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A visually rich document (VRD) utilizes visual features along with linguistic cues to disseminate information. Training a custom extractor that identifies named entities from a document requires a large number of instances of the target document type annotated at textual and visual modalities. This is an expensive bottleneck in enterprise scenarios, where we want to train custom extractors for thousands of different document types in a scalable way. Pre-training an extractor model on unlabeled instances of the target document type, followed by a fine-tuning step on human-labeled instances does not work in these scenarios, as it surpasses the maximum allowable training time allocated for the extractor. We address this scenario by proposing a Noise-Aware Training method or NAT in this paper. Instead of acquiring expensive human-labeled documents, NAT utilizes weakly labeled documents to train an extractor in a scalable way. To avoid degradation in the model's quality due to noisy, weakly labeled samples, NAT estimates the confidence of each training sample and incorporates it as uncertainty measure during training. We train multiple state-of-the-art extractor models using NAT. Experiments on a number of publicly available and in-house datasets show that NAT-trained models are not only robust in performance -- it outperforms a transfer-learning baseline by up to 6% in terms of macro-F1 score, but it is also more label-efficient -- it reduces the amount of human-effort required to obtain comparable performance by up to 73%.

Recent advancements in Generative Artificial Intelligence, particularly in the realm of Large Language Models (LLMs) and Large Vision Language Models (LVLMs), have enabled the prospect of leveraging cognitive planners within robotic systems. This work focuses on solving the object goal navigation problem by mimicking human cognition to attend, perceive and store task specific information and generate plans with the same. We introduce a comprehensive framework capable of exploring an unfamiliar environment in search of an object by leveraging the capabilities of Large Language Models(LLMs) and Large Vision Language Models (LVLMs) in understanding the underlying semantics of our world. A challenging task in using LLMs to generate high level sub-goals is to efficiently represent the environment around the robot. We propose to use a 3D scene modular representation, with semantically rich descriptions of the object, to provide the LLM with task relevant information. But providing the LLM with a mass of contextual information (rich 3D scene semantic representation), can lead to redundant and inefficient plans. We propose to use an LLM based pruner that leverages the capabilities of in-context learning to prune out irrelevant goal specific information.

In the era of generative artificial intelligence and the Internet of Things, while there is explosive growth in the volume of data and the associated need for processing, analysis, and storage, several new challenges are faced in identifying spurious and fake information and protecting the privacy of sensitive data. This has led to an increasing demand for more robust and resilient schemes for authentication, integrity protection, encryption, non-repudiation, and privacy-preservation of data. The chapters in this book present some of the state-of-the-art research works in the field of cryptography and security in computing and communications., Comment: Published by IntechOpen, London Uk in Nov 2023, the book contains 8 chapters spanning over 131 pages. arXiv admin note: text overlap with arXiv:2307.02055, arXiv:2304.00258

This study focuses on a combined analysis of various available inputs to constrain the parameter spaces of a simplified dark matter (SDM) model featuring a spin-0 mediator and fermionic dark matter (DM). The spin-0 mediator interacts with standard model (SM) fermions, SM gauge bosons, and DM. We constrain the parameter spaces of different relevant couplings, DM mass, and the mediator mass, using the data from flavour-changing charged and neutral current processes, CKM matrices, $W$ and $Z$-pole observables, DM relic density, direct and indirect detection bounds. We have calculated bounds on the couplings from both separate and simultaneous analyses of the mentioned processes. We identify correlated parameter spaces for all the relevant parameters which include the couplings and the masses. For the DM and mediator masses, we have scanned the region between 100 GeV and 1000 GeV. Using our results, we have obtained bounds on the couplings of possible higher dimensional operators from which we can formulate our SDM., Comment: 55 pages, 23 figures

We conducted a study on the X-ray polarization properties of MCG-5-23-16 by analyzing long-term monitoring data from {\it NuSTAR} jointly with {\it IXPE} observations made in May and November 2022. The re-analysis of {\it IXPE} data gives model-dependent polarization degree, PD (\%) = $1.08\pm0.66$ in the energy band $2-8$ keV. The model-independent analysis of PD poses an upper limit of $\leq3.8$ ($1\sigma$ level) for the same energy band. The observed upper limit of PD, along with broadband spectral analysis ($2-79$ keV) using an accretion-ejection based model, allowed us to derive the corona geometry (i.e. radius and height) and the accretion disk inclination ($\sim 33^\circ$). Additional {\it NuSTAR} observations were also analyzed to gain insights into the accretion flow properties of the source and to estimate the expected polarization during those epochs with PD $\sim 4.3\%$. The radius and height of the corona varies between $28.2\pm3.1 - 39.8\pm4.6$ r$_s$ and $14.3\pm1.7-21.4\pm1.9$ r$_s$ respectively, with a mass outflow rate from the corona measuring $0.14\pm0.03-0.2\pm0.03$ Eddington rate ($\dot m_{\rm Edd}$). The spectral analysis further provided an estimate for the mass of the central black hole $\sim 2\times 10^7$ M$_\odot$ and the velocity of the outflowing gas $\sim 0.16-0.19c$. A comparative broadband spectral study using reflection-based models estimates the disk inclination between $\sim 31^\circ\pm8^\circ-45^\circ\pm7^\circ$, and yields an expected PD of 3.4-6.0\%. The expected PD measured using accretion-ejection and reflection models is less compared to the expected PD measured for a given disk inclination of $45^\circ$. Our modeling of the disk-corona-outflows and polarization connection can be extended and validated with data from the recently launched \textit{XPoSat}, India's first X-ray Polarimeter Satellite, offering potential applications to other sources., Comment: 12 pages, 5 figures, 6 tables, in press

