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In this paper, we study the annealed ferromagnetic $q$-state Potts model on sparse rank-1 random graphs, where vertices are equipped with a vertex weight, and the probability of an edge is proportional to the product of the vertex weights. In an annealed system, we take the average on both numerator and denominator of the ratio defining the Boltzmann-Gibbs measure of the Potts model. We show that the thermodynamic limit of the pressure per particle exists for rather general vertex weights. In the infinite-variance weight case, we show that the critical temperature equals infinity. For finite-variance weights, we show that, under a rather general condition, the phase transition is {\em first order} for all $q\geq 3$. However, we cannot generally show that the discontinuity of the order parameter is {\em unique}. We prove this uniqueness under a reasonable condition that holds for various distributions, including uniform, gamma, log-normal, Rayleigh and Pareto distributions. Further, we show that the first-order phase transition {\em persists} even for some small positive external field. In the rather relevant case of Pareto distributions with power-law exponent $\tau$, remarkably, the phase transition is first order when $\tau\geq 4$, but not necessarily when the weights have an infinite third-moment, i.e., when $\tau\in(3,4)$. More precisely, the phase transition is second order for $\tau\in (3,\tau(q)]$, while it is first order when $\tau>\tau(q)$, where we give an explicit equation that $\tau(q)$ solves., Comment: 60 pages, 3 figures

In this paper, we consider the optimized implementation of Multi Controlled Toffoli (MCT) using the Clifford $+$ T gate sets. While there are several recent works in this direction, here we explicitly quantify the trade-off (with concrete formulae) between the Toffoli depth (this means the depth using the classical 2-controlled Toffoli) of the $n$-controlled Toffoli (hereform we will tell $n$-MCT) and the number of clean ancilla qubits. Additionally, we achieve a reduced Toffoli depth (and consequently, T-depth), which is an extension of the technique introduced by Khattar et al. (2024). In terms of a negative result, we first show that using such conditionally clean ancilla techniques, Toffoli depth can never achieve exactly $\ceil{\log_2 n}$, though it remains of the same order. This highlights the limitation of the techniques exploiting conditionally clean ancilla [Nie et al., 2024, Khattar et al., 2024]. Then we prove that, in a more general setup, the T-Depth in the Clifford + T decomposition, via Toffoli gates, is lower bounded by $\ceil{\log_2 n}$, and this bound is achieved following the complete binary tree structure. Since the ($2$-controlled) Toffoli gate can further be decomposed using Clifford $+$ T, various methodologies are explored too in this regard for trade-off related implications., Comment: 13 pages, 12 figures

We used a supervised machine learning algorithm (probabilistic random forest) to classify ~130 million sources in the VISTA Survey of the Magellanic Clouds (VMC). We used multi-wavelength photometry from optical to far-infrared as features to be trained on, and spectra of Active Galactic Nuclei (AGN), galaxies and a range of stellar classes including from new observations with the Southern African Large Telescope (SALT) and SAAO 1.9m telescope. We also retain a label for sources that remain unknown. This yielded average classifier accuracies of ~79% (SMC) and ~87% (LMC). Restricting to the 56,696,719 sources with class probabilities (P$_{class}$) > 80% yields accuracies of ~90% (SMC) and ~98% (LMC). After removing sources classed as 'Unknown', we classify a total of 707,939 (SMC) and 397,899 (LMC) sources, including > 77,600 extragalactic sources behind the Magellanic Clouds. The extragalactic sources are distributed evenly across the field, whereas the Magellanic sources concentrate at the centres of the Clouds, and both concentrate in optical/IR colour-colour/magnitude diagrams as expected. We also test these classifications using independent datasets, finding that, as expected, the majority of X-ray sources are classified as AGN (554/883) and the majority of radio sources are classed as AGN (1756/2694) or galaxies (659/2694), where the relative AGN-galaxy proportions vary substantially with radio flux density. We have found: > 49,500 hitherto unknown AGN candidates, likely including more AGN dust dominated sources which are in a critical phase of their evolution; > 26,500 new galaxy candidates and > 2800 new Young Stellar Object (YSO) candidates., Comment: MNRAS accepted

The Einstein Probe (EP) is an interdisciplinary mission of time-domain and X-ray astronomy. Equipped with a wide-field lobster-eye X-ray focusing imager, EP will discover cosmic X-ray transients and monitor the X-ray variability of known sources in 0.5-4 keV, at a combination of detecting sensitivity and cadence that is not accessible to the previous and current wide-field monitoring missions. EP can perform quick characterisation of transients or outbursts with a Wolter-I X-ray telescope onboard. In this paper, the science objectives of the Einstein Probe mission are presented. EP is expected to enlarge the sample of previously known or predicted but rare types of transients with a wide range of timescales. Among them, fast extragalactic transients will be surveyed systematically in soft X-rays, which include {\gamma}-ray bursts and their variants, supernova shock breakouts, and the predicted X-ray transients associated with binary neutron star mergers. EP will detect X-ray tidal disruption events and outbursts from active galactic nuclei, possibly at an early phase of the flares for some. EP will monitor the variability and outbursts of X-rays from white dwarfs, neutron stars and black holes in our and neighbouring galaxies at flux levels fainter than those detectable by the current instruments, and is expected to discover new objects. A large sample of stellar X-ray flares will also be detected and characterised. In the era of multi-messenger astronomy, EP has the potential of detecting the possible X-ray counterparts of gravitational wave events, neutrino sources, and ultra-high energy {\gamma}-ray and cosmic ray sources. EP is expected to help advance the studies of extreme objects/phenomena and their underlying physical processes revealed in the dynamic X-ray universe, as well as studies in other areas of X-ray astronomy., Comment: 67 pages, 24 figures, accepted for publication in SCIENCE CHINA Physics, Mechanics & Astronomy

eROSITA is the soft X-ray instrument aboard the Spectrum Roentgen Gamma (SRG) satellite that is most sensitive in the energy range between 0.2 and 2.3 keV. Between December 2019 and December 2021, eROSITA completed four all-sky surveys producing all-sky X-ray source lists and sky maps of unprecedented depth. In the energy range between 0.2 keV and 1 keV, we detected about 38,000 sources with a hardness ratio below -0.94, covering a small sample of known white dwarfs found with eROSITA in the dataset to which the German eROSITA consortium has rights (half sky). 264 of these soft sources have a probability of more than 90 % to be a white dwarf. This is more than the 175 white dwarfs ROSAT found in the whole sky. Here we present the results of a pilot study to increase the sensitivity of eROSITA for soft sources by extending the detection threshold down to 0.1 keV. First tests with dedicated sky regions are promising.

