Quantum computers hold promise to enable efficient simulations of the properties of molecules and materials; however, at present they only permit ab initio calculations of a few atoms, due to a limited number of qubits. In order to harness the power of near-term quantum computers for simulations of larger systems, it is desirable to develop hybrid quantum-classical methods where the quantum computation is restricted to a small portion of the system. This is of particular relevance for molecules and solids where an active region requires a higher level of theoretical accuracy than its environment. Here we present a quantum embedding theory for the calculation of strongly-correlated electronic states of active regions, with the rest of the system described within density functional theory. We demonstrate the accuracy and effectiveness of the approach by investigating several defect quantum bits in semiconductors that are of great interest for quantum information technologies. We perform calculations on quantum computers and show that they yield results in agreement with those obtained with exact diagonalization on classical architectures, paving the way to simulations of realistic materials on near-term quantum computers.
Characterization of the deformation of materials across different length scales has continuously attracted enormous attention from the mechanics and materials communities. In this study, the possibility of utilizing a computer vision algorithm to extract deformation information of materials has been explored, which greatly expands the use of computer vision approaches to studying mechanics of materials and potentially opens new dialogues between the two communities. The computer vision algorithm is first developed and tested on computationally deformed images, before evaluating experimentally …
A highly anticipated application for quantum computers is as a universal simulator of quantum many-body systems, as was conjectured by Richard Feynman in the 1980s. The last decade has witnessed the growing success of quantum computing for simulating static properties of quantum systems, i.e., the ground state energy of small molecules. However, it remains a challenge to simulate quantum many-body dynamics on current-to-near-future noisy intermediate-scale quantum computers. Here, we demonstrate successful simulation of nontrivial quantum dynamics on IBM's Q16 Melbourne quantum processor and R…
An extremely scalable linear-algebraic algorithm was developed for quantum material simulation (electronic state calculation) with 10$^8$ atoms or 100-nm-scale materials. The mathematical foundation is generalized shifted linear equations ((zB - A) x = b), instead of conventional generalized eigenvalue equations. The method has a highly parallelizable mathematical structure. The fundamental theory is mathematical and is applicable also to other scientific fields. The benchmark shows an extreme strong scaling and a qualified time-to-solution on the full system of the K computer. The method was …
BerkeleyGW is a massively parallel computational package for electron excited-state properties that is based on the many-body perturbation theory employing the ab initio GW and GW plus Bethe-Salpeter equation methodology. It can be used in conjunction with many density-functional theory codes for ground-state properties, including PARATEC, PARSEC, Quantum ESPRESSO, OCTOPUS and SIESTA. The package can be used to compute the electronic and optical properties of a wide variety of material systems from bulk semiconductors and metals to nanostructured materials and molecules. The package scales to …
Spectroscopy is an indispensable tool in understanding the structures and dynamics of molecular systems. However computational modelling of spectroscopy is challenging due to the exponential scaling of computational complexity with system sizes unless drastic approximations are made. Quantum computer could potentially overcome these classically intractable computational tasks, but existing approaches using quantum computers to simulate spectroscopy can only handle isolated and static molecules. In this work we develop a workflow that combines multi-scale modeling and time-dependent variational…
In this paper, we review some recent work on amorphous materials using current "first principles" electronic structure/molecular dynamics techniques. The main theme of the paper is to emphasize new directions in the use of such ab initio methods. Some of these, being quite new, need development, but we believe have promise for solving new and important kinds of problems in the physics of glassy and amorphous materials. Initially, we discuss first principles calculations in broad outline and comment on the various approximations in common use. Then, we describe methods for forming a computer mo…
Quantum computers hold promise to improve the efficiency of quantum simulations of materials and to enable the investigation of systems and properties more complex than tractable at present on classical architectures. Here, we discuss computational frameworks to carry out electronic structure calculations of solids on noisy intermediate scale quantum computers using embedding theories, and we give examples for a specific class of materials, i.e., spin defects in solids. These are promising systems to build future quantum technologies, e.g., computers, sensors and devices for quantum communicat…
There is a pressing need to develop new rechargeable battery technologies that can offer higher energy storage, faster charging, and lower costs. Despite the success of existing methods for the simulation of battery materials, they can sometimes fall short of delivering accurate and reliable results. Quantum computing has been discussed as an avenue to overcome these issues, but only limited work has been done to outline how they may impact battery simulations. In this work, we provide a detailed answer to the following question: how can a quantum computer be used to simulate key properties of…
University of Wisconsin Milwaukee（威斯康星大学密尔沃基分校）；SUNY Polytechnic Institute（纽约州立大学理工学院）
Finding quantitative descriptors representing the microstructural features of a given material is an ongoing research area in the paradigm of Materials-by-Design. Historically, microstructural analysis mostly relies on qualitative descriptions. However, to build a robust and accurate process-structure-properties relationship, which is required for designing new advanced high-performance materials, the extraction of quantitative and meaningful statistical data from the microstructural analysis is a critical step. In recent years, computer vision (CV) methods, especially those which are centered…
The present paper gives a review of our recent progress and latest results for novel linear-algebraic algorithms and its application to large-scale quantum material simulations or electronic structure calculations. The algorithms are Krylov-subspace (iterative) solvers for generalized shifted linear equations, in the form of (zS-H)x=b,in stead of conventional generalized eigen-value equation. The method was implemented in our order-$N$ calculation code ELSES (http://www.elses.jp/) with modelled systems based on ab initio calculations. The code realized one-hundred-million-atom, or 100-nm-scale…
Lithium niobate, LiNbO3, is an important technological material with good electro-optic, acousto-optic, elasto-optic, piezoelectric and nonlinear properties. Doping LiNbO3 with hafnium, Hf has been shown to improve the resistance of the material to optical damage. Computer modelling provides a useful means of determining the properties of doped and undoped LiNbO3, including its defect chemistry, and the effect of doping on the structure. In this paper, Hf doped LiNbO3 has been modelled, and the final defect configurations are found to be consistent with experimental results.
