecting any element of ${\cal A}$ with all the elements…

Strongly Correlated Electrons · Physics 2007-05-23 Gianluca Stefanucci , Michele Cini

The exact ground state of four electrons in an arbitrary large two leg Hubbard ladder is deduced from nine analytic and explicit linear equations. The used procedure is described, and the properties of the ground state are analyzed. The…

Strongly Correlated Electrons · Physics 2007-05-23 Endre Kovacs , Zsolt Gulacsi

As a result of the interplay between the intrinsic off-diagonal terms of the dipolar interaction and an applied {\it transverse} field $H_t$, the diluted ${\rm LiHo_xY_{1-x}F_4}$ system at x$> 0.5$ is equivalent to a ferromagnet in a…

Disordered Systems and Neural Networks · Physics 2008-01-09 Moshe Schechter

While the variational principle for excited-state energies leads to a route to obtaining excited-state densities from time-dependent density functional theory, relatively little attention has been paid to the quality of the resulting…

Chemical Physics · Physics 2025-09-12 Anna Baranova , Neepa T. Maitra

It is known for quite some time that approximate density functional (ADF) theories fail disastrously when describing the dis-sociative symmetric radical cations R2+. Considering this dissociation limit, previous work has shown that…

Materials Science · Physics 2016-09-28 Ester Livshits , Roi Baer

It is shown that a Hopfield recurrent neural network exhibits a scaling regime, whose specific exponents depend on the number of parcels used and the decay length of the coupling strength. This scaling regime recovers the picture introduced…

Disordered Systems and Neural Networks · Physics 2025-02-17 Giorgio Gosti , Sauro Succi , Giancarlo Ruocco

We introduce a new, algebraic method to construct duality functions for integrable dynamic models. This method will be implemented on dynamic stochastic higher spin vertex models, where we prove the duality functions are the $ _3 \varphi_2$…

Probability · Mathematics 2024-05-20 Jeffrey Kuan , Zhengye Zhou