arXiv subjects

Prashant Sharma

Publications and source records attributed to Prashant Sharma.

At least 19 recordsLinked to original sources

arXiv2026

Scalable Secure Biometric Authentication without Auxiliary Identifiers

The prevalence of biometric authentication has been on the rise due to its ease of use and elimination of weak passwords. To date, most biometric authentication systems have been designed for on-device authentication of the device owner (e.g., smartphones and laptops). Recently, biometric authentication systems have started to emerge that are designed to authenticate users against cloud databases storing representations of biometrics for large numbers of users (potentially millions), such as those facilitating biometric payments. However, the use of a large cloud database introduces a significant attack vector, as a breach of the database could lead to the compromise of all enrolled users' sensitive biometric data. Indeed, all such existing systems either do not adequately protect against such a breach, or are impractical to deploy and use due to their high computational overhead. In this work, we present a new biometric authentication system that provides provable security guarantees against data breaches, while remaining scalable and performant. To do so, we marry artificial intelligence with advanced cryptographic techniques in a novel fashion, providing several optimizations along the way. Our work is the first to show that real-world scalable privacy-preserving biometric authentication without auxiliary identifiers is feasible, and we believe that it will spur widespread industrial adoption and further research in this area.

cs.CR↗

arXiv2026

Collisional-radiative data for tokamak disruption mitigation modeling

Effective tokamak disruption mitigation is crucial for ensuring the safety and integrity of fusion power reactors. Accurate collisional-radiative (CR) modeling of a radiative plasma is a critical component in predictive disruption mitigation design. In this paper, we focus on quasi-steady-state CR modeling applicable to the current quench phase of a tokamak disruption. We employ the ATOMIC collisional-radiative code from the Los Alamos suite and the newly developed Fusion Collisional-Radiative (FCR) code to model the atomic processes, providing high-fidelity data for radiative power loss, as well as average and effective charge states for hydrogen, helium, neon, and argon plasma species over a wide range of tokamak-relevant electron temperatures and electron densities. Fine-structure-resolved CR models are used for hydrogen and helium plasma species, while configuration-average CR models are implemented for neon and argon plasma species. The calculated values are compared with the superconfiguration CR model (FLYCHK) and the commonly used coronal equilibrium approximation to demonstrate the advantages and limitations of each model. To facilitate coupling of high-fidelity CR data to plasma simulation models, we represent the ATOMIC/FCR results over the relevant plasma parameter range using a smooth tensor product B-spline surface in electron temperature and electron density. This approach yields compact coefficient tables that can be evaluated efficiently while preserving spline smoothness across the domain. These data were previously used to examine ways to minimize runaway electrons in a tokamak current quench, and they are now made available in easy-to-use forms for community use and benchmarking.

physics.plasm-ph↗

arXiv2026

Hybrid collisional-radiative modeling for high-fidelity atomic kinetics

The fidelity of collisional-radiative (CR) models is critical for advancing our understanding of radiative properties and ionization balance in fusion plasmas. In this work, we present and evaluate hybrid CR schemes that combine fine-structure resolution with superconfiguration averaging, offering a practical compromise between accuracy and computational efficiency. Two hybrid CR models are developed for helium, lithium, and beryllium, retaining detailed fine-structure states up to selected principal quantum numbers, while higher-lying states are statistically averaged to form superconfigurations. These models are applied to compute radiative power loss, as well as average and effective charge states, across a wide range of electron temperatures and densities. The results are benchmarked against a fully fine-structure-resolved CR model to assess the accuracy of the hybrid approach. The findings demonstrate the versatility of hybrid CR schemes and their suitability for detailed plasma simulations where predictive fidelity must be balanced with computational cost.

physics.plasm-ph↗

arXiv2025

Efficient Numerical Evaluation of Triple Integral Using the Euler's Method and Richardson's Extrapolation

In this study, we employ Euler's method and Richardson's extrapolation to solve a triple integral, which is then transformed into a third-order initial value problem. Our objective is to resolve the computational challenges associated with triple integration by transforming it into an initial value problem. Euler's method is the fundamental numerical technique for approximating the solution, thereby establishing a baseline for accuracy. The precision of our computations is subsequently improved by employing Richardson's extrapolation to reduce errors systematically. This approach not only illustrates the adaptability of numerical methods in solving intricate mathematical problems, but it also emphasizes the significance of strategic error reduction techniques in enhancing computational outcomes. We present the efficacy of this method in solving triple integrals in an efficient manner through experimentation and analysis, thereby making a significant contribution to the fields of numerical computation and mathematical modeling.

