Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Log inSign up
Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Blog
Job Board
Q3AS

© 2026 Aqora Quantum S.A.S.

TermsPrivacyLegal Notice

arXiv:2211.13355 · Springer eBooks

Software for Massively Parallel Quantum Computing

Thien Nguyen, Daanish Arya, Marcus W. Doherty, Nils Herrmann, Johannes Kuhlmann, Florian Preis, Pat Scott, Simon Yin

Published Aug 7, 2023• 6 citations
arXivHTMLPDF
DOI
10.1007/978-3-031-37966-6_6

Related papers

Massively parallel quantum computer simulator

Koen De Raedt, Kristel F. L. Michielsen, Hans A. De Raedt +6 more

arXiv:quant-ph/0608239•Computer Physics Communications•Dec 16, 2006•213 citations

Massively Parallel Quantum Computer Simulations: Towards Realistic Systems

Mark Richter, Binh Trieu, G. W. Arnold +1 more

•Jan 1, 2007•5 citations

Quantum Software Engineering Supremacy in Intelligent Robotics

V. Korenkov, Andrey G. Reshetnikov, Sergey Victorovich Ulyanov

A new approach to a circuit implementation design of quantum algorithmic gates for the realization of quantum massive parallel computing presented. The main attention focused on the development of design method of fast quantum algorithm operators as superposition, entanglement and interference which are in general time-consuming operations due to the number of products that have to be performed. SW&HW support toolkit of supercomputing accelerator of quantum algorithm simulation on classical computer described. The method for performing Grover's interference without product operations introduced. New quantum genetic and quantum fuzzy inference algorithm gate design for intelligent robotic control considered. Quantum software engineering supremacy on Benchmarks demonstrated.

Modern Network technologies•Oct 27, 2020•5 citations

Software for Quantum Computation

Daniel Herr

•Mar 1, 2019•0 citations

Massively Parallel Tensor Network State Algorithms on Hybrid CPU-GPU Based Architectures

Andor Menczer, Örs Legeza

High Resolution Image Download MS PowerPoint Slide The interplay of quantum and classical simulation and the delicate divide between them is in the focus of massively parallelized tensor network state (TNS) algorithms designed for high performance computing (HPC). In this contribution, we present novel algorithmic solutions together with implementation details to extend current limits of TNS algorithms on HPC infrastructure building on state-of-the-art hardware and software technologies. Benchmark results obtained via large-scale density matrix renormalization group (DMRG) simulations on single node multiGPU NVIDIA A100 system are presented for selected strongly correlated molecular systems addressing problems on Hilbert space dimensions up to 4.17 × 10 35 .

arXiv:2305.05581•Journal of Chemical Theory and Computation•Feb 4, 2025•10 citations

Parallel Environment for Quantum Computing

Frank Tabakin A, Bruno Julia Diaz

Bulletin of the American Physical Society•Mar 19, 2009•0 citations
A new approach to a circuit implementation design of quantum algorithmic gates for the realization of quantum massive parallel computing presented. The main attention focused on the development of design method of fast quantum algorithm operators as superposition, entanglement and interference which are in general time-consuming operations due to the number of products that have to be performed. SW&HW support toolkit of supercomputing accelerator of quantum algorithm simulation on classical computer described. The method for performing Grover's interference without product operations introduced. New quantum genetic and quantum fuzzy inference algorithm gate design for intelligent robotic control considered. Quantum software engineering supremacy on Benchmarks demonstrated.
High Resolution Image Download MS PowerPoint Slide The interplay of quantum and classical simulation and the delicate divide between them is in the focus of massively parallelized tensor network state (TNS) algorithms designed for high performance computing (HPC). In this contribution, we present novel algorithmic solutions together with implementation details to extend current limits of TNS algorithms on HPC infrastructure building on state-of-the-art hardware and software technologies. Benchmark results obtained via large-scale density matrix renormalization group (DMRG) simulations on single node multiGPU NVIDIA A100 system are presented for selected strongly correlated molecular systems addressing problems on Hilbert space dimensions up to 4.17 × 10 35 .