Zobrazeno 1 - 10
of 239
pro vyhledávání: '"Jejjala, Vishnu"'
Autor:
Berglund, Per, Butbaia, Giorgi, Hübsch, Tristan, Jejjala, Vishnu, Peña, Damián Mayorga, Mishra, Challenger, Tan, Justin
Calabi--Yau compactifications of the $E_8\times E_8$ heterotic string provide a promising route to recovering the four-dimensional particle physics described by the Standard Model. While the topology of the Calabi--Yau space determines the overall ma
Externí odkaz:
http://arxiv.org/abs/2407.13836
We apply reinforcement learning (RL) to generate fine regular star triangulations of reflexive polytopes, that give rise to smooth Calabi-Yau (CY) hypersurfaces. We demonstrate that, by simple modifications to the data encoding and reward function, o
Externí odkaz:
http://arxiv.org/abs/2405.21017
Autor:
Butbaia, Giorgi, Peña, Damián Mayorga, Tan, Justin, Berglund, Per, Hübsch, Tristan, Jejjala, Vishnu, Mishra, Challenger
One of the challenges of heterotic compactification on a Calabi-Yau threefold is to determine the physical $(\mathbf{27})^3$ Yukawa couplings of the resulting four-dimensional $\mathcal{N}=1$ theory. In general, the calculation necessitates knowledge
Externí odkaz:
http://arxiv.org/abs/2401.15078
We apply machine learning to understand fundamental aspects of holographic duality, specifically the entropies obtained from the apparent and event horizon areas. We show that simple features of only the time series of the pressure anisotropy, namely
Externí odkaz:
http://arxiv.org/abs/2312.08442
In this work we employ machine learning to understand structured mathematical data involving finite groups and derive a theorem about necessary properties of generators of finite simple groups. We create a database of all 2-generated subgroups of the
Externí odkaz:
http://arxiv.org/abs/2312.05299
Calabi-Yau manifolds can be obtained as hypersurfaces in toric varieties built from reflexive polytopes. We generate reflexive polytopes in various dimensions using a genetic algorithm. As a proof of principle, we demonstrate that our algorithm repro
Externí odkaz:
http://arxiv.org/abs/2306.06159
Autor:
Berglund, Per, Butbaia, Giorgi, Hübsch, Tristan, Jejjala, Vishnu, Peña, Damián Mayorga, Mishra, Challenger, Tan, Justin
Publikováno v:
ATMP v.27 no.4 (2023) 1107-1158
Finding Ricci-flat (Calabi-Yau) metrics is a long standing problem in geometry with deep implications for string theory and phenomenology. A new attack on this problem uses neural networks to engineer approximations to the Calabi-Yau metric within a
Externí odkaz:
http://arxiv.org/abs/2211.09801
We automate the process of machine learning correlations between knot invariants. For nearly 200,000 distinct sets of input knot invariants together with an output invariant, we attempt to learn the output invariant by training a neural network on th
Externí odkaz:
http://arxiv.org/abs/2211.01404
Superconformal indices of four-dimensional $\mathcal{N}=1$ gauge theories factorize into holomorphic blocks. We interpret this as a modular property resulting from the combined action of an $SL(3,\mathbb{Z})$ and $SL(2,\mathbb{Z})\ltimes \mathbb{Z}^2
Externí odkaz:
http://arxiv.org/abs/2210.17551
Autor:
Akhalwaya, Ismail Yunus, Ubaru, Shashanka, Clarkson, Kenneth L., Squillante, Mark S., Jejjala, Vishnu, He, Yang-Hui, Naidoo, Kugendran, Kalantzis, Vasileios, Horesh, Lior
Publikováno v:
In the Proceedings of The Twelfth International Conference on Learning Representations (ICLR 2024)
Topological data analysis (TDA) is a powerful technique for extracting complex and valuable shape-related summaries of high-dimensional data. However, the computational demands of classical algorithms for computing TDA are exorbitant, and quickly bec
Externí odkaz:
http://arxiv.org/abs/2209.09371