arXiv subjects

Anirban Das

Publications and source records attributed to Anirban Das.

At least 55 records · Page 3Linked to original sources

arXiv2023

mmDrive: mmWave Sensing for Live Monitoring and On-Device Inference of Dangerous Driving

Detecting dangerous driving has been of critical interest for the past few years. However, a practical yet minimally intrusive solution remains challenging as existing technologies heavily rely on visual features or physical proximity. With this motivation, we explore the feasibility of purely using mmWave radars to detect dangerous driving behaviors. We first study characteristics of dangerous driving and find some unique patterns of range-doppler caused by 9 typical dangerous driving actions. We then develop a novel Fused-CNN model to detect dangerous driving instances from regular driving and classify 9 different dangerous driving actions. Through extensive experiments with 5 volunteer drivers in real driving environments, we observe that our system can distinguish dangerous driving actions with an average accuracy of > 95%. We also compare our models with existing state-of-the-art baselines to establish their significance.

cs.HC↗

arXiv2023

Role of interface hybridization on induced superconductivity in 1T$^\prime$-WTe$_2$ and 2H-NbSe$_2$ heterostructures

Heterostructures between two-dimensional quantum spin Hall insulators (QSHI) and superconducting materials can allow for the presence of Majorana Fermions at their conducting edge states. Although a strong interface hybridization helps induce a reasonable superconducting gap on the topological material, the hybridization can modify the material's electronic structure. In this work, we utilize a realistic low-energy model with tunable interlayer hybridization to study the edge state physics in a heterostructure between monolayer quantum spin Hall insulator 1T$^\prime$-WTe$_2$ and s-wave superconductor 2H-NbSe$_2$. We find that even in the presence of strong inter-layer hybridization that renders the surface to become conducting, the edge state shows a significantly enhanced local density of states and induced superconductivity compared to the surface. We provide an alternate heterostructure geometry that can utilize the strong inter-layer hybridization and realize a spatial interface between a regime with a clean QSHI gap and a topological conducting edge state.

cond-mat.supr-con↗

arXiv2023

Compressed-VFL: Communication-Efficient Learning with Vertically Partitioned Data

We propose Compressed Vertical Federated Learning (C-VFL) for communication-efficient training on vertically partitioned data. In C-VFL, a server and multiple parties collaboratively train a model on their respective features utilizing several local iterations and sharing compressed intermediate results periodically. Our work provides the first theoretical analysis of the effect message compression has on distributed training over vertically partitioned data. We prove convergence of non-convex objectives at a rate of $O(\frac{1}{\sqrt{T}})$ when the compression error is bounded over the course of training. We provide specific requirements for convergence with common compression techniques, such as quantization and top-$k$ sparsification. Finally, we experimentally show compression can reduce communication by over $90\%$ without a significant decrease in accuracy over VFL without compression.

cs.LG↗

arXiv2023

Neutrino secret self-interactions: a booster shot for the cosmic neutrino background

Neutrinos might interact among themselves through forces that have so far remained hidden. Throughout the history of the Universe, such \emph{secret} interactions could lead to scatterings between the neutrinos from supernova explosions and the non-relativistic relic neutrinos left over from the Big Bang. Such scatterings can boost the cosmic neutrino background (C$ν$B) to energies of ${\cal O}$(MeV), making it, in principle, observable in experiments searching for the diffuse supernova neutrino background. Assuming a model-independent, but flavor universal, four-Fermi interaction, we determine the upscattered cosmic neutrino flux, and derive constraints on such secret interactions from the latest results from Super-Kamiokande. Furthermore, we also study prospects for detection of the boosted flux in future lead-based coherent elastic neutrino-nucleus scattering experiments. Nevertheless, given current constraints on flavor universal self-interactions, we find that the upscattered C$ν$B~contribution to the total DSNB flux is negligible, making a possible measurement of the boosted C$ν$B insurmountable.

