arXiv subjects

Sandeep Kumar

Publications and source records attributed to Sandeep Kumar.

At least 145 records · Page 8Linked to original sources

arXiv2019

Robust Factor Analysis Parameter Estimation

This paper considers the problem of robustly estimating the parameters of a heavy-tailed multivariate distribution when the covariance matrix is known to have the structure of a low-rank matrix plus a diagonal matrix as considered in factor analysis (FA). By assuming the observed data to follow the multivariate Student's t distribution, we can robustly estimate the parameters via maximum likelihood estimation (MLE). However, the MLE of parameters becomes an intractable problem when the multivariate Student's t distribution and the FA structure are both introduced. In this paper, we propose an algorithm based on the generalized expectation maximization (GEM) method to obtain estimators. The robustness of our proposed method is further enhanced to cope with missing values. Finally, we show the performance of our proposed algorithm using both synthetic data and real financial data.

stat.CO↗

arXiv2019

Structured Graph Learning Via Laplacian Spectral Constraints

Learning a graph with a specific structure is essential for interpretability and identification of the relationships among data. It is well known that structured graph learning from observed samples is an NP-hard combinatorial problem. In this paper, we first show that for a set of important graph families it is possible to convert the structural constraints of structure into eigenvalue constraints of the graph Laplacian matrix. Then we introduce a unified graph learning framework, lying at the integration of the spectral properties of the Laplacian matrix with Gaussian graphical modeling that is capable of learning structures of a large class of graph families. The proposed algorithms are provably convergent and practically amenable for large-scale semi-supervised and unsupervised graph-based learning tasks. Extensive numerical experiments with both synthetic and real data sets demonstrate the effectiveness of the proposed methods. An R package containing code for all the experimental results is available at https://cran.r-project.org/package=spectralGraphTopology.

stat.ML↗

arXiv2019

On the Evolution of the Vortex Filament Equation for regular $M$-polygons with nonzero torsion

In this paper, we consider the evolution of the Vortex Filament equation (VFE): \begin{equation*} \mathbf X_t = \mathbf Xs \wedge \mathbf Xss, \end{equation*} taking $M$-sided regular polygons with nonzero torsion as initial data. Using algebraic techniques, backed by numerical simulations, we show that the solutions are polygons at rational times, as in the zero-torsion case. However, unlike in that case, the evolution is not periodic in time; moreover, the multifractal trajectory of the point $\mathbf X(0,t)$ is not planar, and appears to be a helix for large times. These new solutions of VFE can be used to illustrate numerically that the smooth solutions of VFE given by helices and straight lines share the same instability as the one already established for circles. This is accomplished by showing the existence of variants of the so-called Riemann's non-differentiable function that are as close to smooth curves as desired, when measured in the right topology. This topology is motivated by some recent results on the well-posedness of VFE, which prove that the selfsimilar solutions of VFE have finite renormalized energy.

math.NA↗

arXiv2019

Performance modeling of a distributed file-system

Data centers have become center of big data processing. Most programs running in a data center processes big data. The storage requirements of such programs cannot be fulfilled by a single node in the data center, and hence a distributed file system is used where the the storage resource are pooled together from more than one node and presents a unified view of it to outside world. Optimum performance of these distributed file-systems given a workload is of paramount important as disk being the slowest component in the framework. Owning to this fact, many big data processing frameworks implement their own file-system to get the optimal performance by fine tuning it for their specific workloads. However, fine-tuning a file system for a particular workload results in poor performance for workloads that do not match the profile of desired workload. Hence, these file systems cannot be used for general purpose usage, where the workload characteristics shows high variation. In this paper we model the performance of a general purpose file-system and analyse the impact of tuning the file-system on its performance. Performance of these parallel file-systems are not easy to model because the performance depends on a lot of configuration parameters, like the network, disk, under lying file system, number of servers, number of clients, parallel file-system configuration etc. We present a Multiple Linear regression model that can capture the relationship between the configuration parameters of a file system, hardware configuration, workload configuration (collectively called features) and the performance metrics. We use this to rank the features according to their importance in deciding the performance of the file-system.

