arXiv subjects

Inderpreet Kaur

Publications and source records attributed to Inderpreet Kaur.

7 recordsLinked to original sources

arXiv2026

Photon-mediated thermodynamics and density fluctuations in an ensemble of laser-cooled Cesium atoms

We present an experimental study of detuning-dependent properties of a laser-cooled cesium cloud in a magneto-optical trap. Fluorescence images are used to extract the cloud size, shot-to-shot width fluctuations, optical depth, density profiles, and spatial density fluctuation spectra as the trapping-laser detuning is varied. Near resonance, the cloud exhibits larger spatial extent, increased width fluctuations, higher optical depth, and enhanced density-fluctuation power, while larger detunings produce a more reproducible and spatially confined cloud. The measured density profiles are analysed phenomenologically using a generalized Lane-Emden model with a polytropic equation of state, yielding detuning-dependent effective fit parameters in a weak-interaction regime. Power-spectrum and autocorrelation analyses reveal reproducible scale-dependent density correlations. The results provide a quantitative characterization of detuning-dependent radiative and collective effects in a cesium MOT and establish a basis for future measurements that can more directly test nonequilibrium transport and photon-mediated interaction models.

cond-mat.quant-gas↗

arXiv2026

On the Performance of Malware Detection Classifiers Using Hardware Performance Counters

Malware detection using Hardware Performance Counters (HPC) has emerged as a promising solution to improve the security of computing systems as a complement to antivirus software. Hardware-based malware detectors (HMD) use Machine Learning (ML) classifiers to detect malicious application patterns. The inputs to ML classifiers are low-level performance features known as HPCs, hardware-related activity data collected from a processor at run time to profile the low-level microarchitectural behavior of an application. This paper proposes malware detection using HPCs and machine learning classifiers and highlights the effectiveness of malware detection at run-time. We use ensemble learning techniques to improve the performance of the hardware-based malware detectors, which reduces the number of necessary micro-architectural events. This improves the processor's efficiency by eliminating the need to run an application several times since a processor can measure only 2 to 8 events at a cycle. We use 18 machine-learning models along with two ensemble learning methods to evaluate the malware detection performance, creating a total of 144 different configurations. The experimental results show that the ensemble learning-based malware detection with 2 HPCs using the ensemble technique outperforms standard classifiers with 8 HPCs by up to 10%. It also matches the performance of standard ML-based detectors that use 16 HPCs while requiring only 4 HPCs, thereby enabling effective run-time malware detection.

cs.CR↗

arXiv2024

Commensurate supersolids and re-entrant transitions in an extended Bose-Hubbard ladder

We investigate the ground state phases of an extended Bose-Hubbard ladder of unit filling via the density-matrix-renormalization-group method and, in particular, the effect of rung-hoppings. In contrast to a single-chain, a commensurate supersolid emerges, and based on the Luttinger parameter, we classify them into two types. The latter leads to a reentrant gapless behavior as the onsite interaction is increased while keeping all other parameters intact. A reentrant gapped transition is also found as a function of nearest-neighbor interactions. Further, we show that the string order characterizing the Haldane phase vanishes for a finite inter-chain hopping amplitude, however small it is. Finally, we propose two experimental platforms to observe our findings, using either dipolar atoms or polar molecules and Rydberg admixed atoms.

cond-mat.quant-gas↗

arXiv2024

Stripe and checkerboard patterns in a stack of driven quasi-one-dimensional dipolar condensates

The emergence of transient checkerboard and stripe patterns in a stack of driven quasi-one-dimensional homogeneous dipolar condensates is studied. The parametric driving of the $s$-wave scattering length leads to the excitation of the lowest collective Bogoliubov mode. The character of the lowest mode depends critically on the orientation of the dipoles, corresponding to out-of-phase and in-phase density modulations in neighboring condensates, resulting in checkerboard and stripe patterns. Further, we show that a dynamical transition between the checkerboard and stripe patterns can be realized by quenching the dipole orientation either linearly or abruptly once the initial pattern is formed via periodic driving.

cond-mat.quant-gas↗

arXiv2021

Bogoliubov spectrum and the dynamic structure factor in a quasi-two-dimensional spin-orbit coupled BEC

We compute the the Bogoliubov-de-Gennes excitation spectrum in a trapped two-component spin-orbit-coupled (SOC) Bose-Einstein condensate (BEC) in quasi-two-dimensions as a function of linear and angular momentum and analyse them. The excitation spectrum exhibits a minima-like feature at finite momentum for the immiscible SOC-BEC configuration. We augment these results by computing the dynamic structure factor in the density and pseudo-spin sector, and discuss its interesting features that can be experimentally measured through Bragg spectroscopy of such ultra cold-condensate.

cond-mat.quant-gas↗

arXiv2020

(2+1)$-dimensional sonic black hole from spin-orbit coupled Bose-Einstein condensate and its analogue Hawking radiation

We study the properties of a $2+1$ dimensional Sonic black hole (SBH) that can be realised, in a quasi-two-dimensional two-component spin-orbit coupled Bose-Einstein condensate (BEC). The corresponding equation for phase fluctuations in the total density mode that describes phonon field in the hydrodynamic approximation is described by a scalar field equation in $2+1$ dimension whose space-time metric is significantly different from that of the SBH realised from a single component BEC that was studied experimentally, and, theoretically meticulously in literature. Given the breakdown of the irrotationality constraint of the velocity field in such spin-orbit coupled BEC, we study in detail how the time evolution of such condensate impacts the various properties of the resulting SBH. By time evolving the condensate in a suitably created laser-induced potential, we show that such a sonic black hole is formed, in an annular region bounded by inner and outer event horizon as well as elliptical ergo-surfaces. We observe amplifying density modulation due to the formation of such sonic horizons and show how they change the nature of analogue Hawking radiation emitted from such sonic black hole by evaluating the density-density correlation at different times, using the truncated Wigner approximation (TWA) for different values of spin-orbit coupling parameters. We finally investigate the thermal nature of such analogue Hawking radiation.

cond-mat.quant-gas↗

arXiv2016

Turbulence and fire-spotting effects into wild-land fire simulators

This paper presents a mathematical approach to model the effects of phenomena with random nature such as turbulence and fire-spotting into the existing wildfire simulators. The formulation proposes that the propagation of the fire-front is the sum of a drifting component (obtained from an existing wildfire simulator without turbulence and fire-spotting) and a random fluctuating component. The modelling of the random effects is embodied in a probability density function accounting for the fluctuations around the fire perimeter which is given by the drifting component. In past, this formulation has been applied to include these random effects into a wildfire simulator based on an Eulerian moving interface method, namely the Level Set Method (LSM), but in this paper the same formulation is adapted for a wildfire simulator based on a Lagrangian front tracking technique, namely the Discrete Event System Specification (DEVS). The main highlight of the present study is the comparison of the performance of a Lagrangian and an Eulerian moving interface method when applied to wild-land fire propagation. Simple idealised numerical experiments are used to investigate the potential applicability of the proposed formulation to DEVS and to compare its behaviour with respect to the LSM. The results show that DEVS based wildfire propagation model qualitatively improves its performance (e.g., reproducing flank and back fire, increase in fire spread due to pre-heating of the fuel by hot air and firebrands, fire propagation across no fuel zones, secondary fire generation, \dots). Though the results presented here are devoid of any validation exercise and provide only a proof of concept, they show a strong inclination towards an intended operational use. The existing LSM or DEVS based operational simulators like WRF-SFIRE and ForeFire respectively can serve as an ideal basis for the same.

physics.ao-ph↗