arXiv subjects

Ankit Shukla

Publications and source records attributed to Ankit Shukla.

At least 19 recordsLinked to original sources

arXiv2025

Influence of thermal noise on the field-driven dynamics of the non-collinear antiferromagnet Mn3Sn

$\mathrm{Mn_3Sn}(0\overline{1}\overline{1}0)[0001]$ experiences a tensile strain when grown epitaxially on $\mathrm{MgO}(110)[001]$, and thus the energy landscape changes from six-fold symmetry to two-fold symmetry. External magnetic field further breaks the symmetry and the resulting energy landscape is sensitive to the field orientation relative to the easy axis. In the presence of thermal noise, the relaxation of the magnetic octupole moment in a strained Mn$_3$Sn film is composed of four distinct escape processes involving the two saddle points and two equilibrium states in the energy landscape. Here, we apply harmonic transition-state theory to derive analytical expressions for the inter-well escape time and octupole moment relaxation time, both influenced by an external symmetry-breaking magnetic field and finite thermal noise in the intermediate-to-high damping regime. The analytical predictions are in strong agreement with comprehensive numerical simulations based on coupled LLG equations. The results presented here are crucial toward realizing Mn$_3$Sn's applications in random number generation and probabilistic computing.

cond-mat.mes-hall↗

arXiv2024

LWIRPOSE: A novel LWIR Thermal Image Dataset and Benchmark

Human pose estimation faces hurdles in real-world applications due to factors like lighting changes, occlusions, and cluttered environments. We introduce a unique RGB-Thermal Nearly Paired and Annotated 2D Pose Dataset, comprising over 2,400 high-quality LWIR (thermal) images. Each image is meticulously annotated with 2D human poses, offering a valuable resource for researchers and practitioners. This dataset, captured from seven actors performing diverse everyday activities like sitting, eating, and walking, facilitates pose estimation on occlusion and other challenging scenarios. We benchmark state-of-the-art pose estimation methods on the dataset to showcase its potential, establishing a strong baseline for future research. Our results demonstrate the dataset's effectiveness in promoting advancements in pose estimation for various applications, including surveillance, healthcare, and sports analytics. The dataset and code are available at https://github.com/avinres/LWIRPOSE

cs.CV↗

arXiv2024

Spintronic devices and applications using noncollinear chiral antiferromagnets

Antiferromagnetic materials have a vanishingly small net magnetization, which generates weak dipolar fields and makes them robust against external magnetic perturbation and rapid magnetization dynamics, as dictated by the geometric mean of their exchange and anisotropy energies. However, experimental and theoretical techniques to detect and manipulate the antiferromagnetic order in a fully electrical manner must be developed to enable advanced spintronic devices with antiferromagnets (AFMs) as their active spin-dependent elements. Among the various AFMs, conducting AFMs offer high electrical and thermal conductivities and strong electron-spin-phonon interactions. Noncollinear metallic AFMs with negative chirality, including Mn3Sn, Mn3Ge, and Mn3GaN, offer rich physics that arises from their topology. In this review article, we introduce the crystal structure and the physical phenomena observed in negative chirality AFMs. Experimental and theoretical advances related to current-induced dynamics on the spin structure of Mn3Sn are discussed. We then present a potential AFM spintronic device that can serve as a non-volatile memory, high-frequency signal generator, neuron emulator, and even a probabilistic bit, depending on the design parameters and the input stimuli, i.e., amplitude and pulse width of the injected spin current and the external magnetic field. In this device, spin-orbit torques can be used to manipulate the order parameter, while the device state can be read via tunneling magnetoresistance. We also present analytic models that relate the performance characteristics of the device with its design parameters, thus enabling a rapid technology-device assessment. Effects of Joule heating and thermal noise on the device characteristics are briefly discussed. We close the paper by summarizing the status of research and present our outlook in this rapidly evolving research field.

