Search

We present the results of a search for gravitational-wave transients associated with core-collapse supernova SN 2023ixf, which was observed in the galaxy Messier 101 via optical emission on 2023 May 19th, during the LIGO-Virgo-KAGRA 15th Engineering Run. We define a five-day on-source window during which an accompanying gravitational-wave signal may have occurred. No gravitational waves have been identified in data when at least two gravitational-wave observatories were operating, which covered $\sim 14\%$ of this five-day window. We report the search detection efficiency for various possible gravitational-wave emission models. Considering the distance to M101 (6.7 Mpc), we derive constraints on the gravitational-wave emission mechanism of core-collapse supernovae across a broad frequency spectrum, ranging from 50 Hz to 2 kHz where we assume the GW emission occurred when coincident data are available in the on-source window. Considering an ellipsoid model for a rotating proto-neutron star, our search is sensitive to gravitational-wave energy $1 \times 10^{-5} M_{\odot} c^2$ and luminosity $4 \times 10^{-5} M_{\odot} c^2/\text{s}$ for a source emitting at 50 Hz. These constraints are around an order of magnitude more stringent than those obtained so far with gravitational-wave data. The constraint on the ellipticity of the proto-neutron star that is formed is as low as $1.04$, at frequencies above $1200$ Hz, surpassing results from SN 2019ejj., Comment: Main paper: 6 pages, 4 figures and 1 table. Total with appendices: 20 pages, 4 figures, and 1 table

Pressure-induced emission enhancement and bandgap narrowing in vacancy-ordered halide double perovskite $Cs_2TeBr_6$ are extensively investigated through photoluminescence and absorption experiments. The below bandgap broad emission is attributed to self-trapped excitons recombination. The $Cs_2TeBr_6$ crystal, consisting of undistorted octahedra, exhibits substantial emission enhancement due to the lowering of the energy barrier between $^3P_1$ and self-trapped exciton states, as well as the suppression of nonradiative energy loss with increasing pressure. In the Raman measurements, the observed behavior of full width at half maximum of all Raman modes implies dominant electron-phonon interactions rather than anharmonic interactions between phonons. The pressure-dependent X-ray diffraction measurements reveal an anomalous behaviour in the normalized pressure as a function of the Eulerian strain.

The magnetar SGR 1935+2154 is the only known Galactic source of fast radio bursts (FRBs). FRBs from SGR 1935+2154 were first detected by CHIME/FRB and STARE2 in 2020 April, after the conclusion of the LIGO, Virgo, and KAGRA Collaborations' O3 observing run. Here we analyze four periods of gravitational wave (GW) data from the GEO600 detector coincident with four periods of FRB activity detected by CHIME/FRB, as well as X-ray glitches and X-ray bursts detected by NICER and NuSTAR close to the time of one of the FRBs. We do not detect any significant GW emission from any of the events. Instead, using a short-duration GW search (for bursts $\leq$ 1 s) we derive 50\% (90\%) upper limits of $10^{48}$ ($10^{49}$) erg for GWs at 300 Hz and $10^{49}$ ($10^{50}$) erg at 2 kHz, and constrain the GW-to-radio energy ratio to $\leq 10^{14} - 10^{16}$. We also derive upper limits from a long-duration search for bursts with durations between 1 and 10 s. These represent the strictest upper limits on concurrent GW emission from FRBs., Comment: 15 pages of text including references, 4 figures, 5 tables

Motivated by Gromov's geodesic flow problem on hyperbolic groups $G$, we develop in this paper an analog using random walks. This leads to a notion of a harmonic analog $\Theta$ of the Bowen-Margulis-Sullivan measure on $\partial^2 G$. We provide three different but related constructions of $\Theta$: 1) by moving the base-point along a quasigeodesic ray 2) by moving the base-point along random walk trajectories 3) directly as a push-forward under the boundary map to $\partial^2 G$ of a measure inherited from studying all bi-infinite random walk trajectories (with no restriction on base-point) on $G^{\mathbb{Z}}$. Of these, the third construction is the most involved and needs new techniques. It relies on developing a framework where we can treat bi-infinite random walk trajectories as analogs of bi-infinite geodesics on complete simply connected negatively curved manifolds. Geodesic flow on a hyperbolic group is typically not well-defined due to non-uniqueness of geodesics. We circumvent this problem in the random walk setup by considering \emph{all} trajectories. We thus get a well-defined \emph{discrete flow} given by the $\mathbb{Z}-$shift on bi-infinite random walk trajectories. The $\mathbb{Z}-$shift is the random analog of the time one map of the geodesic flow. As an analog of ergodicity of the geodesic flow on a closed negatively curved manifold, we establish ergodicity of the $G$-action on $(\partial^2G, \Theta)$.

A fundamental longstanding problem in studying spin models is the efficient and accurate numerical simulation of the long-time behavior of larger systems. The exponential growth of the Hilbert space and the entanglement accumulation at long times pose major challenges for current methods. To address these issues, we employ the multilayer multiconfiguration time-dependent Hartree (ML-MCTDH) framework to simulate the many-body spin dynamics of the Heisenberg model in various settings, including the Ising and XYZ limits with different interaction ranges and random couplings. Benchmarks with analytical and exact numerical approaches show that ML-MCTDH accurately captures the time evolution of one- and two-body observables in both one- and two-dimensional lattices. A comparison of ML-MCTDH with the discrete truncated Wigner approximation (DTWA) demonstrates that our approach excels in handling anisotropic models and consistently provides better results for two-point observables in all simulation instances. Our results indicate that the multilayer structure of ML-MCTDH is a promising numerical framework for handling the dynamics of generic many-body spin systems., Comment: 12 pages, 9 figures

Despite rapid advancements in TTS models, a consistent and robust human evaluation framework is still lacking. For example, MOS tests fail to differentiate between similar models, and CMOS's pairwise comparisons are time-intensive. The MUSHRA test is a promising alternative for evaluating multiple TTS systems simultaneously, but in this work we show that its reliance on matching human reference speech unduly penalises the scores of modern TTS systems that can exceed human speech quality. More specifically, we conduct a comprehensive assessment of the MUSHRA test, focusing on its sensitivity to factors such as rater variability, listener fatigue, and reference bias. Based on our extensive evaluation involving 471 human listeners across Hindi and Tamil we identify two primary shortcomings: (i) reference-matching bias, where raters are unduly influenced by the human reference, and (ii) judgement ambiguity, arising from a lack of clear fine-grained guidelines. To address these issues, we propose two refined variants of the MUSHRA test. The first variant enables fairer ratings for synthesized samples that surpass human reference quality. The second variant reduces ambiguity, as indicated by the relatively lower variance across raters. By combining these approaches, we achieve both more reliable and more fine-grained assessments. We also release MANGO, a massive dataset of 47,100 human ratings, the first-of-its-kind collection for Indian languages, aiding in analyzing human preferences and developing automatic metrics for evaluating TTS systems., Comment: 19 pages, 12 Figures

In this work, we attempted to extend the thought and showcase a way forward for the Self-supervised Learning (SSL) learning paradigm by combining contrastive learning, self-distillation (knowledge distillation) and masked data modelling, the three major SSL frameworks, to learn a joint and coordinated representation. The proposed technique of SSL learns by the collaborative power of different learning objectives of SSL. Hence to jointly learn the different SSL objectives we proposed a new SSL architecture KDC-MAE, a complementary masking strategy to learn the modular correspondence, and a weighted way to combine them coordinately. Experimental results conclude that the contrastive masking correspondence along with the KD learning objective has lent a hand to performing better learning for multiple modalities over multiple tasks.

