activity
20242026
collaborators

5 papers

quant-ph2026

Experimental demonstration of the absence of noise-induced barren plateaus using information content landscape analysis

Sebastian Schmitt, Linus Ekstrøm, Alberto Bottarelli +1

Variational quantum algorithms are promising candidates for near-term quantum computing but can be hindered by barren plateaus, where gradients vanish exponentially and optimizatio…

quant-ph2026

Hierarchically discriminating Haar-randomness in quantum states from a black-box device

Xavier Bonet-Monroig, Hao Wang, Adrián Pérez-Salinas

The concept of randomness in quantum computing has been central to constructing benchmarking tools, cryptographic protocols, as well as a proof of beyond-classical computation. Dis…

quant-ph2026

Improving Quantum Multi-Objective Optimization with Archiving and Substitution

Linus Ekstrøm, Takafumi Hosogi, Xavier Bonet-Monroig +3

Finding optimal solutions of conflicting objectives is a daily matter in many industrial applications, with multi-objective optimization trying to find the best solutions to them.…

cs.NE2025

An Adaptive Re-evaluation Method for Evolution Strategy under Additive Noise

Catalin-Viorel Dinu, Yash J. Patel, Xavier Bonet-Monroig +1

The Covariance Matrix Adaptation Evolutionary Strategy (CMA-ES) is one of the most advanced algorithms in numerical black-box optimization. For noisy objective functions, several a…

quant-ph2024

The role of data-induced randomness in quantum machine learning classification tasks

Berta Casas, Xavier Bonet-Monroig, Adrián Pérez-Salinas

Quantum machine learning (QML) has surged as a prominent area of research with the objective to go beyond the capabilities of classical machine learning models. A critical aspect o…