Research
The project aims to invent and demonstrate experimental approaches to coherent Ising machines and related photonic optimization systems.
The team is tackling two fundamental challenges: building coherent Ising machines at large scale without bottlenecking photonic processing through electronic processing, and building systems that can operate in regimes difficult to simulate classically.
Device efforts focus on miniaturization using nanophotonics, including nonlinear devices such as optical parametric amplifiers based on thin-film lithium niobate. Miniaturized components can improve energy consumption, speed, and access to new quantum optical regimes.
At the system level, the project explores time, frequency, and space multiplexing strategies for constructing coherent Ising machines at large scale. Each strategy involves tradeoffs in construction, connectivity, and performance.
Research areas
fundamentals
Physical dynamics beyond conventional digital electronics as foundations for hard optimization.
What performance advantages can unconventional approaches offer, and what obstacles must be overcome to realize them? Do unconventional models of computing enable new analyses of why some optimization instances are much harder than others?
generalizations
Coherent Ising Machines as a reference architecture for broader coherent network computing.
The project studies operational bottlenecks of canonical CIMs and generalizations for non-binary variables, higher-than-quadratic cost functions, constraints, and potential quantum advantages.
applications
Practical uses of CIMs and related architectures for real-world optimization.
The team studies how real-world problems map into binary quadratic optimization frameworks, what overheads are incurred, and which generalizations could unlock important applications.
benchmarking
Principled comparisons among unconventional, quantum, and conventional optimization approaches.
Benchmarking work focuses on scaling definitions, heuristic complementarity, testbeds, and statistically meaningful performance comparisons.
participation
Education and participation studies connected to computer science identity and persistence.
The project partners with education and outreach collaborators to study factors affecting computer science identity and career-track persistence among students from historically minoritized backgrounds.
