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For over three decades, scanning probe microscopy (SPM) has been a key method for exploring material structures and functionalities at nanometer and often atomic scales in ambient, liquid, and vacuum environments. Historically, SPM…

A new approach for describing the effective electronic states of "atoms in compounds" to study the properties of molecules and condensed matter which are circumscribed by the operators heavily concentrated in atomic cores is proposed. Among…

Chemical Physics · Physics 2014-12-02 Anatoly V. Titov , Yuriy V. Lomachuk , Leonid V. Skripnikov

In the supplemental materials we justify our choice of the number of Chebychev moments used within the kernel polynomial method, show some preliminary results for the large coupling behavior, discuss possible correlation effects in the…

Disordered Systems and Neural Networks · Physics 2016-01-07 Daniel Jung , Keith Slevin , Stefan Kettemann

This thesis focuses on the experimental creation and detection of a variety of quantum correlations using nuclear magnetic resonance hardware. Quantum entanglement, being most common and counter-intuitive, is one of the main type considered…

Quantum Physics · Physics 2019-05-16 Amandeep Singh

Ultra-short pulses propagating in nonlinear nanophotonic waveguides can simultaneously leverage both temporal and spatial field confinement, promising a route towards single-photon nonlinearities in an all-photonic platform. In this…

Quantum Physics · Physics 2021-10-05 Ryotatsu Yanagimoto , Edwin Ng , Logan G. Wright , Tatsuhiro Onodera , Hideo Mabuchi

Quantum materials are driving a technology revolution in sensing, communication, and computing, while simultaneously testing many core theories of the past century. Materials such as topological insulators, complex oxides, quantum dots,…

Machine learning algorithms based on parametrized quantum circuits are prime candidates for near-term applications on noisy quantum computers. In this direction, various types of quantum machine learning models have been introduced and…

This study presents a comprehensive workflow for investigating particulate materials through combined 360{\deg} electron tomography (ET), nano-computed X-ray tomography (nanoCT), and micro-computed X-ray tomography (microCT), alongside a…

The material point method (MPM) has been increasingly used for the simulation of large deformation processes in fluid-infiltrated porous materials. For undrained poromechanical problems, however, standard MPMs are numerically unstable…

Numerical Analysis · Mathematics 2020-02-27 Yidong Zhao , Jinhyun Choo

High-dimensional Hilbert spaces possess large information encoding and transmission capabilities. Characterizing exactly the real potential of high-dimensional entangled systems is a cornerstone of tomography and quantum imaging. The…

Quantum Physics · Physics 2017-10-10 Laszlo Gyongyosi

A quantitative and predictive theory of quantum light-matter interactions in ultra thin materials involves several fundamental challenges. Any realistic model must simultaneously account for the ultra-confined plasmonic modes and their…

We search for new superhard B-N-O compounds with an iterative machine learning (ML) procedure, where ML models are trained using sample crystal structures from evolutionary algorithm. We first use cohesive energy to evaluate the…

Materials Science · Physics 2022-06-22 Wei-Chih Chen , Yogesh K. Vohra , Cheng-Chien Chen

One of the challenging problems in the condensed matter physics is to understand the quantum many-body systems, especially, their physical mechanisms behind. Since there are only a few complete analytical solutions of these systems, several…

Statistical Mechanics · Physics 2020-03-27 Jozef Genzor , Tomotoshi Nishino , Andrej Gendiar

Quantum impurity solvers are the computational bottleneck of quantum embedding approaches to correlated materials, such as dynamical mean-field theory (DMFT). We show that neural networks trained on synthetic, material-agnostic data learn…

Strongly Correlated Electrons · Physics 2026-03-25 Agnes Valenti , Ina Park , Antoine Georges , Andrew J. Millis , Olivier Parcollet

Simulating quantum many-body systems (QMBS) is one of the long-standing, highly non-trivial challenges in condensed matter physics and quantum information due to the exponentially growing size of the system's Hilbert space. To date, tensor…

Quantum Physics · Physics 2026-02-06 Belal Abouraya , Jirawat Saiphet , Fedor Jelezko , Ressa S. Said

Coupled tensor approximation has recently emerged as a promising approach for the fusion of hyperspectral and multispectral images, reconciling state of the art performance with strong theoretical guarantees. However, tensor-based…

Signal Processing · Electrical Eng. & Systems 2021-04-21 Ricardo Augusto Borsoi , Clémence Prévost , Konstantin Usevich , David Brie , José Carlos Moreira Bermudez , Cédric Richard

Strongly correlated materials are profoundly affected by the repulsive electron-electron interaction. This stands in contrast to many commonly used materials such as silicon and aluminum, whose properties are comparatively unaffected by the…

Strongly Correlated Electrons · Physics 2013-09-19 Emilia Morosan , Douglas Natelson , Andriy H. Nevidomskyy , Qimiao Si

The analysis of Fourier-transformed scanning-tunneling-microscopy (STM) images with subatomic resolution is a common tool for studying properties of quasiparticle excitations in strongly correlated materials. While Fourier amplitudes are…

Strongly Correlated Electrons · Physics 2016-11-30 Emanuele G. Dalla Torre , Yang He , Eugene Demler

A numerical algorithm for studying strongly correlated electron systems is proposed. The groundstate wavefunction is projected out after numerical renormalization procedure in the path integral formalism. The wavefunction is expressed from…

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

Continuous variables systems find valuable applications in quantum information processing. To deal with an infinite-dimensional Hilbert space, one in general has to handle large numbers of discretized measurements in tasks such as…