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In this paper, we introduce a scanner package enhanced by deep learning (DL) techniques. The proposed package addresses two significant challenges associated with previously developed DL-based methods: slow convergence in high-dimensional scans and the limited generalization of the DL network when mapping random points to the target space. To tackle the first issue, we utilize a similarity learning network that maps sampled points into a representation space. In this space, in-target points are grouped together while out-target points are effectively pushed apart. This approach enhances the scan convergence by refining the representation of sampled points. The second challenge is mitigated by integrating a dynamic sampling strategy. Specifically, we employ a VEGAS mapping to adaptively suggest new points for the DL network while also improving the mapping when more points are collected. Our proposed framework demonstrates substantial gains in both performance and efficiency compared to other scanning methods., Comment: 34 pages, 6 figures and 2 tables

The chaotic nature of ocean motion is a major challenge that hinders the discovery of spatio-temporal current routes that govern the transport of material. Certain material, such as oil spills, pose significant environmental threats and these are enhanced by the fact that they evolve in a chaotic sea, in a way which still nowadays is far from being systematically anticipated. Recently such an oil spill event has affected the Mediterranean coast of several Middle Eastern countries. No accidents were reported for these spills previous to their arrival at the coast, and therefore there was no hint of their origin. Modelling such an event, in which uncertainties are increased due to the lack of information on where and when the spills was produced, stretches available technologies to their limits, and requires the use of novel ideas that help to understand the essential features of oil and tar transport by ocean currents. In this regard Lagrangian Coherent Structures enable us to find order within ocean chaos and provide powerful insights into chaotic events and their relationships over different locations and times like the one addressed. Using the observed locations of the oil impacting the coast at specific times, we seek to determine its original location and the time it was released in the open ocean. We have determined both using a combination of earlier satellite observations and computational modelling of the time evolution. The observed agreement between modeled cases and satellite observations highlights the power of these ideas., Comment: 12 pages, 4 figures

In this work a formalism for proportional generalized double Kerr-Schild ansatz in bigravity is considered, where both metrics are coupled to matter. We study time-dependent and stationary solutions in the framework of the Kerr-Schild classical double copy and obtain the classical Kerr-Schild for the double, single and zeroth copy equations. For the time-dependent case, we use AdS waves solutions in bigravity previously studied in the literature. For the stationary case, we discuss a kind of Pleba\'nski-Demia\'nski solutions in bigravity which permit different masses, NUT parameters, electric and magnetic charges, while the kinematical parameters are the same, and the cosmological constants related. These solution is presented in Pleba\'nski coordinates, and it is noticed that in these coordinates the description simplifies the classical double copy equations allowing a clearer interpretation in terms of the defined fields. We present and interpret some cases for these solutions for the separate matter sector and using the effective metric., Comment: 43 pages, no figures

According to Albert Einstein, gravitation is analogous to an optical medium. Building on this idea, various definitions of the gradient-index (GRIN) medium representing curved spacetime have been proposed; often, these approaches demand advanced knowledge of General Relativity and its associated mathematical methods. This paper introduces a novel approach for generating the form of GRIN media that reproduces the behavior of light in the presence of a Schwarzschild black hole or about the equatorial spacetime of a Kerr black hole. Our approach is based on Noether's theorem that leads to optical Fermat's principle, leveraging the system's symmetry, resulting in a general method for finding GRIN media in a flat spacetime that reproduces the behavior of light in Schwarzschild-like spacetimes where only using photon trajectories as input. This approach is also valid for material particles and provides a complementary understanding of General Relativity.

We present the dynamics of a single harmonically trapped ion interacting with a laser, considering a linear combination of two eigenstates of the system as the initial state. The conditions on the physical parameters that allow for the evolution of the system are discussed. We are able to obtain analytical results even though no approximations are realized and are able to show Rabi oscillations for such initial states., Comment: 8 pages, 5 figures

We develop a machine learning algorithm to turn around stratification in Monte Carlo sampling. We use a different way to divide the domain space of the integrand, based on the height of the function being sampled, similar to what is done in Lebesgue integration. This means that isocontours of the function define regions that can have any shape depending on the behavior of the function. We take advantage of the capacity of neural networks to learn complicated functions in order to predict these complicated divisions and preclassify large samples of the domain space. From this preclassification we can select the required number of points to perform a number of tasks such as variance reduction, integration and even event selection. The network ultimately defines the regions with what it learned and is also used to calculate the multi-dimensional volume of each region., Comment: 44 pages, 17 figures

The custodial Two-Higgs-Doublet-Model with SU(2) gauge fields is studied on the lattice. This model has the same global symmetry structure as the Standard Model but the additional Higgs field enlarges the scalar spectrum and opens the possibility for the occurrence of spontaneous symmetry breaking of the global symmetries. Both the spectrum and the running of the gauge coupling of the custodial 2HDM are studied on a line of constant Standard Model physics with cutoff ranging from 300 to 600 GeV. The lower bounds of the realizable masses for the additional BSM scalar states are found to be well bellow the W boson mass. In fact, for the choice of quartic couplings in this work the estimated lower mass for one of the BSM states is found to be about $\sim 0.2m_{W}$ and independent of the cutoff., Comment: 10 pages, 4 figures; Proceedings of the 41th International Symposium on Lattice Field Theory (LATTICE2024)

The bulk photovoltaic effect (BPVE) offers a promising avenue to surpass the efficiency limitations of current solar cell technology. However, disentangling intrinsic and extrinsic contributions to photocurrent remains a significant challenge. Here, we fabricate high-quality, lateral devices based on atomically thin ReS2 with minimal contact resistance, providing an optimal platform for distinguishing intrinsic bulk photovoltaic signals from other extrinsic photocurrent contributions originating from interfacial effects. Our devices exhibit large bulk photovoltaic performance with intrinsic responsivities of 1 mA/W in the visible range, without the need for external tuning knobs such as strain engineering. Our experimental findings are supported by theoretical calculations. Furthermore, our approach can be extrapolated to investigate the intrinsic BPVE in other non-centrosymmetric van der Waals materials, paving the way for a new generation of efficient light-harvesting devices.

