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Some of the issues that make sampling parameter spaces of various beyond the Standard Model (BSM) scenarios computationally expensive are the high dimensionality of the input parameter space, complex likelihoods, and stringent experimental constraints. In this work, we explore likelihood-free approaches, leveraging neural network-aided Simulation-Based Inference (SBI) to alleviate this issue. We focus on three amortized SBI methods: Neural Posterior Estimation (NPE), Neural Likelihood Estimation (NLE), and Neural Ratio Estimation (NRE) and perform a comparative analysis through the validation test known as the \textit{ Test of Accuracy with Random Points} (TARP), as well as through posterior sample efficiency and computational time. As an example, we focus on the scalar sector of the phenomenological minimal supersymmetric SM (pMSSM) and observe that the NPE method outperforms the others and generates correct posterior distributions of the parameters with a minimal number of samples. The efficacy of this framework will be more evident with additional experimental data, especially for high dimensional parameter space., Comment: 31 pages, 11 figures

Our study explores the mixture of polar particles in apolar environment. We employ a coarse-grained approach to model the mixture, where polar particles are in minority. The interaction between polar and apolar components is incorporated via a coupling term in the free energy. Coupling generates local interaction in the system which results in the formation of string like structures connecting a pair of half integer topological defects. The increase in the coupling strength or the density of polar particles results in the: Sharper strings with larger probability of connecting the topological defects of same charge and the enhanced dynamics of topological defects. However, the ordering kinetics of the system shows the delayed coarsening for larger coupling or polar density. Our results can be used to develop controlled kinetics as well as to detect the impurities in liquid crystals.

The realization of a global quantum network capable of supporting secure communication and other quantum information processing (QIP) tasks hinges on the ability to distribute high-fidelity entanglement across long distances while optimizing resource usage. This work describes a scalable approach for building large quantum networks by connecting quantum sub-networks using entanglement backbones as interconnections and a swapping based entanglement distribution protocol. Using a statistical model for parametrized quantum sub-networks we derive a set of equations whose solutions give the optimal values of average network parameters that meet threshold requirements for QIP tasks while minimizing resource cost functions. Our analysis extends to the scenario where multiple sub-networks must be interconnected simultaneously based on the formulation of a global resource cost function. The probability of successfully satisfying the parameter thresholds of a QIP task as a function of average parameters of the sub-networks for random network demands reveals a transition from zero to full satisfiability above critical network parameter values. Moreover, we find that the satisfiability transition can be smooth or discontinuous depending on the topology of the sub-networks. Our results present a pathway for calculating optimal resource requirements in quantum sub-networks interconnected to form the global quantum internet.

Despite considerable advancements, high electron mobility transistors (HEMTs) based on gallium nitride (GaN) channels remain largely limited to power applications below 650 V. For higher power demands, the ultra-wide bandgap semiconductor alloy aluminium gallium nitride, (Al,Ga)N, has emerged as a key contender for next-generation HEMTs. In this theoretical study, we show that Al-rich Al$_x$Ga$_{1-x}$N-channel HEMTs (with $x \geq 0.5$) outperform the GaN-channel counterparts at and above room temperature, across all Al compositions, $x$. This contrasts with recent theory reports which suggest that only Al$_x$Ga$_{1-x}$N HEMTs with high Al content ($x \geq 0.85$) offer comparable performance to GaN-channel devices. Unlike previous assumptions of a constant two-dimensional electron gas (2DEG) density across the entire composition range $x$, we show that the 2DEG density is highly sensitive to both the Al content and thickness of the individual layers in a HEMT structure. We demonstrate that the superior performance of Al-rich (Al,Ga)N-channel HEMTs is driven by a competing effect between 2DEG density and electron mobility. This work challenges the assumptions of prior studies, which can result in a significant under or overestimation of the potential of high Al content HEMTs. The insights gained from our work provide a comprehensive understanding of the trade-offs between device and material parameters, thus help to guide the design of future Al-rich ($x = 0.5-1.0$) Al$_x$Ga$_{1-x}$N-channel HEMTs for high-power applications., Comment: Main article: 7 pages, 5 figures; Supplementary article: 16 pages, 12 figures, 10 sections; Supplementary attachment: (Processed) Data and additional supplementary figures

I prove a convergence theorem in the context of $3+1$ dimensional vacuum Einstein's equations including a positive cosmological constant on spacetimes $\widetilde{M}$ of topological type $M\times \mathbb{R}$, where $M$ is a closed connected oriented Riemannian $3-$manifold of negative Yamabe type. The theorem concerns the global existence of the solutions of the vacuum Einstein$-\Lambda$ equations for arbitrary large initial data and convergence of the spatial geometry to a constant negative scalar curvature metric in a constant mean extrinsic curvature (CMC) transported spatial gauge. This theorem could be interpreted as a weak cosmic censorship result in the cosmological framework under \textit{generic} initial data. An important corollary of the theorem is the failure of cosmological principle as a derived consequence of Einstein's equations including a positive cosmological constant as well as the failure of geometrization of spatial slice in the sense of Thurston. A similar theorem is stated for positive Yamabe slices under a technical assumption., Comment: Comments welcome, 39 pages

Accurate prediction of CB2 receptor ligand activity is pivotal for advancing drug discovery targeting this receptor, which is implicated in inflammation, pain management, and neurodegenerative conditions. Although conventional machine learning and deep learning techniques have shown promise, their limited interpretability remains a significant barrier to rational drug design. In this work, we introduce CB2former, a framework that combines a Graph Convolutional Network with a Transformer architecture to predict CB2 receptor ligand activity. By leveraging the Transformer's self attention mechanism alongside the GCN's structural learning capability, CB2former not only enhances predictive performance but also offers insights into the molecular features underlying receptor activity. We benchmark CB2former against diverse baseline models including Random Forest, Support Vector Machine, K Nearest Neighbors, Gradient Boosting, Extreme Gradient Boosting, Multilayer Perceptron, Convolutional Neural Network, and Recurrent Neural Network and demonstrate its superior performance with an R squared of 0.685, an RMSE of 0.675, and an AUC of 0.940. Moreover, attention weight analysis reveals key molecular substructures influencing CB2 receptor activity, underscoring the model's potential as an interpretable AI tool for drug discovery. This ability to pinpoint critical molecular motifs can streamline virtual screening, guide lead optimization, and expedite therapeutic development. Overall, our results showcase the transformative potential of advanced AI approaches exemplified by CB2former in delivering both accurate predictions and actionable molecular insights, thus fostering interdisciplinary collaboration and innovation in drug discovery.