This study presents the modeling of the gravitational wave (GW) bias parameter by bridging a connection between simulated GW sources and galaxies in low redshift galaxy surveys 2MPZ and WISExSCOS (WISC). We study this connection by creating a mock GW catalog, populating galaxy surveys with binary black holes (BBHs) for different scenarios of the GW occupation fraction (or selection function) as a function of the galaxy stellar mass. We probe the observable consequences of this connection by exploring the spatial clustering of the GW sources in terms of the GW bias parameter. We consider a phenomenological broken power law model for the selection function, with a potential turnover $M_{K}$ at high stellar mass ($10^{11}$ $M_{\odot}$ in the fiducial model) where the star formation efficiency begins to drop. We vary the parameters of the selection function and find that generically the GW bias increases as $M_{K}$ increases (and gets suppressed as $M_{K}$ decreases). The change in the GW bias parameter shows a maximum change of about $30\%$ for different scenarios explored in this work in comparison to the galaxy bias. Future measurements of the GW bias can help constrain $M_{K}$ and the slopes of the selection function and thus offer insights into the underlying astrophysical processes., Comment: 29 pages (+15 pages in appendices), 15 figures (+9 figures in appendices), to be submitted to JCAP

We prove that the monodromy diffeomorphism of a complex 2-dimensional isolated hypersurface singularity of weighted-homogeneous type has infinite order in the smooth mapping class group of the Milnor fiber, provided the singularity is not a rational double point. This is a consequence of our main result: the boundary Dehn twist diffeomorphism of an indefinite symplectic filling of the canonical contact structure on a negatively-oriented Seifert-fibered rational homology 3-sphere has infinite order in the smooth mapping class group. Our techniques make essential use of analogues of the contact invariant in the setting of $\mathbb{Z}/p$-equivariant Seiberg--Witten--Floer homology of 3-manifolds., Comment: Comments welcome!

The majority of atomic nuclei have deformed shapes and nearly all these shapes are symmetric with respect to reflection. There are only a few reflection asymmetric pear-shaped nuclei that have been found in actinide and lanthanide regions, which have static octupole deformation. These nuclei possess an intrinsic electric dipole moment due to the shift between the center of charge and the center of mass. This manifests in the enhancement of the electric dipole transition rates. In this article, we report on the measurement of the lifetimes of the high spin levels of the two alternate parity bands in $^{100}$Ru through the Doppler Shift Attenuation Method. The estimated electric dipole transition rates have been compared with the calculated transition rates using the triaxial projected shell model without octupole deformation, and are found to be an order of magnitude enhanced. Thus, the observation of seven inter-leaved electric dipole transitions with enhanced rates establish $^{100}$Ru as possibly the first octupole deformed nucleus reported in the A $\approx$ 100 mass region.

We present JWST/MIRI low-resolution spectroscopy ($4.75-14~\mu$m) of the first known substellar companion, Gliese 229 Bab, which was recently resolved into a tight binary brown dwarf. Previous atmospheric retrieval studies modeling Gliese 229 B as a single brown dwarf have reported anomalously high carbon-to-oxygen ratios (C/O) of $\approx 1.1$ using $1-5~\mu$m ground-based spectra. Here, we fit the MIRI spectrum of Gliese 229 Bab with a two-component binary model using the Sonora Elf Owl grid and additionally account for the observed $K$ band flux ratio of the binary brown dwarf. Assuming the two brown dwarfs share the same abundances, we obtain $\rm C/O=0.65\pm0.05$ and $\rm [M/H]=0.00^{+0.04}_{-0.03}$ as their abundances ($2\sigma$ statistical errors), which are fully consistent with the host star abundances. We also recover the same abundances if we fit the MIRI spectrum with a single brown dwarf model, indicating that binarity does not strongly affect inferred abundances from mid-infrared data when the $T_\rm{eff}$ are similar between components of the binary. We measure $T_\rm{eff}=900^{+78}_{-29}~$K and $T_\rm{eff}=775^{+20}_{-33}~$K for the two brown dwarfs. We find that the vertical diffusion coefficients of $\log{K_\rm{zz}} \approx4.0$ are identical between the two brown dwarfs and in line with $\log{K_\rm{zz}}$ values inferred for isolated brown dwarfs with similar $T_\rm{eff}$. Our results demonstrate the power of mid-infrared spectroscopy in providing robust atmospheric abundance measurements for brown dwarf companions and by extension, giant planets., Comment: Accepted to ApJL

Important advances have recently been made in the search for materials with complex multi-phase landscapes that host photoinduced metastable collective states with exotic functionalities. In almost all cases so far, the desired phases are accessed by exploiting light-matter interactions via the imaginary part of the dielectric function through above-bandgap or resonant mode excitation. Nonresonant Raman excitation of coherent modes has been experimentally observed and proposed for dynamic material control, but the resulting atomic excursion has been limited to perturbative levels. Here, we demonstrate that it is possible to overcome this challenge by employing nonresonant ultrashort pulses with low photon energies well below the bandgap. Using mid-infrared pulses, we induce ferroelectric reversal in lithium niobate and phase switching in tin selenide and characterize the large-amplitude mode displacements through femtosecond Raman scattering, second harmonic generation, and x-ray diffraction. This approach, validated by first-principle calculations, defines a novel method for synthesizing hidden phases with unique functional properties and manipulating complex energy landscapes at reduced energy consumption and ultrafast speeds., Comment: 5 figures

The study of $\bar{B} \to D^* \tau {\bar{\nu}}_\tau$ angular distribution can be used to get information about new physics, which has been motivated by the presence of various $B$ anomalies. However, the inability to measure precisely the three-momentum of tau hinders this process, as the tau decay contains one or more undetected neutrinos. In this work, we present a measurable angular distribution of $\bar{B} \to D^* \tau {\bar{\nu}}_\tau$ by considering the additional decay $\tau \to \ell \nu_\tau \bar{\nu}_\ell$, where $\ell \in \{ e , \mu \}$. The full process used is $\bar{B} \to D^* (\to D \pi) \tau (\to \ell \nu_\tau \bar{\nu}_\ell) \bar{\nu}_\tau$, where only the $\ell$ and $D^*$ are reconstructed, and a fit to the experimental angular distribution of this process can be used to extract information on new physics parameters. To demonstrate, we generate simulated data for this process and perform a sensitivity study to obtain the expected statistical errors on new physics parameters from experiments in the near future. We obtained a sensitivity of the order of 5% for the right-handed current and around 6% for the tensor current. In addition, we use the recent lattice QCD data on $B \to D^*$ form factors and obtain correlations between form factors and new physics parameters., Comment: 40 pages, 8 figures