Financial market like the price of stock, share, gold, oil, mutual funds are affected by the news and posts on social media. In this work deep learning based models are proposed to predict the trend of financial market based on NLP analysis of the twitter handles of leaders of different fields. There are many models available to predict financial market based on only the historical data of the financial component but combining historical data with news and posts of the social media like Twitter is the main objective of the present work. Substantial improvement is shown in the result. The main features of the present work are: a) proposing completely generalized algorithm which is able to generate models for any twitter handle and any financial component, b) predicting the time window for a tweets effect on a stock price c) analyzing the effect of multiple twitter handles for predicting the trend. A detailed survey is done to find out the latest work in recent years in the similar field, find the research gap, and collect the required data for analysis and prediction. State-of-the-art algorithm is proposed and complete implementation with environment is given. An insightful trend of the result improvement considering the NLP analysis of twitter data on financial market components is shown. The Indian and USA financial markets are explored in the present work where as other markets can be taken in future. The socio-economic impact of the present work is discussed in conclusion., Comment: 20 pages original research

We study the 4-body angular distribution for $\Lambda_b \to \Lambda_c^{+}(\to \Lambda \pi^{+})\ell^- \bar{\nu}$ decays and find out the analytical expressions for various asymmetric and angular observables in the Standard Model and the new physics scenarios and compared them with the literature. Using the available inputs from the lattice, we have predicted the values with uncertainties of all these observables in the Standard Model. Considering the new physics effects in $b\to c\tau^-\bar{\nu}_{\tau}$ transitions, we have constrained the new Wilson coefficients of the one operator and two operator scenarios from the available data on these decays. The two-operator scenario with scalar-pseudoscalar and tensor quark current provides the most plausible solution to the current data. Also, we have tested the new physics sensitivities (one or two-operator scenarios) of the different angular observables in $\Lambda_b \to \Lambda_c (\to \Lambda \pi^{+}) \tau^- \bar{\nu}_{\tau}$ decays and found correlations among them. We have noted a few one or two-operator scenarios to which some of these observables are sensitive. By measuring these observables, it will be possible to distinguish these effects from one another., Comment: 42 pages, 56 figures, 15 tables

Machine learning potentials (MLPs) are widely applied as an efficient alternative way to represent potential energy surfaces (PES) in many chemical simulations. The MLPs are often evaluated with the root-mean-square errors on the test set drawn from the same distribution as the training data. Here, we systematically investigate the relationship between such test errors and the simulation accuracy with MLPs on an example of a full-dimensional, global PES for the glycine amino acid. Our results show that the errors in the test set do not unambiguously reflect the MLP performance in different simulation tasks such as relative conformer energies, barriers, vibrational levels, and zero-point vibrational energies. We also offer an easily accessible solution for improving the MLP quality in a simulation-oriented manner, yielding the most precise relative conformer energies and barriers. This solution also passed the stringent test by the diffusion Monte Carlo simulations.

We introduce an innovative method to explore gravity's quantum aspects using a novel theoretical framework. Our model delves into gravity-induced entanglement (GIE) while sidestepping classical communication limitations imposed by the LOCC principle. Specifically, we connect a non-relativistic two-dimensional quantum oscillator detector with linearly polarized gravitational waves (GWs), leveraging the quantum properties inherent in GWs to observe GIE within the oscillator's quantum states. Because our model adheres to both the ``event" and the ``system" localities, the detected GIE serves as a robust indicator of gravity's quantum nature. Detecting this entanglement via gravitational wave detectors could corroborate gravity's quantization and unveil crucial properties of its sources., Comment: A few comments added, to appear in Phys. Lett. B

Dynamics is central to living systems. In the last two decades, experiments have revealed that the dynamics in diverse biological systems - from intracellular cytoplasm to cellular and organismal aggregates - are remarkably similar to that in dense systems of inanimate particles in equilibrium. They show a glass transition from a solid-like jammed state to a fluid-like flowing state, where a moderate change in control parameter leads to an enormous variation in relaxation time. However, biological systems have crucial differences from the equilibrium systems: the former have activity that drives them out of equilibrium, novel control parameters, and enormous levels of complexity. These active systems showing glassy dynamics are known as active glasses. The field is at the interface of physics and biology, freely borrowing tools from both disciplines and promising novel, fascinating discoveries. We review the experiments that started this field, simulations that have been instrumental for insights, and theories that have helped unify diverse phenomena, reveal correlations, and make novel quantitative predictions. We discuss the primary characteristics that define a glassy system. For most concepts, we first discuss the known equilibrium scenario and then present the key aspects when activity is introduced. We end the article with a discussion of the challenges in the field and possible future directions., Comment: 25 pages, 13 figures