cs.DC↗

arXiv2019

Deep sub micron normally off AlGaN/GaN MOSFET on silicon with VTH > 5V and On Current > 0.5 A/mm

We report on the demonstration of a deep sub-micron normally-off AlGaN/GaN HEMT with high on-current and high threshold voltage (VTH). The high-performance device was realized by utilizing a gate recess with length and depth of 200 nm and 124 nm respectively. The recess etched region had a roughness of 0.7 nm. Various recess etch depths and dielectric annealing conditions were used to tune the VTH. The optimized device exhibited on-current and VTH of 500 mA/mm and 5 V respectively. The measured breakdown characteristics of the devices and their limitations were investigated using 2D-TCAD device simulation. The penetration of the residual electric field in most of the recess region could be the reason for the premature breakdown of deeply scaled recess-gate e-mode HEMTs.

physics.app-ph↗

arXiv2019

Distributed Inexact Successive Convex Approximation ADMM: Analysis-Part I

In this two-part work, we propose an algorithmic framework for solving non-convex problems whose objective function is the sum of a number of smooth component functions plus a convex (possibly non-smooth) or/and smooth (possibly non-convex) regularization function. The proposed algorithm incorporates ideas from several existing approaches such as alternate direction method of multipliers (ADMM), successive convex approximation (SCA), distributed and asynchronous algorithms, and inexact gradient methods. Different from a number of existing approaches, however, the proposed framework is flexible enough to incorporate a class of non-convex objective functions, allow distributed operation with and without a fusion center, and include variance reduced methods as special cases. Remarkably, the proposed algorithms are robust to uncertainties arising from random, deterministic, and adversarial sources. The part I of the paper develops two variants of the algorithm under very mild assumptions and establishes first-order convergence rate guarantees. The proof developed here allows for generic errors and delays, paving the way for different variance-reduced, asynchronous, and stochastic implementations, outlined and evaluated in part II.

math.OC↗

arXiv2019

Meandering gate edges for breakdown voltage enhancement in AlGaN/GaN HEMTs

In this letter, we report on a unique device design strategy for increasing the breakdown voltage and hence Baliga Figure of Merit (BFOM) of III-nitride HEMTs by engineering the gate edge towards the drain. The breakdown of such devices with meandering gate-drain access region (M-HEMT) are found to be 62% more compared to that of conventional HEMT while the ON resistance suffers by 76%, leading to an overall improvement in the BFOM for by 28%. 3D-TCAD simulations show that the decrease in the peak electric field at the gate edge was responsible for increased breakdown voltage.

physics.app-ph↗

arXiv2019

A Unified Framework for Structured Graph Learning via Spectral Constraints

Graph learning from data represents a canonical problem that has received substantial attention in the literature. However, insufficient work has been done in incorporating prior structural knowledge onto the learning of underlying graphical models from data. Learning a graph with a specific structure is essential for interpretability and identification of the relationships among data. Useful structured graphs include the multi-component graph, bipartite graph, connected graph, sparse graph, and regular graph. In general, structured graph learning is an NP-hard combinatorial problem, therefore, designing a general tractable optimization method is extremely challenging. In this paper, we introduce a unified graph learning framework lying at the integration of Gaussian graphical models and spectral graph theory. To impose a particular structure on a graph, we first show how to formulate the combinatorial constraints as an analytical property of the graph matrix. Then we develop an optimization framework that leverages graph learning with specific structures via spectral constraints on graph matrices. The proposed algorithms are provably convergent, computationally efficient, and practically amenable for numerous graph-based tasks. Extensive numerical experiments with both synthetic and real data sets illustrate the effectiveness of the proposed algorithms. The code for all the simulations is made available as an open source repository.

