Miracle-dz/UniFAR-FTUs huggingface dataset:
Isomorphism theorems for some parabolic initial-boundary value problems in Hörmander spaces

Abstract In Hörmander inner product spaces, we investigate initial-boundary value problems for an arbitrary second order parabolic partial differential equation and the Dirichlet or a general first-order boundary conditions. We prove that the operators corresponding to these problems are isomorphisms between appropriate Hörmander spaces. The regularity of the functions which form these spaces is characterized by a pair of number parameters and a function parameter varying regularly at infinity in the sense of Karamata. Owing to this function parameter, the Hörmander spaces describe the regularity of functions more finely than the anisotropic Sobolev spaces.
Improved Techniques for the Conditional Generative Augmentation of Clinical Audio Data

Data augmentation is a valuable tool for the design of deep learning systems to overcome data limitations and stabilize the training process. Especially in the medical domain, where the collection of large-scale data sets is challenging and expensive due to limited access to patient data, relevant environments, as well as strict regulations, community-curated large-scale public datasets, pretrained models, and advanced data augmentation methods are the main factors for developing reliable systems to improve patient care. However, for the development of medical acoustic sensing systems, an emerging field of research, the community lacks large-scale publicly available data sets and pretrained models. To address the problem of limited data, we propose a conditional generative adversarial neural network-based augmentation method which is able to synthesize mel spectrograms from a learned data distribution of a source data set. In contrast to previously proposed fully convolutional models, the proposed model implements residual Squeeze and Excitation modules in the generator architecture. We show that our method outperforms all classical audio augmentation techniques and previously published generative methods in terms of generated sample quality and a performance improvement of 2.84% of Macro F1-Score for a classifier trained on the augmented data set, an enhancement of $1.14\%$ in relation to previous work. By analyzing the correlation of intermediate feature spaces, we show that the residual Squeeze and Excitation modules help the model to reduce redundancy in the latent features. Therefore, the proposed model advances the state-of-the-art in the augmentation of clinical audio data and improves the data bottleneck for the design of clinical acoustic sensing systems.
Data-Driven Emergency Frequency Control for Multi-Infeed Hybrid AC-DC System

With the continuous development of large-scale complex hybrid AC-DC grids, the fast adjustability of HVDC systems is required by the grid to provide frequency regulation services. This article develops a fully data-driven linear quadratic regulator (LQR) for the HVDC to provide temporal frequency support. The main technical challenge is the complexity and the nonlinearity of multi-infeed hybrid AC-DC (MIDC) systems dynamics that make the LQR intractable. Based on Koopman operator (KO) theory, a Koopman eigenpairs construction method is developed to fit a global linear dynamic model of MIDC systems. Once globally linear representation of uncontrolled system dynamics is obtained offline, the control term is constituted by the gradient of the identified eigenfunctions and the control matrix $\boldsymbol{B}$. In case that $\boldsymbol{B}$ is unknown, we propose a method to identify it based on the verified Koopman eigenfunctions. The active power reference is optimized online for LCC-HVDC in a moving horizon fashion to provide frequency support, with only locally measurable frequency and transmission power. The robustness of the proposed control method against approximation errors of the linear representation in eigenfunction coordinates is analyzed. Simulation results show the effectiveness, robustness and adaptability of the proposed emergency control strategy.
Molecular simulation of bulk and confined (1,1,1,3,3-pentafluorobutane)

Here we present a computational study of the thermodynamic and structural properties of bulk and confined (1,1,1,3,3-pentafuorobutane). The DREIDING force field model has been used in the method of molecular dynamics. In order to study the effect of confinement we have placed (1,1,1,3,3-pentauorobutane) molecules between two graphene walls. In order to study the influence of pore loading on system behavior we have simulated systems of the same size, but with a different number of (1,1,1,3,3-pentauorobutane) molecules, from 200 to 2000. The equations of state at T = 300 K in a wide range of densities for all considered systems had a single peculiarity that is attributed to gas-liquid transition. From the two-dimensional radial distribution functions, density profile and angular distribution we have observed the systems split into layers with amorphization rather than crystallization in them.
Effect of topological length on bound state signatures in a topological nanowire

