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Hernán Indíbil de la Cruz Calvo, Fernando Cuartero Gómez, José Javier Paulet González, Mauro Mezzini et al. • Mathematics
(2023)
In simulating Quantum Computing by using the circuit model the size of the matrices to deal with, together with the number of products and additions required to apply every quantum gate becomes a really hard computational restriction. This ...
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Open Access (DOAJ)
DOI: 10.3390/math11173742
Raviraju Balappa D, Gautam Kumar Rajput • Shodh Sari
(2025)
Matrices are foundational to artificial intelligence (AI), serving as critical tools for data representation, manipulation, and transformation across various applications. From machine learning algorithms to neural network architectures, ma...
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Open Access (DOAJ)
DOI: https://doi.org/10.59231/SARI7840
Hiroomi Chono, Hayato Goto • APL Quantum
(2025)
Kerr parametric oscillators (KPOs), two-photon driven Kerr-nonlinear resonators, can stably hold coherent states with opposite-sign amplitudes and are promising devices for quantum computing. Recently, we have theoretically proposed a two-q...
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Open Access (DOAJ)
DOI: 10.1063/5.0241996
Adam Callison, Nicholas Chancellor, Florian Mintert, Viv Kendon • New Journal of Physics
(2019)
Quantum computation using continuous-time evolution under a natural hardware Hamiltonian is a promising near- and mid-term direction toward powerful quantum computing hardware. We investigate the performance of continuous-time quantum walks...
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Open Access (DOAJ)
DOI: 10.1088/1367-2630/ab5ca2
Alberto Di Meglio, Karl Jansen, Ivano Tavernelli, Constantia Alexandrou et al. • PRX Quantum
(2024)
Quantum computers offer an intriguing path for a paradigmatic change of computing in the natural sciences and beyond, with the potential for achieving a so-called quantum advantage—namely, a significant (in some cases exponential) speedup o...
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DOI: https://doi.org/10.1103/prxquantum.5.037001
Scott Aaronson • Physical Review A
(2005)
This paper initiates the study of hidden variables from a quantum computing perspective. For us, a hidden-variable theory is simply a way to convert a unitary matrix that maps one quantum state to another into a stochastic matrix that maps ...
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Open Access
DOI: https://doi.org/10.1103/physreva.71.032325
Sayaki Matsushita • IEEE Transactions on Quantum Engineering
(2026)
Linear regression is fundamental to statistical analysis and machine learning, but its application to large-scale datasets necessitates distributed computing. The problem also arises in quantum computing, where handling extensive data requi...
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Open Access (DOAJ)
DOI: 10.1109/TQE.2026.3687237
Fei Yan, Abdullah M. Iliyasu, Sihao Jiao, Huamin Yang • Applied Sciences
(2019)
Utilising the properties of quantum mechanics, i.e., entanglement, parallelism, etc., a quantum structure is proposed for representing and manipulating emotion space of robots. This quantum emotion space (QES) provides a mechanism to extend...
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Open Access (DOAJ)
DOI: 10.3390/app9163351
Kyle Lee, Shuvro Chowdhury, Kerem Y. Camsari • Communications Physics
(2025)
Abstract Ising machines are hardware accelerators for combinatorial optimization and probabilistic sampling, using stochasticity to explore spin configurations and avoid local minima. We refine the previously proposed coupled chaotic bits (...
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Open Access (DOAJ)
DOI: 10.1038/s42005-025-01945-1
Ruofan Chen, Xiansong Xu, Chu Guo • New Journal of Physics
(2024)
Tensor-network-based methods are promising candidates to solve quantum impurity problems (QIP). They are free of sampling noises and the sign problem compared to state-of-the-art continuous-time quantum Monte Carlo methods. Recent progress ...
DOAJ
Open Access (DOAJ)
DOI: 10.1088/1367-2630/ad19fa
Ziqiang Wang, Jing Zhang, Huili Chen, Xinyu Zhang et al. • Frontiers in Immunology
(2025)
BackgroundM2-like tumor-associated macrophages (TAMs) promote an immunosuppressive microenvironment and contribute to tumor progression and metastasis. However, their molecular characterization and prognostic value have not been fully explo...
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Open Access (DOAJ)
DOI: 10.3389/fimmu.2025.1650726
Jr-Shin Li, Justin Ruths, Steffen J. Glaser • Nature Communications
(2017)
Coherent control of two-level systems is crucial for achieving fidelity in spectroscopy and quantum computing, but inherent nonlinearities and parameter variation have, to date, required an approximate, numerical approach. Here, Li et al. s...
DOAJ
Open Access (DOAJ)
DOI: 10.1038/s41467-017-00441-7
J.M. Clemente-Juan, Eugenio Coronado, Alejandro Gaita‐Ariño • Chemical Society Reviews
(2012)
In this review we discuss the relevance of polyoxometalate (POM) chemistry to provide model objects in molecular magnetism. We present several potential applications in nanomagnetism, in particular, in molecular spintronics and quantum comp...
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DOI: https://doi.org/10.1039/c2cs35205b
Stefano Mangini, Francesco Tacchino, Dario Gerace, Daniele Bajoni et al. • Europhysics Letters (EPL)
(2021)
Abstract Neural networks are computing models that have been leading progress in Machine Learning (ML) and Artificial Intelligence (AI) applications. In parallel, the first small-scale quantum computing devices have become available in rece...
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Open Access
DOI: https://doi.org/10.1209/0295-5075/134/10002
Dan Cristian Marinescu, Gabriela M. Marinescu (2005)
1 Preface 2 Introduction 2.1 Computing and the Laws of Physics 2.2 Quantum Information 2.3 Quantum Computers 2.4 The Wave and the Corpuscular Nature of Light 2.5 Deterministic versus Probabilistic Photon Behavior 2.6 State Description, Supe...
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Cristian S. Calude, Michael J. Dinneen, Karl Svozil • Complexity
(2000)
In this rather speculative note three problems pertaining to the power and limits of quantum computing are posed and partially answered: (a) when are quantum speedups possible? (b) is fixed-point computing a better model for quantum computi...
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DOI: https://doi.org/10.1002/1099-0526(200009/10)6:1<35::aid-cplx1005>3.0.co;2-t
Andris Ambainis, Abuzer Yakaryılmaz • EMS Press eBooks
(2021)
Quantum computing is a new model of computation, based on quantum physics. Quantum computers can be exponentially faster than conventional computers for problems such as factoring. Besides full-scale quantum computers, more restricted model...
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DOI: https://doi.org/10.4171/automata-2/17
Andris Ambainis, Abuzer Yakaryılmaz • arXiv (Cornell University)
(2015)
Quantum computing is a new model of computation, based on quantum physics. Quantum computers can be exponentially faster than conventional computers for problems such as factoring. Besides full-scale quantum computers, more restricted model...
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Open Access
DOI: https://doi.org/10.48550/arxiv.1507.01988
Jeffery C. Atik, Valentin Jeutner • Law Innovation and Technology
(2019)
Quantum computing technology will greatly enhance the abilities of the emerging field of computational law to express, model, and operationalise law in algorithmic form. Foreshadowing the harnessing of the power of quantum computing technol...
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DOI: https://doi.org/10.1080/17579961.2021.1977216
Bertrand Georgeot, Dima L. Shepelyansky • Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics
(2000)
We study a generic model of quantum computer, composed of many qubits coupled by short-range interaction. Above a critical interqubit coupling strength, quantum chaos sets in, leading to quantum ergodicity of the computer eigenstates. In th...
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Open Access
DOI: https://doi.org/10.1103/physreve.62.3504