This article is intended to an introductory lecture in material physics, in which the modern computational group theory and the electronic structure calculation are in collaboration. The effort of mathematicians in field of the group theory, have ripened as a new trend, called "computer algebra", outcomes of which now can be available as handy computational packages, and would also be useful to physicists with practical purposes. This article, in the former part, explains how to use the computer algebra for the applications in the solid-state simulation, by means of one of the computer algebra…
In this review, we present our recent computational work on carbon-based nanostructured composites. These materials consist of carbon crystallites embedded in an amorphous carbon matrix and are modeled here through classical and semi-empirical quantum-mechanical simulations. We investigate the energetics, mechano-elastic, and optoelectronic properties of these materials. Once the stability of the composites is discussed, we move on to the calculation of their elastic moduli and constants, their anisotropy and elastic recovery. At a next step, we focus on diamond composites, which were found to…
Despite 2D materials holding great promise for a broad range of applications, the proliferation of devices and their fulfillment of real-life demands are still far from being realized. Experimentally obtainable samples commonly experience a wide range of perturbations (ripples and wrinkles, point and line defects, grain boundaries, strain field, doping, water intercalation, oxidation, edge reconstructions) significantly deviating the properties from idealistic models. These perturbations, in general, can be entangled or occur in groups with each group forming a complex perturbation making the …
I've been building Powerpoint-based quantum computers with electron spins in silicon for 20 years. Unfortunately, real-life-based quantum dot quantum computers are harder to implement. Materials, fabrication, and control challenges still impede progress. The way to accelerate discovery is to make and measure more qubits. Here I discuss separating the qubit realization and testing circuitry from the materials science and on-chip fabrication that will ultimately be necessary. This approach should allow us, in the shorter term, to characterize wafers non-invasively for their qubit-relevant proper…
Site-occupancy disorder, defined as the non-periodic occupation of lattice sites in a crystal structure, is a ubiquitous phenomenon in solid-state physics and chemistry. Examples are mineral solid solutions, synthetic non-stoichiometric compounds and metal alloys. The experimental investigation of these materials using diffraction techniques only provides averaged information of their structure. However, many properties of interest in these solids are determined by the local geometry and degree of disorder, which escape an "average crystal" description, either from experiments or from theory. …
Quantum computers can potentially achieve an exponential speedup versus classical computers on certain computational tasks, as recently demonstrated in systems of superconducting qubits. However, these qubits have large footprints due to their large capacitor electrodes needed to suppress losses by avoiding dielectric materials. This tactic hinders scaling by increasing parasitic coupling among circuit components, degrading individual qubit addressability, and limiting the spatial density of qubits. Here, we take advantage of the unique properties of the van der Waals (vdW) materials to reduce…
The anharmonic phenomena in Zirconium Hydrides and Deuterides, including ε-ZrH2, γ-ZrH, and γ-ZrD, have been investigated from aspects of inelastic neutron scattering (INS) and lattice dynamics calculations within the framework of density functional theory (DFT). The observed multiple sharp peaks below harmonic multi-phonon bands in the experimental spectra of all three materials did not show up in the simulated INS spectra based on the harmonic approximation, indicating the existence of strong anharmonicity in those materials and the necessity of further explanations. We present a detailed st…
Revealing the Evolution of Order in Materials Microstructures Using Multi-Modal Computer Vision
Department of Materials Science and Engineering, University of California, Irvine, Irvine, California 92697（材料科学与工程系，加州大学伊尔弗斯分校）；National Security Directorate, Pacific Northwest National Laboratory, Richland, Washington 99352（国家安全 Directorate，太平洋西北国家实验室）；Environment Directorate, Pacific Northwest National Laboratory, Richland, Washington 99352（环境 Directorate，太平洋西北国家实验室）；Computational Sciences Directorate, Pacific Northwest National Laboratory, Richland, Washington 99352（计算科学 Directorate，太平洋西北国家实验室）；Department of Physics, Auburn University, Auburn, Alabama 36849（物理系，阿伯茨海德大学）；Department of Nuclear Engineering, University of New Mexico, Albuquerque, New Mexico 87131（核工程系，新墨西哥大学）；Department of Nuclear Engineering, University of Tennessee, Knoxville, Tennessee 37996（核工程系，田纳西大学， Knoxville分校）；Engineering, University of Delaware, Newark, Delaware 19716（工程系，德雷塞尔大学，新阿罗约分校）；National Renewable Energy Laboratory, Golden, Colorado 80401（国家可再生能源实验室）；Sustainable Energy Institute, University of Colorado Boulder, Boulder, CO, 80309（可持续能源学院，科罗拉多大学波德分校）
