S. D. Singh - Aligarh Muslim University

S. D. Singh
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Name
S. D. Singh
Affiliation
Aligarh Muslim University
City
Aligarh
Country
India

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Physics - Materials Science (6)
 
Nuclear Theory (6)
 
Statistics - Machine Learning (6)
 
Computer Science - Computer Vision and Pattern Recognition (6)
 
High Energy Physics - Phenomenology (5)
 
Physics - Strongly Correlated Electrons (5)
 
Computer Science - Artificial Intelligence (5)
 
Computer Science - Learning (5)
 
High Energy Physics - Theory (3)
 
Physics - Mesoscopic Systems and Quantum Hall Effect (3)
 
Mathematics - Number Theory (2)
 
Computer Science - Distributed; Parallel; and Cluster Computing (2)
 
Computer Science - Databases (2)
 
Computer Science - Networking and Internet Architecture (2)
 
Quantum Physics (2)
 
Cosmology and Nongalactic Astrophysics (2)
 
Computer Science - Data Structures and Algorithms (2)
 
Statistics - Computation (1)
 
Statistics - Theory (1)
 
Mathematics - Classical Analysis and ODEs (1)
 
Mathematics - Group Theory (1)
 
Physics - Superconductivity (1)
 
Mathematics - Information Theory (1)
 
Mathematics - Combinatorics (1)
 
Computer Science - Neural and Evolutionary Computing (1)
 
Physics - General Physics (1)
 
General Relativity and Quantum Cosmology (1)
 
Nuclear Experiment (1)
 
Physics - Atomic Physics (1)
 
Instrumentation and Methods for Astrophysics (1)
 
Mathematics - Statistics (1)
 
Mathematics - Optimization and Control (1)
 
Mathematics - Algebraic Topology (1)
 
Computer Science - Computation and Language (1)
 
Computer Science - Information Theory (1)

Publications Authored By S. D. Singh

We introduce a stop-code tolerant (SCT) approach to training recurrent convolutional neural networks for lossy image compression. Our methods introduce a multi-pass training method to combine the training goals of high-quality reconstructions in areas around stop-code masking as well as in highly-detailed areas. These methods lead to lower true bitrates for a given recursion count, both pre- and post-entropy coding, even using unstructured LZ77 code compression. Read More

User-side performance in millimeter-wave (mmWave) cellular systems is known to be severely affected by blockage of the line-of-sight (LoS) propagation path. In contrast to microwave systems, at shorter mmWave wavelengths such blockage can be caused by human bodies while their mobility within the environment makes the wireless channel alternate between the blocked and non-blocked LoS states. Following recent 3GPP requirements on the dynamic blockage as well as the temporal consistency of the channel at mmWave frequencies, we in this paper develop a new model for predicting the state of a user in a field of mobile blockers for two representative 3GPP scenarios: urban micro cell (UMi) street canyon and park/stadium/square. Read More

How detailed should we make the goals we prescribe to AI agents acting on our behalf in complex environments? Detailed and low-level specification of goals can be tedious and expensive to create, and abstract and high-level goals could lead to negative surprises as the agent may find behaviors that we would not want it to do, i.e., lead to unsafe AI. Read More

Let G be a finite group acting freely on a finitistic space X having cohomology type (0, b) (for example, S^n x S^{2n} is a space of type (0, 1) and the one-point union S^n V S^{2n} V S^{3n} is a space of type (0, 0)). It is known that a finite group G which contains Zp + Zp + Zp, p a prime, can not act freely on S^n x S^{2n}. In this paper, we show that if a finite group G acts freely on a space of type (0, 1), where n is odd, then G can not contain Zp + Zp, p an odd prime. Read More

In two-dimensional (2D) semiconducting transition metal dichalcogenides (TMDs), new electronic phenomena such as tunable band gaps and strongly bound excitons and trions emerge from strong many-body effects, beyond spin-orbit coupling- and lattice symmetry-induced spin and valley degrees of freedom. Combining single-layer (SL) TMDs with other 2D materials in van der Waals heterostructures offers an intriguing means of controlling the electronic properties through these many-body effects via engineered interlayer interactions. Here, we employ micro-focused angle-resolved photoemission spectroscopy (microARPES) and in-situ surface doping to manipulate the electronic structure of SL WS$_2$ on hexagonal boron nitride (WS$_2$/h-BN). Read More

