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The dynamical and geometric structures of the Broad Line Region (BLR), along with the origins of continuum time delays in active galaxies, remain topics of ongoing debate. In this study, we aim to reproduce the broadband spectrum, the H$\beta$ line delay, and the continuum time delays available for the source NGC 5548. We employ the standard accretion disk model with the option of an inner hot flow, alongside the lamp-post model to account for disk irradiation and a BLR structure model based on radiation pressure acting on dust. The model is parameterized by the black hole mass (fixed), accretion rate, viewing angle, lamp-post height, cloud density, and cloud covering factor. The resulting continuum delays are calculated as a combination of disk reprocessing and the reprocessing of a fraction of radiation by the BLR. Our model reasonably reproduces the observed broad-band continuum, the H$\beta$ delay, and the continuum inter-band time delays measured during the observational campaign. When the accretion rate is not fixed based on the known distance to the source, we can directly estimate the distance from our model. The resulting value of H$_0$ = $69.03^{+17.81}_{-11.75}$ km s$^{-1}$ Mpc$^{-1}$ represents a noteworthy improvement compared to the findings of Cackett et al. (2007). This pilot study demonstrates that, with sufficient data coverage, it is possible to disentangle the time delays originating from the accretion disk and the BLR. This paves the way for effectively using inter-band continuum time delays in determining the Hubble constant. Additionally, the findings support the adopted model for the formation of the H$\beta$ line., Comment: submitted to A&A, comments welcome

The rapid advancements in artificial intelligence (AI) have revolutionized smart healthcare, driving innovations in wearable technologies, continuous monitoring devices, and intelligent diagnostic systems. However, security, explainability, robustness, and performance optimization challenges remain critical barriers to widespread adoption in clinical environments. This research presents an innovative algorithmic method using the Adaptive Feature Evaluator (AFE) algorithm to improve feature selection in healthcare datasets and overcome problems. AFE integrating Genetic Algorithms (GA), Explainable Artificial Intelligence (XAI), and Permutation Combination Techniques (PCT), the algorithm optimizes Clinical Decision Support Systems (CDSS), thereby enhancing predictive accuracy and interpretability. The proposed method is validated across three diverse healthcare datasets using six distinct machine learning algorithms, demonstrating its robustness and superiority over conventional feature selection techniques. The results underscore the transformative potential of AFE in smart healthcare, enabling personalized and transparent patient care. Notably, the AFE algorithm, when combined with a Multi-layer Perceptron (MLP), achieved an accuracy of up to 98.5%, highlighting its capability to improve clinical decision-making processes in real-world healthcare applications.

We investigate the 1D stellar evolution of a 16.5 M$_{\odot}$ zero-age main-sequence star having different initial rotations. Starting from the pre-main-sequence, the models evolve up to the onset of the core collapse stage. The collapse of such a massive star can result in several kinds of energetic transients, such as Gamma-Ray Bursts (GRBs), Supernovae, etc. Using the simulation parameters, we calculate their free-fall timescales when the models reach the stage of the onset of core collapse. Estimating the free-fall timescale is crucial for understanding the duration for which the central engine can be fueled, allowing us to compare the free-fall timescale with the T$_{\rm 90}$ duration of GRBs. Our results indicate that, given the constraints of the parameters and initial conditions in our models, rapidly rotating massive stars might serve as potential progenitors of Ultra-Long GRBs (T$_{\rm 90}$ $>>$ 500 sec). In contrast, the non-rotating or slowly rotating models are more prone to explode as hydrogen-rich Type IIP-like core-collapse supernovae., Comment: 8 pages, 4 figures, 1 table, accepted

Flexoelectricity is a universal effect that generates electric polarization due to broken inversion symmetry caused by local strain gradient. The large strain gradient at nanoscale makes flexo-electric effects, especially in nanoscopic ferroelectric materials, promising in sensors, actuator, energy harvesting, and memory applications. In this work, we studied flexoelectricity in hexagonal ferrites h-YbFeO3, an improper ferroelectric expected to have weak piezoelectricity and low sensitivity to depolarization field, which are advantageous for studying flexoelectric effects. We show that in h-YbFeO3 epitaxial thin films, strain gradient on the order of 10^6 m-1 occurs near grain boundaries, which has a significant impact on the non-polar K3 structural distortion that induces spontaneous polarization. The phenomenological model based on the Landau theory of improper ferroelectricity suggests an indirect flexoelectric effect on the order of 10 nC/m in h-YbFeO3, which is substantially larger than the expectation from Kogan mechanism. These results reveal a novel microscopic mechanism of coupling between strain gradient and polarization mediated by structural distortion, which we call improper flexoelectricity.