The inverse diffusion flame (IDF) can experience thermoacoustic instability due to variations in power input or flow conditions. However, the dynamical transitions in IDF that lead to this instability when altering control parameters have not been thoroughly investigated. In this study, we explore the control parameters through two different approaches and employ multifractal detrended fluctuation analysis to characterize the transitions observed prior to the onset of thermoacoustic instability in the inverse diffusion flame. Our findings reveal a loss of multifractality near the region associated with thermoacoustic instability, which suggests a more ordered behavior. We determine that the singularity exponent, the width of the multifractal spectrum, and the Hurst exponent are reliable indicators of thermoacoustic instability and serve as effective classifiers of dynamical states in inverse diffusion flames., Comment: 17 pages, 10 figures

Using data samples of 102 million Upsilon(1S) events and 158 million Upsilon(2S) events collected by the Belle detector at the KEKB asymmetric-energy $e^+e^-$ collider, we search for [udsccbar] pentaquark states decaying to Jpsi Lambda. Using the first observations of Upsilon(1S, 2S) inclusive decays to Jpsi Lambda, we find evidence of the P_ccbars(4459)0 state with a significance of 3.3 standard deviations, including statistical and systematic uncertainties. We measure the mass and width of the Pccbars(4459)0 to be (4471.7 +- 4.8 +- 0.6) MeV/c2 and (21.9 +- 13.1 +- 2.7) MeV, respectively. The branching fractions for P_ccbars(4459)0 production are measured to be B[Upsilon(1S) -> P_ccbars(4459)0/ Pbar_ccbars(4459)0 + anything] = (3.5 +- 2.0 +- 0.2)*10-6 and B[Upsilin(2S) -> P_ccbars(4459)0/ Pbar_ccbars(4459)0 +anything] = (2.9 +- 1.7 +- 0.4)*10-6. The inclusive branching fractions of Upsilon(1S, 2S) -> Jpsi Lambda/Lambdabar are measured to be B[Upsilin(1S) -> Jpsi Lambda/Lambdabar + anything] = (36.9 +- 5.3 +- 2.4)*10-6 and B[Upsilon(2S) -> Jpsi Lambda/Lambdabar + anything] = (22.3 +- 5.7 +- 3.1)*10-6. We measure the visible cross section $\sigma(e^+e^- \to J/psi \Lambda/\bar\Lambda$ + anything) = (90 +- 14 +- 6) fb for the continuum production at $\sqrt{s} = 10.52$ GeV. In all cases, the first uncertainties are statistical and the second are systematic., Comment: 8 pages, 3 figures

This paper extends the concepts of Minimal Redundancy Condition (MRC) and robustness of erasures for infinite frames in Hilbert spaces. We begin by establishing a comprehensive framework for the MRC, emphasizing its importance in ensuring the stability and resilience of frames under finite erasures. Furthermore, we discussed the robustness of erasures, which generalizes the ability of a frame to withstand information loss. The relationship between robustness, MRC, and excess of a frame is carefully examined, providing new insights into the interplay between these properties. The robustness of Besselian frames, highlighting their potential in applications where erasure resilience is critical. Our results contribute to a deeper understanding of frame theory and its role in addressing challenges posed by erasure recovery.

We study the effect of magnon interactions on the spin wave spectra of the All-in-All-out phase of the pyrochlore nearest neighbour antiferromagnet with a Dzyaloshinskii-Moriya interaction $D$. The leading order corrections to spin wave energies indicate a significant renormalisation for commonly encountered strengths of the Dzyaloshinskii-Moriya term. For low values of $D$ we find a potential instability of the phase itself, indicated by the renormalisation of magnon frequencies to negative values. We have also studied the renormalized spectra in the presence of magnetic fields along three high symmetry directions of the lattice, namely the $[111]$, $[100]$ and $[110]$ directions. Generically, we find that for a fixed value of the Dzyaloshinskii-Moriya interaction renormalized spectra for the lowest band decrease with an increasing strength of the field. We have also analyzed the limits of the two magnon continuum and probed the possibility of magnon decay. For a range of $D$ and the field strength we identify possible parameter regimes where the decay of the higher bands of the system are kinematically allowed.

In quantum networks, a set of entangled states distributed over multiple, alternative, distinct paths between a pair of source-destination nodes can be purified to obtain a higher fidelity entangled state between the nodes. This multipath entanglement purification (MP-EP) strategy can exploit the network's complex structure to strengthen the entanglement connection between node pairs separated by appropriate graph distances. We investigate the network scenarios in which MP-EP outperforms entanglement distribution over single network paths utilising a statistical model of a quantum network and find that MP-EP can be an effective entanglement distribution strategy over a range of node separations determined by the average edge fidelities and probabilities of the network. We find that MP-EP can bost the entanglement connection between suitably separated node pairs to reach fidelities sufficient for a given quantum task thereby increasing the functionality of a quantum network. Further, we provide statistical criteria in terms of network parameters that can determine the regions of the network where MP-EP can be a useful entanglement distribution strategy.

The properties (masses and decay widths) of the $\phi$ meson are investigated in nuclear matter from the $\phi$ meson self-energy, using the tree-level $\phi K\bar{K}$ Lagrangian, and, incorporating in-medium masses of (anti)kaons calculated within the quark meson coupling (QMC) model. These mass shifts and decay widths are incorporated in the Breit-Wigner spectral function of the $\phi$ meson to calculate the production cross-section of $\phi$ in asymmetric nuclear matter. Considerable modifications to the production cross-section are observed at normal nuclear matter density, driven by the in-medium mass reduction and the increase in the decay width of $\phi$ meson. The potential experienced by $\phi$ meson in nuclear matter is used to study the possibility of formation of the $\phi$ mesic bound state with atomic nuclei. We explore the potential formation of $\phi$-mesic bound states in ${\rm{^{4}He}}$, ${\rm{^{12}C}}$, ${\rm{^{16}O}}$, ${\rm{^{40}Ca}}$, ${\rm{^{90}Zr}}$, ${\rm{^{197}Au}}$ and ${\rm{^{208}Pb}}$ nuclei by investigating their binding energies and absorption widths based on the corresponding $\phi$-nucleus potentials. Our study shows shallow bound states with the light nuclei and deeply bound states in heavy nuclei. Among the investigated nuclei, a particularly distinct signal for a $\phi$-mesic bound state is identified in ${\rm{^{16}O}}$, suggesting its potential experimental observability. The work provides valuable insights into $\phi$ meson interactions in infinite nuclear matter and the potential formation of exotic $\phi$-mesic nuclear states, offering promising probes for strongly interacting matter in the upcoming experiments at J-PARC, JLab, and ${\rm{\bar{P}}ANDA}$@FAIR physics program., Comment: 11 pages, 10 figures

