Cited by Physics Nobel Prize '24: Ising machines as hardware solvers (paper review)

CS597s seminar discussion at Princeton.

Slides: https://kyleatprinceton.github.io/cos...
Paper: https://www.nature.com/articles/s4225...


Authors: Naeimeh Mohseni, Peter L. McMahon, Tim Byrnes
Abstract: Ising machines are hardware solvers that aim to find the absolute or approximate ground states of the Ising model. The Ising model is of fundamental computational interest because any problem in the complexity class NP can be formulated as an Ising problem with only polynomial overhead, and thus a scalable Ising machine that outperforms existing standard digital computers could have a huge impact for practical applications. We survey the status of various approaches to constructing Ising machines and explain their underlying operational principles. The types of Ising machines considered here include classical thermal annealers based on technologies such as spintronics, optics, memristors and digital hardware accelerators; dynamical systems solvers implemented with optics and electronics; and superconducting-circuit quantum annealers. We compare and contrast their performance using standard metrics such as the ground-state success probability and time-to-solution, give their scaling relations with problem size, and discuss their strengths and weaknesses.

00:00:00 Intro
00:00:43 HP-Hard and Ising Hamiltonian
00:01:50 Ising Hamiltonian
00:08:10 Degenerate Optical Parametric Oscillator (DOPO)
00:10:20 Coherent Ising Machine (CIM)
00:10:48 Solving Max Cut with Ising Machine
00:12:31 Programming Ising Machine
00:16:39 Quantum Annealing
00:18:44 Challenges of Quantum Annealing
00:20:20 Stochastic magnetic tunnel junctions, memoristors, CMOS
00:21:32 Comparing Ising Machines

#nobelprize2024 #computerscience #physics #engineering