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Ramón L. Panadés-Barrueta

Publications and source records attributed to Ramón L. Panadés-Barrueta.

4 recordsLinked to original sources

Observable Estimation in the Absence of Classical Verification

The predictive success of quantum mechanics underpins many areas of modern science, even as the exact simulation of large, interacting quantum systems remains beyond the reach of classical computation. This success has been enabled by the remarkable advancement of scalable numerical approximation methods, which often demonstrate practical accuracy despite the absence of formal guarantees. As quantum simulation pushes into regimes where these approximations struggle, a fundamental challenge arises: How can quantum outcomes be trusted when reliable classical benchmarks are unavailable? Here, we establish a framework for the independent validation of quantum estimates in this setting and present evidence that they provide the most credible result among several considered methods, in the absence of an immediately accessible ground-truth solution. We apply our framework to the semi-scrambling dynamics of a physical model that strains several leading classical simulation methods yet remains experimentally accessible, in part through our introduction of the \textit{operator Loschmidt echo}. We systematically design a series of experiments using quantum heuristics that, taken together, test the underlying assumptions and provide strong confidence in the observable estimates obtained from the quantum computer. We then show how this framework can be extended to place accuracy bounds on quantum estimates via careful characterization and manipulation of the device noise, transforming the problem of validating the observable estimation to validating the noise model. These results establish a route towards trusted quantum computation for scientific discovery, independent of classical verification.

quant-ph↗

QMCkl: A Kernel Library for Quantum Monte Carlo Applications

Quantum Monte Carlo (QMC) methods deliver highly accurate electronic structure calculations but are computationally intensive. The quantum Monte Carlo kernel library (QMCkl) provides a modular, portable collection of high-performance kernels implementing the core building blocks of QMC calculations. It offers a C-compatible API, supports the TREXIO standard for input, and covers essential QMC kernels including atomic and molecular orbitals, cusp corrections, Jastrow factor, and the necessary derivatives also to perform variational and structural optimization. QMCkl separates algorithmic development from hardware-specific tuning by combining human-readable reference implementations with performance-optimized kernels that produce identical numerical results. The library enables consistent, efficient, and reproducible simulations across different QMC codes and architectures, and achieves substantial speedups in the evaluation of the energy and its derivatives. Beyond QMC, QMCkl can accelerate deterministic quantum chemistry workflows and visualization tools, promoting cross-code interoperability and simplifying high-performance scientific software development.

physics.chem-ph↗

Validation of the GreenX library time-frequency component for efficient GW and RPA calculations

Electronic structure calculations based on many-body perturbation theory (e.g. GW or the random-phase approximation (RPA)) require function evaluations in the complex time and frequency domain, for example inhomogeneous Fourier transforms or analytic continuation from the imaginary axis to the real axis. For inhomogeneous Fourier transforms, the time-frequency component of the GreenX library provides time-frequency grids that can be utilized in low-scaling RPA and GW implementations. In addition, the adoption of the compact frequency grids provided by our library also reduces the computational overhead in RPA implementations with conventional scaling. In this work, we present low-scaling GW and conventional RPA benchmark calculations using the GreenX grids with different codes (FHI-aims, CP2K and ABINIT) for molecules, two-dimensional materials and solids. Very small integration errors are observed when using 30 time-frequency points for our test cases, namely $<10^{-8}$ eV/electron for the RPA correlation energies, and 10 meV for the GW quasiparticle energies.

physics.comp-ph↗

Accelerating core-level $GW$ calculations by combining the contour deformation approach with the analytic continuation of $W$

In recent years, the $GW$ method has emerged as a reliable tool for computing core-level binding energies. The contour deformation (CD) technique has been established as an efficient, scalable, and numerically stable approach to compute the $GW$ self-energy for deep core excitations. However, core-level $GW$ calculations with CD face the challenge of higher scaling with respect to system size $N$ compared to the conventional quartic scaling in valence state algorithms. In this work, we present the CD-WAC method (CD with $W$ Analytic Continuation), which reduces the scaling of CD applied to the inner shells from $O(N^5)$ to $O(N^4)$ by employing an analytic continuation of the screened Coulomb interaction $W$. Our proposed method retains the numerical accuracy of CD for the computationally challenging deep core case, yielding mean absolute errors $<5$ meV for well-established benchmark sets, such as CORE65, for single-shot $GW$ calculations. More extensive testing for different $GW$ flavors prove the reliability of the method. We have confirmed the theoretical scaling by performing scaling experiments on large acene chains and amorphous carbon clusters, achieving speedups of up to 10x for structures of only 116 atoms. This improvement in computational efficiency paves the way for more accurate and efficient core-level $GW$ calculations on larger and more complex systems.

physics.comp-ph↗