A new parameter set is generated for finite and infinite nuclear system within the effective field theory motivated relativistic mean field (ERMF) formalism. The isovector part of the ERMF model employed in the present study includes the coupling of nucleons to the {\delta} and \r{ho} mesons and the cross-coupling of \r{ho} mesons to the {\sigma} and {\omega} mesons. The results for the finite and infinite nuclear systems obtained using our parameter set are in harmony with the available experimental data. Read More

Recent advances in 3D vision have demonstrated the strengths of photometric bundle adjustment. By directly minimizing reprojected pixel errors, instead of geometric reprojection errors, such methods can achieve sub-pixel alignment accuracy in both high and low textured regions. Typically, these problems are solved using a forwards compositional Lucas-Kanade formulation parameterized by 6-DoF rigid camera poses and a depth per point in the structure. Read More

Recently the effect of nucleon shadowing on the Monte-Carlo Glauber initial condition was studied and its role on the centrality dependence of elliptic flow ($v_2$) and fluctuations in initial eccentricity for different colliding nuclei were explored. It was found that the results with shadowing effects are closer to the QCD based dynamical model as well as to the experimental data. Inspired by this outcome, in this work we study the transverse momentum ($p_T$) spectra and elliptic flow ($v_2$) of thermal photons for Au+Au collisions at RHIC and Pb+Pb collisions at the LHC by incorporating the shadowing effect to deduce the initial energy density profile required to solve the relativistic hydrodynamical equations. Read More

We look at particle production by a homogenous electric field \'a la Schwinger mechanism in an expanding, flat de Sitter patch relevant for the inflationary epoch of our universe. Defining states and particle content in curved spacetime is certainly not a unique process. There being different line of thoughts on how to do that, we have used the Schr\"odinger formalism to define instantaneous particle content, classicality of the state etc. Read More

With the availability of high luminosity electron beam at the accelerators, there is now the possibility of studying weak quasielastic hyperon production off the proton i.e. $e^-p \to \nu_e Y(Y=\Lambda,\Sigma^0)$, which will enable the determination of nucleon-hyperon vector and axial-vector transition form factors at high $ Q^2$ in the strangeness sector and provide test of the Cabibbo model, G-invariance, CVC, PCAC hypotheses and SU(3) symmetry. Read More

The inclusive quasielastic (anti)neutrino induced charged and neutral current reaction cross sections in $^{12}C$, $^{16}O$, $^{40}Ar$, $^{56}Fe$ and $^{208}Pb$ in the energy region of supernova (anti)neutrinos are studied. The calculations are performed in local density approximation (LDA) taking into account the effects due to Pauli blocking, Fermi motion and the renormalisation of weak transition strengths in the nuclear medium. The effect of Coulomb distortion of the lepton produced in the charged current reactions has also been included. Read More

A simple and low cost apparatus has been designed and built to measure the electrical resistivity, ($\rho$), of metal and semiconductors in 300-620 K temperature range. The present design is suitable to do measurement on rectangular bar sample by using conventional four-probe dc method. A small heater is made on the sample mounting copper block to achieve the desired temperature. Read More

A grand goal of computer vision is to build systems that learn visual representations over time that can be applied to many tasks. In this paper, we investigate a vision-language embedding as a core representation and show that it leads to better cross-task transfer than standard multi-task learning. In particular, the task of visual recognition is aligned to the task of visual question answering by forcing each to use the same word-region embeddings. Read More

We propose a method for lossy image compression based on recurrent, convolutional neural networks that outperforms BPG (4:2:0 ), WebP, JPEG2000, and JPEG as measured by MS-SSIM. We introduce three improvements over previous research that lead to this state-of-the-art result. First, we show that training with a pixel-wise loss weighted by SSIM increases reconstruction quality according to several metrics. Read More

We present additional magic wavelengths ($\lambda_{\rm{magic}}$) for the clock transitions in the alkaline-earth metal ions considering circular polarized light aside from our previously reported values in [J. Kaur et al., Phys. Read More

We address the problem of distance metric learning (DML), defined as learning a distance consistent with a notion of semantic similarity. Traditionally, for this problem supervision is expressed in the form of sets of points that follow an ordinal relationship -- an anchor point $x$ is similar to a set of positive points $Y$, and dissimilar to a set of negative points $Z$, and a loss defined over these distances is minimized. While the specifics of the optimization differ, in this work we collectively call this type of supervision Triplets and all methods that follow this pattern Triplet-Based methods. Read More