Several interesting phenomena are observed when materials are put under pressure. The goal is to achieve modification and control over their mechanical and electronic (conduction) properties. Within this spirit, we have recently focused our attention into how carbon nanostructures respond to hydrostatic pressure. We performed Monte Carlo simulations with the Tersoff potential of various free-standing carbon nanostructures. These range from fullerenes, onions and carbon spheres to nanotubes and nanodiamonds. Our simulations show that the nanostructures undergo some notable structural modificati…
We derive and validate a quantitative analytical model of the near-field electrostatic effects in the vicinity (>=3Å) of two-dimensional (2D) materials. In solving the Poisson equation of a near-planar point charge ansatz for the electronic density of a 2D material, our formula quantitatively captures the out-of-plane decay and the in-plane modulation of density functional theory (DFT)-calculated potentials. We provide a method for quickly constructing the electronic density ansatz, and apply it to the case of hexagonal monolayers (BN, AlN, GaN) and monochalcogenides (GeS, GeSe, GeTe, SnS, SnS…
Autonomous epitaxial atomic-layer synthesis via real-time computer vision of electron diffraction
University of Maryland, College Park（马里兰大学帕克分校）；Maryland Quantum Materials Center, Department of Physics, University of Maryland, College Park（马里兰大学帕克分校物理系马里兰量子材料中心）；Institute for Solid State Physics, University of Tokyo（东京大学固体物理研究所）；U.S. Naval Research Laboratory（美国海军研究实验室）；National Institute of Standards and Technology（美国国家标准与技术研究院）
Epsilon-near-zero (ENZ) materials such as indium tin oxide (ITO), have recently emerged as a new platform to enhance optical nonlinearities. Here we report a theoretical and experimental study on the origin of nonlinearities in ITO thin films that are dominated by two mechanisms based on intraband and interband transitions. We show that there are two competing factors that jointly contribute to a spectrally-invertible nonlinearity of ITO near its ENZ region i.e. the non-parabolicity of the band structure that results in a larger effective mass in the intraband transition and the Fermi energy s…
We compute the electronic structure of two-dimensional (2D) materials decorated with self-assembled organic monolayers using density functional theory. We find that 2D materials are strongly impacted by near-field electrostatic effects resulting from high multipoles of the organic layer electronic density. We show that this effect can lead to significant (~0.5V) modulation of the in-plane potential experienced by electrons in 2D materials within ~4Åfrom the molecular layer, with a transition between near- and far-field depending on the lateral extent of the molecules. We develop a theory of th…
Conventional computer electronics creates a dichotomy between how information is processed and how it is stored. Silicon chips process information by controlling the flow of charge through a network of logic gates. This information is then stored, most commonly, by encoding it in the orientation of magnetic domains of a computer hard disk. The key obstacle to a more intimate integration of magnetic materials into devices and circuit processing information is a lack of efficient means to control their magnetization. This is usually achieved with an external magnetic field or by the injection of…
Near-field microwave microscopy has created the opportunity for a new class of electrodynamics experiments of materials. Freed from the constraints of traditional microwave optics, experiments can be carried out at high spatial resolution over a broad frequency range. In addition, the measurements can be done quantitatively so that images of microwave materials properties can be created. We review the five major types of near-field microwave microscopes and discuss our own form of microscopy in detail. Quantitative images of microwave sheet resistance, dielectric constant, and dielectric tunab…
We explore the application of computer vision and machine learning (ML) techniques to predict material properties (e.g. compressive strength) based on SEM images. We show that it's possible to train ML models to predict materials performance based on SEM images alone, demonstrating this capability on the real-world problem of predicting uniaxially compressed peak stress of consolidated molecular solids samples. Our image-based ML approach reduces mean absolute percent error (MAPE) by an average of 24% over baselines representative of the current state-of-the-practice (i.e., domain-expert's ana…
