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We develop a numerically exact method for the summation of irreducible Feynman diagrams for fermionic self-energy in the thermodynamic limit. The technique, based on the Diagrammatic Determinant Monte Carlo and its recent extension to…

Strongly Correlated Electrons · Physics 2019-09-11 Fedor Simkovic IV. , Evgeny Kozik

Recently developed neural network-based \emph{ab-initio} solutions (Pfau et. al arxiv:1909.02487v2) for finding ground states of fermionic systems can generate state-of-the-art results on a broad class of systems. In this work, we improve…

Chemical Physics · Physics 2021-03-26 Max Wilson , Nicholas Gao , Filip Wudarski , Eleanor Rieffel , Norm M. Tubman

The Random-Field Ising Model (RFIM) has been extensively studied as a model system for understanding the effects of disorder in magnets. Since the late 1970s, there has been a particular focus on realizations of the RFIM in site-diluted…

Disordered Systems and Neural Networks · Physics 2008-01-16 D. M. Silevitch , D. Bitko , J. Brooke , S. Ghosh , G. Aeppli , T. F. Rosenbaum

We present a realistic study for electronic and magnetic properties in dilute magnetic semiconductor (Ga,Mn)As. A multi-orbital Haldane-Anderson model parameterized by density-functional calculations is presented and solved with the…

Uncertainty estimation in deep models is essential in many real-world applications and has benefited from developments over the last several years. Recent evidence suggests that existing solutions dependent on simple Gaussian formulations…

Machine Learning · Computer Science 2022-05-11 Jurijs Nazarovs , Ronak R. Mehta , Vishnu Suresh Lokhande , Vikas Singh

We present a method for optimizing the location of the fermion ground-state nodes using a combination of diffusion Monte Carlo (DMC) and projected gradient descent (PGD). A PGD iteration shifts the parameters of an arbitrary node-fixing…

Computational Physics · Physics 2022-04-06 John McFarland , Efstratios Manousakis

Effects of the site dilution on spin-gapped Heisenberg antiferromagnets with $S=1/2$ and S=1 on a square lattice are investigated by means of the quantum Monte Carlo method. It is found that effective magnetic moments induced around the…

Disordered Systems and Neural Networks · Physics 2009-11-07 Chitoshi Yasuda , Synge Todo , Munehisa Matsumoto , Hajime Takayama

The critical behavior of the disordered ferromagnetic Ising model is studied numerically by the Monte Carlo method in a wide range of variation of concentration of nonmagnetic impurity atoms. The temperature dependences of correlation…

Disordered Systems and Neural Networks · Physics 2007-09-11 V. Prudnikov , P. Prudnikov , A. Vakilov , A. Krinitsyn

Diagrammatic Monte Carlo -- the technique for numerically exact summation of all Feynman diagrams to high orders -- offers a unique unbiased probe of continuous phase transitions. Being formulated directly in the thermodynamic limit, the…

Strongly Correlated Electrons · Physics 2022-09-07 Connor Lenihan , Aaram J. Kim , Fedor Šimkovic IV. , Evgeny Kozik

On the basis of the mean spherical approximation of multicomponent dipolar hard sphere mixtures an analytical expression is proposed for the magnetic field dependence of the magnetization of size polydisperse ferrofluids. The polydispersity…

Soft Condensed Matter · Physics 2013-07-18 I. Szalai , S. Nagy , S. Dietrich

A Monte Carlo method based on a density-of-states sampling is proposed for study of arbitrary statistical mechanical ensembles in a continuum. A random walk in the two-dimensional space of particle number and energy is used to estimate the…

Soft Condensed Matter · Physics 2009-11-07 Qiliang Yan , Roland Faller , Juan J. de Pablo

The magnetic properties of graphene on finite geometries are studied using a self-consistent mean-field theory of the Hubbard model. This approach is known to predict ferromagnetic edge states close to the zig-zag edges in single-layer…

Strongly Correlated Electrons · Physics 2020-03-04 Hélène Feldner , Zi Yang Meng , Andreas Honecker , Daniel Cabra , Stefan Wessel , Fakher F. Assaad

Strongly-coupled fermionic systems can support a variety of low-energy phenomena, giving rise to collective condensation, symmetry breaking and a rich phase structure. We explore the potential of worldline Monte Carlo methods for analyzing…

High Energy Physics - Theory · Physics 2010-11-11 Gerald Dunne , Holger Gies , Klaus Klingmuller , Kurt Langfeld

Two improved kMC models for investigations of the magnetic properties of finite-size atomic chains are presented. These models take the possible noncollinearity of magnetic moments into account. The spontaneous remagnetization of…

Mesoscale and Nanoscale Physics · Physics 2022-05-18 Sergey Kolesnikov

Ferrofluids belong to an important class of highly functional soft matter, benefiting from their magnetically controllable physical properties. Therefore, it is of central importance to quantitatively predict the dynamic magnetic response…

Soft Condensed Matter · Physics 2020-11-17 Angbo Fang

The problem of calculating the frequencies of network motifs on three and four nodes in large networks is considered. Telecommunications networks, cell molecular networks are investigated. The sizes of the investigated networks are hundreds…

Social and Information Networks · Computer Science 2020-01-08 M. N. Yudina , V. N. Zadorozhnyi , E. B. Yudin

We investigate the Monte Carlo approach to propagation of experimental uncertainties within the context of the established "MSTW 2008" global analysis of parton distribution functions (PDFs) of the proton at next-to-leading order in the…

High Energy Physics - Phenomenology · Physics 2012-08-13 G. Watt , R. S. Thorne

We present a promising coarse-graining strategy for linking micro- and mesoscales of soft matter systems. The approach is based on effective pairwise interaction potentials obtained from detailed atomistic molecular dynamics (MD)…

Soft Condensed Matter · Physics 2007-05-23 A. P. Lyubartsev , M. Karttunen , I. Vattulainen , A. Laaksonen

We report results of a Monte Carlo study of doped, diluted magnetic semiconductors in the low carrier density (insulating) regime. We find that the system undergoes a transition from a paramagnet at high temperatures to a ferromagnet at low…

Materials Science · Physics 2007-05-23 Xin Wan , R. N. Bhatt

We develop a diagrammatic Monte Carlo method for the real-time dynamics of dissipative quantum impurity models. These are small open quantum systems with interaction and local Markovian dissipation, coupled to a large quantum bath. Our…

Strongly Correlated Electrons · Physics 2024-03-26 Matthieu Vanhoecke , Marco Schirò