most citedA Hybrid Quantum-Classical Particle-in-Cell Method for Plasma Simulations

2 citations · 4 across the 16 of their papers we have counts for

collaborators

17 papers

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

Not Your Usual FFT: QFTFFT via Classical Quantum-Circuit Simulation

Stefano Markidis, Gilbert Netzer, Luca Pennati +2

We introduce QFTFFT, a family of HPC FFT libraries that compute the discrete Fourier transform by executing a quantum Fourier transform (QFT) circuit on classical quan…

cs.ET2026

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…

cs.CE2026

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…

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

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…

physics.plasm-ph2026★ 1 cited

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…

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…

physics.comp-ph2026

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.…

cs.ET2025

QPU Micro-Kernels for Stencil Computation

Stefano Markidis, Luca Pennati, Marco Pasquale +2

We introduce QPU micro-kernels: shallow quantum circuits that perform a stencil node update and return a Monte Carlo estimate from repeated measurements. We show how to use them to…

cs.ET2025

An HPC-Inspired Blueprint for a Technology-Agnostic Quantum Middle Layer

Stefano Markidis, Gilbert Netzer, Luca Pennati +1

We present a blueprint for a quantum middle layer that supports applications across various quantum technologies. Inspired by concepts and abstractions from HPC libraries and middl…

cs.CE2025★ 1 cited

Exascale Implicit Kinetic Plasma Simulations on El~Capitan for Solving the Micro-Macro Coupling in Magnetospheric Physics

Stefano Markidis, Andong Hu, Ivy Peng +9

Our fully kinetic, implicit Particle-in-Cell (PIC) simulations of global magnetospheres on up to 32,768 of El Capitan's AMD Instinct MI300A Accelerated Processing Units (APUs) repr…

quant-ph2025★ 2 cited

A Hybrid Quantum-Classical Particle-in-Cell Method for Plasma Simulations

Pratibha Raghupati Hegde, Paolo Marcandelli, Yuanchun He +4

We present a hybrid quantum-classical electrostatic Particle-in-Cell (PIC) method, where the electrostatic field Poisson solver is implemented on a quantum computer simulator using…

cs.CE2025

Discovering Governing Equations of Geomagnetic Storm Dynamics with Symbolic Regression

Stefano Markidis, Jonah Ekelund, Luca Pennati +2

Geomagnetic storms are large-scale disturbances of the Earth's magnetosphere driven by solar wind interactions, posing significant risks to space-based and ground-based infrastruct…

cs.CE2025

Physics-Aware Compression of Plasma Distribution Functions with GPU-Accelerated Gaussian Mixture Models

Andong Hu, Luca Pennati, Ivy Peng +1

Data compression is a critical technology for large-scale plasma simulations. Storing complete particle information requires Terabyte-scale data storage, and analysis requires ad-h…

cs.DC2025

A Parallel and Highly-Portable HPC Poisson Solver: Preconditioned Bi-CGSTAB with alpaka

Luca Pennati, Måns I. Andersson, Klaus Steiniger +4

This paper presents the design, implementation, and performance analysis of a parallel and GPU-accelerated Poisson solver based on the Preconditioned Bi-Conjugate Gradient Stabiliz…