Long wavelength spectral distortions in the Cosmic Microwave Background arising from the 21-cm transition in neutral Hydrogen are a key probe of Cosmic Dawn and the Epoch of Reionization. These features may reveal the nature of the first stars and ultra-faint galaxies that transformed the spin temperature and ionization state of the primordial gas. SARAS 2 is a spectral radiometer purposely designed for precision measurement of these monopole or all-sky global 21-cm spectral distortions. Read More

Normally, understanding the temperature dependent transport properties of strongly correlated electron systems remains challenging task due to complex electronic structure and its variations (around E$_{F}$) with temperature. Here, we report the applicability of DFT+U in explaining thermopower ($\alpha$) and electrical conductivity ($\sigma$) in high temperature region. We have measured temperature dependent $\alpha$ and $\sigma$ in the 300-600 K range. Read More

Code-mixing or code-switching are the effortless phenomena of natural switching between two or more languages in a single conversation. Use of a foreign word in a language; however, does not necessarily mean that the speaker is code-switching because often languages borrow lexical items from other languages. If a word is borrowed, it becomes a part of the lexicon of a language; whereas, during code-switching, the speaker is aware that the conversation involves foreign words or phrases. Read More

In cooperative multiagent planning, it can often be beneficial for an agent to make commitments about aspects of its behavior to others, allowing them in turn to plan their own behaviors without taking the agent's detailed behavior into account. Extending previous work in the Bayesian setting, we consider instead a worst-case setting in which the agent has a set of possible environments (MDPs) it could be in, and develop a commitment semantics that allows for probabilistic guarantees on the agent's behavior in any of the environments it could end up facing. Crucially, an agent receives observations (of reward and state transitions) that allow it to potentially eliminate possible environments and thus obtain higher utility by adapting its policy to the history of observations. Read More

Recently high density (HD) nonmagnetic (NM) cobalt has been discovered in a cobalt thin film, grown on Si(111). This cobalt film had a natural cobalt oxide at the top. The oxide layer forms when the film is taken out of the electron-beam deposition chamber and exposed to air. Read More

Let $L_u=\begin{bmatrix}1 & 0u & 1\end{bmatrix}$ and $R_v=\begin{bmatrix}1 & v0 & 1\end{bmatrix}$ be matrices in $SL_2(\mathbb Z)$ with $u, v\geq 1$. In 1991, Z\'emor developed a hash function based on $L_1$ and $R_1$. Recently, Bromberg, Shpilrain, and Vdovina proposed a hash function based on $L_u$ and $R_v$ when $u=v\in \{2,3\}$. Read More

In this work we have presented current understanding of neutrino-nucleon/nucleus cross sections in the few GeV energy region relevant for a precise determination of neutrino oscillation parameters and CP violation in the leptonic sector. In this energy region various processes like quasielastic and inelastic production of single and multipion production, coherent pion production, kaon, eta, hyperon production, associated particle production as well as deep inelastic scattering processes contribute to the neutrino event rates. Read More

We report on the effect of the strong spin orbit coupling and the Lorentz force on the efficiency of TiO2 based dye sensitized solar cells. Upon inclusion of Ho2O3, due to the strong spin orbit coupling of the rare earth Ho3+ ion, we do see 13 percent enhancement in the efficiency. We attribute such an enhancement in power conversion efficiency to the increased lifetime of the photo-excited excitons. Read More

In this paper we present a framework for risk-averse model predictive control (MPC) of linear systems affected by multiplicative uncertainty. Our key innovation is to consider time-consistent, dynamic risk metrics as objective functions to be minimized. This framework is axiomatically justified in terms of time-consistency of risk assessments, is amenable to dynamic optimization, and is unifying in the sense that it captures a full range of risk preferences from risk-neutral to worst case. Read More

Experimental results and a model are presented to explain the observed unusual enhancement of the effective magnetic anisotropy Keff with decreasing particle size D from 15 nm to 2.5 nm in {\gamma}-Fe2O3 nanoparticles (NPs). The samples include oleic acid-coated NPs with D = 2. Read More

The Apriori algorithm that mines frequent itemsets is one of the most popular and widely used data mining algorithms. Now days many algorithms have been proposed on parallel and distributed platforms to enhance the performance of Apriori algorithm. They differ from each other on the basis of load balancing technique, memory system, data decomposition technique and data layout used to implement them. Read More

