arXiv subjects

J. A. Hernández

Publications and source records attributed to J. A. Hernández.

5 recordsLinked to original sources

arXiv2026

Polyconvex neural-network surrogates with learned paired directional features for anisotropic hyperelastic homogenization

Approximating the effective anisotropic hyperelastic response of a representative volume element (RVE) requires constitutive expressiveness, mechanical consistency, and computational efficiency. This work develops a polyconvex physics-augmented neural network (PANN) construction based on paired directional features whose orientations, stretch powers, and determinant exponents adapt to the RVE response. The features are composed with convex, componentwise nondecreasing cores, realized as an input-convex neural network (ICNN) or an input-convex Kolmogorov-Arnold network (ICKAN). The complete energies satisfy objectivity, an exactly stress-free reference, two-dimensional polyconvexity, and prescribed growth conditions by construction, and nonnegative energy is certified separately for the selected models. On a multicavity and a single-cavity periodic cell, these energies are compared with an Unconstrained energy, trained identically without the curvature and growth constraints, and with three hyperreduced projection-based reduced-order models (HPROMs), which serve as physics-based references. On the first cell, learning the features lowers the stress error sevenfold, and six features suffice on both. The constrained energies remain below one percent in stress error and in the displacement error of a tensile-coupon FE$^2$ application with a full-order reference, whereas the Unconstrained energy and the HPROMs are more accurate inside the data. Beyond the data, however, the Unconstrained energy loses rank-one convexity, and under confined compression it stops below half of the 500 MPa that the constrained energies reach. These results quantify what the guarantees cost in accuracy and what they secure beyond the data.

physics.comp-ph↗

arXiv2025

Field-Induced Magnon Decay, Magnon Shadows, and Roton-like Excitations in the Honeycomb Antiferromagnet YbBr$_3$

Although the search for quantum many-body phenomena in magnetic materials has a strong focus on highly frustrated systems, even unfrustrated quantum magnets show a multitude of unconventional phenomena in their spin excitation spectra. YbBr$_3$ is an excellent realization of the $S = 1/2$ antiferromagnetic Heisenberg model on the honeycomb lattice, and we have performed detailed spectroscopic experiments with both unpolarized and polarized neutrons at all applied magnetic fields up to saturation. We observe extensive excitation continua, which cause strong renormalization and the decay of single magnons at higher fields, while coherent features include field-induced ``shadows'' of the single magnons and the spectacular emergence of a roton-like excitation. To guide and interpret our experiments, we performed systematic calculations by the method of cylinder matrix-product states that provide quantitative agreement with the neutron scattering data and a qualitative benchmark for the spectral signatures of strong quantum fluctuations even in the absence of magnetic frustration.

cond-mat.str-el↗

arXiv2024

Molecular gas budget of strongly magnified low-mass star-forming galaxies at cosmic noon

This study aims to investigate the molecular gas content of strongly magnified low-mass star-forming galaxies around the cosmic noon period ($z\sim2$) through observations of CO emission lines and dust continuum emission, both of which serve as tracers for molecular gas. We observed twelve strongly lensed galaxies with the Atacama Compact Array to detect CO mid-j rotational transitions and dust continuum. Thanks to the strong lensing, we were able to probe the low-mass regime, previously understudied. With a compiled set of observations, we recalibrate empirical relations between star formation rate density and the CO line ratios. Using SED fitting, we derived galaxy properties and performed galaxy stacking to combine the faint signals. In all cases, molecular gas masses were estimated using both tracers. We detected CO emission in three out of 12 galaxies and dust continuum emission in three of them. The obtained molecular gas masses indicate that most of these galaxies ($\rm{M}_* < 10^{10.7}$ $\rm{M}_\odot$) have lower molecular gas fractions and shorter depletion times compared to the expectations from established scaling relations at these redshifts. Several possible explanations for this gas deficit were explored, including uncertainties in mass estimates, effects of low metallicity environments, larger atomic gas reservoirs in low-mass systems, and the possibility that these represent low-mass analogs of "main sequence starburst" galaxies, which are undergoing sustained star formation due to gas compaction despite low overall gas fractions. We conclude that there is a molecular gas deficit at these mass and metallicity regimes. Our results suggest that this deficit is likely due to a significant amount of atomic gas, which our stacking indicates is about 91% of the total gas. However, this estimation might be an upper limit in the case of our galaxies containing CO-dark gas.

astro-ph.GA↗

arXiv2024

A subspace-adaptive weights cubature method with application to the local hyperreduction of parameterized finite element models

This paper is concerned with quadrature/cubature rules able to deal with multiple subspaces of functions, in such a way that the integration points are common for all the subspaces, yet the weights are tailored to each specific subspace. These subspace-adaptive weights cubature rules can be used to accelerate computational mechanics applications requiring efficiently evaluating spatial integrals whose integrand function dynamically switches between multiple pre-computed subspaces. One of such applications is local hyperreduced-order modeling (HROM), in which the solution manifold is approximately represented as a collection of basis matrices, each basis matrix corresponding to a different region in parameter space. We pose the optimization problem and propose two algorithms for its resolution. The first one is a greedy strategy based on an enhanced version of the Empirical Cubature Method (ECM) developed by the authors elsewhere (we call it the Subspace-Adaptive Weights ECM, SAW-ECM for short), while the second method is based on a convexification of the cubature problem so that it can be addressed by linear programming algorithms. We show in a toy problem involving integration of polynomial functions that the SAW-ECM clearly outperforms the other method both in terms of computational cost and optimality. We illustrate the performance of the SAW-ECM in the construction of a local HROMs in a highly nonlinear equilibrium problem (large strains regime). We demonstrate that, provided that the subspace-transition errors are negligible, the error associated to hyperreduction using adaptive weights can be controlled by the truncation tolerances of the SVDs used for determining the basis matrices. The Python source codes of the proposed SAW-ECM are openly accessible in the public repository https://github.com/Rbravo555/localECM.

math-ph↗

arXiv2024

On the impact of VR/AR applications on optical transport networks: First experiments with Meta Quest 3 gaming and conferencing application

With the advent of next-generation AR/VR headsets, many of them with affordable prices, telecom operators have forecasted an explosive growth of traffic in their networks. Penetration of AR/VR services and applications is estimated to grow exponentially in the next few years. This work attempts to shed light on the bandwidth capacity requirements and latency of popular AR/VR applications with four different real experimental settings on the Meta Quest 3 headsets, and their potential impact on the network.

cs.NI↗