Harihara Sudhan Kumar
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Previous Organizations / Institutes
The organizations / institutes from the scholar's other articles in the past ten years
Harihara Sudhan Kumar has a total of 88 co-authors. Here are the top co-authors by number of shared publications:
- Alessio Morace
Osaka University
3 shared publications - Chun-Sung Jao
National Center for High-Performance Computing, National Institutes of Applied Research 1 , Hsinchu
3 shared publications - Fuka Nikaido
The University of Osaka Graduate School of Engineering 2-1 Yamadaoka, Suita, Osaka 565-0871
3 shared publications - Kentaro Sakai
National Institute for Fusion Science, 322-6 Oroshicho, Toki, Gifu 509-5292, Japan
3 shared publications - Masato Kanasaki
Graduate School of Maritime Sciences, Kobe University, 5-1-1 Fukaeminami-machi, Higashinada-ku, Kobe 658-0022, Japan
3 shared publications - Naofumi Ohnishi
Department of Aerospace Engineering, Tohoku University, Sendai 980-8579, Japan
3 shared publications
Latest Publications
- Open Access
- 1 October 2026
- Published by Oxford University Press (OUP) in Progress of Theoretical and Experimental Physics
- Vol. 2026 (10)
Proton Surfing Acceleration via Propagating Electrostatic Waves Induced by Intense Laser Irradiation on Large-Area Suspended Graphene
Generating 100-MeV protons is pivotal to developing laser-driven ion sources for many applications that range from medicine to laboratory astrophysics. An ultra-thin target is a way to increase the ion energy; however, such a target is easily destroyed by the interaction with laser prepulses. We have developed a large-area suspended graphene (LSG) target and demonstrated its durability by generating energetic protons and carbons by irradiating the thinnest target ever (2 nm) with an ultra-intense laser without a plasma mirror. Here, we show the experimental results of proton energies reaching 132 MeV by optimizing the laser conditions for the ultra-thin LSG targets. Ion diagnostics were primarily performed using a CR-39 stack detector combined with machine-learning-assisted analysis. Numerical simulations support the experimental results, where the radiation pressure of a relatively long-duration, low-intensity laser pulse slowly pushes the plasma, leading to the formation of a propagating electrostatic wave that efficiently accelerates protons, as in surfing acceleration.
- 1 October 2026
- Published by Oxford University Press (OUP) in Progress of Theoretical and Experimental Physics
- Vol. 2026 (10)
Open AccessProton Surfing Acceleration via Propagating Electrostatic Waves Induced by Intense Laser Irradiation on Large-Area Suspended Graphene
Generating 100-MeV protons is pivotal to developing laser-driven ion sources for many applications that range from medicine to laboratory astrophysics. An ultra-thin target is a way to increase the ion energy; however, such a target is easily destroyed by the interaction with laser prepulses. We have developed a large-area suspended graphene (LSG) target and demonstrated its durability by generating energetic protons and carbons by irradiating the thinnest target ever (2 nm) with an ultra-intense laser without a plasma mirror. Here, we show the experimental results of proton energies reaching 132 MeV by optimizing the laser conditions for the ultra-thin LSG targets. Ion diagnostics were primarily performed using a CR-39 stack detector combined with machine-learning-assisted analysis. Numerical simulations support the experimental results, where the radiation pressure of a relatively long-duration, low-intensity laser pulse slowly pushes the plasma, leading to the formation of a propagating electrostatic wave that efficiently accelerates protons, as in surfing acceleration.
- 24 August 2024
- Published by Elsevier in High Energy Density Physics
- Vol. 53
A hybrid simulation integrating molecular dynamics and particle-in-cell methods for improved laser-target interaction
- 24 August 2024
- Published by Elsevier in High Energy Density Physics
- Vol. 53
A hybrid simulation integrating molecular dynamics and particle-in-cell methods for improved laser-target interaction
- Open Access
- 1 May 2024
- Published by AIP Publishing in Physics of Plasmas
- Vol. 31 (5)
Optimization of laser-driven quantum beam generation and the applications with artificial intelligence
We have investigated space and astrophysical phenomena in nonrelativistic laboratory plasmas with long high-power lasers, such as collisionless shocks and magnetic reconnections, and have been exploring relativistic regimes with intense short pulse lasers, such as energetic ion acceleration using large-area suspended graphene. Increasing the intensity and repetition rate of the intense lasers, we have to handle large amounts of data from the experiments as well as the control parameters of laser beamlines. Artificial intelligence (AI) such as machine learning and neural networks may play essential roles in optimizing the laser and target conditions for efficient laser ion acceleration. Implementing AI into the laser system in mind, as the first step, we are introducing machine learning in ion etch pit analyses detected on plastic nuclear track detectors. Convolutional neural networks allow us to analyze big ion etch pit data with high precision and recall. We introduce one of the applications of laser-driven ion beams using AI to reconstruct vector electric and magnetic fields in laser-produced turbulent plasmas in three dimensions.