Understanding the origins of massive black hole seeds and their co-evolution with their host galaxy requires studying intermediate-mass black holes (IMBHs) and estimating their mass. However, measuring the mass of these IMBHs is challenging due to the high spatial resolution requirement. A spectrophotometric reverberation monitoring is performed for a low-luminosity Seyfert 1 galaxy NGC 4395 to measure the size of the broad line region (BLR) and black hole mass. The data were collected using the 1.3-m Devasthal fast optical telescope (DFOT) and 3.6-m Devasthal optical telescope (DOT) at ARIES, Nainital, over two consecutive days in March 2022. The analysis revealed strong emission lines in the spectra and light curves of merged 5100{\AA} spectroscopic continuum flux ($f_{\mathrm{5100}}$) with photometric continuum V-band and H$\alpha$, with fractional variabilities of 6.38\% and 6.31\% respectively. In comparison to several previous studies with lag estimation $<$ 90 minutes, our calculated H$\alpha$ lag supersedes by $125.0^{+6.2}_{-6.1}$ minutes using ICCF and {\small JAVELIN} methods. The velocity dispersion ($\sigma_{\mathrm{line}}$) of the broad line clouds is measured to be $544.7^{+22.4}_{-25.1}$ km s$^{-1}$, yielding a black hole mass of $\sim$ $2.2^{+0.2}_{-0.2}\times 10^{4}M_{\mathrm{\odot}}$ and an Eddington ratio of 0.06., Comment: 17 pages, 8 figures, accepted for publication in ApJ

We present near-simultaneous X-ray and optical polarization measurements in the high synchrotron peaked (HSP) blazar Mrk 421. The X-ray polarimetric observations were carried out using {\it Imaging X-ray Polarimetry Explorer} ({\it IXPE}) on 06 December 2023. During {\it IXPE} observations, we also carried out optical polarimetric observations using 104cm Sampurnanand telescope at Nainital and multi-band optical imaging observations using 2m Himalayan Chandra Telescope at Hanle. From model-independent analysis of {\it IXPE} data, we detected X-ray polarization with degree of polarization ($\Pi_X$) of 8.5$\pm$0.5\% and an electric vector position angle ($\Psi_X$) of 10.6$\pm$1.7 degrees in the 2$-$8 keV band. From optical polarimetry on 06 December 2023, in B, V, and R bands, we found values of $\Pi_B$ = 4.27$\pm$0.32\%, $\Pi_V$= 3.57$\pm$0.31\%, and $\Pi_R$= 3.13$\pm$0.25\%. The value of $\Pi_B$ is greater than that observed at longer optical wavelengths, with the degree of polarization suggesting an energy-dependent trend, gradually decreasing from higher to lower energies. This is consistent with that seen in other HSP blazars and favour a stratified emission region encompassing a shock front. The emission happening in the vicinity of the shock front will be more polarized due to the ordered magnetic field resulting from shock compression. The X-ray emission, involving high-energy electrons, originates closer to the shock front than the optical emission. The difference in the spatial extension could plausibly account for the observed variation in polarization between X-ray and optical wavelengths. This hypothesis is further supported by the broadband spectral energy distribution modeling of the X-ray and optical data., Comment: 9 pages, 3 figures. Accepted for publication in ApJ

Diffusion-based speech generators are ubiquitous. These methods can generate very high quality synthetic speech and several recent incidents report their malicious use. To counter such misuse, synthetic speech detectors have been developed. Many of these detectors are trained on datasets which do not include diffusion-based synthesizers. In this paper, we demonstrate that existing detectors trained on one such dataset, ASVspoof2019, do not perform well in detecting synthetic speech from recent diffusion-based synthesizers. We propose the Diffusion-Based Synthetic Speech Dataset (DiffSSD), a dataset consisting of about 200 hours of labeled speech, including synthetic speech generated by 8 diffusion-based open-source and 2 commercial generators. We also examine the performance of existing synthetic speech detectors on DiffSSD in both closed-set and open-set scenarios. The results highlight the importance of this dataset in detecting synthetic speech generated from recent open-source and commercial speech generators., Comment: Submitted to IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP) 2025