A novel semantic approach to data selection and compression is presented for the dynamic adaptation of IoT data processing and transmission within "wireless islands", where a set of sensing devices (sensors) are interconnected through one-hop wireless links to a computational resource via a local access point. The core of the proposed technique is a cooperative framework where local classifiers at the mobile nodes are dynamically crafted and updated based on the current state of the observed system, the global processing objective and the characteristics of the sensors and data streams. The edge processor plays a key role by establishing a link between content and operations within the distributed system. Read More

We explore the temperature dependent magnetoresistance of bulk insulating topological insulator thin films. Thin films of Bi2Se2Te and BiSbTeSe1.6 were grown using Pulsed Laser Deposition technique and subjected to transport measurements. Read More

The distribution of real and complex zeros of some special entire functions such as Wright, hyper-Bessel, and a special case of generalized hypergeometric functions is studied by using some classical results of Laguerre, P\'olya, Obreschkhoff and Runckel. The obtained results extend the well-known theorem of Hurwitz on complex zeros of Bessel functions of the first kind. Moreover, results on zeros of Bessel function derivatives and cross-product of Bessel functions are also given, which are related to some recent open problems. Read More

In the holographic correspondence of quantum gravity, a global onsite symmetry at the boundary generally translates to a local gauge symmetry in the bulk. In this paper, we extend the tensor network based toy model for holography introduced in [arXiv:1701.04778] to incorporate this feature. Read More

Search of novel two-dimensional giant Rashba semiconductors is a crucial step in the development of the forthcoming nano-spintronics technology. Using first-principle calculations, we study a stable two-dimensional crystal phase of BiSb having buckled honeycomb lattice geometry, which is yet unexplored. The phonon, room temperature molecular dynamics and elastic constant calculations verify the dynamical and mechanical stability of the monolayer at 0~K and at room temperature. Read More

Designing fast and scalable algorithm for mining frequent itemsets is always being a most eminent and promising problem of data mining. Apriori is one of the most broadly used and popular algorithm of frequent itemset mining. Designing efficient algorithms on MapReduce framework to process and analyze big datasets is contemporary research nowadays. Read More

We introduce a toy holographic correspondence based on the multi-scale entanglement renormalization ansatz (MERA) representation of ground states of local Hamiltonians. Given a MERA representation of the ground state of a local Hamiltonian acting on an one dimensional `boundary' lattice, we lift it to a tensor network representation of a quantum state of a dual two dimensional `bulk' hyperbolic lattice. The dual bulk degrees of freedom are associated with the bonds of the MERA, which describe the renormalization group flow of the ground state, and the bulk tensor network is obtained by inserting tensors with open indices on the bonds of the MERA. Read More

This paper presents the two body weak nonleptonic decays of B mesons emitting pseudoscalar (P) and vector (V) mesons within the framework of the diagrammatic approach at flavor SU(3) symmetry level. Using the decay amplitudes, we are able to relate the branching fractions of B PV decays induced by both b c and b u transitions, which are found to be well consistent with the measured data. We also make predictions for some decays, which can be tested in future experiments. Read More

This work addresses the problem of extracting deeply learned features directly from compressive measurements. There has been no work in this area. Existing deep learning tools only give good results when applied on the full signal, that too usually after preprocessing. Read More

Currently there are two predominant ways to train deep neural networks. The first one uses restricted Boltzmann machine (RBM) and the second one autoencoders. RBMs are stacked in layers to form deep belief network (DBN); the final representation layer is attached to the target to complete the deep neural network. Read More

We compute invariants of quadratic forms associated to orthogonal hypergeometric groups of degree five. This allows us to determine some commensurabilities between these groups, as well as to say when some thin groups cannot be conjugate to each other. Read More

A Monte Carlo algorithm typically simulates a prescribed number of samples, taking some random real time to complete the computations necessary. This work considers the converse: to impose a real-time budget on the computation, so that the number of samples simulated is random. To complicate matters, the real time taken for each simulation may depend on the sample produced, so that the samples themselves are not independent of their number, and a length bias with respect to computation time is introduced. Read More

We present nonlinear optical absorption properties of pulsed laser deposited thin films of topological insulator (TI), Bi2Se3 on quartz substrate, using open aperture Z - scan technique. The saturable intensity of as-deposited thin films has been found remarkably improved by an order of magnitude compared to the values reported earlier in the literature. Past results from the literature are inconclusive in establishing whether the saturable absorption is coming from surface states or the bulk. Read More