Majorana bound states (MBS) at the end of nanowires have been proposed as one of the most important candidate for the topological qubits. However, similar tunneling conductance features for both the MBS and Andreev bound states (ABS) have turned out to be a major obstacle in the verification of the presence of MBS in semiconductor-superconductor heterostructures. In this article, we use a protocol to probe properties specific to the MBS and use it to distinguish the topological zero-bias peak (ZBP) from a trivial one. For a scenario involving quantized ZBP in the nanowire, we propose a scheme wherein the length of the topological region in the wire is altered. The tunneling conductance signatures can then be utilized to gauge the impact on the energy of the low-energy states. We show that the topological and trivial ZBP behave differently under our protocol, in particular, the topological ZBP remains robust at zero bias throughout the protocol, while the trivial ZBP splits into two peaks at finite bias. This protocol probes the protection of near zero energy states due to their separable nature, allowing us to distinguish between topological and trivial ZBP.
Intelligent Omni-Surfaces Aided Wireless Communications: Does the Reciprocity Hold?

Intelligent omni-surfaces (IOS) have attracted great attention recently due to its potential to achieve full-dimensional communications by simultaneously reflecting and refracting signals toward both sides of the surface. However, it still remains an open question whether the reciprocity holds between the uplink and downlink channels in the IOS-aided wireless communications. In this work, we first present a physics-compliant IOS-related channel model, based on which the channel reciprocity is investigated. We then demonstrate the angle-dependent electromagnetic response of the IOS element in terms of both incident and departure angles. This serves as the key feature of IOS that drives our analytical results on beam non-reciprocity. Finally, simulation and experimental results are provided to verify our theoretical analyses.
FROM THE COLOR–MAGNITUDE DIAGRAM OF ω CENTAURI AND (SUPER-)ASYMPTOTIC GIANT BRANCH STELLAR MODELS TO A GALACTIC PLANE PASSAGE GAS PURGING CHEMICAL EVOLUTION SCENARIO

We have investigated the color–magnitude diagram of ω Centauri and find that the blue main sequence (bMS) can be reproduced only by models that have a helium abundance in the range Y = 0.35–0.40. To explain the faint subgiant branch of the reddest stars (“MS-a/RG-a” sequence), isochrones for the observed metallicity ([Fe/H] ≈−0.7) appear to require both a high age (∼13 Gyr) and enhanced CNO abundances ([CNO/Fe] ≈0.9). Y ≈ 0.35 must also be assumed in order to counteract the effects of high CNO on turnoff colors and thereby to obtain a good fit to the relatively blue turnoff of this stellar population. This suggests a short chemical evolution period of time (<1 Gyr) for ω Cen. Our intermediate-mass (super-)asymptotic giant branch (AGB) models are able to reproduce the high helium abundances, along with [N/Fe] ∼2 and substantial O depletions if uncertainties in the treatment of convection are fully taken into account. These abundance features distinguish the bMS stars from the dominant [Fe/H] ≈−1.7 population. The most massive super-AGB stellar models (MZAMS ⩾ 6.8 M☉, MHe, core ⩾ 1.245 M☉) predict too large N enhancements, which limit their role in contributing to the extreme populations. In order to address the observed central concentration of stars with He-rich abundance, we show here quantitatively that highly He- and N-enriched AGB ejecta have particularly efficient cooling properties. Based on these results and on the reconstruction of the orbit of ω Cen with respect to the Milky Way, we propose the Galactic plane passage gas purging scenario for the chemical evolution of this cluster. The bMS population formed shortly after the purging of most of the cluster gas as a result of the passage of ω Cen through the Galactic disk (which occurs today every ∼40 Myr for ω Cen) when the initial mass function of the dominant population had “burned” through most of the Type II supernova mass range. AGB stars would eject most of their masses into the gas-depleted cluster through low-velocity winds that sink to the cluster core due to their favorable cooling properties and form the bMS population. In our discussion we follow our model through four passage events, which could explain some key properties not only of the bMS but also of the MS-a/RGB-a and the s-enriched stars.
HAQJSK: Hierarchical-Aligned Quantum Jensen-Shannon Kernels for Graph Classification