Spin-orbit-coupled Bose-Einstein condensates are a flexible experimental platform to engineer synthetic quantum many-body systems. In particular, they host the so-called stripe phase, an instance of a supersolid state of matter. The peculiar excitation spectrum of the stripe phase, a definite footprint of its supersolidity, has so far remained out of experimental reach. We achieve in situ imaging of the stripes and directly observe both superfluid and crystal excitations. We investigate superfluid hydrodynamics and reveal a stripe compression mode, thus demonstrating that the system possesses a compressible crystalline structure. Through the frequency softening of this mode, we locate the supersolid transition point. Our results establish spin-orbit-coupled supersolids as a platform of choice to investigate supersolidity and its rich dynamics., Comment: 15 pages, 8 figures, includes supplementary materials

The measurement of orbital eccentricity in gravitational-wave (GW) signals will provide unique insights into the astrophysical origin of binary systems, while ignoring eccentricity in waveform models could introduce significant biases in parameter estimation and tests of General Relativity. Upcoming LIGO-Virgo-KAGRA observing runs are expected to detect a subpopulation of eccentric signals, making it vital to develop accurate waveform models for eccentric orbits. Here, employing recent analytical results through the third post-Newtonian order, we develop SEOBNRv5EHM: a new time-domain, effective-one-body, multipolar waveform model for eccentric binary black holes with spins aligned (or antialigned) with the orbital angular momentum. Besides the dominant (2,2) mode, the model includes the (2,1), (3,3), (3,2), (4,4) and (4,3) modes. We validate the model's accuracy by computing its unfaithfulness against 99 (28 public and 71 private) eccentric numerical-relativity (NR) simulations, produced by the Simulating eXtreme Spacetimes Collaboration. Importantly, for NR waveforms with initial GW eccentricities below 0.5, the maximum (2,2)-mode unfaithfulness across the total mass range 20-200 $M_\odot$ is consistently below or close to $1 \%$, with a median value of $ \sim 0.02 \% $, reflecting an accuracy improvement of approximately an order of magnitude compared to the previous-generation SEOBNRv4EHM and the state-of-the-art TEOBResumS-Dal\'i eccentric model. In the quasi-circular-orbit limit, SEOBNRv5EHM is in excellent agreement with the highly accurate SEOBNRv5HM model. The accuracy, robustness, and speed of SEOBNRv5EHM make it suitable for data analysis and astrophysical studies. We demonstrate this by performing a set of recovery studies of synthetic NR-signal injections, and parameter-estimation analyses of the events GW150914 and GW190521, which we find to have no eccentricity signatures., Comment: 44 pages, 16 figures

We present the polarization spectra of the nucleus of 3C 270. We confirm that the polarization angle of both the continuum and the emission lines are close to perpendicular to the jet direction after careful correction of interstellar polarization, which indicates polar scattering. The Stokes flux spectrum resembles the total flux spectrum, with no need for a broad component from the Broad Line Region. Over 94% of the Seyfert I type broad line profile would be significantly detected if present in our polarized flux spectrum. We favor that we are mostly likely observing beamed synchrotron instead of Big Blue Bump, and the innermost Narrow Line Region through reflection. This makes 3C 270 the third known case, after NGC 4258 and Centaurus A, where only narrow lines (and beamed continuum, if present) are scattered, with no evidence of an underlying Big Blue Bump., Comment: The authors of this paper have not yet reached full consensus on certain aspects of the interpretation, but we want to emphasize that the data presented is completely accurate and reliable

In this paper, we prove that the Ekeland-Hofer capacities coincide on all star-shaped domain in $\mathbb{R}^{2n}$ with the equivariant symplectic homology capacities defined by the first author and Hutchings, answering a 35 years old question. Along the way, we prove that given a Hamiltonian $H$, the (equivariant) Floer homology of $H$ is chain-complex isomorphic to the Morse homology of the Hamiltonian action functional., Comment: 33 pages

Grasping is essential in robotic manipulation, yet challenging due to object and gripper diversity and real-world complexities. Traditional analytic approaches often have long optimization times, while data-driven methods struggle with unseen objects. This paper formulates the problem as a rigid shape matching between gripper and object, which optimizes with Annealed Stein Iterative Closest Point (AS-ICP) and leverages GPU-based parallelization. By incorporating the gripper's tool center point and the object's center of mass into the cost function and using a signed distance field of the gripper for collision checking, our method achieves robust grasps with low computational time. Experiments with the Kinova KG3 gripper show an 87.3% success rate and 0.926 s computation time across various objects and settings, highlighting its potential for real-world applications.

Recent gain in popularity of AI conversational agents has led to their increased use for improving productivity and supporting well-being. While previous research has aimed to understand the risks associated with interactions with AI conversational agents, these studies often fall short in capturing the lived experiences. Additionally, psychological risks have often been presented as a sub-category within broader AI-related risks in past taxonomy works, leading to under-representation of the impact of psychological risks of AI use. To address these challenges, our work presents a novel risk taxonomy focusing on psychological risks of using AI gathered through lived experience of individuals. We employed a mixed-method approach, involving a comprehensive survey with 283 individuals with lived mental health experience and workshops involving lived experience experts to develop a psychological risk taxonomy. Our taxonomy features 19 AI behaviors, 21 negative psychological impacts, and 15 contexts related to individuals. Additionally, we propose a novel multi-path vignette based framework for understanding the complex interplay between AI behaviors, psychological impacts, and individual user contexts. Finally, based on the feedback obtained from the workshop sessions, we present design recommendations for developing safer and more robust AI agents. Our work offers an in-depth understanding of the psychological risks associated with AI conversational agents and provides actionable recommendations for policymakers, researchers, and developers., Comment: 25 pages, 2 figures, 4 tables; Corrected typos

We report on the successful design and fabrication of optical modules using a 50 micron pitch polymer waveguide interface, integrated for low loss, high density optical data transfer with very low space requirements on a Si photonics die. This prototype module meets JEDEC reliability standards and promises to increase the number of optical fibers that can be connected at the edge of a chip, a measure known as beachfront density, by six times compared to state of the art technology. Scalability of the polymer waveguide to less than 20 micron pitch stands to improve the bandwidth density upwards of 10 Tbps/mm.

