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Accurate estimation of noise parameters is critical for optimal filter performance, especially in systems where true noise parameter values are unknown or time-varying. This article presents a quaternion left-invariant extended Kalman filter (LI-EKF) for attitude estimation, integrated with an adaptive noise covariance estimation algorithm. By employing an iterative expectation-maximization (EM) approach, the filter can effectively estimate both process and measurement noise covariances. Extensive simulations demonstrate the superiority of the proposed method in terms of attitude estimation accuracy and robustness to initial parameter misspecification. The adaptive LI-EKF's ability to adapt to time-varying noise characteristics makes it a promising solution for various applications requiring reliable attitude estimation, such as aerospace, robotics, and autonomous systems., Comment: This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible

We present a peer-to-peer (P2P) live-streaming architecture designed to address challenges such as free-riding, malicious peers, churn, and network instability through the integration of a reputation system. The proposed algorithm incentivizes active peer participation while discouraging opportunistic behaviors, with a reputation mechanism that rewards altruistic peers and penalizes free riders and malicious actors. To manage peer dynamics, the algorithm continuously updates the strategies and adjusts to changing neighbors. It also implements a request-to-join mechanism for flash crowd scenarios, allowing the source node to delegate requests to child nodes, forming an interconnected tree structure that efficiently handles high demand and maintains system stability. The decentralized reputation mechanism promotes long-term sustainability in the P2P live streaming system., Comment: 6 Pages, 6 Figure

The availability of high-quality datasets play a crucial role in advancing research and development especially, for safety critical and autonomous systems. In this paper, we present AssistTaxi, a comprehensive novel dataset which is a collection of images for runway and taxiway analysis. The dataset comprises of more than 300,000 frames of diverse and carefully collected data, gathered from Melbourne (MLB) and Grant-Valkaria (X59) general aviation airports. The importance of AssistTaxi lies in its potential to advance autonomous operations, enabling researchers and developers to train and evaluate algorithms for efficient and safe taxiing. Researchers can utilize AssistTaxi to benchmark their algorithms, assess performance, and explore novel approaches for runway and taxiway analysis. Addition-ally, the dataset serves as a valuable resource for validating and enhancing existing algorithms, facilitating innovation in autonomous operations for aviation. We also propose an initial approach to label the dataset using a contour based detection and line extraction technique.

Conservation of energy under thermal operations, \textbf{TO}, is ensured by commutation of the unitary generating such operations with the total Hamiltonian. However in realistic scenarios, perturbations or disturbances in the system are unavoidable, which in turn may alter the commutation relation and hence in succession may affect the physical processes governed by \textbf{TO}. We call the altered set of operations as approximate thermal operations, \textbf{TO}$_\epsilon$, where $\epsilon$ denotes a degree of disturbance. We provide state transformation conditions under such operations, providing what can be referred to as approximate second laws. We show that in presence of feeble perturbations in the system's Hamiltonian, the states transform in such a way that diagonal elements of the system states start talking not only with each other but also with the off-diagonal elements. In parallel, the off-diagonal elements transform in a way such that they start connecting with diagonal elements and other off-diagonal elements. Such cross-talk is disallowed in the unperturbed second laws. As an application, we show that approximate thermal operations may lead to finite ergotropy extraction from quantum batteries, something that the exact ones are unable to., Comment: 10 pages, 1 figure

We present a multi-wavelength spectral study of NGC 4151 based on five epochs of simultaneous AstroSat observations in the near ultra-violet (NUV) to hard X-ray band ($\sim 0.005-80$ keV) during $2017 - 2018$. We derived the intrinsic accretion disk continuum after correcting for internal and Galactic extinction, contributions from broad and narrow line regions, and emission from the host galaxy. We found a bluer continuum at brighter UV flux possibly due to variations in the accretion disk continuum or the UV reddening. We estimated the intrinsic reddening, $E(B-V) \sim 0.4$, using high-resolution HST/STIS spectrum acquired in March 2000. We used thermal Comptonization, neutral and ionized absorption, and X-ray reflection to model the X-ray spectra. We obtained the X-ray absorbing neutral column varying between $N_H \sim 1.2-3.4 \times 10^{23} cm^{-2}$, which are $\sim 100$ times larger than that estimated from UV extinction, assuming the Galactic dust-to-gas ratio. To reconcile this discrepancy, we propose two plausible configurations of the obscurer: (a) a two-zone obscurer consisting of dust-free and dusty regions, divided by the sublimation radius, or (b) a two-phase obscurer consisting of clumpy, dense clouds embedded in a low-density medium, resulting in a scenario where a few dense clouds obscure the compact X-ray source substantially, while the bulk of UV emission arising from the extended accretion disk passes through the low-density medium. Furthermore, we find a positive correlation between X-ray absorption column and $NUV-FUV$ color and UV flux, indicative of enhanced winds possibly driven by the 'bluer-when-brighter' UV continuum., Comment: 21 pages, 22 figures, 6 tables, accepted for publication in ApJ

Consider a bounded symmetric domain $\Omega$ with a finite pseudo-reflection group acting on it as a subgroup of the group of automorphisms. This gives rise to quotient domains by means of basic polynomials $\theta$ which by virtue of being proper maps map the \v Silov boundary of $\Omega$ to the \v Silov boundary of $\theta(\Omega)$. Thus, the natural measure on the \v Silov boundary of $\Omega$ can be pushed forward. This gives rise to Hardy spaces on the quotient domain. The study of Hankel operators on the Hardy spaces of the quotient domains is introduced. The use of the weak product space shows that an analogue of Hartman's theorem holds for the small Hankel operator. Nehari's theorem fails for the big Hankel operator and this has the consequence that when the domain $\Omega$ is the polydisc $\mathbb D^d$, the {\em Hardy space} is not a projective object in the category of all Hilbert modules over the algebra $\mathcal A (\theta(\mathbb D^d))$ of functions which are holomorphic in the quotient domain and continuous on the closure $\overline {\theta(\mathbb D^d)}$. It is not a projective object in the category of cramped Hilbert modules either. Indeed, no projective object is known in these two categories. On the other hand, every normal Hilbert module over the algebra of continuous functions on the \v Silov boundary, treated as a Hilbert module over the algebra $\mathcal A (\theta(\mathbb D^d))$, is projective.