The chirality-induced spin selectivity (CISS) effect has garnered significant interest in the field of molecular spintronics due to its potential for creating spin-polarized electrons without the need for a magnet. Recent studies devoted to CISS effects in various chiral materials demonstrate exciting prospects for spintronics, chiral recognition, and quantum information applications. Several experimental studies have confirmed the applicability of chiral molecules towards spin-filtering properties, influencing spin-polarized electron transport, and photoemission. Researchers aim to predict CISS phenomena and apply this concept to practical applications by compiling experimental results and enhancing understanding of the CISS effect. To expand the possibilities of spin manipulation and create new opportunities for spin-based technologies, researchers are diligently exploring different chiral organic and inorganic materials for probing the CISS effect. This ongoing research holds promise for developing novel spin-based technologies and advancing the understanding of the intricate relationship between chirality and electron spin. This review showcases the remarkable CISS effect and its impact on spintronics, as well as its relevance in various other scientific areas., Comment: 29 pages, 20 figures

Large Language Models (LLMs) have revolutionised the capability of AI models in comprehending and generating natural language text. They are increasingly being used to empower and deploy agents in real-world scenarios, which make decisions and take actions based on their understanding of the context. Therefore researchers, policy makers and enterprises alike are working towards ensuring that the decisions made by these agents align with human values and user expectations. That being said, human values and decisions are not always straightforward to measure and are subject to different cognitive biases. There is a vast section of literature in Behavioural Science which studies biases in human judgements. In this work we report an ongoing investigation on alignment of LLMs with human judgements affected by order bias. Specifically, we focus on a famous human study which showed evidence of order effects in similarity judgements, and replicate it with various popular LLMs. We report the different settings where LLMs exhibit human-like order effect bias and discuss the implications of these findings to inform the design and development of LLM based applications., Comment: Accepted at The First Workshop on AI Behavioral Science (AIBS 2024), held in conjunction with KDD 2024

Blazars, the peculiar class of active galactic nuclei (AGN), are known to show flux variations across the accessible electromagnetic spectrum. Though they have been studied extensively for their flux variability characteristics across wavelengths, information on their ultraviolet (UV) flux variations on time scales of hours is very limited. Here, we present the first UV flux variability study on intraday time scales of a sample of 10 blazars comprising 2 flat spectrum radio quasars (FSRQs) and 8 BL Lacertae objects (BL Lacs). These objects, spanning a redshift (z) range of 0.034 <= z <= 1.003, were observed in the far-UV (FUV: 1300 - 1800 \text{\AA}) and near-UV (NUV: 2000 - 3000 \text{\AA}) wavebands using the ultraviolet imaging telescope on board AstroSat. UV flux variations on time scales of hours were detected in 9 sources out of the observed 10 blazars. The spectral variability analysis showed a bluer-when-brighter trend with no difference in the UV spectral variability behavior between the studied sample of FSRQs and BL Lacs. The observed UV flux and spectral variability in our sample of both FSRQs and BL Lacs revealed that the observed UV emission in them is dominated by jet synchrotron process., Comment: 23 pages, 5 figures, 6 tables; accepted for publication in The Astrophysical Journal

The discovery of ferroelectricity in hafnia-based materials have boosted the potential of incorporating ferroelectrics in advanced electronics, thanks to their compatibility with silicon technology. However, comprehending why these materials defy the common trend of reduced ferroelectric ordering at the nanoscale, and the mechanism that stabilizes the ferroelectric phase (absent in hafnia phase diagram) presents significant challenges to traditional knowledge of ferroelectricity. In this work, we show that the formation of the orthorhombic ferroelectric phase (o-FE, space group Pca21) of the single-crystalline epitaxial films of 10% La-doped HfO2 (LHO) on (111)-oriented yttria stabilized zirconia (YSZ) relies on the stability of the high-pressure orthorhombic antiferroelectric phase (o-AFE, space group Pbca). Our detailed structural characterizations demonstrate that as-grown LHO films represent largely the o-AFE phase being thermodynamically stabilized by the compressive strain. Our Kelvin probe force microscopy studies show, under mechanical poling, the o-AFE phase is converted to the o-FE phase which remains stable under ambient conditions. We find that the orthorhombic phase stability is enhanced in thinner films down to one-unit-cell thickness, a trend that is unknown in any other ferroelectric films. This is due to the vanishing depolarization field of the o-AFE phase and the isomorphic LHO/YSZ interface, supporting strain-enhanced ferroelectricity in the ultrathin films. This results in an unprecedented increase of the Curie temperature up to 850 {\deg}C, the highest reported for sub-nanometer-thick ferroelectrics. Overall, our findings opens the way for advanced engineering of hafnia-based materials for ferroelectric applications and heralding a new frontier of high-temperature ferroelectrics at the two-dimensional limit.