Current large language models have dangerous capabilities, which are likely to become more problematic in the future. Activation steering techniques can be used to reduce risks from these capabilities. In this paper, we investigate the efficacy of activation steering for broad skills and multiple behaviours. First, by comparing the effects of reducing performance on general coding ability and Python-specific ability, we find that steering broader skills is competitive to steering narrower skills. Second, we steer models to become more or less myopic and wealth-seeking, among other behaviours. In our experiments, combining steering vectors for multiple different behaviours into one steering vector is largely unsuccessful. On the other hand, injecting individual steering vectors at different places in a model simultaneously is promising., Comment: Code is available at: https://github.com/TeunvdWeij/extending-activation-addition

Rehabilitation therapies are widely employed to assist people with motor impairments in regaining control over their affected body parts. Nevertheless, factors such as fatigue and low self-efficacy can hinder patient compliance during extensive rehabilitation processes. Utilizing hand redirection in virtual reality (VR) enables patients to accomplish seemingly more challenging tasks, thereby bolstering their motivation and confidence. While previous research has investigated user experience and hand redirection among able-bodied people, its effects on motor-impaired people remain unexplored. In this paper, we present a VR rehabilitation application that harnesses hand redirection. Through a user study and semi-structured interviews, we examine the impact of hand redirection on the rehabilitation experiences of people with motor impairments and its potential to enhance their motivation for upper limb rehabilitation. Our findings suggest that patients are not sensitive to hand movement inconsistency, and the majority express interest in incorporating hand redirection into future long-term VR rehabilitation programs., Comment: Proceedings of the CHI Conference on Human Factors in Computing Systems (CHI '24), May 11--16, 2024, Honolulu, HI, USA

The discovery of a significantly large anomalous Hall effect in the chiral antiferromagnetic system - Mn$_3$Ge - indicates that the Weyl points are widely separated in phase space and positioned near the Fermi surface. In order to examine the effects of Fe substitution in Mn$_3$Ge on the presence and location of the Weyl points, we synthesized (Mn$_{1-\alpha}$Fe$_{\alpha})$$_3$Ge ($\alpha=0-0.30$) compounds. The anomalous Hall effect was observed in compounds up to $\alpha=0.22$, but only within the temperature range where the magnetic structure remains the same as the Mn$_3$Ge. Additionally, positive longitudinal magnetoconductance and planar Hall effect were detected within the same temperature and doping range. These findings strongly suggest the existence of Weyl points in (Mn$_{1-\alpha}$Fe$_{\alpha})$$_3$Ge ($\alpha=0-0.22$) compounds. Further, we observed that with an increase in Fe doping fraction, there is a significant reduction in the magnitude of anomalous Hall conductivity, planar Hall effect, and positive longitudinal magnetoconductance, indicating that the Weyl points move further away from the Fermi surface. Consequently, it can be concluded that suitable dopants in the parent Weyl semimetals have the potential to tune the properties of Weyl points and the resulting anomalous electrical transport effects., Comment: Accepted in New Journal of Physics (03/2024)

Among the various candidates for dark matter (DM), ultralight vector DM can be probed by laser interferometric gravitational wave detectors through the measurement of oscillating length changes in the arm cavities. In this context, KAGRA has a unique feature due to differing compositions of its mirrors, enhancing the signal of vector DM in the length change in the auxiliary channels. Here we present the result of a search for $U(1)_{B-L}$ gauge boson DM using the KAGRA data from auxiliary length channels during the first joint observation run together with GEO600. By applying our search pipeline, which takes into account the stochastic nature of ultralight DM, upper bounds on the coupling strength between the $U(1)_{B-L}$ gauge boson and ordinary matter are obtained for a range of DM masses. While our constraints are less stringent than those derived from previous experiments, this study demonstrates the applicability of our method to the lower-mass vector DM search, which is made difficult in this measurement by the short observation time compared to the auto-correlation time scale of DM., Comment: 20 pages, 5 figures

Event-by-event fluctuations of the charged particle multiplicity are studied for a wide range of centralities for Au$-$Au collisions at $\sqrt{s_{NN}}$ = 200 GeV, Pb$-$Pb collisions at $\sqrt{s_{NN}}$ = 2.76 TeV and 5.02 TeV using the Pythia 8 Angantyr model. The centrality dependence of $\omega_{ch}$ observable, which quantifies the fluctuations in terms of scaled variance is studied for different pseudorapidity ranges and has been compared with those obtained from a simple participant superposition model. The $\omega_{ch}$ was found to be lower than the expectations from the participant model. The estimate would act like a baseline for current and future measurements of event-by-event fluctuations in the charged particle multiplicities in systems at LHC energies where no de-confined medium of quarks and gluons are formed.

Understanding and shaping the behaviour of Large Language Models (LLMs) is increasingly important as applications become more powerful and more frequently adopted. This paper introduces a machine unlearning method specifically designed for LLMs. We introduce a selective pruning method for LLMs that removes neurons based on their relative importance on a targeted capability compared to overall network performance. This approach is a compute- and data-efficient method for identifying and removing neurons that enable specific behaviours. Our findings reveal that both feed-forward and attention neurons in LLMs are specialized; that is, for specific tasks, certain neurons are more crucial than others. Code from all experiments is available at https://github.com/nickypro/selective-pruning

A new observable, $S_{T}$, is introduced in terms of the sum of the transverse momentum of charged particles ($\sum_{i} p_{T_{i}}$ ) produced in proton proton (p$-$p) collisions at LHC energies to probe the underlying events (UE). The UE are defined as those aspects of proton-proton collisions that are not attributed to the primary hard scattering process, but rather to the accompanying interactions of the rest of the proton. The conventional approach of studying underlying events is usually carried out by defining topological regions with respect to the leading particle in an event. The transverse region is generally sensitive to UE and various classifiers have been used to discriminate the extent of UE activity regions. The production of identified particles like $\pi^{\pm}$, $K^{\pm}$, p , $K_{S}^{0}$, and $\Lambda^{0}$ are studied in different ranges of transverse activity classifier in p$-$p collisions at $\sqrt{s} = 13 $ TeV using pQCD inspired PYTHIA 8 event generator. A comparative analysis of the identified particle spectra, mean multiplicity and mean transverse momentum has been carried out with respect to $S_{T}$ and the performance of this new observable is gauged by comparing the results with previously defined $R_{T}$ observable.

