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Sample-based quantum diagonalization (SQD) constructs subspaces from computational-basis configurations obtained via measurements of a quantum state, with the goal of approximating low-energy eigenspaces of many-body Hamiltonians. The…

Quantum Physics · Physics 2026-05-07 Cedric Gaberle , Manpreet Singh Jattana

The accurate prediction of the electronic properties of materials at a low computational expense is a necessary conditions for the development of effective high-throughput quantum-mechanics (HTQM) frameworks for accelerated materials…

Strongly Correlated Electrons · Physics 2014-10-22 Luis A. Agapito , Stefano Curtarolo , Marco Buongiorno Nardelli

We present a digital quantum computation of two-hadron scattering in a $Z_2$ lattice gauge theory in 1+1 dimensions. We prepare well-separated single-particle wave packets with desired momentum-space wavefunctions, and simulate their…

Quantum Physics · Physics 2025-05-28 Zohreh Davoudi , Chung-Chun Hsieh , Saurabh V. Kadam

A finite electronic band gap is a standard filter in high-throughput screening of materials using density functional theory (DFT). However, because of the systematic underestimation of band gaps in standard DFT approximations, a number of…

Materials Science · Physics 2021-09-15 Kristian Berland , Ole Martin Løvvik , Rasmus Tranås

We present a comprehensive first-principles study of the electronic structure of 51 semiconducting monolayer transition metal dichalcogenides and -oxides in the 2H and 1T hexagonal phases. The quasiparticle (QP) band structures with…

Materials Science · Physics 2015-06-10 Filip Anselm Rasmussen , Kristian Sommer Thygesen

A framework for simulating the real-time dynamics of composite particles in a simple model of dense matter that is amenable to quantum computers is developed. As a demonstration, we perform classical simulations of heavy-hadrons propagating…

Quantum Physics · Physics 2025-01-22 Roland C. Farrell , Marc Illa , Martin J. Savage

We present a high-accuracy procedure for electronic structure calculations of strongly correlated materials. To address limitations in current electronic structure methods, we employ density functional theory in combination with the…

Quantum simulation of the electronic structure problem is one of the most researched applications of quantum computing. The majority of quantum algorithms for this problem encode the wavefunction using $N$ Gaussian orbitals, leading to…

Machine learning techniques are utilized to estimate the electronic band gap energy and forecast the band gap category of materials based on experimentally quantifiable properties. The determination of band gap energy is critical for…

Materials Science · Physics 2024-03-11 Sagar Prakash Barad , Sajag Kumar , Subhankar Mishra

We present a $GW$ space-time algorithm for periodic systems in a Gaussian basis including spin-orbit coupling. We employ lattice summation to compute the irreducible density response and the self-energy, while we employ $k$-point sampling…

The quantum simulation of real molecules and materials is one of the most highly anticipated applications of quantum computing. Algorithms for simulating electronic structure using a first-quantized plane wave representation are especially…

Quantum Physics · Physics 2025-01-22 William J. Huggins , Oskar Leimkuhler , Torin F. Stetina , K. Birgitta Whaley

Hybrid classical-quantum algorithms aim at variationally solving optimisation problems, using a feedback loop between a classical computer and a quantum co-processor, while benefitting from quantum resources. Here we present experiments…

In this report, we propose a novel quantum diagonalization algorithm based on the optimization of variational quantum circuits. Diagonalizing a quantum state is a fundamental yet computationally challenging task in quantum information…

Quantum Physics · Physics 2025-05-23 Juan Yao

Efficiently characterising quantum systems, verifying operations of quantum devices and validating underpinning physical models, are central challenges for the development of quantum technologies and for our continued understanding of…

At present, many laboratories are performing experiments to simulate theoretical models of strongly correlated systems using cold atoms in optical lattices, a program referred to as "Quantum Simulation". It is hoped that these experiments…

Superconductivity · Physics 2016-11-07 Tin-Lun Ho , Qi Zhou

A state-of-the-art method that combines a quantum computational algorithm and machine learning, so-called quantum machine learning, can be a powerful approach for solving quantum many-body problems. However, the research scope in the field…

Computational Physics · Physics 2023-04-04 Shu Kanno , Tomofumi Tada

Simulation of materials is one of the most promising applications of quantum computers. On near-term hardware the crucial constraint on these simulations is circuit depth. Many quantum simulation algorithms rely on a layer of unitary…

The last several decades have seen significant advances in the theoretical modeling of materials within the fields of solid-state physics and materials science, but many methods commonly applied to this problem struggle to capture strong…

Strongly Correlated Electrons · Physics 2025-04-07 Anna O. Schouten , Simon Ewing , David A. Mazziotti

Realistic simulation of quantum materials is a central goal of quantum computation. Although quantum processors have advanced rapidly in scale and fidelity, it has remained unclear whether pre-fault-tolerant devices can perform…

We present an approach based on density-functional theory for the calculation of fundamental gaps of both finite and periodic two-dimensional (2D) electronic systems. The computational cost of our approach is comparable to that of total…

Materials Science · Physics 2021-08-11 Alberto Guandalini , Alice Ruini , Esa Räsänen , Carlo Andrea Rozzi , Stefano Pittalis