5 papers · 1 filter
Analog Quantum Asynchronous Event-Based Graph Neural Network
Kristian Sotirov, Shaheen Acheche, Antonio A. Gentile +1
Asynchronous, event-based graph neural networks (AEGNNs) have recently emerged as an efficient paradigm for processing the sparse and high-temporal-resolution data from event camer…
Attributed-graphs kernel implementation using local detuning of neutral-atoms Rydberg Hamiltonian
Mehdi Djellabi, Matthias Hecker, Shaheen Acheche
We extend the quantum-feature kernel framework, which relies on measurements of graph-dependent observables, along three directions. First, leveraging neutral-atom quantum processi…
A Scalable Heuristic for Molecular Docking on Neutral-Atom Quantum Processors
Mathieu Garrigues, Victor Onofre, Wesley Coelho +1
Molecular docking is a critical computational method in drug discovery used to predict the binding conformation and orientation of a ligand within a protein's binding site. Mapping…
Multiparticle quantum walks for distinguishing hard graphs
Sachin Kasture, Shaheen Acheche, Loic Henriet +1
Quantum random walks have been shown to be powerful quantum algorithms for certain tasks on graphs like database searching, quantum simulations etc. In this work we focus on its ap…
Quantum-Enhanced Neural Exchange-Correlation Functionals
Igor O. Sokolov, Gert-Jan Both, Art D. Bochevarov +6
Kohn-Sham Density Functional Theory (KS-DFT) provides the exact ground state energy and electron density of a molecule, contingent on the as-yet-unknown universal exchange-correlat…