S. Prasad

ORCID: 0000-0003-3404-0062
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About
Contact & Profiles
Research Areas
  • Particle physics theoretical and experimental studies
  • High-Energy Particle Collisions Research
  • Quantum Chromodynamics and Particle Interactions
  • Particle Detector Development and Performance
  • CCD and CMOS Imaging Sensors
  • Neutrino Physics Research
  • Radiation Detection and Scintillator Technologies
  • Dark Matter and Cosmic Phenomena
  • Advanced Memory and Neural Computing
  • Neuroscience and Neural Engineering
  • Computational Physics and Python Applications
  • Ferroelectric and Negative Capacitance Devices
  • Calibration and Measurement Techniques
  • Neural dynamics and brain function
  • Particle Accelerators and Free-Electron Lasers
  • Photocathodes and Microchannel Plates
  • Neural Networks and Applications
  • Atomic and Subatomic Physics Research
  • Advanced MEMS and NEMS Technologies
  • Nuclear physics research studies
  • Astrophysics and Cosmic Phenomena
  • Electron and X-Ray Spectroscopy Techniques
  • Black Holes and Theoretical Physics
  • Nuclear Physics and Applications

Argonne National Laboratory
2022-2023

University of Illinois Urbana-Champaign
2021-2023

Bose Institute
2016-2022

Fermi National Accelerator Laboratory
2019

Indian Institute of Technology Bombay
2018

European Organization for Nuclear Research
2012-2015

Harvard University
2012-2013

Harvard University Press
2012

Ludwig-Maximilians-Universität München
2012

Evidence for a flavor asymmetry between the $\overline{u}$ and $\overline{d}$ quark distributions in proton has been found deep-inelastic scattering Drell-Yan experiments. The pronounced dependence of this on $x$ (fraction nucleon momentum carried by partons) observed Fermilab E866 experiment suggested drop $\overline{d}(x)/\overline{u}(x)$ ratio $x>0.15$ region. We report results from SeaQuest E906 with improved statistical precision large region up to $x=0.45$ using 120 GeV beam. Two...

10.1103/physrevc.108.035202 article EN cc-by Physical review. C 2023-09-06

10.1016/j.nima.2018.10.060 article EN Nuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated Equipment 2018-10-15

The main aim of the study is to perform long-term stability test gain single mask triple GEM detector. A simple method used for this using a radioactive X-ray source with high activity. continued till accumulation charge per unit area > 12.0 mC/mm2. details chamber fabrication, set-up, measurement and results are presented in paper.

10.1088/1748-0221/11/10/t10001 article EN Journal of Instrumentation 2016-10-06

The SeaQuest spectrometer at Fermilab was designed to detect oppositely-charged pairs of muons (dimuons) produced by interactions between a 120 GeV proton beam and liquid hydrogen, deuterium solid nuclear targets. primary physics program uses the Drell-Yan process probe antiquark distributions in target nucleon. consists system, two dipole magnets four detector stations. upstream magnet is closed-aperture iron which also serves as dump, while second an open aperture magnet. Each stations...

10.48550/arxiv.1706.09990 preprint EN other-oa arXiv (Cornell University) 2017-01-01

To enable a dense integration of model synapses in spiking neural networks (SNN) hardware, various nanoscale devices are being considered. Such devices, besides exhibiting spike-timing dependent plasticity (STDP), need to be highly scalable, have large endurance and require low energy for transitioning between states. In this work, first, we introduce empirically determine two new specifications resistive random-access memory (RRAM) based synapse: number conductance levels per synapse...

10.1109/ijcnn.2018.8489429 article EN 2022 International Joint Conference on Neural Networks (IJCNN) 2018-07-01

10.1016/j.nima.2018.08.068 article EN Nuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated Equipment 2018-08-23

Spiking Neural Networks (SNN) are more closely related to brain-like computation and inspire hardware implementation. This is enabled by small networks that give high performance on standard classification problems. In literature, typical SNNs deep complex in terms of network structure, weight update rules learning algorithms. makes it difficult translate them into hardware. this paper, we first develop a simple 2-layered software which compares with the state art four different data-sets...

10.48550/arxiv.1612.02233 preprint EN other-oa arXiv (Cornell University) 2016-01-01

Study of the stability gain and energy resolution for a triple GEM detector has been performed under continuous radiation X-ray with high rate, using premixed gas Argon CO$_2$ in 70/30 ratio conventional NIM electronics. A strong Fe$^{55}$ source is used this study. The novelty study that test same to irradiate chamber monitor spectrum. not collimated point but exposed larger area. Effect temperature pressure on these parameters are also studied. detail method measurement first results...

10.48550/arxiv.1804.02819 preprint EN other-oa arXiv (Cornell University) 2018-01-01

Abstract The long-term stability in terms of gain and energy resolution a prototype triple Gas Electron Multiplier (GEM) detector has been investigated with high rate X-ray irradiation. Premixed Ar/CO 2 (80:20) (90:10) gases have used for this study. A strong Fe 55 source is to irradiate the chamber. uniqueness work that same GEM also monitor spectra. This arrangement important since it reduces mechanical complexity using an generator as well cost setup. small area chamber exposed...

10.1088/1742-6596/1498/1/012037 article EN Journal of Physics Conference Series 2020-04-01

Basic R & D have been carried out with one small straw tube detector prototype premixed gas of Ar+CO2 in 70:30 and 90:10 ratio. The gain the energy resolution are measured Fe55 X-ray source. Effect temperature pressure on these parameters measured. variation rate per unit length also details test set-up, method measurement results presented this paper.

10.48550/arxiv.1709.08030 preprint EN other-oa arXiv (Cornell University) 2017-01-01

To enable a dense integration of model synapses in spiking neural networks hardware, various nano-scale devices are being considered. Such device, besides exhibiting spike-time dependent plasticity (STDP), needs to be highly scalable, have large endurance and require low energy for transitioning between states. In this work, we first introduce empirically determine two new specifications an synapse SNNs: number conductance levels per maximum learning-rate. the best our knowledge, there no...

10.48550/arxiv.1803.04773 preprint EN other-oa arXiv (Cornell University) 2018-01-01
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