In this note, we continue the study of Seshadri constants on blow-ups of Hirzebruch surfaces initiated in arXiv:2312.14555. Now we consider blow-ups of ruled surfaces more generally. We propose a conjecture for classifying all the negative self-intersection curves on the blow-up of a ruled surface at very general points, analogous to the $(-1)$-curves conjecture in $\mathbb{P}^2$. Assuming this conjecture is true, we exhibit an ample line bundle with an irrational Seshadri constant at a very general point on such a surface., Comment: 13 Pages

This study presents novel predictive models using Graph Neural Networks (GNNs) for simulating thermal dynamics in Laser Powder Bed Fusion (L-PBF) processes. By developing and validating Single-Laser GNN (SL-GNN) and Multi-Laser GNN (ML-GNN) surrogates, the research introduces a scalable data-driven approach that learns fundamental physics from small-scale Finite Element Analysis (FEA) simulations and applies them to larger domains. Achieving a Mean Absolute Percentage Error (MAPE) of 3.77% with the baseline SL-GNN model, GNNs effectively learn from high-resolution simulations and generalize well across larger geometries. The proposed models capture the complexity of the heat transfer process in L-PBF while significantly reducing computational costs. For example, a thermomechanical simulation for a 2 mm x 2 mm domain typically requires about 4 hours, whereas the SL-GNN model can predict thermal distributions almost instantly. Calibrating models to larger domains enhances predictive performance, with significant drops in MAPE for 3 mm x 3 mm and 4 mm x 4 mm domains, highlighting the scalability and efficiency of this approach. Additionally, models show a decreasing trend in Root Mean Square Error (RMSE) when tuned to larger domains, suggesting potential for becoming geometry-agnostic. The interaction of multiple lasers complicates heat transfer, necessitating larger model architectures and advanced feature engineering. Using hyperparameters from Gaussian process-based Bayesian optimization, the best ML-GNN model demonstrates a 46.4% improvement in MAPE over the baseline ML-GNN model. In summary, this approach enables more efficient and flexible predictive modeling in L-PBF additive manufacturing.

We study new identities related to the sums of adjacent terms in the Pell sequence, defined by $P_{n} := 2P_{n-1}+P_{n-2}$ for $ n\geq 2$ and $P_{0}=0, P_{1}=1$, and generalize these identities for many similar sequences. We prove that the sum of $N>1$ consecutive Pell numbers is a fixed integer multiple of another Pell number if and only if $4\mid N$. We consider the generalized Pell $(k,i)$-numbers defined by $p(n) :=\ 2p(n-1)+p(n-k-1) $ for $n\geq k+1$, with $p(0)=p(1)=\cdots =p(i)=0$ and $p(i+1)=\cdots = p(k)=1$ for $0\leq i\leq k-1$, and prove that the sum of $N=2k+2$ consecutive terms is a fixed integer multiple of another term in the sequence. We also prove that for the generalized Pell $(k,k-1)$-numbers such a relation does not exist when $N$ and $k$ are odd. We give analogous results for the Fibonacci and other related second-order recursive sequences., Comment: 33 Pages. Comments welcome!

Quantum communication represents a revolutionary advancement over classical information theory, which leverages unique quantum mechanics properties like entanglement to achieve unprecedented capabilities in secure and efficient information transmission. Unlike bits in classical communication, quantum communication utilizes qubits in superposition states, allowing for novel information storage and processing. Entanglement, a key quantum phenomenon, enables advanced protocols with enhanced security and processing power. This paper provides a comprehensive overview of quantum communication, emphasizing the role of entanglement in theoretical foundations, practical protocols, experimental progress, and security implications. It contrasts quantum communications potential applications with classical networks, identifying areas where entanglement offers significant advantages. The paper explores the fundamentals of quantum mechanics in communication, the physical realization of quantum information, and the formation of secure quantum networks through entanglement-based strategies like Quantum Key Distribution (QKD) and teleportation. It addresses the challenges of long-distance quantum communication, the role of quantum repeaters in scaling networks, and the conceptualization of interconnected quantum networks. Additionally, it discusses strides towards the Quantum Internet, Quantum Error-Correcting codes, and quantum cryptographys role in ensuring secure communication. By highlighting the role of entanglement, this paper aims to inspire further research and innovation in secure and efficient information exchange within quantum networks., Comment: 56 pages, 11 figures, 3 tables