This paper studies a graph-based sensor deployment approach in wireless sensor networks (WSNs). Specifically, in today's world, where sensors are everywhere, detecting various attributes like temperature and movement, their deteriorating lifetime is indeed a very concerning issue. In many scenarios, these sensors are placed in extremely remote areas, where maintenance becomes challenging. As a result, it is not very wise to depend on a single sensor to obtain data from a particular terrain or place. Hence, multiple sensors are deployed in these places, such that no problem arises if one or few of them fail. In this work, this problem of intelligent placement of sensors is modelled from the graph theoretic point of view. We propose a new sensor deployment approach here, which results in lesser sensor density per unit area and less number of sensors as compared to the existing benchmark schemes. Finally, the numerical results also support our claims and provide insights regarding the selection of parameters that enhance the system performance., Comment: Submitted for a possible publication

We study the multi-agent Smoothed Online Convex Optimization (SOCO) problem, where $N$ agents interact through a communication graph. In each round, each agent $i$ receives a strongly convex hitting cost function $f^i_t$ in an online fashion and selects an action $x^i_t \in \mathbb{R}^d$. The objective is to minimize the global cumulative cost, which includes the sum of individual hitting costs $f^i_t(x^i_t)$, a temporal "switching cost" for changing decisions, and a spatial "dissimilarity cost" that penalizes deviations in decisions among neighboring agents. We propose the first decentralized algorithm for multi-agent SOCO and prove its asymptotic optimality. Our approach allows each agent to operate using only local information from its immediate neighbors in the graph. For finite-time performance, we establish that the optimality gap in competitive ratio decreases with the time horizon $T$ and can be conveniently tuned based on the per-round computation available to each agent. Moreover, our results hold even when the communication graph changes arbitrarily and adaptively over time. Finally, we establish that the computational complexity per round depends only logarithmically on the number of agents and almost linearly on their degree within the graph, ensuring scalability for large-system implementations., Comment: 39 pages

Recent lattice quantum chromodynamics (lQCD) computations of bottomonium correlation functions with extended sources provide new insights into heavy-quark dynamics at distance scales which are of the order of the inverse temperature. We analyze these results employing the thermodynamic T-matrix approach, in a continued effort to interpret lQCD data for quarkonium correlation functions in a non-perturbative framework suitable for strongly coupled systems. Its key inputs are the in-medium driving kernel (potential) of the scattering equation and an interference function which implements 3-body effects in the quarkonium coupling to the thermal medium. A simultaneous description of lQCD results for the bottomonium correlators with extended operators and the previously analyzed Wilson line correlators only requires minor refinements of the potential but calls for stronger interference effects at larger separation of the bottom quark and antiquark. We then analyze the poles of the self-consistent T-matrices on the real axis to assess the survival of the various bound states. We estimate the pertinent temperatures where the poles disappear for the various bottomonium states and discuss the relation to the corresponding peaks in the bottomonium spectral functions. We also recalculate the spatial diffusion coefficient of the QGP and find it to be similar to that in our previous study., Comment: 30 pages, 17 figures

Supernovae represent some of the most energetically explosive events in the universe, with a substantial fraction of their released gravitational energy carried away by neutrinos. This study evaluates the sensitivity of three next-generation neutrino detectors which are Deep Underground Neutrino Experiment (DUNE), Hyper-Kamiokande (Hyper-K), and the Jiangmen Underground Neutrino Observatory (JUNO) to supernova neutrinos, specifically focusing on their ability to discern between normal and inverted mass hierarchies. We utilize three different flux models: Bollig, Tamborra and Nakazato, employing the SNEWPY software to simulate the expected neutrino fluxes from core-collapse supernovae. These models highlight the variability in the predictions due to different progenitors and simulation methods. By analyzing the event rates across various interaction channels and implementing the adiabatic Mikheyev-Smirnov-Wolfenstein (MSW) effect on the neutrino flux, we have calculated the expected detection rates for each detector. Our results indicate that sensitivities range from ${\sim}3\sigma$ to ${\sim}9\sigma$ for DUNE, ${\sim}4\sigma$ to ${\sim}16\sigma$ for Hyper-K and ${\sim}1.7\sigma$ to ${\sim}6.7\sigma$ for JUNO depending on distance and flux model, with sensitivity diminishing significantly at larger distances. This work underscores the potential of future neutrino observatories to enhance our understanding of fundamental physics through the study of supernova neutrinos.

Given a row-finite higher-rank $k$-graph $\Lambda$, we define a commutative monoid $T_\Lambda$ which is a higher-rank analogue of the talented monoid of a directed graph. The talented monoid $T_\Lambda$ is canonically a $\mathbb{Z}^k$-monoid with respect to the action of state shift. This monoid coincides with the positive cone of the graded Grothendieck group $K_0^{gr}(KP_\mathsf{k}(\Lambda))$ of the Kumjian-Pask algebra $KP_\mathsf{k}(\Lambda)$ with coefficients in a field $\mathsf{k}$. The aim of the paper is to investigate this $\mathbb{Z}^k$-monoid as a capable invariant for classification of Kumjian-Pask algebras. If $\mathbb{Z}^k$ acts freely on $T_\Lambda$ (i.e., if $T_\Lambda$ has no nonzero periodic element), then we show that the $k$-graph $\Lambda$ is aperiodic. The converse is also proved to be true provided $\Lambda$ has no sources and $T_\Lambda$ is atomic. Moreover in this case, we provide a talented monoid characterization for strongly aperiodic $k$-graphs. We prove that for a row-finite $k$-graph $\Lambda$ without sources, cofinality is equivalent to the simplicity of $T_\Lambda$ as a $\mathbb{Z}^k$-monoid. In view of this we provide a talented monoid criterion for the Kumjian-Pask algebra $KP_R(\Lambda)$ of $\Lambda$ over a unital commutative ring $R$ to be graded basic ideal simple. We also describe the minimal left ideals of $KP_\mathsf{k}(\Lambda)$ in terms of the aperiodic atoms of $T_\Lambda$ and thus obtain a monoid theoretic characterization for $Soc(KP_\mathsf{k}(\Lambda)$) to be an essential ideal. These results help us to characterize semisimple Kumjian-Pask algebras through the lens of $T_\Lambda$.