This part of the conference proceeding provides a detailed overview of cutting-edge advancements in detector technologies, focusing on their optimization, characterization, and applications in particle physics experiments. Building on the insights and developments presented at the Hot QCD Matter 2022 conference, this section of the Hot QCD Matter 2024 proceedings highlights significant advancements in detector technologies. The development of Low Gain Avalanche Diodes (LGADs) into Ultra-Fast Silicon Detectors is explored, demonstrating their potential for superior timing resolution in future high-energy experiments. Simulation studies of Micropattern Gaseous Detectors (MPGDs), including MICROMEGAS and Gas Electron Multiplier (GEM) detectors, provide insights into their performance under high-radiation environments using tools like ANSYS and GARFIELD$^{++}$. A novel GEM foil geometry is proposed for improved gain and durability. Characterization of semiconductor detectors, such as Monolithic MALTA pixel detectors and CMS prototype silicon sensors, is also presented, highlighting their radiation tolerance, imaging capabilities, and structural integrity. These studies underscore the critical role of silicon sensors in ensuring detector reliability and performance. Additionally, the J-PARC muon g-2/EDM experiment is reviewed, showcasing its precision measurements to test Standard Model predictions and explore potential physics beyond. By addressing the interplay between detector development, simulation, and characterization, this proceeding showcases a collective effort toward advancing detector technologies and their pivotal role in pushing the boundaries of modern particle physics., Comment: 27 pages, 32 figures

Discrete Morse theory helps us compute the homology groups of simplicial complexes in an efficient manner. A "good" gradient vector field reduces the number of critical simplices, simplifying the homology calculations by reducing them to the computation of homology groups of a simpler chain complex. This homology computation hinges on an efficient enumeration of gradient trajectories. The technique of cancelling pairs of critical simplices reduces the number of critical simplices, though it also perturbs the gradient trajectories. In this article, we demonstrate that (the matrix of) a certain modified boundary operator of interest can be derived from the corresponding original boundary operator through a sequence of elementary row operations. Thus, it eliminates the need of enumeration of the new gradient trajectories. We also obtain a similar result for coboundary operators., Comment: 19 pages, 7 figures, 1 appendix

Powerful new frontier AI technologies are bringing many benefits to society but at the same time bring new risks. AI developers and regulators are therefore seeking ways to assure the safety of such systems, and one promising method under consideration is the use of safety cases. A safety case presents a structured argument in support of a top-level claim about a safety property of the system. Such top-level claims are often presented as a binary statement, for example "Deploying the AI system does not pose unacceptable risk". However, in practice, it is often not possible to make such statements unequivocally. This raises the question of what level of confidence should be associated with a top-level claim. We adopt the Assurance 2.0 safety assurance methodology, and we ground our work by specific application of this methodology to a frontier AI inability argument that addresses the harm of cyber misuse. We find that numerical quantification of confidence is challenging, though the processes associated with generating such estimates can lead to improvements in the safety case. We introduce a method for better enabling reproducibility and transparency in probabilistic assessment of confidence in argument leaf nodes through a purely LLM-implemented Delphi method. We propose a method by which AI developers can prioritise, and thereby make their investigation of argument defeaters more efficient. Proposals are also made on how best to communicate confidence information to executive decision-makers., Comment: 48 pages, 10 figures, 6 tables

Context: 3C 273, a well-studied active galactic nucleus (AGN), displays characteristics of both jetted-AGN and Seyfert galaxies, making it an excellent source to study the disc-jet connection in AGN. Aims: To investigate the disk-jet scenario in 3C 273 using broadband (0.3--78 keV) X-ray spectra from {\it XMM-Newton} and {\it NuSTAR}. Methods: We used simultaneous {\it XMM-Newton} and {\it NuSTAR} observations of 3C 273 carried out between 2012 and 2024. The 0.3--78 keV X-ray spectra were first fit with a simple power-law (PL) and then with the accretion-ejection-based JeTCAF model. The JeTCAF model accounts for emission from the jet, extending up to the sonic surface. In this framework, a reflection hump above 10 keV can also arise due to the bulk motion Comptonization of coronal photons by the jet. Results: We found that the simple PL did not provide a good fit, leaving significant residuals at energies below 1.5 keV. All the spectra were fitted well by the JeTCAF model. The weighted-averaged black hole mass of (7.77$\pm$0.30) $\times 10^8 M_\odot$ obtained from the JeTCAF model is comparable with the previous estimates based on reverberation mapping observations and accretion disk models. Conclusions: The 0.3--78 keV X-ray emission of 3C 273 can be fit by the accretion-ejection-based model in which the corona and the jet on top of it make significant contributions to the X-ray flux. The Doppler boosting factor estimated from the jet flux ranges from 1.6 to 2.2, consistent with the lower limit from the literature., Comment: 12 pages, 7 figures, 3 tables, accepted for publication in the Astronomy & Astrophysics journal

We present a measurement of the branching fraction of $B^+\to\tau^+\nu_\tau$ decays using $(387\pm6)\times 10^6$ $\Upsilon(4S)$ collected between 2019 and 2022 with the Belle II detector at the SuperKEKB $e^+e^-$ collider. We reconstruct the accompanying $B^-$ meson using the hadronic tagging method, while $B^+\to\tau^+\nu_\tau$ candidates are identified in the recoil. We find evidence for $B^+\to\tau^+\nu_\tau$ decays at 3.0 standard deviations, including systematic uncertainties. The measured branching fraction is $\mathcal{B}(B^+\to\tau^+\nu_\tau) = [1.24 \pm 0.41 (\text{stat.}) \pm 0.19 (\text{syst.})] \times 10^{-4}$.