Noisy unsharp measurements incorporated in quantum information protocols may hinder performance, reducing the quantum advantage. However, we show that, unlike projective measurements which completely destroy quantum correlations between nodes in quantum networks, sequential applications of noisy measurements can mitigate the adverse impact of noise in the measurement device on quantum information processing tasks. We demonstrate this in the case of concentrating entanglement on chosen nodes in quantum networks via noisy measurements performed by assisting qubits. In the case of networks with a cluster of three or higher number of qubits, we exhibit that sequentially performing optimal unsharp measurements on the assisting qubits yields localizable entanglement between two nodes akin to that obtained by optimal projective measurements on the same assisting qubits. Furthermore, we find that the proposed approach using consecutive noisy measurements can potentially be used to prepare desired states that are resource for specific quantum schemes. We also argue that assisting qubits have greater control over the qubits on which entanglement is concentrated via unsharp measurements, in contrast to sharp measurement-based protocols, which may have implications for secure quantum communication., Comment: 14 pages, 9 figures

With the recent advancements and developments in quantum technologies, the emerging field of quantum communication and networking has gained the attention of the researchers. Owing to the unique properties of quantum mechanics, viz., quantum superposition and entanglement, this new area of quantum communication has shown potential to replace modernday communication technologies. The enhanced security and high information sharing ability using principles of quantum mechanics has encouraged networking engineers and physicists to develop this technology for next generation wireless systems. However, a conceptual bridge between the fundamentals of quantum mechanics, photonics and the deployability of a quantum communication infrastructure is not well founded in the current literature. This paper aims to fill this gap by merging the theoretical concepts from quantum physics to the engineering and computing perspectives of quantum technology. This paper builds the fundamental concepts required for understanding quantum communication, reviews the key concepts and demonstrates how these concepts can be leveraged for accomplishing successful communication. The paper delves into implementation advancements for executing quantum communication protocols, explaining how hardware implementation enables the achievement of all basic quantum computing operations. Finally, the paper provides a comprehensive and critical review of the state-of-the-art advancements in the field of quantum communication and quantum internet; and points out the recent trends, challenges and open problems for the real-world realization of next generation networking systems.

The brightest Gamma-ray burst (GRB) ever, GRB 221009A, displays ultra-long GRB (ULGRB) characteristics, with a prompt emission duration exceeding 1000 s. To constrain the origin and central engine of this unique burst, we analyze its prompt and afterglow characteristics and compare them to the established set of similar GRBs. To achieve this, we statistically examine a nearly complete sample of Swift-detected GRBs with measured redshifts. Categorizing the sample to Bronze, Silver, and Gold by fitting a Gaussian function to the log-normal of T$_{90}$ duration distribution and considering three sub-samples respectively to 1, 2, and 3 times of the standard deviation to the mean value. GRB 221009A falls into the Gold sub-sample. Our analysis of prompt emission and afterglow characteristics aims to identify trends between the three burst groups. Notably, the Gold sub-sample (a higher likelihood of being ULGRB candidates) suggests a collapsar scenario with a hyper-accreting black hole as a potential central engine, while a few GRBs (GRB 060218, GRB 091024A, and GRB 100316D) in our Gold sub-sample favor a magnetar. Late-time near-IR (NIR) observations from 3.6m Devasthal Optical Telescope (DOT) rule out the presence of any bright supernova associated with GRB 221009A in the Gold sub-sample. To further constrain the physical properties of ULGRB progenitors, we employ the tool MESA to simulate the evolution of low-metallicity massive stars with different initial rotations. The outcomes suggest that rotating ($\Omega \geq 0.2\,\Omega_{\rm c}$) massive stars could potentially be the progenitors of ULGRBs within the considered parameters and initial inputs to MESA., Comment: Accepted in Astrophysical Journal: 39 pages, 19 Figures and 8 Tables

The bright GRB 210610B was discovered simultaneously by Fermi and Swift missions at redshift 1.13. We utilized broadband Fermi-GBM observations to perform a detailed prompt emission spectral analysis and to understand the radiation physics of the burst. Our analysis displayed that the low energy spectral index ($\alpha_{\rm pt}$) exceeds boundaries expected from the typical synchrotron emission spectrum (-1.5,-0.67), suggesting additional emission signature. We added an additional thermal model with the typical Band or CPL function and found that CPL + BB function is better fitting to the data, suggesting a hybrid jet composition for the burst. Further, we found that the beaming corrected energy (E$_{\rm \gamma, \theta_{j}}$ = 1.06 $\times$ 10$^{51}$ erg) of the burst is less than the total energy budget of the magnetar. Additionally, the X-ray afterglow light curve of this burst exhibits achromatic plateaus, adding another layer of complexity to the explosion's behavior. Interestingly, we noted that the X-ray energy release during the plateau phase (E$_{\rm X,iso}$ = 1.94 $\times$ 10$^{51}$ erg) is also less than the total energy budget of the magnetar. Our results indicate the possibility that a magnetar could be the central engine for this burst., Comment: Accepted for publication in the Bulletin of Liege Royal Society of Sciences as a part of the 3rd BINA workshop, March 22-24, 2023, 10 pages, 2 figures, and 2 table

