109 citations · 328 across the 10 of their papers we have counts for
11 papers
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…
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.…
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…
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…
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…
Curriculum reinforcement learning for quantum architecture search under hardware errors
Yash J. Patel, Akash Kundu, Mateusz Ostaszewski +3
The key challenge in the noisy intermediate-scale quantum era is finding useful circuits compatible with current device limitations. Variational quantum algorithms (VQAs) offer a p…
Simulating quantum error mitigation in fermionic encodings
Riley W. Chien, Kanav Setia, Xavier Bonet-Monroig +2
The most scalable proposed methods of simulating lattice fermions on noisy quantum computers employ encodings that eliminate nonlocal operators using a constant factor more qubits…
Analyzing variational quantum landscapes with information content
Adrián Pérez-Salinas, Hao Wang, Xavier Bonet-Monroig
The parameters of the quantum circuit in a variational quantum algorithm induce a landscape that contains the relevant information regarding its optimization hardness. In this work…
Performance comparison of optimization methods on variational quantum algorithms
Xavier Bonet-Monroig, Hao Wang, Diederick Vermetten +5
Variational quantum algorithms (VQAs) offer a promising path toward using near-term quantum hardware for applications in academic and industrial research. These algorithms aim to f…
Nearly Optimal Measurement Scheduling for Partial Tomography of Quantum States
Xavier Bonet-Monroig, Ryan Babbush, Thomas E. O'Brien
Many applications of quantum simulation require to prepare and then characterize quantum states by performing an efficient partial tomography to estimate observables corresponding…
Calculating energy derivatives for quantum chemistry on a quantum computer
T. E. O'Brien, B. Senjean, R. Sagastizabal +5
Modeling chemical reactions and complicated molecular systems has been proposed as the `killer application' of a future quantum computer. Accurate calculations of derivatives of mo…