Gravitational Wave (GW) sources offer a valuable window to the physical processes that govern the formation of binary compact objects (BCOs). However, deciphering such information from GW data is substantially challenging due to the difficulty in mapping from the space of observation to the space of numerous theoretical models. We introduce the concept of BCO Phase-Space that connects the observable space to the evolution trajectories of the BCO formation channels with cosmic time and apply it to the third GW transient catalog (GWTC-3) that brings new insights into probable astrophysical formation scenarios of nearly $90$ events. Our study reveals that two events, GW190425 and GW230529, show an overlap with a $\texttt{BCO Phase Space}$ trajectory of the same formation channel arising from a sub-solar mass black hole scenario that has grown into a higher mass by accretion, hinting towards the common primordial origin of both these sources. Though the actual formation channel is yet to be confirmed, with the availability of more GW events, the $\texttt{BCO Phase Space}$ can delve into distinguishing features of different formation channels for both astrophysical and primordial origin and opens the possibility of bringing new and deeper insights on the formation and evolution of BCOs across all observable masses over most of the cosmic time., Comment: 5 (+10 in Appendix) pages, 2 (+9 in Appendix) figures

Vehicle-to-Everything (V2X) communication, which includes Vehicle-to-Infrastructure (V2I), Vehicle-to-Vehicle (V2V), and Vehicle-to-Pedestrian (V2P) networks, is gaining significant attention due to the rise of connected and autonomous vehicles. V2X systems require diverse Quality of Service (QoS) provisions, with V2V communication demanding stricter latency and reliability compared to V2I. The 5G New Radio-V2X (NR-V2X) standard addresses these needs using multi-numerology Orthogonal Frequency Division Multiple Access (OFDMA), which allows for flexible allocation of radio resources. However, V2I and V2V users sharing the same radio resources leads to interference, necessitating efficient power and resource allocation. In this work, we propose a novel resource allocation and sharing algorithm for 5G-based V2X systems. Our approach first groups Resource Blocks (RBs) into Resource Chunks (RCs) and allocates them to V2I users using the Gale-Shapley stable matching algorithm. Power is then allocated to RCs to facilitate efficient resource sharing between V2I and V2V users through a bisection search method. Finally, the Gale-Shapley algorithm is used to pair V2I and V2V users, maintaining low computational complexity while ensuring high performance. Simulation results demonstrate that our proposed Gale-Shapley Resource Allocation with Gale-Shapley Sharing (GSRAGS) achieves competitive performance with lower complexity compared to existing works while effectively meeting the QoS demands of V2X communication systems., Comment: 8 pages, 10 figures

We present a comprehensive first-principles analysis of the thermoelectric transport properties of hole-doped pyrite FeS$_2$ that includes electron-phonon interactions. This work was motivated by the observed variations in the magnitude of thermopower reported in previous experimental and theoretical studies of hole-doped FeS$_2$ systems. Our calculations reveal that hole-doped FeS$_2$ exhibits large positive room-temperature thermopower across all doping levels, with a room-temperature thermopower of 608 $\mu$V/K at a low hole-doping concentration of 10$^{19}$ cm$^{-3}$. This promising thermopower finding prompted a comprehensive investigation of other key thermoelectric parameters governing the thermoelectric figure of merit $ZT$. The calculated electrical conductivity is modest and remains below 10$^5$ S/m at room-temperature for all doping levels, limiting the achievable power factor. Furthermore, the thermal conductivity is found to be phonon driven, with a high room-temperature lattice thermal conductivity of 40.5 W/mK. Consequently, the calculated $ZT$ remains below 0.1, suggesting that hole-doped FeS$_2$ may not a viable candidate for effective thermoelectric applications despite its promising thermopower., Comment: 8 pages, 10 figures, 1 table, 6 equations

We conduct a scoping review of existing approaches for synthetic EHR data generation, and benchmark major methods with proposed open-source software to offer recommendations for practitioners. We search three academic databases for our scoping review. Methods are benchmarked on open-source EHR datasets, MIMIC-III/IV. Seven existing methods covering major categories and two baseline methods are implemented and compared. Evaluation metrics concern data fidelity, downstream utility, privacy protection, and computational cost. 42 studies are identified and classified into five categories. Seven open-source methods covering all categories are selected, trained on MIMIC-III, and evaluated on MIMIC-III or MIMIC-IV for transportability considerations. Among them, GAN-based methods demonstrate competitive performance in fidelity and utility on MIMIC-III; rule-based methods excel in privacy protection. Similar findings are observed on MIMIC-IV, except that GAN-based methods further outperform the baseline methods in preserving fidelity. A Python package, ``SynthEHRella'', is provided to integrate various choices of approaches and evaluation metrics, enabling more streamlined exploration and evaluation of multiple methods. We found that method choice is governed by the relative importance of the evaluation metrics in downstream use cases. We provide a decision tree to guide the choice among the benchmarked methods. Based on the decision tree, GAN-based methods excel when distributional shifts exist between the training and testing populations. Otherwise, CorGAN and MedGAN are most suitable for association modeling and predictive modeling, respectively. Future research should prioritize enhancing fidelity of the synthetic data while controlling privacy exposure, and comprehensive benchmarking of longitudinal or conditional generation methods.

New physics and systematic errors can lead to deviations between the models used to analyze gravitational wave data and the actual signal. Such deviations will generally be correlated between detectors and manifest differently across the gravitational wave source parameter space. The previously introduced \ttt{SCoRe} framework uses these features to distinguish these deviations from noise and extract physical information from their source-dependent variation. In this work, we further analyze the hierarchical component of the method -- we include the expected dependence of the deviations on the source parameters into the inference process, obtaining more physically informative results. As a specific example, we study a deviation that scales as a power law of the mass scale of black hole binaries -- as, for example, in Effective Field Theory of gravity. We show how the signal-to-noise ratio of the cross-correlated residual power can be used to recover the power-law index. We demonstrate how both the distribution in source and deviation strength determine which region of source parameter space influences the inference most. Finally, we forecast the constraint on the power law index for a network of two Cosmic Explorer-like detectors with a year of observation period., Comment: 18 pages, 10 figures

The $\Lambda$ Cold Dark Matter ($\Lambda$CDM) cosmological model has been highly successful in predicting cosmic structure and evolution, yet recent precision measurements have highlighted discrepancies, especially in the Hubble constant inferred from local and early-Universe data. Gamma-ray bursts (GRBs) present a promising alternative for cosmological measurements, capable of reaching higher redshifts than traditional distance indicators. This work leverages GRBs to refine cosmological parameters independently of the $\Lambda$CDM framework. Using the Platinum compilation of long GRBs, we calibrate the Dainotti relations-empirical correlations among GRB luminosity properties-as standard candles through artificial neural networks (ANNs). We analyze both the 2D and 3D Dainotti calibration relations, leveraging an ANN-driven Markov Chain Monte Carlo approach to minimize scatter in the calibration parameters, thereby achieving a stable Hubble diagram. This ANN-based calibration approach offers advantages over Gaussian processes, avoiding issues such as kernel function dependence and overfitting. Our results emphasize the need for model-independent calibration approaches to address systematic challenges in GRB luminosity variability, ultimately extending the cosmic distance ladder in a robust way. By addressing redshift evolution and reducing systematic uncertainties, GRBs can serve as reliable high-redshift distance indicators, offering critical insights into current cosmological tensions., Comment: 21 pages; 10 figures