math.NA↗

arXiv2025

Civil Servants as Builders: Enabling Non-IT Staff to Develop Secure Python and R Tools

Current digital government literature focuses on professional in-house IT teams, specialized digital service teams, vendor-developed systems, or proprietary low-code/no-code tools. Almost no scholarship addresses a growing middle ground: technically skilled civil servants outside formal IT roles who can write real code but lack a sanctioned, secure path to deploy their work. This paper introduces a limits-aware, open-source and replicable platform that enables such public servants to develop, peer review, and deploy small-scale, domain-specific applications within government networks via a sandboxed, auditable workflow. By combining Jupyter Notebooks, preapproved open-source libraries, and lightweight governance, the platform works within institutional constraints such as procurement rules and IT security policies while avoiding vendor lock-in. Unlike low/no-code approaches, it preserves and enhances civil servants' programming skills, keeping them technically competitive with their private-sector peers. This contribution fills a critical gap, offering a replicable model for public-sector skill retention, resilience, and bottom-up digital transformation.

cs.HC↗

arXiv2024

Rayleigh Taylor Instability in Multiple Finite-Thickness Fluid Layers

We develop a general transfer-matrix formalism for determining the growth rate of the Rayleigh-Taylor instability in a fluid system with spatially varying density and viscosity. We use this formalism to analytically and numerically treat the case of a stratified heterogeneous fluid. We introduce the inviscid-flow approximation in our transfer-matrix formalism to find analytic solutions in the limit of uniform kinematic viscosity for a stratified heterogeneous fluid. We discuss the applicability of these results and the no-acceleration approximation that also yields analytical solutions in the large viscosity limit.

physics.flu-dyn↗

arXiv2022

Current redistribution model of anomalous resistance behaviour in superconductor-topological insulator heterostructures

Anomalous resistance upturn and downturn have been observed on the topological insulator (TI) surface in superconductor-TI (NbN-Bi1.95Sb0.05Se3) heterostructures at ~ mm length scales away from the interface. Magnetotransport measurements were performed to verify that the anomaly is caused due to the superconducting transition of the NbN layer. The possibility of long range superconducting proximity effect due to the spin-polarized TI surface state was ruled out due to the observation of similar anomaly in NbN-Au and NbN-Al heterostructures. It was discovered that the unusual resistance jumps were caused due to current redistribution at the superconductor-TI interface on account of the geometry effects. Results obtained from finite element analysis using COMSOL package has validated the proposed current redistribution (CRD) model of long range resistance anomalies in superconductor-TI and superconductor-metal heterostructures.

cond-mat.supr-con↗

arXiv2022

The constraint of plasma power balance on runaway avoidance

In a post-thermal-quench plasma, mitigated or unmitigated, the plasma power balance is mostly between collisional or Ohmic heating and plasma radiative cooling. In a plasma of atomic mixture $\{n_\alpha\}$ with $\alpha$ labeling the atomic species, the power balance sets the plasma temperature, ion charge state distribution $\{n_\alpha^i\}$ with $i$ the charge number, and through the electron temperature $T_e$ and ion charge state distribution $\{n_\alpha^i\},$ the parallel electric field $E_\parallel.$ Since the threshold electric field for runaway avalanche growth $E_{av}$ is also set by the atomic mixture, ion charge state distribution and its derived quantity, the electron density $n_e,$ the plasma power balance between Ohmic heating and radiative cooling imposes a stringent constraint on the plasma regime for avoiding and minimizing runaways when a fusion-grade tokamak plasma is rapidly terminated.

