Results 51 to 60 of about 548 (174)

Addressing ecological challenges from a quantum computing perspective

Methods in Ecology and Evolution, Volume 17, Issue 3, Page 632-649, March 2026.
Abstract With increased access to data and the advent of computers, the use of statistical tools and numerical simulations is becoming commonplace for ecologists. These approaches help improve our understanding of ecological phenomena and their underlying mechanisms in increasingly complex environments.
Maxime Clenet, Maxime Dion, F. Guillaume Blanchet   +2 more
wiley   +1 more source

Synchrotron Radiation for Quantum Technology

Advanced Functional Materials, Volume 36, Issue 15, 19 February 2026.
Materials and interfaces underpin quantum technologies, with synchrotron and FEL methods key to understanding and optimizing them. Advances span superconducting and semiconducting qubits, 2D materials, and topological systems, where strain, defects, and interfaces govern performance.
Oliver Rader, Sakura Pascarelli, Klaus Attenkofer, Anna A. Makarova, Karsten Holldack, Kai Rossnagel, Kristiaan Temst, George Kourousias, Stefano Carretta, Caterina Biscari, Helmut Dosch   +10 more
wiley   +1 more source

Recursive QAOA outperforms the original QAOA for the MAX-CUT problem on complete graphs

Quantum Information Processing
8 pages, 1 ...
Eunok Bae, Soojoon Lee
openaire   +2 more sources

Quantifying the impact of precision errors on quantum approximate optimization algorithms

Physical Review Research
The quantum approximate optimization algorithm (QAOA) is a hybrid quantum-classical algorithm that seeks to achieve approximate solutions to optimization problems by iteratively alternating between intervals of controlled quantum evolution.
Gregory Quiroz, Paraj Titum, Phillip Lotshaw, Pavel Lougovski, Kevin Schultz, Eugene Dumitrescu, Itay Hen   +6 more
doaj   +1 more source

A Quantum Framework for Protein Binding‐Site Structure Prediction on Utility‐Level Quantum Processors

Advanced Science, Volume 13, Issue 12, 27 February 2026.
This study presents a hybrid quantum‐classical framework for accurate prediction of protein structures on utility‐level quantum processors. We evaluate the practical application of the Variational Quantum Eigen‐solver (VQE) in protein structure prediction and demonstrate its superiority over state‐of‐the‐art deep learning methods in molecular docking ...
Yuqi Zhang, Yuxin Yang, William Martin, Kingsten Lin, Zixu Wang, Cheng‐Chang Lu, Weiwen Jiang, Ruth Nussinov, Joseph Loscalzo, Qiang Guan, Feixiong Cheng   +10 more
wiley   +1 more source

Snapshot-QAOA: Extending QAOA to Quantum Hamiltonian Simulation

Abstract We present Snapshot-QAOA, a variation of the Quantum Approximate Optimization Algorithm (QAOA) that finds approximate minimum energy eigenstates of a large set of quantum Hamiltonians. Traditionally, QAOA targets the task of approximately solving combinatorial optimization problems. Snapshot-QAOA enables a significant expansion
Tate, Reuben, Langfitt, Quinn, Pelofske, Elijah, Kirmani, Ammar, Bärtschi, Andreas, Golden, John, Eidenbenz, Stephan   +6 more
openaire   +2 more sources

Proactively incremental-learning QAOA

, 2023
Solving optimization problems with high performance is the target of existing works of Quantum Approximate Optimization Algorithm (QAOA). With this intention, we propose an advanced QAOA based on incremental learning, where the training trajectory is proactively segmented into incremental phases.
Li, Lingxiao, Li, Jing, Song, Yanqi, Qin, Sujuan, Wen, Qiaoyan, Gao, Fei   +5 more
openaire   +2 more sources

Sampling frequency thresholds for the quantum advantage of the quantum approximate optimization algorithm

npj Quantum Information, 2023
We compare the performance of the Quantum Approximate Optimization Algorithm (QAOA) with state-of-the-art classical solvers Gurobi and MQLib to solve the MaxCut problem on 3-regular graphs. We identify the minimum noiseless sampling frequency and depth p
Danylo Lykov, Jonathan Wurtz, Cody Poole, Mark Saffman, Tom Noel, Yuri Alexeev   +5 more
doaj   +1 more source

Mapping Quantum Computing Techniques for NP‐Hard Problems in Operations Management and Operations Research

Engineering Reports, Volume 8, Issue 2, February 2026.
Quantum computing techniques such as Quantum Annealing and Quadratic Unconstrained Binary Optimization are effectively solving NP‐hard problems in operations management and research, particularly in logistics, manufacturing, and finance. This study maps these applications to present a framework for future adoption across industries. ABSTRACT This study
Daniel Bouzon Nagem Assad, Patricia Gomes Ferreira da Costa, Thaís Spiegel, Hélcio de Oliveira Rocha   +3 more
wiley   +1 more source

Quantum approximate optimization algorithms for maximum cut on low-girth graphs

Physical Review Research
Maximum cut (MaxCut) on graphs is a classic NP-hard problem. In quantum computing, Farhi, Gutmann, and Goldstone proposed the quantum approximate optimization algorithm (QAOA) for solving the MaxCut problem.
Tongyang Li, Yuexin Su, Ziyi Yang, Shengyu Zhang   +3 more
doaj   +1 more source