Overview
Software engineering for quantum computing
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In my current role as a Software Engineer at Algorithmiq, I focus on implementing cuttingedge, highperformance, hybrid
quantumclassical algorithms using tensornetwork methods, while also contributing to the development and
dissemination of coding best practices and robust software design within the company.
Lowscaling MBPT algorithms
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My second postdoc was at the TU Dresden, in the LargeScale Theoretical Spectroscopy Emmy
Noether group (LSTS) of Dr.
Dorothea Golze. I was a developer of the FHIaims software package. As such, I advanced highperformance theoretical
methods
for corelevel spectroscopy that are suitable for the new generation of exascale supercomputers. More
specifically, I designed lowscaling GWbased algorithms for the prediction of XPS and XAS spectra. These methods
were implemented in FHIaims and in the GreenX library of the NOMAD CoE. Here is an introductory GW
talk I have given in the LSTS group, and a poster
of my work.
Massively parallel quantum Monte Carlo algorithms
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I did my first postdoc within the TREX CoE, at the Computational Chemical Physics (CCP) group of the
University of Twente. This European project aimed at developing opensource, highperformance quantum chemistry
software tailored to the emerging exascale architectures. As a member of Prof. Claudia Filippi's group, I
contribute to the CornellHolland Abinitio Materials Package (CHAMP). During my time in the project, I have employed innovative programming
techniques like the Implicit Reference to Parameters method (IRP). Here is a QMC lecture I have imparted to the master students of M19 (MRBO02) at the TU Dresden.
Nuclear quantum dynamics and tensor decomposition algorithms
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I obtained my PhD in physics at the University of Lille, under the supervision of Prof.
Daniel Peláez. The subject of my thesis was the development and application of optimization and tensor
decomposition algorithms for representing potential energy surfaces. The later were employed in nuclear quantum
dynamics calculations with the Multiconfiguration Timedependent Hartree (MCTDH) method. I have also prepared an introductory MCTDH talk for the CCP group at the University of Twente.
Publications

PanadésBarrueta, R, L., Duflot, D., Soto, J., MartínezNúñez, E., and Peláez, D. (2024). Automatic determination of the
non‐covalent stable conformations of the NO2‐Pyrene cluster in full dimensionality (81D) using the vdW‐TSSCDS approach,
ChemPhysChem, e202301001.

Azizi, M., Wilhelm, J., Golze, D., Delesma, F. A., PanadésBarrueta, R, L., Rinke, P.,
Giantomassi, M. and Gonze, X. (2024). Validation of the GreenX library timefrequency component
for efficient GW and RPA calculations,
Physical Review B, 109, 245101
(arXiv:2403.06709).

Azizi, M., Wilhelm, J., Golze, D., Giantomassi, M., PanadésBarrueta, R, L. Delesma, F. A., Buccheri, A.,
Gulans, A. Rinke, P., Draxl, C. and Gonze, X. (2023). Timefrequency component of the GreenX library: minimax
grids for efficient
RPA and GW calculations,
Journal of Open Source
Software, 8(90), 5570.

PanadésBarrueta, R. L. Nadoveza, N., Gatti, F., and Peláez, D. (2023). On the sumofproducts
to productofsums transformation between analytical lowrank approximations in finite basis representation,
The European
Physical Journal Special Topics, 18.

PanadésBarrueta, R. L. and Golze, D. (2023). Accelerating corelevel GW calculations by combining the
contour deformation
approach with the analytic continuation of W,
Journal of Chemical
Theory and Computation 19 (16), 5450–5464
(arXiv:2305.15955).

Nadoveza, N., PanadésBarrueta, R. L., Shi, L., Gatti, F., and Peláez, D. (2023). Analytical
highdimensional operators
in canonical polyadic finite basis representation (CPFBR),
The Journal of Chemical
Physics, 158, 114109.

Shepard, S., PanadésBarrueta, R. L., Moroni, S., Scemama A., and Filippi, C. (2022). Double excitation
energies from quantum Monte Carlo using statespecific energy optimization,
Journal of Chemical
Theory and Computation, 18, 11, 6722–6731
(arXiv:2207.12160).
 PanadésBarrueta, R. L. and Peláez, D. (2020). LowRank SumofProducts FiniteBasisRepresentation
(SOPFBR) of Potential Energy Surfaces,
The Journal of Chemical
Physics, 153, 234110.

PanadésBarrueta, R. L., MartínezNúñez, E., & Peláez, D. (2019). Specific Reaction Parameter Multigrid
POTFIT (SRPMGPF): Automatic Generation of SumofProducts Form
Potential Energy Surfaces for Quantum Dynamical Calculations,
Frontiers in
Chemistry, 7, 576.
Included in the book Application of Optimization Algorithms in Chemistry.

PanadésBarrueta, R. L., RubayoSoneira, J., Monnerville, M., Larregaray, P., Dayou, F.,
and RiveroSantamaría, A. (2016). Mean Potential Phase Space Theory study of the Si(3P) + OH(X2Π) → SiO(X1Σ+) +
H(2S) reaction,
Revista Cubana de Física, 33(2), 102117.
Doctoral dissertation
Full quantum simulations of the interaction between atmospheric molecules and model soot particles,
PanadésBarrueta, R. L. (2020).
University of Lille,
theses.fr.