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Quantum Approximate Optimization Algorithm (QAOA) is a promising hybrid quantum-classical algorithm for solving combinatorial optimization problems. However, it cannot overcome qubit limitation for large-scale problems. Furthermore, the…

Emerging Technologies · Computer Science 2021-03-01 Junde Li , Mahabubul Alam , Swaroop Ghosh

Code switching is an established technique that facilitates a universal set of FT quantum gate operations by combining two QEC codes with complementary sets of gates, which each by themselves are easy to implement fault-tolerantly. In this…

Quantum Physics · Physics 2025-09-10 Sascha Heußen , Janine Hilder

We present a new parallel PM N-body code named PMFAST that is freely available to the public. PMFAST is based on a two-level mesh gravity solver where the gravitational forces are separated into long and short range components. The…

Astrophysics · Physics 2007-05-23 Hugh Merz , Ue-Li Pen , Hy Trac

Sample-based quantum diagonalization (SQD) is a hybrid quantum-classical algorithm for estimating ground-state energies in electronic-structure calculations. It uses a quantum processor as a sampler to construct a variational subspace, with…

Quantum Physics · Physics 2026-04-21 Byeongyong Park , Sanha Kang , Jongseok Seo , Juhee Baek , Doyeol Ahn , Keunhong Jeong

Hybrid density functional theory (DFT) remains intractable for large periodic systems due to the demanding computational cost of exact exchange. We apply the tensor hypercontraction (THC) (or interpolative separable density fitting)…

Computational Physics · Physics 2023-10-13 Adam Rettig , Joonho Lee , Martin Head-Gordon

This article introduces a novel communication scheme, termed coded compressed sensing, for unsourced multiple-access communication. The proposed divide-and-conquer approach leverages recent advances in compressed sensing and forward error…

Signal Processing · Electrical Eng. & Systems 2019-06-26 Vamsi K. Amalladinne , Jean-Francois Chamberland , Krishna R. Narayanan

Sensing networks underpin applications from fundamental physics to real-world engineering. Recently, distributed quantum sensing (DQS) has been investigated to boost the sensing performance, yet current schemes typically rely on entangled…

Quantum Physics · Physics 2026-01-22 Binke Xia , Zhaotong Cui , Jingzheng Huang , Yuxiang Yang , Guihua Zeng

Simulations of galaxy formation follow the gravitational and hydrodynamical interactions between gas, stars and dark matter through cosmic time. The huge dynamic range of such calculations severely limits strong scaling behaviour of the…

Instrumentation and Methods for Astrophysics · Physics 2015-08-04 Tom Theuns , Aidan Chalk , Matthieu Schaller , Pedro Gonnet

Density functional theory (DFT) stands as a cornerstone method in computational quantum chemistry and materials science due to its remarkable versatility and scalability. Yet, it suffers from limitations in accuracy, particularly when…

We present an algorithm to solve very large one-dimensional disordered and interacting few-particle systems. Our approach exploits the localized nature of the eigenfunctions in real space to achieve a linear scaling with the total system…

Disordered Systems and Neural Networks · Physics 2022-11-24 Lluís Hernández-Mulà , Andreas M. Läuchli

Stochastic and mixed stochastic-deterministic density functional theory (DFT) are promising new approaches for the calculation of the equation-of-state and transport properties in materials under extreme conditions. In the intermediate warm…

Computational Physics · Physics 2023-09-27 Vidushi Sharma , Lee A. Collins , Alexander J. White

Nonequispaced discrete Fourier transformation (NDFT) is widely applied in all aspects of computational science and engineering. The computational efficiency and accuracy of NDFT has always been a critical issue in hindering its…

Mathematical Software · Computer Science 2020-08-06 Sheng-Chun Yang , Yong-Lei Wang

We present an approach to the DFT+U method (Density Functional Theory + Hubbard model) within which the computational effort for calculation of ground state energies and forces scales linearly with system size. We employ a formulation of…

Strongly Correlated Electrons · Physics 2012-02-14 David D. O'Regan , Nicholas D. M. Hine , Mike C. Payne , Arash A. Mostofi

We present the Tucker tensor DFT (TTDFT) code which uses a tensor-structured algorithm with graphic processing unit (GPU) acceleration for conducting ground-state DFT calculations on large-scale systems. The Tucker tensor DFT algorithm uses…

Computational Physics · Physics 2021-11-01 Chih-Chuen Lin , Vikram Gavini

Simulation of quantum computing on supercomputers is a significant research topic, which plays a vital role in quantum algorithm verification, error-tolerant verification and other applications. Tensor network contraction based on density…

The complexity of quantum many-body problems scales exponentially with the size of the system, rendering any finite size scaling analysis a formidable challenge. This is particularly true for methods based on the full representation of the…

Strongly Correlated Electrons · Physics 2025-02-19 Robin Schäfer , David J. Luitz

We present a modification of the $\Delta$SCF method of calculating energies of excited states, in order to make it applicable to resonance calculations of molecules adsorbed on metal surfaces, where the molecular orbitals are highly…

Materials Science · Physics 2009-03-06 Jeppe Gavnholt , Thomas Olsen , Mads Engelund , Jakob Schiøtz

We present an efficient post-processing method for calculating the electronic structure of nanosystems based on the divide-and-conquer approach to density functional theory (DC-DFT), in which a system is divided into subsystems whose…

Materials Science · Physics 2017-01-06 Shunsuke Yamada , Fuyuki Shimojo , Ryosuke Akashi , Shinji Tsuneyuki

The performance of distributing entanglement between two distant nodes in a large-scale quantum network (QN) of partially entangled bipartite pure states is generally benchmarked against the classical entanglement percolation (CEP) scheme.…

Quantum Physics · Physics 2023-06-05 Xiangyi Meng , Yulong Cui , Jianxi Gao , Shlomo Havlin , Andrei E. Ruckenstein

In this work, we derive particle schemes, based on micro-macro decomposition, for linear kinetic equations in the diffusion limit. Due to the particle approximation of the micro part, a splitting between the transport and the collision part…

Numerical Analysis · Mathematics 2017-01-19 Anaïs Crestetto , Nicolas Crouseilles , Mohammed Lemou
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