We investigate the topological-to-non-topological quantum phase transitions (QPTs) occurring in the Kitaev code under local perturbations in the form of local magnetic field and spin-spin interactions of the Ising-type using fidelity susceptibility (FS) and entanglement as the probes. We assume the code to be embedded on the surface of a wide cylinder of height $M$ and circumference $D$ with $M\ll D$. We demonstrate a power-law divergence of FS across the QPT, and determine the quantum critical points (QCPs) via a finite-size scaling analysis. We verify these results by mapping the perturbed Kitaev code to the 2D Ising model with nearest- and next-nearest-neighbor interactions, and computing the single-site magnetization as order parameter using quantum Monte-Carlo technique. We also point out an odd-even dichotomy in the occurrence of the QPT in the Kitaev ladder with respect to the odd and even values of $D$, when the system is perturbed with only Ising interaction. Our results also indicate a higher robustness of the topological phase of the Kitaev code against local perturbations if the boundary is made open along one direction. We further consider a local entanglement witness operator designed specifically to capture a lower bound to the localizable entanglement on the vertical non-trivial loop of the code. We show that the first derivative of the expectation value of the witness operator exhibits a logarithmic divergence across the QPT, and perform the finite-size scaling analysis. We demonstrate similar behaviour of the expectation value of the appropriately constructed witness operator also in the case of locally perturbed color code with open boundaries., Comment: 14 pages, 7 figures, 1 table

FM1/NM/FM2 trilayers have garnered considerable attention because of their potential in spintronic applications. A thorough investigation of the spin transport properties of these trilayers is therefore important. Asymmetric trilayers, particularly those including Platinum (Pt) as a spacer are less explored. Pt mediates exchange coupling between the two FM layers and thus offers a unique platform to investigate the spin-transport properties under indirect exchange coupling conditions through the spin-pumping mechanism. Our analytical focus on the acoustic mode of the ferromagnetic resonance spectrum, facilitated by the distinct magnetizations of the Ni80Fe20 and Co layers, allows for the isolation of individual layer resonances. The derived spin-pumping induced damping of the Ni80Fe20 and Co layers reveals a direct dependence on the Pt spacer thickness. Furthermore, fitting of the weighted average of the damping parameters to the spin-pumping induced damping of acoustic mode reveals that the observed FMR spectra is indeed a result of the in-phase precession of the magnetizations in two FM layers. The extracted effective spin-mixing conductance varies with the FM/NM interface, specifically 1.72x10^19 m^(-2) at the Ni80Fe20/Pt and 4.07x10^19 m^(-2) at the Co/Pt interface, indicating a strong correlation with interfacial characteristics. Additionally, we deduce the spin diffusion length in Pt to be between 1.02 and 1.55 nm and calculate the interfacial spin transparency and spin current densities, highlighting significant disparities between the Ni80Fe20/Pt and Co/Pt interfaces. This detailed analysis enhances our understanding of spin transport in Ni80Fe20/Pt/Co trilayers. It offers insights important for advancing spintronic device design and lays the groundwork for future theoretical investigations of trilayer system., Comment: 16 pages, 11 figures

In communication-deprived disaster scenarios, this paper introduces a Micro-Unmanned Aerial Vehicle (UAV)- enhanced content management system. In the absence of cellular infrastructure, this system deploys a hybrid network of stationary and mobile UAVs to offer vital content access to isolated communities. Static anchor UAVs equipped with both vertical and lateral links cater to local users, while agile micro-ferrying UAVs, equipped with lateral links and greater mobility, reach users in various communities. The primary goal is to devise an adaptive content dissemination system that dynamically learns caching policies to maximize content accessibility. The paper proposes a decentralized Top-k Multi-Armed Bandit (Top-k MAB) learning approach for UAV caching decisions, accommodating geotemporal disparities in content popularity and diverse content demands. The proposed mechanism involves a Selective Caching Algorithm that algorithmically reduces redundant copies of the contents by leveraging the shared information between the UAVs. It is demonstrated that Top-k MAB learning, along with selective caching algorithm, can improve system performance while making the learning process adaptive. The paper does functional verification and performance evaluation of the proposed caching framework under a wide range of network size, swarm of micro-ferrying UAVs, and heterogeneous popularity distributions., Comment: 12 pages, 7 figures, 2 algorithms, 1 table. arXiv admin note: substantial text overlap with arXiv:2312.14967

