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Entropy
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Quantum Computing in the NISQ Era
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Quantum Computing in the NISQ Era

A special issue of Entropy (ISSN 1099-4300). This special issue belongs to the section "Quantum Information".

Deadline for manuscript submissions: 31 October 2024 | Viewed by 1538

Special Issue Editors

Dr. Xiao Yuan

E-Mail Website
Guest Editor
Center on Frontiers of Computing Studies, Peking University, Beijing 100871, China
Interests: quantum computing; quantum information; quantum resource theories
Dr. Xiaoming Zhang

E-Mail Website
Guest Editor
Center on Frontiers of Computing Studies, Peking University, Beijing 100871, China
Interests: quantum computing; quantum algorithms; quantum circuit; quantum control; quantum error mitigation; quantum machine learning
Dr. Bálint Koczor

E-Mail Website
Guest Editor
Department of Materials, University of Oxford, Oxford OX1 3PH, UK
Interests: quantum information theory; quantum physics; quantum computing; quantum algorithms; quantum error mitigation

Special Issue Information

Dear Colleagues,

Realizing a universal quantum computer is challenging with the current technology. Before having a fully fledged quantum computer, a more practical question is what we can do with current and near-term quantum hardware, i.e., the noisy-intermediate-scaled-quantum (NISQ) era. Leveraging the idea of hybrid quantum-classical computing, many works have shown the potential of NISQ devices in solving various tasks, such as in chemistry, materials, many-body physics, machine learning, etc. However, owing to the limitations of NISQ hardware, it remains an open problem to realize quantum advantages for practical problems over classical computation methods. On the other hand, new theoretical tools are being demanded for benchmarking the performance and power of NISQ devices, which typically have restricted number of qubits, gate fidelities and connectivity.

This Special Issue will focus on recent theoretical and experimental developments of quantum computing in the NISQ era. This Special Issue will accept unpublished original papers and comprehensive reviews focused on (but not restricted to) the following research areas:

  • Design of more efficient variational quantum algorithms;
  • Analysis of the performance of hybrid quantum-classical algorithms;
  • Theoretical tools for studying the expressivity of ansatz and trainability of variational quantum algorithms;
  • Applications of quantum algorithms for chemistry, materials, and other physics problems;
  • Applications of quantum algorithms in machine learning, combinatorial problems, and other problems beyond physics;
  • Quantum error mitigation;
  • Quantum error correction;
  • Benchmarking the performance and power of NISQ devices;
  • Experimental realization of variational quantum algorithms.

Dr. Xiao Yuan
Dr. Xiaoming Zhang
Dr. Bálint Koczor
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Entropy is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • quantum computing
  • noisy intermediate-scale quantum
  • variational quantum simulation
  • quantum computational chemistry
  • quantum materials
  • quantum error mitigation
  • quantum error correction

Published Papers (2 papers)

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Research

17 pages, 1472 KiB  
Article
Hybrid Classical–Quantum Branch-and-Bound Algorithm for Solving Integer Linear Problems
by Claudio Sanavio, Edoardo Tignone and Elisa Ercolessi
Entropy 2024, 26(4), 345; https://doi.org/10.3390/e26040345 - 19 Apr 2024
Viewed by 327
Abstract
Quantum annealers are suited to solve several logistic optimization problems expressed in the QUBO formulation. However, the solutions proposed by the quantum annealers are generally not optimal, as thermal noise and other disturbing effects arise when the number of qubits involved in the [...] Read more.
Quantum annealers are suited to solve several logistic optimization problems expressed in the QUBO formulation. However, the solutions proposed by the quantum annealers are generally not optimal, as thermal noise and other disturbing effects arise when the number of qubits involved in the calculation is too large. In order to deal with this issue, we propose the use of the classical branch-and-bound algorithm, that divides the problem into sub-problems which are described by a lower number of qubits. We analyze the performance of this method on two problems, the knapsack problem and the traveling salesman problem. Our results show the advantages of this method, that balances the number of steps that the algorithm has to make with the amount of error in the solution found by the quantum hardware that the user is willing to risk. The results are obtained using the commercially available quantum hardware D-Wave Advantage, and they outline the strategy for a practical application of the quantum annealers. Full article
(This article belongs to the Special Issue Quantum Computing in the NISQ Era)
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28 pages, 558 KiB  
Article
Leakage Benchmarking for Universal Gate Sets
by Bujiao Wu, Xiaoyang Wang, Xiao Yuan, Cupjin Huang and Jianxin Chen
Entropy 2024, 26(1), 71; https://doi.org/10.3390/e26010071 - 13 Jan 2024
Cited by 1 | Viewed by 791
Abstract
Errors are common issues in quantum computing platforms, among which leakage is one of the most-challenging to address. This is because leakage, i.e., the loss of information stored in the computational subspace to undesired subspaces in a larger Hilbert space, is more difficult [...] Read more.
Errors are common issues in quantum computing platforms, among which leakage is one of the most-challenging to address. This is because leakage, i.e., the loss of information stored in the computational subspace to undesired subspaces in a larger Hilbert space, is more difficult to detect and correct than errors that preserve the computational subspace. As a result, leakage presents a significant obstacle to the development of fault-tolerant quantum computation. In this paper, we propose an efficient and accurate benchmarking framework called leakage randomized benchmarking (LRB), for measuring leakage rates on multi-qubit quantum systems. Our approach is more insensitive to state preparation and measurement (SPAM) noise than existing leakage benchmarking protocols, requires fewer assumptions about the gate set itself, and can be used to benchmark multi-qubit leakages, which has not been achieved previously. We also extended the LRB protocol to an interleaved variant called interleaved LRB (iLRB), which can benchmark the average leakage rate of generic n-site quantum gates with reasonable noise assumptions. We demonstrate the iLRB protocol on benchmarking generic two-qubit gates realized using flux tuning and analyzed the behavior of iLRB under corresponding leakage models. Our numerical experiments showed good agreement with the theoretical estimations, indicating the feasibility of both the LRB and iLRB protocols. Full article
(This article belongs to the Special Issue Quantum Computing in the NISQ Era)
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