Coronal jets are the captivating eruptions which are often found in the solar atmosphere, and primarily formed due to magnetic reconnection. Despite their short-lived nature and lower energy compared to many other eruptive events, e.g. flares and coronal mass ejections, they play an important role in heating the corona and accelerating charged particles. However, their generation in the ambience of non-standard flare regime is not fully understood, and warrant a deeper investigation, in terms of their onset, growth, eruption processes, and thermodynamic evolution. Toward this goal, this paper reports the results of a data-constrained three-dimensional (3D) magnetohydrodynamics (MHD) simulation of an eruptive jet; initialized with a Non-Force-Free-Field (NFFF) extrapolation and carried out in the spirit of Implicit Large Eddy Simulation (ILES). The simulation focuses on the magnetic and dynamical properties of the jet during its onset, and eruption phases, that occurred on February 5, 2015 in an active region NOAA AR12280, associated with a seemingly three-ribbon structure. In order to correlate its thermal evolution with computed energetics, the simulation results are compared with differential emission measurement (DEM) analysis in the vicinity of the jet. Importantly, this combined approach provides an insight to the onset of reconnection in transients in terms of emission and the corresponding electric current profiles from MHD evolutions. The presented study captures the intricate topological dynamics, finds a close correspondence between the magnetic and thermal evolution in and around the jet location. Overall, it enriches the understanding of the thermal evolution due to MHD processes, which is one of the broader aspects to reveal the coronal heating problem., Comment: 26 pages, 16 figures, accepted for publication in the Astrophysical Journal. Animations associated with Figure 1, Figure 7, and Figure 8 are available upon reasonable request from the corresponding authors

Eclipses of radio emission have been reported for ~ 58 spider millisecond pulsars (MSP), of which only around 19% have been extensively studied. Such studies at low frequencies are crucial for probing the properties of the eclipse medium, as eclipses are more prominent at such frequencies. This study investigates eclipses in 10 MSPs in compact orbit using wide-bandwidth observations with the upgraded Giant Metrewave Radio Telescope. We report the first evidence of eclipsing for PSR J2234+0944 and J2214+3000 in one epoch, while no evidence of eclipsing was observed in the subsequent two epochs, indicating temporal evolution of the eclipse cutoff frequency in these systems. Constraints on the eclipse cutoff frequency were obtained for PSR J1555-2908, J1810+1744, and J2051-0827. Moreover, for the first time, we detected an eclipse at a non-standard orbital phase (~ 0.5) for PSR J1810+1744, with a duration longer than the eclipse observed at superior conjunction. No eclipses were detected for PSR J0751+1807, J1738+0333, and J1807-2459A at 300-500 MHz and 550-750 MHz, for which we discuss the possible reasons. We calculated the mass loss rates of the companions for PSR J1555-2908 and PSR J1810+1744, and found that these rates are insufficient to ablate the companion stars. We cataloged the $\dot{E}/a^2$, mass function, roche lobe filling factor, and inclination angle for compact MSP binaries with low-mass companions and found that higher spin-down flux does not guarantee eclipses. Our analysis, supported by the Kolmogorov-Smirnov statistic, reveals that eclipsing black widow binaries generally exhibit a higher mass function compared to non-eclipsing black widow binaries, as reported by previous studies for a limited sample of black widow MSPs., Comment: Submitted in ApJ

We theoretically propose the occurrence of a quantum spin Hall (QSH) and a second order topological phase transition (TPT) driven by electron-phonon (e-p) coupling in a pseudospin-$1$ fermionic system on an $\alpha$-$T_3$ lattice. Our model is formulated in the spirit of the Kane-Mele model modified by the Holstein Hamiltonian. The Lang-Firsov approach is employed to describe polarons reasonably well in the anti-adiabatic (high frequency) limit and to obtain an effective electronic Hamiltonian. It is shown that the system possesses topologically nontrivial phases up to a critical e-p coupling, $\lambda_c$ and are characterized by the helical QSH edge states along with a non-zero $\mathbb{Z}_2$ invariant for a certain range of $\alpha$. The topological phase vanishes beyond $\lambda_c$ and is accompanied by a bulk gap closing transition at $\lambda_c$, manifesting a TPT. We observe a more intriguing phenomenon for higher values of $\alpha$, where the system exhibits TPTs supported by two distinct gap closing transitions at $\lambda_{c_1}$ and $\lambda_{c_2}$, while a slim region at slightly lower values hosts a semi-metallic signature below $\lambda_{c_1}$. Subsequently, to explore more intricate features, we introduce a time reversal symmetry breaking magnetic field to trigger the formation of a second order topological phase. The magnetic field, by construction causes a boundary dependent gapping out of the edge states, consequently giving rise to robust corner modes in a tailored open boundary conditions. We justify the formation of the higher order phase by employing an appropriate invariant, namely the projected spin Chern number. Finally, we show that the e-p coupling significantly influences the corner modes (and also the real space energy bandstructure), corroborating a higher order TPT as we tune $\lambda$ beyond a critical value for a given value of $\alpha$., Comment: 18 pages, 18 figures. Comments are welcome

In this article, we investigate the in-situ growth of Al$_2$O$_3$ on $\beta$-Ga$_2$O$_3$ using metal-organic chemical vapor deposition (MOCVD) at a high temperature of 800{\deg}C. The Al$_2$O$_3$ is grown within the same reactor as the $\beta$-Ga$_2$O$_3$, employing trimethylaluminum (TMAl) and O$_2$ as precursors without breaking the vacuum. We characterize the shallow and deep-level traps through stressed capacitance-voltage (C-V) and photo-assisted C-V methods. The high-temperature deposited dielectric demonstrates an impressive breakdown field of approximately 10 MV/cm. Furthermore, we evaluate the reliability and lifetime of the dielectrics using time-dependent dielectric breakdown (TDDB) measurements. By modifying the dielectric deposition process to include a high-temperature (800{\deg}C) thin interfacial layer and a low-temperature (600{\deg}C) bulk layer, we report a 10-year lifetime under a stress field of 3.5 MV/cm along a breakdown field of 7.8 MV/cm.

We introduce Synthetic Playground (SynPlay), a new synthetic human dataset that aims to bring out the diversity of human appearance in the real world. We focus on two factors to achieve a level of diversity that has not yet been seen in previous works: i) realistic human motions and poses and ii) multiple camera viewpoints towards human instances. We first use a game engine and its library-provided elementary motions to create games where virtual players can take less-constrained and natural movements while following the game rules (i.e., rule-guided motion design as opposed to detail-guided design). We then augment the elementary motions with real human motions captured with a motion capture device. To render various human appearances in the games from multiple viewpoints, we use seven virtual cameras encompassing the ground and aerial views, capturing abundant aerial-vs-ground and dynamic-vs-static attributes of the scene. Through extensive and carefully-designed experiments, we show that using SynPlay in model training leads to enhanced accuracy over existing synthetic datasets for human detection and segmentation. The benefit of SynPlay becomes even greater for tasks in the data-scarce regime, such as few-shot and cross-domain learning tasks. These results clearly demonstrate that SynPlay can be used as an essential dataset with rich attributes of complex human appearances and poses suitable for model pretraining. SynPlay dataset comprising over 73k images and 6.5M human instances, is available for download at https://synplaydataset.github.io/., Comment: Project Page: https://synplaydataset.github.io/