hep-ph↗

arXiv2022

Tuning the Many-body Interactions in a Helical Luttinger Liquid

In one-dimensional (1D) systems, electronic interactions lead to a breakdown of Fermi liquid theory and the formation of a Tomonaga-Luttinger Liquid (TLL). The strength of its many-body correlations can be quantified by a single dimensionless parameter, the Luttinger parameter $K$, characterising the competition between the electrons' kinetic and electrostatic energies. Recently, signatures of a TLL have been reported for the topological edge states of quantum spin Hall (QSH) insulators, strictly 1D electronic structures with linear (Dirac) dispersion and spin-momentum locking. Here we show that the many-body interactions in such helical Luttinger Liquid can be effectively controlled by the edge state's dielectric environment. This is reflected in a tunability of the Luttinger parameter $K$, distinct on different edges of the crystal, and extracted to high accuracy from the statistics of tunnelling spectra at tens of tunneling points. The interplay of topology and many-body correlations in 1D helical systems has been suggested as a potential avenue towards realising non-Abelian parafermions.

cond-mat.str-el↗

arXiv2022

UniPreCIS : A data pre-processing solution for collocated services on shared IoT

Next-generation smart city applications, attributed by the power of Internet of Things (IoT) and Cyber-Physical Systems (CPS), significantly rely on the quality of sensing data. With an exponential increase in intelligent applications for urban development and enterprises offering sensing-as-aservice these days, it is imperative to provision for a shared sensing infrastructure for better utilization of resources. However, a shared sensing infrastructure that leverages low-cost sensing devices for a cost effective solution, still remains an unexplored territory. A significant research effort is still needed to make edge based data shaping solutions, more reliable, feature-rich and costeffective while addressing the associated challenges in sharing the sensing infrastructure among multiple collocated services with diverse Quality of Service (QoS) requirements. Towards this, we propose a novel edge based data pre-processing solution, named UniPreCIS that accounts for the inherent characteristics of lowcost ambient sensors and the exhibited measurement dynamics with respect to application-specific QoS. UniPreCIS aims to identify and select quality data sources by performing sensor ranking and selection followed by multimodal data pre-processing in order to meet heterogeneous application QoS and at the same time reducing the resource consumption footprint for the resource constrained network edge. As observed, the processing time and memory utilization has been reduced in the proposed approach while achieving upto 90% accuracy which is arguably significant as compared to state-of-the-art techniques for sensing. The effectiveness of UniPreCIS has been evaluated on a testbed for a specific use case of indoor occupancy estimation that proves its effectiveness.

cs.NI↗

arXiv2022

Estimations by stable motions and applications

We propose a nonparametric parameter estimation of confidence intervals when the underlying has large or infinite variance. We explain the method by a simple numerical example and provide an application to estimate the coupling strength in neuronal networks.

math.ST↗

arXiv2022

Multi-Band Superconductivity in Strongly Hybridized 1T'-WTe$_2$/NbSe$_2$ Heterostructures

The interplay of topology and superconductivity has become a subject of intense research in condensed matter physics for the pursuit of topologically non-trivial forms of superconducting pairing. An intrinsically normal-conducting material can inherit superconductivity via electrical contact to a parent superconductor via the proximity effect, usually understood as Andreev reflection at the interface between the distinct electronic structures of two separate conductors. However, at high interface transparency, strong coupling inevitably leads to changes in the band structure, locally, owing to hybridization of electronic states. Here, we investigate such strongly proximity-coupled heterostructures of monolayer 1T'-WTe$_2$, grown on NbSe$_2$ by van-der-Waals epitaxy. The superconducting local density of states (LDOS), resolved in scanning tunneling spectroscopy down to 500~mK, reflects a hybrid electronic structure, well-described by a multi-band framework based on the McMillan equations which captures the multi-band superconductivity inherent to the NbSe$_2$ substrate and that induced by proximity in WTe$_2$, self-consistently. Our material-specific tight-binding model captures the hybridized heterostructure quantitatively, and confirms that strong inter-layer hopping gives rise to a semi-metallic density of states in the 2D WTe$_2$ bulk, even for nominally band-insulating crystals. The model further accurately predicts the measured order parameter $Δ\simeq 0.6$~meV induced in the WTe$_2$ monolayer bulk, stable beyond a 2~T magnetic field. We believe that our detailed multi-band analysis of the hybrid electronic structure provides a useful tool for sensitive spatial mapping of induced order parameters in proximitized atomically thin topological materials.

