Zobrazeno 1 - 10
of 923
pro vyhledávání: '"Chakraborty, Subrata"'
Autor:
Boonstra, Marjolein, Bruneault, Frédérick, Chakraborty, Subrata, Faber, Tjitske, Gallucci, Alessio, Hickman, Eleanore, Kema, Gerard, Kim, Heejin, Kooiker, Jaap, Hildt, Elisabeth, Lamadé, Annegret, Mathez, Emilie Wiinblad, Möslein, Florian, Pathuis, Genien, Sartor, Giovanni, Steege, Marijke, Stocco, Alice, Tadema, Willy, Tuimala, Jarno, van Vledder, Isabel, Vetter, Dennis, Vetter, Jana, Westerlund, Magnus, Zicari, Roberto V.
This report shares the experiences, results and lessons learned in conducting a pilot project ``Responsible use of AI'' in cooperation with the Province of Friesland, Rijks ICT Gilde-part of the Ministry of the Interior and Kingdom Relations (BZK) (b
Externí odkaz:
http://arxiv.org/abs/2404.14366
Autor:
Tuncer, Turker, Dogan, Sengul, Baygin, Mehmet, Barua, Prabal Datta, Hafeez-Baig, Abdul, Tan, Ru-San, Chakraborty, Subrata, Acharya, U. Rajendra
The generative pre-trained transformer (GPT)-based chatbot software ChatGPT possesses excellent natural language processing capabilities but is inadequate for solving arithmetic problems, especially multiplication. Its GPT structure uses a computatio
Externí odkaz:
http://arxiv.org/abs/2310.13016
Autor:
Chakraborty, Subrata, Nikolić, Danilo, Souto, Rubén Seoane, Belzig, Wolfgang, Cuevas, Juan Carlos
Publikováno v:
Phys. Rev. B 108, 094518(2023)
Motivated by recent experiments [Nat. Phys. $\textbf{16}$, 1227 (2020)], we present here a theoretical study of the DC Josephson effect in a system comprising two magnetic impurities coupled to their respective superconducting electrodes and which ex
Externí odkaz:
http://arxiv.org/abs/2308.01678
Autor:
Horry, Michael James, Chakraborty, Subrata, Pradhan, Biswajeet, Paul, Manoranjan, Zhu, Jing, Barua, Prabal Datta, Acharya, U. Rajendra, Chen, Fang, Zhou, Jianlong
Lung cancer is the leading cause of cancer death and early diagnosis is associated with a positive prognosis. Chest X-ray (CXR) provides an inexpensive imaging mode for lung cancer diagnosis. Suspicious nodules are difficult to distinguish from vascu
Externí odkaz:
http://arxiv.org/abs/2307.06547
A novel over-dispersed discrete distribution, namely the PoiTG distribution is derived by the convolution of a Poisson variate and an independently distributed transmuted geometric random variable. This distribution generalizes the geometric, transmu
Externí odkaz:
http://arxiv.org/abs/2306.07219
Autor:
Spuri, Alfredo, Nikolić, Danilo, Chakraborty, Subrata, Klang, Maya, Alpern, Hen, Millo, Oded, Steinberg, Hadar, Belzig, Wolfgang, Scheer, Elke, Di Bernardo, Angelo
Publikováno v:
Phys. Rev. Research 6, L012046 (2024)
The combination of a superconductor with a magnetically inhomogeneous material has been established as an efficient mechanism for the generation of long-ranged spin-polarized (spin-triplet) Cooper pairs. Evidence for this mechanism, however, has been
Externí odkaz:
http://arxiv.org/abs/2305.02216
Autor:
Chakraborty, Subrata, Nikolić, Danilo, Cuevas, Juan Carlos, Giazotto, Francesco, Di Bernardo, Angelo, Scheer, Elke, Cuoco, Mario, Belzig, Wolfgang
Recently gate-mediated supercurrent suppression in superconducting nano-bridges has been reported in many experiments. This could be either a direct or an indirect gate effect. The microscopic understanding of this observation is not clear till now.
Externí odkaz:
http://arxiv.org/abs/2303.07801
In this article, we discuss a bivariate distribution whose conditionals are univariate binomial distributions and the marginals are not binomial that exhibits negative correlation. Some useful structural properties of this distribution namely margina
Externí odkaz:
http://arxiv.org/abs/2301.03087
A new two-parameter discrete distribution, namely the PoiG distribution is derived by the convolution of a Poisson variate and an independently distributed geometric random variable. This distribution generalizes both the Poisson and geometric distri
Externí odkaz:
http://arxiv.org/abs/2301.01480
The ever-growing volume of satellite imagery data presents a challenge for industry and governments making data-driven decisions based on the timely analysis of very large data sets. Commonly used deep learning algorithms for automatic classification
Externí odkaz:
http://arxiv.org/abs/2203.08267