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We investigate the exclusive rare semileptonic decays: $B(B_c)\to K(D_{(s)})l\bar{l}/\Sigma\nu_l\bar{\nu_l}$ ($l=\mu, \tau$) in the framework of relativistic independent quark (RIQ) model based on an average flavor independent confining potential in equally mixed scalar-vector harmonic form. The invariant weak form factors, parametrising the matrix elements between participating meson states are calculated in the parent meson rest frame. The momentum transfer dependence of the form factors is reliably determined in the whole accessible kinematical range: $q^2_{min}\leq 0\leq q^2_{max}$. Our predicted branching fractions for $B\to K\mu^+\mu^-/\tau^+\tau^-(\Sigma\nu_l\bar{\nu_l})$, $B_c\to D(D_s)\mu^+\mu^-$, $B_c\to D(D_s)\tau^+\tau^-$ and $B_c\to D(D_s)\Sigma\nu_l\bar{\nu_l}$, obtained in order of $10^{-7}(10^{-6})$, $10^{-9}(10^{-7})$, $10^{-9}(10^{-8})$ and $10^{-8}(10^{-7})$, respectively are in reasonable agreement with other Standard Model predictions and Lattice QCD results. The averaged values of the lepton polarization asymmetries for decay modes are obtained as $\langle P_L(B\to K\mu^+\mu^-)\rangle$=-0.97, $\langle P_L(B_c\to D_{(s)}\mu^+\mu^-)\rangle$=-0.972, $\langle P_L(B\to K\tau^+\tau^-)\rangle$=-0.224, $\langle P_L(B_c\to D\tau^+\tau^-)\rangle$=-0.275 and $\langle P_L(B_c\to D_s\tau^+\tau^-)\rangle$=-0.194., Comment: 34 pages, 16 figures, 8 tables

A deep learning based method with Convolutional Neural Network (CNN) algorithm is developed for simultaneous determination of the Elliptic Flow coefficient ($v_{2}$) and the Impact Parameter in Heavy-Ion Collisions at relativistic energies. The proposed CNN is trained on Pb$-$Pb collisions at $\sqrt{s_{NN}}$ = 5.02 TeV with minimum biased events simulated with the AMPT event generator. A total of twelve models were built on different input and output combinations and their performances were evaluated. The predictions of the CNN models were compared to the estimations of the simulated and experimental data. The deep learning model seems to preserve the centrality and $p_{T}$ dependence of $v_{2}$ at the LHC energy together with predicting successfully the impact parameter with low margins of error. This is the first time a CNN is built to predict both $v_{2}$ and the impact parameter simultaneously in heavy-ion system., Comment: First simultaneous estimate of elliptic flow and impact parameter using CNN

Reconfigurable intelligent surfaces (RIS) and index modulation (IM) represent key technologies for enabling reliable wireless communication with high energy efficiency. However, to fully take advantage of these technologies in practical deployments, comprehending the impact of the non-ideal nature of the underlying transceivers is paramount. In this context, this paper introduces two RIS-assisted IM communication models, in which the RIS is part of the transmitter and space-shift keying (SSK) is employed for IM, and assesses their performance in the presence of hardware impairments. In the first model, the RIS acts as a passive reflector only, reflecting the oncoming SSK modulated signal intelligently towards the desired receive diversity branch/antenna. The second model employs RIS as a transmitter, employing M-ary phase-shift keying for reflection phase modulation (RPM), and as a reflector for the incoming SSK modulated signal. Considering transmissions subjected to Nakagami-m fading, and a greedy detection rule at the receiver, the performance of both the system configurations is evaluated. Specifically, the pairwise probability of erroneous index detection and the probability of erroneous index detection are adopted as performance metrics, and their closed-form expressions are derived for the RIS-assisted SSK and RIS-assisted SSK-RPM system models. Monte-Carlo simulation studies are carried out to verify the analytical framework, and numerical results are presented to study the dependency of the error performance on the system parameters. The findings highlight the effect of hardware impairment on the performance of the communication system under study., Comment: 12 pages, 8 figures

The highly energetic particle medium formed in the ultrarelativistic heavy ion collision displays a notable difference in temperatures between its central and peripheral regions. This temperature gradient can generate an electric field within the medium, a phenomenon referred to as the Seebeck effect. We have estimated the Seebeck coefficient for a dense quark-gluon plasma medium by using the relativistic Boltzmann transport equation in the recently developed novel relaxation time approximation (RTA) model within the kinetic theory framework. This study explores the Seebeck coefficient of individual quark flavors as well as the entire partonic medium, with the emphasis on its dependence on the temperature and the chemical potential. Our observation indicates that, for given current quark masses, the magnitude of the Seebeck coefficient for each quark flavor as well as for the partonic medium decreases as the temperature rises and increases as the chemical potential increases. Furthermore, we have investigated the Seebeck effect by considering the partonic interactions described in perturbative thermal QCD within the quasiparticle model. In addition, we have presented a comparison between our findings and the results of the standard RTA model., Comment: 22 pages, 10 figures

Using the combination of a new effective Hamiltonian approach and hybrid Monte-Carlo simulations, we unveil a variety of partially magnetically ordered (PMO) phases in the Kondo lattice model. Our approximation is motivated by two crucial features of the Hamiltonian: (i) formation of Kondo singlets leading to vanishing local magnetic moments, and (ii) spatially correlated nature of the effective single-particle kinetic energy. We discover PMO phases with fractional values $1/4$, $3/8$, and $1/2$ of Kondo-screened sites. A common understanding of these states emerges in terms of a non-local ordering mechanism. The concept of site-selective spontaneous symmetry breaking introduced here provides a new general approach to study models of interacting fermions in the intermediate coupling regime., Comment: Supplemental material appended

