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Audio-text contrastive models have become a powerful approach in music representation learning. Despite their empirical success, however, little is known about the influence of key design choices on the quality of music-text representations learnt through this framework. In this work, we expose these design choices within the constraints of limited data and computation budgets, and establish a more solid understanding of their impact grounded in empirical observations along three axes: the choice of base encoders, the level of curation in training data, and the use of text augmentation. We find that data curation is the single most important factor for music-text contrastive training in resource-constrained scenarios. Motivated by this insight, we introduce two novel techniques, Augmented View Dropout and TextSwap, which increase the diversity and descriptiveness of text inputs seen in training. Through our experiments we demonstrate that these are effective at boosting performance across different pre-training regimes, model architectures, and downstream data distributions, without incurring higher computational costs or requiring additional training data., Comment: To appear in the Proceedings of the 25th International Society for Music Information Retrieval Conference (ISMIR 2024)

Open-vocabulary audio-language models, like CLAP, offer a promising approach for zero-shot audio classification (ZSAC) by enabling classification with any arbitrary set of categories specified with natural language prompts. In this paper, we propose a simple but effective method to improve ZSAC with CLAP. Specifically, we shift from the conventional method of using prompts with abstract category labels (e.g., Sound of an organ) to prompts that describe sounds using their inherent descriptive features in a diverse context (e.g.,The organ's deep and resonant tones filled the cathedral.). To achieve this, we first propose ReCLAP, a CLAP model trained with rewritten audio captions for improved understanding of sounds in the wild. These rewritten captions describe each sound event in the original caption using their unique discriminative characteristics. ReCLAP outperforms all baselines on both multi-modal audio-text retrieval and ZSAC. Next, to improve zero-shot audio classification with ReCLAP, we propose prompt augmentation. In contrast to the traditional method of employing hand-written template prompts, we generate custom prompts for each unique label in the dataset. These custom prompts first describe the sound event in the label and then employ them in diverse scenes. Our proposed method improves ReCLAP's performance on ZSAC by 1%-18% and outperforms all baselines by 1% - 55%., Comment: Code and Checkpoints: https://github.com/Sreyan88/ReCLAP

A spring in parallel with an effort source (e.g., electric motor or human muscle) can reduce its energy consumption and effort (i.e., torque or force) depending on the spring stiffness, spring preload, and actuation task. However, selecting the spring stiffness and preload that guarantees effort or energy reduction for an arbitrary set of tasks is a design challenge. This work formulates a convex optimization problem to guarantee that a parallel spring reduces the root-mean-square source effort or energy consumption for multiple tasks. Specifically, we guarantee the benefits across multiple tasks by enforcing a set of convex quadratic constraints in our optimization variables -- the parallel spring stiffness and preload. These quadratic constraints are equivalent to ellipses in the stiffness and preload plane, any combination of stiffness and preload inside the ellipse represents a parallel spring that minimizes effort source or energy consumption with respect to an actuator without a spring. This geometric interpretation intuitively guides the stiffness and preload selection process. We analytically and experimentally prove the convex quadratic function of the spring stiffness and preload. As applications, we analyze the stiffness and preload selection of a parallel spring for a knee exoskeleton using human muscle as the effort source and a prosthetic ankle powered by electric motors. To promote adoption, the optimization and geometric methods are available as supplemental open-source software that can be executed in a web browser., Comment: 10 pages

In this paper, we develop a data-driven approach to generate incomplete LU factorizations of large-scale sparse matrices. The learned approximate factorization is utilized as a preconditioner for the corresponding linear equation system in the GMRES method. Incomplete factorization methods are one of the most commonly applied algebraic preconditioners for sparse linear equation systems and are able to speed up the convergence of Krylov subspace methods. However, they are sensitive to hyper-parameters and might suffer from numerical breakdown or lead to slow convergence when not properly applied. We replace the typically hand-engineered algorithms with a graph neural network based approach that is trained against data to predict an approximate factorization. This allows us to learn preconditioners tailored for a specific problem distribution. We analyze and empirically evaluate different loss functions to train the learned preconditioners and show their effectiveness to decrease the number of GMRES iterations and improve the spectral properties on our synthetic dataset. The code is available at https://github.com/paulhausner/neural-incomplete-factorization., Comment: The first two authors contributed equally, under review. 12 pages, 5 figures

We present a versatile framework that employs Physics-Informed Neural Networks (PINNs) to discover the entropic contribution that leads to the constitutive equation for the extra-stress in rheological models of polymer solutions. In this framework the training of the Neural Network is guided by an evolution equation for the conformation tensor which is GENERIC-compliant. We compare two training methodologies for the data-driven PINN constitutive models: one trained on data from the analytical solution of the Oldroyd-B model under steady-state rheometric flows (PINN-rheometric), and another trained on in-silico data generated from complex flow CFD simulations around a cylinder that use the Oldroyd-B model (PINN-complex). The capacity of the PINN models to provide good predictions are evaluated by comparison with CFD simulations using the underlying Oldroyd-B model as a reference. Both models are capable of predicting flow behavior in transient and complex conditions; however, the PINN-complex model, trained on a broader range of mixed flow data, outperforms the PINN-rheometric model in complex flow scenarios. The geometry agnostic character of our methodology allows us to apply the learned PINN models to flows with different topologies than the ones used for training.

