arXiv subjects

Georgy Samsonidze

Publications and source records attributed to Georgy Samsonidze.

11 recordsLinked to original sources

arXiv2024

OnionVQE Optimization Strategy for Ground State Preparation on NISQ Devices

The Variational Quantum Eigensolver (VQE) is one of the most promising and widely used algorithms for exploiting the capabilities of current Noisy Intermediate-Scale Quantum (NISQ) devices. However, VQE algorithms suffer from a plethora of issues, such as barren plateaus, local minima, quantum hardware noise, and limited qubit connectivity, thus posing challenges for their successful deployment on hardware and simulators. In this work, we propose a VQE optimization strategy that builds upon recent advances in the literature, and exhibits very shallow circuit depths when applied to the specific system of interest, namely a model Hamiltonian representing a cuprate superconductor. These features make our approach a favorable candidate for generating good ground state approximations on current NISQ devices. Our findings illustrate the potential of VQE algorithmic development for leveraging the full capabilities of NISQ devices.

quant-ph↗

arXiv2024

Dynamical Mean Field Theory for Real Materials on a Quantum Computer

Quantum computers (QC) could harbor the potential to significantly advance materials simulations, particularly at the atomistic scale involving strongly correlated fermionic systems where an accurate description of quantum many-body effects scales unfavorably with size. While a full-scale treatment of condensed matter systems with currently available noisy quantum computers remains elusive, quantum embedding schemes like dynamical mean-field theory (DMFT) allow the mapping of an effective, reduced subspace Hamiltonian to available devices to improve the accuracy of ab initio calculations such as density functional theory (DFT). Here, we report on the development of a hybrid quantum-classical DFT+DMFT simulation framework which relies on a quantum impurity solver based on the Lehmann representation of the impurity Green's function. Hardware experiments with up to 14 qubits on the IBM Quantum system are conducted, using advanced error mitigation methods and a novel calibration scheme for an improved zero-noise extrapolation to effectively reduce adverse effects from inherent noise on current quantum devices. We showcase the utility of our quantum DFT+DMFT workflow by assessing the correlation effects on the electronic structure of a real material, Ca2CuO2Cl2, and by carefully benchmarking our quantum results with respect to exact reference solutions and experimental spectroscopy measurements.

cond-mat.str-el↗

arXiv2023

Quantum-centric Supercomputing for Materials Science: A Perspective on Challenges and Future Directions

Computational models are an essential tool for the design, characterization, and discovery of novel materials. Hard computational tasks in materials science stretch the limits of existing high-performance supercomputing centers, consuming much of their simulation, analysis, and data resources. Quantum computing, on the other hand, is an emerging technology with the potential to accelerate many of the computational tasks needed for materials science. In order to do that, the quantum technology must interact with conventional high-performance computing in several ways: approximate results validation, identification of hard problems, and synergies in quantum-centric supercomputing. In this paper, we provide a perspective on how quantum-centric supercomputing can help address critical computational problems in materials science, the challenges to face in order to solve representative use cases, and new suggested directions.

quant-ph↗

arXiv2023

Quantum-enhanced quantum Monte Carlo: an industrial view

In this work, we test a recently developed method to enhance classical auxiliary-field quantum Monte Carlo (AFQMC) calculations with quantum computers against examples from chemistry and material science, representatives of classes of industry-relevant systems. As molecular test cases, we calculate the energy curve of H4 and relative energies of ozone and singlet molecular oxygen with respect to triplet molecular oxygen, which are industrially relevant in organic oxidation reactions. We find that trial wave functions beyond single Slater determinants improve the performance of AFQMC and allow to generate energies close to chemical accuracy compared to full configuration interaction (FCI) or experimental results. As a representative for material science we study a quasi-1D Fermi-Hubbard model derived from CuBr2, a compound displaying electronic structure properties analogous to cuprates. We find that trial wave functions with both, significantly larger fidelities and lower energies over a Hartree-Fock solution, do not necessarily lead to better AFQMC results.

quant-ph↗

arXiv2019

Fast Neural Network Approach for Direct Covariant Forces Prediction in Complex Multi-Element Extended Systems

Neural network force field (NNFF) is a method for performing regression on atomic structure-force relationships, bypassing expensive quantum mechanics calculation which prevents the execution of long ab-initio quality molecular dynamics simulations. However, most NNFF methods for complex multi-element atomic systems indirectly predict atomic force vectors by exploiting just atomic structure rotation-invariant features and the network-feature spatial derivatives which are computationally expensive. We develop a staggered NNFF architecture exploiting both rotation-invariant and covariant features separately to directly predict atomic force vectors without using spatial derivatives, thereby reducing expensive structural feature calculation by ~180-480x. This acceleration enables us to develop NNFF which directly predicts atomic forces in complex ternary and quaternary-element extended systems comprised of long polymer chains, amorphous oxide, and surface chemical reactions. The staggered rotation-invariant-covariant architecture described here can also directly predict complex covariant vector outputs from local physical structures in domains beyond computational material science.