Transparency in automated systems could be afforded through the provision of intelligible explanations. While transparency is desirable, might it lead to catastrophic outcomes (such as anxiety), that could outweigh its benefits? It's quite unclear how the specificity of explanations (level of transparency) influences recipients, especially in autonomous driving (AD). In this work, we examined the effects of transparency mediated through varying levels of explanation specificity in AD. We first extended a data-driven explainer model by adding a rule-based option for explanation generation in AD, and then conducted a within-subject lab study with 39 participants in an immersive driving simulator to study the effect of the resulting explanations. Specifically, our investigation focused on: (1) how different types of explanations (specific vs. abstract) affect passengers' perceived safety, anxiety, and willingness to take control of the vehicle when the vehicle perception system makes erroneous predictions; and (2) the relationship between passengers' behavioural cues and their feelings during the autonomous drives. Our findings showed that passengers felt safer with specific explanations when the vehicle's perception system had minimal errors, while abstract explanations that hid perception errors led to lower feelings of safety. Anxiety levels increased when specific explanations revealed perception system errors (high transparency). We found no significant link between passengers' visual patterns and their anxiety levels. Our study suggests that passengers prefer clear and specific explanations (high transparency) when they originate from autonomous vehicles (AVs) with optimal perceptual accuracy., Comment: Submitted to Transportation Research Part F: Traffic Psychology and Behaviour. arXiv admin note: text overlap with arXiv:2307.00633

Molecular dynamics triggered by interaction with light often involve the excitation of several electronic, vibrational, and rotational states. Characterizing the resulting coupled electronic and nuclear wave packet motion represents a severe challenge, even for small polyatomic systems. In this Letter, we demonstrate how the interplay between vibrational, rotational, and electronic degrees of freedom governs the evolution of molecular wave packets in the low-lying states of strong-field-ionized sulfur dioxide. Using time-resolved Coulomb explosion imaging (CEI) in combination with quantum mechanical wave packet simulations, we directly map bending vibrations of the molecule, show how the vibrational wave packet is influenced by molecular alignment, and elucidate the role of the coupling between the two lowest electronic states of the cation. A conical intersection between these states couples the bending and asymmetric stretching coordinates, which is clearly reflected in the correlated fragment momenta. Our results suggest that multi-coincident CEI represents an efficient experimental tool for characterizing coupled electronic and nuclear motion in polyatomic molecules.

Coulomb explosion imaging (CEI) with x-ray free electron lasers has recently been shown to be a powerful method for obtaining detailed structural information of gas-phase planar ring molecules [R. Boll et al. Nat. Phys. 18, 423-428 (2022)]. In this Letter, we investigate the potential of CEI driven by a tabletop laser and extend this approach to differentiating three-dimensional (3D) structures. We study the static CEI patterns of planar and nonplanar organic molecules that resemble the structures of typical products formed in ring-opening reactions. Our results reveal that each molecule exhibits a well-localized and distinctive pattern in 3D fragment-ion momentum space. We find that these patterns yield direct information about the molecular structures and can be qualitatively reproduced using a classical Coulomb explosion simulation. Our findings suggest that laser-induced CEI can serve as a robust method for differentiating molecular structures of organic ring and chain molecules. As such, it holds great promise as a method for following ultrafast structural changes, e.g., during ring-opening reactions, by tracking the motion of individual atoms in pump-probe experiments.

The accreting collapsed object GRO J1655-40 could contain the gravitomagnetic monopole (GMM), and it was shown to be better described by the Kerr-Taub-NUT (KTN) spacetime instead of the Kerr spacetime. The warped accretion disk has also been observed for the same collapsed object. Motivated by these, we study a tilted thin inner accretion disk around a slowly-spinning KTN black hole that contains a small GMM. Such a tilting could have a significant effect on the X-ray spectral and timing features via the Lense-Thirring effect. Taking into account the contribution from the inner accretion disk for the KTN black hole, here we calculate the radial profile of a tilt angle. Depending on the numerical values of the viscosity of the accreting material and Kerr parameter, we show that the GMM tends the angular momentum of the disk to align along the black hole's spin axis, or to make it more tilted. Our solution for the radial profile of the tilted disk around a KTN black hole could be useful to probe the strong gravity regime, and could also give indirect evidence for the existence of GMM in nature., Comment: 17 pages, 7 figures

EXO 0748-676 is a well-studied neutron star (NS) Low Mass X-ray Binary (LMXB) that recently emerged from 16 years of quiescence into a new outburst. Here, we report the results from a 53 ks XMM-Newton observation to compare with studies for the previous outburst, particularly focusing on high-resolution spectroscopy using the same instrument (RGS) that produced important results for this source during the previous outburst. The EPIC light curve reveals a type I X-ray burst at MJD 60492.31. The entire data are divided into burstless, pre-, and post-burst spectra to understand the effect of the burst on the ionization structure. The spectra for dip and non-dip phases are also created. The primary spectral feature in all phases is a broad O VII recombination line, along with velocity-broadened OVIII, NVII, and Ne IX lines. Notably, the Ne IX line is detected at different ionization states for the pre-burst (11.65 \AA) and post-burst (13.56 \AA) phases. The O VIII line profile also shows a difference in equivalent width between dip and non-dip phases. These findings suggest the presence of highly ionized circumstellar material or collisionally ionized gas affected by the burst and dips. The source remains in a soft spectral state, which is consistent with observations during the previous outburst., Comment: 12 pages, 5 figures, 2 tables

In this paper, we compute the partition functions of $\mathcal{N}=1$ SUGRA for different boundary topologies, i.e. sphere and torus, using super-Virasoro TQFT. We use fusion and modular kernels of the super-Liouville theory to compute the necklace-channel conformal block and showcase formalism by proving that the inner product holds for superconformal blocks, defined as states in the Hilbert space. Finally, we compute the out-of-time-order correlator for the torus topology with superconformal primary insertions as matter using the tools of super-Virasoro TQFT and investigate its early-time behaviour., Comment: 48 pages, 4 figures, 1 table

As machine learning models become increasingly prevalent in critical decision-making models and systems in fields like finance, healthcare, etc., ensuring their robustness against adversarial attacks and changes in the input data is paramount, especially in cases where models potentially overfit. This paper proposes a comprehensive framework for assessing the robustness of machine learning models through covariate perturbation techniques. We explore various perturbation strategies to assess robustness and examine their impact on model predictions, including separate strategies for numeric and non-numeric variables, summaries of perturbations to assess and compare model robustness across different scenarios, and local robustness diagnosis to identify any regions in the data where a model is particularly unstable. Through empirical studies on real world dataset, we demonstrate the effectiveness of our approach in comparing robustness across models, identifying the instabilities in the model, and enhancing model robustness., Comment: 31 pages, 11 figures, 14 tables