Health outcomes depend on complex environmental and sociodemographic factors whose effects change over location and time. Only recently has fine-grained spatial and temporal data become available to study these effects, namely the MEDSAT dataset of English health, environmental, and sociodemographic information. Leveraging this new resource, we use a variety of variable importance techniques to robustly identify the most informative predictors across multiple health outcomes. We then develop an interpretable machine learning framework based on Generalized Additive Models (GAMs) and Multiscale Geographically Weighted Regression (MGWR) to analyze both local and global spatial dependencies of each variable on various health outcomes. Our findings identify NO2 as a global predictor for asthma, hypertension, and anxiety, alongside other outcome-specific predictors related to occupation, marriage, and vegetation. Regional analyses reveal local variations with air pollution and solar radiation, with notable shifts during COVID. This comprehensive approach provides actionable insights for addressing health disparities, and advocates for the integration of interpretable machine learning in public health., Comment: AAAI

We present two Device Independent Quantum Random Number Generator (DI-QRNG) protocols using two self-testing methodologies in Preparation \& Measure (P\&M) scenario. These two methodologies are the variants of two well-known non-local games, namely, CHSH and pseudo-telepathy games, in P\&M framework. We exploit them as distinguishers in black-box settings to differentiate the classical and the quantum paradigms and hence to certify the Device Independence. The first self-test was proposed by Tavakoli et al. (Phys. Rev. A, 2018). We show that this is actually a P\&M variant of the CHSH game. Then based on this self-test, we design our first DI-QRNG protocol. We also propose a new self-testing methodology, which is the first of its kind that is reducible from pseudo-telepathy game in P\&M framework. Based on this new self-test, we design our second DI-QRNG protocol.

Each monomial ideal over a polynomial ring admits a free resolution which has the structure of a DG-algebra, namely, the Taylor resolution. A pivot resolution of a monomial ideal, which we introduce, is a resolution that is always shorter than the Taylor resolution (unless the Taylor resolution is as short as possible) but still retains a DG-algebra structure. We study the basic properties of this family of resolutions including a characterization of when the construction is minimal. Following the work of Sobieska, we use the explicit nature of pivot resolutions to give formulae for the Eisenbud-Shamash construction of a free resolution of a given monomial ideal over complete intersections., Comment: are welcome. 18 pages. Dedicated to J\"urgen Herzog

Detecting a pulsar associated with a supernova remnant (SNR) and/or pulsar wind nebula (PWN) is crucial for unraveling its formation history and pulsar wind dynamics, yet the association with a radio pulsar is observed only in a small fraction of known SNRs and PWNe. In this paper, we report the discovery of a young pulsar J1631$-$4722, associated with the Galactic SNR G336.7$+$0.5 using Murriyang, CSIRO's Parkes radio telescope. It is also potentially associated with a PWN revealed by the Rapid ASKAP (Australian Square Kilometre Array Pathfinder) Continuum Survey (RACS). This 118 ms pulsar has a high dispersion measure of 873 $\mathrm{pc\,cm^{-3}}$ and a rotation measure of $-$1004 $\mathrm{rad\,m^{-2}}$. Because of such a high DM, at frequencies below 2 GHz, the pulse profile is significantly scattered, making it effectively undetectable in previous pulsar surveys at $\sim$1.4 GHz. Follow-up observations yield a period derivative of $\dot{P} = 3.6 \times 10^{-15}$, implying a characteristic age, $\tau_{c} = 33\,$kyr, and spin-down luminosity, $\dot{E} = 1.3\times10^{36}\,$erg$\,s^{-1}$. PSR$\,$J1631$-$4722, with its high spin-down luminosity and potential link to a PWN, stands out as a promising source of the high-energy $\gamma$-ray emission observed in the region.

A new giant outburst of the Be X-ray binary RX J0520.5-6932 was detected and subsequently observed with several space-borne and ground-based instruments. This study presents a comprehensive analysis of the optical and X-ray data, focusing on the spectral and timing characteristics of selected X-ray observations. A joint fit of spectra from simultaneous observations performed by the X-ray telescope (XRT) on the Neil Gehrels Swift Observatory (Swift) and Nuclear Spectroscopic Telescope ARray (NuSTAR) provides broadband parameter constraints, including a cyclotron resonant scattering feature (CRSF) at 32.2(+0.8/-0.7) keV with no significant energy change since 2014, and a weaker Fe line. Independent spectral analyses of observations by the Lobster Eye Imager for Astronomy (LEIA), Einstein Probe (EP), Swift-XRT, and NuSTAR demonstrate the consistency of parameters across different bands. Luminosity variations during the current outburst were tracked. The light curve of the Optical Gravitational Lensing Experiment (OGLE) aligns with the X-ray data in both 2014 and 2024. Spin evolution over 10 years is studied after adding Fermi Gamma-ray Burst Monitor (GBM) data, improving the orbital parameters, with an estimated orbital period of 24.39 days, slightly differing from OGLE data. Despite intrinsic spin-up during outbursts, a spin-down of ~0.04s over 10.3 years is suggested. For the new outburst, the pulse profiles indicate a complicated energy-dependent shape, with decreases around 15 keV and 25 keV in the pulsed fraction, a first for an extragalactic source. Phase-resolved NuSTAR data indicate variations in parameters such as flux, photon index, and CRSF energy with rotation phase., Comment: 17 pages, 15 figures, accepted for publication in MNRAS

Given the advancements in conversational artificial intelligence, the evaluation and assessment of Large Language Models (LLMs) play a crucial role in ensuring optimal performance across various conversational tasks. In this paper, we present a comprehensive study that thoroughly evaluates the capabilities and limitations of five prevalent LLMs: Llama, OPT, Falcon, Alpaca, and MPT. The study encompasses various conversational tasks, including reservation, empathetic response generation, mental health and legal counseling, persuasion, and negotiation. To conduct the evaluation, an extensive test setup is employed, utilizing multiple evaluation criteria that span from automatic to human evaluation. This includes using generic and task-specific metrics to gauge the LMs' performance accurately. From our evaluation, no single model emerges as universally optimal for all tasks. Instead, their performance varies significantly depending on the specific requirements of each task. While some models excel in certain tasks, they may demonstrate comparatively poorer performance in others. These findings emphasize the importance of considering task-specific requirements and characteristics when selecting the most suitable LM for conversational applications., Comment: 39 pages, 12 tables

