Dr. Mikel Sanz

Ramón y Cajal Researcher

Mikel Sanz is a Ramón y Cajal Researcher and Ikerbasque Fellow at the Department of Physical Chemistry at EHU since 2022.

He obtained his PhD under the supervision of Ignacio Cirac at the Max Planck Institute of Quantum Optics in Munich (Germany). He joined EHU in 2013 and, since 2018, has led the Quantum Computation and Architectures group, which includes a senior researcher, several postdoctoral researchers, PhD students, and junior researchers.

His research focuses on quantum computing and quantum metrology, with strong collaborations with experimental groups in superconducting circuits and quantum photonics, including S. Filipp and K. Fedorov at the Walther-Meissner Institute (Garching, Germany), Y. Nakamura at the University of Tokyo (Japan), and R. Barends at RWTH Aachen (Germany). His group also works on hollow-core antiresonant optical fibers in collaboration with D. Novoa at EHU.

He has participated in numerous national, European, and international research projects and has organized several major scientific events, including Ultra-Strong Light-Matter Interactions (2016), ICE2021, the Workshop on Quantum Computing with Superconducting Circuits (2023), and the biennial meeting of the Spanish Royal Society of Physics in 2024.

He has supervised undergraduate and master’s theses and currently supervises PhD students. He teaches at the master’s level at EHU and has also taught undergraduate courses at TU Munich. He serves as referee for several international journals, is a member of the council of the Spanish Royal Society of Physics, and acts as evaluator for agencies such as the ERC, the Spanish Research Agency, and the U.S. Department of Energy.

Publications

2026
Benchmarking quantum computers: towards a standard performance evaluation approach
Acuaviva,A.; Aguirre,D.; Peña,R.; Sanz,M.
Squeezing-enhanced rotational Doppler metrology
Navarro,J.; Casariego,M.; Molina-Terriza,G.; Egusquiza,Í.L.; Sanz,M.
Tight bound for the total time in digital-analog quantum computation
Garcia de Andoin,M.; Sanz,M.
Robust multimode superconducting circuit optimized for quantum information processing
García-Azorín,P.; Cárdenas-López,F.A.; Huber,G.B.P.; Romero,G.; Werninghaus,M.; Motzoi,F.; Filipp,S.; Sanz,M.
Disentangling Aleatoric and Epistemic Uncertainty in Physics-Informed Neural Networks: Application to Insulation Material Degradation Prognostics
Ramirez,I.; Alcibar,J.; Pino,J.; Sanz,M.; Aizpurua,J.I.
Neutrino telescope event classification on quantum computers
Rodriguez-Grasa,P.; Zhelnin,P.; Argüelles,C.A.; Sanz,M.
2025
Symmetry-enhanced counterdiabatic quantum algorithm for qudits
Bottarelli,A.; De Andoin,M.G.; Chandarana,P.; Paul,K.; Chen,X.; Sanz,M.; Hauke,P.
Resilient superconducting-element design with genetic algorithms
Cárdenas-López,F.A.; Retamal,J.C.; Chen,X.; Romero,G.; Sanz,M.
Satellite image classification with neural quantum kernels
Rodriguez-Grasa, Pablo; Farzan-Rodriguez, Robert; Novelli, Gabriele; Ban, Yue; Sanz, Mikel
Residual-based attention Physics-informed Neural Networks for spatio-temporal ageing assessment of transformers operated in renewable power plants
Ramirez, I.; Pino, J.; Pardo, D.; Sanz, M.; del Rio, L.; Ortiz, A.; Morozovska, K.; Aizpurua, J.I.
Quantum active learning
Ding,Y.; Ban,Y.; Sanz,M.; Martín-Guerrero,J.D.; Chen,X.
Quantum approximated cloning-assisted density matrix exponentiation
Rodriguez-Grasa, P.; Ibarrondo, R.; Gonzalez-Conde, J.; Ban, Y.; Rebentrost, P.; Sanz, M.
Pathways in neutrino physics via quantum-encoded data analysis
Lazar,J.; Giner Olavarrieta,S.; Gatti,G.; Argüelles,C.A.; Sanz,M.
Quantum Carleman linearization efficiency in nonlinear fluid dynamics
Gonzalez-Conde,J.; Lewis,D.; Bharadwaj,S.S.; Sanz,M.
Neural quantum kernels: Training quantum kernels with quantum neural networks
Rodriguez-Grasa,P.; Ban,Y.; Sanz,M.
Entanglement transfer during quantum frequency conversion in gas-filled hollow-core fibers
Gonzalez-Raya, T.; Mena, A.; Lazo, M.; Leggio, L.; Novoa, D.; Sanz, M.
Existence of unbiased estimators in discrete quantum systems
Navarro, J.; Rodríguez, R.R.; Sanz, M.
Bayesian Physics Informed Neural Networks for Reliable Transformer Prognostics
Ramirez,I.; Alcibar,J.; Pino,J.; Sanz,M.; Pardo,D.; Aizpurua,J.I.
2024
Heisenberg-Limited Quantum Lidar for Joint Range and Velocity Estimation
Reichert, M.; Zhuang, Q.; Sanz, M.
Digital-analog quantum computation with arbitrary two-body Hamiltonians
Garcia-De-Andoin, M.; Saiz, Á.; Pérez-Fernández, P.; Lamata, L.; Oregi, I.; Sanz, M.
Efficient quantum amplitude encoding of polynomial functions
Gonzalez-Conde, J.; Watts, T.W.; Rodriguez-Grasa, P.; Sanz, M.
2023
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2022
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2021
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2020
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2019
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2018
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2017
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2016
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2015
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2014
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2012
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2011
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2010
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2009
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2008
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2007
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2006
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2005
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