In this study, we demonstrate the efficacy of the Ultraviolet Imaging Telescope (UVIT) in identifying and characterizing white dwarfs (WDs) within the Milky Way Galaxy. Leveraging the UVIT point source catalogue towards SMC and crossmatching with Gaia DR3 data, we identified 43 single WDs (37 new detections), 13 new WD+main sequence (MS) candidates and 161 UV bright MS stars by analysing their Spectral Energy Distributions (SED). Using the WD evolutionary models, we determine the masses, effective temperatures, and cooling ages of these identified WDs. Masses of these WDs range from 0.2 to 1.3 M$_{\odot}$ and effective temperatures (T$_{eff}$) between 10000 K to 15000 K, with cooling ages spanning 0.1 to 2 Gyr. Notably, we detect hotter WDs compared to literature values, which is attributed to the sensitivity of UVIT. Furthermore, we report the detection of 20 new extremely low-mass (ELM) candidates from our analysis. Future spectroscopic studies of the ELM candidates will help us understand the formation scenarios of these exotic objects. Despite limitations in Gaia DR3 distance measurements for optically faint WDs, we provide a crude estimate of the WD space density within 1kpc as 1.3 $\times$ 10$^{-3}$ pc$^{-3}$, which is higher than previous estimates in the literature. Our results underscore the instrumental capabilities of UVIT and anticipate the forthcoming UV missions like INSIST for systematic WD discovery. Our methodology sets a precedent for future analyses in other UVIT fields to find more WDs and perform spectroscopic studies to verify their candidacy., Comment: Accepted for publication in Astronomy & Astrophysics

This study provides an analysis of atmospheric neutrino oscillations at the ESSnuSB far detector facility. The prospects of the two cylindrical Water Cherenkov detectors with a total fiducial mass of 540 kt are investigated over 10 years of data taking in the standard three-flavor oscillation scenario. We present the confidence intervals for the determination of mass ordering, $\theta_{23}$ octant as well as for the precisions on $\sin^2\theta_{23}$ and $|\Delta m_{31}^2|$. It is shown that mass ordering can be resolved by $3\sigma$ CL ($5\sigma$ CL) after 4 years (10 years) regardless of the true neutrino mass ordering. Correspondingly, the wrong $\theta_{23}$ octant could be excluded by $3\sigma$ CL after 4 years (7 years) in the case where the true neutrino mass ordering is normal ordering (inverted ordering). The results presented in this work are complementary to the accelerator neutrino program in the ESSnuSB project., Comment: 13 pages, 6 figures, 2 tables

We show that estimation of multiple independent field strengths of a local Hamiltonian, i.e., one formed by a sum of single-party terms, necessitates the utility of a highly symmetric genuine multiparty entangled state, viz. the Greenberger-Horne-Zeilinger (GHZ) state, as the input probe. This feature however depends on the choice of the weight matrix considered, to define a figure of merit in the multiparameter estimation. We obtain this result by providing a lower bound on the precision of multiparameter estimation, optimized over input probes, for an arbitrary weight matrix. We find that the bound can be expressed in terms of eigenvalues of the arbitrary multiparty local encoding Hamiltonian. We show that there exists a weight matrix for which this bound is attainable only when the probe is the GHZ state, up to a relative phase. In particular, no pure product state can achieve this lower bound. Indeed, the gap - in precision - between genuinely multiparty entangled and product states acting as probes, increases with increasing number of parties. Finally we also prove that using a probe that is in a mixed state provides a precision lower than that for the GHZ state. To emphasize the importance of the weight matrix considered, we also prove that the choice of identity operator as the same - thereby ignoring the covariances in the precision matrix - does not require the use of genuine multiparty entanglement in input probes for attaining the best precision, and the optimal probe can be a pure product., Comment: 11 pages

We study multicomponent liquids by increasing the mass of $15\%$ of the particles in a binary Kob-Andersen model. We find that the heavy particles have dual effects on the lighter particles. At higher temperatures, there is a significant decoupling of the dynamics between heavier and lighter particles, with the former resembling a pinned particle to the latter. The dynamics of the lighter particles slow down due to the excluded volume around the nearly immobile heavier particles. Conversely, at lower temperatures, there is a coupling between the dynamics of the heavier and lighter particles. The heavier particles' mass slows down the dynamics of both types of particles. This makes the soft pinning effect of the heavy particles questionable in this regime. We demonstrate that as the mass of the heavy particles increases, the coupling of the dynamics between the lighter and heavier particles weakens. Consequently, the heavier the mass of the heavy particles, the more effectively they act as soft pinning centres in both high and low-temperature regimes. A key finding is that akin to the pinned system, the self and collective dynamics of the lighter particles decouple from each other as the mass of the heavy particles has a more pronounced impact on the latter. We analyze the structure dynamics correlation by considering the system under the binary and modified quaternary framework, the latter describing the pinned system. Our findings indicate that whenever the heavy mass particles function as soft pinning centres, the modified quaternary framework predicts a higher correlation., Comment: 15 pages, 28 figures, 1 table

In this work, it has been indicated that the key features requisite for preserving causality and stability of the popularly existing relativistic hydrodynamic theories, can be translated into each other. It has been shown here, that a generic `fluid frame transformation' including all orders of gradient corrections can recast a stable-causal hydrodynamic theory that (i) only includes fundamental fluid variables (velocity and temperature) but requires to be in a general hydrodynamic frame other than the Landau or Eckart, to a theory that is (ii) pathology free in Landau frame but needs newer degrees of freedom. Since frame choice provides the first principle field definitions and degrees of freedom indicate the number of conserved quantities, the causality and stability of a theory seem to require a consensus between the two unless the derivative correction goes to infinity. The key finding of this work is to indicate a connection between these different formalisms, that lead to a causal and stable hydrodynamic theory., Comment: Version accepted in Physics Letters B; This paper is a companion paper of arXiv:2312.16407 [nucl-th] which is an elaborate version of this paper

Contribution of metal ions on nucleic acids structures and functions is undeniable. Among the available metal ions like Na+, K+, Ca2+, Mg2+ etc., the role that play the Mg2+ ion is very significant related to the stability of the structures of RNA and this is quite well studied. But it is not possible to grasp the entire functionality of Mg2+ ion in the structure of RNA. So, to have a better understanding of the Mg-RNA complexes, in the present study, we have investigated 1541 non-redundant crystal structures of RNA and generated reports for various statistics related to these Mg-RNA complexes by computing base pairs and Mg2+ binding statistics. In this study, it has also been reported whether the presence of Mg2+ ions can alter the stability of base pairs or not by computing and comparing the base pairs stability. We noted that the Mg2+ ions do not affect the canonical base pair G:C W:WC while majority of the non-canonical base pair G:G W:HC, which is important also in DNA telomere structures, has Magnesium ion binding to O6 or N7 atoms of one of the Guanines., Comment: 19 pages, 10 figures