The eROSITA instrument on board Spectrum-Roentgen-Gamma has completed four scans of the X-ray sky, leading to the detection of almost one million X-ray sources in eRASS1 only, including multiple new X-ray binary candidates. We report on analysis of the X-ray binary 1eRASS J085039.9-421151, using a ~55\,ks long NuSTAR observation, following its detection in each eROSITA scan. Analysis of the eROSITA and NuSTAR X-ray spectra in combination with X-shooter data of the optical counterpart provide evidence of an X-ray binary with a red supergiant (RSG) companion, confirming previous results, although we determine a cooler spectral type of M2-3, owing to the presence of TiO bands in the optical and near infrared spectra. The X-ray spectrum is well-described by an absorbed power law with a high energy cutoff typically applied for accreting high mass X-ray binaries. In addition, we detect a strong fluorescent neutral iron line with an equivalent width of ~700\,eV and an absorption edge, the latter indicating strong absorption by a partial covering component. It is unclear if the partial absorber is ionised. There is no significant evidence of a cyclotron resonant scattering feature. We do not detect any pulsations in the NuSTAR lightcurves, possibly on account of a large spin period that goes undetected due to insufficient statistics at low frequencies or potentially large absorption that causes pulsations to be smeared out. Even so, the low persistent luminosity, the spectral parameters observed (photon index, $\Gamma<1.0$), and the minuscule likelihood of detection of RSG-black hole systems, suggest that the compact object is a neutron star., Comment: 17 pages, 11 figures, accepted by A&A

A striking example of the need to accurately capture states of double-excitation character in molecules is seen in predicting photo-induced dynamics in small polyenes. Due to the coupling of electronic and nuclear motions,the dark 2$^1$Ag state, known to have double-excitation character, can be reached after an initial photo-excitation to the bright $^1$Bu state via crossings of their potential energy surfaces. However, the shapes of the surfaces are so poorly captured by most electronic structure methods, that the crossing is missed or substantially mis-located. We demonstrate that the frequency-dependent kernel of dressed TDDFT beyond Tamm-Dancoff successfully captures the curve-crossing, providing an energy surface close to the highly accurate but more expensive $\delta$-CR-EOMCC(2,3) benchmark reference. This, along with its accurate prediction of the excitation character of the state makes dressed TDDFT a practical and accurate route to electronic structure quantities needed in modeling ultrafast dynamics in molecules.

We report the discovery of a peculiar X-ray transient, EP240408a, by Einstein Probe (EP) and follow-up studies made with EP, Swift, NICER, GROND, ATCA and other ground-based multi-wavelength telescopes. The new transient was first detected with Wide-field X-ray Telescope (WXT) on board EP on April 8th, 2024, manifested in an intense yet brief X-ray flare lasting for 12 seconds. The flare reached a peak flux of 3.9x10^(-9) erg/cm2/s in 0.5-4 keV, about 300 times brighter than the underlying X-ray emission detected throughout the observation. Rapid and more precise follow-up observations by EP/FXT, Swift and NICER confirmed the finding of this new transient. Its X-ray spectrum is non-thermal in 0.5-10 keV, with a power-law photon index varying within 1.8-2.5. The X-ray light curve shows a plateau lasting for about 4 days, followed by a steep decay till becoming undetectable about 10 days after the initial detection. Based on its temporal property and constraints from previous EP observations, an unusual timescale in the range of 7-23 days is found for EP240408a, which is intermediate between the commonly found fast and long-term transients. No counterparts have been found in optical and near-infrared, with the earliest observation at 17 hours after the initial X-ray detection, suggestive of intrinsically weak emission in these bands. We demonstrate that the remarkable properties of EP240408a are inconsistent with any of the transient types known so far, by comparison with, in particular, jetted tidal disruption events, gamma-ray bursts, X-ray binaries and fast blue optical transients. The nature of EP240408a thus remains an enigma. We suggest that EP240408a may represent a new type of transients with intermediate timescales of the order of about 10 days. The detection and follow-ups of more of such objects are essential for revealing their origin., Comment: 25 pages, 11 figures

We consider a susceptible-infected-susceptible (SIS) epidemic model in which a large group of individuals decide whether to adopt partially effective protection without being aware of their individual infection status. Each individual receives a signal which conveys noisy information about its infection state, and then decides its action to maximize its expected utility computed using its posterior probability of being infected conditioned on the received signal. We first derive the static signal which minimizes the infection level at the stationary Nash equilibrium under suitable assumptions. We then formulate an optimal control problem to determine the optimal dynamic signal that minimizes the aggregate infection level along the solution trajectory. We compare the performance of the dynamic signaling scheme with the optimal static signaling scheme, and illustrate the advantage of the former through numerical simulations.

The collective motion of epithelial cells is a fundamental biological process which plays a significant role in embryogenesis, wound healing and tumor metastasis. While it has been broadly investigated for over a decade both in vivo and in vitro, large scale coherent flocking phases remain underexplored and have so far been mostly described as fluid. In this work, we report a mode of large-scale collective motion for different epithelial cell types in vitro with distinctive new features. By tracking individual cells, we show that cells move over long time scales coherently not as a fluid, but as a polar elastic solid with negligible cell rearrangements. Our analysis reveals that this solid flocking phase exhibits signatures of long-range polar order, unprecedented in cellular systems, such as scale-free correlations, anomalously large density fluctuations, and shear waves. Based on a general theory of active polar solids, we argue that these features result from massless Goldstone modes, which, in contrast to polar fluids where they are generic, require the decoupling of global rotations of the polarity and in-plane elastic deformations in polar solids. We theoretically show and consistently observe in experiments that the fluctuations of elastic deformations diverge for large system size in such polar active solid phases, leading eventually to rupture and thus potentially loss of tissue integrity at large scales.

