16 research outputs found
Synchronously-pumped OPO coherent Ising machine: benchmarking and prospects
The coherent Ising machine (CIM) is a network of optical parametric oscillators (OPOs) that solves for the ground state of Ising problems through OPO bifurcation dynamics. Here, we present experimental results comparing the performance of the CIM to quantum annealers (QAs) on two classes of NP-hard optimization problems: ground state calculation of the Sherrington-Kirkpatrick (SK) model and MAX-CUT. While the two machines perform comparably on sparsely-connected problems such as cubic MAX-CUT, on problems with dense connectivity, the QA shows an exponential performance penalty relative to CIMs. We attribute this to the embedding overhead required to map dense problems onto the sparse hardware architecture of the QA, a problem that can be overcome in photonic architectures such as the CIM
Large-scale photonic Ising machine by spatial light modulation
Quantum and classical physics can be used for mathematical computations that
are hard to tackle by conventional electronics. Very recently, optical Ising
machines have been demonstrated for computing the minima of spin Hamiltonians,
paving the way to new ultra-fast hardware for machine learning. However, the
proposed systems are either tricky to scale or involve a limited number of
spins. We design and experimentally demonstrate a large-scale optical Ising
machine based on a simple setup with a spatial light modulator. By encoding the
spin variables in a binary phase modulation of the field, we show that light
propagation can be tailored to minimize an Ising Hamiltonian with spin
couplings set by input amplitude modulation and a feedback scheme. We realize
configurations with thousands of spins that settle in the ground state in a
low-temperature ferromagnetic-like phase with all-to-all and tunable pairwise
interactions. Our results open the route to classical and quantum photonic
Ising machines that exploit light spatial degrees of freedom for parallel
processing of a vast number of spins with programmable couplings.Comment: https://journals.aps.org/prl/accepted/7007eYb7N091546c41ad4108828a97d5f92006df
Synchronously-pumped OPO coherent Ising machine: benchmarking and prospects
The coherent Ising machine (CIM) is a network of optical parametric oscillators (OPOs) that solves for the ground state of Ising problems through OPO bifurcation dynamics. Here, we present experimental results comparing the performance of the CIM to quantum annealers (QAs) on two classes of NP-hard optimization problems: ground state calculation of the Sherrington-Kirkpatrick (SK) model and MAX-CUT. While the two machines perform comparably on sparsely-connected problems such as cubic MAX-CUT, on problems with dense connectivity, the QA shows an exponential performance penalty relative to CIMs. We attribute this to the embedding overhead required to map dense problems onto the sparse hardware architecture of the QA, a problem that can be overcome in photonic architectures such as the CIM
Annealing by simulating the coherent Ising machine
The coherent Ising machine (CIM) enables efficient sampling of low-lying
energy states of the Ising Hamiltonian with all-to-all connectivity by encoding
the spins in the amplitudes of pulsed modes in an optical parametric oscillator
(OPO). The interaction between the pulses is realized by means of
measurement-based optoelectronic feedforward which enhances the gain for
lower-energy spin configurations. We present an efficient method of simulating
the CIM on a classical computer that outperforms the CIM itself as well as the
noisy mean-field annealer in terms of both the quality of the samples and the
computational speed. It is furthermore advantageous with respect to the CIM in
that it can handle Ising Hamiltonians with arbitrary real-valued node coupling
strengths. These results illuminate the nature of the faster performance
exhibited by the CIM and may give rise to a new class of quantum-inspired
algorithms of classical annealing that can successfully compete with existing
methods