Results 61 to 70 of about 2,321 (167)

Quantum dropout: On and over the hardness of quantum approximate optimization algorithm

Physical Review Research, 2023
A combinatorial optimization problem becomes very difficult in situations where the energy landscape is rugged, and the global minimum locates in a narrow region of the configuration space. When using the quantum approximate optimization algorithm (QAOA)
Zhenduo Wang (王朕铎), Pei-Lin Zheng, Biao Wu (吴飙), Yi Zhang   +3 more
doaj   +1 more source

QAOA-GPT: Efficient Generation of Adaptive and Regular Quantum Approximate Optimization Algorithm Circuits

Quantum computing has the potential to improve our ability to solve certain optimization problems that are computationally difficult for classical computers, by offering new algorithmic approaches that may provide speedups under specific conditions.
Tyagin, Ilya, Farag, Marwa H., Sherbert, Kyle, Shirali, Karunya, Alexeev, Yuri, Safro, Ilya   +5 more
openaire   +2 more sources

The Identification of Emerging Quantum Technologies in the Healthcare Sector: A Horizon Scanning Study

FUTURES &FORESIGHT SCIENCE, Volume 7, Issue 3, December 2025.
ABSTRACT Quantum technologies, driven by principles of quantum mechanics like superposition and entanglement, have shown transformative potential in drug discovery, medical diagnosis, precision medicine, and other therapeutic interventions. However, the research on emerging quantum technologies at early to late stages of development for healthcare ...
Oshin Sharma, Ross Fairbairn, Imogen Forsythe, Oleta Williams, Andrew Mkwashi   +4 more
wiley   +1 more source

Machine‐learning‐assisted photonic device development: a multiscale approach from theory to characterization

Nanophotonics, Volume 14, Issue 23, Page 3761-3793, 02 November 2025.
Abstract Photonic device development (PDD) has achieved remarkable success in designing and implementing new devices for controlling light across various wavelengths, scales, and applications, including telecommunications, imaging, sensing, and quantum information processing.
Yuheng Chen, Alexander Montes McNeil, Taehyuk Park, Blake A. Wilson, Vaishnavi Iyer, Michael Bezick, Jae‐Ik Choi, Rohan Ojha, Pravin Mahendran, Daksh Kumar Singh, Geetika Chitturi, Peigang Chen, Trang Do, Alexander V. Kildishev, Vladimir M. Shalaev, Michael Moebius, Wenshan Cai, Yongmin Liu, Alexandra Boltasseva   +18 more
wiley   +1 more source

BHT-QAOA: Generalizing Quantum Approximate Optimization Algorithm to Solve Arbitrary Boolean Problems as Hamiltonians

A new methodology is proposed to solve classical Boolean problems as Hamiltonians, using the quantum approximate optimization algorithm (QAOA). Our methodology successfully finds all optimized approximated solutions for Boolean problems, after converting them from Boolean oracles (in different structures) into Phase oracles, and then into the ...
Al-Bayaty, Ali, Perkowski, Marek
openaire   +2 more sources

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  

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

Performance of parity QAOA for the signed Max-Cut problem

New Journal of Physics
The practical implementation of quantum optimization algorithms on noisy intermediate-scale quantum devices requires accounting for their limited connectivity. As such, the Parity architecture was introduced to overcome this limitation by encoding binary
Anita Weidinger, Glen Bigan Mbeng, Michael Fellner, Davit Khachatryan, Wolfgang Lechner   +4 more
doaj   +1 more source

QAOA-PCA: Enhancing Efficiency in the Quantum Approximate Optimization Algorithm via Principal Component Analysis

The Quantum Approximate Optimization Algorithm (QAOA) is a promising variational algorithm for solving combinatorial optimization problems on near-term devices. However, as the number of layers in a QAOA circuit increases, which is correlated with the quality of the solution, the number of parameters to optimize grows linearly.
Parry, Owain, McMinn, Phil
openaire   +2 more sources

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