stat.ML↗

arXiv2019

Moonshots for aging

As the global population ages, there is increased interest in living longer and improving one's quality of life in later years. However, studying aging - the decline in body function - is expensive and time-consuming. And despite research success to make model organisms live longer, there still aren't really any feasible solutions for delaying aging in humans. With space travel, scientists couldn't know what it would take to get to the moon. They had to extrapolate from theory and shorter-range tests. Perhaps with aging, we need a similar moonshot philosophy. And though "shot" might imply medicine, perhaps we need to think beyond biological interventions. Like the moon, we seem a long way away from provable therapies to increase human healthspan (the healthy period of one's life) or lifespan (how long one lives). This review therefore focuses on radical proposals. We hope it might stimulate discussion on what we might consider doing significantly differently than ongoing aging research.

q-bio.OT↗

arXiv2019

A Comprehensive Performance Evaluation of a DF-Based Multi-Hop System Over $α-κ-μ$ and $α-κ-μ$-Extreme Fading Channels

In this work, an integrated performance evaluation of a decode-and-forward (DF) multi-hop wireless communication system is undertaken over the non-linear generalized $α-κ-μ$ and $α-κ-μ$-Extreme fading models. Analytical formulas for the probability density function (PDF) and the cumulative distribution function (CDF) of the received signal-to-noise ratio (SNR) as well as its generalized moments and moment generating function (MGF) are derived. Based on the derived PDFs, novel closed-form expressions for traditional performance metrics such as amount of fading (AF), outage probability (OP), bit error rate (BER) under coherent and non-coherent modulation schemes as well as channel capacity under various adaptive transmission techniques are derived. Additionally, asymptotic analyses of BER based on Poincare series expansions of SNR PDFs are carried out and results show good approximations for low SNR regimes. The correctness of the proposed solutions has been corroborated by comparing them with Monte Carlo simulation results.

cs.IT↗

arXiv2019

Learning Semantic Sentence Embeddings using Sequential Pair-wise Discriminator

In this paper, we propose a method for obtaining sentence-level embeddings. While the problem of securing word-level embeddings is very well studied, we propose a novel method for obtaining sentence-level embeddings. This is obtained by a simple method in the context of solving the paraphrase generation task. If we use a sequential encoder-decoder model for generating paraphrase, we would like the generated paraphrase to be semantically close to the original sentence. One way to ensure this is by adding constraints for true paraphrase embeddings to be close and unrelated paraphrase candidate sentence embeddings to be far. This is ensured by using a sequential pair-wise discriminator that shares weights with the encoder that is trained with a suitable loss function. Our loss function penalizes paraphrase sentence embedding distances from being too large. This loss is used in combination with a sequential encoder-decoder network. We also validated our method by evaluating the obtained embeddings for a sentiment analysis task. The proposed method results in semantic embeddings and outperforms the state-of-the-art on the paraphrase generation and sentiment analysis task on standard datasets. These results are also shown to be statistically significant.

cs.CL↗

arXiv2019

Parameter Estimation of Heavy-Tailed AR Model with Missing Data via Stochastic EM

The autoregressive (AR) model is a widely used model to understand time series data. Traditionally, the innovation noise of the AR is modeled as Gaussian. However, many time series applications, for example, financial time series data, are non-Gaussian, therefore, the AR model with more general heavy-tailed innovations is preferred. Another issue that frequently occurs in time series is missing values, due to system data record failure or unexpected data loss. Although there are numerous works about Gaussian AR time series with missing values, as far as we know, there does not exist any work addressing the issue of missing data for the heavy-tailed AR model. In this paper, we consider this issue for the first time, and propose an efficient framework for parameter estimation from incomplete heavy-tailed time series based on a stochastic approximation expectation maximization (SAEM) coupled with a Markov Chain Monte Carlo (MCMC) procedure. The proposed algorithm is computationally cheap and easy to implement. The convergence of the proposed algorithm to a stationary point of the observed data likelihood is rigorously proved. Extensive simulations and real datasets analyses demonstrate the efficacy of the proposed framework.

