Results 71 to 80 of about 3,222 (193)

Solving Standard and Generalized EMPM Eigenvalue Problems: A QUBO Approach for the D-Wave Quantum Annealer [PDF]

EPJ Web of Conferences
Within the Equation of Motion Phonon Method (EMPM) framework, we address the computation of the ground-state eigenpair of nuclear Hamiltonians by reformulating the eigenvalue problem as a Quadratic Unconstrained Binary Optimization (QUBO).
De Gregorio G., De Lucia C., Martone A., D’Aniello F.A., Mastroianni A., Nunziata G., Knapp F., Iudice N. Lo, Veselý P.   +8 more
doaj   +1 more source

Quantum annealing for systems of polynomial equations

, 2019
Numerous scientific and engineering applications require numerically solving systems of equations. Classically solving a general set of polynomial equations requires iterative solvers, while linear equations may be solved either by direct matrix ...
Chang, Chia Cheng, Gambhir, Arjun, Humble, Travis S., Sota, Shigetoshi   +3 more
core   +2 more sources

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

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

Image recognition with an adiabatic quantum computer I. Mapping to quadratic unconstrained binary optimization [PDF]

, 2008
Many artificial intelligence (AI) problems naturally map to NP-hard optimization problems. This has the interesting consequence that enabling human-level capability in machines often requires systems that can handle formally intractable problems.
Macready, William G., Neven, Hartmut, Rose, Geordie   +2 more
core  

Performance Models for Split-execution Computing Systems

, 2016
Split-execution computing leverages the capabilities of multiple computational models to solve problems, but splitting program execution across different computational models incurs costs associated with the translation between domains.
Britt, Keith A., Humble, Travis S., Imam, Neena, McCaskey, Alexander J., Schrock, Jonathan, Seddiqi, Hadayat   +5 more
core   +1 more source

Machine Learning‐Driven Cooling Window Design Beyond Hyperbolic Metamaterials

Nanophotonics, Volume 15, Issue 4, 24 February 2026.
Machine learning‐driven inverse design enables ultrathin metal/dielectric cooling‐window coatings that outperform analytical hyperbolic metamaterials under identical material and thickness constraints. Optimized aperiodic multilayers simultaneously enhance visible transparency, near‐infrared rejection, and color tunability, demonstrating a practical ...
Seok‐Beom Seo, Ye‐Rin Choi, Jong‐Goog Lee, Gumin Kang, Hyungduk Ko, Run Hu, Sun‐Kyung Kim   +6 more
wiley   +1 more source

Nonnegative/binary matrix factorization with a D-Wave quantum annealer

, 2017
D-Wave quantum annealers represent a novel computational architecture and have attracted significant interest, but have been used for few real-world computations. Machine learning has been identified as an area where quantum annealing may be useful. Here,
Alexandrov, Boian S., Alexandrov, Ludmil B., O'Malley, Daniel, Vesselinov, Velimir V.   +3 more
core   +2 more sources

A QUBO Framework for Team Formation

The team formation problem assumes a set of experts and a task, where each expert has a set of skills and the task requires some skills. The objective is to find a set of experts that maximizes coverage of the required skills while simultaneously minimizing the costs associated with the experts.
Karan Vombatkere, Evimaria Terzi, Theodoros Lappas   +2 more
openaire   +2 more sources

A Quadratic Unconstrained Binary Optimization (QUBO) Model for Elevation‐Aware Vehicle Routing: Optimizing Fuel Consumption and Traffic Congestion

Advanced Quantum Technologies, Volume 9, Issue 2, February 2026.
This study proposes an elevation‐aware QUBO model that optimizes multi‐vehicle routes by jointly reducing fuel consumption and traffic congestion. By integrating gradient‐corrected Dijkstra routing with quantum annealing, the method achieves substantial fuel‐saving effects in hilly regions such as San Francisco and significantly decreases route overlap,
Tsubasa Suzuki, Takao Tomono
wiley   +1 more source