Human pose estimation (HPE) in the top-view using fisheye cameras presents a promising and innovative application domain. However, the availability of datasets capturing this viewpoint is extremely limited, especially those with high-quality 2D and 3D keypoint annotations. Addressing this gap, we leverage the capabilities of Neural Radiance Fields (NeRF) technique to establish a comprehensive pipeline for generating human pose datasets from existing 2D and 3D datasets, specifically tailored for the top-view fisheye perspective. Through this pipeline, we create a novel dataset NToP570K (NeRF-powered Top-view human Pose dataset for fisheye cameras with over 570 thousand images), and conduct an extensive evaluation of its efficacy in enhancing neural networks for 2D and 3D top-view human pose estimation. A pretrained ViTPose-B model achieves an improvement in AP of 33.3 % on our validation set for 2D HPE after finetuning on our training set. A similarly finetuned HybrIK-Transformer model gains 53.7 mm reduction in PA-MPJPE for 3D HPE on the validation set.

The negative parity states in 116Sn have been investigated in terms of octupole correlation. The same is probed by using the Indian National Gamma Array (INGA) facility at Variable Energy Cyclotron Centre, Kolkata using the reaction, 114Cd({\alpha},2n) 116Sn at 34 MeV energy. Three new {\gamma}-transitions relevant to the present investigation are reported and the spin-parities of the associated levels are assigned based on the DCO-ratios and polarisation measurements. The interband transitions between the positive parity ground band and the negative parity band are newly observed and the corresponding extracted ratio of transition probability, B(E1)/B(E2) indicated the existence of octupole correlation in these nuclei. The enhanced transition rates for E1 and E3 transitions between these opposite parity bands and corroboration of soft octupole deformation ultimately aid the onset of octupole excitation in this isotope., Comment: 14 Pages, 9 figures, 1 table, for referred journal publication

Large language models (LLMs) have demonstrated impressive performance on a number of natural language processing tasks, such as question answering and text summarization. However, their performance on sequence labeling tasks such as intent classification and slot filling (IC-SF), which is a central component in personal assistant systems, lags significantly behind discriminative models. Furthermore, there is a lack of substantive research on the robustness of LLMs to various perturbations in the input prompts. The contributions of this paper are three-fold. First, we show that fine-tuning sufficiently large LLMs can produce IC-SF performance comparable to discriminative models. Next, we systematically analyze the performance deterioration of those fine-tuned models due to three distinct yet relevant types of input perturbations - oronyms, synonyms, and paraphrasing. Finally, we propose an efficient mitigation approach, Prompt Perturbation Consistency Learning (PPCL), which works by regularizing the divergence between losses from clean and perturbed samples. Our experiments demonstrate that PPCL can recover on average 59% and 69% of the performance drop for IC and SF tasks, respectively. Furthermore, PPCL beats the data augmentation approach while using ten times fewer augmented data samples.

Identifying methods to discover dual AGN has proven to be challenging. Several indirect tracers have been explored in the literature, including X/S-shaped radio morphologies and double-peaked (DP) emission lines in the optical spectra. However, the detection rates of confirmed dual AGN candidates from the individual methods remain extremely small. We search for binary black holes in a sample of six sources that exhibit both X-shaped radio morphology and DP emission lines using the VLBA. Three out of the six sources show dual VLBA compact components, making them strong candidates for binary black hole sources. In addition, we present deep uGMRT images revealing the exquisite details of the X-shaped wings in three sources. We present a detailed precession modeling analysis of these sources. The BH separations estimated from the simplistic geodetic precession model are incompatible with those estimated from emission line offsets and the VLBA separations. However, precession induced by a noncoplanar secondary black hole is a feasible mechanism for explaining the observed X-shaped radio morphologies and the black hole separations estimated from other methods. The black hole separations estimated from the double-peaked emission lines agree well with the VLBA compact component separations. Future multi-frequency VLBA observations will be critical in ruling out or confirming the binary black hole scenario in the three galaxies with dual component detections., Comment: Accepted for publication in MNRAS