Object detection in art is a valuable tool for the digital humanities, as it allows for faster identification of objects in artistic and historical images compared to humans. However, annotating such images poses significant challenges due to the need for specialized domain expertise. We present NADA (no annotations for detection in art), a pipeline that leverages diffusion models' art-related knowledge for object detection in paintings without the need for full bounding box supervision. Our method, which supports both weakly-supervised and zero-shot scenarios and does not require any fine-tuning of its pretrained components, consists of a class proposer based on large vision-language models and a class-conditioned detector based on Stable Diffusion. NADA is evaluated on two artwork datasets, ArtDL 2.0 and IconArt, outperforming prior work in weakly-supervised detection, while being the first work for zero-shot object detection in art. Code is available at https://github.com/patrick-john-ramos/nada, Comment: 8 pages, 6 figures, to be published in WACV 2025

The interplay between ion beam modification techniques in the MeV range and the controlled generation of negatively charged nitrogen-vacancy (NV-) centers in nitrogen-doped synthetic diamond crystals is explored. An experimental approach employing both light (H+) and heavy (Br+6) ions was followed to assess their respective impacts on the creation of NV- centers, using different ion energies or fluences to generate varying amounts of vacancies. Photoluminescence spectroscopy was applied to characterize NV- and neutral NV0 centers. Initially, no NV centers were detected post-irradiation, despite the presence of substitutional nitrogen and vacancies. However, after annealing at 800C (and in some cases at 900C), most samples exhibited a high density of NV0 and especially NV- centers. This demonstrates that thermal treatment is essential for vacancy-nitrogen recombination and NV- formation, often through electron capture from nearby nitrogen atoms. Notably, we achieved high NV- densities without graphitization, which is essential for preserving the material's properties for quantum applications. This study underscores and quantifies the effectiveness of MeV-range ions in controlling vacancy distributions and highlights their potential for optimizing NV- center formation to enhance the sensitivity of diamond-based quantum magnetic sensors., Comment: 21 pages, 10 figures, 3 tables

We present low-temperature specific heat (Cp) measurements of a monoclinic P2_{1}/c crystal formed by quasiplanar molecules of tetrachloro-m-xylene. The dynamic disorder frozen at low-temperature of the asymmetric unit (formed by a half molecule) consists of reorientation around a three-fold-like axis perpendicular to the benzene ring. Such a minimal disorder gives rise to typical glassy anomalies, as a linear in contribution in Cp ascribed to two-level systems and a broad maximum around 6.6 K in Cp/T^3 (the boson peak). We discuss these results in the framework of other quasiplanar molecular crystals with different accountable number of in-plane molecular orientations We find that the density of two-level systems does not correlate with the degree of orientational disorder. Rather, it is the molecular asymmetry that seems to play a relevant role in the thermal anomalies. Furthermore, we discuss the suggested correlation between the boson peak and Debye temperatures. We find that a linear correlation between the boson peak and Debye temperatures holds for many -- but not all -- structural glasses and strikingly holds even better for some disordered crystals, including our studied quasiplanar molecular crystals., Comment: 27 pages, 11 figures, 4 tables

Let $\mathcal{C}$ be a positive integer cone and $k\in \mathcal{C}$. A $\mathcal{C}$-semigroup $S$ is $k$-positioned if for every $h\in \mathcal{C}\setminus S$ we have that $k-h$ belongs to $S$. In this work, we focus on this family of semigroups and introduce primary positioned $\mathcal{C}$-semigroups, characterizing a subfamily of them through the perspective of irreducibility. Furthermore, we provide some procedures to compute all such semigroups, describing a family of graphs containing all the primary positioned $\mathcal{C}$-semigroups for a fixed $k\in \mathcal{C}$.

The advent of large-scale quantum computers implies that our existing public-key cryptography infrastructure has become insecure. That means that the privacy of many mobile applications involving dynamic peer groups, such as multicast messaging or pay-per-view, could be compromised. In this work we propose a generalization of the well known group key exchange protocol proposed by Burmester and Desmedt to the non-abelian case by the use of finite group actions and we prove that the presented protocol is secure in Katz and Yung's model., Comment: 18 pages

In 1989 H.Karcher rewrote the theory of elliptic functions through an approach that is much more geometrical than analytical. Therewith he obtained an optimal control over the behaviour and image values of these functions, which allowed for their broad application in minimal surfaces. Our work is devoted to presenting the theory of elliptic functions according to Karcher's approach, as well as some of its applications in minimal surfaces. The original publication was a mini-course that can be downloaded at https://www.dm.ufscar.br/profs/lobos/IIEPG, Comment: in Portuguese language

We study for the first time the $\textit{complete}$ parameter space of a bulk extra-dimensional axion. We find novel regimes where no single KK mode is produced along the canonical QCD axion line, and instead, it is maximally deviated along with several other axions that constitute a multiple solution to the strong CP problem. In the most common extra-dimensional models, namely for flat and curved Randall-Sundrum scenarios, and assuming that all Peccei-Quinn breaking comes from QCD, we find that these solutions are however subject to tight phenomenological constraints. In light of these results, only one -- canonical -- pattern can be expected from a bulk axion in one or more extra spacetime dimensions. As a byproduct, we generalize the axions eigenvalue and eigenvector equations for an arbitrary number of spacetime dimensions and compactifications., Comment: 14 pages, 3 figures

Constructing valid confidence sets is a crucial task in statistical inference, yet traditional methods often face challenges when dealing with complex models or limited observed sample sizes. These challenges are frequently encountered in modern applications, such as Likelihood-Free Inference (LFI). In these settings, confidence sets may fail to maintain a confidence level close to the nominal value. In this paper, we introduce two novel methods, TRUST and TRUST++, for calibrating confidence sets to achieve distribution-free conditional coverage. These methods rely entirely on simulated data from the statistical model to perform calibration. Leveraging insights from conformal prediction techniques adapted to the statistical inference context, our methods ensure both finite-sample local coverage and asymptotic conditional coverage as the number of simulations increases, even if n is small. They effectively handle nuisance parameters and provide computationally efficient uncertainty quantification for the estimated confidence sets. This allows users to assess whether additional simulations are necessary for robust inference. Through theoretical analysis and experiments on models with both tractable and intractable likelihoods, we demonstrate that our methods outperform existing approaches, particularly in small-sample regimes. This work bridges the gap between conformal prediction and statistical inference, offering practical tools for constructing valid confidence sets in complex models.