In this work, we propose a family of novel quantum kernels, namely the Hierarchical Aligned Quantum Jensen-Shannon Kernels (HAQJSK), for un-attributed graphs. Different from most existing classical graph kernels, the proposed HAQJSK kernels can incorporate hierarchical aligned structure information between graphs and transform graphs of random sizes into fixed-sized aligned graph structures, i.e., the Hierarchical Transitive Aligned Adjacency Matrix of vertices and the Hierarchical Transitive Aligned Density Matrix of the Continuous-Time Quantum Walk (CTQW). For a pair of graphs to hand, the resulting HAQJSK kernels are defined by measuring the Quantum Jensen-Shannon Divergence (QJSD) between their transitive aligned graph structures. We show that the proposed HAQJSK kernels not only reflect richer intrinsic global graph characteristics in terms of the CTQW, but also address the drawback of neglecting structural correspondence information arising in most existing R-convolution kernels. Furthermore, unlike the previous Quantum Jensen-Shannon Kernels associated with the QJSD and the CTQW, the proposed HAQJSK kernels can simultaneously guarantee the properties of permutation invariant and positive definiteness, explaining the theoretical advantages of the HAQJSK kernels. Experiments indicate the effectiveness of the proposed kernels.
A NEW SUB-STELLAR COMPANION AROUND THE YOUNG STAR HD 284149

Even though only a handful of sub-stellar companions have been found via direct imaging, each of these discoveries has had a tremendous impact on our understanding of the star formation process and the physics of cool atmospheres. Young stars are prime targets for direct imaging searches for planets and brown dwarfs due to the favorable brightness contrast expected at such ages and also because it is often possible to derive relatively good age estimates for these primaries. Here we present the direct imaging discovery of HD 284149 b, a 18–50 MJup companion at a projected separation of 400 AU from a young ( Myr) F8 star, with which it shares common proper motion.
Zero-Error Coding for Computing with Encoder Side-Information

—We study the zero-error source coding problem in which an encoder with Side Information (SI) g ( Y ) transmits source symbols X to a decoder. The decoder has SI Y and wants to recover f ( X, Y ) where f, g are deterministic. We exhibit a condition on the source distribution and g that we call “pairwise shared side information”, such that the optimal rate has a single-letter expression. This condition is satisﬁed if every pair of source symbols “share” at least one SI symbol for all output of g . It has a practical interpretation, as Y models a request made by the encoder on an image X , and g ( Y ) corresponds to the type of request. It also has a graph-theoretical interpretation: under “pairwise shared side information” the characteristic graph can be written as a disjoint union of OR products. In the case where the source distribution is full-support, we provide an analytic expression for the optimal rate. We develop an example under “pairwise shared side information”, and we show that the optimal coding scheme outperforms several strategies from the literature.
Redshift drift cosmography with ELT and SKAO measurements

Mapping the expansion history of the universe is a compelling task of physical cosmology, especially in the context of the observational evidence for the recent acceleration of the universe, which demonstrates that canonical theories of cosmology and particle physics are incomplete and that there is new physics still to be discovered. Cosmography is a phenomenological approach to cosmology, where (with some caveats) physical quantities are expanded as a Taylor series in the cosmological redshift $z$, or analogous parameters such as the rescaled redshift $y=z/(1+z)$ or the logarithmic redshift $x=\ln{(1+z)}$. Moreover, the redshift drift of objects following cosmological expansion provides a model-independent observable, detectable by facilities currently under construction, {\it viz.} the Extremely Large Telescope and the Square Kilometre Array Observatory (at least in its full configuration). Here we use simulated redshift drift measurements from the two facilities to carry out an assessment of the cosmological impact and model discriminating power of redshift drift cosmography. We find that the combination of measurements from the two facilities can provide a stringent test of the $\Lambda$CDM paradigm, and that overall the logarithmic based expansions of the spectroscopic velocity drift are the most reliable ones, performing better than analogous expansions in the redshift or the rescaled redshift: the former nominally gives the smaller error bars for the cosmographic coefficients but is vulnerable to biases in the higher order terms (in other words, it is only reliable at low redshifts), while the latter always performs poorly.
Learning to Infer from Unlabeled Data: A Semi-supervised Learning Approach for Robust Natural Language Inference