We report the results of first ever spectro-polarimetric analyses of the Galactic ultra-luminous X-ray pulsar Swift J0243.6$+6124$ during the 2023 outburst using quasi-simultaneous {\it IXPE}, {\it NICER} and {\it NuSTAR} observations. A pulsation of period $\sim 9.79$ s is detected in {\it IXPE} and {\it NuSTAR} observations with pulse fractions (PFs) $\sim 18\%$ ($2-8$ keV) and $\sim 28\%$ ($3-78$ keV), respectively. Energy dependent study of the pulse profiles with {\it NuSTAR} indicates an increase in PF from $\sim 27\%$ ($3-10$ keV) to $\sim 50\%$ ($40-78$ keV). Further, epoch-dependent polarimetric measurements during the decay phase of the outburst confirm the detection of significant polarization, with the polarization degree (PD) and polarization angle (PA) ranging between $\sim 2 -3.1\%$ and $\sim8.6^{\circ}-10.8^{\circ}$, respectively, in the $2-8$ keV energy range. We also observe that the PD increases up to $\sim 4.8\%$ at higher energies ($\gtrsim 5$ keV) with dominating \texttt{bbodyrad} flux contribution ($1.5 \lesssim F_{\rm BB}/F_{\rm PL} \lesssim 3.4$) in the {\it IXPE} spectra. The phase-resolved polarimetric study yields PD as $\sim 1.7-3.1\%$ suggesting a marginal correlation with the pulse profiles. Moreover, the broad-band ($0.6-70$ keV) energy spectrum of combined {\it NICER} and {\it NuSTAR} observations is well described by the combination of \texttt{bbodyrad} and \texttt{cutoffpl} components with seed photon temperature ($kT_{\rm bb}$) $\sim 0.86 \pm 0.03$ keV and photon index ($\Gamma$) $\sim 0.98 \pm 0.01$. With the above findings, we infer that the observed `low' PD in Swift J0243.6$+6124$ is attributed possibly due to `vacuum resonance' effect between the overheated and relatively cooler regions of the neutron star boundary layer., Comment: 11 pages + Appendix, 6 figures, 3 tables, accepted for publication in The Astrophysical Journal Letters

Let $\left\{ \mathcal{F}_{n}\right\}_{n \in \mathbb{N}}$ be an infinite sequence of families of compact connected sets in $\mathbb{R}^{d}$. An infinite sequence of compact connected sets $\left\{ B_{n} \right\}_{n\in \mathbb{N}}$ is called heterochromatic sequence from $\left\{ \mathcal{F}_{n}\right\}_{n \in \mathbb{N}}$ if there exists an infinite sequence $\left\{ i_{n} \right\}_{n\in \mathbb{N}}$ of natural numbers satisfying the following two properties: (a) $\{i_{n}\}_{n\in \mathbb{N}}$ is a monotonically increasing sequence, and (b) for all $n \in \mathbb{N}$, we have $B_{n} \in \mathcal{F}_{i_n}$. We show that if every heterochromatic sequence from $\left\{ \mathcal{F}_{n}\right\}_{n \in \mathbb{N}}$ contains $d+1$ sets that can be pierced by a single hyperplane then there exists a finite collection $\mathcal{H}$ of hyperplanes from $\mathbb{R}^{d}$ that pierces all but finitely many families from $\left\{ \mathcal{F}_{n}\right\}_{n \in \mathbb{N}}$. As a direct consequence of our result, we get that if every countable subcollection from an infinite family $\mathcal{F}$ of compact connected sets in $\mathbb{R}^{d}$ contains $d+1$ sets that can be pierced by a single hyperplane then $\mathcal{F}$ can be pierced by finitely many hyperplanes. To establish the optimality of our result we show that, for all $d \in \mathbb{N}$, there exists an infinite sequence $\left\{ \mathcal{F}_{n}\right\}_{n \in \mathbb{N}}$ of families of compact connected sets satisfying the following two conditions: (1) for all $n \in \mathbb{N}$, $\mathcal{F}_{n}$ is not pierceable by finitely many hyperplanes, and (2) for any $m \in \mathbb{N}$ and every sequence $\left\{B_n\right\}_{n=m}^{\infty}$ of compact connected sets in $\mathbb{R}^d$, where $B_i\in\mathcal{F}_i$ for all $i \geq m$, there exists a hyperplane in $\mathbb{R}^d$ that pierces at least $d+1$ sets in the sequence., Comment: 23 pages, 7 figures

Decoding of Low-Density Parity Check (LDPC) codes can be viewed as a special case of XOR-SAT problems, for which low-computational complexity bit-flipping algorithms have been proposed in the literature. However, a performance gap exists between the bit-flipping LDPC decoding algorithms and the benchmark LDPC decoding algorithms, such as the Sum-Product Algorithm (SPA). In this paper, we propose an XOR-SAT solver using log-sum-exponential functions and demonstrate its advantages for LDPC decoding. This is then approximated using the Margin Propagation formulation to attain a low-complexity LDPC decoder. The proposed algorithm uses soft information to decide the bit-flips that maximize the number of parity check constraints satisfied over an optimization function. The proposed solver can achieve results that are within $0.1$dB of the Sum-Product Algorithm for the same number of code iterations. It is also at least 10x lesser than other Gradient-Descent Bit Flipping decoding algorithms, which are also bit-flipping algorithms based on optimization functions. The approximation using the Margin Propagation formulation does not require any multipliers, resulting in significantly lower computational complexity than other soft-decision Bit-Flipping LDPC decoders., Comment: 12 pages, 7 figures, Paper submitted to IEEE Transactions on Communications