Multimodal device operations are essential to advancing the integration of 2D semiconductors in electronics, photonics, information and quantum technology. Precise control over carrier dynamics, particularly exciton generation and transport, is crucial for finetuning the functionality of optoelectronic devices based on 2D semiconductor heterostructure. However, the traditional exciton engineering methods in 2D semiconductors are mainly restricted to the artificially assembled vertical pn heterostructures with electrical or strain induced confinements. In this study, we utilized bilayer 2D lateral npn multijunction heterostructures with intrinsically spatially separated energy landscapes to achieve preferential exciton generation and manipulation without external confinement. In lateral npn FET geometry, we uncover unique and nontrivial properties, including dynamic tuning of channel photoresponsivity from positive to negative. The multimodal operation of these 2D FETs is achieved by carefully adjusting electrical bias and the impinging photon energy, enabling precise control over the trions generation and transport. Cryogenic photoluminescence measurement revealed the presence of trions in bilayer MoSe2 and intrinsic trap states in WSe2. Measurements in different FET device geometries show the multifunctionality of 2D lateral heterostructure phototransistors for efficient tuning and electrical manipulation of excitonic characteristics. Our findings pave the way for developing practical exciton-based transistors, sensors, multimodal optoelectronic and quantum technologies

Coronal Mass Ejections (CMEs) are subject to changes in their direction of propagation, tilt, and other properties as they interact with the variable solar wind. We investigated the heliospheric propagation of 15 Earth-impacting CMEs observed during April 2010 to August 2018 in the field of view (FOV) of the Heliospheric Imager (HI) onboard the STEREO. About half of the 15 events followed self-similar expansion up to 40 $R_\odot$. The remaining events showed deflection either in latitude, longitude, or a tilt change. Only two events showed significant rotation in the HI1 FOV. We also use toroidal and cylindrical flux rope fitting on the in situ observations of interplanetary magnetic field (IMF) and solar wind parameters to estimate the tilt at L1 for these two events. Although the sample size is small, this study suggests that CME rotation is not very common in the heliosphere. We attributed the observed deflections and rotations of CMEs to a combination of factors, including their interaction with the ambient solar wind and the influence of the ambient magnetic field. These findings contribute to our understanding of the complex dynamics involved in CME propagation and highlight the need for comprehensive modeling and observational studies to improve space weather prediction. In particular, HI observations help us to connect observations near the Sun and near Earth, improving our understanding of how CMEs move through the heliosphere., Comment: Accepted for publication in the Astrophysical Journal

A reconfigurable intelligent surface (RIS)-aided multiple-input multiple-output (MIMO) wireless communication system is considered in this paper wherein the transmitter, Alice modulates secret keys, by using a continuous variable quantum key distribution technique to be transmitted to the receiver, Bob, which employs homodyne detection for data decoding. The data is transmitted over two paths, namely a direct path between Alice and Bob and the wireless path between them via the RIS. Transmit and receive beamsplitters are employed in the system to transform the MIMO terahertz channels into parallel single-input single-output channels. Considering an eavesdropper, Eve, to attack all the three wireless channels in the system (i.e., the direct channel, the channel between Alice and RIS, and between the RIS and Bob) but having restricted quantum memory limiting it to store the ancilla modes from either of these three wireless channels, novel expressions for the secret key rate (SKR) of the system are derived. Numerical results are presented to demonstrate the dependency of the system's performance on various system parameters. It is observed that the RIS plays a key role in increasing the SKR of the system and the transmission distance, ensuring secure communications between Alice and Bob. The significance of employing RIS is observed specifically for the case when Eve measures the ancilla modes of the channel between the RIS and Bob. Furthermore, for all such measurement scenarios, optimal angles are obtained for the phase shifts of the RIS elements to maximize the SKR for various MIMO configurations and transmission distance between Alice and Bob., Comment: 13 pages, 6 figures

An attempt has been made to estimate the minimum size of the de-confined matter of Quark-Gluon Plasma (QGP) in small system that could be satisfactorily modeled with low-order hydrodynamics. The elliptic flow coefficient has been studied for the variation of second order transport coefficient called the shear relaxation time, which acts as a regulator of the non-hydrodynamic mode of theory. The small system of p-Pb collision at $\sqrt{s_{NN}} =$ 5.02 TeV is simulated on the state-of-art framework of JETSCAPE. We modeled the soft sector dynamics using an initial condition, a pre-equilibrium stage, hydrodynamics and a hadron afterburner. We generated results of transverse momentum spectra and rapidity spectra of light particles to match the simulated system with the experimental data. We looked at elliptic flow variation for extreme values of shear relaxation time for peripheral collision centralities. The increase in elliptic flow fluctuations indicate breakdown of fluid behavior at around $dN/dy \approx 8$ for p-Pb collision at $\sqrt{s_{NN}} =$ 5.02 TeV.

In this paper, we analyze the performance of one- and two-sided amplitude shift keying (ASK) modulations in single-input single-output wireless communication aided by a reconfigurable intelligent surface (RIS). Two scenarios are considered for the channel conditions: a blocked direct channel between the transmitter and the receiver, and an unblocked one. For the receiver, a noncoherent maximum likelihood detector is proposed, which detects the transmitted data signal based on statistical knowledge of the channel. The system's performance is then evaluated by deriving the symbol error probability (SEP) for both scenarios using the proposed noncoherent receiver structures. We also present a novel optimization framework to obtain the optimal one- and two-sided ASK modulation schemes that minimize the SEP under constraints on the available average transmit power for both the blocked and unblocked direct channel scenarios. Our extensive numerical investigations showcase that the considered RIS-aided communication system achieves superior error performance with both derived SEP-optimal ASK modulation schemes as compared to respective traditional ASK modulation. It is also demonstrated that, between the two proposed modulation schemes, the two-sided one yields the best SEP. The error performance is further analyzed for different system parameters, providing a comprehensive performance investigation of RIS-assisted noncoherent wireless communication systems., Comment: 13 pages, 6 figures