Determination of molecular energetics and properties is one of the core challenges in the near-term quantum computing. To this end, hybrid quantum-classical algorithms are preferred for Noisy Intermediate Scale Quantum (NISQ) architectures. The Projective Quantum Eigensolver (PQE) is one such algorithms that optimizes the parameters of the chemistry-inspired unitary coupled cluster (UCC) ansatz using a conventional coupled cluster-like residual minimization. Such a strategy involves the projection of the Schrodinger equation on to linearly independent basis towards the parameter optimization, restricting the ansatz is solely defined in terms of the excitation operators. This warrants the inclusion of high-rank operators for strongly correlated systems, leading to increased utilization of quantum resources. In this manuscript, we develop a methodology for determining the generalized operators in terms of a closed form residual equations in the PQE framework that can be efficiently implemented in a quantum computer with manageable quantum resources. Such a strategy requires the removal of the underlying redundancy in high-rank excited determinants, generated due to the presence of the generalized operators in the ansatz, by projecting them on to an internally contracted lower dimensional manifold. With the application on several molecular systems, we have demonstrated our ansatz achieves similar accuracy to the (disentangled) UCC with singles, doubles and triples (SDT) ansatz, while utilizing an order of magnitude fewer quantum gates. Furthermore, when simulated under stochastic Gaussian noise or depolarizing hardware noise, our method shows significantly improved noise resilience compared to the other members of PQE family and the state-of-the-art variational quantum eigensolver., Comment: 10 pages, 4 figures

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

Visualizing high-dimensional datasets through a generalized embedding has been a challenge for a long time. Several methods have shown up for the same, but still, they have not been able to generate a generalized embedding, which not only can reveal the hidden patterns present in the data but also generate realistic high-dimensional samples from it. Motivated by this aspect, in this study, a novel generative model, called G-NeuroDAVIS, has been developed, which is capable of visualizing high-dimensional data through a generalized embedding, and thereby generating new samples. The model leverages advanced generative techniques to produce high-quality embedding that captures the underlying structure of the data more effectively than existing methods. G-NeuroDAVIS can be trained in both supervised and unsupervised settings. We rigorously evaluated our model through a series of experiments, demonstrating superior performance in classification tasks, which highlights the robustness of the learned representations. Furthermore, the conditional sample generation capability of the model has been described through qualitative assessments, revealing a marked improvement in generating realistic and diverse samples. G-NeuroDAVIS has outperformed the Variational Autoencoder (VAE) significantly in multiple key aspects, including embedding quality, classification performance, and sample generation capability. These results underscore the potential of our generative model to serve as a powerful tool in various applications requiring high-quality data generation and representation learning., Comment: 15 pages, 8 figures

Self-supervised learning has developed rapidly over the last decade and has been applied in many areas of computer vision. Decorrelation-based self-supervised pretraining has shown great promise among non-contrastive algorithms, yielding performance at par with supervised and contrastive self-supervised baselines. In this work, we explore the decorrelation-based paradigm of self-supervised learning and apply the same to learning disentangled stroke features for writer identification. Here we propose a modified formulation of the decorrelation-based framework named SWIS which was proposed for signature verification by standardizing the features along each dimension on top of the existing framework. We show that the proposed framework outperforms the contemporary self-supervised learning framework on the writer identification benchmark and also outperforms several supervised methods as well. To the best of our knowledge, this work is the first of its kind to apply self-supervised learning for learning representations for writer verification tasks.

Due to the rapid advancement of quantum technology, the traditional established classical cryptographic protocols are no longer secure. To make the world quantum safe, different quantum protocols have been taken into account. Quantum Key Distribution (QKD) protocols are one of them where two legitimate parties can securely communicate by upholding the quantum principles. Out of various QKD protocols, Coherent One Way (COW) protocol is one of the most famous protocol because of its ease of hardware deployment, and resilience nature towards PNS attack. In this initiative, we have implemented the original version of two pulses COW QKD protocol and a very recent variant of it, three pulses COW (Phys. Rev. Applied 18, 064053 Published 19 December 2022), in Optisystem v21.1. We demonstrate the encoding as well as decoding portions of the protocols under both noisy and noiseless scenario considering different weather conditions. Finally, we report a comparative study amongst the protocols under wired (optical fibre) and wireless (free space) environments to check the proper integrity of transmission. The simulation results provide us an overview regarding the practical implementation of the protocols under different weather conditions.

Growing experimental evidence shows that cell monolayers can induce long-lived perturbations to their environment, akin to footprints, which in turn influence the global dynamics of the system. Inspired by these observations, we propose a comprehensive theoretical framework to describe systems where an active field dynamically interacts with a non-advected footprint field, deposited by the active field. We derive the corresponding general hydrodynamics for both polar and nematic fields. Our findings reveal that the dynamic coupling to a footprint field induces remarkable effects absent in classical active hydrodynamics, such as symmetry-dependent modifications to the isotropic-ordered transition, which may manifest as either second-order or first-order, alterations in spontaneous flow transitions, potentially resulting in oscillating flows and rotating fields, and initial condition-dependent aging dynamics characterized by long-lived transient states. Our results suggest that footprint deposition could be a key mechanism determining the dynamical phases of cellular systems, or more generally active systems inducing long-lived perturbations to their environment.

Let $(R,\mathfrak{m})$ be a commutative Noetherian local ring, and suppose $R$ is Cohen-Macaulay with canonical module $\omega_R$. We develop new tools for analyzing questions involving annihilators of several homologically defined objects. Using these, we study a generalization introduced by Dao-Kobayashi-Takahashi of the famous Tachikawa conjecture, asking in particular whether the vanishing of $\mathfrak{m} \operatorname{Ext}_R^i(\omega_R,R)$ should force the trace ideal of $\omega_R$ to contain $\mathfrak{m}$, i.e., for $R$ to be nearly Gorenstein. We show this question has an affirmative answer for numerical semigroup rings of minimal multiplicity, but that the answer is negative in general. Our proofs involve a technical analysis of homogeneous ideals in a numerical semigroup ring, and exploit the behavior of Ulrich modules in this setting., Comment: 24 Pages

We study the roughening of interfaces in phase-separated active suspensions on substrates. At large length and timescales, we show that the interfacial dynamics belongs to the |q|KPZ universality class discussed in Besse et al. Phys. Rev. Lett. 130, 187102 (2023). This holds despite the presence of long-ranged fluid flows. At early times, instead, the roughening exponents are the same as those in the presence of a momentum-conserving fluid. Surprisingly, when the effect of substrate friction can be ignored, the interface becomes random beyond a de Gennes-Taupin lengthscale which depends on the interfacial tension.

