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ObliQ: Solving Quadratic Unconstrained Binary Optimization Problems on Real Photonic Quantum Machines

Quadratic Unconstrained Binary Optimization (QUBO) problems are central to combinatorial optimization but challenging due to their exponential solution space.
Aditya Ranjan, Tirthak Patel, Daniel Silver, Devesh Tiwari, Bhargav Chickmagalurnanjun   +4 more
core   +1 more source

Discrete quadratic model QUBO solution landscapes [PDF]

Many computational problems involve optimization over discrete variables with quadratic interactions. Known as discrete quadratic models (DQMs), these problems in general are NP-hard.
Zaborniak, Tristan, Stege, Ulrike
core   +1 more source

Efficient Digital Quadratic Unconstrained Binary Optimization Solvers for SAT Problems [PDF]

Boolean satisfiability (SAT) is a propositional logic problem of determining whether an assignment of variables satisfies a Boolean formula. Many combinatorial optimization problems can be formulated in Boolean SAT logic -- either as k-SAT decision ...
Yosifov, Alexander, Fong, Robert Simon, Song, Yanming   +2 more
core   +2 more sources

Towards arbitrary QUBO optimization: analysis of classical and quantum-activated feedforward neural networks

Machine Learning: Science and Technology
Quadratic unconstrained binary optimization (QUBO) is at the heart of many industries and academic fields such as logistics, supply chain, finance, pharmaceutical science, chemistry, IT, and energy sectors, among others (Bangert 2012 Optimization for ...
Chia-Tso Lai, Carsten Blank, Peter Schmelcher, Rick Mukherjee   +3 more
doaj   +1 more source

Computing canonical averages with quantum and classical optimizers: Thermodynamic reweighting for QUBO models of physical systems

Physical Review Research
We present a general method to compute canonical averages for physical models sampled via quantum or classical quadratic unconstrained binary optimization (QUBO).
Francesco Slongo, Cristian Micheletti
doaj   +1 more source

New algorithms for Quadratic Unconstrained Binary Optimization (QUBO) with applications in engineering and social sciences

, 2008
This dissertation investigates the Quadratic Unconstrained Binary Optimization (QUBO) problem, i.e. the problem of minimizing a quadratic function in binary variables. QUBO is studied at two complementary levels.
Tavares, Gabriel
core   +1 more source

Range dependent Hamiltonian algorithms for numerical QUBO formulation

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   +1 more source

Training squared-hinge support vector machines by an explicit QUBO–Ising construction with quantum-annealing execution

Scientific Reports
Quantum annealers natively minimize quadratic unconstrained binary optimization (QUBO) problems, yet faithfully compiling continuous convex objectives into discrete binary forms with formal guarantees remains challenging.
Zonglin Yang, Jie Zhou, Xiaohui Yang, Huilan Ma, Jiahao Li   +4 more
doaj   +1 more source

Ising Machine Approach to the Lecturer–Student Assignment Problem

IEEE Access
Ising machines are efficient solvers for combinatorial optimization problems (COPs). After mapping COPs to Quadratic Unconstrained Binary Optimization (QUBO) problems, Ising machines search for the lowest energy solution of the QUBO corresponding to the ...
Sora Tomita, Tatsuhiko Shirai, Nozomu Togawa   +2 more
doaj   +1 more source

Quantum-annealing-inspired algorithms for multijet clustering

Physics Letters B
Jet clustering or reconstruction is a crucial component at high-energy colliders, a procedure to identify sprays of collimated particles originating from the fragmentation and hadronization of quarks and gluons.
Hideki Okawa, Xian-Zhe Tao, Qing-Guo Zeng, Man-Hong Yung   +3 more
doaj   +1 more source