NP-complete problemsLOW-rank matricesCOMPUTATIONAL mathematicsMACHINERYSpatial-photonic Ising machines (SPIMs) have shown promise as an energy-efficient Ising machine, but currently can only solve a limited set of Ising problems. There is currently limited understanding on what experimental constraints may...
Here, we report a 16-bit coherent Ising machine based on a network of time-division-multiplexed femtosecond degenerate optical parametric oscillators. The system experimentally gives more than 99.6% of success rates for one-dimensional Ising ring and nondeterministic polynomial-time (NP) hard ...
discrete and continuous variables, some of which belong to NP-hard or NP-complete class in complexity theory, are ubiquitous in numerous important areas, including operations and scheduling, drug discovery, wireless communications, finance, integrated circuit design, compressed sensing, and machine ...
Quantum machine learning 12.2 The Ising model, adiabatic quantum computing, and quantum annealing Many problems in ML can be mapped to the Ising problem formalism; first, let us describe the Ising model [19]. 12.2.1 The Ising model The Ising model, named for German physicist Ernst Ising, was...
We also identify a common effect, in which the DOPO dynamics freeze-out and prevent the machine from reaching the ground state as a dominant performance inhibiting factor. By analyzing the dynamics of the DOPO net- work, we find how this effect is linked to the calculation success and the ...
It was shown that many computationally intractable problems (such as those in class NP complete or NP hard) can be converted into Ising models [4]. Some natural processes, such as quantum annealing process, were proposed as an effective way for finding such a ground state [5,6]. D-Wave ...
Ising machines (IMs) have emerged as a promising solution for rapidly solving NP-complete combinatorial optimization problems, surpassing the capabilities of traditional computing methods. By efficiently determining the ground state of the Hamiltonian during the annealing process, IMs can effectively ...
They can map a family of NP-complete problems and derive competitive solutions at speeds much greater than conventional algorithms and in some cases, at a fraction of the energy cost of a von Neumann computer. However, certain shortcomings prohibit Ising machines in realizing its true potential. ...
Scaling up the optoelectronic oscillator Ising machine remains challenging owing to its time-multiplexed architecture and highly complex and costly optoelectronic setup12,13. All of the proposed systems bear close resemblance to those described in the field of stochastic computing, where so-called ‘p-...
The Max-Cut problem is frequently used for circuit design and machine learning47,48, and is one of the most basic combinatorial optimization problems. In a typical Max-Cut problem, one starts with a system (a graph) in which a certain number of elements (the vertices of a graph) are rel...