We present a long-term X-ray study of a nearby Active Galactic Nucleus Mrk 6, utilizing observations from XMM-Newton, Suzaku, Swift and NuSTAR observatories, spanning 22 years from 2001 to 2022. From timing analysis, we estimated variance, normalized variance, and fractional rms amplitude in different energy bands.The temporal study shows fractional rms amplitude ($F_{\rm var}$) below $10\%$ for the shorter timescale $(\sim60 ~\rm ks)$ and above $20\%$ for the longer timescale ($\sim \rm weeks$ ). A complex correlation is observed between the soft $(0.5-3.0$ keV) and hard $(3.0-10.0$ keV) X-ray bands of different epochs of observations. This result prompts a detailed investigation through spectral analysis, employing various phenomenological and physical models on the X-ray spectra. Our analysis reveals a heterogeneous structure of the obscuring material surrounding Mrk 6. A partially ionized absorber exhibits a rapid change in location and extends up to the narrow line regions or torus. In contrast, another component, located far from the central engine, remained relatively stable. During the observation period, the source luminosity in the 3.0--10.0 keV range varies between $(3-15) \times10^{42}$ erg $\rm sec^{-1}$., Comment: 16 pages,6 figures,9 tables Accepted for publication in MNRAS

We have measured the spherically averaged bispectrum of the SDSS DR17 main galaxy sample, considering a volume-limited $[273\, \rm Mpc]^3$ data cube with mean galaxy number density $1.76 \times 10^{-3} \, {\rm Mpc}^{-3}$ and median redshift $0.093$. Our analysis considers $\sim 1.37 \times 10^{8}$ triangles, for which we have measured the binned bispectrum and analyzed its dependence on the size and shape of the triangle. It spans wavenumbers $k_1=(0.082-0.472)\,{\rm Mpc}^{-1}$ for equilateral triangles, and a smaller range of $k_1$ (the largest side) for triangles of other shapes. For all shapes, we find that the measured bispectrum is well modelled by a power law $A\big(k_1/1 Mpc^{-1}\big)^{n}$, where the best-fit values of $A$ and $n$ vary with the shape. The parameter $A$ is the minimum for equilateral triangles and increases as the shape is deformed to linear triangles where the two largest sides are nearly aligned, reaching its maximum value for squeezed triangles. The values of $n$ are all negative, $|n|$ is minimum $(3.31 \pm 0.17)$ for squeezed triangles, and $4.12 \pm 0.16$ for equilateral. We have also analyzed mock galaxy samples constructed from $\Lambda$CDM N-body simulations by applying a simple Eulerian bias prescription where the galaxies reside in regions where the smoothed density field exceeds a threshold. We find that the bispectrum from the mock samples with bias $b_1=1.2$ is in good agreement with the SDSS results., Comment: 27 pages, 12 figures, 2 tables, significantly revised, analysis for red and blue galaxies using SDSS data are included, accepted for publication in New Astronomy

In the evolving landscape of online communication, moderating hate speech (HS) presents an intricate challenge, compounded by the multimodal nature of digital content. This comprehensive survey delves into the recent strides in HS moderation, spotlighting the burgeoning role of large language models (LLMs) and large multimodal models (LMMs). Our exploration begins with a thorough analysis of current literature, revealing the nuanced interplay between textual, visual, and auditory elements in propagating HS. We uncover a notable trend towards integrating these modalities, primarily due to the complexity and subtlety with which HS is disseminated. A significant emphasis is placed on the advances facilitated by LLMs and LMMs, which have begun to redefine the boundaries of detection and moderation capabilities. We identify existing gaps in research, particularly in the context of underrepresented languages and cultures, and the need for solutions to handle low-resource settings. The survey concludes with a forward-looking perspective, outlining potential avenues for future research, including the exploration of novel AI methodologies, the ethical governance of AI in moderation, and the development of more nuanced, context-aware systems. This comprehensive overview aims to catalyze further research and foster a collaborative effort towards more sophisticated, responsible, and human-centric approaches to HS moderation in the digital era. WARNING: This paper contains offensive examples., Comment: Preprint; Under-Review

We present the results obtained from detailed X-ray timing and spectral studies of X-ray pulsar Swift J0243.6+6124 during its giant and normal X-ray outbursts between 2017 and 2023 observed by the Neutron star Interior Composition Explorer (NICER). We focused on the timing analysis of the normal outbursts. A distinct break is found in the power density spectra of the source. The corresponding break frequency and slope of power-laws around the break vary with luminosity, indicating the change in accretion dynamics with mass accretion rate. Interestingly, we detected quasi-periodic oscillations within a specific luminosity range, providing further insights into the underlying physical processes. We also studied the neutron star spin period evolution and a luminosity variation in pulse profile during the recent 2023 outburst. The spectral analysis was conducted comprehensively for the giant and all other normal outbursts. We identified a double transition at luminosities of $\approx$7.5$\times$10$^{37}$ and 2.1$\times$10$^{38}$ erg s$^{-1}$ in the evolution of continuum parameters like photon index and cutoff energy with luminosity. This indicates three distinct accretion modes experienced by the source mainly during the giant X-ray outburst. A soft blackbody component with a temperature of 0.08-0.7 keV is also detected in spectra. The observed temperature undergoes a discontinuous transition when the pulsar evolves from a sub- to super-Eddington state. Notably, in addition to an evolving 6-7 keV iron line complex, a 1 keV emission line was observed during the super-Eddington state of the source, implying the X-ray reflection from the accretion disc or outflow material., Comment: This paper is accepted now in Astrophysical journal

