Zobrazeno 1 - 10
of 1 393 458
pro vyhledávání: '"AS Kumar"'
Publikováno v:
Fortschritte der Physik (2024) 2400092
In this study, we developed the geometrically deformed compact objects in the $f(Q, T)$ gravity theory under an electric field through gravitational decoupling via. minimal geometric deformation (MGD) technique for the first time. The decoupled field
Externí odkaz:
http://arxiv.org/abs/2408.02051
Autor:
Jyothish, Kumar J., Mishra, Subhankar
Publikováno v:
ACM Comput. Surv. 56, 8, Article 195 (August 2024), 44 pages
The field of robotics is a quickly evolving feat of technology that accepts contributions from various genres of science. Neuroscience, Physiology, Chemistry, Material science, Computer science, and the wide umbrella of mechatronics have all simultan
Externí odkaz:
http://arxiv.org/abs/2408.01729
Autor:
Kaplon, L., Baran, J., Chug, N., Coussat, A., Curceanu, C., Czerwinski, E., Dadgar, M., Dulski, K., Gajewski, J., Gajos, A., Hiesmayr, B., Valsan, E. Kavya, Klimaszewski, K., Korcyl, G., Kozik, T., Krzemien, W., Kumar, D., Moskal, G., Niedzwiecki, S., Panek, D., Parzych, S., del Rio, E. Perez, Raczynski, L., Rucinski, A., Sharma, S., Shivani, S., Shopa, R., Silarski, M., Skurzok, M., Stepien, E., Ardebili, F. Tayefi, Ardebili, K. Tayefi, Wislicki, W., Moskal, P.
Publikováno v:
Nuclear Inst. and Methods in Physics Research, A 1051 (2023) 168186
Plastic scintillator strips are considered as one of the promising solutions for the cost-effective construction of total-body positron emission tomography, (PET) system. The purpose of the performed measurements is to compare the transparency of lon
Externí odkaz:
http://arxiv.org/abs/2407.19465
In this work, we explore the usage of the Frequency Transformation for reducing the domain shift between the source and target domain (e.g., synthetic image and real image respectively) towards solving the Domain Adaptation task. Most of the Unsuperv
Externí odkaz:
http://arxiv.org/abs/2407.19551
Autor:
Kumar, Raj
A sufficiently precise measurement of black hole spin is required to carry out quantitative tests of the Kerr metric and to understand several phenomena related to astrophysical black holes. After 24 years, XTE J2012+381 again underwent an outburst i
Externí odkaz:
http://arxiv.org/abs/2407.07362
Autor:
Srivastav, Saurabh Kumar, Das, Anindya
Publikováno v:
Modern Physics Letters B (2024)
Topological quantum numbers are often used to characterise the topological order of phase having protected gapless edge modes when the system is kept in a space with the boundary. The famous examples in this category are the quantized electrical Hall
Externí odkaz:
http://arxiv.org/abs/2407.05903
Publikováno v:
Computers and Geotechnics (2024)
Numerical modeling of slope failures seeks to predict two key phenomena: the initiation of failure and the post-failure runout. Currently, most modeling methods for slope failure analysis excel at one of these two but are deficient in the other. For
Externí odkaz:
http://arxiv.org/abs/2407.05185
Publikováno v:
Physics of Fluids, 36, 065116 (2024)
This paper uses a reactive flow large eddy simulation (LES) and decomposition techniques to study combustion instabilities in a methane-oxygen combustor. This work examines two case scenarios to elucidate the significance of injector-chamber frequenc
Externí odkaz:
http://arxiv.org/abs/2407.03055
Autor:
Kumar, Naveen, Chatterjee, Arpita
Publikováno v:
Int. J. Theo. Phys., 63(5), Article no. 124 (1-17) (2024)
We consider a nonclassical state generated by an atom-cavity field interaction in presence of a driven field. In the scheme, the two-level atom is moved through the cavity and driven by a classical field. The atom interacts dispersively with the cavi
Externí odkaz:
http://arxiv.org/abs/2407.00982
Autor:
Barman, Rahool Kumar, Biswas, Sumit
Publikováno v:
Eur. Phys. J. Spec. Top. (2024)
In this article, we review the application of modern machine-learning (ML) techniques to boost the search for processes involving the top quarks at the LHC. We revisit the formalism of Convolutional Neural Networks (CNNs), Graph Neural Networks (GNNs
Externí odkaz:
http://arxiv.org/abs/2407.00183