11 papers
Hierarchical Spline-Based Bayesian Beta-Binomial Regression for Estimating Time-Varying Risk in Power Outages
Justin Jacobs, Jesse Piburn, Aaron Myers
We propose a hierarchical Bayesian model for estimating time-varying outage risk from county-level power outage data. The model combines cubic B-spline basis functions with a Beta-…
Probabilistic Computers for Neural Quantum States
Shuvro Chowdhury, Jasper Pieterse, Navid Anjum Aadit +3
Neural quantum states efficiently represent many-body wavefunctions with neural networks, but the cost of Monte Carlo sampling limits their scaling to large system sizes. Here we a…
Probabilistic approximate optimization using single-photon avalanche diode arrays
Ziyad Alswaidan, Abdelrahman S. Abdelrahman, Md Sakibur Sajal +9
Combinatorial optimization problems are central to science and engineering and specialized hardware from quantum annealers to classical Ising machines are being actively developed…
How to Build a Quantum Supercomputer: Scaling from Hundreds to Millions of Qubits
Masoud Mohseni, Artur Scherer, K. Grace Johnson +48
In the span of four decades, quantum computation has evolved from an intellectual curiosity to a potentially realizable technology. Today, small-scale demonstrations have become po…
Configurable p-Neurons Using Modular p-Bits
Saleh Bunaiyan, Mohammad Alsharif, Abdelrahman S. Abdelrahman +5
Probabilistic bits (p-bits) have recently been employed in neural networks (NNs) as stochastic neurons with sigmoidal probabilistic activation functions. Nonetheless, there remain…
Metrics for spin-based computing
Hidekazu Kurebayashi, Giovanni Finocchio, Karin Everschor-Sitte +10
Spin-based computing is emerging as a powerful approach for energy-efficient and high-performance solutions to future data processing hardware. Spintronic devices function by elect…