cond-mat.mtrl-sci↗

arXiv2024

Behavior Trees with Dataflow: Coordinating Reactive Tasks in Lingua Franca

Behavior Trees (BTs) provide a lean set of control flow elements that are easily composable in a modular tree structure. They are well established for modeling the high-level behavior of non-player characters in computer games and recently gained popularity in other areas such as industrial automation. While BTs nicely express control, data handling aspects so far must be provided separately, e. g. in the form of blackboards. This may hamper reusability and can be a source of nondeterminism. We here present a dataflow extension to BTs that explicitly models data relations and communication. We provide a combined textual/graphical approach in line with modern, productivity-enhancing pragmatics-aware modeling techniques. We realized and validated that approach in the recently introduced polyglot coordination language Lingua Franca (LF).

cs.PL↗

arXiv2023

Temperature-Resilient True Random Number Generation with Stochastic Actuated Magnetic Tunnel Junction Devices

Nanoscale magnetic tunnel junction (MTJ) devices can efficiently convert thermal energy in the environment into random bitstreams for computational modeling and cryptography. We recently showed that perpendicular MTJs activated by nanosecond pulses can generate true random numbers at high data rates. Here, we explore the dependence of probability bias-the deviations from equal probability (50/50) 0/1 bit outcomes-of such devices on temperature, pulse amplitude, and duration. Our experimental results and device model demonstrate that operation with nanosecond pulses in the ballistic limit minimizes variation of probability bias with temperature to be far lower than that of devices operated with longer-duration pulses. Further, operation in the short-pulse limit reduces the bias variation with pulse amplitude while rendering the device more sensitive to pulse duration. These results are significant for designing TRNG MTJ circuits and establishing operating conditions.

cond-mat.mes-hall↗

arXiv2023

Reduced sensitivity to process, voltage and temperature variations in activated perpendicular magnetic tunnel junctions based stochastic devices

True random number generators (TRNGs) are fundamental building blocks for many applications, such as cryptography, Monte Carlo simulations, neuromorphic computing, and probabilistic computing. While perpendicular magnetic tunnel junctions (pMTJs) based on low-barrier magnets (LBMs) are natural sources of TRNGs, they tend to suffer from device-to-device variability, low speed, and temperature sensitivity. Instead, medium-barrier magnets (MBMs) operated with nanosecond pulses - denoted, stochastic magnetic actuated random transducer (SMART) devices - are potentially superior candidates for such applications. We present a systematic analysis of spin-torque-driven switching of MBM-based pMTJs (Eb ~ 20 - 40 kBT) as a function of pulse duration (1 ps to 1 ms), by numerically solving their macrospin dynamics using a 1-D Fokker-Planck equation. We investigate the impact of voltage, temperature, and process variations (MTJ dimensions and material parameters) on the switching probability of the device. Our findings indicate SMART devices activated by short-duration pulses (< 1 ns) are much less sensitive to process-voltage-temperature (PVT) variations while consuming lower energy (~ fJ) than the same devices operated with longer pulses. Our results show a path toward building fast, energy-efficient, and robust TRNG hardware units for solving optimization problems.

physics.app-ph↗

arXiv2023

Impact of strain on the SOT-driven dynamics of thin film Mn$_3$Sn

Mn$_3$Sn, a metallic antiferromagnet with an anti-chiral 120$^\circ$ spin structure, generates intriguing magneto-transport signatures such as a large anomalous Hall effect, spin-polarized current with novel symmetries, anomalous Nernst effect, and magneto-optic Kerr effect. When grown epitaxially as MgO(110)[001]$\parallel$ Mn$_3$Sn($0\bar{1}\bar{1}0$)[0001], Mn$_3$Sn experiences a uniaxial tensile strain, which changes the bulk six-fold anisotropy landscape to a perpendicular magnetic anisotropy with two stable states. In this work, we investigate the field-assisted spin orbit-torque (SOT)-driven response of the order parameter in single-domain Mn$_3$Sn with uniaxial tensile strain. We find that for a non-zero external magnetic field, the order parameter can be switched between the two stable states if the magnitude of the input current is between two field-dependent critical currents. Below the lower critical current, the order parameter exhibits a stationary state in the vicinity of the initial stable state. On the other hand, above the higher critical current, the order parameter shows oscillatory dynamics which could be tuned from the 100's of megahertz to the gigahertz range. We obtain approximate expressions of the two critical currents and find them to agree very well with the numerical simulations for experimentally relevant magnetic fields. We also obtain unified functional form of the switching time versus the input current for different magnetic fields. Finally, we show that for lower values of Gilbert damping ($\alpha \leq 2\times 10^{-3}$), the critical currents and the final steady states depend significantly on the damping constant. The numerical and analytic results presented in our work can be used by both theorists and experimentalists to understand the SOT-driven order dynamics in PMA Mn$_3$Sn and design future experiments and devices.