Knowledge of the global magnetic field distribution and its evolution on the Sun's surface is crucial for modeling the coronal magnetic field, understanding solar wind dynamics, computing the heliospheric open flux distribution and predicting solar cycle strength. As the far side of the Sun cannot be observed directly and high-latitude observations always suffer from projection effects, we often rely on surface flux transport simulations (SFT) to model long-term global magnetic field distribution. Meridional circulation, the large-scale north-south component of the surface flow profile, is one of the key components of the SFT simulation that requires further constraints near high latitudes. Prediction of the photospheric magnetic field distribution requires knowledge of the flow profile in the future, which demands reconstruction of that same flow at the current time so that it can be estimated at a later time. By performing Observing System Simulation Experiments, we demonstrate how the Ensemble Kalman Filter technique, when used with a SFT model, can be utilized to make ``posterior'' estimates of flow profiles into the future that can be used to drive the model forward to forecast photospheric magnetic field distribution., Comment: Accepted for publication in The Astrophysical Journal

Single photon emitters (SPEs) are building blocks of quantum technologies. Defect engineering of 2D materials is ideal to fabricate SPEs, wherein spatially deterministic and quality-preserving fabrication methods are critical for integration into quantum devices and cavities. Existing methods use combination of strain and electron irradiation, or ion irradiation, which make fabrication complex, and limited by surrounding lattice damage. Here, we utilise only ultra-low energy electron beam irradiation (5 keV) to create dilute defect density in hBN-encapsulated monolayer MoS2, with ultra-high spatial resolution (< 50 nm, extendable to 10 nm). Cryogenic photoluminescence spectra exhibit sharp defect peaks, following power-law for finite density of single defects, and characteristic Zeeman splitting for MoS2 defect complexes. The sharp peaks have low spectral jitter (< 200 {\mu}eV), and are tuneable with gate-voltage and electron beam energy. Use of low-momentum electron irradiation, ease of processing, and high spatial resolution, will disrupt deterministic creation of high-quality SPEs., Comment: 31 pages, 16 figures, 1 table. Supplementary Material included

Despite staggering growth over the past couple of decades, the concept of the metaverse is still in its early stages. Eventually, it is expected to become a common medium connecting every individual. Considering the complexity of this plausible scenario at hand, there's a need to define an advanced metaverse -- a metaverse in which, at every point in space and time, two distinct paradigms exist: that of the user in the physical world and that of its real-time digital replica in the virtual one, that can engage seamlessly with each other. The developing metaverse can be thus defined as the transitional period from the current state to, possibly, the advanced metaverse. This paper seeks to model, from a graphical standpoint, some of the structures in the current metaverse and ones that might be key to the developing and advanced metaverses under one umbrella, unlike existing approaches that treat different aspects of the metaverse in isolation. This integration allows for the accurate representation of cross-domain interactions, leading to optimized resource allocation, enhanced user engagement, and improved content distribution. This work demonstrates the usefulness of such an approach in capturing these correlations, providing a powerful tool for the analysis and future development of the metaverse., Comment: 4 pages, 2 figures, accepted at the IEEE International Symposium on Emerging Metaverse (ISEMV) 2024

In this paper, we propose and investigate algorithms for the structured orthogonal dictionary learning problem. First, we investigate the case when the dictionary is a Householder matrix. We give sample complexity results and show theoretically guaranteed approximate recovery (in the $l_{\infty}$ sense) with optimal computational complexity. We then attempt to generalize these techniques when the dictionary is a product of a few Householder matrices. We numerically validate these techniques in the sample-limited setting to show performance similar to or better than existing techniques while having much improved computational complexity., Comment: 10 pages, 5 figures, Submitted to IEEE ICASSP, 2025

Two-dimensional (2D) semiconductors have emerged as leading candidates for the development of low-power and multifunctional computing applications, thanks to their qualities such as layer-dependent band gap tunability, high carrier mobility, and excellent electrostatic control. Here, we explore a pair of 2D semiconductors with broken-gap (Type III) band alignment and demonstrate a highly gate-tunable p-MoTe$_{2}$/n-SnS$_{2}$ heterojunction tunnel field-effect transistor with multifunctional behavior. Employing a dual-gated asymmetric device geometry, we unveil its functionality as both a forward and backward rectifying device. Consequently, we observe a highly gate-tunable negative differential resistance (NDR), with a gate-coupling efficiency of $\eta \simeq 0.5$ and a peak-to-valley ratio of $\sim$ 3 down to 150K. By employing density functional theory and exploring the density of states, we determine that interband tunneling within the valence bands is the cause of the observed NDR characteristics. The combination of band-to-band tunneling and gate controllability of NDR signal open the pathway for realizing gate-tunable 2D material-based neuromorphic and energy-efficient electronics., Comment: 22 pages, 5 figures

Robotic Autonomous Vehicles (RAVs) rely on their sensors for perception, and follow strict mission specifications (e.g., altitude, speed, and geofence constraints) for safe and timely operations. Physical attacks can corrupt the RAVs' sensors, resulting in mission failures. Recovering RAVs from such attacks demands robust control techniques that maintain compliance with mission specifications even under attacks to ensure the RAV's safety and timely operations. We propose SpecGuard, a technique that complies with mission specifications and performs safe recovery of RAVs. There are two innovations in SpecGuard. First, it introduces an approach to incorporate mission specifications and learn a recovery control policy using Deep Reinforcement Learning (Deep-RL). We design a compliance-based reward structure that reflects the RAV's complex dynamics and enables SpecGuard to satisfy multiple mission specifications simultaneously. Second, SpecGuard incorporates state reconstruction, a technique that minimizes attack induced sensor perturbations. This reconstruction enables effective adversarial training, and optimizing the recovery control policy for robustness under attacks. We evaluate SpecGuard in both virtual and real RAVs, and find that it achieves 92% recovery success rate under attacks on different sensors, without any crashes or stalls. SpecGuard achieves 2X higher recovery success than prior work, and incurs about 15% performance overhead on real RAVs., Comment: CCS'24 (a shorter version of this paper will appear in the conference proceeding)