- 1 May 2024
- Published by AIP Publishing in Physics of Plasmas
- Vol. 31 (5)
Open AccessOptimization of laser-driven quantum beam generation and the applications with artificial intelligence
We have investigated space and astrophysical phenomena in nonrelativistic laboratory plasmas with long high-power lasers, such as collisionless shocks and magnetic reconnections, and have been exploring relativistic regimes with intense short pulse lasers, such as energetic ion acceleration using large-area suspended graphene. Increasing the intensity and repetition rate of the intense lasers, we have to handle large amounts of data from the experiments as well as the control parameters of laser beamlines. Artificial intelligence (AI) such as machine learning and neural networks may play essential roles in optimizing the laser and target conditions for efficient laser ion acceleration. Implementing AI into the laser system in mind, as the first step, we are introducing machine learning in ion etch pit analyses detected on plastic nuclear track detectors. Convolutional neural networks allow us to analyze big ion etch pit data with high precision and recall. We introduce one of the applications of laser-driven ion beams using AI to reconstruct vector electric and magnetic fields in laser-produced turbulent plasmas in three dimensions.
- Open Access
- 1 January 2024
- Published by AIP Publishing in Chaos: An Interdisciplinary Journal of Nonlinear Science
- Vol. 34 (1)
Characterization of stability of dynamic particle ensemble systems using topological data analysis
Holes are ubiquitous structures in phase space, and their time evolution could indicate an instability in the dynamics of the system. However, the properties of these holes are difficult to study directly due to their theoretical complexity and lack of computational tools. This study proposes the use of persistent homology (PH), a technique from topological data analysis, as a computational tool for analyzing the properties of these phase-space holes, or more formally the H1 homology class according to PH. Initially, by using a toy data set, it is shown that the time evolution and the growth rate of a H1 class in phase space could be obtained by PH. For further validation, PH is applied to particle ensemble systems, such as the Hamiltonian flow and the two-stream instability (TSI). Both the stable case, where no H1 forms, and the unstable case, where H1 forms, were analyzed. It was shown that PH can distinguish between the stable and unstable cases purely from the phase-space time evolution plots. In unstable TSI, the PH also distinguished the transition of the H1 class from linear to non-linear growth. The growth rate, thus, obtained is in excellent agreement with the growth rate of the particle energy in the TSI system.
- 1 January 2024
- Published by AIP Publishing in Chaos: An Interdisciplinary Journal of Nonlinear Science
- Vol. 34 (1)
Open AccessCharacterization of stability of dynamic particle ensemble systems using topological data analysis
Holes are ubiquitous structures in phase space, and their time evolution could indicate an instability in the dynamics of the system. However, the properties of these holes are difficult to study directly due to their theoretical complexity and lack of computational tools. This study proposes the use of persistent homology (PH), a technique from topological data analysis, as a computational tool for analyzing the properties of these phase-space holes, or more formally the H1 homology class according to PH. Initially, by using a toy data set, it is shown that the time evolution and the growth rate of a H1 class in phase space could be obtained by PH. For further validation, PH is applied to particle ensemble systems, such as the Hamiltonian flow and the two-stream instability (TSI). Both the stable case, where no H1 forms, and the unstable case, where H1 forms, were analyzed. It was shown that PH can distinguish between the stable and unstable cases purely from the phase-space time evolution plots. In unstable TSI, the PH also distinguished the transition of the H1 class from linear to non-linear growth. The growth rate, thus, obtained is in excellent agreement with the growth rate of the particle energy in the TSI system.
- Open Access
Enhancement of Film Cooling Effectiveness in a Supersonic Nozzle
Film cooling as applied to rocket nozzles is analyzed numerically with emphasis on the assessment of the effect of the mixing of coolant with the hot stream. Cooling performance, as characterized by cooling effectiveness, is studied for three different coolants in the three-dimensional, turbulent flow field of a supersonic convergent-divergent nozzle operating with a hot stream temperature of 2500 K over a range of blowing ratios. The coolant stream is injected tangentially into the mainstream using a diffuser-type injector. Parameters influencing the effectiveness, such as coolant injector configuration and mixing layer, are analyzed. Thermal and species mixing between the coolant and the mainstream are investigated with regard to their impact on cooling effectiveness. The results obtained provide insight into the film cooling performance of the gases and the heat transfer characteristics associated with these three gases. An injector taper angle of 30° results in the most effective cooling among the configurations considered (0°, 15°, 30° and 45°). Mixing of the coolant with the hot stream is examined based on the distributions of velocity, temperature and species. The higher values of cooling effectiveness for Helium are attributed to its thermophysical properties and the reduced rate of mixing with the hot stream. The results further indicate that through optimization of the blowing ratio and the coolant injector configuration, the film cooling effectiveness can be substantially improved.