cond-mat.mtrl-sci↗

arXiv2023

Resiliency Analysis of LLM generated models for Industrial Automation

This paper proposes a study of the resilience and efficiency of automatically generated industrial automation and control systems using Large Language Models (LLMs). The approach involves modeling the system using percolation theory to estimate its resilience and formulating the design problem as an optimization problem subject to constraints. Techniques from stochastic optimization and regret analysis are used to find a near-optimal solution with provable regret bounds. The study aims to provide insights into the effectiveness and reliability of automatically generated systems in industrial automation and control, and to identify potential areas for improvement in their design and implementation.

cs.SE↗

arXiv2023

Physics-Based Modeling and Validation of 2D Schottky Barrier Field-Effect Transistors

In this work, we describe the charge transport in two-dimensional (2D) Schottky barrier field-effect transistors (SB-FETs) based on the carrier injection at the Schottky contacts. We first develop a numerical model for thermionic and field-emission processes of carrier injection that occur at a Schottky contact. The numerical model is then simplified to yield an analytic equation for current versus voltage ($I$-$V$) in the SB-FET. The lateral electric field at the junction, controlling the carrier injection, is obtained by accurately modeling the electrostatics and the tunneling barrier width. Unlike previous SB-FET models that are valid for near-equilibrium conditions, this model is applicable for a broad bias range as it incorporates the pertinent physics of thermionic, thermionic field-emission, and field-emission processes from a 3D metal into a 2D semiconductor. The $I$-$V$ model is validated against the measurement data of 2-, 3-, and 4-layer ambipolar MoTe$_2$ SB-FETs fabricated in our lab, as well as the published data of unipolar 2D SB-FETs using MoS$_2$. Finally, the model's physics is tested rigorously by comparing model-generated data against TCAD simulation data.

physics.app-ph↗

arXiv2023

Content Addressable Memories and Transformable Logic Circuits Based on Ferroelectric Reconfigurable Transistors for In-Memory Computing

As a promising alternative to the Von Neumann architecture, in-memory computing holds the promise of delivering high computing capacity while consuming low power. Content addressable memory (CAM) can implement pattern matching and distance measurement in memory with massive parallelism, making them highly desirable for data-intensive applications. In this paper, we propose and demonstrate a novel 1-transistor-per-bit CAM based on the ferroelectric reconfigurable transistor. By exploiting the switchable polarity of the ferroelectric reconfigurable transistor, XOR/XNOR-like matching operation in CAM can be realized in a single transistor. By eliminating the need for the complementary circuit, these non-volatile CAMs based on reconfigurable transistors can offer a significant improvement in area and energy efficiency compared to conventional CAMs. NAND- and NOR-arrays of CAMs are also demonstrated, which enable multi-bit matching in a single reading operation. In addition, the NOR array of CAM cells effectively measures the Hamming distance between the input query and stored entries. Furthermore, utilizing the switchable polarity of these ferroelectric Schottky barrier transistors, we demonstrate reconfigurable logic gates with NAND/NOR dual functions, whose input-output mapping can be transformed in real-time without changing the layout. These reconfigurable circuits will serve as important building blocks for high-density data-stream processors and reconfigurable Application-Specific Integrated Circuits (r-ASICs). The CAMs and transformable logic gates based on ferroelectric reconfigurable transistors will have broad applications in data-intensive applications from image processing to machine learning and artificial intelligence.