Natural Language Inference (NLI) or Recognizing Textual Entailment (RTE) aims at predicting the relation between a pair of sentences (premise and hypothesis) as entailment, contradiction or semantic independence. Although deep learning models have shown promising performance for NLI in recent years, they rely on large scale expensive human-annotated datasets. Semi-supervised learning (SSL) is a popular technique for reducing the reliance on human annotation by leveraging unlabeled data for training. However, despite its substantial success on single sentence classification tasks where the challenge in making use of unlabeled data is to assign"good enough"pseudo-labels, for NLI tasks, the nature of unlabeled data is more complex: one of the sentences in the pair (usually the hypothesis) along with the class label are missing from the data and require human annotations, which makes SSL for NLI more challenging. In this paper, we propose a novel way to incorporate unlabeled data in SSL for NLI where we use a conditional language model, BART to generate the hypotheses for the unlabeled sentences (used as premises). Our experiments show that our SSL framework successfully exploits unlabeled data and substantially improves the performance of four NLI datasets in low-resource settings. We release our code at: https://github.com/msadat3/SSL_for_NLI.
Gradient Gibbs measures and fuzzy transformations on trees

We study Gibbsian models of unbounded integer-valued spins on trees which possess a symmetry under height-shift. We develop a theory relating boundary laws to gradient Gibbs measures, which applies also in cases where the corresponding Gibbs measures do not exist. Our results extend the classical theory of Zachary beyond the case of normalizable boundary laws, which implies existence of Gibbs measures, to periodic boundary laws. We provide a construction for classes of tree-automorphism invariant gradient Gibbs measures in terms of mixtures of pinned measures, whose marginals to infinite paths on the tree are random walks in a q-periodic environment. Here the mixture measure is the invariant measure of a finite state Markov chain which arises as a mod-q fuzzy transform, and which governs the correlation decay. The construction applies for example to SOS-models and discrete Gaussian models and delivers a large number of gradient Gibbs measures. We also discuss relations of certain gradient Gibbs measures to Potts and Ising models.
BigCilin: An Automatic Chinese Open-domain Knowledge Graph with Fine-grained Hypernym-Hyponym Relations

This paper presents BigCilin, the first Chinese open-domain knowledge graph with fine-grained hypernym-hyponym relations which are extracted automatically from multiple sources for Chinese named entities. With the fine-grained hypernym-hyponym relations, BigCilin owns flexible semantic hierarchical structure. Since the hypernym-hyponym paths are automatically generated and one entity may have several senses, we provide a path disambiguation solution to map a hypernym-hyponym path of one entity to its one sense on the condition that the path and the sense express the same meaning. In order to conveniently access our BigCilin Knowledge graph, we provide web interface in two ways. One is that it supports querying any Chinese named entity and browsing the extracted hypernym-hyponym paths surro-unding the query entity. The other is that it gives a top-down browsing view to illust-rate the overall hierarchical structure of our BigCilin knowledge graph over some sampled entities.
Quantum classical approach to spin and charge pumping and the ensuing radiation in terahertz spintronics: Example of the ultrafast light-driven Weyl antiferromagnet 
Mn3Sn

