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20242026
most citedCharacterizing the Performance of the Implicit Massively Parallel Particle-in-Cell iPIC3D Code

2 citations · 2 across the 9 of their papers we have counts for

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cs.DC2026

Engineering Low-Latency, High-Throughput Quantum Decoders on NVIDIA GPUs

Stefano Markidis, Luca Pennati, Ivy Peng

We design and optimize a quantum error correction (QEC) decoder for NVIDIA GPUs, combining Relay belief propagation, a state-of-the-art message-passing algorithm, with order-zero o…

cs.ET2026

Fewer Histories, Faster Paths: Distributed Quantum Circuit Feynman Simulation via History Reduction, Checkpointing, and Pruning

Frej Larssen, Luca Pennati, Erik M. Åsgrim +2

We present a distributed method for exact sparse-output quantum circuit simulation based on the pure Feynman sum-over-histories formulation. The method computes selected computatio…

cs.ET2026

Which Superconducting Qubit Model is Good Enough? From Effective Two-Level to Circuit-Based Hamiltonians for Pulse-Level Simulation

Frej Larssen, Ivy Peng, Stefano Markidis

Pulse-level simulators are the lowest-level, most widely used abstraction layer for studying how quantum hardware responds to control signals, but they can be built on Hamiltonian…

cs.CE2026

BVH-Accelerated Ray Tracing for High-Frequency Electromagnetic Backscattering

Marco Pasquale, Andong Hu, Luca Pennati +2

As computational complexity in electromagnetics increases with frequency, full-wave solvers become computationally infeasible for electrically large problems. To address this limit…

cs.DC2026

Enabling AI Deep Potentials for Ab Initio-quality Molecular Dynamics Simulations in GROMACS

Andong Hu, Luca Pennati, Stefano Markidis +1

State-of-the-art AI deep potentials provide ab initio-quality results, but at a fraction of the computational cost of first-principles quantum mechanical calculations, such as dens…