5 papers
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…
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…
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…
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…
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…