Search arXiv⌕ Search

arXiv subjects

Sunil Kumar

Publications and source records attributed to Sunil Kumar.

At least 19 recordsLinked to original sources
arXiv2026

Transition metal (group V) doping induced spin and valley polarization in MoS$_2$ monolayer

Doping in two-dimensional materials has emerged as an effective tool for modulating their electronic properties and thereby enabling their multifunctional applications. In this work, we present a first-principles study on induced effective magnetic moment and metallicity in MoS$_2$ monolayer by substitutional doping of group-5 transition metal (TM) elements -- V, Nb and Ta. From our study, we observe that the V doping induces half-metallicity, whereas metallic characteristics are observed in the case of Nb and Ta doping. Moreover, V and Ta-doped MoS$_2$ monolayers are observed to show total induced magnetic moments of 0.922 and 0.624 $\mu_{\rm B}$, respectively. Importantly, the combined effects of strong spin-orbit coupling (SOC), broken inversion symmetry, and structural asymmetry is observed to lead to a permanent valley polarization in the V- and Ta-MoS$_2$ systems. In particular, we observed a valley polarization of 121 and 21 meVs for V and Ta-doped MoS$_2$, respectively. Furthermore, an enhanced piezoelectric coefficient for the doped systems is observed compared to pristine MoS$_2$. Notably, the simultaneous presence of half-metallicity, substantial valley polarization, and enhanced piezoelectricity in V-doped MoS$_2$ establishes this system as a promising multifunctional platform for next-generation spintronic, valleytronic, and piezoelectric nanodevices. Overall, our findings provide fundamental insights into engineering coupled spin-valley-mechanical degrees of freedom in two-dimensional materials for advanced quantum and nanoelectronic applications.

cond-mat.mtrl-sci↗
arXiv2026

Rate-Dependent Reversibility and Lithium Losses in Hybrid Anode-Collector Metal Electrodes

Understanding how practical lithium storage capacity varies with charge-discharge rate is crucial for designing durable anode free lithium batteries. We examine the lithiation behavior of single element metal electrodes-Al (alloying), Mg (solid solution intercalation), Ag (solid solution then alloying), and Cu (surface Li plating)-to determine how their mechanisms influence reversibility, measured by coulombic efficiency. Using electrochemistry combined with depth resolved ion beam profiling, we map local coulombic efficiency across current densities and identify dominant lithium loss pathways. Ag uniquely sustains fast kinetics and high reversibility at elevated rates due to rapid formation of gamma brass-type alloy phases. In contrast, Mg and Al show increasing irreversibility from kinetically or structurally driven Li trapping, while Cu exhibits the largest losses through porous, highly reactive plated lithium. These results reveal fundamental limits of anode free systems that depend on reversible Li plating without excess lithium and underscore the importance of metal selection for stable, high rate performance.

cond-mat.mtrl-sci↗
arXiv2025

Excitonic shift current induced broadband THz pulse emission efficiency of layered MoS2 crystals

Following the ultrafast photoexcitation of a semiconductor, it embodies competing dynamics among photocarriers, many-body transient states of highly energetic excitons, and electron-hole liquid. Here, we show that femtosecond optical pulse excitation induces transient excitonic shift current contributing to stronger THz emission from a single crystalline bulk MoS2 at low temperatures. The control of dominating excitonic shift current is elucidated from excitation density dependent experiments at varying temperatures. A strong decrease in the excitonic contribution beyond a critical fluence of 150microJ/cm^2 is observed at a very low temperature of 20K. This behavior suggests the formation of a new quantum condensate, i.e., the electron-hole liquid, in the regime when the exciton density is overwhelmingly large that the average spacing between exciton pairs is comparable to the exciton radius. Furthermore, the exciton density dependent THz emission at varying temperatures is consistent with the Varshni model and the crystal Debye temperature of 260K.

cond-mat.mtrl-sci↗
arXiv2025

Reinforcing VLMs to Use Tools for Detailed Visual Reasoning Under Resource Constraints

Despite tremendous recent advances in large model reasoning ability, vision-language models (VLMs) still struggle with detailed visual reasoning, especially when compute resources are limited. To address this challenge, we draw inspiration from methods like Deepseek-r1 for VLMs and train smaller-scale models with Group Relative Policy Optimization (GRPO) to use external tools such as zoom. The greatest benefit is obtained with a combination of GRPO learning, a simple reward structure, a simplified tool-calling interface, allocating additional tokens to the result of the tool call, and a training data mix that over-represents visually difficult examples. Compared to similarly-sized baseline models, our method achieves better performance on some visual question-answering (VQA) tasks, thanks to the detailed visual information gathered from the external tool.