Many critical biological processes, like wound healing, require confluent cell monolayers/bulk tissues to transition from a jammed solid-like to a fluid-like state. Although numerical studies anticipate changes in the cell shape alone can lead to unjamming, experimental support for this prediction is not definitive because, in living systems, fluidization due to density changes cannot be ruled out. Additionally, a cell's ability to modulate its motility only compounds difficulties since even in assemblies of rigid active particles, changing the nature of self-propulsion has non-trivial effects on the dynamics. Here, we design and assemble a monolayer of synthetic cell-mimics and examine their collective behaviour. By systematically increasing the persistence time of self-propulsion, we discovered a cell shape-driven, density-independent, re-entrant jamming transition. Notably, we observed cell shape and shape variability were mutually constrained in the confluent limit and followed the same universal scaling as that observed in confluent epithelia. Dynamical heterogeneities, however, did not conform to this scaling, with the fast cells showing suppressed shape variability, which our simulations revealed is due to a transient confinement effect of these cells by their slower neighbors. Our experiments unequivocally establish a morphodynamic link, demonstrating that geometric constraints alone can dictate epithelial jamming/unjamming.

Motivated by the symmetry in the non-relativistic limit of anti-de Sitter geometry, we employ planar dynamical models featuring exotic (deformed) harmonic oscillators, presented through direct and indirect Lagrangian representations. The latter introduces Bateman dissipative oscillator system. Analyzing these dynamic systems with a first-order Lagrangian scheme, our phase-space-based approach utilizes the moment map components to reveal the underlying symmetry algebra. This obtained algebra, interpreted as an extended version of Newton-Hooke (NH) cosmological symmetry algebras, has the potential to cast an augmented non-relativistic shadow over the expanding universe, offering an insightful perspective on extended NH spacetime in 2+1 dimensions through our dynamical realizations.

Assessments of machine-learned (ML) potentials are an important aspect of the rapid development of this field. We recently reported an assessment of the linear-regression permutationally invariant polynomial (PIP) method for ethanol, using the widely used (revised) MD17 dataset. We demonstrated that the PIP approach outperformed numerous other methods, e.g., ANI, PhysNet, sGDML, p-KRR, with respect to precision and notably with respect to speed [Houston $et$ $al$., $J. Chem. Phys.$ 2022, 156, 044120.]. Here we extend this assessment to the 21-atom aspirin molecule, using the rMD17 dataset. Both energies and forces are used for training and the precision of several PIPs is examined for both. Normal mode frequencies, the methyl torsional potential, and 1d vibrational energies for an OH stretch are presented. Overall, we show that the PIPs approach outperforms other ML methods, including sGDML, ANI, GAP, PhysNet, and ACE, as reported by Kov\'acs $et$ $al.$ in $J. Chem. Theory$ $Comput.$ 2021, 17, 7696-7711.

Superlattices are materials created by the alternating growth of two chemically different materials. The direct consequence of creating a superlattice is the folding of the Brillouin zone which gives rise to additional electronic bands and phonon modes. This has been successfully exploited to achieve new transport and optical properties in semiconductor superlattices, for example. Here, we show that multiferroic BiFeO$_3$/LaFeO$_3$ superlattices are more than just periodic chemical stacking. Using transmission electron microscopy, X-ray diffraction and first-principles calculations, we demonstrate the existence of a new order of FeO$_6$ octahedra, with a period along the growth direction about twice that of the chemical supercell, i.e. a superorder. The effect of this new structural order on the lattice dynamics is studied with ultrafast optical pump-probe experiments. While a mode at 1.2 THz is attributed solely to the chemical modulation of the superlattice, the existence of another 0.7 THz mode seems to be explained only by a double Brillouin zone folding in agreement with the structural description. Our work shows that multiferroic BiFeO$_3$/LaFeO$_3$ superlattices can be used to tune the spectrum of coherent THz phonons, and potentially that of magnons or electromagnons.

We consider proper holomorphic maps of complements and differences of balls in complex euclidean space of dimension at least $2$. We prove that every proper map of ball complements gives a polynomial proper map of balls, and conversely, every polynomial proper map of balls whose norm goes to infinity at infinity is a proper map of ball complements. The case of ball differences is more complex and naturally leads to what we call rational $m$-fold sphere maps, that is, rational maps taking $m$ zero-centric spheres to $m$ zero-centric spheres. A proper map of the difference of zero-centric balls is automatically a rational $2$-fold sphere map. We show that a polynomial $m$-fold sphere map of degree $m$ or less is an $\infty$-fold sphere map, that is, a map that takes infinitely many (and hence every) zero-centric spheres to zero-centric spheres. Similarly, every rational $m$-fold sphere map of degree less than $m$ is an $\infty$-fold sphere map. We then show that $\infty$-fold sphere maps are up to a unitary transformation direct sums of a finite number of homogeneous sphere maps. We construct rational $m$-fold degree-$m$ sphere maps that do not take any other zero-centric sphere to a zero-centric sphere. In particular, every first-degree rational proper map of the difference of zero-centric balls is a unitary composed with an affine linear embedding; however, there exist nonpolynomial second-degree rational maps of a difference of balls., Comment: 21 pages, Theorem 1.1 is corrected, extraneous examples of Section 5 are removed

Low-temperature scanning probe microscopes (SPMs) are critical for the study of quantum materials and quantum information science. Due to the rising costs of helium, cryogen-free cryostats have become increasingly desirable. However, they typically suffer from comparatively worse vibrations than cryogen-based systems, necessitating the understanding and mitigation of vibrations for SPM applications. Here we demonstrate the construction of two cryogen-free dilution refrigerator SPMs with minimal modifications to the factory default and we systematically characterize their vibrational performance. We measure the absolute vibrations at the microscope stage with geophones, and use both microwave impedance microscopy and a scanning single electron transistor to independently measure tip-sample vibrations. Additionally, we implement customized filtering and thermal anchoring schemes, and characterize the cooling power at the scanning stage and the tip electron temperature. This work serves as a reference to researchers interested in cryogen-free SPMs, as such characterization is not standardized in the literature or available from manufacturers.