The van der Waals (vdW) heterostructure of emerging two-dimensional (2D) quantum materials, with control over their quantum geometries, crystal symmetries, spin-orbit coupling, and magnetic anisotropies, provides a new platform for generating unconventional nonlinear Hall effects, spin polarization and efficiently controlling the magnetization dynamics for non-volatile spin-based computing. However, so far, the generation of a large out-of-plane spin polarization is limited to achieve energy-efficient field-free magnetization switching and spin dynamics measurements in all-2D vdW heterostructure are so far missing, where the interplay between spins and magnetization dynamics should enable the design of ultrafast spintronic devices. Here, we demonstrate magnetization dynamics and energy-efficient field-free spin-orbit torque (SOT) switching of out-of-plane magnet Fe3GaTe2 due to unconventional Berry curvature-induced out-of-plane spin polarization from a topological Weyl semimetal TaIrTe4 in a vdW heterostructure at room temperature. We observed a large non-linear 2nd harmonic Hall signal at room temperature and evaluated the SOT-induced magnetization dynamics with a large damping-like torque. Deterministic field-free SOT magnetization switching in vdW heterostructure of TaIrTe4/Fe3GaTe2 is observed at room temperature with a low current and power density, which is an order of magnitude better than that of conventional systems. From the magnetization switching experiments, a large SOT efficiency and a very large spin Hall conductivity. These findings on all-vdW heterostructures offer a promising route to energy-efficient and external field-free ultrafast spintronic technologies.

An experimental study on Rydberg electromagnetically induced transparency (EIT) in rubidium (Rb) vapor cells containing inert gases at pressures $\le 5$ Torr is reported. Using an inert-gas-free Rb vapor cell as a reference, we measure frequency shift and line broadening of the EIT spectra in Rb vapor cells with argon, neon or nitrogen gases at pressures ranging from a few mTorr to 5 Torr. The results qualitatively agree with a pseudo-potential model that includes $s$-wave scattering between the Rydberg electron and the inert-gas atoms, and the effect of polarization of the inert-gas atoms by the Rydberg atoms. Our results are important for establishing Rydberg-EIT as an all-optical and non-intrusive spectroscopic probe for field diagnostics in low-pressure radio-frequency discharges., Comment: 8 pages, 4 figures

The notion of charge balance function, originally designed to study the evolution of charge production in heavy-ion collisions, is extended to consider quark flavor balancing. This extension is considered based on simulations performed with the PYTHIA 8 event generator in the context of pp collisions at $\sqrt{s} = 13.6$ TeV but can be trivially applied to any other scenario and implemented in measurements of correlated particle production in pp, pA, and AA collisions at colliders. Correlation of selected flavor balancing pairs are examined as function of the produced charged particle multiplicity. One finds that the amplitude of the correlations increases monotonically with the number of balanced flavors and the actual flavor content of correlated particles.

We develop non-Hermitian counterpart of a new class of collinear magnets, dubbed altermagnets, delineated by net zero magnetization with momentum-dependent spin splitting bands. With the introduction of an imaginary gauge field in the hopping parameter of a two-dimensional d-wave altermagnet, we discover an inversion broken mixed phase featuring the coexistence of spin-momentum locked and unlocked spin polarized bands along with the altermagnetic order, without hosting exceptional points (EPs). By attaching a ferromagnetic lead with d-wave altermagnet, we uncover the emergence of two pairs of exceptional points, a hallmark signature of the non-Hermitian topology. Further, we demonstrate that the application of a planar magnetic field to the junction not only tune the location of the EPs but also can annihilate single pair or even all pairs of EPs depending on the field direction. Finally, we establish that the spin expectation value coalesces at the EPs, revealing its another fingerprint., Comment: 6 Pages, 3 Figures

The rise of machine learning workload on smartphones has propelled GPUs into one of the most power-hungry components of modern smartphones and elevates the need for optimizing the GPU power draw by mobile apps. Optimizing the power consumption of mobile GPUs in turn requires accurate estimation of their power draw during app execution. In this paper, we observe that the prior-art, utilization-frequency based GPU models cannot capture the diverse micro-architectural usage of modern mobile GPUs.We show that these models suffer poor modeling accuracy under diverse GPU workload, and study whether performance monitoring counter (PMC)-based models recently proposed for desktop/server GPUs can be applied to accurately model mobile GPU power. Our study shows that the PMCs that come with dominating mobile GPUs used in modern smartphones are sufficient to model mobile GPU power, but exhibit multicollinearity if used altogether. We present APGPM, the mobile GPU power modeling methodology that automatically selects an optimal set of PMCs that maximizes the GPU power model accuracy. Evaluation on two representative mobile GPUs shows that APGPM-generated GPU power models reduce the MAPE modeling error of prior-art by 1.95x to 2.66x (i.e., by 11.3% to 15.4%) while using only 4.66% to 20.41% of the total number of available PMCs.

The levitating Leidenfrost (LF) state of a droplet on a heated substrate is often accompanied by fascinating behaviors such as star-shaped deformations, self-propulsion, bouncing, and trampolining. These behaviors arise due to the vapor flow instabilities at the liquid-vapor interface beneath the droplet at sizes typically comparable to the capillary length scale of the liquid. Here, we report on the spontaneous bouncing, trampolining, and hovering behavior of an unconstrained LF water droplet. We observe that a droplet exhibits intermittent increase in bouncing height at specific radii and subsequent reduction in the height of bounce leading to a quiescent LF state. The reemergence of the trampolining behavior from the quiescent hovering state without any external forcing is observed at sizes as low as 0.1 times the capillary length. We attribute the droplet bouncing behavior to the dynamics of vapor flow beneath the LF droplet. We propose that the trampolining behavior of the droplet at specific radii is triggered by subharmonic and harmonic excitation of the liquid-vapor interface. We attribute the intermittent trampolining events to the change in the natural frequency of the droplet and the vapor layer due to evaporative mass loss. This proposed mechanism of resonance-driven trampolining of LF droplets is observed to be applicable for different liquids irrespective of the initial volume and substrate temperatures, thus indicating a universality of the behavior.

