2016/04/18
NTT Basic Research Laboratories and Osaka University have realized a large-scale artificial spin network based on photonics technologies. This research was funded by the ImPACT Program of the Council for Science, Technology and Innovation (Cabinet Office, Government of Japan) under the program "Advanced Information Society Infrastructure Linking Quantum Artificial Brains in Quantum Network" led by Prof. Yoshihisa Yamamoto. This achievement will provide a fundamental component for the coherent Ising machine (CIM), which is expected to be able to solve combinatorial optimization problems efficiently.
As various systems in modern society grow larger and more complex, analysis and optimization of such systems become increasingly important. Many such operations are classified as combinatorial optimization problems, which are hard to solve with modern digital computers. The research team is now studying the CIM, which utilizes interacting artificial spins realized with optical parametric oscillators (OPO) for computation of combinatorial optimization problems.
The team successfully generated more than 10,000 time-multiplexed OPOs using four-wave mixing in a highly nonlinear fiber (HNLF) placed in a fiber cavity, whose length was as long as 1 km. In addition, it simulated a one-dimensional spin network and found that the OPOs in the network behaved like low-temperature spins, which showed that they could be used as high-quality artificial spins.
Our results constitute an important step towards computers that will be able to solve large-scale combinatorial optimization problems efficiently. This work will be reported in the UK science journal "Nature Photonics" on April 18, 2006.
=> Press Release
=> Quantum Optical State Control Research Group
In our society, systems, such as the internet and traffic and social networks, are becoming more and more complex. Therefore, optimizing them is important for efficient use of natural and social resources. Many such problems are reduced to mathematical problems called combinatorial optimization problems, where we find an optimum combination from a finite set of combination. Such problems are known to be very hard to solve with modern digital computers, because the computation time ‘explodes’ as the number of combinations increases. On the other hand, combinatorial optimization problems can be mapped onto the ground-state-search problems of the Ising model, which is a theoretical model for interacting spins. Today, several institutions are trying to solve the Ising model by using artificial spin networks.
Among 'Ising machines', the CIM is now drawing attention as a way to solve the Ising model efficiently by utilizing artificial spins realized with photonics technologies (Fig. 1and Fig. 2). In the CIM, a group of OPOs is used as spins. An OPO is a special kind of laser oscillator that takes only the 0 or π phase and can therefore be used as a stable artificial spin. The spin-spin interactions can be implemented by mutual injection of OPO lights. With sufficiently slow pumping of the oscillator network, the OPO network tends to start oscillating with the combination of phases that gives the loss-minimum of the whole network, which is the ground state of the corresponding spin network.
In 2014, a group from Stanford University performed a proof-of-principle CIM experiment using four OPOs. However, in order to solve complex combinatorial optimization problems, we need to increase the number of artificial spins.
We have succeeded in generating more than10,000 time-multiplexed OPOs using an optical fiber cavity as long as 1 km (Fig. 3). This was accomplished by utilizing technologies developed through the R&D of optical fiber communications. The OPOs can be used as artificial spins for a large-scale CIM to solve combinatorial optimization problems in the real world. In addition, we have realized a one-dimensional Ising spin network by introducing nearest-neighbor coupling between OPOs, and found that our room-temperature OPOs can simulate the behavior of low-temperature spins.
In the present experiment, since we implemented only nearest-neighbor coupling, only a one-dimensional spin network could be simulated. We are now planning to implement more flexible coupling between OPOs to simulate more complex spin networks, so that we can realize a CIM that solves large-scale combinatorial optimization problems.
"Large-scale Ising spin network based on degenerate optical parametric oscillators"
Takahiro Inagaki, Kensuke Inaba, Ryan Hamerly, Kyo Inoue, Yoshihisa Yamamoto & Hiroki Takesue
Nature Photonics 2016