We report on metalorganic chemical vapor deposition (MOCVD) growth of controllably Si-doped 4.5 $\mu$m thick $\beta$-Ga$_2$O$_3$ films with electron concentrations in the 10$^{15}$ cm$^{-3}$ range and record-high room temperature Hall electron mobilities of up to 200 cm$^2$/V.s, reaching the predicted theoretical maximum room temperature mobility value for $\beta$-Ga$_2$O$_3$. Growth of the homoepitaxial films was performed on Fe-doped (010) $\beta$-Ga$_2$O$_3$ substrates at a growth rate of 1.9 $\mu$m/hr using TEGa as the Gallium precursor. To probe the background electron concentration, an unintentionally doped film was grown with a Hall concentration of 3.43 x 10$^{15}$ cm$^{-3}$ and Hall mobility of 196 cm$^2$/V.s. Growth of intentionally Si-Doped films was accomplished by fixing all growth conditions and varying only the silane flow, with controllable Hall electron concentrations ranging from 4.38 x 10$^{15}$ cm$^{-3}$ to 8.30 x 10$^{15}$ cm$^{-3}$ and exceptional Hall mobilities ranging from 194 - 200 cm$^2$/V.s demonstrated. C-V measurements showed a flat charge profile with the N$_D^+$ - N$_A^-$ values correlating well with the Hall-measured electron concentration in the films. SIMS measurements showed the silicon atomic concentration matched the Hall electron concentration with Carbon and Hydrogen below detection limit in the films. The Hall, C-V, and SIMS data indicate the growth of high-quality 4.5 $\mu$m thick $\beta$-Ga$_2$O$_3$ films and controllable doping into the mid 10$^{15}$ cm$^{-3}$ range. These results demonstrate MOCVD growth of electronics grade record-high mobility, low carrier density, and thick $\beta$-Ga$_2$O$_3$ drift layers for next generation vertical $\beta$-Ga$_2$O$_3$ power devices., Comment: 16 Pages, 10 Figures, 2 Tables

We present a multi-node, multi-objective open-loop microwave distributed beamforming system based on high-accuracy wireless synchronization and localization. Distributed beamforming requires accurate coordination of the spatial and electrical states of the individual elements within the array to achieve and maintain coherent beamforming at intended destinations. Of the basic coordination aspects, time synchronization and localization of the elements are among the most critical to support beamforming of modulated waveforms to destinations in both the near-field and far-field of the array. In this work, we demonstrate multi-objective distributed beamforming from a three-node distributed phased array consisting of software-defined radios that leverages high-accuracy wireless time coordination for both time synchronization and two-dimensional localization of the elements. We use a spectrally-sparse two-tone waveform for high-accuracy inter-node range estimation combined with a linear-frequency modulated waveform to mitigate multipath interference. Localization is performed in a centralized format, where one node is designated as the origin and the remaining nodes build the array geometry relative to the origin, from which we obtain localization accuracy of less than 1 cm. We implement a near-field multi-objective beamformer based on the location estimates, which enables the simultaneous steering of a beam and a null to two receiving antennas. Multi-objective beamforming of pulsed waveforms at a carrier frequency of 2.1 GHz is demonstrated in cases where one of the nodes in the distributed antenna array is moved, and where the targets (the two receiving antennas) are moved., Comment: This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may may no longer be accessible

Video tasks are compute-heavy and thus pose a challenge when deploying in real-time applications, particularly for tasks that require state-of-the-art Vision Transformers (ViTs). Several research efforts have tried to address this challenge by leveraging the fact that large portions of the video undergo very little change across frames, leading to redundant computations in frame-based video processing. In particular, some works leverage pixel or semantic differences across frames, however, this yields limited latency benefits with significantly increased memory overhead. This paper, in contrast, presents a strategy for masking regions in video frames that leverages the semantic information in images and the temporal correlation between frames to significantly reduce FLOPs and latency with little to no penalty in performance over baseline models. In particular, we demonstrate that by leveraging extracted features from previous frames, ViT backbones directly benefit from region masking, skipping up to 80% of input regions, improving FLOPs and latency by 3.14x and 1.5x. We improve memory and latency over the state-of-the-art (SOTA) by 2.3x and 1.14x, while maintaining similar detection performance. Additionally, our approach demonstrates promising results on convolutional neural networks (CNNs) and provides latency improvements over the SOTA up to 1.3x using specialized computational kernels.

X-ray observations of neutron star (NS) low mass X-ray binaries (LMXBs) are useful to probe physical processes close to the NS and to constrain source parameters. Aql X-1 is a transient NS LMXB which frequently undergoes outbursts provides an excellent opportunity to study source properties and accretion mechanism in strong gravity regime over a wide range of accretion rates. In this work, we systematically investigate the spectral evolution of Aql X-1 using NICER observations during the source outbursts in 2019 and 2020. The NICER observations cover the complete transition of the source from its canonical hard state to soft state and back. The spectra extracted from most observations can be explained by a partially Comptonised accretion disc. We find that the system can be described by an accretion disk with an inner temperature of $\approx0.7$ keV and a Comptonising medium of thermal electrons at $\approx2$ keV, while the photon index is strongly degenerate with the covering fraction of the medium. We also find evidence of Fe K$\alpha$ fluorescence emission in the spectra indicating reprocessing of the Comptonised photons. We observe an absorption column density higher than the Galactic column density for most of the observations indicating a significant local absorption. But for some of the observations in 2020 outburst, the local absorption is negligible., Comment: 10 pages,5 figures,5 tables,accepted for publication in MNRAS

Reduplication and repetition, though similar in form, serve distinct linguistic purposes. Reduplication is a deliberate morphological process used to express grammatical, semantic, or pragmatic nuances, while repetition is often unintentional and indicative of disfluency. This paper presents the first large-scale study of reduplication and repetition in speech using computational linguistics. We introduce IndicRedRep, a new publicly available dataset containing Hindi, Telugu, and Marathi text annotated with reduplication and repetition at the word level. We evaluate transformer-based models for multi-class reduplication and repetition token classification, utilizing the Reparandum-Interregnum-Repair structure to distinguish between the two phenomena. Our models achieve macro F1 scores of up to 85.62% in Hindi, 83.95% in Telugu, and 84.82% in Marathi for reduplication-repetition classification.

Tasks at the intersection of vision and language have had a profound impact in advancing the capabilities of vision-language models such as dialog-based assistants. However, models trained on existing tasks are largely limited to turn-based interactions, where each turn must be stepped (i.e., prompted) by the user. Open-ended, asynchronous interactions where an AI model may proactively deliver timely responses or feedback based on the unfolding situation in real-time are an open challenge. In this work, we present the QEVD benchmark and dataset which explores human-AI interaction in the challenging, yet controlled, real-world domain of fitness coaching - a task which intrinsically requires monitoring live user activity and providing timely feedback. It is the first benchmark that requires assistive vision-language models to recognize complex human actions, identify mistakes grounded in those actions, and provide appropriate feedback. Our experiments reveal the limitations of existing state of the art vision-language models for such asynchronous situated interactions. Motivated by this, we propose a simple end-to-end streaming baseline that can respond asynchronously to human actions with appropriate feedbacks at the appropriate time., Comment: The benchmark and dataset is available here: https://developer.qualcomm.com/software/ai-datasets/qevd

This article presents constraints on dark-matter-electron interactions obtained from the first underground data-taking campaign with multiple SuperCDMS HVeV detectors operated in the same housing. An exposure of 7.63 g-days is used to set upper limits on the dark-matter-electron scattering cross section for dark matter masses between 0.5 and 1000 MeV/$c^2$, as well as upper limits on dark photon kinetic mixing and axion-like particle axioelectric coupling for masses between 1.2 and 23.3 eV/$c^2$. Compared to an earlier HVeV search, sensitivity was improved as a result of an increased overburden of 225 meters of water equivalent, an anticoincidence event selection, and better pile-up rejection. In the case of dark-matter-electron scattering via a heavy mediator, an improvement by up to a factor of 25 in cross-section sensitivity was achieved., Comment: 7 pages + title and references, 4 figures, and 1 table