Classical novae are known to demonstrate a supersoft X-ray source (SSS) state following outbursts, which is associated with residual thermonuclear burning on the white dwarf (WD) surface. During its all-sky survey (eRASS1), the eROSITA telescope onboard the Spectrum-Roentgen-Gamma observatory discovered a bright new SSS, whose position is consistent with the known classical nova AT 2018bej in the Large Magellanic Cloud. There were two eROSITA spectra obtained during eRASS1 and eRASS2 monitoring epochs and one XMM-Newton grating spectrum close to the eRASS1 epoch. We aim to describe the eROSITA and XMM-Newton spectra of AT 2018bej with our local thermodynamic equilibrium (LTE) atmosphere models. We focused on the evolution of the hot WD properties between the eRASS1 and eRASS2 epochs, especially on the change of the carbon abundance. A grid of LTE model atmosphere spectra were calculated for different values of the effective temperature (from $T_{\rm eff}= 525$ to $700\,\rm kK$), surface gravity (six values) and chemical composition with five different values of carbon and nitrogen abundances. Both eRASS1 and XMM $0.3-0.6$ keV spectral analyses yield a temperature of the WD of $T_{\rm eff}{\sim}\,600\, \rm kK$ and a WD radius of $8000-8700\,\rm km$. Simultaneous fitting of the eROSITA spectra for two epochs (eRASS1 and eRASS2) with a common WD mass parameter demonstrates a decrease in $T_{\rm eff}$ accompanied by an increase in the WD radius and a decrease in the carbon abundance. However, these changes are marginal and coincide within errors. The derived WD mass is estimated to be $1.05-1.15\, M_\odot$. We traced a minor evolution of the source on a half-year timescale accompanied by a decrease in carbon abundance and concluded that LTE model atmospheres can be used to analyse the available X-ray spectra of classical novae during their SSS stage., Comment: 12 pages, 16 figures, accepted for publication to A&A

Recent quantum algorithms pertaining to electronic structure theory primarily focus on threshold-based dynamic construction of ansatz by selectively including important many-body operators. These methods can be made systematically more accurate by tuning the threshold to include more number of operators into the ansatz. However, such improvements come at the cost of rapid proliferation of the circuit depth, especially for highly correlated molecular systems. In this work, we address this issue by the development of a novel theoretical framework that relies on the segregation of an ansatz into a dynamically selected core principal component, which is, by construction adiabatically decoupled from the remaining operators. This enables us to perform computations involving the principal component using extremely shallow-depth circuits whereas, the effect of the remaining auxiliary component is folded into the energy function via a cost-efficient non-iterative correction, ensuring the requisite accuracy. We propose a formalism that analytically predicts the auxiliary parameters from the principal ones, followed by a suite of non-iterative auxiliary subspace correction techniques with different levels of sophistication. The auxiliary subspace corrections incur no additional quantum resources, yet complement an inadequately expressive core of the ansatz to recover significant amount of electronic correlations. We have numerically validated the resource efficiency and accuracy of our formalism with a number of strongly correlated molecular systems., Comment: 14 pages, 5 figures

We report new radio timing solutions from a three-year observing campaign conducted with the MeerKAT and Murriyang telescopes for nine Small Magellanic Cloud pulsars, increasing the number of characterised rotation-powered extragalactic pulsars by 40 per cent. We can infer from our determined parameters that the pulsars are seemingly all isolated, that six are ordinary pulsars, and that three of the recent MeerKAT discoveries have a young characteristic age of under 100 kyr and have undergone a spin-up glitch. Two of the sources, PSRs J0040$-$7337 and J0048$-$7317, are energetic young pulsars with spin-down luminosities of the order of 10$^{36}$ erg s$^{-1}$. They both experienced a large glitch, with a change in frequency of about 30 $\mu$Hz, and a frequency derivative change of order $-10^{-14}$ Hz s$^{-1}$. These glitches, the inferred glitch rate, and the properties of these pulsars (including potentially high inter-glitch braking indices) suggest these neutron stars might be Vela-like repeating glitchers and should be closely monitored in the future. The position and energetics of PSR J0048$-$7317 confirm it is powering a new Pulsar Wind Nebula (PWN) detected as a radio continuum source; and similarly the association of PSR J0040$-$7337 with the PWN of Supernova Remnant (SNR) DEM S5 (for which we present a new Chandra image) is strengthened. Finally, PSR J0040$-$7335 is also contained within the same SNR but is a chance superposition. It has also been seen to glitch with a change of frequency of $10^{-2}$ $\mu$Hz. This work more than doubles the characterised population of SMC radio pulsars., Comment: 20 pages, 13 figures, accepted for publication in Monthly Notices of the Royal Astronomical Society

On May 27 2024, the Wide-field X-ray Telescope onboard the Einstein Probe (EP) mission detected enhanced X-ray emission from a new transient source in the Small Magellanic Cloud (SMC) during its commissioning phase. Prompt follow-up with the EP Follow-up X-ray Telescope, the Swift X-ray Telescope and NICER have revealed a very soft, thermally emitting source (kT$\sim$0.1 keV at the outburst peak) with an X-ray luminosity of $L\sim4\times10^{38}$ erg s$^{-1}$, labelled EP J005245.1-722843. This super-soft outburst faded very quickly in a week time. Several emission lines and absorption edges were present in the X-ray spectrum, including deep Nitrogen (0.67 keV) and Oxygen (0.87 keV) absorption edges. The X-ray emission resembles the SSS phase of typical nova outbursts from an accreting white dwarf (WD) in a binary system, despite the X-ray source being historically associated with an O9-B0e massive star exhibiting a 17.55 days periodicity in the optical band. The discovery of this super-soft outburst suggests that EP J005245.1-722843 is a BeWD X-ray binary: an elusive evolutionary stage where two main-sequence massive stars have undergone a common envelope phase and experienced at least two episodes of mass transfer. In addition, the very short duration of the outburst and the presence of Ne features hint at a rather massive, i.e., close to the Chandrasekhar limit, Ne-O WD in the system., Comment: 9 pages, 5 figures; accepted for publication in ApJL

