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pro vyhledávání: '"Pasquarella, A."'
Autor:
Pasquarella, Veronica
A fundamental step towards studying string theory vacua, and, ultimately, their stability, is that of understanding the underlying mathematical structure of the QFT resulting from its dimensional reduction on Calabi-Yau (CY) manifolds, the latter bei
Externí odkaz:
http://arxiv.org/abs/2406.11964
Autor:
Pasquarella, Veronica
This introductory work combines bottom-up and top-down approaches towards understanding the underlying categorical structure of possible unifying theories descending from string theory. Guided by well-established developments in the realm of categori
Externí odkaz:
http://arxiv.org/abs/2404.08100
Autor:
Pasquarella, Veronica
Based on recent advancements in algebraic geometry, algebraic topology, and higher-categorical structures, we show how ground state degeneracies in closed stratified manifolds can be used for describing class ${\cal S}$ theories whose AGT dual requir
Externí odkaz:
http://arxiv.org/abs/2312.06760
Autor:
Pasquarella, Veronica
We propose a generalisation of the Moore-Tachikawa varieties for the case in which the target category of the 2D TFT is a hyperk$\ddot{\text{a}}$hler quotient. The setup requires generalising the bordism operators of Moore and Segal to the case invol
Externí odkaz:
http://arxiv.org/abs/2310.01489
Autor:
Pasquarella, Veronica
The present work shows that magnetic quivers encode the necessary information for determining the Drinfeld center in the symmetry topological field theory constructions (SymTFT) associated to a given absolute theory. The crucial argument resides in t
Externí odkaz:
http://arxiv.org/abs/2306.12471
Autor:
Pasquarella, Veronica
Exploiting the symmetry topological field theory/topological order correspondence (SymTFT/TO), together with the higher-categorical structure of 6D N =(2,0) SCFTs, we prove that the total quantum dimension of the relative condensation algebra leading
Externí odkaz:
http://arxiv.org/abs/2305.18515
We calculate amplitudes for 2D vacuum transitions by means of the Euclidean methods of Coleman-De Luccia (CDL) and Brown-Teitelboim (BT), as well as the Hamiltonian formalism of Fischler, Morgan and Polchinski (FMP). The resulting similarities and di
Externí odkaz:
http://arxiv.org/abs/2211.07664
Self- and semi-supervised machine learning techniques leverage unlabeled data for improving downstream task performance. These methods are especially valuable for remote sensing tasks where producing labeled ground truth datasets can be prohibitively
Externí odkaz:
http://arxiv.org/abs/2111.10079
Akademický článek
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Autor:
Veronica Pasquarella, Fernando Quevedo
Publikováno v:
Journal of High Energy Physics, Vol 2023, Iss 5, Pp 1-60 (2023)
Abstract We calculate amplitudes for 2D vacuum transitions by means of the Euclidean methods of Coleman-De Luccia (CDL) and Brown-Teitelboim (BT), as well as the Hamiltonian formalism of Fischler, Morgan and Polchinski (FMP). The resulting similariti
Externí odkaz:
https://doaj.org/article/2f17f8f162f444d4a316aa9e7218e69d
