Results 71 to 80 of about 2,386 (159)

Leveraging Quantum Annealing for Layout Optimization

Advanced Quantum Technologies, Volume 8, Issue 11, November 2025.
The authors address wind farm layout optimization by formulating it as a QUBO problem using the Jensen wake model. They compare quantum annealing, Gurobi, and QAOA, highlighting trade‐offs between solution quality and computational time. Results show that quantum annealing offers rapid, near‐optimal solutions, making it suitable for fast approximations
Luca Nigro, Simone Sala, Alfonso Amendola, Enrico Prati   +3 more
wiley   +1 more source

Limitations of quantum approximate optimization in solving generic higher-order constraint-satisfaction problems

Physical Review Research
The ability of the quantum approximate optimization algorithm (QAOA) to deliver a quantum advantage on combinatorial optimization problems is still unclear. Recently, a scaling advantage over a classical solver was postulated to exist for random 8-SAT at
Thorge Müller, Ajainderpal Singh, Frank K. Wilhelm, Tim Bode   +3 more
doaj   +1 more source

On the Use of the Quantum Alternating Operator Ansatz in Quantum-Informed Recursive Optimization: A Case Study on the Minimum Vertex Cover

AppliedMath
In recent years, several quantum algorithms have been proposed for addressing combinatorial optimization problems. Among them, the Quantum Approximate Optimization Algorithm (QAOA) has become a widely used approach.
Pablo Ramos-Ruiz, Antonio Miguel Fuentes-Jiménez, José E. Ramos-Ruiz, Inmaculada Jiménez-Manchado   +3 more
doaj   +1 more source

Quantum Algorithm Implementations for Beginners

, 2020
As quantum computers become available to the general public, the need has arisen to train a cohort of quantum programmers, many of whom have been developing classical computer programs for most of their careers.
Adedoyin, Adetokunbo, Ambrosiano, John, Anisimov, Petr, Bärtschi, Andreas, Casper, William, Chennupati, Gopinath, Coffrin, Carleton, Coles, Patrick J., Djidjev, Hristo, Eidenbenz, Stephan, Gunter, David, J., Abhijith, Karra, Satish, Lemons, Nathan, Lin, Shizeng, Lokhov, Andrey Y., Malyzhenkov, Alexander, Mascarenas, David, Mniszewski, Susan, Nadiga, Balu, O'Malley, Daniel, Oyen, Diane, Pakin, Scott, Prasad, Lakshman, Roberts, Randy, Romero, Phillip, Santhi, Nandakishore, Sinitsyn, Nikolai, Swart, Pieter J., Vuffray, Marc, Wendelberger, James G., Yoon, Boram, Zamora, Richard, Zhu, Wei   +33 more
core  

Quantum machine learning [PDF]

, 2019
We use reinforcement learning techniques to optimize the Quantum Approximate Optimization Algorithm when applied to the MaxCut problem. We explore Q-learning based techniques both for continuous and discrete action environments with regular and irregular
Riu I Vicente, Jordi
core  

Q‐fid: Quantum Circuit Fidelity Improvement with LSTM Networks

Advanced Quantum Technologies, Volume 8, Issue 10, October 2025.
Q‐fid is introduced, an LSTM‐based fidelity prediction system accompanied by a novel metric designed to quantify the fidelity of quantum circuits. This approach frames fidelity prediction as a Time Series Forecasting problem to analyze the tokenized circuits, capturing the causal dependence of the gate sequences and their impact on overall fidelity ...
Yikai Mao, Shaswot Shresthamali, Masaaki Kondo   +2 more
wiley   +1 more source

Improving Quantum Approximate Optimization by Noise-Directed Adaptive Remapping [PDF]

Quantum
We present Noise-Directed Adaptive Remapping (NDAR), a heuristic algorithm for approximately solving binary optimization problems by leveraging certain types of noise.
Filip B. Maciejewski, Jacob Biamonte, Stuart Hadfield, Davide Venturelli   +3 more
doaj   +1 more source

Quantum Computing in Industrial Internet of Things (IIoT) Forensics: Framework, Implications, Opportunities, and Future Directions

WIREs Forensic Science, Volume 7, Issue 3, September 2025.
Generic Quantum‐Safe IIoT Forensics Framework (QS‐IIoT‐F) ABSTRACT The continuous evolution of quantum computing has shown novel and transformative possibilities and critical implications for the Industrial Internet of Things (IIoT) forensic processes.
Victor R. Kebande
wiley   +1 more source

Adam assisted Fully informed Particle Swarm Optimization ( Adam-FIPSO ) based Parameter Prediction for the Quantum Approximate Optimization Algorithm (QAOA)

The Quantum Approximate Optimization Algorithm (QAOA) is a prominent variational algorithm used for solving combinatorial optimization problems such as the Max-Cut problem. A key challenge in QAOA lies in efficiently identifying suitable parameters (gamma, beta) that lead to high-quality solutions.
Bhat, Shashank Sanjay, Wang, Peiyong, Parampalli, Udaya   +2 more
openaire   +2 more sources

Quantum Computing: Foundations, Architecture and Applications

Engineering Reports, Volume 7, Issue 8, August 2025.
This paper presents a study on quantum computing's theoretical foundations and applications, illustrated by a quantum circuit diagram featuring gates and measurements that demonstrate qubit manipulation and entanglement. ABSTRACT Quantum computing exploits the principles of quantum mechanics to address computational problems that are intractable to ...
Christopher Columbus Chinnappan, Palani Thanaraj Krishnan, Elakiya Elamaran, Rajakumar Arul, T. Sunil Kumar   +4 more
wiley   +1 more source