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Expressibility and trainability of parametrized analog quantum systems for machine learning applications

Jirawat Tangpanitanon, Supanut Thanasilp, Ninnat Dangniam, Marc-Antoine Lemonde et al. • Physical Review Research (2020)

Parametrized quantum evolution is the main ingredient in variational quantum algorithms for near-term quantum devices. In digital quantum computing, it has been shown that random parametrized quantum circuits are able to express complex dis...

DOAJ Open Access (DOAJ) DOI: 10.1103/PhysRevResearch.2.043364

Multi-target quantum compilation algorithm

Vu Tuan Hai, Nguyen Tan Viet, Jesus Urbaneja, Nguyen Vu Linh et al. • Machine Learning: Science and Technology (2024)

Quantum compilation is the process of converting a target unitary operation into a trainable unitary represented by a quantum circuit. It has a wide range of applications, including gate optimization, quantum-assisted compiling, quantum sta...

DOAJ Open Access (DOAJ) DOI: 10.1088/2632-2153/ad9705

Collective dynamics in holographic fractonic solids

Ling-Zheng Xia, Lixin Xu, Wei-Jia Li • Journal of High Energy Physics (2026)

Abstract Fractonic phases of matter, a class of states in which collective excitations with constrained mobility exist, were originally discovered in the study of quantum error-correcting codes in solvable lattice spin models such as Haah’s...

DOAJ Open Access (DOAJ) DOI: 10.1007/JHEP02(2026)089

Cyclic order superpositions enable quantum information transmission through completely depolarizing channels

Yaxin Wang, Linxiang Zhou, Tianfeng Feng, Hanlin Nie et al. • Communications Physics (2026)

Abstract Noise fundamentally limits quantum communication capacity, completely preventing information transmission in fully depolarizing environments. While indefinite causal order theoretically circumvents this limitation, experimentally r...

DOAJ Open Access (DOAJ) DOI: 10.1038/s42005-026-02698-1

Framework for Implementing Quantum Neural Networks in Wireless Communications

Salik Siddiqui, Justin Holzer, Joshua Malcarne, Galahad M. B. Wernsing et al. • IEEE Access (2025)

While quantum computing is already being employed in different domains to solve large scale and highly complex optimization problems, the wireless communications community has only recently begun exploring the potential of Quantum Machine L...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2025.3572416

An introduction to Bayesian simulation-based inference for quantum machine learning with examples

Ivana Nikoloska, Osvaldo Simeone • Frontiers in Quantum Science and Technology (2024)

Simulation is an indispensable tool in both engineering and the sciences. In simulation-based modeling, a parametric simulator is adopted as a mechanistic model of a physical system. The problem of designing algorithms that optimize the sim...

DOAJ Open Access (DOAJ) DOI: 10.3389/frqst.2024.1394533

Evolution of Quantum Computing: A Systematic Survey on the Use of Quantum Computing Tools

Paramita Basak Upama, Md Jobair Hossain Faruk, Mohammad Taneem Bin Nazim, Mohammad Masum et al. • IEEE Annual International Computer Software and Applications Conference (COMPSAC) (2022)

Quantum Computing (QC) refers to an emerging paradigm that inherits and builds with the concepts and phenomena of Quantum Mechanic (QM) with the significant potential to unlock a remarkable opportunity to solve complex and computationally i...

OPENALEX Open Access DOI: https://doi.org/10.1109/compsac54236.2022.00096

Quantum computing: an introduction

Tony Hey • Computing & Control Engineering Journal (1999)

The basic ideas of quantum computation are introduced by a brief discussion of Bennett (1973, 1982) and Fredkin's (1982, 1997) ideas of reversible computation. After some remarks about Deutsch's (1985) pioneering work on quantum complexity ...

OPENALEX Open Access DOI: https://doi.org/10.1049/cce:19990303

The future of quantum computing with superconducting qubits

Sergey B. Bravyi, Oliver Dial, Jay Gambetta, Darı́o Gil et al. • Journal of Applied Physics (2022)

For the first time in history, we are seeing a branching point in computing paradigms with the emergence of quantum processing units (QPUs). Extracting the full potential of computation and realizing quantum algorithms with a super-polynomi...

OPENALEX Open Access DOI: https://doi.org/10.1063/5.0082975

ℤ<sub>2</sub> × ℤ<sub>2</sub> Equivariant Quantum Neural Networks: Benchmarking against Classical Neural Networks

Zhongtian Dong, Marçal Comajoan Cara, Gopal Ramesh Dahale, Roy T. Forestano et al. • Axioms (2024)

This paper presents a comparative analysis of the performance of Equivariant Quantum Neural Networks (EQNNs) and Quantum Neural Networks (QNNs), juxtaposed against their classical counterparts: Equivariant Neural Networks (ENNs) and Deep Ne...

DOAJ Open Access (DOAJ) DOI: 10.3390/axioms13030188

A quantum fuzzy logic-enhanced evolutionary framework for energy-latency optimization in 6G Edge-IioT

Siavash Siavashian Rashidi, Ali Broumandnia, Abbas Mirzaei, Ramin Karimi • Scientific Reports (2026)

Abstract The transition toward 6G-enabled Industrial Internet of Things (IIoT) requires strict Ultra-Reliable Low-Latency Communication (URLLC), creating a fundamental trade-off with energy consumption. Orchestrating resources in dense, hyp...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41598-026-55177-6

Blind spots of randomized benchmarking under temporal correlations

Varun Srivastava, Abhinash Kumar Roy, Soumik Mahanti, Jasleen Kaur et al. • Physical Review Research (2026)

Randomized benchmarking (RB) is a widely adopted protocol for estimating the average gate fidelity in quantum hardware. However, its standard formulation relies on the assumption of temporally uncorrelated noise, an assumption often violate...

DOAJ Open Access (DOAJ) DOI: 10.1103/r1z5-ycqc

mRNA codon optimization with quantum computers.

Dillion M Fox, Kim M Branson, Ross C Walker • PLoS ONE (2021)

Reverse translation of polypeptide sequences to expressible mRNA constructs is a NP-hard combinatorial optimization problem. Each amino acid in the protein sequence can be represented by as many as six codons, and the process of selecting t...

DOAJ Open Access (DOAJ) DOI: 10.1371/journal.pone.0259101

Dynamics of superconducting qubit relaxation times

M. Carroll, S. Rosenblatt, P. Jurcevic, I. Lauer et al. • npj Quantum Information (2022)

Abstract Superconducting qubits are a leading candidate for quantum computing but display temporal fluctuations in their energy relaxation times T 1. This introduces instabilities in multi-qubit device performance. Furthermore, autocorrelat...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41534-022-00643-y