Split-vacancy color centers in diamond are promising solid state platforms for the implementation of photonic quantum technologies. These luminescent defects are commonly fabricated upon low energy ion implantation and subsequent thermal annealing. Their technological uptake will require the availability of reliable methods for the controlled, large scale production of localized individual photon emitters. This task is partially achieved by controlled ion implantation to introduce selected impurities in the host material, and requires the development of challenging beam focusing or collimation procedures coupled with single-ion detection techniques. We report on protocol for the direct optical activation of split-vacancy color centers in diamond via localized processing with continuous wave laser at mW optical powers. We demonstrate the activation of photoluminescent Mg- and Sn-related centers at both the ensemble and single-photon emitter level in ion-implanted, high-purity diamond crystals without further thermal processing. The proposed lithographic method enables the activation of individual color centers at specific positions of a large area sample by means of a relatively inexpensive equipment offering the real-time, in situ monitoring of the process., Comment: 17 pages, 7 figures

Ionic liquids have been suggested as new engineering fluids, namely in the area of heat transfer, as alternatives to current biphenyl and diphenyl oxide, alkylated aromatics and dimethyl polysiloxane oils, which degrade above 200 {\deg}C and pose some environmental problems. Recently, we have proposed 1-ethyl-3-methylimidazolium methanesulfonate, [$C_{2}mim$][$CH_{3}SO_{3}$], as a new heat transfer fluid, because of its thermophysical and toxicological properties. However, there are some interesting points raised in this work, namely the possibility of the existence of liquid metastability below the melting point (303 K) or second order-disorder transitions ($\lambda$-type) before reaching the calorimetric freezing point. This paper analyses in more detail this zone of the phase diagram of the pure fluid, by reporting accurate thermal-conductivity measurements between 278 and 355 K with an estimated uncertainty of 2% at a 95% confidence level. A new value of the melting temperature is also reported, $T_{melt}$ = 307.8 $\pm$ 1 K. Results obtained support liquid metastability behaviour in the solid-phase region and permit the use of this ionic liquid at a heat transfer fluid at temperatures below its melting point. Thermal conductivity models based on Bridgman theory and estimation formulas were also used in this work, failing to predict the experimental data within its uncertainty.

Ionic liquids have proved to be excellent heat transfer fluids and alternatives to common HTFs used in industries for heat exchangers and other heat transfer equipment. However, its industrial utilization depends on the cost per kg of its production, to be competitive for industrial applications with biphenyl and diphenyl oxide, alkylated aromatics, and dimethyl polysiloxane oils, which degrade above 200 {\deg}C and possess some environmental problems. The efficiency of a heat transfer fluid depends on the fundamental thermophysical properties influencing convective heat transfer (density, heat capacity, thermal conductivity, and viscosity), as these properties are necessary to calculate the heat transfer coefficients for different heat exchanger geometries. In Part 1, the thermophysical properties of pure 1-ethyl-3-methylimidazolium methanesulfonate $[C_{2}mim][CH_{3}SO_{3}]$ (CAS no. 145022-45-3), (ECOENG 110), produced by BASF, under the trade name of Basionics ST35, with an assay $\geq$97% with $\leq$0.5% water and $\leq$2% chloride ($Cl^{-}$), were presented, for temperatures slightly below room temperature and up to 355 K. In this paper, we report the thermophysical properties of mixtures of [C2mim][CH3SO3] with water, in the whole concentration range, at $P$ = 0.1 MPa. The properties measured were density and speed of sound (293.15 < $T$/K < 343.15), viscosity, electrical and thermal conductivities, refractive index (293.15 < $T$/K < 353.15), and infinite dilution diffusion coefficient of the ionic liquid in water (298.15 K).

We show that a novel holographic correspondence appears after taking a suitable stringy non-relativistic limit of the AdS$_5$/CFT$_4$ duality. This correspondence relates string theory in String Newton-Cartan AdS$_5\times$S$^5$ with Galilean Electrodynamics with five scalars defined on the Penrose conformal boundary. As a first test, we match the Killing vectors on the string theory side with the on-shell symmetries of the dual field theory., Comment: 7 pages. Concise letter version of our longer paper arXiv:2403.02379. To appear in PRL

Lattice deformations in graphene couple to the low-energy electronic degrees of freedom as pseudo scalar and gauge fields. Using molecular dynamics simulations, we show that the optical component of the displacement field, i.e., the relative motion of different sublattices, contributes at equal order as the acoustic component and effectively screens the pseudo gauge fields. In particular, we consider twisted bilayer graphene and corrugated monolayer graphene. In both cases, optical lattice displacement significantly reduce the overall magnitude of the pseudo magnetic fields. For corrugated graphene, we further show that the corresponding electronic bands are significantly modified by the screened pseudo magnetic field. Previous studies based on continuum elasticity, which ignores this effect, have therefore systematically overestimated the strength of the strain-induced pseudo magnetic field. Our results have important consequences for the interpretation of experiments and design of straintronic applications., Comment: 7 + 14 pages, 4 + 11 figures

This paper deals with time-fractional stochastic Navier-Stokes equations, which are characterized by the coexistence of stochastic noise and a fractional power of the Laplacian. We establish sufficient conditions for the existence and approximate controllability of a unique mild solution to time-fractional stochastic Navier-Stokes equations. Using a fixed point technique, we first demonstrate the existence and uniqueness of a mild solution to the equation under consideration. We then establish approximate controllability results by using the concepts of fractional calculus, semigroup theory, functional analysis and stochastic analysis.