This paper presents a computationally efficient and distributed speaker diarization framework for networked IoT-style audio devices. The work proposes a Federated Learning model which can identify the participants in a conversation without the requirement of a large audio database for training. An unsupervised online update mechanism is proposed for the Federated Learning model which depends on cosine similarity of speaker embeddings. Moreover, the proposed diarization system solves the problem of speaker change detection via. unsupervised segmentation techniques using Hotelling's t-squared Statistic and Bayesian Information Criterion. In this new approach, speaker change detection is biased around detected quasi-silences, which reduces the severity of the trade-off between the missed detection and false detection rates. Additionally, the computational overhead due to frame-by-frame identification of speakers is reduced via. unsupervised clustering of speech segments. The results demonstrate the effectiveness of the proposed training method in the presence of non-IID speech data. It also shows a considerable improvement in the reduction of false and missed detection at the segmentation stage, while reducing the computational overhead. Improved accuracy and reduced computational cost makes the mechanism suitable for real-time speaker diarization across a distributed IoT audio network., Comment: 11 pages, 7 figures, 1 table

Methods that can generate synthetic speech which is perceptually indistinguishable from speech recorded by a human speaker, are easily available. Several incidents report misuse of synthetic speech generated from these methods to commit fraud. To counter such misuse, many methods have been proposed to detect synthetic speech. Some of these detectors are more interpretable, can generalize to detect synthetic speech in the wild and are robust to noise. However, limited work has been done on understanding bias in these detectors. In this work, we examine bias in existing synthetic speech detectors to determine if they will unfairly target a particular gender, age and accent group. We also inspect whether these detectors will have a higher misclassification rate for bona fide speech from speech-impaired speakers w.r.t fluent speakers. Extensive experiments on 6 existing synthetic speech detectors using more than 0.9 million speech signals demonstrate that most detectors are gender, age and accent biased, and future work is needed to ensure fairness. To support future research, we release our evaluation dataset, models used in our study and source code at https://gitlab.com/viper-purdue/fairssd., Comment: Accepted at CVPR 2024 (WMF)

A connected graph, on four or more vertices, is matching covered if every edge is present in some perfect matching. An ear decomposition theorem (similar to the one for $2$-connected graphs) exists for bipartite matching covered graphs due to Hetyei. From the results and proofs of Lov\'asz and Plummer, that rely on Hetyei's theorem, one may deduce that any minimal bipartite matching covered graph has at least $2(m-n+2)$ vertices of degree two (where minimal means that deleting any edge results in a graph that is not matching covered); such a graph is said to be extremal if it attains the stated lower bound. In this paper, we provide a complete characterization of the class of extremal minimal bipartite matching covered graphs. In particular, we prove that every such graph $G$ is obtained from two copies of a tree devoid of degree two vertices, say $T$ and $T'$, by adding edges -- each of which joins a leaf of $T$ with the corresponding leaf of $T'$. Apart from the aforementioned bound, there are four other bounds that appear in, or may be deduced from, the work of Lov\'asz and Plummer. Each of these bounds leads to a notion of extremality. In this paper, we obtain a complete characterization of all of these extremal classes and also establish relationships between them. Two of our characterizations are in the same spirit as the one stated above. For the remaining two extremal classes, we reduce each of them to one of the already characterized extremal classes using standard matching theoretic operations., Comment: Submitted to Innovations in Graph Theory

In this short manuscript, we will put some light on the different outcomes when two non-constant meromorphic functions share a value with prescribed weight two., Comment: arXiv admin note: text overlap with arXiv:1608.02125 by other authors