cs.LG↗
arXiv2024

Emergence of half-metallic ferromagnetism and valley polarization in transition metal substituted WSTe monolayer

Two-dimensional (2D) Janus materials hold a great importance in spintronic and valleytronic applications due to their unique lattice structures and emergent properties. They intrinsically exhibit both an in-plane inversion and out-of-plane mirror symmetry breakings, which offer a new degree of freedom to electrons in the material. One of the main limitations in the multifunctional applications of these materials is, however, that, they are usually non-magnetic in nature. Here, using first-principles calculations, we propose to induce magnetic degree of freedom in non-magnetic WSTe via doping with transition metal (TM) elements -- Fe, Mn and Co. Further, we comprehensively probe the electronic, spintronic and valleytronic properties in these systems. Our simulations predict intrinsic Rashba and Zeeman-type spin splitting in pristine WSTe. The obtained Rashba parameter is $\sim$ 422 meV\AA\; along the $\Gamma - K$ direction. Our study shows a strong dependence on uniaxial and biaxial strains where we observe an enhancement of $\sim$ 2.1\% with 3\% biaxial compressive strain. The electronic structure of TM-substituted WSTe reveals half-metallic nature for 6.25 and 18.75\% of Fe, 25\% of Mn, and 18.75 and 25\% of Co structures, which leads to 100\% spin polarization. The obtained values of valley polarization 65, 54.4 and 46.3 meV for 6.25\% of Fe, Mn and Co, respectively, are consistent with the literature data for other Janus materials. Further, our calculations show a strain dependent tunability of valley polarization, where we find an increasing (decreasing) trend with uniaxial and biaxial tensile (compressive) strains. We observed a maximum enhancement of $\sim$ 1.72\% for 6.25\% of Fe on application of 3\% biaxial tensile strain.

cond-mat.mtrl-sci↗
arXiv2024

Fine-tuning Vision Classifiers On A Budget

Fine-tuning modern computer vision models requires accurately labeled data for which the ground truth may not exist, but a set of multiple labels can be obtained from labelers of variable accuracy. We tie the notion of label quality to confidence in labeler accuracy and show that, when prior estimates of labeler accuracy are available, using a simple naive-Bayes model to estimate the true labels allows us to label more data on a fixed budget without compromising label or fine-tuning quality. We present experiments on a dataset of industrial images that demonstrates that our method, called Ground Truth Extension (GTX), enables fine-tuning ML models using fewer human labels.

cs.LG↗
arXiv2024

A Hybrid Reactive Routing Protocol for Decentralized UAV Networks

Wireless networks consisting of low SWaP, FW-UAVs are used in many applications, such as monitoring, search and surveillance of inaccessible areas. A decentralized and autonomous approach ensures robustness to failures; the UAVs explore and sense within the area and forward their information, in a multihop manner, to nearby aerial gateway nodes. However, the unpredictable nature of the events, relatively high speed of UAVs, and dynamic UAV trajectories cause the network topology to change significantly over time, resulting in frequent route breaks. A holistic routing approach is needed to support multiple traffic flows in these networks to provide mobility- and congestion-aware, high-quality routes when needed, with low control and computational overheads, using the information collected in a distributed manner. Existing routing schemes do not address all the mentioned issues. We present a hybrid reactive routing protocol for decentralized UAV networks. Our scheme searches routes on-demand, monitors a region around the selected route (the pipe), and proactively switches to an alternative route before the current route's quality degrades below a threshold. We empirically evaluate the impact of pipe width and node density on our ability to find alternate high-quality routes within the pipe and the overhead required to maintain the pipe. Compared to existing reactive routing schemes, our approach achieves higher throughput and reduces the number of route discoveries, overhead, and resulting flow interruptions at different traffic loads, node densities and speeds. Despite having limited network topology information, and low overhead and route computation complexity, our proposed scheme achieves superior throughput to proactive optimized link state routing scheme at different network and traffic settings. We also evaluate the relative performance of reactive and proactive routing schemes.

cs.NI↗
arXiv2024

Investigation of injector-coupled combustion dynamics in a methane-oxygen combustor using large eddy simulation and dynamic mode decomposition