In this paper we study some algebraic properties of the rack structure as well as the representation theory of it, following the ideas given by M. Elhamdadi and E. M. Moutuou in \cite{Elhamdadi}. We establish a correspondence between the irreducible strong representations of a finite and connected rack with the irreducible representation of its finite enveloping group which allows to use techniques of the latter topic in the other setting.

Motivated by the interface between curved spacetime quantum mechanics and applications in space quantum communications, quantum technologies and quantum optics, the Dirac equation is considered with the recently proposed generalized gravitational interaction (Kepler or Coulomb), which includes post-Newtonian (relativistic) and quantum corrections to the classical potential. The general idea in choosing the metric is that the spacetime contributions are contained in an external potential or in an electromagnetic potential which can be considered as a good basis for future studies on space quantum communication. We also discuss several known generalizations of the Coulomb potential within this formulation in terms of certain Heun functions. The impossibility of solving our equation for the quantum-corrected Coulomb terms using known exact or quasi-exact nonperturbative analytical techniques is discussed, and finally the Bethe-ansatz approach is proposed to overcome this challenging problem., Comment: 15 pages

The Duffin-Kemmer-Petiau equation is investigated for spin one bosons with the so-called natural (normal) and unnatural (abnormal) parity states for non-minimal vector interactions. To illustrate the current state of knowledge about the equation, a thorough but concise discussion is made on what can be achieved analytically within this framework for well-known phenomenological interactions, including Coulomb, soft-core, Cornell, Kratzer, and exponential type interactions. In the non-exponential cases, the equation, depending on the chosen interaction, is studied in relation to the confluent, doubly-confluent, and biconfluent Heun functions. Furthermore, to show the need for careful treatment of various parity states, a Kratzer-type potential, such as a generalized Coulomb interaction, is discussed in depth using the Lie algebraic approach, showing the need for careful analysis of abnormal parity states in a fairly explicit way. The energies obtained are discussed using some figures to explicitly show the different regimes, as well as the absence of the Klein paradox. Finally, some directions for future work that would undoubtedly need to be explored in this field are discussed., Comment: 10 pages, 2 figures

Surrogate models combining dimensionality reduction and regression techniques are essential to reduce the need for costly high-fidelity CFD data. New approaches using $\beta$-Variational Autoencoder ($\beta$-VAE) architectures have shown promise in obtaining high-quality low-dimensional representations of high-dimensional flow data while enabling physical interpretation of their latent spaces. We propose a surrogate model based on latent space regression to predict pressure distributions on a transonic wing given the flight conditions: Mach number and angle of attack. The $\beta$-VAE model, enhanced with Principal Component Analysis (PCA), maps high-dimensional data to a low-dimensional latent space, showing a direct correlation with flight conditions. Regularization through $\beta$ requires careful tuning to improve the overall performance, while PCA pre-processing aids in constructing an effective latent space, improving autoencoder training and performance. Gaussian Process Regression is used to predict latent space variables from flight conditions, showing robust behavior independent of $\beta$, and the decoder reconstructs the high-dimensional pressure field data. This pipeline provides insight into unexplored flight conditions. Additionally, a fine-tuning process of the decoder further refines the model, reducing dependency on $\beta$ and enhancing accuracy. The structured latent space, robust regression performance, and significant improvements from fine-tuning collectively create a highly accurate and efficient surrogate model. Our methodology demonstrates the effectiveness of $\beta$-VAEs for aerodynamic surrogate modeling, offering a rapid, cost-effective, and reliable alternative for aerodynamic data prediction., Comment: 18 pages, 12 figures

We study the spin chain model which captures the one-loop spectral problem of a prototypical example of an $\mathcal{N}=2$ SCFT in four dimensions. Up to date, this spin chain model remains unfathomable; the coordinate Bethe Ansatz does not lead to a solution from three magnons on, as the Yang-Baxter equation is not satisfied by the two-magnon scattering coefficients. In this paper, we find a long-range solution to the eigenvalue problem for three magnons. Remarkably, the scattering coefficients of our solution together with the position-dependent corrections, obey an infinite tower of Yang-Baxter equations. Our method of solving the three-magnon problem is interesting in its own right and generalizes the coordinate Bethe Ansatz approach to cases where the permutation symmetry is broken., Comment: 49 pages, 6 figures

Originating in game theory, Shapley values are widely used for explaining a machine learning model's prediction by quantifying the contribution of each feature's value to the prediction. This requires a scalar prediction as in binary classification, whereas a multiclass probabilistic prediction is a discrete probability distribution, living on a multidimensional simplex. In such a multiclass setting the Shapley values are typically computed separately on each class in a one-vs-rest manner, ignoring the compositional nature of the output distribution. In this paper, we introduce Shapley compositions as a well-founded way to properly explain a multiclass probabilistic prediction, using the Aitchison geometry from compositional data analysis. We prove that the Shapley composition is the unique quantity satisfying linearity, symmetry and efficiency on the Aitchison simplex, extending the corresponding axiomatic properties of the standard Shapley value. We demonstrate this proper multiclass treatment in a range of scenarios., Comment: To be published in ECAI2024's proceedings