cond-mat.mes-hall↗

arXiv2023

Order parameter dynamics in Mn$_3$Sn driven by DC and pulsed spin-orbit torques

We numerically investigate and develop analytic models for both the DC and pulsed spin-orbit-torque (SOT)-driven response of order parameter in single-domain Mn$_3$Sn, which is a metallic antiferromagnet with an anti-chiral 120$^\circ$ spin structure. We show that DC currents above a critical threshold can excite oscillatory dynamics of the order parameter in the gigahertz to terahertz frequency spectrum. Detailed models of the oscillation frequency versus input current are developed and found to be in excellent agreement with the numerical simulations of the dynamics. In the case of pulsed excitation, the magnetization can be switched from one stable state to any of the other five stable states in the Kagome plane by tuning the duration or the amplitude of the current pulse. Precise functional forms of the final switched state versus the input current are derived, offering crucial insights into the switching dynamics of Mn$_3$Sn. The readout of the magnetic state can be carried out via either the anomalous Hall effect, or the recently demonstrated tunneling magnetoresistance in an all-Mn$_3$Sn junction. We also discuss possible disturbance of the magnetic order due to heating that may occur if the sample is subject to large currents. Operating the device in pulsed mode or using low DC currents reduces the peak temperature rise in the sample due to Joule heating. Our predictive modeling and simulation results can be used by both theorists and experimentalists to explore the interplay of SOT and the order dynamics in Mn$_3$Sn, and to further benchmark the device performance.

cond-mat.mtrl-sci↗

arXiv2023

A True Random Number Generator for Probabilistic Computing using Stochastic Magnetic Actuated Random Transducer Devices

Magnetic tunnel junctions (MTJs), which are the fundamental building blocks of spintronic devices, have been used to build true random number generators (TRNGs) with different trade-offs between throughput, power, and area requirements. MTJs with high-barrier magnets (HBMs) have been used to generate random bitstreams with $\lesssim$ 200~Mb/s throughput and pJ/bit energy consumption. A high temperature sensitivity, however, adversely affects their performance as a TRNG. Superparamagnetic MTJs employing low-barrier magnets (LBMs) have also been used for TRNG operation. Although LBM-based MTJs can operate at low energy, they suffer from slow dynamics, sensitivity to process variations, and low fabrication yield. In this paper, we model a TRNG based on medium-barrier magnets (MBMs) with perpendicular magnetic anisotropy. The proposed MBM-based TRNG is driven with short voltage pulses to induce ballistic, yet stochastic, magnetization switching. We show that the proposed TRNG can operate at frequencies of about 500~MHz while consuming less than 100~fJ/bit of energy. In the short-pulse ballistic limit, the switching probability of our device shows robustness to variations in temperature and material parameters relative to LBMs and HBMs. Our results suggest that MBM-based MTJs are suitable candidates for building fast and energy-efficient TRNG hardware units for probabilistic computing.

physics.app-ph↗

arXiv2022

Facilitating Change Implementation for Continuous ML-Safety Assurance

We propose a method for deploying a safety-critical machine-learning component into continuously evolving environments where an increased degree of automation in the engineering process is desired. We associate semantic tags with the safety case argumentation and turn each piece of evidence into a quantitative metric or a logic formula. With proper tool support, the impact can be characterized by a query over the safety argumentation tree to highlight evidence turning invalid. The concept is exemplified using a vision-based emergency braking system of an autonomous guided vehicle for factory automation.

cs.SE↗

arXiv2022

Spin-Torque-driven Terahertz Auto Oscillations in Non-Collinear Coplanar Antiferromagnets