physics.plasm-ph↗

arXiv2022

PLOD: An Abbreviation Detection Dataset for Scientific Documents

The detection and extraction of abbreviations from unstructured texts can help to improve the performance of Natural Language Processing tasks, such as machine translation and information retrieval. However, in terms of publicly available datasets, there is not enough data for training deep-neural-networks-based models to the point of generalising well over data. This paper presents PLOD, a large-scale dataset for abbreviation detection and extraction that contains 160k+ segments automatically annotated with abbreviations and their long forms. We performed manual validation over a set of instances and a complete automatic validation for this dataset. We then used it to generate several baseline models for detecting abbreviations and long forms. The best models achieved an F1-score of 0.92 for abbreviations and 0.89 for detecting their corresponding long forms. We release this dataset along with our code and all the models publicly in https://github.com/surrey-nlp/PLOD-AbbreviationDetection

cs.CL↗

arXiv2022

An Ensemble Approach to Acronym Extraction using Transformers

Acronyms are abbreviated units of a phrase constructed by using initial components of the phrase in a text. Automatic extraction of acronyms from a text can help various Natural Language Processing tasks like machine translation, information retrieval, and text summarisation. This paper discusses an ensemble approach for the task of Acronym Extraction, which utilises two different methods to extract acronyms and their corresponding long forms. The first method utilises a multilingual contextual language model and fine-tunes the model to perform the task. The second method relies on a convolutional neural network architecture to extract acronyms and append them to the output of the previous method. We also augment the official training dataset with additional training samples extracted from several open-access journals to help improve the task performance. Our dataset analysis also highlights the noise within the current task dataset. Our approach achieves the following macro-F1 scores on test data released with the task: Danish (0.74), English-Legal (0.72), English-Scientific (0.73), French (0.63), Persian (0.57), Spanish (0.65), Vietnamese (0.65). We release our code and models publicly.

cs.CL↗

arXiv2021

Cognition-aware Cognate Detection

Automatic detection of cognates helps downstream NLP tasks of Machine Translation, Cross-lingual Information Retrieval, Computational Phylogenetics and Cross-lingual Named Entity Recognition. Previous approaches for the task of cognate detection use orthographic, phonetic and semantic similarity based features sets. In this paper, we propose a novel method for enriching the feature sets, with cognitive features extracted from human readers' gaze behaviour. We collect gaze behaviour data for a small sample of cognates and show that extracted cognitive features help the task of cognate detection. However, gaze data collection and annotation is a costly task. We use the collected gaze behaviour data to predict cognitive features for a larger sample and show that predicted cognitive features, also, significantly improve the task performance. We report improvements of 10% with the collected gaze features, and 12% using the predicted gaze features, over the previously proposed approaches. Furthermore, we release the collected gaze behaviour data along with our code and cross-lingual models.

cs.CL↗

arXiv2021

Observation of fast current redistribution in an imploding plasma column

Spectroscopic measurements of the magnetic field evolution in a Z-pinch throughout stagnation and with particularly high spatial resolution reveal a sudden current redistribution from the stagnating plasma (SP) to a low density plasma (LDP) at larger radii, while the SP continues to implode. Based on the plasma parameters it is shown that the current is transferred to an increasing-conductance LDP outside the stagnation, a process likely to be induced by the increasing impedance of the SP. Since an LDP often exists around imploding plasmas and in various pulsed-power systems, such a fast current redistribution may dramatically affect the behavior and achievable parameters in these systems.

physics.plasm-ph↗

arXiv2021

Zeptosecond dynamics in atoms: fact or fiction?

Photon exchange due to nuclear bremsstrahlung during nuclear collisions can cause Coulomb excitation in the projectile and the target nuclei. The corresponding process originated in nuclear timescales can also be observed in atomic phenomenon experimentally if it delayed by at least with an attosecond or longer timescales. We have found that this happens due to a mechanism involving the Eisenbud-Wigner-Smith time delay process. We have estimated photoionization time delays in atomic collisions utilizing the nonrelativistic version of random phase approximation with exchange and Hartree-Fock methods. We present three representative processes in which we can observe the phenomena in attosecond timescales even though they originate from excitations in the zeptosecond timescales. Thus the work represents an investigation of parallels between two neighboring areas of physics. Furthermore the present work suggests new possibilities for atomic physics research near the Coulomb barrier energy, where the laser is replaced by nuclear bremsstrahlung.

physics.atom-ph↗

arXiv2021

Exploring a novel model for projectile charge state distribution inside a solid-target

