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A key step in unraveling the mysteries of materials exhibiting unconventional superconductivity is to understand the underlying pairing mechanism. While it is widely agreed upon that the pairing glue in many of these systems originates from…

Strongly Correlated Electrons · Physics 2024-09-09 Annabelle Bohrdt , Eugene Demler , Fabian Grusdt

We present an optimization strategy for atom-specific spin-polarization constants within the spin-polarized GFN2-xTB framework, aiming to enhance the accuracy of molecular simulations. We compare a sequential and global optimization of spin…

In this study, we present a general workflow that enables the automatic generation of auxiliary density basis sets for all elements of the periodic table (from H to Og) to facilitate the general applicability of relativistic Dirac-Kohn-Sham…

Chemical Physics · Physics 2025-06-19 Nicolo' Antonini , Enrico Ronca , Loriano Storchi , Leonardo Belpassi

Modern population genetics studies typically involve genome-wide genotyping of individuals from a diverse network of ancestries. An important, unsolved problem is how to formulate and estimate probabilistic models of observed genotypes that…

Populations and Evolution · Quantitative Biology 2017-01-10 Wei Hao , Minsun Song , John D. Storey

Elements of nuclear symmetry energy evaluated from different energy density functionals parametrized by fitting selective bulk properties of few representative nuclei are seen to vary widely. Those obtained from experimental data on nuclear…

Nuclear Theory · Physics 2015-08-07 C. Mondal , B. K. Agrawal , J. N. De

The explanation of heavy-fermion superconductivity is a long-standing challenge to theory. It is commonly thought to be connected to non-local fluctuations of either spin or charge degrees of freedom and therefore of unconventional type.…

Strongly Correlated Electrons · Physics 2013-04-15 Oliver Bodensiek , Rok Zitko , Matthias Vojta , Mark Jarrell , Thomas Pruschke

We have used VLT FLAMES data to constrain the uncertain physics of rotational mixing in stellar evolution models. We have simulated a population of single stars and find two groups of observed stars that cannot be explained: (1) a group of…

Astrophysics · Physics 2009-01-21 I. Brott , I. Hunter , A. de Koter , N. Langer , D. Lennon , P. Dufton

Strong gravitational lensing (SL) has emerged as a very accurate probe of the mass distribution of cluster- and galaxy-scale dark matter (DM) haloes in the inner regions of galaxy clusters. The derived properties of DM haloes can be…

Astrophysics of Galaxies · Physics 2022-10-26 Giovanni Granata

High temperature atomic configurations of fcc Fe-Cr-Ni alloys with alloy composition close to austenitic steel are studied in statistical thermodynamic simulations with effective interactions obtained in ab initio calculations. The latter…

Materials Science · Physics 2016-09-21 Andrei V. Ruban , Mohammad Dehghani

The structure, binding energy, magnetic moments and electronic structure of FemIrn clusters are investigated using state of the art density functional theory techniques. Fully unconstrained structural relaxations are undertaken by…

Mesoscale and Nanoscale Physics · Physics 2013-01-23 S. Assa Aravindh

The interaction between electronic and nuclear spins in the presence of external magnetic fields can be described by a spin Hamiltonian, with parameters obtained from first principles, electronic structure calculations. We describe an…

Materials Science · Physics 2019-04-10 Krishnendu Ghosh , He Ma , Vikram Gavini , Giulia Galli

This paper studies identifiability and convergence behaviors for parameters of multiple types in finite mixtures, and the effects of model fitting with extra mixing components. First, we present a general theory for strong identifiability,…

Statistics Theory · Mathematics 2015-01-13 Nhat Ho , XuanLong Nguyen

I describe the foundation of a Density Functional Theory approach to include pairing correlations, which was applied to a variety of systems ranging from dilute fermions, to neutron stars and finite nuclei. Ground state properties as well…

Nuclear Theory · Physics 2017-08-23 Aurel Bulgac

A new analysis method to investigate halos in finite many-fermion systems is designed, as existing characterization methods are proven to be incomplete/inaccurate. A decomposition of the internal wave-function of the {$N$-body} system in…

Nuclear Theory · Physics 2013-05-29 V. Rotival , T. Duguet

We present a method which enables solid-state density functional theory calculations to be applied to systems of almost unlimited size. Computations of physical effects up to the micron length scale but which nevertheless depend on the…

Materials Science · Physics 2021-01-04 Tristan Müller , Sangeeta Sharma , E. K. U. Gross , J. K. Dewhurst

We present an information-theoretic approach inspired by distributional clustering to assess the structural heterogeneity of particulate systems. Our method identifies communities of particles that share a similar local structure by…

Statistical Mechanics · Physics 2020-04-20 Joris Paret , Robert L. Jack , Daniele Coslovich

The structural, electronic and magnetic properties of small ${\rm Fe}_m {\rm Rh}_n$ clusters having $N = m+n \leq 8$ atoms are studied in the framework of a generalized-gradient approximation to density-functional theory. For $N = m+n \leq…

Materials Science · Physics 2012-01-31 Junais Habeeb Mokkath , G. M. Pastor

The density of an atom in a state of well-defined angular momentum has a specific finite spherical harmonic content, without and with interactions. Approximate single-particle schemes, such as the Hartree, Hartree-Fock, and Local Density…

Materials Science · Physics 2009-02-05 H. A. Fertig , W. Kohn

The production of heavy mass resonances has been widely studied theoretically and experimentally. Several extensions of the standard model (SM) of particle physics, naturally give rise to a new resonance, with neutral electric charge,…

High Energy Physics - Phenomenology · Physics 2023-05-31 Diego Barbosa , Felipe Díaz , Liliana Quintero , Andrés Flórez , Manuel Sanchez , Alfredo Gurrola , Elijah Sheridan , Francesco Romeo

Machine-learning of atomic-scale properties amounts to extracting correlations between structure, composition and the quantity that one wants to predict. Representing the input structure in a way that best reflects such correlations makes…

Chemical Physics · Physics 2021-02-02 Michael J. Willatt , Félix Musil , Michele Ceriotti