Wide-field high-precision photometric observations such as \textit{Transiting Exoplanet Survey Satellite (TESS)} allowed the investigation of the stellar magnetic activity of cool stars. M-dwarf's starspots and stellar flares are the main indicators of magnetic activity. The present study focuses on modeling light curves (LCs) to analyze the distribution and characteristics of starspots e.g., location, temperature, and spot size. The \textit{TESS} light curves of two selected young M-dwarfs i.e. GJ~182 and 2MASS~J05160212+2214528 were reconstructed using the \textsc{BASSMAN} software, obtaining a three-spot model for GJ~182 and two-spot model for 2MASS~J05160212+2214528, describing their light curves. For GJ~182, the mean spot temperature was estimated to be approximately 3279~K, covering 5-8.5\% of the stellar surface while for 2MASS~J05160212+2214528 the average spot temperature was approximately 2631~K, with a mean spottedness of about 5.4\%. Using the 2-min cadence LC data, we identified and analyzed 48 flare events from GJ~182, while no flares were detected in 2MASS~J05160212+2214528. The estimated bolometric flare energy ranged from $10^{32} - 10^{35}$ erg, and 10$^{31}$ - 10$^{33}$ erg in the TESS bandpass. We derived the power-law index of -1.53 $\pm$ 0.12 and -1.86 $\pm$ 0.22 for flare frequency distribution in sectors 5 and 32 respectively in the flare energy 10$^{33}$ to 10$^{35}$ erg, consistent with previous studies for M-dwarfs. A positive linear correlation between flare energy and duration was found with a slope of $0.67 \pm 0.02$, suggesting a similar mechanism followed by stellar superflares and solar flares. By assuming the similarities with solar flares, we also estimated the lower limit of the magnetic field strength around 12 - 232~G to produce such superflare events.

In this work, we explore two classes of density dependent relativistic mean-field models, their predictions of proton fractions at high densities and neutron star structure. We have used a metamodelling approach to these relativistic density functionals. We have generated a large ensemble of models with these classes and then applied constraints from theoretical and experimental nuclear physics and astrophysical observations. We find that both models produce similar equations of state and neutron star mass-radius sequences. But, their underlying compositions, denoted by the proton fraction in this case, are vastly different. This reinstates previous findings that information on composition gets masqueraded in $\beta$-equilibrium. Additional observations of non-equilibrium phenomena are necessary to pin it down.

Niobium (Nb) and its alloys are extensively used in various technological applications owing to their favorable mechanical, thermal and irradiation properties. Accurately modeling Nb under irradiation is essential for predicting microstructural changes, defect evolution, and overall material performance. Traditional interatomic potentials for Nb fail to predict the correct self-interstitial atom (SIA) configuration, a critical factor in radiation damage simulations. We develop a machine learning interatomic potential (MLIP) using the Spectral Neighbor Analysis Potential (SNAP) framework, trained on ab-initio Density Functional Theory (DFT) calculations, which accurately captures the relative stability of different SIA dumbbell configurations. The resulting potential reproduces DFT-level accuracy while maintaining computational efficiency for large-scale Molecular Dynamics (MD) simulations. Through a series of validation tests involving elastic, thermal, and defect properties -- including collision cascade simulations -- we show that our SNAP potential resolves persistent limitations in existing Embedded Atom Method (EAM) and Finnis--Sinclair (FS) potentials and is effective for MD simulations of collision cascades. Notably, it accurately captures the ground-state SIA configuration of Nb in the primary damage of a collision cascade, offering a robust tool for predictive irradiation studies.

The longitudinal oscillations of air columns composed of contractions and rarefaction make up sound. Sound amplification is widely used in medical, electronic and communication fields. A simplistic technique for producing and amplifying can be rewarding. In this study, we investigate a simplistic DIY speaker configuration that can be utilized for sound creation and modulation by implementing response of magnets and a solenoid to an oscillating input signal. We use steady state solution of forced simple harmonic oscillator with damping parameters to analyze our design and show its characteristic frequencies. We present an analytical way of obtaining optimal parameters of the setup to theoretically obtain experimental characteristic frequencies and provide an in-depth investigation of the setup., Comment: 22 pages

CrSb has recently gained immense attention as an altermagnetic candidate. This work reports on the experimental observation of direction-dependent conduction polarity (DDCP) in altermagnetic CrSb through Hall and Seebeck thermopower measurements. Conduction is dominated by holes along the c-axis and by electrons in the ab-plane of the hexagonal crystal of CrSb. Density functional theory (DFT) calculations indicate that DDCP in CrSb arises from a multicarrier mechanism, where electrons and holes living in distinct bands dominate conduction along different crystallographic directions. Furthermore, DFT predicts that DDCP exists within a narrow energy window near the Fermi level and is sensitive to small doping levels. This prediction is experimentally validated by the loss of DDCP in hole-doped Cr$_{0.98}$V$_{0.02}$Sb. These findings highlight the potential for tunable electronic behavior in CrSb, offering promising avenues for applications in devices that require both p-type and n-type functionalities within a single material., Comment: 6 main figures, 8 SI figures

Integrating Unmanned Aerial Vehicles (UAVs) with Unmanned Ground Vehicles (UGVs) provides an effective solution for persistent surveillance in disaster management. UAVs excel at covering large areas rapidly, but their range is limited by battery capacity. UGVs, though slower, can carry larger batteries for extended missions. By using UGVs as mobile recharging stations, UAVs can extend mission duration through periodic refueling, leveraging the complementary strengths of both systems. To optimize this energy-aware UAV-UGV cooperative routing problem, we propose a planning framework that determines optimal routes and recharging points between a UAV and a UGV. Our solution employs a deep reinforcement learning (DRL) framework built on an encoder-decoder transformer architecture with multi-head attention mechanisms. This architecture enables the model to sequentially select actions for visiting mission points and coordinating recharging rendezvous between the UAV and UGV. The DRL model is trained to minimize the age periods (the time gap between consecutive visits) of mission points, ensuring effective surveillance. We evaluate the framework across various problem sizes and distributions, comparing its performance against heuristic methods and an existing learning-based model. Results show that our approach consistently outperforms these baselines in both solution quality and runtime. Additionally, we demonstrate the DRL policy's applicability in a real-world disaster scenario as a case study and explore its potential for online mission planning to handle dynamic changes. Adapting the DRL policy for priority-driven surveillance highlights the model's generalizability for real-time disaster response., Comment: Submitted