Text-to-Image (T2I) models are being increasingly adopted in diverse global communities where they create visual representations of their unique cultures. Current T2I benchmarks primarily focus on faithfulness, aesthetics, and realism of generated images, overlooking the critical dimension of cultural competence. In this work, we introduce a framework to evaluate cultural competence of T2I models along two crucial dimensions: cultural awareness and cultural diversity, and present a scalable approach using a combination of structured knowledge bases and large language models to build a large dataset of cultural artifacts to enable this evaluation. In particular, we apply this approach to build CUBE (CUltural BEnchmark for Text-to-Image models), a first-of-its-kind benchmark to evaluate cultural competence of T2I models. CUBE covers cultural artifacts associated with 8 countries across different geo-cultural regions and along 3 concepts: cuisine, landmarks, and art. CUBE consists of 1) CUBE-1K, a set of high-quality prompts that enable the evaluation of cultural awareness, and 2) CUBE-CSpace, a larger dataset of cultural artifacts that serves as grounding to evaluate cultural diversity. We also introduce cultural diversity as a novel T2I evaluation component, leveraging quality-weighted Vendi score. Our evaluations reveal significant gaps in the cultural awareness of existing models across countries and provide valuable insights into the cultural diversity of T2I outputs for under-specified prompts. Our methodology is extendable to other cultural regions and concepts, and can facilitate the development of T2I models that better cater to the global population., Comment: 30 pages, 10 figures, preprint

In this paper, we compute the WQFT partition function, specifically the eikonal phase in a black hole scattering event in the dynamical Chern-Simons theory, using the techniques of spinning worldline quantum field theory. We consider the scattering of spinning black holes and highlight the necessary details for the calculation of the partition function. We present the $\epsilon$-expansion of the essential two-loop integrals using Integration-by-Parts (IBP) reduction and differential equation techniques, which we then utilize to compute the linear-in-order spin eikonal phase up to 3PM. Additionally, we discuss the dependence of the phase on the spin orientations of the black holes., Comment: 57 Pages

XB 1254-690 is a neutron star low-mass X-ray binary with an orbital period of 3.88 hrs, and it exhibits energy-dependent intensity dips, thermonuclear bursts, and flares. We present the results of an analysis of a long observation of this source using the AstroSat satellite. The X-ray light curve gradually changed from a high-intensity flaring state to a low-intensity one with a few dips. The hardness intensity diagram showed that the source is in a high-intensity banana state with a gradually changing flux. Based on this, we divide the observation into four flux levels for a flux-resolved spectral study. The X-ray spectra can be explained by a model consisting of absorption, thermal emission from the disc and non-thermal emission from the corona. From our studies, we detect a correlation between the temperature of the thermal component and the flux and we examine the implications of our results for the accretion disc geometry of this source., Comment: Accepted for publication in MNRAS; 11 pages, 12 figures

This paper introduces Helios, the first extremely low-power, real-time, event-based hand gesture recognition system designed for all-day on smart eyewear. As augmented reality (AR) evolves, current smart glasses like the Meta Ray-Bans prioritize visual and wearable comfort at the expense of functionality. Existing human-machine interfaces (HMIs) in these devices, such as capacitive touch and voice controls, present limitations in ergonomics, privacy and power consumption. Helios addresses these challenges by leveraging natural hand interactions for a more intuitive and comfortable user experience. Our system utilizes a extremely low-power and compact 3mmx4mm/20mW event camera to perform natural hand-based gesture recognition for always-on smart eyewear. The camera's output is processed by a convolutional neural network (CNN) running on a NXP Nano UltraLite compute platform, consuming less than 350mW. Helios can recognize seven classes of gestures, including subtle microgestures like swipes and pinches, with 91% accuracy. We also demonstrate real-time performance across 20 users at a remarkably low latency of 60ms. Our user testing results align with the positive feedback we received during our recent successful demo at AWE-USA-2024., Comment: Accepted at ECCV-Integrating Computer Vision in Smart Eyewear, 2024. 18 pages, 10 figures. First three authors contributed equally to this paper

Recent work shows Large Language Models (LLMs) struggle to understand natural language constraints for various text generation tasks in zero- and few-shot settings. While, in the code domain, there is wide usage of constraints in code format to maintain the integrity of code written in Domain-Specific Languages (DSLs) like JSON and YAML which are widely used for system-level programming tasks in enterprises. Given that LLMs are increasingly used for system-level code tasks, evaluating if they can comprehend these code constraints is crucial. However, no work has been done to evaluate their controllability over code constraints. Hence, we introduce ConCodeEval, a first-of-its-kind benchmark having two novel tasks for code constraints across five representations. Our findings suggest that language models struggle with code constraints. Code languages that perform excellently for normal code tasks do not perform well when the same languages represent fine-grained constraints.

In document-level neural machine translation (DocNMT), multi-encoder approaches are common in encoding context and source sentences. Recent studies \cite{li-etal-2020-multi-encoder} have shown that the context encoder generates noise and makes the model robust to the choice of context. This paper further investigates this observation by explicitly modelling context encoding through multi-task learning (MTL) to make the model sensitive to the choice of context. We conduct experiments on cascade MTL architecture, which consists of one encoder and two decoders. Generation of the source from the context is considered an auxiliary task, and generation of the target from the source is the main task. We experimented with German--English language pairs on News, TED, and Europarl corpora. Evaluation results show that the proposed MTL approach performs better than concatenation-based and multi-encoder DocNMT models in low-resource settings and is sensitive to the choice of context. However, we observe that the MTL models are failing to generate the source from the context. These observations align with the previous studies, and this might suggest that the available document-level parallel corpora are not context-aware, and a robust sentence-level model can outperform the context-aware models., Comment: Accepted to EAMT 2024 (poster)

This study presents an orbital phase-dependent analysis of three black widow spider millisecond pulsars (BW MSPs), aiming to investigate the magnetic field within the eclipse environment. The ultra-wide-bandwidth low-frequency receiver (UWL) of the Parkes 'Murriyang' radio telescope is utilised for full polarisation observations covering frequencies from 704-4032 MHz. Depolarisation of pulsed emission is observed during the eclipse phase of three BW MSPs namely, J0024-7204J, J1431-4715 and PSR J1959+2048, consistent with previous studies of other BW MSPs. We estimated orbital phase dependent RM values for these MSPs. The wide bandwidth observations also provided the constraints on eclipse cutoff frequency for these BW MSPs. For PSR J0024-7204J, we report temporal variation of the eclipse cutoff frequency coupled with changes in the electron column density within the eclipse medium across six observed eclipses. Moreover, the eclipse cutoff frequency for PSR J1431-4715 is determined to be 1251 $\pm$ 80 MHz, leading to the conclusion that synchrotron absorption is the primary mechanism responsible for the eclipsing. Additionally, for PSR J1959+2048, the estimated cutoff frequency exceeded 1400 MHz, consistent with previous studies. With this investigation, we have doubled the sample size of BW MSPs with orbital phase-resolved studies allowing a better probe to the eclipse environment., Comment: Accepted for publication in ApJ

