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Related papers: Phase Diagrams Construction Using Mean-Field Renor…

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We have studied the problem of phase stability in NiPt alloy system. We have used the augmented space recursion based on the TB-LMTO as the method for studying the electronic structure of the alloys. In particular, we have used the…

Materials Science · Physics 2009-11-07 Durga Paudyal , Tanusri Saha-Dasgupta , Abhijit Mookerjee

Systems of Y-junctions are interesting both from a fundamental viewpoint and because of their potential use in nanoscale devices. These systems can be studied numerically with the density matrix renormalization group(DMRG), but existing…

Strongly Correlated Electrons · Physics 2007-05-23 Haihui Guo , Steven R. White

The particle-flow (PF) algorithm is used in general-purpose particle detectors to reconstruct a comprehensive particle-level view of the collision by combining information from different subdetectors. A graph neural network (GNN) model,…

Data Analysis, Statistics and Probability · Physics 2021-11-29 Farouk Mokhtar , Raghav Kansal , Daniel Diaz , Javier Duarte , Joosep Pata , Maurizio Pierini , Jean-Roch Vlimant

We use the numerical renormalization group method (NRG) to investigate a single-impurity Anderson model with a coupling of the impurity to a superconducting host. Analysis of the energy flow shows, in contrast to previous belief, that NRG…

Strongly Correlated Electrons · Physics 2015-05-13 Theresa Hecht , Andreas Weichselbaum , Jan von Delft , Ralf Bulla

We develop a controlled weak coupling renormalization group (RG) approach to itinerant electrons. Within this formalism we rederive the phase diagram for two-dimensional (2D) non-nested systems. Then we study how nesting modifies this phase…

Strongly Correlated Electrons · Physics 2009-10-31 F. Vistulo de Abreu , B. Doucot

The one dimensional Hubbard model with nearest and (negative) next-nearest neighbour hopping has been studied with the density-matrix renormalization group (DMRG) method. A large region of ferromagnetism has been found for finite density…

Strongly Correlated Electrons · Physics 2009-10-28 S. Daul , R. Noack

Automated polyp segmentation is essential for early diagnosis of colorectal cancer, yet developing robust models remains challenging due to limited annotated data and significant performance degradation under domain shift. Although…

Computer Vision and Pattern Recognition · Computer Science 2025-08-12 Haoran Xi , Chen Liu , Xiaolin Li

The use of Mean-Field theory to unwrap principal phase patterns has been recently proposed. In this paper we generalize the Mean-Field approach to process phase patterns with arbitrary degree of undersampling. The phase unwrapping problem…

Statistical Mechanics · Physics 2009-10-31 S. Stramaglia , A. Refice , L. Guerriero

We introduce a new phase-field formulation of rapid alloy solidification that quantitatively incorporates nonequilibrium effects at the solid-liquid interface over a very wide range of interface velocities. Simulations identify a new…

Materials Science · Physics 2023-01-16 Kaihua Ji , Elaheh Dorari , Amy J. Clarke , Alain Karma

A renormalization group (RG) analysis of the superconductive instability of an anisotropic fermionic system is developed at a finite temperature. The method appears a natural generalization of Shankar's approach to interacting fermions and…

Condensed Matter · Physics 2009-10-28 Fabio Siringo , Giuseppe G. N. Angilella , Renato Pucci

We employ the functional renormalization group flow equations to investigate the phase structure of the two-flavor quark-meson model in the presence of a finite isospin chemical potential, incorporating interactions with omega and rho…

High Energy Physics - Phenomenology · Physics 2025-06-10 Mohammed Osman , Defu Hou , Wentao Wang , Hui Zhang

A mean field rate theory description of the homo- and co-polymerization of $f$-functional molecules is developed, which contains the formation of short cyclic structures inside the network. The predictions of this model are compared with…

Soft Condensed Matter · Physics 2021-03-31 Michael Lang , Konrad Schwenke , Jens-Uwe Sommer

Machine-learned force fields (MLFFs) promise to offer a computationally efficient alternative to ab initio simulations for complex molecular systems. However, ensuring their generalizability beyond training data is crucial for their wide…

Machine Learning · Computer Science 2024-12-24 Shaswat Mohanty , Yifan Wang , Wei Cai

The traditional Triangular Maximally Filtered Graph (TMFG) construction requires pre-computation and storage of a dense correlation matrix; this limits its applicability to small and medium-sized datasets. Here we identify key memory and…

Machine Learning · Statistics 2026-03-11 Lionel Yelibi

By combining ab-initio electron theory and statistical mechanics, the physical properties of the ternary intermetallic system Ni-Fe-Al in the ground state and at finite temperatures were investigated. The Ni-Fe-Al system is not only of high…

Materials Science · Physics 2007-05-23 Frank Lechermann , Manfred Faehnle , Juan M. Sanchez

Using density functional theory, we study the magnetic stability of the Ga$_{1-x}$Mn$_x$N alloy system. We show that unlike Ga$_{1-x}$Mn$_x$As, which shows only ferromagnetic (FM) phase, Ga$_{1-x}$Mn$_x$N can be stable in either FM or…

Materials Science · Physics 2015-06-25 Gustavo M. Dalpian , Su-Huai Wei

We present a functional renormalization group (fRG) study of the two dimensional Hubbard model, performed with an algorithmic implementation which lifts some of the common approximations made in fRG calculations. In particular, in our fRG…

Strongly Correlated Electrons · Physics 2019-10-23 Agnese Tagliavini , Cornelia Hille , Fabian B. Kugler , Sabine Andergassen , Alessandro Toschi , Carsten Honerkamp

We explore the zero-temperature phase diagram of a one-dimensional gas composed of three-color fermions, which interact locally and with their next neighbors. Using the density matrix renormalization group method and considering one-third…

Quantum Gases · Physics 2021-12-08 A. Pérez-Romero , R. Franco , J. Silva-Valencia

Graph neural networks (GNNs) have emerged as the state of the art for a variety of graph-related tasks and have been widely used in Heterogeneous Graphs (HetGs), where meta-paths help encode specific semantics between various node types.…

Machine Learning · Computer Science 2025-02-25 Xuqi Mao , Zhenying He , X. Sean Wang

Inspired by the superblock method of White, we introduce a simple modification of the standard Renormalization Group (RG) technique for the study of quantum lattice systems. Our method which takes into account the effect of Boundary…

Statistical Mechanics · Physics 2009-10-28 A. Langari , V. Karimipour