The Tarantula Nebula in the Large Magellanic Cloud is known for its high star formation activity. At its center lies the young massive star cluster R136, providing a significant amount of the energy that makes the nebula shine so brightly at many wavelengths. Recently, young massive star clusters have been suggested to also efficiently produce high-energy cosmic rays, potentially beyond PeV energies. Here, we report the detection of very-high-energy $\gamma$-ray emission from the direction of R136 with the High Energy Stereoscopic System, achieved through a multicomponent, likelihood-based modeling of the data. This supports the hypothesis that R136 is indeed a very powerful cosmic-ray accelerator. Moreover, from the same analysis, we provide an updated measurement of the $\gamma$-ray emission from 30 Dor C, the only superbubble detected at TeV energies presently. The $\gamma$-ray luminosity above $0.5\,\mathrm{TeV}$ of both sources is $(2-3)\times 10^{35}\,\mathrm{erg}\,\mathrm{s}^{-1}$. This exceeds by more than a factor of 2 the luminosity of HESS J1646$-$458, which is associated with the most massive young star cluster in the Milky Way, Westerlund 1. Furthermore, the $\gamma$-ray emission from each source is extended with a significance of $>3\sigma$ and a Gaussian width of about $30\,\mathrm{pc}$. For 30 Dor C, a connection between the $\gamma$-ray emission and the nonthermal X-ray emission appears likely. Different interpretations of the $\gamma$-ray signal from R136 are discussed., Comment: 10+11 pages, 4+6 figures. Corresponding authors: L. Mohrmann, N. Komin

Having in mind the significance of parity (reflection) in various areas of physics, the single-mode and two-mode Wigner algebras are considered adding to them a reflection operator. The associated deformed $su(2)$ algebra, $su_{\nu}(2)$, and the deformed $so(3)$ algebra, $so_{\nu}(3)$, are constructed for the widely used Jordan-Schwinger and Holstein-Primakoff realizations, commenting on various aspects and ingredients of the formalism for both single-mode and two-mode cases. Finally, in this framework the parity-deformed $so_{\nu}(3)$ representation is analyzed, due to its potential application in the study of qubit and qutrit systems., Comment: 10 pages

In this work, we study a static, spherically charged AdS black hole within a modified cosmological Chaplygin gas (MCG), adhering to the calorific equation of state, as a unified dark fluid model of dark energy and dark matter. We explore the influence of model parameters on several characteristics of the MCG-motivated charged AdS black hole (MCG-AdSBH), including the geodesic structure and some astrophysical phenomena such as null trajectories, shadow silhouettes, light deflection angles, and the determination of greybody bounds. We then discuss how the model parameters affect the Hawking temperature, remnant radius, and evaporation process of the MCG-AdSBH. Quasinormal modes are also investigated using the eikonal approximation method. Constraints on the MCG-AdSBH parameters are derived from EHT observations of M87* and Sgr A*, suggesting that MCG-AdSBH could be strong candidates for astrophysical black hole., Comment: 8 pages, 11 figures, 4 tables

Supernova remnants (SNRs) are believed to be capable of accelerating cosmic rays (CRs) to PeV energies. SNR G106.3+2.7 is a prime PeVatron candidate. It is formed by a head region, where the pulsar J2229+6114 and its boomerang-shaped pulsar wind nebula are located, and a tail region containing SN ejecta. The lack of observed gamma ray emission from the two regions of this SNR has made it difficult to assess which region would be responsible for the PeV CRs. We aim to characterize the very-high-energy (VHE, 0.1-100 TeV) gamma ray emission from SNR G106.3+2.7 by determining the morphology and spectral energy distribution of the region. This is accomplished using 2565 days of data and improved reconstruction algorithms from the HAWC Observatory. We also explore possible gamma ray production mechanisms for different energy ranges. Using a multi-source fitting procedure based on a maximum-likelihood estimation method, we evaluate the complex nature of this region. We determine the morphology, spectrum, and energy range for the source found in the region. Molecular cloud information is also used to create a template and evaluate the HAWC gamma ray spectral properties at ultra-high-energies (UHE, >56 TeV). This will help probe the hadronic nature of the highest-energy emission from the region. We resolve one extended source coincident with all other gamma ray observations of the region. The emission reaches above 100~TeV and its preferred log-parabola shape in the spectrum shows a flux peak in the TeV range. The molecular cloud template fit on the higher energy data reveals that the SNR's energy budget is fully capable of producing a purely hadronic source for UHE gamma rays.

The resonant energy transfer mechanism, responsible for the presence of fractal patterns in the velocity diagrams of kink-antikink scattering, is analyzed for a family of two-component scalar field theory models, in which the kink solutions have two shape modes (one longitudinal and one orthogonal to the kink orbit), in addition to the zero mode, and in which energy redistribution can occur among these three discrete modes. We investigate the scattering between wobbling kinks whose orthogonal shape mode is initially excited, examining how the final velocities, amplitudes, and frequencies depend on the initial excitation amplitude. The differences that this model presents with respect to the $\phi^4$ model and its novel properties are highlighted. This analysis sheds light on the intricate dynamics that arise from the interplay between multiple degrees of freedom in kink scattering processes, offering insights distinct from those observed in simpler models., Comment: 20 pages, 11 figures

Cancer is a disease that takes millions of lives every year. Then, to propose treatments, avoid recurrence, and improve the patient's life quality, we need to analyze this disease from a biophysical perspective with a solid mathematical formulation. In this paper we introduce a novel deterministic model for the evolution of tumors under several conditions (untreated tumors and treated tumors using chemotherapy). Our model is characterized by a second-order differential equation, whose origin and interpretation are presented by exploiting our understanding of fluid mechanics (via continuity equations) and the theory of differential equations. Additionally, we show that our model can fit various experimental data sets. Thus, we prove that our nuanced and general model can describe accelerated growth, as well as cytostatic and cytotoxic effects. All in all, our model opens up a new window in the understanding of tumor evolution and represents a promising connection between the macroscopic and microscopic descriptions of cancer.