The demand for efficient and accurate assessment methods has intensified as education systems transition to digital platforms. Providing feedback is essential in educational settings and goes beyond simply conveying marks as it justifies the assigned marks. In this context, we present a significant advancement in automated grading by introducing Engineering Short Answer Feedback (EngSAF) -- a dataset of 5.8k student answers accompanied by reference answers and questions for the Automatic Short Answer Grading (ASAG) task. The EngSAF dataset is meticulously curated to cover a diverse range of subjects, questions, and answer patterns from multiple engineering domains. We leverage state-of-the-art large language models' (LLMs) generative capabilities with our Label-Aware Synthetic Feedback Generation (LASFG) strategy to include feedback in our dataset. This paper underscores the importance of enhanced feedback in practical educational settings, outlines dataset annotation and feedback generation processes, conducts a thorough EngSAF analysis, and provides different LLMs-based zero-shot and finetuned baselines for future comparison. Additionally, we demonstrate the efficiency and effectiveness of the ASAG system through its deployment in a real-world end-semester exam at the Indian Institute of Technology Bombay (IITB), showcasing its practical viability and potential for broader implementation in educational institutions.

Bayes nets are extensively used in practice to efficiently represent joint probability distributions over a set of random variables and capture dependency relations. In a seminal paper, Chickering et al. (JMLR 2004) showed that given a distribution $\mathbb{P}$, that is defined as the marginal distribution of a Bayes net, it is $\mathsf{NP}$-hard to decide whether there is a parameter-bounded Bayes net that represents $\mathbb{P}$. They called this problem LEARN. In this work, we extend the $\mathsf{NP}$-hardness result of LEARN and prove the $\mathsf{NP}$-hardness of a promise search variant of LEARN, whereby the Bayes net in question is guaranteed to exist and one is asked to find such a Bayes net. We complement our hardness result with a positive result about the sample complexity that is sufficient to recover a parameter-bounded Bayes net that is close (in TV distance) to a given distribution $\mathbb{P}$, that is represented by some parameter-bounded Bayes net, generalizing a degree-bounded sample complexity result of Brustle et al. (EC 2020)., Comment: 15 pages, 2 figures

We explore both experimental and theoretical aspects of the superconducting properties in the distinctive layered caged compound, Ba$_{3}$Ir$_{4}$Ge$_{16}$. Our approach integrates muon spin rotation and relaxation ($\mu$SR) measurements with magnetization and heat capacity experiments, accompanied by first-principle calculations. The compound's bulk superconductivity is unequivocally established through DC magnetization measurements, revealing a critical temperature ($T_\mathrm{C}$) of 5.7 K. A noteworthy characteristic observed in the low-temperature superfluid density is its saturating behavior, aligning with the features typical of conventional Bardeen-Cooper-Schrieffer (BCS) superconductors. The assessment of moderate electron-phonon coupling superconductivity is conducted through transverse field $\mu$SR measurements, yielding a superconducting gap to $T_\mathrm{C}$ ratio ($2\Delta(0)/k_\mathrm{B}T_\mathrm{C}$) of 4.04, a value corroborated by heat capacity measurements. Crucially, zero field $\mu$SR measurements dismiss the possibility of any spontaneous magnetic field emergence below $T_\mathrm{C}$, highlighting the preservation of time-reversal symmetry. Our experimental results are reinforced by first-principles density functional calculations, underscoring the intricate interplay between crystal structure and superconducting order parameter symmetry in polyhedral caged compounds. This comprehensive investigation enhances our understanding of the nuanced relationship between crystal structure and superconductivity in such unique compounds.

In this study, we present a thorough investigation into the superconducting state of the ruthenium-based ternary equiatomic compound ScRuSi. Our analysis combines experimental techniques, including muon spin rotation/relaxation ($\mu$SR) and low-temperature resistivity measurements, with theoretical insights derived from first-principles calculations. The low-temperature resistivity measurements reveal a distinct superconducting phase transition in the orthorhombic structure of ScRuSi at a critical temperature ($T_\text{C}$) of $2.5$ K. Further, the TF-$\mu$SR analysis yields a gap-to-critical-temperature ratio of $2\Delta/k_\mathrm{B}T_\mathrm{C} = 2.71$, a value consistent with results obtained from previous heat capacity measurements. The temperature dependence of the superconducting normalized depolarization rate is fully described by the isotropic $s$-wave gap model. Additionally, zero-field $\mu$SR measurements indicate that the relaxation rate remains nearly identical below and above $T_\text{C}$. This observation strongly suggests the preservation of time-reversal symmetry within the superconducting state. By employing the McMillan-Allen-Dynes equation, we calculate a $T_\text{C}$ of $2.11$ K from first-principles calculations within the density functional theory framework. This calculated value aligns closely with the experimentally determined critical temperature. The coupling between the low-frequency phonon modes and the transition metal d-orbital states play an important role in governing the superconducting pairing in ScRuSi. The combination of experimental and theoretical approaches provides a comprehensive microscopic understanding of the superconducting nature of ScRuSi, offering insights into its critical temperature, pairing symmetry, and the underlying electron-phonon coupling mechanism., Comment: 10 pages, 7 figures

The strength of the HI signal originating from a distant galaxy at a cosmological distance is several orders of magnitude lower than the foreground and background noise and hence it is difficult to observe this signal at a given radio telescope. However, a few recent studies reported the detection of that signal at the radio band suggests the strength of this signal is somehow magnified. In this analysis, we study the prospects of detecting this signal at different frequency bands of the uGMRT where this signal is supposed to be amplified through the strong gravitational lensing by an isolated neutron star located in a cosmological distance. Our study shows the effects of the lensing parameters on the observables of that amplified signal and discusses its variation with the frequency bands considered here. We present a method to estimate the position and size of an isolated neutron star using the signal-to-noise ratio of that signal supposed to be detected at different frequency bands of the uGMRT. We discuss the scope of multi-messenger astronomy in the era of HI observation where the estimated lensing parameters can be cross-validated using the pulsar detection at the X-ray band from the same location in the sky. Our analysis is equally applicable to any radio telescope with given specifications., Comment: 16 Pages, 4 figures, comments and suggestions are welcome

Bangla (Bengali) is the fifth most spoken language globally and, yet, the problem of automatic grammar correction in Bangla is still in its nascent stage. This is mostly due to the need for a large corpus of grammatically incorrect sentences, with their corresponding correct counterparts. The present state-of-the-art techniques to curate a corpus for grammatically wrong sentences involve random swapping, insertion and deletion of words. However,these steps may not always generate grammatically wrong sentences in Bangla. In this work, we propose a pragmatic approach to generate grammatically wrong sentences in Bangla. We first categorize the different kinds of errors in Bangla into 5 broad classes and 12 finer classes. We then use these to generate grammatically wrong sentences systematically from a correct sentence. This approach can generate a large number of wrong sentences and can, thus, mitigate the challenge of lacking a large corpus for neural networks. We provide a dataset, Vaiyakarana, consisting of 92,830 grammatically incorrect sentences as well as 18,426 correct sentences. We also collected 619 human-generated sentences from essays written by Bangla native speakers. This helped us to understand errors that are more frequent. We evaluated our corpus against neural models and LLMs and also benchmark it against human evaluators who are native speakers of Bangla. Our analysis shows that native speakers are far more accurate than state-of-the-art models to detect whether the sentence is grammatically correct. Our methodology of generating erroneous sentences can be applied for most other Indian languages as well.

