About me
I am a Research Fellow in the QML-CVC group, specializing in quantum machine learning and quantum-inspired computational methods. I hold a BSc in Physics from the University of Córdoba and an MSc in Quantum Science and Technology from the Basque Country University.
I earned my PhD at the Institute of Fundamental Physics (IFF-CSIC) in Madrid, where I was part of the Quantum Information and Foundations Group. My doctoral research focused on quantum and quantum-inspired algorithms for numerical analysis, and it was supported by an FPU grant.
My scientific interests include: Quantum Machine Learning, Quantum Computing, Tensor Networks, and Quantum-Inspired Algorithms.
Publications
- Jorge Gidi, Paula García-Molina, Luca Tagliacozzo, and Juan José García-Ripoll. Pseudospectral method for solving PDEs using Ma-trix Product States, arXiv e-prints, arXiv:2409.02916, 2024
- Paula García-Molina, Ana Martin, Mikel Garcia de Andoin, Mikel Sanz. Mitigating noise in digital and digital-analog quantum computation, Communications Physics, 321, 2024
- Juan José Rodríguez-Aldavero, Paula García-Molina, Luca Tagli-acozzo, Juan José García-Ripoll. Chebyshev approximation and composition of functions in matrix product states for quantum-inspired numerical analysis, arXiv e-prints, arXiv:2407.09609, 2024.
- Paula García-Molina, Luca Tagliacozzo, and Juan José García-Ripoll. Global optimization of MPS in quantum-inspired numerical
analysis, arXiv e-prints, arXiv:2303.09430, 2023. - Paula García-Molina, Javier Rodríguez-Mediavilla, and Juan JoséGarcía-Ripoll. Quantum Fourier analysis for multivariate functions and applications to a class of Schrödinger-type partial differential equations, Physical Review A 105 (1), 012433, 2022.
Ph.D. Thesis
PhD Title: Quantum Computing and Quantum-Inspired Numerical Methods: Applications to Problems in Condensed Matter Physics and Other Fields
Supervisor: Prof. Juan José García Ripoll
Doctoral Program: Condensed Matter Physics, Nanoscience, and Biophysics
Institution: Universidad Autónoma de Madrid
Year of Completion: 2025
Software
One of the main contributions of my PhD thesis is the development and extension of the SElf-Explaining Matrix-Product-State (SeeMPS) library. SeeMPS is a Python-based software package, accelerated with Cython, designed for implementing matrix product state (MPS) algorithms. The library emphasizes applications in numerical analysis, bridging techniques from quantum physics and quantum-inspired computing.
GitHub: https://github.com/juanjosegarciaripoll/seemps2
Documentation: https://seemps2.hbar.es/
Contributions to conferences
ORAL CONTRIBUTIONS
Quantum Fourier analysis for multivariate functions and applications to a class of Schrödinger-type partial differential equations
XXXVIII Biennial of Physics of the Spanish Royal Physics Society (RSEF), 2022
Global optimization of MPS in quantum-inspired numerical analysis
Quantum Matter, 2023
Solving partial differential equations on quantum computers
6th Quantum Information Conference in Spain (ICE-6), 2021
Variational quantum algorithm for eigenvalue problems of a class of Schrödinger-type partial differential equations
Machine Learning for Quantum X (MLQX), 2021
Invited Talk: Introducción a la computación cuántica. Implementación de algoritmos cuánticos y aplicaciones
SALMO-REJOTECH, 2022
POSTER CONTRIBUTIONS
SElf-Explaining Matrix-Product-State (SeeMPS) library
Fourth Meeting of the International Quantum Tensor Network, 2024
Global optimization of MPS in quantum-inspired numerical analysis
8th Quantum Information Conference in Spain (ICE-8), 2023
Third Meeting of the International Quantum Tensor Network, 2023
Quantum and quantum-inspired algorithms for numerical analysis
First Meeting of the International Quantum Tensor Network, 2022
Variational quantum algorithm for eigenvalue problems of a class of Schrödinger-type partial differential equations
EQTC, 2021
QCE 2021 IEEE Quantum Week, 2021
Tensor Network Based Approaches to Quantum Many-Body Systems, ICCUB School, 2021
Munich Conference on Quantum Science and Technology (MCQST), 2021
Contact information
E-mail: paula.garcia.molina.phys@gmail.com
LinkedIn: https://www.linkedin.com/in/paula-garc%C3%ADa-molina-538b86199/
Scholar: https://scholar.google.com/citations?user=z98sXO8AAAAJ&hl=es