arXiv subjects

J. K. Sahoo

Publications and source records attributed to J. K. Sahoo.

5 recordsLinked to original sources

arXiv2024

Study of $^{113}$In($α,α$) elastic scattering to determine $α$-optical potential relevant for astrophysical $γ$-process

The $α$-optical potential is one of the key input parameters used to measure the reaction rate of the ($γ,α$)-process using the Hauser-Feshbach(HF) statistical model and the principle of detailed balance. $α$-elastic scattering experiment on $^{113}$In $p$-nucleus was carried out in the energy range E$_{lab}$=26$-$32 MeV. The vacuum evaporation technique was used to prepare the $^{113}$In target~($\sim$86 $μ$g/cm$^2$). An energy-dependent local optical potential parameters set was obtained by analysing the experimental elastic scattering angular distribution data. The local potential parameters are extrapolated for lower energies and are used to measure the $^{113}$In($α,γ$) reaction cross-section.

nucl-ex↗

arXiv2021

Preparation of Isotopically enriched $^{112,116,120,124}$Sn targets at VECC

Resistive heating and mechanical rolling methods have been employed to prepare isotopically enriched thin target foils of 116Sn (~380 μg/cm2), 124Sn(~400 μg/cm2) and thicker foils of 112Sn (1.7 mg/cm2),120Sn (1.6 mg/cm2),respectively. Preparation of enriched targets with small amount of material, selection of releasing agent for thin targets and separation of deposited material insolvent were among the several challenges while fabrication of the thin targets. Uniformity of the targets has been measured using 241Am α-source. NaCl has been used as releasing agent in preparation of the thin targets. These targets have been successfully used in nuclear physics experiments at VECC.

physics.ins-det↗

arXiv2020

The determination of α-spectroscopic factors and ANC of 16O states using 12C(20Ne,16O)16O reaction at Elab=150 MeV incident energy

The 12C(20Ne,16O)16O α-transfer reaction at Elab=150 MeV is first time used to determine the ANC of the 6.92 MeV and 7.12 MeV states of 16O. The 20Ne+ 12C potential parameters are also obtained from elastic scattering. The direct reaction code FRESCO is used to determine the α-spectroscopy factor (Sα ) of the three states of 16O (6.92 MeV, 7.12 MeV and 11.52 MeV) and ANC of the two states (6.92 MeV and 7.12 MeV) of 16O. The extracted ANC and Sα are compareable to previous measurements.

nucl-ex↗

arXiv2019

ChAKRA : The high resolution charged particle detector array at VECC

A large 4$π$ array of charged particle detectors has been developed at Variable Energy Cyclotron Centre to facilitate high resolution charged particle reaction and spectroscopy studies by detecting event-by-event the charged reaction products emitted in heavy ion reactions at energy $\sim$ 10-60 MeV/A. The forward part ($θ\sim \pm $ $7^{0}$ - $\pm 45^{0}$) of the array consists of 24 highly granular, high resolution charged particle telescopes, each of which is made by three layers [single sided silicon strip($Δ$E) + double sided silicon strip (E/$Δ$E) + CsI(Tl)(E)]of detectors. The backward part of the array consists of 112 CsI(Tl) detectors which are capable of detecting primarily the light charged particles (Z $\le$ 2) emitted in the angular range of $θ\sim \pm $ $45^{0}$ - $\pm 175^{0}$. The extreme forward part of the array ($θ\sim \pm $ $3^{0}$ - $\pm 7^{0}$) is made up of 32 slow-fast plastic phoswich detectors that are capable of detecting light (Z $\le$2) and heavy charged particles (3 $\le$ Z $\lesssim$ 20) as well as handling high count rates. The design, construction and characterization of the array has been described.

physics.ins-det↗

arXiv2014

Polyphonic Music Generation by Modeling Temporal Dependencies Using a RNN-DBN

In this paper, we propose a generic technique to model temporal dependencies and sequences using a combination of a recurrent neural network and a Deep Belief Network. Our technique, RNN-DBN, is an amalgamation of the memory state of the RNN that allows it to provide temporal information and a multi-layer DBN that helps in high level representation of the data. This makes RNN-DBNs ideal for sequence generation. Further, the use of a DBN in conjunction with the RNN makes this model capable of significantly more complex data representation than an RBM. We apply this technique to the task of polyphonic music generation.

cs.LG↗