The rapid development of digital stages has greatly compounded the dispersal of untrue data, dissolving certainty and judgment in society, especially among the Bengali-speaking community. Our ponder addresses this critical issue by presenting an interesting strategy that utilizes a profound learning innovation, particularly the Gated Repetitive Unit (GRU), to recognize fake news within the Bangla dialect. The strategy of our proposed work incorporates intensive information preprocessing, which includes lemmatization, tokenization, and tending to course awkward nature by oversampling. This comes about in a dataset containing 58,478 passages. We appreciate the creation of a demonstration based on GRU (Gated Repetitive Unit) that illustrates remarkable execution with a noteworthy precision rate of 94%. This ponder gives an intensive clarification of the methods included in planning the information, selecting the show, preparing it, and assessing its execution. The performance of the model is investigated by reliable metrics like precision, recall, F1 score, and accuracy. The commitment of the work incorporates making a huge fake news dataset in Bangla and a demonstration that has outperformed other Bangla fake news location models., Comment: 6 pages, THE 15th INTERNATIONAL IEEE CONFERENCE ON COMPUTING, COMMUNICATION AND NETWORKING TECHNOLOGIES (ICCCNT)

We propose a novel technique for sampling particle physics model parameter space. The main sampling method applied is Nested Sampling (NS), which is boosted by the application of multiple Machine Learning (ML) networks, e.g., Self-Normalizing Network (SNN) and Normalizing Flow (specifically RealNVP). We apply this on Type-II Seesaw model to test the efficacy of the algorithm. We present the results of our detailed Bayesian exploration of the model parameter space subjected to theoretical constraints and experimental data corresponding to the 125 GeV Higgs boson, $\rho$-parameter, and the oblique parameters. All associated data, figures, and trained ML models can be found here: https://github.com/sunandopatra/MLNS-T2SS, Comment: 19 pages, 10 figures, Version Submitted to EPJC

Asymptotic behavior of generic Tomonaga-Luttinger liquid in the vicinity of phase-separated regions is known to produce an instability where well-known relativistic Conformal Field Theory (CFT) techniques fail. In this letter, we introduce an analytic paradigm which solves this important issue. We show that there is an emergent Carrollian symmetry when phase separation is reached and techniques of Carroll CFT, as opposed to its relativistic relative, is central to the understanding of the physics. We work with the analogous spinless fermionic system in this region and capture the transition across this phase separation. Our numerical results corroborate the density-density correlations intrinsically computed using Carroll CFT., Comment: 8+\epsilon pages including supplementary material. Comments are welcome!

Let $k$ be a field of characteristic zero. Let $m$ and $\alpha$ be positive integers. For $n\geq 2$, let $R_n=k[x_1,x_2,\dots,x_n]$ with the $k$-derivation $d_n$ given by $d_n=(1-x_1x_2^{\alpha})\partial_{x_1}+x_1^m\partial_{x_2}+x_2\partial_{x_3}+\dots+x_{n-1}\partial_{x_n}$. We prove that for integers $m\geq 2$ and $\alpha \geq 1$, $d_n$ is a simple derivation on $R_n$ and $d_n(R_n)$ contains no units. This generalizes a result of D. A. Jordan. We also show that the isotropy group of $d_n$ is conjugate to a subgroup of translations., Comment: 12 pages; Comments are welcome

Accessing visual information is crucial yet challenging for people with low vision due to their visual conditions (e.g., low visual acuity, limited visual field). However, unlike blind people, low vision people have and prefer using their functional vision in daily tasks. Gaze patterns thus become an important indicator to uncover their visual challenges and intents, inspiring more adaptive visual support. We seek to deeply understand low vision users' gaze behaviors in different image viewing tasks, characterizing typical visual intents and the unique gaze patterns exhibited by people with different low vision conditions. We conducted a retrospective think-aloud study using eye tracking with 14 low vision participants and nine sighted controls. Participants completed various image viewing tasks and watched the playback of their gaze trajectories to reflect on their visual experiences. Based on the study, we derived a visual intent taxonomy with five intents characterized by participants' gaze behaviors and demonstrated how low vision conditions affect gaze patterns across visual intents. Our findings underscore the importance of combining visual ability information, image context, and eye tracking data in visual intent recognition, setting up a foundation for intent-aware assistive technologies for low vision.

This article explores the estimation of unknown parameters and reliability characteristics under the assumption that the lifetimes of the testing units follow an Inverted Exponentiated Pareto (IEP) distribution. Here, both point and interval estimates are calculated by employing the classical maximum likelihood and a pivotal estimation methods. Also, existence and uniqueness of the maximum likelihood estimates are verified. Further, asymptotic confidence intervals are derived by using the asymptotic normality property of the maximum likelihood estimator. Moreover, generalized confidence intervals are obtained by utilizing the pivotal quantities. Additionally, some mathematical developments of the IEP distribution are discussed based on the concept of order statistics. Furthermore, all the estimations are performed on the basis of the block censoring procedure, where an adaptive progressive Type-II censoring is employed to every block. In this regard, the performances of two estimation methods, namely maximum likelihood estimation and pivotal estimation, is evaluated and compared through a simulation study. Finally, a real data is illustrated to demonstrate the flexibility of the proposed IEP model., Comment: 26 pages, 13 figures

We show that the holographic Schr\"odinger equation of light-front chiral QCD, together with the 't Hooft equation of (1+1)-dimensional QCD in the large $N_c$ limit, can simultaneously describe the $\phi$-meson mass spectroscopy as well as diffractive cross-section. We compute the $\phi$-meson diffractive cross-section by utilizing its resulting light-front wave functions (LFWFs), in conjunction with the color glass condensate (CGC) dipole scattering amplitude. Our predictions for the diffractive cross sections show good agreement with the existing experimental data from HERA at various energies from H1 and ZEUS collaborations. Additionally, we show that the obtained $\phi$-meson LFWFs effectively describe its various properties, including the decay constant, distribution amplitudes, electromagnetic form factors, charge radius, and magnetic and quadrupole moments., Comment: 17 pages, 9 figures, 3 tables

