52 citations · 61 across the 7 of their papers we have counts for
7 papers
Do emulated quantum circuits change what CNNs look at? Performance and explainability comparison in medical image classification
Guillermo Rubiños Rodríguez, Martín Ottavianelli, Mateo Alonso +4
Numerous studies have analyzed the use of hybrid quantum-classical convolutional neural networks as a promising alternative to classical deep learning. However, network components…
Error-Mitigation Enabled Multicomponent Quantum Simulations Beyond the Born-Oppenheimer Approximation
Delmar G. A. Cabral, Brandon Allen, Fabijan Pavošević +6
We introduce a multicomponent unitary coupled cluster framework for quantum simulations of molecular systems that incorporate both electronic and nuclear quantum effects beyond the…
Universal Resources for QAOA and Quantum Annealing
Pablo Díez-Valle, Fernando J. Gómez-Ruiz, Diego Porras +1
The Quantum Approximate Optimization Algorithm (QAOA) is a variational ansatz that resembles the Trotterized dynamics of a Quantum Annealing (QA) protocol. This work formalizes thi…
Physics-Inspired Extrapolation for efficient error mitigation and hardware certification
Pablo Díez-Valle, Gaurav Saxena, Jack S. Baker +2
Quantum error mitigation (QEM) is essential for the noisy intermediate-scale quantum era, and will remain relevant for early fault-tolerant quantum computers, where logical error r…
Learning Generalized Statistical Mechanics with Matrix Product States
Pablo Díez-Valle, Fernando Martínez-García, Juan José García-Ripoll +1
We introduce a variational algorithm based on Matrix Product States that is trained by minimizing a generalized free energy defined using Tsallis entropy instead of the standard Gi…
Connection between single-layer Quantum Approximate Optimization Algorithm interferometry and thermal distributions sampling
Pablo Díez-Valle, Diego Porras, Juan José García-Ripoll
The Quantum Approximate Optimization Algorithm (QAOA) is an algorithm originally proposed to find approximate solutions to Combinatorial Optimization problems on quantum computers.…
Quantum variational optimization: The role of entanglement and problem hardness
Pablo Díez-Valle, Diego Porras, Juan José García-Ripoll
Quantum variational optimization has been posed as an alternative to solve optimization problems faster and at a larger scale than what classical methods allow. In this paper we st…