The detailed feeding and feedback mechanisms of Active Galactic Nuclei (AGN) are not yet well known. For low-luminosity and obscured AGN, as well as late-type galaxies, determining the central black hole (BH) masses is challenging. Our goal with the GATOS sample is to study circum-nuclear regions and better estimate BH masses with more precision than scaling relations offer. Using ALMA's high spatial resolution, we resolve CO(3-2) emissions within ~100 pc around the supermassive black hole (SMBH) in seven GATOS galaxies to estimate their BH masses when sufficient gas is present. We study seven bright ($L_{AGN}(14-150\mathrm{keV}) \geq 10^{42}\mathrm{erg/s}$), nearby (<28 Mpc) galaxies from the GATOS core sample. For comparison, we searched the literature for previous BH mass estimates and made additional calculations using the \mbh~ - $\sigma$ relation and the fundamental plane of BH activity. We developed a supervised machine learning method to estimate BH masses from position-velocity diagrams or first-moment maps using ALMA CO(3-2) observations. Numerical simulations with a wide range of parameters created the training, validation, and test sets. Seven galaxies provided enough gas for BH mass estimations: NGC4388, NGC5506, NGC5643, NGC6300, NGC7314, NGC7465, and NGC~7582. Our BH masses, ranging from 6.39 to 7.18 log$(M_{BH}/M_\odot)$, align with previous estimates. Additionally, our machine learning method provides robust error estimations with confidence intervals and offers greater potential than scaling relations. This work is a first step toward an automated \mbh estimation method using machine learning.

We present a 19.7 - 214 $\mu$m imaging atlas of local (4 - 181 Mpc; median 43 Mpc) active galactic nuclei (AGN) observed with FORCAST and HAWC+ on board the SOFIA telescope with angular resolutions ~ 3"- 20". This atlas comprises 22 Seyferts (17 Type 2 and 5 Type 1) with a total of 69 images, 41 of which have not been previously published. The AGN span a range of luminosities of log$_{10}$ ($L_{bol}$ [erg/s]) = [42, 46] with a median of log$_{10}$ ($L_{bol}$ [erg/s]) = 44.1 $\pm$ 1.0. We provide total fluxes of our sample using aperture photometry for point source objects and a 2-D Gaussian fitting for objects with extended host galaxy emission, which was used to estimate the unresolved nuclear component. Most galaxies in our sample are point-like sources, however, four sources (Centaurus A, Circinus, NGC 1068, and NGC 4388) show extended emission in all wavelengths. The 30 - 40 $\mu$m extended emission in NGC 4388 is coincident with the narrow line region at PA ~ 50$^{\circ}$, while the dusty extension at longer wavelengths arises from the host galaxy at PA ~ 90$^{\circ}$. Our new observations allow us to construct the best sampled spectral energy distributions (SEDs) available between 30 - 500 $\mu$m for a sample of nearby AGN. We estimate that the average peak wavelength of the nuclear SEDs is ~ 40 $\mu$m in $\nu$F$_{\nu}$ , which we associate with an unresolved extended dusty region heated by the AGN., Comment: 27 pages, 15 figures

Conversational systems are now capable of producing impressive and generally relevant responses. However, we have no visibility nor control of the socio-emotional strategies behind state-of-the-art Large Language Models (LLMs), which poses a problem in terms of their transparency and thus their trustworthiness for critical applications. Another issue is that current automated metrics are not able to properly evaluate the quality of generated responses beyond the dataset's ground truth. In this paper, we propose a neural architecture that includes an intermediate step in planning socio-emotional strategies before response generation. We compare the performance of open-source baseline LLMs to the outputs of these same models augmented with our planning module. We also contrast the outputs obtained from automated metrics and evaluation results provided by human annotators. We describe a novel evaluation protocol that includes a coarse-grained consistency evaluation, as well as a finer-grained annotation of the responses on various social and emotional criteria. Our study shows that predicting a sequence of expected strategy labels and using this sequence to generate a response yields better results than a direct end-to-end generation scheme. It also highlights the divergences and the limits of current evaluation metrics for generated content. The code for the annotation platform and the annotated data are made publicly available for the evaluation of future models.

We present the notion of complexity $\text{C}(G,H)$ of two graphs $G$ and $H$, along with basic results for this numerical invariant. This was motivated by the Data Migration Problem. This invariant $\text{C}(G,H)$ is a number that measures \aspas{complexity} of the question: when is there a homomorphism $G\to H$? More precisely, $\text{C}(G,H)$ is the minimal number $\ell$ such that there are $\ell$ different subgraphs $G_j$ of $G$ such that $G=G_1\cup\cdots\cup G_\ell$ and for each $G_j$, there is a homomorphism $G_j\to H$. The complexity $\text{C}(-,-)$ is a graph invariant. Additionally, $\text{C}(G,H)$ provides a obstruction to the existence of homomorphisms. We explore the sub-additivity of the complexity $\text{C}(-,-)$ and study the complexity for products. We present a relation between $\text{C}(G,H)$ and the chromatic numbers $\chi(G),\chi(H)$. Specifically, we present a lower and an upper bounds for the complexity in terms of the chromatic number. We compute $\text{C}(K_j,K_i)$ and demonstrate a triangular inequality. Furthermore, we apply our theory to solve an example related to Data Migration. A primary objective of this paper is to present a well-defined methodology that can help manage the complexity of data migration tasks., Comment: 21 pages. Comments are welcome