cond-mat.supr-con↗

arXiv2022

Neutrino Self-Interactions: A White Paper

Neutrinos are the Standard Model (SM) particles which we understand the least, often due to how weakly they interact with the other SM particles. Beyond this, very little is known about interactions among the neutrinos, i.e., their self-interactions. The SM predicts neutrino self-interactions at a level beyond any current experimental capabilities, leaving open the possibility for beyond-the-SM interactions across many energy scales. In this white paper, we review the current knowledge of neutrino self-interactions from a vast array of probes, from cosmology, to astrophysics, to the laboratory. We also discuss theoretical motivations for such self-interactions, including neutrino masses and possible connections to dark matter. Looking forward, we discuss the capabilities of searches in the next generation and beyond, highlighting the possibility of future discovery of this beyond-the-SM physics.

hep-ph↗

arXiv2022

Boosted dark matter from diffuse supernova neutrinos

The XENON collaboration recently reported an excess of electron recoil events in the low energy region with a significance of around $3.3σ$. An explanation of this excess in terms of thermal dark matter seems challenging. We propose a scenario where dark matter in the Milky Way halo gets boosted as a result of scattering with the diffuse supernova neutrino background. This interaction can accelerate the dark-matter to semi-relativistic velocities, and this flux, in turn, can scatter with the electrons in the detector, thereby providing a much better fit to the data. We identify regions in the parameter space of dark-matter mass and interaction cross-section which satisfy the excess. Furthermore, considering the data only hypothesis, we also impose bounds on the dark-matter scattering cross-section, which are competitive with bounds from other experiments.

hep-ph↗

arXiv2022

Multi-Level Local SGD for Heterogeneous Hierarchical Networks

We propose Multi-Level Local SGD, a distributed gradient method for learning a smooth, non-convex objective in a heterogeneous multi-level network. Our network model consists of a set of disjoint sub-networks, with a single hub and multiple worker nodes; further, worker nodes may have different operating rates. The hubs exchange information with one another via a connected, but not necessarily complete communication network. In our algorithm, sub-networks execute a distributed SGD algorithm, using a hub-and-spoke paradigm, and the hubs periodically average their models with neighboring hubs. We first provide a unified mathematical framework that describes the Multi-Level Local SGD algorithm. We then present a theoretical analysis of the algorithm; our analysis shows the dependence of the convergence error on the worker node heterogeneity, hub network topology, and the number of local, sub-network, and global iterations. We back up our theoretical results via simulation-based experiments using both convex and non-convex objectives.

cs.LG↗

arXiv2022

Stellar Shocks From Dark Matter Asteroid Impacts

Macroscopic dark matter is almost unconstrained over a wide "asteroid-like" mass range, where it could scatter on baryonic matter with geometric cross section. We show that when such an object travels through a star, it produces shock waves which reach the stellar surface, leading to a distinctive transient optical, UV and X-ray emission. This signature can be searched for on a variety of stellar types and locations. In a dense globular cluster, such events occur far more often than flare backgrounds, and an existing UV telescope could probe orders of magnitude in dark matter mass in one week of dedicated observation.

hep-ph↗

arXiv2021

Solar Mass Primordial Black Holes in Moduli Dominated Universe

We explore the prospect of producing primordial black holes around the solar mass region during an early matter domination epoch. The early matter-dominated epoch can arise when a moduli field comes to dominate the energy density of the Universe prior to big bang nucleosynthesis. The absence of radiation pressure during a matter-dominated epoch enhances primordial black hole formation from the gravitational collapse of primordial density fluctuations. In particular, we find that primordial black holes are produced in the $0.1-10~M_{\odot}$ mass range with a favorable choice of parameters in the theory. However, they cannot explain all of the merger events detected by the LIGO/Virgo gravitational wave search. In such a case, primordial black holes form about $4\%$ of the total dark matter abundance, of which $95\%$ belongs to the LIGO/Virgo consistent mass range. The rest of the dark matter could be in the form of particles that are produced from the decay of the moduli field during reheating.

astro-ph.CO↗

arXiv2021

Self-interacting neutrinos as a solution to the Hubble tension?