We present a novel AI-based ideation assistant and evaluate it in a user study with a group of innovators. The key contribution of our work is twofold: we propose a method of idea exploration in a constrained domain by means of LLM-supported semantic navigation of problem and solution spaces, and employ novel automated data input filtering to improve generations. We found that semantic exploration is preferred to the traditional prompt-output interactions, measured both in explicit survey rankings, and in terms of innovation assistant engagement, where 2.1x more generations were performed using semantic exploration. We also show that filtering input data with metrics such as relevancy, coherence and human alignment leads to improved generations in the same metrics as well as enhanced quality of experience among innovators., Comment: arXiv admin note: text overlap with arXiv:2402.06053

We study the problem of globally optimising a target variable of an unknown causal graph on which a sequence of soft or hard interventions can be performed. The problem of optimising the target variable associated with a causal graph is formalised as Causal Bayesian Optimisation (CBO). We study the CBO problem under the cumulative regret objective with unknown causal graphs for two settings, namely structural causal models with hard interventions and function networks with soft interventions. We propose Graph Agnostic Causal Bayesian Optimisation (GACBO), an algorithm that actively discovers the causal structure that contributes to achieving optimal rewards. GACBO seeks to balance exploiting the actions that give the best rewards against exploring the causal structures and functions. To the best of our knowledge, our work is the first to study causal Bayesian optimization with cumulative regret objectives in scenarios where the graph is unknown or partially known. We show our proposed algorithm outperforms baselines in simulated experiments and real-world applications.

We investigate relativistic effects on the performance of a quantum battery in an open quantum framework. We consider an Unruh-DeWitt detector driven by a coherent classical pulse as a quantum battery that is interacting with a massless scalar field through a quadratic coupling. The battery follows a trajectory composed of uniform acceleration along one direction, combined with constant four-velocity components in the orthogonal plane to the acceleration. Accelerated motion degrades the performance of the quantum battery rapidly in the absence of the orthogonal velocity component. We show that the quadratic scalar field coupling enhances coherence and stability in the presence of orthogonal velocity. We observe that decoherence is mitigated significantly, resulting in remarkable improvement in the battery capacity and efficiency compared to the case of the usual linear field coupling. This opens up the possibility of nonlinear environmental coupling enabling stored energy to be retained over longer durations, leading to more efficient operation of quantum devices., Comment: 15 pages LaTeX; Comments are welcome

A space-dependent mean for cosmological perturbations negates the ansatz of statistical homogeneity and isotropy, and hence ergodicity. In this work, we construct such a primordial mean of scalar perturbations from an alternative quantum initial state (coherent state) and examine the associated power and bi-spectra. A multitude of cosmological tests based on these spectra are discussed. We find that current cosmological data doesn't favor a primordial mean over large scales and strong constraints arise from the limit on bispectrum from Planck data. At small scales, this hypothesis can be tested by future observables such as $\mu$-distortion of CMB., Comment: 14 pages (including supplemental material), 2 figures

Optical clocks have improved their frequency stability and estimated accuracy by more than two orders of magnitude over the best caesium microwave clocks that realise the SI second. Accordingly, an optical redefinition of the second has been widely discussed, prompting a need for the consistency of optical clocks to be verified worldwide. While satellite frequency links are sufficient to compare microwave clocks, a suitable method for comparing high-performance optical clocks over intercontinental distances is missing. Furthermore, remote comparisons over frequency links face fractional uncertainties of a few $10^{-18}$ due to imprecise knowledge of each clock's relativistic redshift, which stems from uncertainty in the geopotential determined at each distant location. Here, we report a landmark campaign towards the era of optical clocks, where, for the first time, state-of-the-art transportable optical clocks from Japan and Europe are brought together to demonstrate international comparisons that require neither a high-performance frequency link nor information on the geopotential difference between remote sites. Conversely, the reproducibility of the clocks after being transported between countries was sufficient to determine geopotential height offsets at the level of 4 cm. Our campaign paves the way for redefining the SI second and has a significant impact on various applications, including tests of general relativity, geodetic sensing for geosciences, precise navigation, and future timing networks., Comment: 29 pages, 5 figures

We explore the stationary densities in totally asymmetric exclusion processes (TASEP) with open boundary conditions and spatially inhomogeneous hopping rates. We calculate the steady state density profiles that characterise the associated phases. We show that in the contrast to the low and high density phases, the stationary density profile in the maximal current phase can be discontinuous, even when the space-dependent hopping rate is continuous. The phase diagrams in the plane of the control parameters show universal topology. The associated phase transitions are explored. We further investigate the domain walls, which are delocalised and calculate their envelops, which reveal their dependence on the spatial nonuniformity of the hopping rates., Comment: 17 pages, 16 figures, preliminary version

ATi$_3$Bi$_5$ (A = Cs or Rb) are emerging topological kagome metals that exhibit superconductivity and nematicity without intertwining translational symmetry-breaking charge orders. In this work, we explore the Fermionology of their titanium kagome electrons and identify a set of sublattice-pure, high-order van Hove singularities (VHSs) that can suppress charge ordering and enhance electronic correlations and superconductivity. Our calculations of charge susceptibility for kagome bands with both normal and high-order VHSs emphasize the role of these VHSs in driving electronic nematicity in CsTi$_3$Bi$_5$. Additionally, we compute the phonon spectrum and electron-phonon interactions for CsTi$_3$Bi$_5$ under pristine, doped, and kagome-exposed surface conditions, revealing its robustness against structural instabilities while enhancing the superconducting transition temperature. Our work positions ATi$_3$Bi$_5$ as a key platform for investigating superconductivity and electronic nematicity without translational symmetry-breaking states in kagome metals.