Interleaving sponsored results (advertisements) amongst organic results on search engine result pages (SERP) has become a common practice across multiple digital platforms. Advertisements have catered to consumer satisfaction and fostered competition in digital public spaces; making them an appealing gateway for businesses to reach their consumers. However, especially in the context of digital marketplaces, due to the competitive nature of the sponsored results with the organic ones, multiple unwanted repercussions have surfaced affecting different stakeholders. From the consumers' perspective the sponsored ads/results may cause degradation of search quality and nudge consumers to potentially irrelevant and costlier products. The sponsored ads may also affect the level playing field of the competition in the marketplaces among sellers. To understand and unravel these potential concerns, we analyse the Amazon digital marketplace in four different countries by simulating 4,800 search operations. Our analyses over SERPs consisting 2M organic and 638K sponsored results show items with poor organic ranks (beyond 100th position) appear as sponsored results even before the top organic results on the first page of Amazon SERP. Moreover, we also observe that in majority of the cases, these top sponsored results are costlier and are of poorer quality than the top organic results. We believe these observations can motivate researchers for further deliberation to bring in more transparency and guard rails in the advertising practices followed in digital marketplaces., Comment: This work has been accepted as a full paper in AAAI/ACM conference on Artificial Intelligence, Ethics and Society (AIES) 2024

This study examines the interdependence between cryptocurrencies and international financial indices, such as MSCI World and MSCI Emerging Markets. We compute the value at risk, expected shortfall (ES), and range value at risk (RVaR) and investigate the dynamics of risk spillover. We employ a hybrid approach to derive these risk measures that integrate GARCH models, extreme value models, and copula functions. This framework uses a bivariate portfolio approach involving cryptocurrency data and traditional financial indices. To estimate the above risks of these portfolio structures, we employ symmetric and asymmetric GARCH and both tail flexible EVT models as marginal to model the marginal distribution of each return series and apply different copula functions to connect the pairs of marginal distributions into a multivariate distribution. The empirical findings indicate that the eGARCH EVT-based copula model adeptly captures intricate dependencies, surpassing conventional methodologies like Historical simulations and t-distributed parametric in VaR estimation. At the same time, the HS method proves superior for ES, and the t-distributed parametric method outperforms RVaR. Eventually, the Diebold-Yilmaz approach will be applied to compute risk spillovers between four sets of asset sequences. This phenomenon implies that cryptocurrencies reveal substantial spillover effects among themselves but minimal impact on other assets. From this, it can be concluded that cryptocurrencies propose diversification benefits and do not provide hedging advantages within an investor's portfolio. Our results underline RVaR superiority over ES regarding regulatory arbitrage and model misspecification. The conclusions of this study will benefit investors and financial market professionals who aspire to comprehend digital currencies as a novel asset class and attain perspicuity in regulatory arbitrage., Comment: 29 pages, 5 figures 13

Facial Recognition Systems (FRSs) are being developed and deployed globally at unprecedented rates. Most platforms are designed in a limited set of countries but deployed in worldwide, without adequate checkpoints. This is especially problematic for Global South countries which lack strong legislation to safeguard persons facing disparate performance of these systems. A combination of unavailability of datasets, lack of understanding of FRS functionality and low-resource bias mitigation measures accentuate the problem. In this work, we propose a new face dataset composed of 6,579 unique male and female sportspersons from eight countries around the world. More than 50% of the dataset comprises individuals from the Global South countries and is demographically diverse. To aid adversarial audits and robust model training, each image has four adversarial variants, totaling over 40,000 images. We also benchmark five popular FRSs, both commercial and open-source, for the task of gender prediction (and country prediction for one of the open-source models as an example of red-teaming). Experiments on industrial FRSs reveal accuracies ranging from 98.2%--38.1%, with a large disparity between males and females in the Global South (max difference of 38.5%). Biases are also observed in all FRSs between females of the Global North and South (max difference of ~50%). Grad-CAM analysis identifies the nose, forehead and mouth as the regions of interest on one of the open-source FRSs. Utilizing this insight, we design simple, low-resource bias mitigation solutions using few-shot and novel contrastive learning techniques significantly improving the accuracy with disparity between males and females reducing from 50% to 1.5% in one of the settings. In the red-teaming experiment with the open-source Deepface model, contrastive learning proves more effective than simple fine-tuning., Comment: This work has been accepted for publication at AAAI/ACM AIES 2024

E-commerce platforms support the needs and livelihoods of their two most important stakeholders -- customers and producers/sellers. Multiple algorithmic systems, like ``search'' systems mediate the interactions between these stakeholders by connecting customers to producers with relevant items. Search results include (i) private label (PL) products that are manufactured/sold by the platform itself, as well as (ii) third-party products on advertised / sponsored and organic positions. In this paper, we systematically quantify the extent of PL product promotion on e-commerce search results for the two largest e-commerce platforms operating in India -- Amazon.in and Flipkart. By analyzing snapshots of search results across the two platforms, we discover high PL promotion on the initial result pages (~ 15% PLs are advertised on the first SERP of Amazon). Both platforms use different strategies to promote their PL products, such as placing more PLs on the advertised positions -- while Amazon places them on the first, middle, and last rows of the search results, Flipkart places them on the first two positions and the (entire) last column of the search results. We discover that these product placement strategies of both platforms conform with existing user attention strategies proposed in the literature. Finally, to supplement the findings from the collected data, we conduct a survey among 68 participants on Amazon Mechanical Turk. The click pattern from our survey shows that users strongly prefer to click on products placed at positions that correspond to the PL products on the search results of Amazon, but not so strongly on Flipkart. The click-through rate follows previously proposed theoretically grounded user attention distribution patterns in a two-dimensional layout.

