Zobrazeno 1 - 10
of 58
pro vyhledávání: '"Akanksha Bhardwaj"'
Autor:
Akanksha Bhardwaj, Christoph Englert, Wrishik Naskar, Vishal S. Ngairangbam, Michael Spannowsky
Publikováno v:
Journal of High Energy Physics, Vol 2024, Iss 7, Pp 1-15 (2024)
Abstract This study introduces a novel Graph Neural Network (GNN) architecture that leverages infrared and collinear (IRC) safety and equivariance to enhance the analysis of collider data for Beyond the Standard Model (BSM) discoveries. By integratin
Externí odkaz:
https://doaj.org/article/53b13e68c00f4fb79236844d4fa0e758
Publikováno v:
Heliyon, Vol 9, Iss 11, Pp e21735- (2023)
Surface oxygen functional groups of biochar were tuned by oxidation and reduction of biochar for establishing Cr(VI) adsorption mechanism. Oxygen functional groups (OFGs) on the surface of leached rice straw biochar (LBC4-6) obtained from pyrolysis a
Externí odkaz:
https://doaj.org/article/40a775106099460faf6a4699124ab2bc
Publikováno v:
Journal of High Energy Physics, Vol 2022, Iss 10, Pp 1-30 (2022)
Abstract Constraints on quartic interactions of the Higgs boson with gauge bosons have been obtained by the experimental LHC collaborations focussing on the so-called κ framework of flat rescalings of SM-like interactions in weak boson fusion (WBF)
Externí odkaz:
https://doaj.org/article/abc3bb54e58f40349f463137d7f3af7f
Autor:
Oliver Atkinson, Akanksha Bhardwaj, Stephen Brown, Christoph Englert, David J. Miller, Panagiotis Stylianou
Publikováno v:
Journal of High Energy Physics, Vol 2022, Iss 4, Pp 1-20 (2022)
Abstract We explore the potential of Graph Neural Networks (GNNs) to improve the performance of high-dimensional effective field theory parameter fits to collider data beyond traditional rectangular cut-based differential distribution analyses. In th
Externí odkaz:
https://doaj.org/article/05de6bdc53cc4a0188a9ce82169bebae
Autor:
Oliver Atkinson, Akanksha Bhardwaj, Christoph Englert, Vishal S. Ngairangbam, Michael Spannowsky
Publikováno v:
Journal of High Energy Physics, Vol 2021, Iss 8, Pp 1-19 (2021)
Abstract We devise an autoencoder based strategy to facilitate anomaly detection for boosted jets, employing Graph Neural Networks (GNNs) to do so. To overcome known limitations of GNN autoencoders, we design a symmetric decoder capable of simultaneo
Externí odkaz:
https://doaj.org/article/cf254222ff9841e9ac0fc3f816b0c48c
Publikováno v:
Physics Letters B, Vol 832, Iss , Pp 137246- (2022)
Improving the sensitivity to CP-violation in the Higgs sector is one of the pillars of the precision Higgs programme at the Large Hadron Collider. We present a simple method that allows CP-sensitive observables to be directly constructed from the out
Externí odkaz:
https://doaj.org/article/78325934fd044747b25eebfb63f036d0
Autor:
Oliver Atkinson, Akanksha Bhardwaj, Christoph Englert, Partha Konar, Vishal S. Ngairangbam, Michael Spannowsky
Publikováno v:
Frontiers in Artificial Intelligence, Vol 5 (2022)
Anomaly detection through employing machine learning techniques has emerged as a novel powerful tool in the search for new physics beyond the Standard Model. Historically similar to the development of jet observables, theoretical consistency has not
Externí odkaz:
https://doaj.org/article/ce1dabaf649a4c84a38cea05b01d4ba3
Publikováno v:
European Physical Journal C: Particles and Fields, Vol 80, Iss 11, Pp 1-25 (2020)
Abstract Vector boson fusion proposed initially as an alternative channel for finding heavy Higgs has now established itself as a crucial search scheme to probe different properties of the Higgs boson or for new physics. We explore the merit of deep-
Externí odkaz:
https://doaj.org/article/3e9e36040abd40d1a82d798b59397fe1
Publikováno v:
Journal of High Energy Physics, Vol 2020, Iss 10, Pp 1-23 (2020)
Abstract Search for compressed supersymmetry at multi-TeV scale, in the presence of a light gravitino dark matter, can get sizable uplift while looking into the associated fat- jets with missing transverse momenta as a signature of the boson produced
Externí odkaz:
https://doaj.org/article/ebbf97035d184c5e86ea84ce2b091827
Autor:
Akanksha Bhardwaj, Suram Singh Verma
Publikováno v:
Plasmonics. 17:2297-2306