We investigate the probability that a random polynomial with independent, mean-zero and finite variance coefficients has no real zeros. Specifically, we consider a random polynomial of degree $2n$ with coefficients given by an i.i.d. sequence of mean-zero, variance-1 random variables, multiplied by an $\frac{\alpha}{2}$-regularly varying sequence for $\alpha>-1$. We show that the probability of no real zeros is asymptotically $n^{-2(b_{\alpha}+b_0)}$, where $b_{\alpha}$ is the persistence exponents of a mean-zero, one-dimensional stationary Gaussian processes with covariance function as $\mathrm{sech}((t-s)/2)^{\alpha+1}$. Our work generalizes the previous results of Dembo et al. [DPSZ02] and Dembo \& Mukherjee [DM15] by removing the requirement of finite moments of all order or Gaussianity. In particular, in the special case $\alpha = 0$, our findings confirm a conjecture by Poonen and Stoll [PS99, Section 9.1] concerning random polynomials with i.i.d. coefficients., Comment: 62 pages, 2 figures

In the Horava Lifshitz gravity scenario, we have described the mass accretion process of a 4 dimensional Kehagias Sfetsos black hole caused by some candidates of dark energy in detail. Firstly, we have obtained the equation of mass for the black hole with respect to the cosmic scale parameter a in the Horava Lifshitz gravity framework. Then, one by one, we have considered dark energies like Generalized Cosmic Chaplygin gas, Variable Modified Chaplygin gas, New Variable Modified Chaplygin gas, Modified Chaplygin Jacobi gas, and Modified Chaplygin Abel gas, respectively, and established their equation of mass in terms of the redshift function z. In addition, we have presented the results with graphical representations of the mass and redshift functions. Finally, we came to the conclusion that, due to the accretion of all of the dark energy candidates mentioned above, the mass of a 4-dimensional Kehagias-Sfetsos Black Hole will increase gradually in correspondence to the evolution of the universe.

In this paper, we consider the problem of estimating the interaction parameter $p$ of a $p$-spin Curie-Weiss model at inverse temperature $\beta$, given a single observation from this model. We show, by a contiguity argument, that joint estimation of the parameters $\beta$ and $p$ is impossible, which implies that estimation of $p$ is impossible if $\beta$ is unknown. These impossibility results are also extended to the more general $p$-spin Erd\H{o}s-R\'enyi Ising model. The situation is more delicate when $\beta$ is known. In this case, we show that there exists an increasing threshold function $\beta^*(p)$, such that for all $\beta$, consistent estimation of $p$ is impossible when $\beta^*(p) > \beta$, and for almost all $\beta$, consistent estimation of $p$ is possible for $\beta^*(p)<\beta$., Comment: 8 pages

Here, we report the full-fledged journey towards the material synthesis and characterization of few-layered/thin WSe$_2$ using sputtered W-films on SiO$_2$/Si substrates followed by electrical studies under dark and illumination conditions. Growth temperature 500oC and gas pressure 55 sccm are found to be the optimized parameters for formation of thermodynamically stable WSe$_{2-x}$ with dominant Raman peak at 265 cm-1. XRD and HR-TEM measurement clarify the formation of high crystallinity along the c-axis and quasi-crystallinity along a and b axes respectively. Lower intensities from Raman-measurement and PL-peak at 768 nm (with 532 nm excitation wavelength) infers the thin nature of the grown film, along with strong second harmonic emission with excitation wavelength varying from 350nm to 450 nm. This work also retracks the controlled etching by reactive ions to achieve large area bi/tri-layer films to fabricate advanced devices. We also have fabricated an advanced MOS structure on SiO$_2$/p-Si substrate which shows tremendous performance by means of photo-capacitance under illumination condition where photo-carriers can survive the higher probe frequencies (> 1MHz). Under illumination condition, HfO$_2$/WSe$_2$ embedded MOS shows its dominance showing a huge electron-inversion region over HfO$_2$/ SiO$_2$/p-Si and SiO$_2$/p-Si MOS devices even at high frequencies (1-10 MHz). Thereby, this work also reveals a possible route for capacitance based highly sensitive photodetection using conventional Si-technology with integration of such WSe$_2$/W as an active material., Comment: 23, 7

We investigate the prospect of using ultracold alkali diatomic molecules to implement many-body quantum systems with SU($N$) symmetry. Experimentally accessible molecules offer large $N$ for both bosonic and fermionic systems, with both attractive and repulsive interactions. We carry out coupled-channel scattering calculations on pairs of NaK, NaRb and NaCs molecules that are shielded from destructive collisions with static electric fields. We develop new methods to handle the very large basis sets required to include nuclear spins. We show that all the molecules studied have the properties required for SU($N$) symmetry: the collisions are principally elastic, and the scattering lengths depend only weakly on the spin states of the molecules. The rates of spin-changing inelastic collisions are very low. We develop and test a semiclassical model of the spin dependence and find that it performs well., Comment: 15 pages, 12 figures, and 6 tables

Despite seemingly performant web agents on the task-completion benchmarks, most existing methods evaluate the agents based on a presupposition: the web navigation task consists of linear sequence of actions with an end state that marks task completion. In contrast, our work focuses on web navigation for information aggregation, wherein the agent must explore different websites to gather information for a complex query. We consider web information aggregation from two different perspectives: (i) Direct API-driven Access relies on a text-only view of the Web, leveraging external tools such as Google Search API to navigate the web and a scraper to extract website contents. (ii) Interactive Visual Access uses screenshots of the webpages and requires interaction with the browser to navigate and access information. Motivated by these diverse information access settings, we introduce Infogent, a novel modular framework for web information aggregation involving three distinct components: Navigator, Extractor and Aggregator. Experiments on different information access settings demonstrate Infogent beats an existing SOTA multi-agent search framework by 7% under Direct API-Driven Access on FRAMES, and improves over an existing information-seeking web agent by 4.3% under Interactive Visual Access on AssistantBench., Comment: Preprint

We present spectroscopic properties of 22 Lyman-alpha emitters(LAEs) at z=5.5-6.6 with Lyman-alpha(Lya) luminosity log($L_{Lya}$[$ergs^{-1}$])=42.4-43.5, obtained using VLT/MUSE as part of the Middle Ages Galaxy Properties with Integral Field Spectroscopy(MAGPI) survey. Additionally, we incorporate broad-band photometric data from the Subaru Hyper Suprime-Cam(HSC) for 17 LAEs in our sample. The HSC-y band magnitudes show that our LAEs are UV-bright, with rest-frame absolute UV magnitudes -19.7 < $M_{UV}$ < -23.3. We find that the Lya line width increases with luminosity, and this trend becomes more prominent at z > 6 where Lya lines become significantly broadened (> 260 $kms^{-1}$) at luminosities log($L_{Lya}$[$ergs^{-1}$]) > 43. This broadening is consistent with previous studies, suggesting that these sources are located inside larger ionized bubbles. We observe a slightly elevated ionizing photon production efficiency estimated for LAEs at z > 6, indicating that younger galaxies could be producing more ionizing photons per UV luminosity. A tentative anti-correlation between ionizing photon production efficiency and Lya rest-frame equivalent width is noticed, which could indicate a time delay between production and escape of ionizing photon primarily due to supernovae activity. Furthermore, we find a positive correlation between bubble radius and Lya line width, which again suggests that large ionized bubbles are created around these LAEs, allowing them to self-shield from the scattering effects of the intergalactic medium (IGM). We also detect two closely separated LAEs at z=6.046 (projected spatial separation is 15.92 kpc). The size of their respective bubbles suggests that they likely sit inside a common large ionized region. Such a closely-separated LAE pair increases the size of ionized bubble, potentially allowing a boosted transmission of Lya through neutral IGM. (Abridged), Comment: 14 pages, 6 figures, 2 tables, Accepted for publication in PASA

