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Corentin Delacour

Department of Electrical and Computer Engineering, University of California, Santa Barbara

Builder The claim is about what the hardware does, and the philosophy is left open

Corentin Delacour is a researcher in the Department of Electrical and Computer Engineering at the University of California, Santa Barbara, working in Kerem Y. Camsari’s probabilistic computing group. His background spans sub-threshold CMOS oscillator networks, energy-based physics hardware, and variational Monte Carlo algorithms for stochastic circuits.

In Probabilistic Algorithms for Ising Machines from Optimization to Generative AI (arXiv:2610.03972 and Nature Reviews Electrical Engineering), Delacour, Xiuqi Zhang, Abdelrahman S. Abdelrahman, Saleh Bunaiyan, Kyle Lee, Shuvro Chowdhury, and Kerem Y. Camsari synthesize the algorithmic stack for programmable Ising machines. A central contribution of their work is the Probabilistic Approximate Optimization Algorithm (PAOA), a classical variational framework that trains time-dependent coupling and inverse-temperature schedules directly on networks of probabilistic bits (p-bits), alongside parallel tempering and cluster mean-field methods.

Delacour is classified as a Builder on this site. His work provides the hardware-software co-design rules that let physical thermal noise execute variational inference and Boltzmann sampling at scale, without claiming that p-bit circuits possess subjective awareness.

Known for. Probabilistic Approximate Optimization Algorithm (PAOA), Ising machine algorithms, coupled oscillator and p-bit circuit design

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