stat.AP↗

arXiv2018

Low-Latitude Aurorae during the Extreme Space Weather Events in 1859

The Carrington storm (September 1/2, 1859) is one of the largest magnetic storms ever observed and it has caused global auroral displays in low-latitude areas, together with a series of multiple magnetic storms during August 28 and September 4, 1859. In this study, we revisit contemporary auroral observation records to extract information on their elevation angle, color, and direction to investigate this stormy interval in detail. We first examine their equatorward boundary of "auroral emission with multiple colors" based on descriptions of elevation angle and color. We find that their locations were 36.5 deg ILAT on August 28/29 and 32.7 deg ILAT on September 1/2, suggesting that trapped electrons moved to, at least, L~1.55 and L~1.41, respectively. The equatorward boundary of "purely red emission" was likely located at 30.8 deg ILAT on September 1/2. If "purely red emission" was a stable auroral red arc, it would suggest that trapped protons moved to, at least, L~1.36. This reconstruction with observed auroral emission regions provides conservative estimations of magnetic storm intensities. We compare the auroral records with magnetic observations. We confirm that multiple magnetic storms occurred during this stormy interval, and that the equatorward expansion of the auroral oval is consistent with the timing of magnetic disturbances. It is possible that the August 28/29 interplanetary coronal mass ejections (ICMEs) cleared out the interplanetary medium, making the ICMEs for the Carrington storm on September 1/2 more geoeffective.

physics.space-ph↗

arXiv2018

Spin phonon interactions and magneto-thermal transport behavior in p-Si

The spin-phonon interaction is the dominant process for spin relaxation in Si, and as thermal transport in Si is dominated by phonons, one would expect spin polarization to influence Si's thermal conductivity. Here we report the experimental evidence of just such a coupling. We have performed concurrent measurements of spin, charge, and phonon transport in p-doped Si across a wide range of temperatures. In an experimental system of a freestanding two um p-Si beam coated on one side with a thin (25 nm) ferromagnetic spin injection layer, we use the self-heating 3 omega method to measure changes in electrical and thermal conductivity under the influence of a magnetic field. These magneto-thermal transport measurements reveal signatures in the variation of electrical and thermal transport that are consistent with spin-phonon interaction. Raman spectroscopy measurements and first principle's calculations support that these variations are due to spin-phonon interaction. Spin polarization leads to softening of phonon modes, a reduction in the group velocity of acoustic modes, and a subsequent decrease in thermal conductivity at room temperature. Moreover, magneto-thermal transport measurements as a function of temperature indicate a change in the spin-phonon relaxation behavior at low temperature.

cond-mat.mes-hall↗

arXiv2018

Investigation of Ta2O5 as an alternative high \k{appa} dielectric for InAlN/GaN MOS HEMT on Si

We report on the demonstration and investigation of Ta2O5 as high-\k{appa} dielectric for InAlN/GaN-MOS HEMT-on-Si. Ta2O5 of thickness 24 nm and dielectric constant ~ 30 was sputter deposited on InAlN/GaN HEMT and was investigated for different post deposition anneal conditions (PDA). The gate leakage was 16nA/mm at -15 V which was ~ 5 orders of magnitude lower compared to reference HEMT. The 2-dimensional electron gas (2DEG) density was found to vary with annealing temperature suggesting the presence of net charge at the Ta2O5/InAlN interface. Dispersion in the capacitance-voltage (C-V) characteristics was used to estimate the frequency-dependent interface charge while energy band diagrams under flat band conditions were investigated to estimate fixed charge. The optimum anneal condition was found to be 500° C which has resulted into a flat band voltage spread (VFB) of 0.4 V and interface fix charge (Qf) of 3.98x10^13 cm-2. XPS (X-ray photoelectron spectroscopy) spectra of as deposited and annealed Ta2O5 film were analyzed for Ta and O compositions in the film. The sample annealed at 500° C has shown Ta:O ratio of 0.41.XRD (X-ray diffraction) analysis was done to check the evolution of poly-crystallization of the Ta2O5 film at higher annealing temperatures.

