Layer VQE: A Variational Approach for Combinatorial Optimization on Noisy Quantum Computers-Reference-Cited by-同舟云学术

Layer VQE: A Variational Approach for Combinatorial Optimization on Noisy Quantum Computers

Published:2022 Issue: Volume:3 Page:1-20
ISSN:2689-1808
Container-title:IEEE Transactions on Quantum Engineering
language:
Short-container-title:IEEE Trans. Quantum Eng.

Author:

Liu Xiaoyuan¹^ORCID,Angone Anthony²,Shaydulin Ruslan³^ORCID,Safro Ilya¹^ORCID,Alexeev Yuri⁴^ORCID,Cincio Lukasz⁵^ORCID

Affiliation:

1. Department of Computer and Information Sciences, University of Delaware, Newark, DE, USA

2. School of Computing, Clemson University, Clemson, SC, USA

3. Mathematics and Computer Science Division, Argonne National Laboratory, Lemont, IL, USA

4. Computational Science Division, Argonne National Laboratory, Lemont, IL, USA

5. Theoretical Division, Los Alamos National Laboratory, Los Alamos, NM, USA

Funder

Defense Advanced Research Projects Agency

Laboratory Directed Research and Development

Argonne National Laboratory

Office of Science

U.S. Department of Energy

Office of Advanced Scientific Computing Research

Accelerated Research for Quantum Computing program

Laboratory Directed Research and Development program of Los Alamos National Laboratory

U.S. DOE

Accelerated Research in Quantum Computing program

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Science Applications,Mechanical Engineering,Engineering (miscellaneous),Condensed Matter Physics,Computer Science (miscellaneous),Software

Link

https://ieeexplore.ieee.org/ielam/8924785/9669178/9669165-aam.pdf

Reference80 articles.

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3. Qiskit: An open-source framework for quantum computing,2019

4. A practical introduction to tensor networks: Matrix product states and projected entangled pair states

5. libEnsemble users manual;hudson,2019

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