20 citations · 52 across the 16 of their papers we have counts for
7 papers · 1 filter
Impact of Data Loss in Postprocessing on Training and Inference of Quantum Neural Networks
Soraya V. Panambalom, Edoardo Altamura, Nick Chancellor +1
As quantum hardware scales to larger devices, the classical software layers that interface with it must evolve in step. Postprocessing routines developed and tested primarily in si…
Quantum chemistry with provable convergence via randomized sample-based Krylov quantum diagonalization
Samuele Piccinelli, Alberto Baiardi, Stefano Barison +12
Quantum algorithms based on classical processing of individual samples have recently emerged as a promising route to perform large-scale quantum-chemical calculations on pre-fault-…
Imaginary Time Spectral Transforms for Excited State Preparation
D. A. Millar, L. W. Anderson, E. Altamura +4
Excited states of many-body quantum systems play a key role in a wide range of physical and chemical phenomena. Despite this, there is a notable lack of scalable algorithms capable…
Approximate quantum circuit compilation for proton-transfer kinetics on quantum processors
Arseny Kovyrshin, Dilhan Manawadu, Edoardo Altamura +15
Proton transfer reactions are fundamental to many chemical and biological systems, where quantum effects such as tunneling, delocalization, and zero-point motion play key kinetic c…
Encoding molecular structures in quantum machine learning
Choy Boy, Edoardo Altamura, Dilhan Manawadu +3
Quantum machine learning (QML) has great potential for the analysis of chemical datasets. However, conventional quantum data-encoding schemes, such as fingerprint encoding, are gen…
Qiskit Machine Learning: an open-source library for quantum machine learning tasks at scale on quantum hardware and classical simulators
M. Emre Sahin, Edoardo Altamura, Oscar Wallis +6
We present Qiskit Machine Learning (ML), a high-level Python library that combines elements of quantum computing with traditional machine learning. The API abstracts Qiskit's primi…
Evolving a multi-population evolutionary-QAOA on distributed QPUs
Francesca Schiavello, Edoardo Altamura, Ivano Tavernelli +2
Our work integrates an Evolutionary Algorithm (EA) with the Quantum Approximate Optimization Algorithm (QAOA) to optimize ansatz parameters in place of traditional gradient-based m…