We report an observation of ultra-high energy (UHE) gamma rays from the Galactic Center region, using seven years of data collected by the High-Altitude Water Cherenkov (HAWC) Observatory. The HAWC data are best described as a point-like source (HAWC J1746-2856) with a power-law spectrum ($\mathrm{d}N/\mathrm{d}E=\phi(E/26 \,\text{TeV})^{\gamma}$), where $\gamma=-2.88 \pm 0.15_{\text{stat}} - 0.1_{\text{sys}} $ and $\phi=1.5 \times 10^{-15}$ (TeV cm$^{2}$s)$^{-1}$ $\pm\, 0.3_{\text{stat}}\,^{+0.08_{\text{sys}}}_{-0.13_{\text{sys}}}$ extending from 6 to 114 TeV. We find no evidence of a spectral cutoff up to $100$ TeV using HAWC data. Two known point-like gamma-ray sources are spatially coincident with the HAWC gamma-ray excess: Sgr A$^{*}$ (HESS J1745-290) and the Arc (HESS J1746-285). We subtract the known flux contribution of these point sources from the measured flux of HAWC J1746-2856 to exclude their contamination and show that the excess observed by HAWC remains significant ($>$5$\sigma$) with the spectrum extending to $>$100 TeV. Our result supports that these detected UHE gamma rays can originate via hadronic interaction of PeV cosmic-ray protons with the dense ambient gas and confirms the presence of a proton PeVatron at the Galactic Center.

Perceiving and understanding non-speech sounds and non-verbal speech is essential to making decisions that help us interact with our surroundings. In this paper, we propose GAMA, a novel General-purpose Large Audio-Language Model (LALM) with Advanced Audio Understanding and Complex Reasoning Abilities. We build GAMA by integrating an LLM with multiple types of audio representations, including features from a custom Audio Q-Former, a multi-layer aggregator that aggregates features from multiple layers of an audio encoder. We fine-tune GAMA on a large-scale audio-language dataset, which augments it with audio understanding capabilities. Next, we propose CompA-R (Instruction-Tuning for Complex Audio Reasoning), a synthetically generated instruction-tuning (IT) dataset with instructions that require the model to perform complex reasoning on the input audio. We instruction-tune GAMA with CompA-R to endow it with complex reasoning abilities, where we further add a soft prompt as input with high-level semantic evidence by leveraging event tags of the input audio. Finally, we also propose CompA-R-test, a human-labeled evaluation dataset for evaluating the capabilities of LALMs on open-ended audio question-answering that requires complex reasoning. Through automated and expert human evaluations, we show that GAMA outperforms all other LALMs in literature on diverse audio understanding tasks by margins of 1%-84%. Further, GAMA IT-ed on CompA-R proves to be superior in its complex reasoning and instruction following capabilities., Comment: Project Website: https://sreyan88.github.io/gamaaudio/

The Event Horizon Telescope (EHT) imaging of the supermassive black holes at the centers of Messier 87 galaxy and the Milky Way galaxy marks a significant step in observing the photon rings and central brightness depression that define the optical appearance of black holes with an accretion disk scenario. Inspired by this, we take into account a static and spherically symmetric magnetically charged regular black hole (MCRBH) metric characterized by its mass and an additional parameter q, which arises from the coupling of Einstein gravity and nonlinear electrodynamics (NLED) in the weak field approximation. This parameterized model offers a robust foundation for testing the coupling of Einstein gravity and NLED in the weak-field approximation, using the EHT observational results. In this study, we investigate the geodesic motion of particles around the solution, followed by a discussion of its fundamental geometrical characteristics such as scalar invariants. Using null geodesics, we examine how the model parameter influences the behavior of the photon sphere radius and the associated shadow silhouette. We seek constraints on q by applying the EHT results for supermassive black holes M87* and Sgr A*. Furthermore, it is observed that the geodesics of time-like particles are susceptible to variations in q, which can have an impact on the traits of the innermost stable circular orbit and the marginally bounded orbit. Our primary objective is to probe how the free parameter q affects various aspects of the accretion disk surrounding the MCRBH using the thin-disk approximation. Next, we discuss the physical characteristics of the thin accretion disk as well as the observed shadows and rings of the MCRBH, along with its luminosity, across various accretion models. Ultimately, variations in accretion models and the parameter q yield distinct shadow images and optical appearances of the MCRBH., Comment: 31 pages, 2 tables, 16 figures