We theoretically and numerically study the terahertz auto oscillations in thin-film metallic non-collinear coplanar antiferromagnets (AFMs), such as $\mathrm{Mn_{3}Sn}$ and $\mathrm{Mn_{3}Ir}$, under the effect of anti-damping spin-torque with spin polarization perpendicular to the plane of the film. To obtain the order parameter dynamics in these AFMs, we solve three Landau-Lifshitz-Gilbert equations coupled by exchange interactions assuming both single- and multi-domain (micromagnetics) dynamical processes. In the limit of strong exchange interaction, the oscillatory dynamics of the order parameter in these AFMs, which have opposite chiralities, could be mapped to that of a linear damped-driven pendulum in the case of $\mathrm{Mn_{3}Sn}$, and a non-linear damped-driven pendulum in case of $\mathrm{Mn_{3}Ir}$. The theoretical framework allows us to identify the input current requirements as a function of the material and geometry parameters for exciting an oscillatory response. We also obtain a closed-form approximate solution of the oscillation frequency for large input currents in case of both $\mathrm{Mn_{3}Ir}$ and $\mathrm{Mn_{3}Sn}$. Our analytical predictions of threshold current and oscillation frequency agree well with the numerical results and thus can be used as compact models to design and optimize the auto oscillator. Employing a circuit model, based on the principle of tunnel anisotropy magnetoresistance, we present detailed models of the output power and efficiency versus oscillation frequency of the auto oscillator. Finally, we explore the spiking dynamics of two unidirectional as well as bidirectional coupled AFM oscillators using non-linear damped-driven pendulum equations.

cond-mat.mes-hall↗

arXiv2020

Switching time of spin-torque-driven magnetization in biaxial ferromagnets

We analytically model the magnetization switching time of a biaxial ferromagnet driven by an antidamping-like spin torque. The macrospin magnetization dynamics is mapped to an energy-flow equation, wherein a rational-function approximation of the elliptic integrals for moderate spin current and small damping results in a closed-form expression of the switching time. Randomness in the initial angle of magnetization gives the distribution function of the switching time. The analytic model conforms to the results obtained from Monte Carlo simulation for a broad range of material parameters. Our results can ameliorate design and benchmarking of in-plane spin torque magnetic memory by obviating expensive numerical computation.

physics.app-ph↗

arXiv2019

Improving Reasoning on DQBF

The aim of this PhD project is to develop fast and robust reasoning tools for dependency quantified Boolean formulas (DQBF). In this paper, we outline two properties, autarkies and symmetries, that potentially can be exploited for pre- and in-processing in the DQBF solving process. DQBF extend quantified Boolean formulas (QBF) with non-linear dependencies between the quantified variables. Automated testing and debugging techniques are an essential part of the solvers tool-chain. For rigorous DQBF solver development, we are working on novel automated testing and debugging techniques as successfully established in SAT and QBF solving. The tool is under development.

cs.LO↗

arXiv2019

Introducing Autarkies for DQCNF

Autarkies for SAT can be used for theoretical studies, pre-processing and inprocessing. They generalise satisfying assignments by allowing to leave some clauses "untouched" (no variable assigned). We introduce the natural generalisation to DQCNF (dependency-quantified boolean CNF), with the perspective of SAT translations for special cases. Finding an autarky for DQCNF is as hard as finding a satisfying assignment. Fortunately there are (many) natural autarky-systems, which allow restricting the range of autarkies to a more feasible domain, while still maintaining the good general properties of arbitrary autarkies. We discuss what seems the most fundamental autarky systems, and how the related reductions can be found by SAT solvers.

cs.LO↗

arXiv2018

Synthesis for Vesicle Traffic Systems

Vesicle Traffic Systems (VTSs) are the material transport mechanisms among the compartments inside the biological cells. The compartments are viewed as nodes that are labeled with the containing chemicals and the transport channels are similarly viewed as labeled edges between the nodes. Understanding VTSs is an ongoing area of research and for many cells they are partially known. For example, there may be undiscovered edges, nodes, or their labels in a VTS of a cell. It has been speculated that there are properties that the VTSs must satisfy. For example, stability, i.e., every chemical that is leaving a compartment comes back. Many synthesis questions may arise in this scenario, where we want to complete a partially known VTS under a given property. In the paper, we present novel encodings of the above questions into the QBF (quantified Boolean formula) satisfiability problems. We have implemented the encodings in a highly configurable tool and applied to a couple of found-in-nature VTSs and several synthetic graphs. Our results demonstrate that our method can scale up to the graphs of interest.

q-bio.SC↗