A simple effective model for the intermediate-density regime is constructed from the high-density effective theory of quantum chromodynamics (QCD). In the effective model, under a renormalization-group (RG) scaling towards low momenta, the original QCD interactions lead to four-quark contact interactions for the relevant quark and hole modes around the Fermi surface. The contact interaction in the scalar channel can be traced back to zero-sound-type collinear quark scattering near the Fermi surface in an instanton background. The quark and hole states in opposite directions of a given Fermi velocity form the collective scalar bosonic mode $\sigma$. The magnitude of $\sigma$ is investigated via the non-perturbative Functional Renormalization Group (FRG) evolution of the effective average action from the ultraviolet (UV) to the infrared (IR). In the mean background-field approximation for $\sigma$, nontrivial minima ($\bar{\sigma} \neq 0$) are found in the IR limit of the effective average action. A nonvanishing $\bar{\sigma}$ corresponds to condensation of quark and hole states in opposite directions of a given Fermi velocity, in a thin shell-like structure in momentum space around the Fermi surface. This looks similar to the shell-like baryon distribution in momentum space assumed in the quarkyonic-matter concept. However, when including a dynamic bosonic $\sigma$-mode in the RG flow, we find that its diffusive nature destroys the quark-hole condensate, i.e., the IR potential does not show any minima beyond the trivial one., Comment: 27 pages, 11 figures

The European Committee for Future Accelerators (ECFA) Early-Career Researcher (ECR) panel, which represents the interests of the ECR community to ECFA, presents in this document its initiatives and activities in the year 2023. This report summarises the process of the first big turnover in the panel composition at the start of 2023 and reports on the activities of the active working groups - either pursued from before or newly established. The overarching goal of the ECFA-ECR panel is to better understand and support the diverse interests of early-career researchers in the ECFA community and beyond., Comment: Editors: Jan-Hendrik Arling, Cecilia Borca, Armin Ilg, Arnau Morancho Tarda, Holly Pacey, Marko Pesut, Elisabetta Spadaro Norella and Marta Urbaniak. arXiv admin note: substantial text overlap with arXiv:2212.11238

We report the first evidence for the $h_{b}(\text{2P}) \to \Upsilon(\text{1S})\eta$ transition with a significance of $3.5$ standard deviations. The decay branching fraction is measured to be $\mathcal{B}[h_{b}(\text{2P}) \to \Upsilon(\text{1S})\eta]=(7.1 ~^{+3.7} _{-3.2}\pm 0.8)\times10^{-3}$, which is noticeably smaller than expected. We also set upper limits on $\pi^0$ transitions of $\mathcal{B}[h_{b}(\text{2P}) \to \Upsilon(\text{1S})\pi^0] < 1.8\times10^{-3}$, and $\mathcal{B}[h_{b}(\text{1P})\to \Upsilon(\text{1S})\pi^0] < 1.8\times10^{-3}$, at the $90\%$ confidence level. These results are obtained with a $131.4$~fb$^{-1}$ data sample collected near the $\Upsilon(\text{5S})$ resonance with the Belle detector at the KEKB asymmetric-energy $e^+e^-$ collider., Comment: to be submitted to PRL

Quantization techniques are widely used to improve inference speed and deployment of large language models. While a wide body of work examines the impact of quantization on LLMs in English, none have evaluated across languages. We conduct a thorough analysis of quantized multilingual LLMs, focusing on performance across languages and at varying scales. We use automatic benchmarks, LLM-as-a-Judge, and human evaluation, finding that (1) harmful effects of quantization are apparent in human evaluation, which automatic metrics severely underestimate: a 1.7% average drop in Japanese across automatic tasks corresponds to a 16.0% drop reported by human evaluators on realistic prompts; (2) languages are disparately affected by quantization, with non-Latin script languages impacted worst; and (3) challenging tasks like mathematical reasoning degrade fastest. As the ability to serve low-compute models is critical for wide global adoption of NLP technologies, our results urge consideration of multilingual performance as a key evaluation criterion for efficient models., Comment: Findings of EMNLP 2024 Camera-Ready

Hand gesture recognition (HGR) is a vital component in enhancing the human-computer interaction experience, particularly in multimedia applications, such as virtual reality, gaming, smart home automation systems, etc. Users can control and navigate through these applications seamlessly by accurately detecting and recognizing gestures. However, in a real-time scenario, the performance of the gesture recognition system is sometimes affected due to the presence of complex background, low-light illumination, occlusion problems, etc. Another issue is building a fast and robust gesture-controlled human-computer interface (HCI) in the real-time scenario. The overall objective of this paper is to develop an efficient hand gesture detection and classification model using a channel-pruned YOLOv5-small model and utilize the model to build a gesture-controlled HCI with a quick response time (in ms) and higher detection speed (in fps). First, the YOLOv5s model is chosen for the gesture detection task. Next, the model is simplified by using a channel-pruned algorithm. After that, the pruned model is further fine-tuned to ensure detection efficiency. We have compared our suggested scheme with other state-of-the-art works, and it is observed that our model has shown superior results in terms of mAP (mean average precision), precision (\%), recall (\%), and F1-score (\%), fast inference time (in ms), and detection speed (in fps). Our proposed method paves the way for deploying a pruned YOLOv5s model for a real-time gesture-command-based HCI to control some applications, such as the VLC media player, Spotify player, etc., using correctly classified gesture commands in real-time scenarios. The average detection speed of our proposed system has reached more than 60 frames per second (fps) in real-time, which meets the perfect requirement in real-time application control.