Recent interest in Large Vision-Language Models (LVLMs) for practical applications is moderated by the significant challenge of hallucination or the inconsistency between the factual information and the generated text. In this paper, we first perform an in-depth analysis of hallucinations and discover several novel insights about how and when LVLMs hallucinate. From our analysis, we show that: (1) The community's efforts have been primarily targeted towards reducing hallucinations related to visual recognition (VR) prompts (e.g., prompts that only require describing the image), thereby ignoring hallucinations for cognitive prompts (e.g., prompts that require additional skills like reasoning on contents of the image). (2) LVLMs lack visual perception, i.e., they can see but not necessarily understand or perceive the input image. We analyze responses to cognitive prompts and show that LVLMs hallucinate due to a perception gap: although LVLMs accurately recognize visual elements in the input image and possess sufficient cognitive skills, they struggle to respond accurately and hallucinate. To overcome this shortcoming, we propose Visual Description Grounded Decoding (VDGD), a simple, robust, and training-free method for alleviating hallucinations. Specifically, we first describe the image and add it as a prefix to the instruction. Next, during auto-regressive decoding, we sample from the plausible candidates according to their KL-Divergence (KLD) to the description, where lower KLD is given higher preference. Experimental results on several benchmarks and LVLMs show that VDGD improves significantly over other baselines in reducing hallucinations. We also propose VaLLu, a benchmark for the comprehensive evaluation of the cognitive capabilities of LVLMs., Comment: Preprint. Under review. Code will be released on paper acceptance

In the past decade, although single-robot perception has made significant advancements, the exploration of multi-robot collaborative perception remains largely unexplored. This involves fusing compressed, intermittent, limited, heterogeneous, and asynchronous environmental information across multiple robots to enhance overall perception, despite challenges like sensor noise, occlusions, and sensor failures. One major hurdle has been the lack of real-world datasets. This paper presents a pioneering and comprehensive real-world multi-robot collaborative perception dataset to boost research in this area. Our dataset leverages the untapped potential of air-ground robot collaboration featuring distinct spatial viewpoints, complementary robot mobilities, coverage ranges, and sensor modalities. It features raw sensor inputs, pose estimation, and optional high-level perception annotation, thus accommodating diverse research interests. Compared to existing datasets predominantly designed for Simultaneous Localization and Mapping (SLAM), our setup ensures a diverse range and adequate overlap of sensor views to facilitate the study of multi-robot collaborative perception algorithms. We demonstrate the value of this dataset qualitatively through multiple collaborative perception tasks. We believe this work will unlock the potential research of high-level scene understanding through multi-modal collaborative perception in multi-robot settings., Comment: 8 pages, 8 figures, 4 tables, Accepted at the IEEE Robotics Automation Letter (RA-L) 2024

The current standard model of cosmology successfully describes a variety of measurements, but the nature of its main ingredients, dark matter and dark energy, remains unknown. Euclid is a medium-class mission in the Cosmic Vision 2015-2025 programme of the European Space Agency (ESA) that will provide high-resolution optical imaging, as well as near-infrared imaging and spectroscopy, over about 14,000 deg^2 of extragalactic sky. In addition to accurate weak lensing and clustering measurements that probe structure formation over half of the age of the Universe, its primary probes for cosmology, these exquisite data will enable a wide range of science. This paper provides a high-level overview of the mission, summarising the survey characteristics, the various data-processing steps, and data products. We also highlight the main science objectives and expected performance., Comment: Accepted for publication in the A&A special issue`Euclid on Sky'

We study the Birman-Schwinger operator for a self-adjoint realisation of the one-dimensional Hamiltonian with the Coulomb potential. We study both the case in which this Hamiltonian is defined on the whole real line and when it is only defined on the positive semiaxis. In both cases, the Birman-Schwinger operator is Hilbert-Schmidt, even though it is not trace class. Then, we have considered some approximations to the Hamiltonian depending on a positive parameter, under given conditions, and proved the convergence of the Birman-Schwinger operators of these approximations to the original Hamiltonian as the parameter goes to zero. Further comments and results have been included., Comment: 17 pages, no figures, no tables

The High-Altitude Water Cherenkov (HAWC) Gamma-Ray Observatory located on the side of the Sierra Negra volcano in Mexico, has been fully operational since 2015. The HAWC collaboration has recently significantly improved their extensive-air-shower reconstruction algorithms, which has notably advanced the observatory performance. The energy resolution for primary gamma rays with energies below 1~TeV was improved by including a noise-suppression algorithm. Corrections have also been made to systematic errors in direction fitting related to the detector and shower plane inclinations, $\mathcal{O}(0.1^{\circ})$ biases in highly inclined showers, as well as enhancements to the core reconstruction. The angular resolution for gamma rays approaching the HAWC array from large zenith angles ($> 37^{\circ}$) has improved by a factor of four at the highest energies ($> 70$~TeV) as compared to previous reconstructions. The inclusion of a lateral distribution function fit to the extensive air shower footprint on the array to separate gamma-ray primaries from cosmic-ray ones, based on the resulting $\chi^{2}$ values, improved the background rejection performance at all inclinations. At large zenith angles, the improvement in significance is a factor of four compared to previous HAWC publications. These enhancements have been verified by observing the Crab Nebula, which is an overhead source for the HAWC Observatory. We show that the sensitivity to Crab-like point sources ($E^{-2.63}$) with locations overhead to 30$^{\circ}$ zenith is comparable or less than 10\% of the Crab Nebula's flux between 2 and 50~TeV. Thanks to these improvements, HAWC can now detect more sources, including the Galactic Center.