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

Automatic Sign Language (SL) recognition is an important task in the computer vision community. To build a robust SL recognition system, we need a considerable amount of data which is lacking particularly in Indian sign language (ISL). In this paper, we introduce a large-scale isolated ISL dataset and a novel SL recognition model based on skeleton graph structure. The dataset covers 2002 daily used common words in the deaf community recorded by 20 (10 male and 10 female) deaf adult signers (contains 40033 videos). We propose a SL recognition model namely Hierarchical Windowed Graph Attention Network (HWGAT) by utilizing the human upper body skeleton graph. The HWGAT tries to capture distinctive motions by giving attention to different body parts induced by the human skeleton graph. The utility of the proposed dataset and the usefulness of our model are evaluated through extensive experiments. We pre-trained the proposed model on the presented dataset and fine-tuned it across different sign language datasets further boosting the performance of 1.10, 0.46, 0.78, and 6.84 percentage points on INCLUDE, LSA64, AUTSL and WLASL respectively compared to the existing state-of-the-art keypoints-based models.

A vaccine passport serves as documentary proof, providing passport holders with greater freedom while roaming around during pandemics. It confirms vaccination against certain infectious diseases like COVID-19, Ebola, and flu. The key challenges faced by the digital vaccine passport system include passport forgery, unauthorized data access, and inaccurate information input by vaccination centers. Privacy concerns also need to be addressed to ensure that the user's personal identification information (PII) is not compromised. Additionally, it is necessary to track vaccine vials or doses to verify their authenticity, prevent misuse and illegal sales, as well as to restrict the illicit distribution of vaccines. To address these challenges, we propose a Blockchain-Enabled Secure Vaccine Passport System, leveraging the power of smart contracts. Our solution integrates off-chain and on-chain cryptographic computations, facilitating secure communication among various entities. We have utilized the InterPlanetary File System (IPFS) to store encrypted vaccine passports of citizens securely. Our prototype is built on the Ethereum platform, with smart contracts deployed on the Sepolia Test network, allowing for performance evaluation and validation of the system's effectiveness. By combining IPFS as a distributed data storage platform and Ethereum as a blockchain platform, our solution paves the way for secure, efficient, and globally interoperable vaccine passport management, supporting comprehensive vaccination initiatives worldwide.

We extend the DeePMD neural network architecture to predict electronic structure properties necessary to perform non-adiabatic dynamics simulations. While learning the excited state energies and forces follows a straightforward extension of the DeePMD approach for ground-state energies and forces, how to learn the map between the non-adiabatic coupling vectors (NACV) and the local chemical environment descriptors of DeePMD is less trivial. Most implementations of machine-learning-based non-adiabatic dynamics inherently approximate the NACVs, with an underlying assumption that the energy-difference-scaled NACVs are conservative fields. We overcome this approximation, implementing the method recently introduced by Richardson [J. Chem. Phys. 158 011102 (2023)], which learns the symmetric dyad of the energy-difference-scaled NACV. The efficiency and accuracy of our neural network architecture is demonstrated through the example of the methaniminium cation CH$_2$NH$_2^+$., Comment: Presentation of the 3 challenges in learning NACVs was clarified, with references added. A supplementary material section was added to clarify some points made in main text about methods' properties, together with more tests and comparisons of the different methods. Main results of these comparisons are summarized in main text with new figures. Ancillary files with code and data were added

We report on two epochs of simultaneous near-infrared (IR) and X-ray observations with a sub-second time resolution of the low mass X-ray binary black hole candidate Swift J1753.5--0127 during its long 2005--2016 outburst. Data were collected strictly simultaneously with VLT/ISAAC (K$_{S}$ band, 2.2 $\mu m$) and RXTE (2-15 keV) or \textit{XMM-Newton} (0.7-10 keV). A clear correlation between the X-ray and the IR variable emission is found during both epochs but with very different properties. In the first epoch, the near-IR variability leads the X-ray by $ \sim 130 \, ms$. This is the opposite of what is usually observed in similar systems. The correlation is more complex in the second epoch, with both anti-correlation and correlations at negative and positive lags. Frequency-resolved Fourier analysis allows us to identify two main components in the complex structure of the phase lags: the first component, characterised by a few seconds near-IR lag at low frequencies, is consistent with a combination of disc reprocessing and a magnetised hot flow; the second component is identified at high frequencies by a near-IR lag of $\approx$0.7 s. Given the similarities of this second component with the well-known constant optical/near-IR jet lag observed in other black hole transients, we tentatively interpret this feature as a signature of a longer-than-usual jet lag. We discuss the possible implications of measuring such a long jet lag in a radio-quiet black hole transient., Comment: 10 pages, 7 figures, accepted for publication in A&A

This study presents a comprehensive approach to optimizing inventory management under stochastic demand by leveraging Monte Carlo Simulation (MCS) with grid search and Bayesian optimization. By using a business case of historical demand data and through the comparison of periodic review (p, Q) and continuous review (r, Q) inventory policies, it demonstrates that the (r, Q) policy significantly increases expected profit by dynamically managing inventory levels based on daily demand and lead time considerations. The integration of random and conditional sampling techniques highlights critical periods of high demand, providing deeper insights into demand patterns. While conditional sampling reduces execution time, it yields slightly lower profits compared to random sampling. Though Bayesian optimization marginally outperforms grid search in identifying optimal reorder quantities and points, however, given the stochastic nature of the algorithm, this can change with multiple runs. This study accentuates the effectiveness of advanced simulation and optimization techniques in addressing complex inventory challenges, ultimately supporting more informed and profitable inventory management decisions. The simulation model and optimization framework are open-source and written in Python, promoting transparency and enabling other researchers and practitioners to replicate and build upon this work. This contributes to the advancement of knowledge and the development of more effective inventory management solutions.