Automatic Speech Recognition (ASR) systems have been examined and shown to exhibit biases toward particular groups of individuals, influenced by factors such as demographic traits, accents, and speech styles. Noise can disproportionately impact speakers with certain accents, dialects, or speaking styles, leading to biased error rates. In this work, we introduce a novel framework DENOASR, which is a selective denoising technique to reduce the disparity in the word error rates between the two gender groups, male and female. We find that a combination of two popular speech denoising techniques, viz. DEMUCS and LE, can be effectively used to mitigate ASR disparity without compromising their overall performance. Experiments using two state-of-the-art open-source ASRs - OpenAI WHISPER and NVIDIA NEMO - on multiple benchmark datasets, including TIE, VOX-POPULI, TEDLIUM, and FLEURS, show that there is a promising reduction in the average word error rate gap across the two gender groups. For a given dataset, the denoising is selectively applied on speech samples having speech intelligibility below a certain threshold, estimated using a small validation sample, thus ameliorating the need for large-scale human-written ground-truth transcripts. Our findings suggest that selective denoising can be an elegant approach to mitigate biases in present-day ASR systems., Comment: Paper accepted at IEEE ICKG 2024

A primary goal of characterizing exoplanet atmospheres is to constrain planetary bulk properties, such as their metallicity, C/O ratio, and intrinsic heat. However, there are significant uncertainties in many aspects of atmospheric physics, such as the strength of vertical mixing. Here we use PICASO and the photochem model to explore how atmospheric chemistry is influenced by planetary properties like metallicity, C/O ratio, $T_{\rm int}$, $T_{\rm eq}$, and $K_{\rm zz}$ in hydrogen-dominated atmospheres. We vary the $T_{\rm eq}$ of the planets between 400 K- 1600 K, across ``cold",``warm," and `hot" objects. We also explore an extensive range of $T_{\rm int}$ values between 30-500 K, representing sub-Neptunes to massive gas giants. We find that gases like CO and CO$_2$ show a drastically different dependence on $K_{\rm zz}$ and C/O for planets with cold interiors (e.g., sub-Neptunes) compared to planets with hotter interiors (e.g., Jupiter mass planets), for the same $T_{\rm eq}$. We also find that gases like CS and CS$_2$ can carry a significant portion of the S- inventory in the upper atmosphere near $T_{\rm eq}$ $\le$ 600 K, below which SO$_2$ ceases to be abundant. For solar C/O, we show that the CO/CH$_4$ ratio in the upper atmospheres of planets can become $\le$1 for planets with low $T_{\rm eq}$, but only if their interiors are cold ($T_{\rm int}$$\le$100 K). We find that photochemical haze precursor molecules in the upper atmosphere show very complex dependence on C/O, $K_{\rm zz}$, $T_{\rm eq}$, and $T_{\rm int}$ for planets with cold interiors (e.g., sub-Neptunes). We also briefly explore fully coupling PICASO and photochem to generate self-consistent radiative-convective-photochemical-equilibrium models., Comment: Revised and re-submitted to ApJ, Main text: Pages 1 to 34, 25 Figures, Appendix: Pages 35 to 36, 1 Figure

Young supernova remnants (SNRs) are believed to be the origin of energetic cosmic rays (CRs) below the "knee" of their spectrum at $\sim3$ petaelectronvolt (PeV, $10^{15}$ eV). Nevertheless, the precise location, duration, and operation of CR acceleration in young SNRs are open questions. Here, we report on multi-epoch X-ray observations of Cassiopeia A (Cas A), a 350-year-old SNR, in the 15-50 keV band that probes the most energetic CR electrons. The observed X-ray flux decrease $(15\pm1\%)$, contrary to the expected $>$90\% decrease based on previous radio, X-ray, and gamma-ray observations, provides unambiguous evidence for CR electron acceleration operating in Cas A. A temporal model for the radio and X-ray data accounting for electron cooling and continuous injection finds that the freshly injected electron spectrum is significantly harder (exponential cutoff power law index $q=2.15$), and its cutoff energy is much higher ($E_{cut}=36$ TeV) than the relic electron spectrum ($q=2.44\pm0.03$, $E_{cut}=4\pm1$ TeV). Both electron spectra are naturally explained by the recently developed modified nonlinear diffusive shock acceleration (mNLDSA) mechanism. The CR protons producing the observed gamma rays are likely accelerated at the same location by the same mechanism as those for the injected electron. The Cas A observations and spectral modeling represent the first time radio, X-ray, gamma ray and CR spectra have been self-consistently tied to a specific acceleration mechanism -- mNLDSA -- in a young SNR., Comment: Submitted to ApJ. 12 pages, 4 figures, 2 tables

This paper significantly advances the application of Quantum Key Distribution (QKD) in Free- Space Optics (FSO) satellite-based quantum communication. We propose an innovative satellite quantum channel model and derive the secret quantum key distribution rate achievable through this channel. Unlike existing models that approximate the noise in quantum channels as merely Gaussian distributed, our model incorporates a hybrid noise analysis, accounting for both quantum Poissonian noise and classical Additive-White-Gaussian Noise (AWGN). This hybrid approach acknowledges the dual vulnerability of continuous variables (CV) Gaussian quantum channels to both quantum and classical noise, thereby offering a more realistic assessment of the quantum Secret Key Rate (SKR). This paper delves into the variation of SKR with the Signal-to-Noise Ratio (SNR) under various influencing parameters. We identify and analyze critical factors such as reconciliation efficiency, transmission coefficient, transmission efficiency, the quantum Poissonian noise parameter, and the satellite altitude. These parameters are pivotal in determining the SKR in FSO satellite quantum channels, highlighting the challenges of satellitebased quantum communication. Our work provides a comprehensive framework for understanding and optimizing SKR in satellite-based QKD systems, paving the way for more efficient and secure quantum communication networks.

