Results 61 to 70 of about 74,156 (167)

Quantum Approximate Optimization With Parallelizable Gates

IEEE Transactions on Quantum Engineering, 2020
The quantum approximate optimization algorithm (QAOA) has been introduced as a heuristic digital quantum computing scheme to find approximate solutions of combinatorial optimization problems. We present a scheme to parallelize this approach for arbitrary
Wolfgang Lechner
doaj   +1 more source

Multi-target quantum compilation algorithm

Machine Learning: Science and Technology
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 state preparation,
Vu Tuan Hai, Nguyen Tan Viet, Jesus Urbaneja, Nguyen Vu Linh, Lan Nguyen Tran, Le Bin Ho   +5 more
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A Hybrid Deep Learning and Quantum Optimization Framework for Ransomware Response in Healthcare

IEEE Open Journal of the Computer Society
Ransomware poses a growing threat to healthcare systems, compromising patient safety, operational continuity, and financial stability. Although machine learning techniques have been widely used for intrusion detection, most approaches do not support real-
Ahsan Ahmed, Md Aktarujjaman, Mohammad Moniruzzaman, Md Shahab Uddin, Arifa Akter Eva, M. F. Mridha, Kyoungyee Kim, Jungpil Shin   +7 more
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Quantum circuit optimization with AlphaTensor

Nature Machine Intelligence
A key challenge in realizing fault-tolerant quantum computers is circuit optimization. Focusing on the most expensive gates in fault-tolerant quantum computation (namely, the T gates), we address the problem of T-count optimization, i.e., minimizing the number of T gates that are needed to implement a given circuit.
Francisco J. R. Ruiz, Tuomas Laakkonen, Johannes Bausch, Matej Balog, Mohammadamin Barekatain, Francisco J. H. Heras, Alexander Novikov 0001, Nathan Fitzpatrick, Bernardino Romera-Paredes, John van de Wetering, Alhussein Fawzi, Konstantinos Meichanetzidis, Pushmeet Kohli   +12 more
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Modeling Energy Communities: A Case Study of Quantum Approximate Optimization on a Superconducting Processor

IEEE Access
This work explores the use of variational quantum algorithms to optimize energy distribution among users in energy communities, using real data from a community lab.
Mateo Alonso, Guillermo Rubinos Rodriguez, Pablo Diez-Valle, Ana Garbayo, Xela Garcia-Santiago, Gonzalo Blazquez Gil   +5 more
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Introduction to Quantum Optimization

Proceedings of the Companion Conference on Genetic and Evolutionary Computation, 2023
Alberto Moraglio, Francisco Chicano
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Optimizing quantum optimization algorithms via faster quantum gradient computation [PDF]

, 2019
We consider a generic framework of optimization algorithms based on gradient descent. We develop a quantum algorithm that computes the gradient of a multi-variate real-valued function $f:\mathbb{R}^d\rightarrow \mathbb{R}$ by evaluating it at only a logarithmic number of points in superposition.
A.P. Gilyén (András), S. Arunachalam (Srinivasan), N. Wiebe (Nathan)   +2 more
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Thermodynamic significance of QUBO encoding on quantum annealers

New Journal of Physics
Quadratic unconstrained binary optimization (QUBO) is the standard interface to quantum annealers, yet a single constrained task admits many QUBO encodings whose penalty choices reshape the energy landscape experienced by hardware.
Emery Doucet, Zakaria Mzaouali, Reece Robertson, Bartłomiej Gardas, Sebastian Deffner, Krzysztof Domino   +5 more
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QuTIE: quantum optimization for target identification by enzymes. [PDF]

Bioinform Adv, 2023
Ngo HM, Thai MT, Kahveci T.
europepmc   +1 more source

Optimization by decoded quantum interferometry

Nature
80 pages, 15 ...
Stephen P. Jordan, Noah Shutty, Mary Wootters, Adam Zalcman, Alexander Schmidhuber, Robbie King, Sergei V. Isakov, Tanuj Khattar, Ryan Babbush   +8 more
openaire   +4 more sources