physics.app-ph↗

arXiv2018

Spiral waves in driven strongly coupled Yukawa systems

Spiral wave formations are ubiquitous in nature. In the present paper, the excitation of spiral waves in the context of driven two-dimensional dusty plasma (Yukawa system) has been demonstrated at particle level using molecular dynamics simulations. The interaction amidst dust particles is modeled by Yukawa potential to take account of the shielding of dust charges by the lighter electron and ions species. Spatiotemporal evolution of these spiral waves has been characterized as a function of frequency and amplitude of the driving force, dust neutral collisions etc. The effect of strong coupling has been studied which show that the excited spiral wave structures get clearer as the medium gets more strongly coupled. The radial propagation speed of the spiral wave is observed to remain unaltered with the coupling parameter. However, it is found to depend on the screening parameter of the dust medium and decreases when it is increased. In the crystalline phase (with screening parameter \k{appa} > 0.58), spiral wavefront are shown to be hexagonal in shape. This shows that the radial propagation speed depends on the interparticle spacing.

physics.plasm-ph↗

arXiv2018

Giant enhancement in Rashba spin-Seebeck effect in NiFe/p-Si thin films

The spin-Seebeck effect mediated thermoelectric energy conversion can provide efficient alternative to traditional thermoelectrics for waste heat recovery. To achieve this goal, efficient spin to charge conversion using earth-abundant materials is essential. Proximity induced Rashba effect arises from the charge potential mediated by structural inversion asymmetry, which has been reported in Si thin films and can be manipulated by controlling the thickness of Rashba layer. We demonstrate a giant Rashba spin-Seebeck effect in NiFe/p-Si (polycrystalline) bilayer thin films. The bilayer thin film specimens have p-Si layer thickness of 5 nm, 25 nm and 100 nm while keeping the NiFe layer thickness at 25 nm. The Rashba spin Seebeck coefficient has been estimated to be 0.266 μV/K for 100 nm p-Si, and increases by an order of magnitude to 2.11 μV/K for 5 nm p-Si. The measured spin-Seebeck coefficient in 5 nm p-Si specimen is one of the largest coefficient ever reported. The measured voltage of 100.3 μV is one of the largest reported spin-Seebeck voltage, with smallest area of ~160 X 10 μm2 used in any spin-Seebeck measurement. This scientific and technological breakthrough using earth abundant elements brings the spin mediated thermoelectric energy conversion for waste heat recovery closer to reality.

cond-mat.mes-hall↗

arXiv2018

Generation and detection of dissipationless spin current in MgO/Si bilayer

Spintronics is an analogue to electronics where spin of the electron rather than its charge is functionally controlled for devices. The generation and detection of spin current without ferromagnetic or exotic/scarce materials are two the biggest challenges for spintronics devices. In this study, we report a solution to the two problems of spin current generation and detection in Si. Using non-local measurement, we experimentally demonstrate the generation of helical dissipationless spin current using spin-Hall effect. Contrary to the theoretical prediction, we observe the spin-Hall effect in both n-doped and p-doped Si. The helical spin current is attributed to the site-inversion asymmetry of the diamond cubic lattice of Si and structure inversion asymmetry in MgO/Si bilayer. The spin to charge conversion in Si is insignificant due to weak spin-orbit coupling. For the efficient detection of spin current, we report spin to charge conversion at the MgO (1nm)/Si (2 um) (p-doped and n-doped) thin film interface due to Rashba spin-orbit coupling. We detected the spin current at a distance of >100 um, which is an order of magnitude larger than the longest spin diffusion length measured using spin injection techniques. The existence of spin current in Si is verified from coercivity reduction in Co/Pd multilayer due to spin-orbit torque generated by spin current from Si.

cond-mat.mes-hall↗