8 citations · 20 across the 28 of their papers we have counts for
13 papers · 1 filter
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…
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…
Advancing Heliophysics and Space Weather Modeling through Open Science
C. Corti, M. M. Kuznetsova, M. A. Reiss +85
We present a community-wide effort to develop a strategy and action plan to advance heliophysics and space weather modeling through open science. While open science has the potenti…
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…
Robust Matrix-Free Newton-Krylov Solvers via Automatic Differentiation
Marco Pasquale, Stefano Markidis
Jacobian-Free Newton-Krylov (JFNK) methods avoid forming the full Jacobian, but still require Jacobian-vector products, i.e., Gateaux derivatives of the nonlinear residual along Kr…
Post-Moore Technologies for Plasma Simulation: A Community Roadmap
Luca Pennati, Erik M. Åsgrim, Jeremy J. Williams +21
Plasma simulations are among the most computationally demanding scientific workloads, combining high-dimensional kinetic evolution, particle-mesh coupling, field solves, and data-i…
Mass Matrix Assembly on Tensor Cores for Implicit Particle-In-Cell Methods
Luca Pennati, Stefano Markidis
Matrix-multiply-accumulate (MMA) units, or tensor cores, are now widespread across modern computing architectures. Yet, their use for particle-grid operators remains limited. In im…
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…
Making Room for AI: Multi-GPU Molecular Dynamics with Deep Potentials in GROMACS
Luca Pennati, Andong Hu, Ivy Peng +2
GROMACS is a de-facto standard for classical Molecular Dynamics (MD). The rise of AI-driven interatomic potentials that pursue near-quantum accuracy at MD throughput now poses a si…
Multi-GPU Hybrid Particle-in-Cell Monte Carlo Simulations for Exascale Computing Systems
Jeremy J. Williams, Jordy Trilaksono, Stefan Costea +13
Particle-in-Cell (PIC) Monte Carlo (MC) simulations are central to plasma physics but face increasing challenges on heterogeneous HPC systems due to excessive data movement, synchr…
Unsupervised Physics-Informed Operator Learning through Multi-Stage Curriculum Training
Paolo Marcandelli, Natansh Mathur, Stefano Markidis +2
Solving partial differential equations remains a central challenge in scientific machine learning. Neural operators offer a promising route by learning mappings between function sp…
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…
Tensor Network Compression for Fully Spectral Vlasov-Poisson Simulation
Erik M. Åsgrim, Luca Pennati, Marco Pasquale +1
We propose a numerical method for kinetic plasma simulation in which the phase-space distribution is represented by a low-rank tensor network with an adaptive level of compression.…