Language Processing systems such as Part-of-speech tagging, Named entity recognition, Machine translation, Speech recognition, and Language modeling (LM) are well-studied in high-resource languages. Nevertheless, research on these systems for several low-resource languages, including Bodo, Mizo, Nagamese, and others, is either yet to commence or is in its nascent stages. Language model plays a vital role in the downstream tasks of modern NLP. Extensive studies are carried out on LMs for high-resource languages. Nevertheless, languages such as Bodo, Rabha, and Mising continue to lack coverage. In this study, we first present BodoBERT, a language model for the Bodo language. To the best of our knowledge, this work is the first such effort to develop a language model for Bodo. Secondly, we present an ensemble DL-based POS tagging model for Bodo. The POS tagging model is based on combinations of BiLSTM with CRF and stacked embedding of BodoBERT with BytePairEmbeddings. We cover several language models in the experiment to see how well they work in POS tagging tasks. The best-performing model achieves an F1 score of 0.8041. A comparative experiment was also conducted on Assamese POS taggers, considering that the language is spoken in the same region as Bodo., Comment: Accepted to Natural Language Engineering

We present a formalism to detect genuine multipartite entanglement by considering projection map which is a positive but not completely positive map. Projection map has been motivated by the no-pancake theorem which repudiates the existence of a quantum operation that maps the Bloch sphere onto a disk along its equator. The not complete positivity feature of projection map is explored to investigate genuine multipartite entanglement in arbitrary N-qubit quantum systems. Our proposed framework can detect some important classes of genuinely entangled states in tripartite and quadripartite scenarios. We provide illustrative example to show the efficacy of our formalism to detect a class of tripartite PPT bound entangled states. Finally, we construct a suitable witness operator based on projection map to certify genuine tripartite entanglement, which is likely to be feasible experimentally., Comment: 11 pages, 5 figures, new results added

In this paper, we investigate the quantum entanglement induced by phase-space noncommutativity. Both the position-position and momentum-momentum noncommutativity are incorporated to study the entanglement properties of coordinate and momentum degrees of freedom under the shade of oscillators in noncommutative space. Exact solutions for the systems are obtained after the model is re-expressed in terms of canonical variables, by performing a particular Bopp's shift to the noncommuting degrees of freedom. It is shown that the bipartite Gaussian state for an isotropic oscillator is always separable. To extend our study for the time-dependent system, we allow arbitrary time dependency on parameters. The time-dependent isotropic oscillator is solved with the Lewis-Riesenfeld invariant method. It turns out that even for arbitrary time-dependent scenarios, the separability property does not alter. We extend our study to the anisotropic oscillator, which provides an entangled state even for time-independent parameters. The Wigner quasi-probability distribution is constructed for a bipartite Gaussian state. The noise matrix (covariance matrix) is explicitly studied with the help of Wigner distribution. Simon's separability criterion (generalized Peres-Horodecki criterion) has been employed to find the unique function of the (mass and frequency) parameters, for which the bipartite states are separable. In particular, we show that the mere inclusion of non-commutativity of phase-space is not sufficient to generate the entanglement, rather anisotropy is important at the same footing.

Recent proposals are emerging for the experimental detection of entanglement mediated by classical gravity, carrying significant theoretical and observational implications. In fact, the detection of gravitational waves (GWs) in LIGO provides an alternative laboratory for testing various gravity-related properties. By employing LIGO's arms as oscillators interacting with gravitational waves (GWs), our study demonstrates the potential for generating quantum entanglement between two mutually orthogonal modes of simple harmonic oscillators. Our findings reveal unique entanglement dynamics, including periodic "collapse and revival" influenced by GW oscillations, alongside a distinct "quantum memory effect." Effectively, each harmonic oscillator feels a temperature. We believe that these forecasts may hold significance towards both theoretically probing and experimentally verifying various properties of classical gravitational waves., Comment: Modified version, new results added, to appear in Phys. Lett. B

Exploring the molecular fragmentation dynamics induced by low-energy electrons offers compelling insights into the complex interplay between the projectile and target. In this study, we investigate the phenomenon of dissociative electron attachment to ethyl acetate. The recorded yields of various fragment anions within an incident electron energy range of 1 to 13 eV reveal a diverse array of products with six different mass numbers. Examples include (M$-$H)$^-$, CH$_3^-$, C$_2$H$_5$O$^-$, CH$_3$CO$^-$, CH$_2$CHO$^-$, and CH$_3$COO$^-$, formed through the fracture of single bonds. Interestingly, the generation of other fragments, such as HCCO$^-$, suggests a more intricate structural rearrangement of the nuclei, adding a layer of complexity to the observed dissociation dynamics.