physics.comp-ph↗

arXiv2018

Accelerated screening of thermoelectric materials by first-principles computations of electron-phonon scattering

Recent discovery of new materials for thermoelectric energy conversion is enabled by efficient prediction of materials' performance from first-principles, without empirically fitted parameters. The novel simplified approach for computing electronic transport properties is described, which achieves good accuracy and transferability while greatly reducing complexity and computation cost compared to the existing methods. The first-principles calculations of the electron-phonon coupling demonstrate that the energy dependence of the electron relaxation time varies significantly with chemical composition and carrier concentration, suggesting that it is necessary to go beyond the commonly used approximations to screen and optimize materials' composition, carrier concentration, and microstructure. The new method is verified using high accuracy computations and validated with experimental data before applying it to screen and discover promising compositions in the space of half-Heusler alloys. By analyzing data trends the effective electron mass is identified as the single best general descriptor determining material's performance. The Lorenz number is computed from first principles and the universality of the Wiedemann-Franz law in thermoelectrics is discussed.

cond-mat.mtrl-sci↗

arXiv2015

Electron-phonon-averaged approximation for first-principles computations of electron relaxation times and transport properties in semiconductor materials

We present a simple and efficient approximation to the electron-phonon scattering rate suitable for high-throughput screening of candidate materials for thermoelectric devices, based on electronic transport. The method is applied to calculate the electronic transport coefficients of half-Heusler compounds, showing agreement with experimental data. By directly computing electrical and the electronic part of the thermal conductivities, we find deviations from the Wiedemann-Franz law in these compounds at high temperatures and low carrier concentrations.

cond-mat.mtrl-sci↗

arXiv2014

Insights and challenges of applying the $GW$ method to transition metal oxides

The ab initio $GW$ method is considered as the most accurate approach for calculating the band gaps of semiconductors and insulators. Yet its application to transition metal oxides (TMOs) has been hindered by the failure of traditional approximations developed for conventional semiconductors. In this work, we examine the effects of these approximations on the values of band gaps for ZnO, Cu$_2$O, and TiO$_2$. In particular, we explore the origin of the differences between the two widely used plasmon-pole models. Based on the comparison of our results with the experimental data and previously published calculations, we discuss which approximations are suitable for TMOs and why.

cond-mat.mtrl-sci↗

arXiv2014

Electron-Phonon Interactions and the Intrinsic Electrical Resistivity of Graphene

We present a first-principles study of the temperature- and density-dependent intrinsic electrical resistivity of graphene. We use density-functional theory and density-functional perturbation theory together with very accurate Wannier interpolations to compute all electronic and vibrational properties and electron-phonon coupling matrix elements; the phonon-limited resistivity is then calculated within a Boltzmann-transport approach. An effective tight-binding model, validated against first-principles results, is also used to study the role of electron-electron interactions at the level of many-body perturbation theory. The results found are in excellent agreement with recent experimental data on graphene samples at high carrier densities and elucidate the role of the different phonon modes in limiting electron mobility. Moreover, we find that the resistivity arising from scattering with transverse acoustic phonons is 2.5 times higher than that from longitudinal acoustic phonons. Last, high-energy, optical, and zone-boundary phonons contribute as much as acoustic phonons to the intrinsic electrical resistivity even at room temperature and become dominant at higher temperatures.

cond-mat.mtrl-sci↗

arXiv2012

BerkeleyGW: A Massively Parallel Computer Package for the Calculation of the Quasiparticle and Optical Properties of Materials and Nanostructures

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 10,000's of CPUs and can be used to study systems containing up to 100's of atoms.

cond-mat.mtrl-sci↗

arXiv2012

Coulomb-hole summations and energies for GW calculations with limited number of empty orbitals: a modified static remainder approach

Ab initio GW calculations are a standard method for computing the spectroscopic properties of many materials. The most computationally expensive part in conventional implementations of the method is the generation and summation over the large number of empty orbitals required to converge the electron self energy. We propose a scheme to reduce the summation over empty states by the use of a modified static-remainder approximation, which is simple to implement and yields accurate self energies for both bulk and molecular systems requiring a small fraction of the typical number of empty orbitals.

cond-mat.mtrl-sci↗