Modern cosmological research still thoroughly debates the discrepancy between local probes and the Cosmic Microwave Background observations in the Hubble constant ($H_0$) measurements, ranging from $4\sigma$ to $6\sigma$. In the current study we examine this tension using the Supernovae Ia (SNe Ia) data from the Pantheon, PantheonPlus, Joint Lightcurve Analysis (JLA), and Dark Energy Survey (DES) catalogs together with their combination called Master Sample containing 3789 SNe Ia, and dividing all of them into redshift-ordered bins. Two main binning techniques are presented: the equipopulation and the equispace in the $\log\, z$. We perform a Markov-Chain Monte Carlo analysis (MCMC) for each bin to determine the $H_0$ value, estimating it within the standard flat $\Lambda$CDM and the $w_{0}w_{a}$CDM models. These $H_0$ values are then fitted with the following phenomenological function: $\mathcal{H}_0(z) = \tilde{H}_0 / (1 + z)^\alpha$, where $\tilde{H}_0$ is a free parameter representing $\mathcal{H}_0(z)$ fitted at $z=0$, and $\alpha$ is the evolutionary parameter. Our results indicate a decreasing trend characterized by $\alpha \sim 0.01$ whose consistency with zero range from $1.00 \sigma$ at 3 bins in the Pantheon sample with the $w_{0}w_{a}$CDM model to $\geq 6 \sigma$ at 12 bins with the JLA and DES samples within the $\Lambda$CDM model. Such a trend in the SNe Ia catalogs could be due to evolution with redshift for the SNe Ia astrophysical variables or unveiled selection biases. Alternatively, intrinsic physics, possibly the $f(R)$ theory of gravity, could be responsible for this trend., Comment: 45 pages, 8 figures, 7 tables. Submitted to JHEAP. Comments are welcome

In this paper we propose a new paradigm for cosmology: a time dependent scalar condensate background originated from the quadratic $(R + \alpha R^2)$ Starobinski model, where $R$ is the Ricci scalar and $\alpha$ the coupling constant. In weak gravity limit the system decouples into a conventional graviton and a higher derivative scalar. It was shown earlier through works from our group, \cite{ssg,sg,us}, that the latter can sustain an oscillatory lowest energy configuration or a {\it{Geometric Condensate}} as it consists entirely of metric degrees of freedom. In the present work, we study Gravitational Wave propagation in this condensate background. We show that the explicit time dependent nature of the condensate can generate curvature and radiation-like contributions in the scale factor evolution in FLRW cosmology. Subsequently the condensate leaves its signature on the Gravitational Wave profile as it propagates in the condensate modified FLRW spacetime. The wave profile is calculated analytically in terms of Whittaker functions. The main novelty of the Geometric Condensate scheme is that no external (condensate) matter from outside has been considered., Comment: Some new references has been added. The analytical form of GW dispersion relation is also added in the present version. 13 pages, 6 figures

We perform $\textit{exact}$ half-line path integral quantization of flat, homogeneous cosmological models containing a perfect fluid acting as an internal clock, in a $D+1$ dimensional minisuperspace setup. We also discuss certain classes of operator ordering ambiguity inherent in such quantization procedures and argue that a particular ordering prescription in the quantum theory can preserve two symmetries, namely arbitrary lapse rescalings and general covariance, which are already present at the classical level. As a result of this imposition, a large class of quantum Hamiltonians differing by operator ordering produces the same inner products between quantum states. This imposition of the two symmetries of the classical minisuperspace models leads to a unique prescription for writing the quantum Hamiltonian for minisuperspace dimension $D\geq 2$. Interestingly, in the case of $D=1$, the lapse rescaling symmetry is lost in the quantum theory, leading to an essentially ambiguous description of the canonical theory. We provide general proof of this in the context of both canonical quantization and path integrals. We supply concrete examples to validate our findings further.

This paper aims to investigate the Cauchy problem for the semilinear damped wave equation for the fractional sub-Laplacian $(-\mathcal{L}_{\mathbb{H}})^{\alpha}$, $\alpha>0$ on the Heisenberg group $\mathbb{H}^{n}$ with power type non-linearity. With the presence of a positive damping term and nonnegative mass term, we derive $L^2-L^2$ decay estimates for the solution of the homogeneous linear fractional damped wave equation on $\mathbb{H}^{n}$, for its time derivative, and for its space derivatives. We also discuss how these estimates can be improved when we consider additional $L^1$-regularity for the Cauchy data in the absence of the mass term. Also, in the absence of mass term, we prove the global well-posedness for $2\leq p\leq 1+\frac{2\alpha}{(\mathcal{Q}-2\alpha)_{+}}$ $(\text{or }1+\frac{4\alpha}{\mathcal{Q}}

We calculate all leading-twist gluon generalized parton distributions (GPDs) inside the proton at nonzero skewness using the basis light-front quantization framework. The proton's light-front wave functions are derived from a light-front quantized Hamiltonian incorporating Quantum Chromodynamics inputs. Our results show that the qualitative behaviors of the GPDs are consistent with those from other theoretical calculations. Additionally, we analyze the GPDs in the boost-invariant longitudinal coordinate, $\sigma=\frac{1}{2} b^- P^+$, which serves as the Fourier conjugate of the skewness. The GPDs in $\sigma$-space exhibit diffraction patterns, reminiscent of optical wave diffraction., Comment: 11 pages, 3 figures, and 1 table

The emergence of new physical properties at the interfaces between complex oxides has always been of both fundamental and practical importance. Here, we report the observation of a giant topological Hall resistivity of $\sim 2.8 \mu \Omega$ \text{cm} at room temperature in an epitaxial thin-film heterostructure of permalloy (Py, Ni$_{80}$Fe$_{20}$) and the half-metallic ferromagnet La$_{0.65}$Sr$_{0.35}$MnO$_3$ (LSMO). This large magnitude of the topological Hall effect in the Py/LSMO heterostructure, compared to a single-layer Py thin film, is attributed to the optimized combination of ferromagnetism in LSMO and the strong spin-orbit-coupling-driven Rashba interaction at the interface. The introduction of a ferroelectric BaTiO$_3$ (BTO) sandwich layer in the Py/LSMO heterostructure also leads to an enhanced topological Hall resistivity compared to the single-layer Py thin film. Interestingly, magnetic force microscopy measurements reveal skyrmion-like features, suggesting the origin of the topological Hall effect. Our theoretical model calculations for the skyrmion lattice further indicate that the Rashba interaction, driven by the broken inversion symmetry in the Py/LSMO films, can account for the observed changes in the topological Hall effect at the interface. Our work opens the door for the potential use of Py/LSMO thin films in spintronic applications., Comment: 17 pages, 10 figures