We prove a sharp quantitative version of recent Faber-Krahn inequalities for the continuous Wavelet transforms associated to a certain family of Cauchy wavelet windows . Our results are uniform on the parameters of the family of Cauchy wavelets, and asymptotically sharp in both directions. As a corollary of our results, we are able to recover not only the original result for the short-time Fourier transform as a limiting procedure, but also a new concentration result for functions in Hardy spaces. This is a completely novel result about optimal concentration of Poisson extensions, and our proof automatically comes with a sharp stability version of that inequality. Our techniques highlight the intertwining of geometric and complex-analytic arguments involved in the context of concentration inequalities. In particular, in the process of deriving uniform results, we obtain a refinement over the proof of a previous result by the first and fourth authors together with A. Guerra and P. Tilli, further improving the current understanding of the geometry of near extremals in all contexts under consideration., Comment: 43 pages

It is generally assumed that all cells in models of the electrical behavior of cardiac tissue have the same properties. However, there are differences in cardiac cells that are not well characterized but cause spatial heterogeneity of the electrical properties in tissue. Optical mapping can be used to obtain experimental data from cardiac surfaces at high spatial resolution. Variations in model parameters can be defined on a coarser grid than considering each single pixel, which would allow a representation of heterogeneous tissue to be obtained more efficiently. Here, we address how coarse the parameterization grid can be while still obtaining accurate results for complicated dynamical states of spatially discordant alternans. We use the Fenton-Karma model with heterogeneity included as a smooth nonlinear gradient over space for more model parameters. To obtain the more efficient representations, we set parameter values everywhere in space based on the assumption that the exact parameter values are known at the points of the coarser grid; we assume the parameter values could be obtained from experimental data. We assign parameter values in space by fitting either a piecewise-constant or piecewise-linear function to the spatially coarse known data. We wish to identify the maximal grid spacing of such points to obtain good agreement with spatial profiles of action potential duration during complex states. We find that coarse grid spacing of about 1.0-1.6 cm generally results in spatial profiles that agree well with the true profiles for a range of different model parameters and different functions of those parameters over space. In addition, the piecewise-constant and piecewise-linear functions perform similarly. Our results to date suggest that matching the output of models of cardiac tissue to heterogeneous experimental data can be done efficiently, even during complex dynamical states., Comment: 12 pages, 10 figures

Nonreciprocal coupling can alter the transport properties of material media, producing striking phenomena such as unidirectional amplification of waves, boundary modes, or self-assembled pattern formation. It is responsible for nonlinear convective instabilities in nonlinear systems that drive topological dissipative solitons in a single direction, producing a lossless information transmission. Considering fluctuations, which are intrinsic to every macroscopic dynamical system, noise-sustained structures emerge permanently in time. Here, we study arrays of nonreciprocally coupled bistable systems exhibiting noise-sustained topological phase wall (or soliton) dynamics. The bifurcations between different steady states are analytically addressed, and the properties of the noise-sustained states are unveiled as a function of the reciprocal and nonreciprocal coupling parameters. Furthermore, we study critical points where the structures' characteristic size diverges with different power law exponents. Our numerical results agree with the theoretical findings.

Nonlinear waves are a robust phenomenon observed in complex systems ranging from mechanics to ecology. Fronts are fundamental due to their robustness against perturbations and capacity to propagate one state over another. Controlling and understanding these waves is then fundamental to make use of their properties. Their velocity is one of the most important properties, which can be theoretically computed only in limited conditions of the dynamical system, and it becomes elusive in the presence of spatial discreteness and nonreciprocal coupling. This work reveals that fronts in discrete systems can be treated as rigid objects when analyzing their whole trajectory instead of the instantaneous one. Then, a relationship between the front velocity and its found shape is given. The formula provides insight into fronts' long-observed properties and agrees with the approximative and parameterized methods described in the literature. Numerical simulations show perfect agreement with the theory.

We discuss the effects induced by the potential presence of hyperons in hot and ultra-dense matter within the context of neutron star mergers. Specifically, we address their effect on the dominant post-merger frequency of the gravitational waves. By performing a simulation campaign with a large sample of hyperonic and nucleonic equations of state, we explicitly show that the unique thermal behavior of hyperonic equations of state results in a systematic shift of the dominant frequency with respect to the nucleonic reference level. The predicted shift has values of up to 150 Hz, and it could be detected with the newest generations of gravitational wave detectors. Thus this approach opens a new path for signaling the presence of hyperons in neutron star remnant matter., Comment: 6 pages, 2 figures, Contribution to the proceedings of the 10th International Conference on Quarks and Nuclear Physics (QNP2024)

Existing navigation systems mostly consider "success" when the robot reaches within 1m radius to a goal. This precision is insufficient for emerging applications where the robot needs to be positioned precisely relative to an object for downstream tasks, such as docking, inspection, and manipulation. To this end, we design and implement Aim-My-Robot (AMR), a local navigation system that enables a robot to reach any object in its vicinity at the desired relative pose, with centimeter-level precision. AMR achieves high precision and robustness by leveraging multi-modal perception, precise action prediction, and is trained on large-scale photorealistic data generated in simulation. AMR shows strong sim2real transfer and can adapt to different robot kinematics and unseen objects with little to no fine-tuning.

We study an extension to directed graphs of the parameter called the $b$-chromatic number of a graph in terms of acyclic vertex colorings: the dib-chromatic number. We give general bounds for this parameter. We also show some results about tournaments and regular digraphs., Comment: 10 pages, 1 figure

Large Language Models (LLMs) have become integral to various software engineering tasks, including code generation, bug detection, and repair. To evaluate model performance in these domains, numerous bug benchmarks containing real-world bugs from software projects have been developed. However, a growing concern within the software engineering community is that these benchmarks may not reliably reflect true LLM performance due to the risk of data leakage. Despite this concern, limited research has been conducted to quantify the impact of potential leakage. In this paper, we systematically evaluate popular LLMs to assess their susceptibility to data leakage from widely used bug benchmarks. To identify potential leakage, we use multiple metrics, including a study of benchmark membership within commonly used training datasets, as well as analyses of negative log-likelihood and n-gram accuracy. Our findings show that certain models, in particular codegen-multi, exhibit significant evidence of memorization in widely used benchmarks like Defects4J, while newer models trained on larger datasets like LLaMa 3.1 exhibit limited signs of leakage. These results highlight the need for careful benchmark selection and the adoption of robust metrics to adequately assess models capabilities., Comment: preprint