Machine Translation (MT) between linguistically dissimilar languages is challenging, especially due to the scarcity of parallel corpora. Prior works suggest that pivoting through a high-resource language can help translation into a related low-resource language. However, existing works tend to discard the source sentence when pivoting. Taking the case of English to Indian language MT, this paper explores the 'multi-source translation' approach with pivoting, using both source and pivot sentences to improve translation. We conducted extensive experiments with various multi-source techniques for translating English to Konkani, Manipuri, Sanskrit, and Bodo, using Hindi, Marathi, and Bengali as pivot languages. We find that multi-source pivoting yields marginal improvements over the state-of-the-art, contrary to previous claims, but these improvements can be enhanced with synthetic target language data. We believe multi-source pivoting is a promising direction for Low-resource translation.

We present the first X-ray spectropolarimetric results for Cygnus X-1 in its soft state from a campaign of five IXPE observations conducted during 2023 May-June. Companion multiwavelength data during the campaign are likewise shown. The 2-8 keV X-rays exhibit a net polarization degree PD=1.99%+/-0.13% (68% confidence). The polarization signal is found to increase with energy across IXPE's 2-8 keV bandpass. The polarized X-rays exhibit an energy-independent polarization angle of PA=-25.7+/-1.8 deg. East of North (68% confidence). This is consistent with being aligned to Cyg X-1's AU-scale compact radio jet and its pc-scale radio lobes. In comparison to earlier hard-state observations, the soft state exhibits a factor of 2 lower polarization degree, but a similar trend with energy and a similar (also energy-independent) position angle. When scaling by the natural unit of the disk temperature, we find the appearance of a consistent trendline in the polarization degree between soft and hard states. Our favored polarimetric model indicates Cyg X-1's spin is likely high (a* above ~0.96). The substantial X-ray polarization in Cyg X-1's soft state is most readily explained as resulting from a large portion of X-rays emitted from the disk returning and reflecting off the disk surface, generating a high polarization degree and a polarization direction parallel to the black hole spin axis and radio jet. In IXPE's bandpass, the polarization signal is dominated by the returning reflection emission. This constitutes polarimetric evidence for strong gravitational lensing of X-rays close to the black hole., Comment: 20 pages, accepted for publication in ApJL

Recent developments show that Large Language Models (LLMs) produce state-of-the-art performance on natural language (NL) to code generation for resource-rich general-purpose languages like C++, Java, and Python. However, their practical usage for structured domain-specific languages (DSLs) such as YAML, JSON is limited due to domain-specific schema, grammar, and customizations generally unseen by LLMs during pre-training. Efforts have been made to mitigate this challenge via in-context learning through relevant examples or by fine-tuning. However, it suffers from problems, such as limited DSL samples and prompt sensitivity but enterprises maintain good documentation of the DSLs. Therefore, we propose DocCGen, a framework that can leverage such rich knowledge by breaking the NL-to-Code generation task for structured code languages into a two-step process. First, it detects the correct libraries using the library documentation that best matches the NL query. Then, it utilizes schema rules extracted from the documentation of these libraries to constrain the decoding. We evaluate our framework for two complex structured languages, Ansible YAML and Bash command, consisting of two settings: Out-of-domain (OOD) and In-domain (ID). Our extensive experiments show that DocCGen consistently improves different-sized language models across all six evaluation metrics, reducing syntactic and semantic errors in structured code. We plan to open-source the datasets and code to motivate research in constrained code generation.

Code-switching is a widely prevalent linguistic phenomenon in multilingual societies like India. Building speech-to-text models for code-switched speech is challenging due to limited availability of datasets. In this work, we focus on the problem of spoken translation (ST) of code-switched speech in Indian languages to English text. We present a new end-to-end model architecture COSTA that scaffolds on pretrained automatic speech recognition (ASR) and machine translation (MT) modules (that are more widely available for many languages). Speech and ASR text representations are fused using an aligned interleaving scheme and are fed further as input to a pretrained MT module; the whole pipeline is then trained end-to-end for spoken translation using synthetically created ST data. We also release a new evaluation benchmark for code-switched Bengali-English, Hindi-English, Marathi-English and Telugu- English speech to English text. COSTA significantly outperforms many competitive cascaded and end-to-end multimodal baselines by up to 3.5 BLEU points.

Opinion summarization in e-commerce encapsulates the collective views of numerous users about a product based on their reviews. Typically, a product on an e-commerce platform has thousands of reviews, each review comprising around 10-15 words. While Large Language Models (LLMs) have shown proficiency in summarization tasks, they struggle to handle such a large volume of reviews due to context limitations. To mitigate, we propose a scalable framework called Xl-OpSumm that generates summaries incrementally. However, the existing test set, AMASUM has only 560 reviews per product on average. Due to the lack of a test set with thousands of reviews, we created a new test set called Xl-Flipkart by gathering data from the Flipkart website and generating summaries using GPT-4. Through various automatic evaluations and extensive analysis, we evaluated the framework's efficiency on two datasets, AMASUM and Xl-Flipkart. Experimental results show that our framework, Xl-OpSumm powered by Llama-3-8B-8k, achieves an average ROUGE-1 F1 gain of 4.38% and a ROUGE-L F1 gain of 3.70% over the next best-performing model.

Mental disorders pose a global challenge, aggravated by the shortage of qualified mental health professionals. Mental disorder prediction from social media posts by current LLMs is challenging due to the complexities of sequential text data and the limited context length of language models. Current language model-based approaches split a single data instance into multiple chunks to compensate for limited context size. The predictive model is then applied to each chunk individually, and the most voted output is selected as the final prediction. This results in the loss of inter-post dependencies and important time variant information, leading to poor performance. We propose a novel framework which first compresses the large sequence of chronologically ordered social media posts into a series of numbers. We then use this time variant representation for mental disorder classification. We demonstrate the generalization capabilities of our framework by outperforming the current SOTA in three different mental conditions: depression, self-harm, and anorexia, with an absolute improvement of 5% in the F1 score. We investigate the situation where current data instances fall within the context length of language models and present empirical results highlighting the importance of temporal properties of textual data. Furthermore, we utilize the proposed framework for a cross-domain study, exploring commonalities across disorders and the possibility of inter-domain data usage., Comment: RK and KM contributed equally to this work, 15 pages, 5 figures, 9 table