In this paper, using the concept of ideal, we study the idea of rough ideal convergence of sequences which is an extension of the notion of rough convergence of sequences in a partial metric space. We define the set of rough $\mathcal{I}$-limit points and the set of rough $\mathcal{I}$-cluster points and then we prove some relevant results associated with these sets., Comment: 10 pages

Source code authorship attribution is important in software forensics, plagiarism detection, and protecting software patch integrity. Existing techniques often rely on supervised machine learning, which struggles with generalization across different programming languages and coding styles due to the need for large labeled datasets. Inspired by recent advances in natural language authorship analysis using large language models (LLMs), which have shown exceptional performance without task-specific tuning, this paper explores the use of LLMs for source code authorship attribution. We present a comprehensive study demonstrating that state-of-the-art LLMs can successfully attribute source code authorship across different languages. LLMs can determine whether two code snippets are written by the same author with zero-shot prompting, achieving a Matthews Correlation Coefficient (MCC) of 0.78, and can attribute code authorship from a small set of reference code snippets via few-shot learning, achieving MCC of 0.77. Additionally, LLMs show some adversarial robustness against misattribution attacks. Despite these capabilities, we found that naive prompting of LLMs does not scale well with a large number of authors due to input token limitations. To address this, we propose a tournament-style approach for large-scale attribution. Evaluating this approach on datasets of C++ (500 authors, 26,355 samples) and Java (686 authors, 55,267 samples) code from GitHub, we achieve classification accuracy of up to 65% for C++ and 68.7% for Java using only one reference per author. These results open new possibilities for applying LLMs to code authorship attribution in cybersecurity and software engineering., Comment: 12 pages, 5 figures

Generative modeling of symmetric densities has a range of applications in AI for science, from drug discovery to physics simulations. The existing generative modeling paradigm for invariant densities combines an invariant prior with an equivariant generative process. However, we observe that this technique is not necessary and has several drawbacks resulting from the limitations of equivariant networks. Instead, we propose to model a learned slice of the density so that only one representative element per orbit is learned. To accomplish this, we learn a group-equivariant canonicalization network that maps training samples to a canonical pose and train a non-equivariant generative model over these canonicalized samples. We implement this idea in the context of diffusion models. Our preliminary experimental results on molecular modeling are promising, demonstrating improved sample quality and faster inference time., Comment: NeurReps 2024 Workshop Version

In 1966, Tate proposed the Artin--Tate conjectures, which expresses special values of zeta function associated to surfaces over finite fields. Conditional on the Tate conjecture, Milne--Ramachandran formulated and proved similar conjectures for smooth proper schemes over finite fields. The formulation of these conjectures already relies on other unproven conjectures. In this paper, we give an unconditional formulation of these conjectures for dualizable $F$-gauges over finite fields and prove them. In particular, our results also apply unconditionally to smooth proper varieties over finite fields. A key new ingredient is the notion of ``stable Bockstein characteristic" that we introduce. Our proof uses techniques from the stacky approach to $F$-gauges recently introduced by Drinfeld and Bhatt--Lurie and the author's recent work on Dieudonn\'e theory using $F$-gauges., Comment: 31 pages, comments welcome!

Although the star formation process has been studied for decades, many important aspects of the physics involved remain unsolved. Recent advancement of instrumentation in the infrared, far-infrared and sub-millimetre wavelength regimes have contributed to a significantly improved understanding of processes in the interstellar medium (ISM) leading to star formation. The future of research on the ISM and star formation looks exciting with instruments like the JWST, ALMA, etc., already contributing to the topic by gathering high-resolution high-sensitivity data and with several larger ground- and space-bound facilities either being planned or constructed. India has a sizable number of astronomers engaged in research on topics related to the ISM and star formation. In this white paper invited by the Astronomical Society of India to prepare a vision document for Indian astronomy, we review the Indian contributions to the global understanding of the star formation process and suggest areas that require focused efforts both in creating observing facilities and in theoretical front in India, in order to improve the impact of our research in the coming decades., Comment: Accepted for publication in The Journal of Astrophysics and Astronomy Special Issue: Indian Astronomy in the Global Context: A compendium of white papers submitted towards the Astronomical Society of India Vision Document (2024)

Context. The supernova remnant (SNR) W44 and its surroundings are a prime target for studying the acceleration of cosmic rays (CRs). Several previous studies established an extended gamma-ray emission that is set apart from the radio shell of W44. This emission is thought to originate from escaped high-energy CRs that interact with a surrounding dense molecular cloud complex. Aims. We present a detailed analysis of Fermi-LAT data with an emphasis on the spatial and spectral properties of W44 and its surroundings. We also report the results of the observations performed with the MAGIC telescopes of the northwestern region of W44. Finally, we present an interpretation model to explain the gamma-ray emission of the SNR and its surroundings. Methods. We first performed a detailed spatial analysis of 12 years of Fermi-LAT data at energies above 1 GeV, in order to exploit the better angular resolution, while we set a threshold of 100MeV for the spectral analysis. We performed a likelihood analysis of 174 hours of MAGIC data above 130 GeV using the spatial information obtained with Fermi-LAT. Results. The combined spectra of Fermi-LAT and MAGIC, extending from 100MeV to several TeV, were used to derive constraints on the escape of CRs. Using a time-dependent model to describe the particle acceleration and escape from the SNR, we show that the maximum energy of the accelerated particles has to be ' 40 GeV. However, our gamma-ray data suggest that a small number of lower-energy particles also needs to escape. We propose a novel model, the broken-shock scenario, to account for this effect and explain the gamma-ray emission.