We investigate the torus size -- luminosity relation of Type 1 AGNs based on the reverberation-mapping analysis using the light curves of the optical continuum and the IR continuum obtained with the W1 and W2-bands of the Wide-field Infrared Survey Explorer (WISE) survey. The final sample consists of 446 and 416 AGNs, respectively, for W1 and W2-band light curves, covering a large dynamic range of bolometric luminosity from $10^{43.4}$ to $10^{47.6}$ $erg \, s^{-1}$, which show reliable lag measurements based on our quality assessment analysis. After correcting for the accretion disk contamination in the observed IR flux, we constrain the torus size ($R_{dust}$) and AGN bolometric luminosity ($L_{bol}$) relationship with the best-fit slope of 0.39 (0.33) for the W1- (W2-) band, which is shallower than expected from the dust radiation equilibrium model. By combining the previous K-band lag measurements, we find that the measured torus size depends on the observed wavelength of the dust radiation, as $R_{dust,K}:R_{dust,W1}:R_{dust,W2}$ = 1.0:1.5:1.8 ($R_{dust} \, \propto \, \lambda^{0.80}$) at $L_{bol}$ = $10^{46} \, erg \, s^{-1}$, confirming a stratified structure of the torus, where wavelength-dependent emissions originate from distinct regions of the torus. By investigating the deviation from the best-fit torus size -- luminosity relation, we find a moderate correlation between the offset from the $R_{dust}$--$L_{bol}$ relation and Eddington ratio. This suggests a possible influence of the Eddington ratio on the observed flattening of the $R_{dust}$--$L_{bol}$ relationship., Comment: 35 pages, 21 figures, 6 tables. Corrected for typos. Accepted for publication in ApJ

Changing-look (CL) Active Galactic Nuclei (AGNs), characterized by appearance/disappearance of broad emission lines in the span of a few years, present a challenge for the AGN unified model, whereby the Type 1 vs. Type 2 dichotomy results from orientation effects alone. We present a systematic study of a large sample of spectroscopically classified AGNs, using optical variability data from the Zwicky Transient Facility (ZTF) as well as follow-up spectroscopy data. We demonstrate that Type 1 vs. 2 AGN can be neatly separated on the basis of the variability metric $\sigma_{\rm QSO}$, which quantifies the resemblance of a light curve to a damp random walk model. For a small sub-sample, however, the ZTF light curves are inconsistent with their previous classification, suggesting the occurrence of a CL event. Specifically, we identify 35 (12) turn-on (turn-off) CL AGN candidates at $z < 0.35$. Based on follow-up spectroscopy, we confirm 17 (4) turn-on (turn-off) CL AGNs out of 21 (5) candidates, presenting a high success rate of our method. Our results suggest that the occurrence rate of CL AGNs is $\sim$0.3% over timescales of 5 to 20 years, and confirm that the CL transition typically occurs at the Eddington ratio of $\leq 0.01$., Comment: 23 pages, 12 figures. Accepted by ApJ

Production-grade recommender systems rely heavily on a large-scale corpus used by online media services, including Netflix, Pinterest, and Amazon. These systems enrich recommendations by learning users' and items' embeddings projected in a low-dimensional space with two-stage models (two deep neural networks), which facilitate their embedding constructs to predict users' feedback associated with items. Despite its popularity for recommendations, its theoretical behaviors remain comprehensively unexplored. We study the asymptotic behaviors of the two-stage recommender that entail a strong convergence to the optimal recommender system. We establish certain theoretical properties and statistical assurance of the two-stage recommender. In addition to asymptotic behaviors, we demonstrate that the two-stage recommender system attains faster convergence by relying on the intrinsic dimensions of the input features. Finally, we show numerically that the two-stage recommender enables encapsulating the impacts of items' and users' attributes on ratings, resulting in better performance compared to existing methods conducted using synthetic and real-world data experiments., Comment: 18 pages (including references and appendix), 1 figure, 2 tables

Many deep learning synthetic speech generation tools are readily available. The use of synthetic speech has caused financial fraud, impersonation of people, and misinformation to spread. For this reason forensic methods that can detect synthetic speech have been proposed. Existing methods often overfit on one dataset and their performance reduces substantially in practical scenarios such as detecting synthetic speech shared on social platforms. In this paper we propose, Patched Spectrogram Synthetic Speech Detection Transformer (PS3DT), a synthetic speech detector that converts a time domain speech signal to a mel-spectrogram and processes it in patches using a transformer neural network. We evaluate the detection performance of PS3DT on ASVspoof2019 dataset. Our experiments show that PS3DT performs well on ASVspoof2019 dataset compared to other approaches using spectrogram for synthetic speech detection. We also investigate generalization performance of PS3DT on In-the-Wild dataset. PS3DT generalizes well than several existing methods on detecting synthetic speech from an out-of-distribution dataset. We also evaluate robustness of PS3DT to detect telephone quality synthetic speech and synthetic speech shared on social platforms (compressed speech). PS3DT is robust to compression and can detect telephone quality synthetic speech better than several existing methods., Comment: Accepted as long oral paper at ICMLA 2023