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Showing 1–6 of 6 results
Advanced filters: Author: Shuvro Chowdhury Clear advanced filters

  • Finding solutions in rugged energy landscapes is hard. Here, authors introduce a generalized Probabilistic Approximate Optimization Algorithm, a classical variational Monte Carlo method that reshapes the landscape and runs on probabilistic computers, recovers simulated annealing, and learns multi-temperature schedules.

    • Abdelrahman S. Abdelrahman
    • Shuvro Chowdhury
    • Kerem Y. Camsari
    ResearchOpen Access
    Nature Communications
    Volume: 17, P: 1-11

  • Probabilistic computing has emerged as a powerful route for tackling hard optimization. Here, authors show p-computers co-designed with modern hardware to run Monte Carlo algorithms solve hard optimization efficiently and establish a rigorous classical baseline to assess practical quantum advantage.

    • Shuvro Chowdhury
    • Navid Anjum Aadit
    • Kerem Y. Camsari
    ResearchOpen Access
    Nature Communications
    Volume: 16, P: 1-10

  • Specialized hardware for hard optimization is gaining traction. Here, the authors introduce a sparse, multiplexed, and reconfigurable p-bit Ising Machine on Field-Programmable Gate Arrays, using adaptive parallel tempering and higher-order interactions to achieve competitive performance on the 3-Regular 3-XORSAT problem.

    • Srijan Nikhar
    • Sidharth Kannan
    • Kerem Y. Camsari
    ResearchOpen Access
    Nature Communications
    Volume: 15, P: 1-11

  • Probabilistic-bit-based Ising machines implemented on field-programmable gate arrays can be used to train artificial intelligence networks with the same performance as software-based approaches while using fewer model parameters.

    • Shaila Niazi
    • Shuvro Chowdhury
    • Kerem Y. Camsari
    Research
    Nature Electronics
    Volume: 7, P: 610-619

  • Ising Machines are domain-specific computers tailored to solve hard combinatorial optimization and probabilistic sampling problems. Here, the authors augment an earlier Ising machine concept that combines billiard dynamics with latches, so-called chaotic bits, with stochasticity, improving performance to rival probabilistic bits.

    • Kyle Lee
    • Shuvro Chowdhury
    • Kerem Y. Camsari
    ResearchOpen Access
    Communications Physics
    Volume: 8, P: 1-11

  • Quantum Monte Carlo (QMC) techniques have been very successful in quantum simulation. This paper shows a pathway to provide orders of magnitude speedup to QMC simulations through massively parallel architectures (both digital and mixed signal) while maintaining a scaling advantage over QMC implemented in software.

    • Shuvro Chowdhury
    • Kerem Y. Camsari
    • Supriyo Datta
    ResearchOpen Access
    Communications Physics
    Volume: 6, P: 1-9