Results 11 to 20 of about 1,190 (203)

Range dependent Hamiltonian algorithms for numerical QUBO formulation [PDF]

Scientific Reports
With the advent and development of quantum computers, various quantum algorithms that can solve linear equations and eigenvalues faster than classical computers have been developed.
Hyunju Lee, Kyungtaek Jun
doaj   +5 more sources

Quantum image denoising: a framework via Boltzmann machines, QUBO, and quantum annealing [PDF]

Frontiers in Computer Science, 2023
We investigate a framework for binary image denoising via restricted Boltzmann machines (RBMs) that introduces a denoising objective in quadratic unconstrained binary optimization (QUBO) form well-suited for quantum annealing.
Phillip Kerger, Phillip Kerger, Phillip Kerger, Ryoji Miyazaki, Ryoji Miyazaki   +4 more
doaj   +2 more sources

Quantum annealing for inverse kinematics in robotics [PDF]

Scientific Reports
We study a proof-of-concept workflow that reformulates planar inverse kinematics (IK) for robotic manipulators as a Quadratic Unconstrained Binary Optimization (QUBO) using a linear binary discretization of joint angles and one-hot (big-M) constraints ...
Hadi Salloum, Sergei Savin, Yaroslav Kholodov, Gleb Ryzhakov, Mirko Farina, Ivan Oseledets   +5 more
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QUBO Formulation of the Pickup and Delivery Problem with Time Windows for Quantum Annealing [PDF]

Applied Sciences
This paper addresses the Pickup and Delivery Problem with Time Windows (PDPTW), an NP-hard combinatorial optimization problem with major practical relevance in logistics and transportation.
Cosmin Ștefan Curuliuc, Florin Leon
doaj   +2 more sources

Quadratic unconstrained binary optimization and constraint programming approaches for lattice-based cyclic peptide docking [PDF]

Scientific Reports
The peptide-protein docking problem is an important problem in structural biology that facilitates rational and efficient drug design. In this work, we explore modeling and solving this problem with the quantum-amenable quadratic unconstrained binary ...
J. Kyle Brubaker, Kyle E. C. Booth, Akihiko Arakawa, Fabian Furrer, Jayeeta Ghosh, Tsutomu Sato, Helmut G. Katzgraber   +6 more
doaj   +2 more sources

Optimum-Preserving QUBO Parameter Compression [PDF]

Quantum Machine Intelligence, 2023
Abstract Quadratic unconstrained binary optimization (QUBO) problems are well-studied, not least because they can be approached using contemporary quantum annealing or classical hardware acceleration. However, due to limited precision and hardware noise, the effective set of feasible parameter values is severely restricted.
Sascha Mücke, Thore Gerlach, Nico Piatkowski   +2 more
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HUBO and QUBO models for prime factorization [PDF]

Scientific Reports, 2023
AbstractThe security of the RSA cryptosystem is based on the difficulty of factoring a large number N into prime numbers $$p$$ p and $$q$$ q satisfying $$N=p\times q$$ N = p ×
Kyungtaek Jun, Hyunju Lee
openalex   +5 more sources

Ferroelectric compute-in-memory annealer for combinatorial optimization problems [PDF]

Nature Communications
Computationally hard combinatorial optimization problems (COPs) are ubiquitous in many applications. Various digital annealers, dynamical Ising machines, and quantum/photonic systems have been developed for solving COPs, but they still suffer from the ...
Xunzhao Yin, Yu Qian, Alptekin Vardar, Marcel Günther, Franz Müller, Nellie Laleni, Zijian Zhao, Zhouhang Jiang, Zhiguo Shi, Yiyu Shi, Xiao Gong, Cheng Zhuo, Thomas Kämpfe, Kai Ni   +13 more
doaj   +2 more sources

Mean field approximation for solving QUBO problems

PLOS ONE, 2022
The Quadratic Unconstrained Binary Optimization (QUBO) problem is NP-hard. Some exact methods like the Branch-and-Bound algorithm are suitable for small problems. Some approximations like stochastic simulated annealing for discrete variables or mean-field annealing for continuous variables exist for larger ones, and quantum computers based on the ...
Máté Tibor Veszeli, Gábor Vattay
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Quantum annealing learning search for solving QUBO problems [PDF]

Quantum Information Processing, 2019
In this paper we present a novel strategy to solve optimization problems within a hybrid quantum-classical scheme based on quantum annealing, with a particular focus on QUBO problems. The proposed algorithm is based on an iterative structure where the representation of an objective function into the annealer architecture is learned and already visited ...
Davide Pastorello, Enrico Blanzieri
openalex   +6 more sources