4 papers
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…