This paper uses a reactive flow large eddy simulation (LES) and decomposition techniques to study combustion instabilities in a methane-oxygen combustor. This work examines two case scenarios to elucidate the significance of injector-chamber frequency coupling as the cause of thermo-acoustic instability. Initial investigation in a well-known benchmark case of the continuously variable resonance combustor (CVRC) reports the potential instability mechanisms and the role of injector-chamber frequency coupling in thermo-acoustic instability. Subsequently, the multi-element rocket combustor case study identifies the critical resonant modes and highlights potential frequency coupling between the injector and the chamber region. The interplay between longitudinal pressure oscillations in the oxidizer post and transverse pressure waves in the chamber is responsible for the enhanced pressure dynamics in the combustor. The present work uses the dynamic mode decomposition (DMD) technique to reveal the evolution of acoustic modes in injector and chamber for CVRC and multi-element combustor. The dominant pressure mode forms found by DMD analysis also showcase the role of injector-chamber frequency coupling in amplified combustion dynamics. The results demonstrate how the predominant cause of combustion instability in rocket combustors can be effectively determined using the high-fidelity LES framework in conjunction with the modal decomposition technique.

physics.flu-dyn↗
arXiv2024

Pipe Routing with Topology Control for UAV Networks

Routing protocols help in transmitting the sensed data from UAVs monitoring the targets (called target UAVs) to the BS. However, the highly dynamic nature of an autonomous, decentralized UAV network leads to frequent route breaks or traffic disruptions. Traditional routing schemes cannot quickly adapt to dynamic UAV networks and/or incur large control overhead and delays. To establish stable, high-quality routes from target UAVs to the BS, we design a hybrid reactive routing scheme called pipe routing that is mobility, congestion, and energy-aware. The pipe routing scheme discovers routes on-demand and proactively switches to alternate high-quality routes within a limited region around the active routes (called the pipe) when needed, reducing the number of route breaks and increasing data throughput. We then design a novel topology control-based pipe routing scheme to maintain robust connectivity in the pipe region around the active routes, leading to improved route stability and increased throughput with minimal impact on the coverage performance of the UAV network.

cs.NI↗
arXiv2024

THz probing of non-trivial topological states in Co2MnGe Heusler alloy thin films

Co2MnGe (CMG) has been demonstrated recently as a half-metallic ferromagnetic Heusler alloy which possesses a topologically non-trivial band structure. This behavior is unique to such systems and hence warrants extensive experimental exploration for potential spintronic and chirality sensitive optoelectonic applications. Here, we demonstrate that an epitaxial thin film of CMG acts as a source of THz radiation upon photoexcitation by optical femtosecond laser pulses. Detailed experiments have revealed that a large contribution to THz emission occurs due to nonmagnetic or spin-independent origin, however, significant contribution in the THz generation is evidenced through excitation light helicity dependent circular photogalvanic effect (CPGE) confirming the presence of topologically non-trivial carriers. Furthermore, we show that not only the topological contribution is easily suppressed but also the overall THz generation efficiency is also affected adversely for the epitaxial films grown at high substrate temperatures.

physics.app-ph↗
arXiv2024

Asynchronous Distributed Coordinated Hybrid Precoding in Multi-cell mmWave Wireless Networks

Asynchronous distributed hybrid beamformers (ADBF) are conceived for minimizing the total transmit power subject to signal-to-interference-plus-noise ratio (SINR) constraints at the users. Our design requires only limited information exchange between the base stations (BSs) of the mmWave multi-cell coordinated (MCC) networks considered. To begin with, a semidefinite relaxation (SDR)-based fully-digital (FD) beamformer is designed for a centralized MCC system. Subsequently, a Bayesian learning (BL) technique is harnessed for decomposing the FD beamformer into its analog and baseband components and construct a hybrid transmit precoder (TPC). However, the centralized TPC design requires global channel state information (CSI), hence it results in a high signaling overhead. An alternating direction based method of multipliers (ADMM) technique is developed for a synchronous distributed beamformer (SDBF) design, which relies only on limited information exchange among the BSs, thus reducing the signaling overheads required by the centralized TPC design procedure. However, the SDBF design is challenging, since it requires the updates from the BSs to be strictly synchronized. As a remedy, an ADBF framework is developed that mitigates the inter-cell interference (ICI) and also control the asynchrony in the system. Furthermore, the above ADBF framework is also extended to the robust ADBF (R-ADBF) algorithm that incorporates the CSI uncertainty into the design procedure for minimizing the the worst-case transmit power. Our simulation results illustrate both the enhanced performance and the improved convergence properties of the ADMM-based ADBF and R-ADBF schemes.

cs.IT↗
arXiv2023

Investigation of Indian stock markets using topological data analysis and geometry-inspired network measures