For the first time, we report a theoretical methodology to predict charge state distribution of projectile ions inside a solid-target. The method utilizes either a simple Fermi gas model or an ab initio theoretical method and a certain parameterization of width for the Lorentzian charge state distributions. Results obtained from the two approaches are comparable, but the former has a certain edge over the latter. The projectile charge state distribution inside a solid-target plays a significant role in estimating electron capture cross-sections and then to describe the observed K-shell ionization dynamics. The electron capture process plays a certain role in L-shell ionization dynamics too, but in a test case of Si on Au target the subshell charge sharing contributes a more vital role than the electron capture. Thus, we have validated the present model as a reliable as well as useful for many solid-target based applications viz. tumour therapy, biophysics, accelerators, material science etc.

physics.atom-ph↗

arXiv2021

Significance of high charge state of projectile ions inside the target and its role on electron capture leading to target ionization phenomenon

The K x-ray spectra of different targets (Cu, Zn, and Ge) induced by 3 to 5 MeV/u Si projectile ions have been measured to determine the K-shell ionization cross-section. A significant difference is observed between the measurements and theoretical estimates, with the latter being about 50% below the experimental results. This underestimation} is attributed to the charge-exchange from target K-shell to projectile K- and L-shells. Such observation can only be possible if the projectile ions attain up to H- and He-like charge states. Corresponding projectile charge state fractions have been evaluated from the Lorentzian charge state distribution, where mean charge state is taken from the Fermi gas model [Phys. Rev. Lett. 30, 358 (1973)] and width from the Novikov and Teplova approach [Phys. Lett. A378, 1286-1289 (2014)]. The sum of the direct ionization cross-section and K-K + K-L capture cross-sections gives a good agreement with the measured cross-sections. Furthermore, we have validated this methodology with available data for Si-ion on Ti target. Such results may be useful in many solid target based applications.

physics.atom-ph↗

arXiv2019

Unusual charge exchange by swift heavy ions at solid surfaces

We have employed x-ray spectroscopy to probe the charge changing process only in the bulk of the foil when swift heavy ions pass through it. In contrast, the electromagnetic methods take into account integral effect of the charge changing process in the bulk as well as the charge exchange phenomenon at the surface of the foil. Thus, the difference between the mean charge states so measured from the two methods disentangles the charge exchange phenomenon at the surface from the charge changing process in the bulk and, provides opportunities to refine the understanding of ion-surface interactions. Very surprisingly, up to tens of electrons per event participate in the charge exchange phenomenon during swift heavy ion-surface interactions. This finding has been validated with a series of experiments using several ions (z = 22-35) in the energy range of 1.5-3.0 MeV/u and also verified theoretically with Fermi-gas model. Interestingly, such unusual charge exchange phenomenon could play significant role in x-ray emission of many astrophysical environments, infrared emission bands from range of environments in galaxies, accelerator physics, ion energy losses in solids, heavy ion cancer treatments, inner shell ionization by heavy ions, and surface modifications in nano scale.

physics.atom-ph↗

arXiv2019

Structuring an unordered text document

Segmenting an unordered text document into different sections is a very useful task in many text processing applications like multiple document summarization, question answering, etc. This paper proposes structuring of an unordered text document based on the keywords in the document. We test our approach on Wikipedia documents using both statistical and predictive methods such as the TextRank algorithm and Google's USE (Universal Sentence Encoder). From our experimental results, we show that the proposed model can effectively structure an unordered document into sections.

cs.IR↗

arXiv2016

Real time error detection in metal arc welding process using Artificial Neural Netwroks

Quality assurance in production line demands reliable weld joints. Human made errors is a major cause of faulty production. Promptly Identifying errors in the weld while welding is in progress will decrease the post inspection cost spent on the welding process. Electrical parameters generated during welding, could able to characterize the process efficiently. Parameter values are collected using high speed data acquisition system. Time series analysis tasks such as filtering, pattern recognition etc. are performed over the collected data. Filtering removes the unwanted noisy signal components and pattern recognition task segregate error patterns in the time series based upon similarity, which is performed by Self Organized mapping clustering algorithm. Welder quality is thus compared by detecting and counting number of error patterns appeared in his parametric time series. Moreover, Self Organized mapping algorithm provides the database in which patterns are segregated into two classes either desirable or undesirable. Database thus generated is used to train the classification algorithms, and thereby automating the real time error detection task. Multi Layer Perceptron and Radial basis function are the two classification algorithms used, and their performance has been compared based on metrics such as specificity, sensitivity, accuracy and time required in training.

cs.NE↗