E-commerce marketplaces provide business opportunities to millions of sellers worldwide. Some of these sellers have special relationships with the marketplace by virtue of using their subsidiary services (e.g., fulfillment and/or shipping services provided by the marketplace) -- we refer to such sellers collectively as Related Sellers. When multiple sellers offer to sell the same product, the marketplace helps a customer in selecting an offer (by a seller) through (a) a default offer selection algorithm, (b) showing features about each of the offers and the corresponding sellers (price, seller performance metrics, seller's number of ratings etc.), and (c) finally evaluating the sellers along these features. In this paper, we perform an end-to-end investigation into how the above apparatus can nudge customers toward the Related Sellers on Amazon's four different marketplaces in India, USA, Germany and France. We find that given explicit choices, customers' preferred offers and algorithmically selected offers can be significantly different. We highlight that Amazon is adopting different performance metric evaluation policies for different sellers, potentially benefiting Related Sellers. For instance, such policies result in notable discrepancy between the actual performance metric and the presented performance metric of Related Sellers. We further observe that among the seller-centric features visible to customers, sellers' number of ratings influences their decisions the most, yet it may not reflect the true quality of service by the seller, rather reflecting the scale at which the seller operates, thereby implicitly steering customers toward larger Related Sellers. Moreover, when customers are shown the rectified metrics for the different sellers, their preference toward Related Sellers is almost halved., Comment: This work has been accepted for presentation at the ACM Conference on Computer-Supported Cooperative Work and Social Computing (CSCW) 2024. It will appear in Proceedings of the ACM on Human-Computer Interaction

In a post-ChatGPT world, this paper explores the potential of leveraging scalable artificial intelligence for scientific discovery. We propose that scaling up artificial intelligence on high-performance computing platforms is essential to address such complex problems. This perspective focuses on scientific use cases like cognitive simulations, large language models for scientific inquiry, medical image analysis, and physics-informed approaches. The study outlines the methodologies needed to address such challenges at scale on supercomputers or the cloud and provides exemplars of such approaches applied to solve a variety of scientific problems., Comment: 17 pages, 5 figures

We search for excited charmed baryons in the $\Lambda_c^+\eta$ system using a data sample corresponding to an integrated luminosity of 980 $\rm fb^{-1}$. The data were collected by the Belle detector at the KEKB $e^{+}$$e^{-}$ asymmetric-energy collider. No significant signals are found in the $\Lambda_c^+\eta$ mass spectrum, including the known $\Lambda_c(2880)^+$ and $\Lambda_c(2940)^+$. Clear $\Lambda_c(2880)^+$ and $\Lambda_c(2940)^+$ signals are observed in the $pD^0$ mass spectrum. We set upper limits at 90\% credibility level on ratios of branching fractions of $\Lambda_c(2880)^+$ and $\Lambda_c(2940)^+$ decaying to $\Lambda_c^+\eta$ relative to $\Sigma_c(2455)\pi$ of $<0.13$ for the $\Lambda_c(2880)^+$ and $<1.11$ for the $\Lambda_c(2940)^+$. We measure ratios of branching fractions of $\Lambda_c(2880)^+$ and $\Lambda_c(2940)^+$ decaying to $pD^0$ relative to $\Sigma_c(2455)\pi$ of $0.75 \pm 0.03(\text{stat.}) \pm 0.07(\text{syst.})$ for the $\Lambda_c(2880)^+$ and $3.59 \pm 0.21(\text{stat.}) \pm 0.56(\text{syst.})$ for the $\Lambda_c(2940)^+$., Comment: 10 pages, 4 figures, accepted for publication as a Regular Article in Physical Review D

Let $\mathcal{G}(\alpha)$ denote the family of functions $ f(z)$ in the open unit disk $\mathbb D :=\{z\in\mathbb{C}: |z|<1\}$ that satisfy $ f(0)=0= f'(0)=1$ and \[\Re \left(1+ \dfrac{z f''(z)}{ f'(z)}\right)<1+\dfrac{\alpha}{2} , \quad z\in \mathbb D.\] We determine the disks $|z|<\rho_n$ in which sections $ s_n(z; f)$ of $ f(z)$ are convex, starlike, and close-to-convex of order $\beta\;(0\le \beta< 1)$. Further, we obtain certain inequalities of sections in the considered class of functions.

In this paper, we define a subclass of sense-preserving harmonic functions associated with a class of analytic functions satisfying a differential inequality. We then establish a close relation between both subclasses. Further, we obtain some characteristic properties, including radius properties, convolution, coefficient estimates and their properties, growth estimates, and convex combination for the functions in the defined subclass. At last, we produce conditions for some special functions as well as harmonic univalent polynomials to belong to the defined subclass of harmonic functions.

For the family of analytic functions $f(z)$ in the open unit disk $\mathbb{D}$ with $f(0)=f'(0)-1=0$, satisfying the differential equation \begin{equation*} zf'(z) - f(z) = \dfrac{1}{2} z^2 \phi(z), \quad |\phi(z)| \leq 1, \end{equation*} we obtain radii of convexity, starlikeness, and close-to-convexity of partial sums of $f(z)$. We also study the generalization of this family having the form \begin{equation*} zf'(z)-f(z) = \lambda z^2 \phi(z), \quad |\phi(z)| \leq 1, \end{equation*} where $\lambda > 0,$ and obtain some useful properties of these functions.

We analyze an optical atomic clock using two-photon $5S_{1/2} \rightarrow 4D_J$ transitions in rubidium. Four one- and two-color excitation schemes to probe the fine-structure states $4D_{3/2}$ and $4D_{5/2}$ are considered in detail. We compare key characteristics of Rb $4D_J$ and $5D_{5/2}$ two-photon clocks. The $4D_J$ clock features a high signal-to-noise ratio due to two-photon decay at favorable wavelengths, low dc electric and magnetic susceptibilities, and minimal black-body shifts. Ac Stark shifts from the clock interrogation lasers are compensated by two-color Rabi-frequency matching. We identify a "magic" wavelength near 1060~nm, which allows for in-trap, Doppler-free clock-transition interrogation with lattice-trapped cold atoms. From our analysis of clock statistics and systematics, we project a quantum-noise-limited relative clock stability at the $10^{-13}/\sqrt{\tau(s)}$-level, with integration time $\tau$ in seconds, and a relative accuracy of $\sim 10^{-13}$. We describe a potential architecture for implementing the proposed clock using a single telecom clock laser at 1550~nm, which is conducive to optical communication and long-distance clock comparisons. Our work could be of interest in efforts to realize small and portable Rb clocks and in high-precision measurements of atomic properties of Rb $4D_J$-states., Comment: A.D. and C.O. contributed equally to this work; 15 pages, 3 figures, 1 table