Geometry-inspired measures (such as discrete Ricci curvatures) and topological data analysis (TDA) based methods (such as persistent homology) have become attractive tools for characterizing the higher-order structure of networks representing the financial systems. In this study, our goal is to perform a comparative analysis of both these approaches, especially by assessing the fragility and systemic risk in the Indian stock markets, which is known for its high volatility and risk. To achieve this goal, we analyze the time series of daily log-returns of stocks comprising the National Stock Exchange (NSE) and the Bombay Stock Exchange (BSE). Specifically, our aim is to monitor the changes in standard network measures, edge-centric discrete Ricci curvatures, and persistent homology based topological measures computed from cross-correlation matrices of stocks. In this study, the edge-centric discrete Ricci curvatures have been employed for the first time in the analysis of the Indian stock markets. The Indian stock markets are known to be less diverse in comparison to the US market, and hence provides us an interesting example. Our results point that, among the persistent homology based topological measures, persistent entropy is simple and more robust than $L^1$-norm and $L^2$-norm of persistence landscape. In a broader comparison between network analysis and TDA, we highlight that the network analysis is sensitive to the way of constructing the networks (threshold or minimum spanning tree), as well as the threshold values used to construct the correlation-based threshold networks. On the other hand, the persistent homology is a more robust approach and is able to capture the higher-order interactions and eliminate noisy data in financial systems, since it does not take into account a single value of threshold but rather a range of values.

physics.soc-ph↗
arXiv2023

A Deep Q-Learning based, Base-Station Connectivity-Aware, Decentralized Pheromone Mobility Model for Autonomous UAV Networks

UAV networks consisting of low SWaP (size, weight, and power), fixed-wing UAVs are used in many applications, including area monitoring, search and rescue, surveillance, and tracking. Performing these operations efficiently requires a scalable, decentralized, autonomous UAV network architecture with high network connectivity. Whereas fast area coverage is needed for quickly sensing the area, strong node degree and base station (BS) connectivity are needed for UAV control and coordination and for transmitting sensed information to the BS in real time. However, the area coverage and connectivity exhibit a fundamental trade-off: maintaining connectivity restricts the UAVs' ability to explore. In this paper, we first present a node degree and BS connectivity-aware distributed pheromone (BS-CAP) mobility model to autonomously coordinate the UAV movements in a decentralized UAV network. This model maintains a desired connectivity among 1-hop neighbors and to the BS while achieving fast area coverage. Next, we propose a deep Q-learning policy based BS-CAP model (BSCAP-DQN) to further tune and improve the coverage and connectivity trade-off. Since it is not practical to know the complete topology of such a network in real time, the proposed mobility models work online, are fully distributed, and rely on neighborhood information. Our simulations demonstrate that both proposed models achieve efficient area coverage and desired node degree and BS connectivity, improving significantly over existing schemes.

cs.NI↗
arXiv2023

Efficient Creation of Ultracold Ground State $^{6}\textrm{Li}^{40}\textrm{K}$ Polar Molecules

We report the creation of ultracold ground state $^{6}\textrm{Li}^{40}\textrm{K}$ polar molecules with high efficiency. Starting from weakly-bound molecules state, stimulated Raman adiabatic passage (STIRAP) is adopted to coherently transfer the molecules to their singlet ro-vibrational ground state $|\textrm{X}^{1}\Sigma^{+},v=0,J=0>$. By employing a singlet STIRAP pathway and low-phase-noise narrow-linewidth lasers, we observed a one-way transfer efficiency of 96(4)\,\%. Held in an optical dipole trap, the lifetime of the ground-state molecules is measured to be 5.0(3)\,ms. The large permanent dipole moment of LiK is confirmed by applying a DC electric field on the molecules and performing Stark shift spectroscopy of the ground state. With recent advances in the quantum control of collisions, our work paves the way for exploring quantum many-body physics with strongly-interacting $^{6}\textrm{Li}^{40}\textrm{K}$ molecules.

cond-mat.quant-gas↗
arXiv2023

Probing defect induced room temperature ferromagnetism in CVD grown MoO3 flakes: A correlation with electronic structure and first principle-based calculations

In this paper, we report the growth of pure {\alpha}-MoO3 micro-flakes by CVD technique and their structural, electronic, optical, and magnetic properties. Samples are annealed at various temperatures in an H2 atmosphere to induce ferromagnetism. All the samples exhibit ferromagnetism at room temperature, and 250oC annealed sample shows the highest magnetic moment of 0.087 emu/g. It is evident from PL data that pristine as well as annealed samples contain different types of defects like oxygen vacancies, surface defects, interstitial oxygen, etc. It is deduced from the analysis of Mo3d and O1s core-level XPS spectra that oxygen vacancies increase up to an annealing temperature of 250oC that correlates with the magnetic moment. Significant changes in the total density of states and also in the magnetic moment for two and three oxygen vacancies are noticed through first-principle-based calculations. It is concluded that the magnetic moment is produced by oxygen vacancies or vacancy clusters, which is consistent with our experimental findings.