Self-interaction among the neutrinos in the early Universe has been proposed as a solution to the Hubble tension, a discrepancy between the measured values of the Hubble constant from CMB and low-redshift data. However, flavor-universal neutrino self-interaction is highly constrained by Big Bang Nucleosynthesis and other laboratory experiments such as, tau and K-meson decay, double-neutrino beta decay etc. We study the cosmology when only one or two neutrino states are self-interacting. Such flavor-specific interactions are less constrained by the laboratory experiments. Lastly, we address the feasibility of resolving the Hubble tension within the framework of such flavor-specific neutrino self-interaction.

hep-ph↗

arXiv2021

Flavor-specific Interaction Favors Strong Neutrino Self-coupling in the Early Universe

Flavor-universal neutrino self-interaction has been shown to ease the tension between the values of the Hubble constant measured from early and late Universe data. We introduce a self-interaction structure that is flavor-specific in the three active neutrino framework. This is motivated by the stringent constraints on new secret interactions among electron and muon neutrinos from several laboratory experiments. Our study indicates the presence of a strongly interaction mode which implies a late-decoupling of the neutrinos just prior to matter radiation equality. Using the degeneracy of the coupling strength with other cosmological parameters, we explain the origin of this new mode as a result of better fit to certain features in the CMB data. We find that if only one or two of the three active neutrino flavors are interacting, then the statistical significance of the strongly-interacting neutrino mode increases substantially relative to the flavor-universal scenario. However, the central value of the coupling strength for this interaction mode does not change by any appreciable amount in the flavor-specific cases. We also briefly analyze a scenario with more than three neutrino species of which only one is self-interacting. In none of the cases, we find a large enough Hubble constant that could resolve the so-called Hubble tension.

astro-ph.CO↗

arXiv2021

Thermal effects on collective modes in disordered $s$-wave superconductors

We investigate the effect of thermal fluctuations on the two-particle spectral function for a disordered $s$-wave superconductor in two dimensions, focusing on the evolution of the collective amplitude and phase modes. We find three main effects of thermal fluctuations: (a) the phase mode is softened with increasing temperature reflecting the decrease of superfluid stiffness; (b) remarkably, the non-dispersive collective amplitude modes at finite energy near ${\bf q}=[0,0]$ and ${\bf q}=[π,π]$ survive even in presence of thermal fluctuations in the disordered superconductor; and (c) the scattering of the thermally excited fermionic quasiparticles leads to low energy incoherent spectral weight that forms a strongly momentum-dependent background halo around the phase and amplitude collective modes and broadens them. Due to momentum and energy conservation constraints, this halo has a boundary which disperses linearly at low momenta and shows a strong dip near the $[π,π]$ point in the Brillouin zone.

cond-mat.supr-con↗

arXiv2021

Multi-Tier Federated Learning for Vertically Partitioned Data

We consider decentralized model training in tiered communication networks. Our network model consists of a set of silos, each holding a vertical partition of the data. Each silo contains a hub and a set of clients, with the silo's vertical data shard partitioned horizontally across its clients. We propose Tiered Decentralized Coordinate Descent (TDCD), a communication-efficient decentralized training algorithm for such two-tiered networks. To reduce communication overhead, the clients in each silo perform multiple local gradient steps before sharing updates with their hub. Each hub adjusts its coordinates by averaging its workers' updates, and then hubs exchange intermediate updates with one another. We present a theoretical analysis of our algorithm and show the dependence of the convergence rate on the number of vertical partitions, the number of local updates, and the number of clients in each hub. We further validate our approach empirically via simulation-based experiments using a variety of datasets and both convex and non-convex objectives.

cs.LG↗

arXiv2020

Galactic Positron Excess from Selectively Enhanced Dark Matter Annihilation

Precision measurements of the positron flux in cosmic ray have revealed an unexplained bump in the spectrum around $E\simeq 300\,\mathrm{GeV}$, not clearly attributable to known astrophysical processes. We propose annihilation of dark matter of mass $m_χ= 780\,\mathrm{GeV}$ with a late-time cross section $σv = 4.63\times 10^{-24}\,\mathrm{cm^3\,s^{-1}}$ as a possible source. The nonmonotonic dependence of the annihilation rate on dark matter velocity, owing to a selective $p$-wave Sommerfeld enhancement, allows such a large signal from the Milky Way without violating corresponding constraints from CMB and dwarf galaxy observations. We briefly explore other signatures of this scenario, and outline avenues to test it in future experiments.

hep-ph↗