Zobrazeno 1 - 10
of 9 163
pro vyhledávání: '"Tran, Van On"'
Employing effective field theory techniques, we advance computations of thermal parameters that enter predictions for the gravitational wave spectra from first-order electroweak phase transitions. Working with the real-singlet-extended Standard Model
Externí odkaz:
http://arxiv.org/abs/2409.17554
Autor:
Tran, Van Hong, Mehrotra, Aarushi, Sharma, Ranya, Chetty, Marshini, Feamster, Nick, Frankenreiter, Jens, Strahilevitz, Lior
To protect consumer privacy, the California Consumer Privacy Act (CCPA) mandates that businesses provide consumers with a straightforward way to opt out of the sale and sharing of their personal information. However, the control that businesses enjoy
Externí odkaz:
http://arxiv.org/abs/2409.09222
The advancements in generative AI have enabled the improvement of audio synthesis models, including text-to-speech and voice conversion. This raises concerns about its potential misuse in social manipulation and political interference, as synthetic s
Externí odkaz:
http://arxiv.org/abs/2409.07390
Autor:
Tran, Van Que, Yuan, Tzu-Chiang
We explore a novel scenario involving Abelian-non-Abelian kinetic mixing within the framework of the Standard Model Effective Field Theory (SMEFT) and its extension with a real triplet scalar field. In SMEFT, this mixing arises exclusively from a dim
Externí odkaz:
http://arxiv.org/abs/2408.11626
We investigate the possibility of a strong first-order electroweak phase transition during the early universe within the framework of the gauged two-Higgs doublet model (G2HDM) and explore its detectability through stochastic gravitational wave signa
Externí odkaz:
http://arxiv.org/abs/2408.05167
Autor:
Tran, Van Duy, Le, Tran Xuan Hieu, Tran, Thi Diem, Pham, Hoai Luan, Le, Vu Trung Duong, Vu, Tuan Hai, Nguyen, Van Tinh, Nakashima, Yasuhiko
Kolmogorov-Arnold Networks (KANs), a novel type of neural network, have recently gained popularity and attention due to the ability to substitute multi-layer perceptions (MLPs) in artificial intelligence (AI) with higher accuracy and interoperability
Externí odkaz:
http://arxiv.org/abs/2407.17790
Two excesses reported recently at the LHC in the lighter Higgs mass region around 95 GeV and in the rare $Z \gamma$ final state of the Standard Model (SM) 125 GeV Higgs decay are simultaneously scrutinized within the framework of minimal gauged two-H
Externí odkaz:
http://arxiv.org/abs/2405.03127
We study the flavor-changing bottom quark radiative decay $b \to s \gamma$ induced at one-loop level within the minimal gauged two-Higgs-doublet model (G2HDM). Among the three new contributions to this rare process in G2HDM, we find that only the cha
Externí odkaz:
http://arxiv.org/abs/2404.06397
Autor:
Tran, Van, Mehrotra, Aarushi, Chetty, Marshini, Feamster, Nick, Frankenreiter, Jens, Strahilevitz, Lior
The widespread sharing of consumers personal information with third parties raises significant privacy concerns. The California Consumer Privacy Act (CCPA) mandates that online businesses offer consumers the option to opt out of the sale and sharing
Externí odkaz:
http://arxiv.org/abs/2403.17225
A $SU(2)_D \times U(1)_D$ gauge-Higgs sector, an exact dark copy of the Standard Model (SM) one, is proposed. It is demonstrated that the dark gauge bosons ${\cal W}^{(p,m)}$, in analogous to the SM $W^\pm$, can fulfill the role as a self-interacting
Externí odkaz:
http://arxiv.org/abs/2312.10785