Algorithm demonstrates advantages of photonic computer hardware

Researchers from Massachusetts Institute of Technology (MIT) and photonic computer hardware startup, Lightelligence, have revealed novel algorithms which demonstrated the advantages of integrated circuits that rely on light instead of electrons. The Nature Communications paper “Heuristic recurrent algorithms for photonic Ising machines” by Charles Roques-Carmes, Yichen Shen, et al. explains a novel way of using integrated photonic chip to run algorithms that solve hard combinatorial problems.

Many hard optimization problems encountered in various disciplines of science and engineering, from drug/material discovery to routing and scheduling can be reduced to certain forms of NP-complete. Intuitively speaking, NP-complete problems are “hard to solve” because the number of operations that one has to perform in order to find the solution scales exponentially with the problem size. The ubiquity of NP-complete problems has bolstered the development of dedicated hardware (such as optical annealing and quantum annealing machines like “D-Wave”) and special algorithms (heuristic algorithms like simulated annealing). The path to solving NP-complete problems with photonics is opened by the work of Roques-Carmes and Shen et al., published in Nature Communications. In this work, the team developed an algorithm dedicated to solving the well-known NP-complete Ising problem with photonics hardware.

The researchers were guided by their knowledge of fundamental photonics. Professor Marin Soljačić from MIT explains: “Optical computing is a very old field of research. Therefore, we had to identify which recent advances in photonic hardware could make a difference. In other words, we had to identify the value proposition of modern photonics.” Graduate student Charles Roques-Carmes adds: “We identified this value proposition to be: (1) performing fast and cheap fixed matrix multiplication and; (2) performing noisy computation, which means that the result of the computation slightly varies from one run to the other, a little bit like flipping a coin. Therefore, these two elements are the building blocks of our work.”

While developing this algorithm and benchmarking it on various problems, the researchers discovered a variety of related algorithms that could also be implemented in photonics to find solutions even faster. Corresponding author and CEO of Lightelligence, Yichen Shen, is enthusiastic about the prospect of this work: “The field of enhancing computing capability with integrated photonics is currently booming and we believe this work can be part of it. Since the algorithm we developed optimally leverages the strengths and weaknesses of photonic hardware, we aim to develop immediate, real-world applications.”