Generating optimal trajectories for high-dimensional robotic systems in a time-efficient manner while adhering to constraints is a challenging task. This paper introduces PHLAME, which applies pseudospectral collocation and spatial vector algebra to efficiently solve the Affine Geometric Heat Flow (AGHF) Partial Differential Equation (PDE) for trajectory optimization. Unlike traditional PDE approaches like the Hamilton-Jacobi-Bellman (HJB) PDE, which solve for a function over the entire state space, computing a solution to the AGHF PDE scales more efficiently because its solution is defined over a two-dimensional domain, thereby avoiding the intractability of state-space scaling. To solve the AGHF one usually applies the Method of Lines (MOL), which discretizes one variable of the AGHF PDE, and converts the PDE into a system of ordinary differential equations (ODEs) that are solved using standard time-integration methods. Though powerful, this method requires a fine discretization to generate accurate solutions and requires evaluating the AGHF PDE which is computationally expensive for high-dimensional systems. PHLAME overcomes this deficiency by using a pseudospectral method, which reduces the number of function evaluations required to yield a high accuracy solution thereby allowing it to scale efficiently to high-dimensional robotic systems. To further increase computational speed, this paper presents analytical expressions for the AGHF and its Jacobian, both of which can be computed efficiently using rigid body dynamics algorithms. PHLAME is tested across various dynamical systems, with and without obstacles and compared to a number of state-of-the-art techniques. PHLAME generates trajectories for a 44-dimensional state-space system in $\sim5$ seconds, much faster than current state-of-the-art techniques. A project page is available at https://roahmlab.github.io/PHLAME/, Comment: 26 pages, 8 figures, A project page can be found at https://roahmlab.github.io/PHLAME/

We provide a purely dynamical global map of the non-axisymmetric structure of the Milky Way disk. For this, we exploit the information contained within the in-plane motions of disk stars from Gaia DR3 to adjust a model of the Galactic potential, including a detailed parametric form for the bar and spiral arms. We explore the parameter space of the non-axisymmetric components with the backward integration method, first adjusting the bar model to selected peaks of the stellar velocity distribution in the Solar neighbourhood, and then adjusting the amplitude, phase, pitch angle and pattern speed of spiral arms to the median radial velocity as a function of position within the disk. We check a posteriori that our solution also qualitatively reproduces various other features of the global non-axisymmetric phase-space distribution, including most of the moving groups and phase-space ridges despite those not being primarily used in the adjustment. This fiducial model has a bar with pattern speed $37~{\rm kms}^{-1}{\rm kpc}^{-1}$ and two spiral modes that are two-armed and three-armed respectively. The two-armed spiral mode has a $\sim 25~\%$ local contrast surface density, a low pattern speed of $13.1~{\rm kms}^{-1}{\rm kpc}^{-1}$, and matches the location of the Crux-Scutum, Local and Outer arm segments. The three-armed spiral mode has a $\sim 9~\%$ local contrast density, a slightly higher pattern speed of $16.4~{\rm kms}^{-1}{\rm kpc}^{-1}$, and matches the location of the Carina-Sagittarius and Perseus arm segments. The Galactic bar, with a higher pattern speed than both spiral modes, has recently disconnected from those two arms. The fiducial non-axisymmetric potential presented in this paper, reproducing most non-axisymmetric signatures detected in the stellar kinematics of the Milky Way disk, can henceforth be used to confidently integrate orbits within the Galactic plane., Comment: 18 pages, 13 figures, submitted to Astronomy and Astrophysics, comments welcome! Code available at https://github.com/yrkhalil/SPIBACK

Understanding the processes that drive the morphology and kinematics of molecular gas in galaxies is crucial for comprehending star formation and, ultimately, galaxy evolution. Using data obtained with the James Webb Space Telescope (JWST) and the Atacama Large Millimeter/submillimeter Array (ALMA), we study the behavior of the warm molecular gas at temperatures of hundreds of Kelvin and the cold molecular gas at tens of Kelvin in the galaxy MCG$-$05$-$23$-$16, which hosts an active galactic nucleus (AGN). Hubble Space Telescope (HST) images of this spheroidal galaxy, classified in the optical as S0, show a dust lane resembling a nuclear spiral and a surrounding ring. These features are also detected in CO(2$-$1) and H2, and their morphologies and kinematics are consistent with rotation plus local inward gas motions along the kinematic minor axis in the presence of a nuclear bar. The H2 transitions 0-0 S(3), 0-0 S(4), and 0-0 S(5), which trace warmer and more excited gas, show more disrupted kinematics than 0-0 S(1) and 0-0 S(2), including clumps of high-velocity dispersion (of up to $\sim$ 160 km/s), in regions devoid of CO(2$-$1). The kinematics of one of these clumps, located at $\sim$ 350 pc westward from the nucleus, are consistent with outflowing gas, possibly driven by localized star formation traced by Polycyclic Aromatic Hydrocarbon (PAH) emission at 11.3 ${\mu}$m. Overall, we observe a stratification of the molecular gas, with the colder gas located in the nuclear spiral, ring, and connecting arms, while most warmer gas with higher velocity-dispersion fills the inter-arm space. The compact jet, approximately 200 pc in size, detected with Very Large Array (VLA) observations, does not appear to significantly affect the distribution and kinematics of the molecular gas, possibly due to its limited intersection with the molecular gas disc., Comment: 19 pages, 15 figures, 2. Accepted for publication in A&A

