Recent Advances in Quantum Information

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Networks".

Deadline for manuscript submissions: 15 May 2026 | Viewed by 3423

Special Issue Editors

School of Intelligence Science and Engineering, Harbin Institute of Technology, Shenzhen 518055, China
Interests: quantum cybernetics; quantum information; quantum metrology

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Guest Editor
School of Integrated Circuits, Harbin Institute of Technology, Shenzhen 518055, China
Interests: silicon photonics; sensors; optical interconnects
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Guest Editor
College of Physics and Optoelectronic Engineering, Shenzhen University, Shenzhen 518060, China
Interests: quantum metrology; quantum control

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Guest Editor
School of Physics and Microelectronics Science, Hunan University, Changsha 410082, China
Interests: quantum metrology; quantum control; quantum sensing

Special Issue Information

Dear Colleagues,

Quantum information has seen remarkable progress in the past few decades, with advancements spanning from theoretical breakthroughs to practical applications. It continues to push the boundaries of what is computationally and communicatively possible, with potential implications for secure communication, advanced computing, and fundamental physics.

Over the years, there have been significant experimental advancements. For instance, the demonstration of entangled photon pairs from semiconductor quantum dots and the realization of quantum teleportation have been scientific milestones. There have also been significant strides in long-distance quantum communication, with experiments demonstrating entanglement distribution over increasingly long distances through optical fibers and via satellite links. Meanwhile, theoretical work continues to advance the field, including studies on coherent errors and their potential to drive error-correcting codes into high-magic states, which could be a resource for universal quantum computing. By adding superconductivity to semiconductor spin qubits, long-range coupling can be enabled, which is a crucial step towards building more sophisticated quantum computers. In addition, quantum information principles are being applied to enhance precision measurement and sensing, with quantum metrology surpassing classical limits.

The main purpose of this Special Issue is to reflect the important frontier research fields or the high-quality research in quantum information science and technology. We welcome contributions from academic institutions and industry to foster collaboration across disciplines. Prospective authors are invited to submit their review articles or original unpublished research papers. Topics of interest for this Special Issue include, but are not limited to, the following:

  • Quantum metrology;
  • Quantum communication;
  • Quantum computing;
  • Quantum information theory;
  • Quantum control;
  • Quantum teleportation;
  • Quantum cryptography;
  • Quantum algorithms;
  • Quantum machine intelligence.

Dr. Zibo Miao
Prof. Dr. Xiaochuan Xu
Dr. Hongzhen Chen
Dr. Liqiang Liu
Guest Editors

Manuscript Submission Information

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Keywords

  • quantum computing
  • quantum communication
  • quantum metrology
  • quantum control

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Published Papers (3 papers)

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Research

23 pages, 2960 KB  
Article
Analysis of Surface Code Algorithms on Quantum Hardware Using the Qrisp Framework
by Jan Krzyszkowski and Marcin Niemiec
Electronics 2025, 14(23), 4707; https://doi.org/10.3390/electronics14234707 - 29 Nov 2025
Viewed by 618
Abstract
The pursuit of scalable quantum computing is intrinsically limited by qubit decoherence, making robust quantum error correction (QEC) techniques crucial. As a leading solution, the topological surface code offers inherent protection against local noise. This study presents the first comprehensive implementation and quantitative [...] Read more.
The pursuit of scalable quantum computing is intrinsically limited by qubit decoherence, making robust quantum error correction (QEC) techniques crucial. As a leading solution, the topological surface code offers inherent protection against local noise. This study presents the first comprehensive implementation and quantitative characterization of a full surface code pipeline, which includes encompassing lattice construction, multi-round syndrome extraction, and MWPM decoding, using the high-level Qrisp programming framework. The entire pipeline was executed on IQM superconducting quantum processors to provide an empirical assessment under current noisy intermediate-scale quantum (NISQ) conditions. Our experimental data definitively show that the system operates significantly below the fault-tolerance threshold. Crucially, a quantitative resource analysis isolates and establishes the lack of native qubit reset on the hardware as the dominant architectural bottleneck. This constraint forces the physical qubit count to scale as d2+(d21)T, effectively preventing scaling to larger code distances (d) and execution times (T) on current devices. The work confirms Qrisp’s capability to support advanced QEC protocols, demonstrating that high-level abstraction can reduce implementation complexity by simplifying scheduling and mapping, thereby facilitating deeper experimental analysis of hardware limitations. Full article
(This article belongs to the Special Issue Recent Advances in Quantum Information)
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14 pages, 545 KB  
Article
QMProt: A Comprehensive Dataset of Quantum Properties for Proteins
by Laia Coronas Sala and Parfait Atchade-Adelomou
Electronics 2025, 14(14), 2825; https://doi.org/10.3390/electronics14142825 - 14 Jul 2025
Viewed by 1178
Abstract
We introduce Quantum Mechanics for Proteins (QMProt), a dataset developed to support quantum computing applications in protein research. QMProt contains precise quantum-mechanical and physicochemical data, enabling the accurate characterization of biomolecules and supporting advanced computational methods like molecular fragmentation and reassembly. The dataset [...] Read more.
We introduce Quantum Mechanics for Proteins (QMProt), a dataset developed to support quantum computing applications in protein research. QMProt contains precise quantum-mechanical and physicochemical data, enabling the accurate characterization of biomolecules and supporting advanced computational methods like molecular fragmentation and reassembly. The dataset includes 45 molecules covering all 20 essential human amino acids and their core structural elements: amino terminal groups, carboxyl terminal groups, alpha carbons, and unique side chains. QMProt primarily features organic molecules with up to 15 non-hydrogen atoms (C, N, O, S), offering comprehensive molecular Hamiltonians, ground state energies, and detailed physicochemical properties to enhance reproducibility and advance quantum simulations in molecular biology, biochemistry, and drug discovery. Full article
(This article belongs to the Special Issue Recent Advances in Quantum Information)
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21 pages, 1307 KB  
Article
A Quantum Strategy for the Simulation of Large Proteins: From Fragmentation in Small Proteins to Scalability in Complex Systems
by Parfait Atchade-Adelomou and Laia Coronas Sala
Electronics 2025, 14(13), 2601; https://doi.org/10.3390/electronics14132601 - 27 Jun 2025
Cited by 1 | Viewed by 826
Abstract
We present a scalable and resource-aware framework for the quantum simulation of large proteins, grounded in systematic molecular fragmentation, analytical Toffoli gate modeling, and empirical validation. The ground-state energy of a target biomolecule is reconstructed from capped amino acid fragments, with fixed corrections [...] Read more.
We present a scalable and resource-aware framework for the quantum simulation of large proteins, grounded in systematic molecular fragmentation, analytical Toffoli gate modeling, and empirical validation. The ground-state energy of a target biomolecule is reconstructed from capped amino acid fragments, with fixed corrections to account for artificial boundaries. Analytical cost estimates—derived from reduced Hamiltonians—are benchmarked against empirical Toffoli counts using PennyLane’s resource estimation module. Our model maintains predictive accuracy across biologically relevant systems of up to 1852 electrons, capturing consistent patterns across diverse fragments. This framework enables early-stage feasibility assessments for achieving quantum advantage in biochemical simulation pipelines. Full article
(This article belongs to the Special Issue Recent Advances in Quantum Information)
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