The deliberate insertion of magnetic Mn dopants in the Fe sites of the optimally-doped SmFeAsO0.88-F0.12 iron-based superconductor can modify in a controlled way its electronic properties. Read More

We present the results for antineutrino induced quasielastic hyperon production from nucleon and nuclear targets \cite{Alam:2014bya,Singh:2006xp}. The inputs are the nucleon-hyperon(N--Y) transition form factors determined from the analysis of neutrino-nucleon scattering and semileptonic decays of neutron and hyperons using SU(3) symmetry. The calculations for the nuclear targets are done in local density approximation. Read More

We present the results of (anti)neutrino induced CCQE cross sections from some nuclear targets in the energy region of $E_\nu \le 1 GeV$. The aim of the study is to confront electron and muon production cross sections relevant for $\nu_\mu \leftrightarrow \nu_e$ or $\bar\nu_\mu \leftrightarrow \bar\nu_e$ oscillation experiments. The effects due to lepton mass and its kinematic implications, second class currents and uncertainties in the axial and pseudoscalar form factors are discussed for (anti)neutrino induced reaction cross sections on free nucleon as well as the nucleons bound in a nucleus where nuclear medium effects influence the cross section. Read More

In this work, we have discussed the recent developments that have taken place to understand the differences in the weak $F_{2A}^{Weak} (x,Q^2)$ and electromagnetic $F_{2A}^{EM} (x,Q^2)$ nuclear structure functions. Also we present the results of our work on nuclear medium effects on $F_{2A}^{Weak} (x,Q^2)$ and $F_{2A}^{EM} (x,Q^2)$ for a wide range of $x$ and $Q^2$. These results have been obtained using a microscopic nuclear model, where to incorporate nuclear medium effects, Fermi motion, binding energy, nucleon correlations, mesonic contributions from pion and rho mesons and shadowing effects are considered. Read More

2016Nov
Affiliations: 1IBISC, University d'Evry Val d'Essonne, France, 2IBISC, University d'Evry Val d'Essonne, France, 3Stony Brook University, Stony Brook, NY, USA

In this paper, we study the $k$-forest problem in the model of resource augmentation. In the $k$-forest problem, given an edge-weighted graph $G(V,E)$, a parameter $k$, and a set of $m$ demand pairs $\subseteq V \times V$, the objective is to construct a minimum-cost subgraph that connects at least $k$ demands. The problem is hard to approximate---the best-known approximation ratio is $O(\min\{\sqrt{n}, \sqrt{k}\})$. Read More

The premartensite state, considered to be a precursor state of the martensite phase has been intensively investigated in shape memory and magnetic shape memory alloys (MSMAs). The thermodynamic stability of the premartensite phase and its relation to the martensitic phase is still not clear, especially in MSMAs, even though it is critical to understand the functional properties of these alloys. We present here unambiguous evidence for macroscopic symmetry breaking leading to robust Bain distortion of the premartensite phase in Ni2MnGa MSMA doped with 10% Pt through a high resolution synchrotron x-ray diffraction study. Read More

Recent work in model-agnostic explanations of black-box machine learning has demonstrated that interpretability of complex models does not have to come at the cost of accuracy or model flexibility. However, it is not clear what kind of explanations, such as linear models, decision trees, and rule lists, are the appropriate family to consider, and different tasks and models may benefit from different kinds of explanations. Instead of picking a single family of representations, in this work we propose to use "programs" as model-agnostic explanations. Read More

The origin of incommensurate structural modulation in Ni-Mn based magnetic shape memory Heusler alloys is still an unresolved issue inspite of intense focus on this due to the linkage between high magnetic field induced strain and modulated structure. The presence of non-uniform displacement of atoms from their mean positions and phason broadening of satellite peaks of the modulated structure of the martensite phase in Ni2MnGa can be explained in terms of the electronic stability model. On the other hand, the alternative model of modulation in such magnetic shape memory alloys based on the concept of adaptivity predicts uniform atomic displacement of all the atoms but there is no experimental evidence for the proof of this concept till now. Read More

At the core of interpretable machine learning is the question of whether humans are able to make accurate predictions about a model's behavior. Assumed in this question are three properties of the interpretable output: coverage, precision, and effort. Coverage refers to how often humans think they can predict the model's behavior, precision to how accurate humans are in those predictions, and effort is either the up-front effort required in interpreting the model, or the effort required to make predictions about a model's behavior. Read More