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Since the discovery of high-temperature superconductivity in the thin-film FeSe/SrTiO$_3$ system, iron selenide and its derivates have been intensively scrutinized. Using ab initio density functional theory calculations we review the…
The kinetic behavior of a three-dimensional off-lattice heteropolymer model is studied in terms of the time dependence of the average mean-square displacement between configurations. It is found that at short time-scales similar behavior is…
Owing to their small mass, hydrogen atoms exhibit strong quantum behavior even at room temperature. Including these effects in first principles calculations is challenging, because of the huge computational effort required by conventional…
We study a symmetry property of momentum distribution functions in the steady state of heat conduction. When the equation of motion is symmetric under change of signs for all dynamical variables, the distribution function is also symmetric.…
Ultrahigh lattice thermal conductivity materials hold great importance since they play a critical role in the thermal management of electronic and optical devices. Models using machine learning can search for materials with outstanding…
Thermodynamic and electronic properties are obtained for a lattice-gas model fluid with self-consistent, partial, occupation of its sites; the self consistency consists in obtaining ionic configurations from grand-canonical Monte Carlo…
Lattice models are popular methods for simulating deformation of solids by discretizing continuum structures into spring networks. Despite the simplicity and efficiency, most lattice models only rigorously converge to continuum models for…
The isotropic-to-nematic transition in liquid crystals is studied in d=3 spatial dimensions. A simulation method is proposed to measure the angle dependent interfacial tension g(theta), with theta the anchoring angle of the nematic phase at…
There has been a surge of experimental effort recently in cooling trapped fermionic atoms to quantum degeneracy. By varying an external magnetic field, interactions between atoms can be made arbitrarily strong. When the S wave scattering…
The machine learning of lattice operators has three possible bottlenecks. From a statistical standpoint, it is necessary to design a constrained class of operators based on prior information with low bias, and low complexity relative to the…
We perform the analysis of predictions of a classical density functional theory for associating fluids with different association strength concerned with wetting of solid surfaces. The four associating sites water-like models with…
First single crystal fibers of cerium doped strontium yttrate are fabricated using the laser-heated pedestal growth technique. Through thermodynamic equilibrium calculations and by high-temperature mass spectrometry suitable growth…
Convergence detection of iterative stochastic optimization methods is of great practical interest. This paper considers stochastic gradient descent (SGD) with a constant learning rate and momentum. We show that there exists a transient…
The hydrogen phase diagram has a number of unusual features which are generally well reproduced by density functional calculations. Unfortunately, these calculations fail to provide good physical insights into why those features occur. In…
Lattice QCD has the potential this decade to maximize the sensitivity of the entire flavor physics program to new physics and pave the way for understanding physics beyond the Standard Model at the LHC in the coming decade. However, the…
Lanthanide hydrogen-rich materials have long been considered as one of the candidates with high-temperature superconducting properties in condensed matter physics, and have attracted great interest. Attempts to investigate the effects of…
Indentation has been widely used for investigating the mechanical behavior of glasses. However, how the various microscopic properties (such as atomic structure and mechanics) of glass evolve from the immediate contact with the indenter to…
Machine learning promises to accelerate the material discovery by enabling high-throughput prediction of desirable macro-properties from atomic-level descriptors or structures. However, the limited data available about precise values of…
Active matter has been widely studied in recent years because of its rich phenomenology, whose mathematical understanding is still partial. We present some results, based on [8, 17] linking microscopic lattice gases to their macroscopic…
A general machine learning architecture is introduced that uses wavelet scattering coefficients of an inputted three dimensional signal as features. Solid harmonic wavelet scattering transforms of three dimensional signals were previously…