The gut-brain axis is the communication link between the gut and the brain. Although it is known that the gut-brain axis plays a pivotal role in homeostasis, its overall mechanism is still not known. However, for neural synapses, classical molecular communication is described by the formation of ligand-receptor complexes, which leads to the opening of ion channels. Moreover, there are some conditions that need to be fulfilled before the opening of the ion channel. In this study, we consider the gut-brain axis, where neurotransmitters diffuse through the synaptic cleft, considering molecular communication. On the vagus nerve (VN) membrane, i.e., the post-synaptic membrane of the synapse, it undergoes a quantum communication (QC), which initiates the opening of the ion channel, thus initiating the communication signal from the gut to the brain. It evolves a new paradigm of communication approach, Molecular Quantum (MolQ) communication. Based on the QC model, we theoretically analyze the output states, and QC is simulated considering the incoming neurotransmitter's concentration and validated by analyzing the entropy and the mutual information of the input, i.e., neurotransmitter's concentration, and output, i.e., ion channel opening., Comment: 9 pages

In this paper we report our investigations on visibility with respect to the Kobayashi distance and its applications, with a special focus on planar domains. We prove that totally disconnected subsets of the boundary are removable in the context of visibility. We also show that a domain in $\mathbb{C}^n$ is a local weak visibility domain if and only if it is a weak visibility domain. The above holds also for visibility. Along the way, we prove an intrinsic localization result for the Kobayashi distance. Moreover, we observe some interesting consequences of weak visibility; for example, weak visibility implies compactness of the end topology of the closure of the domain. For planar domains: (i) We provide examples of visibility domains that are not locally Goldilocks at any boundary point. (ii) We provide certain general conditions on planar domains that yield the continuous extension of conformal maps, generalizing the Carath\'{e}odory extension theorem. Our conditions are quite general and assume very little regularity of the boundary. We demonstrate this through examples. (iii) We also provide conditions for the homeomorphic extension of biholomorphic maps up to the boundary. (iv) We prove that a hyperbolic, simply connected domain possesses the visibility property if and only if its boundary is locally connected. This leads us to reformulate the MLC conjecture in terms of visibility. (v) We provide a characterization of visibility for a large class of planar domains including certain uncountably connected domains., Comment: 66 pages. Comments are welcome

The coexistence of seemingly mutually exclusive properties such as ferromagnetism, ferroelectricity and metallicity in atomically thin materials is the requirement of the hour in electronics as the Moore's law faces an impending end. Only a few 2D multiferroic materials have been predicted/realized so far. The polar metals with simultaneous presence of polarity and conductivity are also equally rare. Here, we predict, based on first-principles calculations that an Eu-substituted rare-earth halide GdI$_2$ monolayer showcases ferromagnetism, ferroelasticity while being polar and a fully spin-polarized semi-metal at the same time. The ferroelasticity and polarity are shown to be coupled making it possible to switch the polar direction using external mechanical stress. Further, it is observed that, an application of biaxial tensile strain of $5\%$ causes the spin easy-axis to shift from out-of-plane to in-plane direction. Thus spin easy axis gets coupled with the direction of polarization in the strained monolayer making the switching of magnetization also possible using external strain. Simultaneous coexistence and coupling of the ferroic orders in a metallic 2D material makes the Eu substituted GdI$_2$ monolayer an incredibly rare material for nano-electronics and spintronics applications., Comment: 7 pages, 5 figures

We identify the upper large deviation probability for the number of edges in scale-free geometric random graph models as the space volume goes to infinity. Our result covers the models of scale-free percolation, the Boolean model with heavy-tailed radius distribution, and the age-dependent random connection model. In all these cases the mechanism behind the large deviation is based on a condensation effect. Loosely speaking, the mechanism randomly selects a finite number of vertices and increases their power, so that they connect to a macroscopic number of vertices in the graph, while the other vertices retain a degree close to their expectation and thus make no more than the expected contribution to the large deviation event. We verify this intuition by means of limit theorems for the empirical distributions of degrees and edge-lengths under the conditioning. We observe that at large finite volumes, the edge-length distribution splits into a bulk and travelling wave part of asymptotically positive proportions., Comment: 45 pages, one figure

The weak-field limit of Einstein--Cartan (EC) relativity is studied. The equations of EC theory are rewritten such that they formally resemble those of Einstein General Relativity (EGR); this allows ideas from post-Newtonian theory to be imported without essential change. The equations of motion are then written both at first post-Newtonian (1PN) order and at 1.5PN order. EC theory's 1PN equations of motion are found to be those of a micropolar/Cosserat elastic medium, along with a decoupled evolution equation for non-classical, spin-related fields. It seems that a necessary condition for these results to hold is that one chooses the non-classical fields to scale with the speed of light in a certain empirically reasonable way. Finally, the 1.5PN equations give greater insight into the coupling between energy-momentum and spin within slowly moving, weakly gravitating matter. Specifically, the weakly relativistic modifications to Cosserat theory involve a gravitational torque and an augmentation of the gravitational force due to a `dynamic mass moment density' with an accompanying `dynamic mass moment density flux', and new forms of linear momentum density captured by a `dynamic mass density flux' and a `dynamic momentum density'.

The sensitivity of the MeerKAT radio interferometer is an opportunity to probe deeper into the population of rare and faint extragalactic pulsars. The TRAPUM (TRAnsients and PUlsars with MeerKAT) collaboration has conducted a radio-domain search for accelerated pulsars and transients in the Small Magellanic Cloud (SMC). This partially targeted survey, performed at L-band (856-1712 MHz) with the core array of the MeerKAT telescope in 2-h integrations, is twice as sensitive as the latest SMC radio pulsar survey. We report the discovery of seven new SMC pulsars, doubling this galaxy's radio pulsar population and increasing the total extragalactic population by nearly a quarter. We also carried out a search for accelerated millisecond pulsars in the SMC Globular Cluster NGC 121 using the full array of MeerKAT. This improved the previous upper limit on pulsed radio emission from this cluster by a factor of six. Our discoveries reveal the first radio pulsar-PWN systems in the SMC, with only one such system previously known outside our galaxy (the "Crab pulsar twin" in the Large Magellanic Cloud, PSR J0540$-$6919). We associate the 59 ms pulsar discovery PSR J0040$-$7337, now the fastest spinning radio pulsar in the SMC, with the bow-shock Pulsar Wind Nebula (PWN) of Supernova Remnant DEM S5. We also present a new young pulsar with a 79 ms period, PSR J0048$-$7317, in a PWN recently discovered in a MeerKAT radio continuum image. Using the multi-beam capability of MeerKAT, we localised our pulsar discoveries, and two previous Murriyang discoveries, to a positional uncertainty of a few arcseconds., Comment: 32 pages, 14 figures, 10 tables. Accepted for publication in Monthly Notices of the Royal Astronomical Society