Open AccessEnhancement of Film Cooling Effectiveness in a Supersonic Nozzle
Film cooling as applied to rocket nozzles is analyzed numerically with emphasis on the assessment of the effect of the mixing of coolant with the hot stream. Cooling performance, as characterized by cooling effectiveness, is studied for three different coolants in the three-dimensional, turbulent flow field of a supersonic convergent-divergent nozzle operating with a hot stream temperature of 2500 K over a range of blowing ratios. The coolant stream is injected tangentially into the mainstream using a diffuser-type injector. Parameters influencing the effectiveness, such as coolant injector configuration and mixing layer, are analyzed. Thermal and species mixing between the coolant and the mainstream are investigated with regard to their impact on cooling effectiveness. The results obtained provide insight into the film cooling performance of the gases and the heat transfer characteristics associated with these three gases. An injector taper angle of 30° results in the most effective cooling among the configurations considered (0°, 15°, 30° and 45°). Mixing of the coolant with the hot stream is examined based on the distributions of velocity, temperature and species. The higher values of cooling effectiveness for Helium are attributed to its thermophysical properties and the reduced rate of mixing with the hot stream. The results further indicate that through optimization of the blowing ratio and the coolant injector configuration, the film cooling effectiveness can be substantially improved.
- 26 October 2021
- Published by AIP Publishing in Journal of Applied Physics
- Vol. 130 (16) , 163303
Kinetic theory of double layers driven by temperature anisotropy in a non-homogeneous magnetic field
A double layer (DL) is created in a plasma when the plasma is perturbed in the presence of a temperature anisotropy. We derive a new simple theory for the existence of an unstable, non-oscillatory electrostatic DL-like structure in the presence of a magnetic field gradient in a collisionless plasma with a temperature anisotropy in the direction perpendicular to the magnetic field. The DL is treated as a wave perturbation in the plasma using kinetic theory with a gyro-kinetic approximation to obtain a dispersion relation. The presence of an electron temperature anisotropy is the necessary condition to obtain an exponentially growing instability, and the corresponding growth rate is found to be the ratio of the electron kinetic energy and the electric field energy across the DL region. The theoretical predictions are then validated against a one-dimensional electrostatic particle simulation carried out in a traveling magnetic field thruster environment. An anisotropy ratio parameter was introduced, and the theoretical growth rates were found to be in good agreement with the simulation for different anisotropy ratios. An ion beam, associated with the DL dynamics, is observed within the simulation domain. A parametric study revealed that the DL-like structure loses its ambipolar shape for temperature ratios less than 10. It has been found that a stronger anisotropy is required to obtain the DL-like structure.
- 26 October 2021
- Published by AIP Publishing in Journal of Applied Physics
- Vol. 130 (16) , 163303
Kinetic theory of double layers driven by temperature anisotropy in a non-homogeneous magnetic field
A double layer (DL) is created in a plasma when the plasma is perturbed in the presence of a temperature anisotropy. We derive a new simple theory for the existence of an unstable, non-oscillatory electrostatic DL-like structure in the presence of a magnetic field gradient in a collisionless plasma with a temperature anisotropy in the direction perpendicular to the magnetic field. The DL is treated as a wave perturbation in the plasma using kinetic theory with a gyro-kinetic approximation to obtain a dispersion relation. The presence of an electron temperature anisotropy is the necessary condition to obtain an exponentially growing instability, and the corresponding growth rate is found to be the ratio of the electron kinetic energy and the electric field energy across the DL region. The theoretical predictions are then validated against a one-dimensional electrostatic particle simulation carried out in a traveling magnetic field thruster environment. An anisotropy ratio parameter was introduced, and the theoretical growth rates were found to be in good agreement with the simulation for different anisotropy ratios. An ion beam, associated with the DL dynamics, is observed within the simulation domain. A parametric study revealed that the DL-like structure loses its ambipolar shape for temperature ratios less than 10. It has been found that a stronger anisotropy is required to obtain the DL-like structure.