Inferring the coupling of different atmospheric layers requires observing spectral lines sensitive to the atmospheric parameters, particularly the magnetic field vector, at various heights. The best way to tackle this goal is to perform multi-line observations simultaneously. For instance, the new version of the Gregor Infrared Spectrograph instrument offers the possibility to observe the spectral lines at 8542 and 10830 A simultaneously for the first time. The first spectral window contains the Ca II 8542 A spectral line, while the Si I 10827 A transition and He I 10830 A triplet infrared lines can be found in the second spectral window. As the sensitivity to the atmospheric parameters and the height of formation of those transitions is different, combining them can help understand the properties of the solar photosphere and chromosphere and how they are magnetically coupled. Traditionally, the analysis of the Si I 10827 A transition assumes local thermodynamic equilibrium (LTE), which is not the best approximation to model this transition. Hence, in this work, we examine the potential of performing non-LTE (NLTE) inversions of the full Stokes vector of the Si I 10827 A spectral line. The results indicate that we properly infer the atmospheric parameters through an extended range of atmospheric layers in comparison with the LTE case (only valid for the spectral line wings, i.e., the low photosphere), with no impact on the robustness of the solution and just a minor increase in computational time. Thus, the NLTE assumption will help to accurately constrain the photospheric physical parameters when performing combined inversions with, e.g., the Ca II 8542 A spectral line., Comment: 7 pages, 8 figures, regular paper

While previous studies indicated the mobility reversal of an electrically-powered metallo-dielectric Janus particle (JP) with increasing frequency, here we report an intriguing second mobility reversal observed in optoelectronically-driven JPs. In contrast to the commonly used setup with parallel ITO-coated glass substrates to induce a uniform electric field orthogonal to the velocity direction, this setup incorporates a thin photoconductive layer deposited on the bottom ITO-coated glass substrate. We have found that the reversal is associated with the asymmetry of the bottom substrate's photoconductivity, localized underneath the JP, resulting from the self-shading effect of the metallic hemisphere under top optical illumination. Numerous control tests, including optical illumination from the bottom, along with numerical simulations, support this hypothesized mechanism

We present a differentiable optimization-based framework for Task and Motion Planning (TAMP) that is massively parallelizable on GPUs, enabling thousands of sampled seeds to be optimized simultaneously. Existing sampling-based approaches inherently disconnect the parameters by generating samples for each independently and combining them through composition and rejection, while optimization-based methods struggle with highly non-convex constraints and local optima. Our method treats TAMP constraint satisfaction as optimizing a batch of particles, each representing an assignment to a plan skeleton's continuous parameters. We represent the plan skeleton's constraints using differentiable cost functions, enabling us to compute the gradient of each particle and update it toward satisfying solutions. Our use of GPU parallelism better covers the parameter space through scale, increasing the likelihood of finding the global optima by exploring multiple basins through global sampling. We demonstrate that our algorithm can effectively solve a highly constrained Tetris packing problem using a Franka arm in simulation and deploy our planner on a real robot arm. Website: https://williamshen-nz.github.io/gpu-tamp, Comment: 2-page paper presented at the CoRL 2024 Workshop on Differentiable Optimization Everywhere

We study the compatibility between the $K^-\Lambda$ correlation function, recently measured by the ALICE collaboration, and the LHCb $K^-\Lambda$ invariant mass distribution obtained in the $\Xi^-_b \to J/\psi \Lambda K^-$ decay. The $K^-\Lambda$ invariant mass distribution associated with the $\Xi^-_b$ decay has been calculated within the framework of Unitary Effective Field Theories using two models, one of them constrained by the $K^-\Lambda$ correlation function. We consider two degenerate pentaquark $P_{cs}$ states in the $J/\psi \Lambda$ scattering amplitude which allows us to investigate their impact on both the $K^-\Lambda$ and $J/\psi \Lambda$ mass distributions assuming different spin-parity quantum numbers and multiplicity. Without any fitting procedure, the $K^-\Lambda$ model is able to better reproduce the experimental $K^-\Lambda$ mass spectrum in the energy region above $1680$ MeV as compared to previous unitarized scattering amplitudes constrained to a large amount of experimental data in the neutral $S=-1$ meson-baryon sector. We observe a tension between our model and the LHCb $K^-\Lambda$ distribution in the region close to the threshold, largely dominated by the presence of the still poorly known $\Xi$(1620) state. We discuss in detail the different production mechanisms probed via femtoscopy and spectroscopy that could provide valid explanations for such disagreement, indicating the necessity to employ future correlation data in other $S=-2$ channels such as $\pi\Xi$ and $\bar{K}\Sigma$.

Heatwaves (HWs) are extreme atmospheric events that produce significant societal and environmental impacts. Predicting these extreme events remains challenging, as their complex interactions with large-scale atmospheric and climatic variables are difficult to capture with traditional statistical and dynamical models. This work presents a general method for driver identification in extreme climate events. A novel framework (STCO-FS) is proposed to identify key immediate (short-term) HW drivers by combining clustering algorithms with an ensemble evolutionary algorithm. The framework analyzes spatio-temporal data, reduces dimensionality by grouping similar geographical nodes for each variable, and develops driver selection in spatial and temporal domains, identifying the best time lags between predictive variables and HW occurrences. The proposed method has been applied to analyze HWs in the Adda river basin in Italy. The approach effectively identifies significant variables influencing HWs in this region. This research can potentially enhance our understanding of HW drivers and predictability., Comment: 28 pages, 10 figures, 4 tables

The mass of galaxy clusters is a critical quantity for probing cluster cosmology and testing theories of gravity, but its measurement could be biased given assumptions are inevitable. In this paper, we employ and compare two mass proxies for galaxy clusters: thermodynamics of the intracluster medium and kinematics of member galaxies. We select 22 galaxy clusters from the cluster catalog in the first SRG/eROSITA All-Sky Survey (eRASS1) that have sufficient optical and near-infrared observations. We generate multi-band images in the energy range of (0.3, 7) keV for each cluster, and derive their temperature profiles, gas mass profiles and hydrostatic mass profiles using a parametric approach that does not assume dark matter halo models. With spectroscopically confirmed member galaxies collected from multiple surveys, we numerically solve the spherical Jeans equation for their dynamical mass profiles. Our results quantify the correlation between dynamical mass and line-of-sight velocity dispersion with an rms scatter of 0.14 dex. We find the two mass proxies lead to roughly the same total mass, with no observed systematic bias. As such, the $\sigma_8$ tension is not specific to hydrostatic mass or weak lensing shears, but also appears with galaxy kinematics. We also compare our hydrostatic masses with the latest weak lensing masses inferred with scaling relations. The comparison shows the weak lensing mass is significantly higher than our hydrostatic mass by $\sim$110%. This might explain the significantly larger value of $\sigma_8$ from the latest measurement using eRASS1 clusters than almost all previous estimates in the literature. Finally, we test the radial acceleration relation (RAR) established in disk galaxies. We confirm the missing baryon problem in the inner region of galaxy clusters using three independent mass proxies for the first time., Comment: 14 pages, 9 figures, 2 tables, with 12-page appendix for additional figures and tables. Accepted for publication in A&A