Multi-wavelength polarimetry and radio observations of Swift J1727.8-1613 at the beginning of its recent 2023 outburst suggested the presence of a bright compact jet aligned in the north-south direction, which could not be confirmed without high angular resolution images. Using the Very Long Baseline Array and the Long Baseline Array, we imaged Swift J1727.8-1613, during the hard/hard-intermediate state, revealing a bright core and a large, two-sided, asymmetrical, resolved jet. The jet extends in the north-south direction, at a position angle of $-0.60\pm0.07\deg$ East of North. At 8.4 GHz, the entire resolved jet structure is $\sim110 (d/2.7\,\text{kpc})/\sin i$ AU long, with the southern approaching jet extending $\sim80 (d/2.7\,\text{kpc})/\sin i$ AU from the core, where $d$ is the distance to the source and $i$ is the inclination of the jet axis to the line of sight. These images reveal the most resolved continuous X-ray binary jet, and possibly the most physically extended continuous X-ray binary jet ever observed. Based on the brightness ratio of the approaching and receding jets, we put a lower limit on the intrinsic jet speed of $\beta\geq0.27$ and an upper limit on the jet inclination of $i\leq74\deg$. In our first observation we also detected a rapidly fading discrete jet knot $66.89\pm0.04$ mas south of the core, with a proper motion of $0.66\pm0.05$ mas hour$^{-1}$, which we interpret as the result of a downstream internal shock or a jet-ISM interaction, as opposed to a transient relativistic jet launched at the beginning of the outburst., Comment: Accepted in ApJL

Building operations consume 30% of total power consumption and contribute 26% of global power-related emissions. Therefore, monitoring, and early detection of anomalies at the meter level are essential for residential and commercial buildings. This work investigates both supervised and unsupervised approaches and introduces a dynamic anomaly detection system. The system introduces a supervised Light Gradient Boosting machine and an unsupervised autoencoder with a dynamic threshold. This system is designed to provide real-time detection of anomalies at the meter level. The proposed dynamical system comes with a dynamic threshold based on the Mahalanobis distance and moving averages. This approach allows the system to adapt to changes in the data distribution over time. The effectiveness of the proposed system is evaluated using real-life power consumption data collected from smart metering systems. This empirical testing ensures that the system's performance is validated under real-world conditions. By detecting unusual data movements and providing early warnings, the proposed system contributes significantly to visual analytics and decision science. Early detection of anomalies enables timely troubleshooting, preventing financial losses and potential disasters such as fire incidents.

Electronic coherences are key to understanding and controlling photo-induced molecular transformations. We identify a crucial quantum-mechanical feature of electron-nuclear correlation, the projected nuclear quantum momenta, essential to capture the correct coherence behavior. In simulations, we show that, unlike traditional trajectory-based schemes, exact-factorization-based methods approximate these correlation terms, and correctly capture electronic coherences in a range of situations, including their spatial dependence, an important aspect that influences subsequent electron dynamics and that is becoming accessible in more experiments.

Using properties of diffusion according to a quantum heat kernel constructed as an expectation over classical heat kernels on $S^1$, we probe the non-manifold-like nature of quantized space in a model of (1+1)-dimensional quantum gravity. By computing the mean squared displacement of a diffusing particle, we find that diffusion is anomalous, behaving similarly to that on a porous substrate, network, or fractal over short distances. The walk dimension of the path for a particle diffusing in quantized space is calculated to have an infimum of 4, rising to arbitrarily large values depending on a parameter labeling the choice of factor ordering in the quantum Hamiltonian for our model and figuring in the asymptotic behavior of the wavefunction used to construct the quantum heat kernel. Additionally, we derive an expansion for return probability of a diffusing particle, whose modifications from the classical power-series form depend on the factor-ordering parameter., Comment: Accepted for publication in Nuclear Physics B

Chiral active materials display odd dynamical effects in both their elastic and viscous responses. We show that the most symmetric mesophase with two-dimensional odd elasticity in three dimensions is chiral, polar and columnar, with two-dimensional translational order in the plane perpendicular to the columns and no elastic restoring force for their relative sliding. We derive its hydrodynamic equations from those of a chiral active variant of model H. The most striking prediction of the odd dynamics is two distinct types of column oscillation whose frequencies do not vanish at zero wavenumber. In addition, activity leads to a buckling instability coming from the generic force-dipole active stress analogous to the mechanical Helfrich-Hurault instability in passive materials, while the chiral torque-dipole active stress fundamentally modifies the instability by the selection of helical column undulations., Comment: replaces arXiv:2306.03695; new results

Quasi-stellar objects (QSOs) are a basis for an absolute reference system for astrometric studies. There is a need for creating such system behind nearby galaxies, to facilitate the measuring of the proper motions of these galaxies. However, the foreground contamination from the galaxies themselves is a problem for the QSO identification. We search for new QSOs behind both Magellanic Clouds, the Magellanic Bridge, and the Magellanic Stream. We identify QSO candidates with a combination of near-infrared colors and variability criteria from the public ESO Visual and Infrared Survey Telescope for Astronomy (VISTA) Magellanic Clouds (VMC) survey. We confirm their nature from broad emission lines with low-resolution optical spectroscopy. We confirmed the QSO nature of 136 objects. They are distributed as follows: 12 behind the LMC, 37 behind the SMC, 63 behind the Bridge, and 24 behind the Stream. The QSOs span a redshift range from z~0.1 to z~2.9. A comparison of our quasar selection with the Quaia quasar catalog, based on Gaia low-resolution spectra, yields a selection and confirmation success rate of 6-19%, depending on whether the quality of the photometry, the magnitude ranges and the colors are considered. Our candidate list is rather incomplete, but the objects in it are likely to be confirmed as quasars with ~90% probability. Finally, we report a list of 3609 objects across the entire VMC survey that match our color and variability selection criteria; only 1249 of them have Gaia counterparts. Our combined infrared color and variability criteria for QSO selection prove to be efficient - ~90% of the observed candidates are bona fide QSOs and allow to generate a list of new high-probability quasar candidates., Comment: 20 pages, 9 figures, 5 tables