New generation networks, based on Cognitive Radio technology, allow dynamic allocation of the spectrum, alleviating spectrum scarcity. These networks also have a resilient potential for dynamic operation for energy saving. In this paper, we present a novel wireless network optimization algorithm for cognitive radio networks based on a cloud sharing-decision mechanism. Three Key Performance Indicators (KPIs) were optimized: spectrum usage, power consumption, and exposure of human beings. For a realistic suburban scenario in Ghent city, Belgium, we determine the optimality among the KPIs. Compared to a traditional Cognitive Radio network design, our optimization algorithm for the cloud-based architecture reduced the network power consumption by 27.5%, the average global exposure by 34.3%, and spectrum usage by 34.5% at the same time. Even for the worst optimization case, our solution performs better than the traditional architecture by 4.8% in terms of network power consumption, 7.3% in terms of spectrum usage and 4.3% in terms of global exposure.

Starting from a general transformation for spherically symmetric metrics where g\_11=-1/g\_00, we analyze coordinates with the common property of conformal flatness at constant solid angle element. Three general possibilities arise: one where tortoise coordinate appears as the unique solution, other that includes Kruskal-Szekeres coordinates as a very specific case, but that also allows other similar transformations, and finally a new set of coordinates with very different properties than the other two. In particular, this represents any causal patch of the spherically symmetric metrics in a compactified form. We analyze some relations, taking the Schwarzschild case as prototype, but also contrasting the cosmological de-Sitter and Anti-de-Sitter solutions for the new proposed pulsating coordinates., Comment: 17 pages, 4 figures. Preliminar result was presented in GRG23 Conference (China, 2022). Find the published version (DOI below), improving interpretations and a result about AdS Spacetime in: https://rdcu.be/dz1ftrdcu.be/dz1ft

We would like to enable a collaborative multiagent team to navigate at long length scales and under uncertainty in real-world environments. In practice, planning complexity scales with the number of agents in the team, with the length scale of the environment, and with environmental uncertainty. Enabling tractable planning requires developing abstract models that can represent complex, high-quality plans. However, such models often abstract away information needed to generate directly-executable plans for real-world agents in real-world environments, as planning in such detail, especially in the presence of real-world uncertainty, would be computationally intractable. In this paper, we describe the deployment of a planning system that used a hierarchy of planners to execute collaborative multiagent navigation tasks in real-world, unknown environments. By developing a planning system that was robust to failures at every level of the planning hierarchy, we enabled the team to complete collaborative navigation tasks, even in the presence of imperfect planning abstractions and real-world uncertainty. We deployed our approach on a Clearpath Husky-Jackal team navigating in a structured outdoor environment, and demonstrated that the system enabled the agents to successfully execute collaborative plans., Comment: Accepted to the IEEE ICRA Workshop on Field Robotics 2024

The supersymmetric connection that exists between the Jaynes-Cummings (JC) and anti-Jaynes Cummings (AJC) models in quantum optics is unraveled entirely. A new method is proposed to obtain the temporal evolution of observables in the AJC model using supersymmetric techniques, providing an overview of its dynamics and extending the calculation to full photon counting statistics. The approach is general and can be applied to determine the high-order cumulants given an initial state. The analysis reveals that engineering the collapse-revival behavior and the quantum properties of the interacting field is possible by controlling the initial state of the atomic subsystem and the corresponding atomic frequency in the AJC model. The substantial potential for applications of supersymmetric techniques in the context of photonic quantum technologies is thus demonstrated., Comment: 12 pages, 4 Figures, comment welcome to: ivanalejandro.bocanegra@uva.es

In the seminal paper (Phys. Rep. 52, 263, 1979), Boris Chirikov showed that the standard map does not exhibit a boundary to chaos, but rather that there are small islands (islets) of stability for arbitrarily large values of the nonlinear perturbation. In this context, he established that the area of the islets in the phase space and the range of parameter values where they exist should decay following power laws with exponents -2 and -1, respectively. In this paper, we carry out a systematic numerical search for islets of stability and we show that the power laws predicted by Chirikov hold. Furthermore, we use high-resolution 3D islets to reveal that the islets volume decays following a similar power law with exponent -3., Comment: 7 pages

Since their introduction, Brauer configuration algebras (BCAs) and their specialized messages have helped research in several fields of mathematics and sciences. This paper deals with a new perspective on using such algebras as a theoretical framework in classical cryptography and music theory. It is proved that some block cyphers define labeled Brauer configuration algebras. Particularly, the dimension of the BCA associated with a ciphertext-only attack of the Vigenere cryptosystem is given by the corresponding key's length and the captured ciphertext's coincidence index. On the other hand, historically, Bach's canons have been considered solved music puzzles. However, due to how Bach posed such canons, the question remains whether their solutions are only limited to musical issues. This paper gives alternative solutions based on the theory of Brauer configuration algebras to some of the puzzle canons proposed by Bach in his Musical Offering (BWV 1079) and the canon \^a 4 Voc: Perpetuus (BWV 1073). Specifically to the canon \^a 6 Voc (BWV 1076), canon 1 \^a2 (also known as the crab canon), and canon \^a4 Quaerendo Invenietis. These solutions are obtained by interpreting such canons as ciphertexts (via route and transposition cyphers) of some specialized Brauer messages. In particular, it is noted that the structure or form of the notes used in such canons can be described via the shape of the most used symbols in Bach's works., Comment: 50 pages

This paper describes the methodology for building a dynamic risk assessment for ADAS (Advanced Driving Assistance Systems) algorithms in parking scenarios, fusing exterior and interior perception for a better understanding of the scene and a more comprehensive risk estimation. This includes the definition of a dynamic risk methodology that depends on the situation from inside and outside the vehicle, the creation of a multi-sensor dataset of risk assessment for ADAS benchmarking purposes, and a Local Dynamic Map (LDM) that fuses data from the exterior and interior of the car to build an LDM-based Dynamic Risk Assessment System (DRAS).