To enhance the ionization yield of liquid argon time projection chambers (LArTPC) used in dark matter and neutrino experiments it was proposed the use of dopants in LAr, with ionization energies below the scintillation threshold of Ar. While dual-phase LArTPCs have excellent sensitivity to single ionization electrons, their compatibility with photosensitive dopants is hindered by gas-phase electroluminescence photons ionizing the dopants, leading to a positive feedback loop. This can be addressed by optically decoupling the gaseous and liquid phases with a barrier that transmits electrons. A possible solution relies on the use of a pair of structures based on Gaseous Electron Multipliers(GEMs) with misaligned holes. Rather than amplifying electron signals in gas pockets within their holes, their holes will be filled with LAr and a low biasing voltage, so that incident drifting electrons are drawn into the holes but not amplified. Instead, amplification will occur in the gas phase above the structures. Its core element is a GEM-like structure machined from polyethylene naphthalate(PEN). Since PEN scintillates in the visible spectrum, the risk of increased radioactivity due to the larger mass compared to traditional wire grids is negated by the potential to veto its own radioactivity. As such, these structures may also be a useful alternative to wire grids. In this work, we report the newest developments on the production of GEM-like structures using laser-based techniques, namely the manufacture of the first batch PEN and PMMA-based GEM-like structures. This process allows low-cost, reproducible fabrication of a high volume of such structures. In addition to being a low radioactive technique, we expect that it will allow the scaling up of the production of these structures at a reduced cost. First tests indicate good electrical stability, while the performance assessment is still ongoing., Comment: 4 pages, 3 figures, 1 table, conference LRT2024

DNA technologies have evolved significantly in the past years enabling the sequencing of a large number of genomes in a short time. Nevertheless, the underlying computational problem is hard, and many technical factors and limitations complicate obtaining the complete sequence of a genome. Many genomes are left in a draft state, in which each chromosome is represented by a set of sequences with partial information on their relative order. Recently, some approaches have been proposed to compare draft genomes by comparing paths in de Bruijn graphs, which are constructed by many practical genome assemblers. In this article we introduce gcBB, a method for comparing genomes represented as succinct colored de Bruijn graphs directly, without resorting to sequence alignments, by means of the entropy and expectation measures based on the Burrows-Wheeler Similarity Distribution. We also introduce an improved version of gcBB, called mgcBB, that improves the time performance considerably through the selection of different data structures. We have compared phylogenies of genomes obtained by other methods to those obtained with gcBB, achieving promising results.

We introduce a driven-dissipative Bose-Hubbard chain describing coupled lossy photonic modes, in which time-reversal symmetry is broken by a coherent drive with a uniform phase gradient. We investigate this model by means of a Gaussian variational ansatz and numerically prove that the steady-state solution is stabilized by an inhomogeneous profile of the driving amplitude, which damps out boundary effects. Our calculations unveil a non-equilibrium phase diagram showing low- and high-density phases for photons separated by a phase coexistence region in which the system exhibits the phenomenon of topological amplification and is characterized by a finite non-Hermitian winding number. Our work shows the emergence of non-Hermitian topological phases in an interacting model that can be naturally implemented with superconducting circuits., Comment: 10 pages, 9 figures, comments welcomme

Foundation models trained on internet-scale data, such as Vision-Language Models (VLMs), excel at performing tasks involving common sense, such as visual question answering. Despite their impressive capabilities, these models cannot currently be directly applied to challenging robot manipulation problems that require complex and precise continuous reasoning. Task and Motion Planning (TAMP) systems can control high-dimensional continuous systems over long horizons through combining traditional primitive robot operations. However, these systems require detailed model of how the robot can impact its environment, preventing them from directly interpreting and addressing novel human objectives, for example, an arbitrary natural language goal. We propose deploying VLMs within TAMP systems by having them generate discrete and continuous language-parameterized constraints that enable TAMP to reason about open-world concepts. Specifically, we propose algorithms for VLM partial planning that constrain a TAMP system's discrete temporal search and VLM continuous constraints interpretation to augment the traditional manipulation constraints that TAMP systems seek to satisfy. We demonstrate our approach on two robot embodiments, including a real world robot, across several manipulation tasks, where the desired objectives are conveyed solely through language.

In multi-agent systems, strong connectivity of the communication network is often crucial for establishing consensus protocols, which underpin numerous applications in decision-making and distributed optimization. However, this connectivity requirement may not be inherently satisfied in geographically distributed settings. Consequently, we need to find the minimum number of communication links to add to make the communication network strongly connected. To date, such problems have been solvable only through centralized methods. This paper introduces a fully distributed algorithm that efficiently identifies an optimal set of edge additions to achieve strong connectivity, using only local information. The majority of the communication between agents is local (according to the digraph structure), with only a few steps requiring communication among non-neighboring agents to establish the necessary additional communication links. A comprehensive empirical analysis of the algorithm's performance on various random communication networks reveals its efficiency and scalability.

In this paper, we investigate the influence of the geometry in the electronic states of a quantum ripple surface. We have considered an electron governed by the spinless stationary Schr\"{o}dinger equation constrained to move on the ripple surface due to a confining potential from which the Da Costa potential emerges. We investigate the role played by the geometry and orbital angular momentum on the electronic states of the system., Comment: 8 pages, two column, 7 figures