The interaction of fs light pulses with magnetic materials has been intensely studied for more than two decades in order to understand ultrafast demagnetization in single magnetic layers or THz emission from their bilayers with nonmagnetic spin-orbit (SO) materials. Here we develop a multiscale quantum-classical formalism -- where conduction electrons are described by quantum master equation of the Lindblad type; classical dynamics of local magnetization is described by the Landau-Lifshitz-Gilbert (LLG) equation; and incoming light is described by classical vector potential while outgoing electromagnetic radiation is computed using Jefimenko equations for retarded electric and magnetic fields -- and apply it a bilayer of antiferromagnetic Weyl semimetal Mn$_3$Sn with noncollinear local magnetization in contact with SO-coupled nonmagnetic material. Our QME+LLG+Jefimenko scheme makes it possible to understand how fs light pulse generates directly spin and charge pumping and electromagnetic radiation by the latter, including both odd and even high harmonics (of the pulse center frequency) up to order $n \le 7$. The directly pumped spin current then exert spin torque on local magnetization whose dynamics, in turn, pumps additional spin and charge currents radiating in the THz range. By switching on and off LLG dynamics and SO couplings, we unravel which microscopic mechanism contribute the most to emitted THz radiation -- charge pumping by local magnetization of Mn$_3$Sn in the presence of its intrinsic SO coupling is far more important than standardly assumed (for other types of magnetic layers) spin pumping and subsequent spin-to-charge conversion within the neighboring nonmagnetic SO-coupled material.
On the Characteristic Curvature Operator

We introduce the Characteristic Curvature as the curvature of the trajectories of the hamiltonian vector field with respect to the normal direction to the isoenergetic surfaces and by using the Second Fundamental Form we relate it to the Classical and Levi Mean Curvature. Then we prove existence and uniqueness of viscosity solutions for the related Dirichlet problem and we show the Lipschitz regularity of the solutions under suitable hypotheses. Moreover we prove a non existence result on the balls when the prescribed curvature is a positive constant. At the end we show that neither Strong Comparison Principle nor Hopf Lemma do hold for the Characteristic Curvature Operator.
Constraining the sources of ultra-high-energy cosmic rays across and above the ankle with the spectrum and composition data measured at the Pierre Auger Observatory

In this work we present the interpretation of the energy spectrum and mass composition data as measured by the Pierre Auger Collaboration above 6 × 1017 eV. We use an astrophysical model with two extragalactic source populations to model the hardening of the cosmic-ray flux at around 5 × 1018 eV (the so-called “ankle” feature) as a transition between these two components. We find our data to be well reproduced if sources above the ankle emit a mixed composition with a hard spectrum and a low rigidity cutoff. The component below the ankle is required to have a very soft spectrum and a mix of protons and intermediate-mass nuclei. The origin of this intermediate-mass component is not well constrained and it could originate from either Galactic or extragalactic sources. To the aim of evaluating our capability to constrain astrophysical models, we discuss the impact on the fit results of the main experimental systematic uncertainties and of the assumptions about quantities affecting the air shower development as well as the propagation and redshift distribution of injected ultra-high-energy cosmic rays (UHECRs).
Can 1D Radiative-equilibrium Models of Faculae Be Used for Calculating Contamination of Transmission Spectra?

The reliable characterization of planetary atmospheres with transmission spectroscopy requires realistic modeling of stellar magnetic features, since features that are attributable to an exoplanet atmosphere could instead stem from the host star’s magnetic activity. Current retrieval algorithms for analyzing transmission spectra rely on intensity contrasts of magnetic features from 1D radiative–convective models. However, magnetic features, especially faculae, are not fully captured by such simplified models. Here we investigate how well such 1D models can reproduce 3D facular contrasts, taking a G2V star as an example. We employ the well-established radiative magnetohydrodynamic code MURaM to obtain three-dimensional simulations of the magnetoconvection and photosphere harboring a local small-scale dynamo. Simulations without additional vertical magnetic fields are taken to describe the quiet solar regions, while simulations with initially 100 G, 200 G, and 300 G vertical magnetic fields are used to represent facular regions of different magnetic flux density. Subsequently, the spectra emergent from the MURaM cubes are calculated with the MPS-ATLAS radiative transfer code. We find that the wavelength dependence of facular contrast from 1D radiative–convective models cannot reproduce facular contrasts obtained from 3D modeling. This has far-reaching consequences for exoplanet characterization using transmission spectroscopy, where accurate knowledge of the host star is essential for unbiased inferences of the planetary atmospheric properties.