HESS J1813$-$178 is a very-high-energy $\gamma$-ray source spatially coincident with the young and energetic pulsar PSR J1813$-$1749 and thought to be associated with its pulsar wind nebula (PWN). Recently, evidence for extended high-energy emission in the vicinity of the pulsar has been revealed in the Fermi Large Area Telescope (LAT) data. This motivates revisiting the HESS J1813$-$178 region, taking advantage of improved analysis methods and an extended data set. Using data taken by the High Energy Stereoscopic System (H.E.S.S.) experiment and the Fermi-LAT, we aim to describe the $\gamma$-ray emission in the region with a consistent model, to provide insights into its origin. We performed a likelihood-based analysis on 32 hours of H.E.S.S. data and 12 years of Fermi-LAT data and fit a spectro-morphological model to the combined datasets. These results allowed us to develop a physical model for the origin of the observed $\gamma$-ray emission in the region. In addition to the compact very-high-energy $\gamma$-ray emission centered on the pulsar, we find a significant yet previously undetected component along the Galactic plane. With Fermi-LAT data, we confirm extended high-energy emission consistent with the position and elongation of the extended emission observed with H.E.S.S. These results establish a consistent description of the emission in the region from GeV energies to several tens of TeV. This study suggests that HESS J1813$-$178 is associated with a $\gamma$-ray PWN powered by PSR J1813$-$1749. A possible origin of the extended emission component is inverse Compton emission from electrons and positrons that have escaped the confines of the pulsar and form a halo around the PWN., Comment: 13+5 pages, 13+11 figures. Accepted for publication in A&A. Corresponding authors: T.Wach, A.Mitchell, V.Joshi, P.Chamb\'ery

Parametric bivariate copula families have been known to flexibly capture enough various dependence patterns, e.g., either positive or negative dependence in either the lower or upper tails of bivariate distributions. However, to the best of our knowledge, there is not a single parametric model adaptable enough to capture several of these features simultaneously. To address this, we propose a mixture of 4-way rotations of a parametric copula that is able to capture all these features. We illustrate the construction using the Clayton family but the concept is general and can be applied to other families. In order to include dynamic dependence regimes, the approach is extended to a time-dependent sequence of mixture copulas in which the mixture probabilities are allowed to evolve in time via a moving average type of relationship. The properties of the proposed model and its performance are examined using simulated and real data sets.

The Crab Nebula is a unique laboratory for studying the acceleration of electrons and positrons through their non-thermal radiation. Observations of very-high-energy $\gamma$ rays from the Crab Nebula have provided important constraints for modelling its broadband emission. We present the first fully self-consistent analysis of the Crab Nebula's $\gamma$-ray emission between 1 GeV and $\sim$100 TeV, that is, over five orders of magnitude in energy. Using the open-source software package Gammapy, we combined 11.4 yr of data from the Fermi Large Area Telescope and 80 h of High Energy Stereoscopic System (H.E.S.S.) data at the event level and provide a measurement of the spatial extension of the nebula and its energy spectrum. We find evidence for a shrinking of the nebula with increasing $\gamma$-ray energy. Furthermore, we fitted several phenomenological models to the measured data, finding that none of them can fully describe the spatial extension and the spectral energy distribution at the same time. Especially the extension measured at TeV energies appears too large when compared to the X-ray emission. Our measurements probe the structure of the magnetic field between the pulsar wind termination shock and the dust torus, and we conclude that the magnetic field strength decreases with increasing distance from the pulsar. We complement our study with a careful assessment of systematic uncertainties., Comment: 18+6 pages, 15+2 figures. Accepted for publication in A&A. Corresponding authors: M. Meyer, L. Mohrmann, T. Unbehaun. v2: after A&A language editing

Internet censorship and global Internet reachability are prevalent topics of today's Internet. Nonetheless, the impact of network topology and Internet architecture to these aspects of the Internet is under-explored. With the goal of informing policy discussions with an objective basis, we present an approach for evaluating both censorship resilience and global Internet reachability using quantitative network metrics, which are applicable to current BGP/IP networks and also to alternative Internet network architectures. We devise and instantiate the metric on the network topology of multiple countries, comparing the BGP/IP network, an overlay network using a waypoint mechanism for circumventing undesired nodes, and the path-aware Internet architecture SCION. The novelty of the approach resides in providing a metric enabling the analysis of these aspects of the Internet at the routing level, taking into account the innate properties of the routing protocol and architecture. We demonstrate that the Internet topology matters, and strongly influences both censorship resilience and reachability to the global Internet. Finally, we argue that access to multiple paths accompanied with path-awareness could enable a higher level of censorship resilience compared to the current Internet, and reduce the centralization of Internet routing., Comment: Proceedings of the 23rd IFIP Networking Conference

In this letter we use a perturbative approach to find the spectrum of non-relativistic strings in the String Newton-Cartan (SNC) AdS$_5\times$S$^5$ spacetime. We perturb the bosonic sector of the action around a BMN-like folded string solution in light-cone gauge. We find strong evidence that the theory is described by a combination of massive and massless free fields in an anti-de Sitter background by showing that interaction terms up to six scalars vanish after field redefinitions., Comment: 11 pages