Mrk 421 was in its most active state around early 2010, which led to the highest TeV gamma-ray flux ever recorded from any active galactic nuclei. We aim to characterize the multiwavelength behavior during this exceptional year for Mrk 421, and evaluate whether it is consistent with the picture derived with data from other less exceptional years. We investigated the period from November 5, 2009, (MJD 55140) until July 3, 2010, (MJD 55380) with extensive coverage from very-high-energy (VHE; E$\,>\,$100$\,$GeV) gamma rays to radio with MAGIC, VERITAS, Fermi-LAT, RXTE, Swift, GASP-WEBT, VLBA, and a variety of additional optical and radio telescopes. We investigated the variability and correlation behavior among different energy bands in great detail. We find the strongest variability in X-rays and VHE gamma rays, and PSDs compatible with power-law functions. We observe strong correlations between X-rays and VHE gamma rays. We also report a marginally significant positive correlation between high-energy (HE; E$\,>\,$100$\,$MeV) gamma rays and the ultraviolet band. We detected marginally significant correlations between the HE and VHE gamma rays, and between HE gamma rays and the X-ray, that disappear when the large flare in February 2010 is excluded from the correlation study. The activity of Mrk 421 also yielded the first ejection of features in the VLBA images of the jet of Mrk 421. Yet the large uncertainties in the ejection times of these radio features prevent us from firmly associating them to the specific flares recorded during the campaign. We also show that the collected multi-instrument data are consistent with a scenario where the emission is dominated by two regions, a compact and extended zone, which could be considered as a simplified implementation of an energy-stratified jet as suggested by recent IXPE observations., Comment: Accepted for publication in Astronomy & Astrophysics. Corresponding authors: Felix Schmuckermaier, David Paneque, Axel Arbet Engels

We explore the effects of finite cycle period time ($\tau$) on the extractable work, power, and efficiency of the Geometric Brownian Information Engine (GBIE). The GBIE consists of overdamped Brownian particles confined within a monolobal geometry. It incorporates an error-free feedback controller that converts the information obtained about the state of the trapped Brownian particles into extractable work. The engine transitions from a high non-equilibrium steady state to a completely relaxed state. The performance of the information engine depends on the cycle period $(\tau)$, measurement distance $(x_m)$, and feedback location $(x_f)$ of the confinement. When $\tau$ is shorter than the characteristic relaxation time, it has been observed that the maximum power is achieved when the value of $\tilde{x}_f$ is less than 2. In contrast, when cycle period times are longer than the characteristic relaxation time, the maximum power is achieved when the scaled feedback location $\tilde{x}_f$ is exactly at 2. As the $\tau$ increases, the maximum average power decreases. We found that the average extractable work and efficiency of the GBIE increases as the feedback location increases up to a certain point, after which it decreases. In the limit of a long $\tau$, the highest efficiency as well extractable work is attained when $\tilde{x}_f$ is located at 2, regardless of the level of entropic control. As the dominance of entropic control increases, the extractable work and efficiency in the fully relaxed state decrease due to higher information loss during relaxation.

We obtain the mass spectra of strange mesons using a light-front quantized Hamiltonian with Quantum Chromodynamics (QCD) input, incorporating quark-antiquark and quark-antiquark-gluon Fock components, along with a three-dimensional confinement. We work within the basis light-front quantization framework. The resulting eigenvectors can simultaneously describe the kaon's electromagnetic form factor, decay constant, distribution amplitude, and quark and gluon distribution functions under QCD scale evolution. Using the obtained kaon parton distribution functions (PDFs), supplemented by established nuclear PDFs, we also predict the kaon-nucleus-induced Drell-Yan cross section, which is expected to be measured soon by COMPASS++/AMBER at CERN., Comment: 9 pages, 5 figures

Over the last decade, the field of programmable self-assembly has seen an explosion in the diversity of crystal lattices that can be synthesized from DNA-coated colloidal nanometer- and micrometer-scale particles. The prevailing wisdom has been that a particular crystal structure can be targeted by designing the DNA-mediated interactions, to enforce binding between specific particle pairs, and the particle diameters, to control the packing of the various species. In this article, we show that other ubiquitous nonspecific interactions can play equally important roles in determining the relative stability of different crystal polymorphs and therefore what crystal structure is most likely to form in an experiment. For a binary mixture of same-sized DNA-coated colloidal micrometer-scale particles, we show how changing the magnitudes of nonspecific steric and van der Waals interactions gives rise to a family of binary body-centered tetragonal crystals, including both cesium-chloride and copper-gold crystals. Simulations using pair potentials that account for these interactions reproduce our experimental observations quantitatively, and a theoretical model reveals how a subtle balance between specific and nonspecific forces determines the equilibrium crystal structure. These results highlight the importance of accounting for nonspecific interactions in the crystal-engineering design process., Comment: Includes supplementary information

Continuous gravitational waves (CWs) emission from neutron stars carries information about their internal structure and equation of state, and it can provide tests of General Relativity. We present a search for CWs from a set of 45 known pulsars in the first part of the fourth LIGO--Virgo--KAGRA observing run, known as O4a. We conducted a targeted search for each pulsar using three independent analysis methods considering the single-harmonic and the dual-harmonic emission models. We find no evidence of a CW signal in O4a data for both models and set upper limits on the signal amplitude and on the ellipticity, which quantifies the asymmetry in the neutron star mass distribution. For the single-harmonic emission model, 29 targets have the upper limit on the amplitude below the theoretical spin-down limit. The lowest upper limit on the amplitude is $6.4\!\times\!10^{-27}$ for the young energetic pulsar J0537-6910, while the lowest constraint on the ellipticity is $8.8\!\times\!10^{-9}$ for the bright nearby millisecond pulsar J0437-4715. Additionally, for a subset of 16 targets we performed a narrowband search that is more robust regarding the emission model, with no evidence of a signal. We also found no evidence of non-standard polarizations as predicted by the Brans-Dicke theory., Comment: main paper: 12 pages, 6 figures, 4 tables

The information engine extracts work from a single heat bath using mutual information obtained during the operation cycle. This study investigates the influence of the potential shaping in a Brownian information engine (BIE) in harnessing the information from thermal fluctuations. We have designed a BIE by considering an overdamped Brownian particle inside a confined potential and introducing an appropriate symmetric feedback cycle. We find that the upper bound of the extractable work for a BIE with a monostable centrosymmetric confining potential, with a stable state at the potential centre, depends on the bath temperature and the convexity of the confinement. A concave confinement is more efficient for an information-energy exchange. For a bistable confinement with an unstable centre and two symmetric stable basins, one can find an engine-to-refrigeration transition beyond a certain barrier height related to the energy difference between the energy barrier and the stable basins. Finally, we use the concavity-induced gain in information harnessing to device a BIE in the presence of a multistable potential that can harvest even more energy than monostable confinement.