arXiv subjects

Mainak Bandyopadhyay

Publications and source records attributed to Mainak Bandyopadhyay.

4 recordsLinked to original sources

arXiv2026

Mass Spectrometry Studies of Hydrogen Ions Energy Distributions in an ECR- based Large Volume Plasma Source

Plasma is produced in a Large Volume Plasma Source (LVPS; dia. = 1 m, height = 1m) using CW microwaves (= 400 - 600 W, 2.45 GHz), in a compact ECR plasma source (CEPS) attached to LVPS, at hydrogen gas pressures = 1 - 3 mTorr. Plasma expands along the CEPS magnetic field into LVPS. A Hiden Analytical HPR 60 molecular beam mass spectrometer (MBMS) is used to measure the H^- ion energy distribution functions (IEDFs) in the downstream plasma. Previous plasma characterization studies in LVPS indicated favourable downstream plasma conditions for volume production of H^- ions. Measurements conducted with the MBMS probe aligned facing the plasma flow = 80 cm downstream, gave typical H^- count rates = 3 x 10^5 counts /s, at = 400 W, = 1 mTorr, along with a distinct high energy tail (<= 20 eV). These and other results are analyzed in detail. The positive ion spectrum showed the H_3^+ count to be consistently high in all cases (= 60-70 %); the counts for H_2^+ and H^+ were =30-35 % and a =few %. Combining the Langmuir probe (LP) and MBMS data it is possible to determine the approximate densities in front of the MBMS probe aperture. At = 500 W and = 2 mTorr, one finds: n_(H^+) = 9.6 x 10^9 cm^(-3), n_(H_2^+) = 1.7 x 10^10 cm^(-3) and n_(H_3^+) = 4.3 x 10^10 cm^(-3). The corresponding H^- density, = 80 cm downstream is n_(H^-) = 3.9 x 10^8 cm^(-3). Accounting for all H^- losses due to scattering and destruction, one finds the effective mean free path for H^- loss to be = 12.4 cm. Noting that H^- formation takes place about = 10 - 30 cm downstream of the source exit, the approximate average H^- density in the formation zone is determined as = 5.5 x 10^10 cm^(-3). This value is remarkably encouraging for H^- production in volume mode, considering the large chamber volume and area, as well as the very moderate power used for the experiments.

physics.plasm-ph↗

arXiv2026

Attention-ResUNet for Automated Fetal Head Segmentation

Automated fetal head segmentation in ultrasound images is critical for accurate biometric measurements in prenatal care. While existing deep learning approaches have achieved a reasonable performance, they struggle with issues like low contrast, noise, and complex anatomical boundaries which are inherent to ultrasound imaging. This paper presents Attention-ResUNet. It is a novel architecture that synergistically combines residual learning with multi-scale attention mechanisms in order to achieve enhanced fetal head segmentation. Our approach integrates attention gates at four decoder levels to focus selectively on anatomically relevant regions while suppressing the background noise, and complemented by residual connections which facilitates gradient flow and feature reuse. Extensive evaluation on the HC18 Challenge dataset where n = 200 demonstrates that Attention ResUNet achieves a superior performance with a mean Dice score of 99.30 +/- 0.14% against similar architectures. It significantly outperforms five baseline architectures including ResUNet (99.26%), Attention U-Net (98.79%), Swin U-Net (98.60%), Standard U-Net (98.58%), and U-Net++ (97.46%). Through statistical analysis we confirm highly significant improvements (p < 0.001) with effect sizes that range from 0.230 to 13.159 (Cohen's d). Using Saliency map analysis, we reveal that our architecture produces highly concentrated, anatomically consistent activation patterns, which demonstrate an enhanced interpretability which is crucial for clinical deployment. The proposed method establishes a new state of the art performance for automated fetal head segmentation whilst maintaining computational efficiency with 14.7M parameters and a 45 GFLOPs inference cost. Code repository: https://github.com/Ammar-ss

cs.CV↗

arXiv2025

Benchmarking and Parallelization of Electrostatic Particle-In-Cell for low-temperature Plasma Simulation by particle-thread Binding

The Particle-In-Cell (PIC) method for plasma simulation tracks particle phase space information using particle and grid data structures. High computational costs in 2D and 3D device-scale PIC simulations necessitate parallelization, with the Charge Deposition (CD) subroutine often becoming a bottleneck due to frequent particle-grid interactions. Conventional methods mitigate dependencies by generating private grids for each core, but this approach faces scalability issues. We propose a novel approach based on a particle-thread binding strategy that requires only four private grids per node in distributed memory systems or four private grids in shared memory systems, enhancing CD scalability and performance while maintaining conventional data structures and requiring minimal changes to existing PIC codes. This method ensures complete accessibility of grid data structure for concurrent threads and avoids simultaneous access to particles within the same cell using additional functions and flags. Performance evaluations using a PIC benchmark for low-temperature partially magnetized E x B discharge simulation on a shared memory as well as a distributed memory system (1000 cores) demonstrate the method's scalability, and additionally, we show the method has little hardware dependency.

physics.comp-ph↗

arXiv2018

Spatio-temporal evolution of electric field inside a microwave discharge plasma during initial phase of ignition and its effect on power coupling

During the initial phase of microwave (MW) power launch inside a MW discharge ion source (MDIS), plasma and the electric fields are evolved with time together in the plasma volume. The spatio-temporal evolution pattern in the cavity of a MDIS is reported here, highlighting the role of these electric fields on power coupling processes. Evolution of electric field and so power coupling processes are calculated using Finite Element Method (FEM). Unlike PIC/MCC or hybrid fluid, here FEM model uses time dependent Poisson solver through drift-diffusion approach. In presence of plasma gradient in the volume ambipolar electric field is generated which interacts with the MW electric field to form resultant total electric field which continuously vary during this evolution period. It is observed that main power coupling mechanism is electron cyclotron resonance (ECR) method, however with the evolution of plasma, the mode shifts from ECR to off-ECR type heating with time. Off-ECR heating in the form of upper-hybrid resonance (UHR) method, electro-static (ES) ion acoustic wave heating method are important heating mechanisms during the over-dense plasma condition, when density is above critical density for launched MW frequency, 2.45 GHz. An indirect verification of simulated temporal evolution of hot electron temperature and plasma density with the experiment, is done under similar configuration and operating environment. The experimental results are found to be agreed reasonably well with the simulation in the low power range.

physics.plasm-ph↗