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20212026
most citedMassively Parallel Probabilistic Computing with Sparse Ising Machines

217 citations · 597 across the 14 of their papers we have counts for

collaborators

14 papers

cond-mat.dis-nn2026

Extreme-Scale Ising Machines with Cluster Mean-Field Theory

Xiuqi Zhang, Shuvro Chowdhury, Shaila Niazi +3

Scaling analog and digital Ising machines to larger problems requires overcoming finite device capacity and the cost of communication between devices. We present cluster mean-field…

cs.AR2026

A 28nm 27,648-Spin Multichip Digital Ising Accelerator with Pegasus Connectivity

Tong Wu, Atharva Raut, Ian Khor +10

We report a 28 nm four-chip Ising accelerator with 27,648 spins, degree-15 Pegasus connectivity, and 10b coefficients. Boundary-state streaming overlaps interchip transfers with sp…

cs.DC2026

Programmable Probabilistic Computer with 1,000,000 p-bits

Navid Anjum Aadit, Xiuqi Zhang, Shuvro Chowdhury +10

Probabilistic computers built from p-bits have been proposed as hardware accelerators for sampling and optimizing Ising models, but existing systems have been confined to a single…

quant-ph2025

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…

quant-ph2025★ 9 cited

Pushing the Boundary of Quantum Advantage in Hard Combinatorial Optimization with Probabilistic Computers

Shuvro Chowdhury, Navid Anjum Aadit, Andrea Grimaldi +12

Recent demonstrations on specialized benchmarks have reignited excitement for quantum computers, yet whether they can deliver an advantage for practical real-world problems remains…

cs.ET2025★ 10 cited

Scalable Connectivity for Ising Machines: Dense to Sparse

M Mahmudul Hasan Sajeeb, Navid Anjum Aadit, Shuvro Chowdhury +7

In recent years, hardware implementations of Ising machines have emerged as a viable alternative to quantum computing for solving hard optimization problems among other application…

quant-ph2024★ 7 cited

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…

cs.DC2023★ 31 cited

All-to-all reconfigurability with sparse and higher-order Ising machines

Srijan Nikhar, Sidharth Kannan, Navid Anjum Aadit +2

Domain-specific hardware to solve computationally hard optimization problems has generated tremendous excitement. Here, we evaluate probabilistic bit (p-bit) based Ising Machines (…

cond-mat.mes-hall2023★ 82 cited

CMOS + stochastic nanomagnets: heterogeneous computers for probabilistic inference and learning

Nihal Sanjay Singh, Keito Kobayashi, Qixuan Cao +8

Extending Moore's law by augmenting complementary-metal-oxide semiconductor (CMOS) transistors with emerging nanotechnologies (X) has become increasingly important. One important c…

cs.ET2023★ 136 cited

A full-stack view of probabilistic computing with p-bits: devices, architectures and algorithms

Shuvro Chowdhury, Andrea Grimaldi, Navid Anjum Aadit +9

The transistor celebrated its 75 birthday in 2022. The continued scaling of the transistor defined by Moore's Law continues, albeit at a slower pace. Meanwhile, compu…

cs.ET2023★ 52 cited

Training Deep Boltzmann Networks with Sparse Ising Machines

Shaila Niazi, Navid Anjum Aadit, Masoud Mohseni +3

The slowing down of Moore's law has driven the development of unconventional computing paradigms, such as specialized Ising machines tailored to solve combinatorial optimization pr…

cs.AR2022★ 13 cited

Physics-inspired Ising Computing with Ring Oscillator Activated p-bits

Navid Anjum Aadit, Andrea Grimaldi, Giovanni Finocchio +1

The nearing end of Moore's Law has been driving the development of domain-specific hardware tailored to solve a special set of problems. Along these lines, probabilistic computing…

cond-mat.mes-hall2022★ 40 cited

Spintronics-compatible approach to solving maximum satisfiability problems with probabilistic computing, invertible logic and parallel tempering

Andrea Grimaldi, Luis Sánchez-Tejerina1, Navid Anjum Aadit +4

The search of hardware-compatible strategies for solving NP-hard combinatorial optimization problems (COPs) is an important challenge of today s computing research because of their…

cs.ET2021★ 217 cited

Massively Parallel Probabilistic Computing with Sparse Ising Machines

Navid Anjum Aadit, Andrea Grimaldi, Mario Carpentieri +4

Inspired by the developments in quantum computing, building domain-specific classical hardware to solve computationally hard problems has received increasing attention. Here, by in…