Post-Training Quantization (PTQ) enhances the efficiency of Large Language Models (LLMs) by enabling faster operation and compatibility with more accessible hardware through reduced memory usage, at the cost of small performance drops. We explore the role of calibration sets in PTQ, specifically their effect on hidden activations in various notable open-source LLMs. Calibration sets are crucial for evaluating activation magnitudes and identifying outliers, which can distort the quantization range and negatively impact performance. Our analysis reveals a marked contrast in quantization effectiveness across models. The older OPT model, upon which much of the quantization literature is based, shows significant performance deterioration and high susceptibility to outliers with varying calibration sets. In contrast, newer models like Llama-2 7B, Llama-3 8B, Command-R 35B, and Mistral 7B demonstrate strong robustness, with Mistral 7B showing near-immunity to outliers and stable activations. These findings suggest a shift in PTQ strategies might be needed. As advancements in pre-training methods reduce the relevance of outliers, there is an emerging need to reassess the fundamentals of current quantization literature. The emphasis should pivot towards optimizing inference speed, rather than primarily focusing on outlier preservation, to align with the evolving characteristics of state-of-the-art LLMs.

Measurement of higher order cumulants of the distributions of conserved quantities, like net-charge, net-baryon and net-strangeness in heavy-ion collisions, is proposed as a sensitive tool to determine the freeze-out parameters and the nature of phase transitions at the LHC energies. Baseline measurements for heavy-ion collisions are essential to understand the experimental measurements. Recently, several experimental observations have shown some QGP-like scenarios in small systems (pp collisions). We report the first Monte-Carlo study of the measurements of cumulants and their ratios for net-charge, net-hadron, net-kaon, net-baryon, and net-proton distributions in pp collisions at $\sqrt{s}$=13 TeV using pQCD models like Pythia8 and Herwig. We also discuss the effect of different particle production mechanisms on the higher-order cumulants. This simulation study will serve as a baseline for future measurements at the LHC. Furthermore, it will shed more light on the measurement of cumulants and the connection between small systems and heavy-ion collisions at the LHC., Comment: 18 Pages, 12 figures

The Voltage-Dependent Anion Channel (VDAC) protein is the primary conduit for the regulated passage of ions and metabolites into and out of mitochondria. Calculating its solvation free energy is crucial for understanding its stability, function, and interactions within the cellular environment. In this paper, we introduce a total solvation free energy, $E$, which is the sum of electrostatic, ideal gas, and excess free energies, along with a non-polar energy to yield a zero of $E$ in the absence of charges. We develop numerical schemes for computing $E$ and update the current mesh generation package to accelerate the generation of tetrahedral meshes and improve the quality of meshes for computing $E$. By integrating these schemes and the updated mesh package with our non-uniform size modified Poisson-Boltzmann ion channel (nuSMPBIC), SMPBIC, and PBIC finite element packages, the PDB2PQR package, and the OPM database, we create the VDAC Solvation Free Energy Calculation (VSFEC) package. Using the VSFEC package, we perform comparison tests on the nuSMPBIC, SMPBIC, and PBIC models by using six VDAC proteins and various ionic solutions containing up to four ionic species, including ATP$^{4-}$ and Ca$^{2+}$. We also conduct tests with different neutral voltages and permittivity constants to explore the varying patterns of $E$. Our test results underscore the importance of considering non-uniform ionic size effects and demonstrate the high performance of the VSFEC package in calculating the solvation free energy of VDAC proteins., Comment: 22 pages, 7 figures, 3 tables

This technical report introduces Aya 23, a family of multilingual language models. Aya 23 builds on the recent release of the Aya model (\"Ust\"un et al., 2024), focusing on pairing a highly performant pre-trained model with the recently released Aya collection (Singh et al., 2024). The result is a powerful multilingual large language model serving 23 languages, expanding state-of-art language modeling capabilities to approximately half of the world's population. The Aya model covered 101 languages whereas Aya 23 is an experiment in depth vs breadth, exploring the impact of allocating more capacity to fewer languages that are included during pre-training. Aya 23 outperforms both previous massively multilingual models like Aya 101 for the languages it covers, as well as widely used models like Gemma, Mistral and Mixtral on an extensive range of discriminative and generative tasks. We release the open weights for both the 8B and 35B models as part of our continued commitment for expanding access to multilingual progress.

This article explores the intersection of the Coupon Collector's Problem and the Orthogonal Matrix Factorization (OMF) problem. Specifically, we derive bounds on the minimum number of columns $p$ (in $\mathbf{X}$) required for the OMF problem to be tractable, using insights from the Coupon Collector's Problem. Specifically, we establish a theorem outlining the relationship between the sparsity of the matrix $\mathbf{X}$ and the number of columns $p$ required to recover the matrices $\mathbf{V}$ and $\mathbf{X}$ in the OMF problem. We show that the minimum number of columns $p$ required is given by $p = \Omega \left(\max \left\{ \frac{n}{1 - (1 - \theta)^n}, \frac{1}{\theta} \log n \right\} \right)$, where $\theta$ is the i.i.d Bernoulli parameter from which the sparsity model of the matrix $\mathbf{X}$ is derived., Comment: 5 pages

We report the results of the first search for Standard Model and baryon-number-violating two-body decays of the neutral $B$ mesons to $\Lambda^{0}$ and $\Omega^{(*)0}_c$ using 711~${\rm fb^{-1}}$ of data collected at the $\Upsilon(4S)$ resonance with the Belle detector at the KEKB asymmetric-energy $e^+ e^-$ collider. We observe no evidence of signal from any such decays and set 95\% confidence-level upper limits on the products of $B^0$ and $\bar{B}^0$ branching fractions for these two-body decays with $\mathcal{B}(\Omega_{c}^{0} \to \pi^+ \Omega^-)$ in the range between 9.5~$\times 10^{-8}$ and 31.2~$\times 10^{-8}$., Comment: 6 pages, 2 figures, submitted to PRD(L)