Entanglement and nonlocality are two important nonclassical features of quantum correlations. Recently the study of quantum correlations in networks has undergone remarkable progress owing to technological development towards scalable quantum networks. However, compared to standard Bell scenario, manifestation of the interplay between these two aspects has received less attention in network scenarios featuring independent sources. In this work we have analyzed the relation between entanglement content of the sources and detectable non n-locality in two distinct network topologies(linear and star). We have studied the extremal violations of n-local inequalities(compatible with linear and star network) for any fixed amount of entanglement(in terms of concurrence) of the independent sources. It is observed that each of the sources must be entangled for detecting non n-locality in linear network. However, the same is not true for star n-local network. Present analysis is revealing that entanglement of all the independent sources is not a necessity for generation of non n-local correlations in star topology. Characterization of sources in terms of minimum entanglement requirement for any fixed violation amount of the n-local inequalities is also provided. Interestingly, detection of non n-locality is ensured in the network if product of concurrence of all the sources involved exceeds 1/2. ., Comment: Preliminary Version

We theoretically investigate the resonant inelastic X-ray scattering (RIXS) spectra in a quasi-1D chain of weakly coupled frustrated spin-1/2 trimers, as realized in Na$_{2}$Cu$_{3}$Ge$_{4}$O$_{12}$, with Cu $d^{9}$ 1/2 spins. We compute multi-spin correlations contributing to spin-conserving (SC) and spin non-conserving (NSC) RIXS cross-sections using ultra-short core-hole lifetime expansion within the Kramer-Heisenberg formalism. These excitations involve flipping spins of up to three spin-1/2 trimers and include the inelastic neutron scattering (INS) single spin-flip excitations in the lowest order of the NSC channel. We identify the fractionalization of two coupled frustrated trimers in terms of spinons, doublons, and quartons in the spectra evaluated using exact diagonalization, complementing prior studies single spin-spin flip excitation in inelastic neutron scattering. Specifically, we uncover two new high-energy modes at $\omega \approx 2.4J_1$ and $3.0 J_1$ in the NSC and SC channels that are accessible at the Cu $K$-edge and $L$-edge RIXS spectra, which were missing in the INS study. This, therefore, provides pathways to uncover all the possible excitations in coupled trimers. Our work opens new opportunities for understanding the nature of fractionalization and RIXS spectra of frustrated, low-dimensional spin chains.

We present \synver{}, a novel synthesis and verification framework for C programs, that deploys a Large Language Model (LLM) to search for a candidate program that satisfies the given specification. Our key idea is to impose syntactic and semantic biases on programs generated by LLMs, such that the synthesized program is more amenable to automated verification. Based on this idea, we propose a novel specification-verification tool, built on top of Verified Software Toolchain, that help automate the process. Our experiments on a diverse set of benchmarks drawn from the deductive program synthesis community, shows that this approach is scalable and extensible. The benchmarks constitute of specifications comprising of basic coding examples, Separation Logic based assertions, and API specifications.

We consider a few online and offline games under actual playing conditions. Generally it is expected that initially a player obtains additional skill with experience of playing more number of games and then it should finally saturate. This phase is identified when a player, with the experience of very few games, loses more when she plays against players with much longer history. Then the winning proportion curve moves up and finally it saturates. We benchmark our analysis and discussion against Chess, the most skilled one among the games we consider here. We use proprietary data from actual games (online and offline) as well as experiments for our statistical analysis. In this regard, we show that Rummy has stronger skill and learning effects. Ludo has similar characteristics as Rummy, but at a weaker level. Similarly, a game that is perceived as almost no skill such as Teen Patti indeed presents much less skill in the analysis. In the next section we describe the game structures., Comment: 25 pages, 9 figures

The nonequilibrium turbulent response of driven three-dimensional dipolar gases is monitored by dynamically crossing the supersolid-to-superfluid phase transition and vice versa utilizing a periodically modulated scattering length. Following the generation of vortical defects in the bulk, a direct cascade front emerges transporting energy from larger to smaller length scales and leading to a nonequilibrium quasi-steady state at long evolution times. This quasi-steady state is evidenced by the self-similar character of the momentum distributions featuring an algebraic reduction at large momenta with scaling exponents supporting the existence of wave turbulence. We observe that supersolidity sustaining higher-lying momenta, associated with the roton minimum, promotes the emergence of turbulence. Our results provide a stepping stone for unravelling and exploiting turbulent and self-similar behavior in anisotropically interacting quantum gases amenable in current experiments., Comment: 6 pages, 4 figures, 4 pages Supplemental material

We develop a new longitudinal count data regression model that accounts for zero-inflation and spatio-temporal correlation across responses. This project is motivated by an analysis of Iowa Fluoride Study (IFS) data, a longitudinal cohort study with data on caries (cavity) experience scores measured for each tooth across five time points. To that end, we use a hurdle model for zero-inflation with two parts: the presence model indicating whether a count is non-zero through logistic regression and the severity model that considers the non-zero counts through a shifted Negative Binomial distribution allowing overdispersion. To incorporate dependence across measurement occasion and teeth, these marginal models are embedded within a Gaussian copula that introduces spatio-temporal correlations. A distinct advantage of this formulation is that it allows us to determine covariate effects with population-level (marginal) interpretations in contrast to mixed model choices. Standard Bayesian sampling from such a model is infeasible, so we use approximate Bayesian computing for inference. This approach is applied to the IFS data to gain insight into the risk factors for dental caries and the correlation structure across teeth and time.

In retail sales forecasting, accurately predicting future sales is crucial for inventory management and strategic planning. Traditional methods like LR often fall short due to the complexity of sales data, which includes seasonality and numerous product families. Recent advancements in machine learning (ML) provide more robust alternatives. This research benefits from the power of ML, particularly Random Forest (RF), Gradient Boosting (GB), Support Vector Regression (SVR), and XGBoost, to improve prediction accuracy. Despite advancements, a significant gap exists in handling complex datasets with high seasonality and multiple product families. The proposed solution involves implementing and optimizing a RF model, leveraging hyperparameter tuning through randomized search cross-validation. This approach addresses the complexities of the dataset, capturing intricate patterns that traditional methods miss. The optimized RF model achieved an R-squared value of 0.945, substantially higher than the initial RF model and traditional LR, which had an R-squared of 0.531. The model reduced the root mean squared logarithmic error (RMSLE) to 1.172, demonstrating its superior predictive capability. The optimized RF model did better than cutting-edge models like Gradient Boosting (R-squared: 0.942), SVR (R-squared: 0.940), and XGBoost (R-squared: 0.939), with more minor mean squared error (MSE) and mean absolute error (MAE) numbers. The results demonstrate that the optimized RF model excels in forecasting retail sales, handling the datasets complexity with higher accuracy and reliability. This research highlights the importance of advanced ML techniques in predictive analytics, offering a significant improvement over traditional methods and other contemporary models., Comment: IEEE 4th ICSES 2024

We address the optimization problem in a data-driven variational reconstruction framework, where the regularizer is parameterized by an input-convex neural network (ICNN). While gradient-based methods are commonly used to solve such problems, they struggle to effectively handle non-smoothness which often leads to slow convergence. Moreover, the nested structure of the neural network complicates the application of standard non-smooth optimization techniques, such as proximal algorithms. To overcome these challenges, we reformulate the problem and eliminate the network's nested structure. By relating this reformulation to epigraphical projections of the activation functions, we transform the problem into a convex optimization problem that can be efficiently solved using a primal-dual algorithm. We also prove that this reformulation is equivalent to the original variational problem. Through experiments on several imaging tasks, we demonstrate that the proposed approach outperforms subgradient methods in terms of both speed and stability.