Coherent Ising machines—optical neural networks operating at the quantum limit
Y Yamamoto, K Aihara, T Leleu… - npj Quantum …, 2017 - nature.com
In this article, we will introduce the basic concept and the quantum feature of a novel
computing system, coherent Ising machines, and describe their theoretical and experimental …
computing system, coherent Ising machines, and describe their theoretical and experimental …
Combinatorial optimization with physics-inspired graph neural networks
Combinatorial optimization problems are pervasive across science and industry. Modern
deep learning tools are poised to solve these problems at unprecedented scales, but a …
deep learning tools are poised to solve these problems at unprecedented scales, but a …
Quantum approximate optimization algorithm: Performance, mechanism, and implementation on near-term devices
The quantum approximate optimization algorithm (QAOA) is a hybrid quantum-classical
variational algorithm designed to tackle combinatorial optimization problems. Despite its …
variational algorithm designed to tackle combinatorial optimization problems. Despite its …
An Ising Hamiltonian solver based on coupled stochastic phase-transition nano-oscillators
Combinatorial optimization problems belong to the non-deterministic polynomial time (NP)-
hard complexity class, and their computational requirements scale exponentially with …
hard complexity class, and their computational requirements scale exponentially with …
A fully programmable 100-spin coherent Ising machine with all-to-all connections
Unconventional, special-purpose machines may aid in accelerating the solution of some of
the hardest problems in computing, such as large-scale combinatorial optimizations, by …
the hardest problems in computing, such as large-scale combinatorial optimizations, by …
Exploratory combinatorial optimization with reinforcement learning
Many real-world problems can be reduced to combinatorial optimization on a graph, where
the subset or ordering of vertices that maximize some objective function must be found. With …
the subset or ordering of vertices that maximize some objective function must be found. With …
Experimental investigation of performance differences between coherent Ising machines and a quantum annealer
Physical annealing systems provide heuristic approaches to solving combinatorial
optimization problems. Here, we benchmark two types of annealing machines—a quantum …
optimization problems. Here, we benchmark two types of annealing machines—a quantum …
QAOA-in-QAOA: solving large-scale MaxCut problems on small quantum machines
The design of fast algorithms for combinatorial optimization greatly contributes to a plethora
of domains such as logistics, finance, and chemistry. Quantum approximate optimization …
of domains such as logistics, finance, and chemistry. Quantum approximate optimization …
[BUKU][B] Optimization by GRASP
MGC Resende, CC Ribeiro - 2016 - Springer
Greedy randomized adaptive search procedures, or GRASP, were introduced by T. Feo and
M. Resende in 1989 as a probabilistic heuristic for solving hard set covering problems. Soon …
M. Resende in 1989 as a probabilistic heuristic for solving hard set covering problems. Soon …
Towards large-scale quantum optimization solvers with few qubits
Quantum computers hold the promise of more efficient combinatorial optimization solvers,
which could be game-changing for a broad range of applications. However, a bottleneck for …
which could be game-changing for a broad range of applications. However, a bottleneck for …