cond-mat.mtrl-sci↗
arXiv2023

Error analysis of a high-order fully discrete method for two-dimensional time-fractional convection-diffusion equations exhibiting weak initial singularity

This study presents a novel high-order numerical method designed for solving the two-dimensional time-fractional convection-diffusion (TFCD) equation. The Caputo definition is employed to characterize the time-fractional derivative. A weak singularity at the initial time ($t=0$) is encountered in the considered problem, which is effectively managed by adopting a discretization approach for the time-fractional derivative, where Alikhanov's high-order L2-1$_\sigma$ formula is applied on a non-uniform fitted mesh, resulting in successful tackling of the singularity. A high-order two-dimensional compact operator is implemented to approximate the spatial variables. The alternating direction implicit (ADI) approach is then employed to solve the resulting system of equations by decomposing the two-dimensional problem into two separate one-dimensional problems. The theoretical analysis, encompassing both stability and convergence aspects, has been conducted comprehensively, and it has shown that method is convergent with an order $\mathcal O\left(N_t^{-\min\{3-\alpha,\theta\alpha,1+2\alpha,2+\alpha\}}+h_x^4+h_y^4\right)$, where $\alpha\in(0,1)$ represents the order of the fractional derivative, $N_t$ is the temporal discretization parameter and $h_x$ and $h_y$ represent spatial mesh widths. Moreover, the parameter $\theta$ is utilized in the construction of the fitted mesh.

math.NA↗
arXiv2023

Ultrafast THz probing of nonlocal orbital current in transverse multilayer metallic heterostructures

THz generation from femtosecond photoexcited spintronic heterostructures has recently become a versatile tool for investigating ultrafast spin-transport and transient charge-current in a non-contact and non-invasive manner. The same from the orbital effects is still in the primitive stage. Here, we experimentally demonstrate orbital-to-charge current conversion in metallic heterostructures, consisting of a ferromagnetic layer adjacent to either a light or a heavy metal layer, through detection of the emitted THz pulses. Temperature-dependent experiments help to disentangle the orbital and spin components that are manifested in the respective Hall-conductivities, contributing to THz emission. NiFe/Nb shows the strongest inverse orbital Hall effect with an experimentally extracted value of effective Hall-conductivity, \sigma_SOH^int^eff ~ 195 {\Omega}^(-1){cm}^(-1), while CoFeB/Pt shows maximum contribution from the inverse spin Hall effect. In addition, we observe nearly ten-fold enhancement in the THz emission due to pronounced orbital-transport in W-insertion heavy metal layer in CoFeB/W/Ta heterostructure as compared to the CoFeB/Ta bilayer counterpart.

cond-mat.mtrl-sci↗
arXiv2023

Observational constraint from the heaviest pulsar PSR J0952-0607 on the equation of state of dense matter in relativistic mean field model

In the present work, we constrain the equation of the state of dense matter in the context of heaviest observed neutron star mass M$_{max}$ = 2.35$\pm 0.17$ M$_{\odot}$ for the black widow pulsar PSR J0952-0607. We propose three interactions HPU1, HPU2 and HPU3 (named after Himachal Pradesh University)for the relativistic mean field model which include different combinations of non-linear, self and cross-couplings among isoscalar-scalar $\sigma$, isoscalar-vector $\omega$ and isovector-vector $\rho$ meson fields up to the quartic order. These interactions are in harmony with the finite nuclei and bulk nuclear matter properties. The equations of state computed by using newly generated interactions for the $\beta$-equilibrated nucleonic matter satisfy the heaviest observed neutron star mass M$_{max}$ = 2.35$\pm 0.17$ M$_{\odot}$ for the black widow pulsar PSR J0952-0607. The results for the radius ($R_{1.4}$) and dimensionless tidal deformability (${\Lambda_{1.4}}$) corresponding to the canonical mass are also presented and agree well with the GW170817 event and astrophysical observations. The radius of $2.08M_{\odot}$ neutron star mass is predicted to be in the range $R_{2.08}$ = 12.98 -13.09 Km which also satisfies the NICER observations by Miller et al. (2021) and Riley et al.(2021). A covariance analysis is also performed to assess the theoretical uncertainties of model parameters and to determine their correlations with nuclear matter observables.

nucl-th↗