Results 91 to 100 of about 22,651 (215)
Solving Quadratic Unconstrained Binary Optimization with divide-and-conquer and quantum algorithms [PDF]
Gian Giacomo Guerreschi
openalex +1 more source
Statistical Complexity of Quantum Learning
The statistical performance of quantum learning is investigated as a function of the number of training data N$N$, and of the number of copies available for each quantum state in the training and testing data sets, respectively S$S$ and V$V$. Indeed, the biggest difference in quantum learning comes from the destructive nature of quantum measurements ...
Leonardo Banchi +3 more
wiley +1 more source
Quantum‐Enhanced Simulated Annealing Using Rydberg Atoms
This study experimentally demonstrates that a Rydberg hybrid quantum‐classical algorithm, termed as quantum‐enhanced simulated annealing (QESA), provides a computational time advantage over a classical standalone simulated annealing (SA). This scatter plot represents the comparison of QESA versus SA for the 924 graphs with the sizes N=60$N=60$, 80 and ...
Seokho Jeong, Juyoung Park, Jaewook Ahn
wiley +1 more source
The authors unravel how environmental conditions influence sex determination and resource allocation in a haplodiploid bee species. Using high‐resolution field data, they show that individual sex allocation shifts with environmental conditions, while population sex ratio and individual resource allocation remain stable, highlighting the complexity of ...
Katharina Wittmann +3 more
wiley +1 more source
Power Load Management as a Computational Market [PDF]
Power load management enables energy utilities to reduce peak loads and thereby save money. Due to the large number of different loads, power load management is a complicated optimization problem.
Akkermans, Hans, Ygge, Fredrik
core +6 more sources
Improving the Solving of Optimization Problems: A Comprehensive Review of Quantum Approaches
Optimization is a crucial challenge across various domains, including finance, resource allocation, and mobility. Quantum computing has the potential to redefine the way we handle complex problems by reducing computational complexity and enhancing ...
Deborah Volpe +2 more
doaj +1 more source
Lagrangian duality in quantum optimization: Overcoming QUBO limitations for constrained problems
We propose an approach to solving constrained combinatorial optimization problems based on embedding the concept of Lagrangian duality into the framework of adiabatic quantum computation.
Einar Gabbassov +2 more
doaj +1 more source
Efficient Rank Minimization to Tighten Semidefinite Programming for\n Unconstrained Binary Quadratic Optimization [PDF]
Roman Pogodin +2 more
openalex +2 more sources
QUBO Formulation Using Sequence Pair With Search Space Restriction for Rectangle Packing Problem
The development of quantum annealing has stimulated interest in solving NP-hard problems, including various industrial problems, such as quadratic unconstrained binary optimization (QUBO), with specialized solvers.
Akihisa Okada +5 more
doaj +1 more source
Application of Quantum Annealing to Nurse Scheduling Problem
Quantum annealing is a promising heuristic method to solve combinatorial optimization problems, and efforts to quantify performance on real-world problems provide insights into how this approach may be best used in practice.
Humble, Travis S. +2 more
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