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CERN Document Server Sök i 17 journaler efter:  1 - 10nästa  gå till journal: Sökningen tog 0.58 sekunder. 
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Artificial Intelligence for Theoretical Physics and Mathematics / Ruehle, Fabian (speaker)
2022 - 3762. Conferences & Workshops; CERN Winter School on Supergravity, Strings and Gauge Theory 2022 External links: Talk details; Event details In : CERN Winter School on Supergravity, Strings and Gauge Theory 2022
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Artificial Intelligence for Theoretical Physics and Mathematics / Ruehle, Fabian (speaker)
For preparation, students can browse through https://www.sciencedirect.com/science/article/pii/S0370157319303072 (For the purpose of the lecture, the relevant chapters are 1-4 and 8-9)..
2022 - 3337. Conferences & Workshops; CERN Winter School on Supergravity, Strings and Gauge Theory 2022 External links: Talk details; Event details In : CERN Winter School on Supergravity, Strings and Gauge Theory 2022
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3.
Geodesics in the extended Kähler cone of Calabi-Yau threefolds / Brodie, Callum R. (IPhT, Saclay) ; Constantin, Andrei (Oxford U., Theor. Phys.) ; Lukas, Andre (Oxford U., Theor. Phys.) ; Ruehle, Fabian (Oxford U., Theor. Phys. ; CERN)
We present a detailed study of the effective cones of Calabi-Yau threefolds with $h^{1,1}=2$, including the possible types of walls bounding the Kähler cone and a classification of the intersection forms arising in the geometrical phases. For all three normal forms in the classification we explicitly solve the geodesic equation and use this to study the evolution near Kähler cone walls and across flop transitions in the context of M-theory compactifications. [...]
arXiv:2108.10323; CERN-TH-2021-123.- 2022-03-03 - 42 p. - Published in : JHEP 03 (2022) 024 Fulltext: 2108.10323 - PDF; document - PDF;
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4.
Swampland Conjectures and Infinite Flop Chains / Brodie, Callum R. (IPhT, Saclay) ; Constantin, Andrei (Oxford U., Theor. Phys. ; U. Oxford (main)) ; Lukas, Andre (Oxford U., Theor. Phys.) ; Ruehle, Fabian (CERN ; Oxford U., Theor. Phys.)
We investigate swampland conjectures for quantum gravity in the context of M-theory compactified on Calabi-Yau threefolds which admit infinite sequences of flops. Naively, the moduli space of such compactifications contains paths of arbitrary geodesic length traversing an arbitrarily large number of Kähler cones, along which the low-energy spectrum remains virtually unchanged. [...]
arXiv:2104.03325; CERN-TH-2021-051.- 2021-08-04 - 9 p. - Published in : Phys. Rev. D 104 (2021) 046008 Fulltext: PDF; Fulltext from publisher: PDF;
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5.
Moduli-dependent KK towers and the swampland distance conjecture on the quintic Calabi-Yau manifold / Ashmore, Anthony (Chicago U. ; Chicago U., EFI ; Paris, LPTHE) ; Ruehle, Fabian (CERN ; Oxford U., Theor. Phys.)
We use numerical methods to obtain moduli-dependent Calabi-Yau metrics and from them the moduli-dependent massive tower of Kaluza-Klein states for the one-parameter family of quintic Calabi-Yau manifolds. We then compute geodesic distances in their Kähler and complex structure moduli space using exact expressions from mirror symmetry, approximate expressions, and numerical methods and compare the results. [...]
arXiv:2103.07472; CERN-TH-2021-032.- 2021-05-29 - 10 p. - Published in : Phys. Rev. D 103 (2021) 106028 Article from SCOAP3: PDF; Fulltext: PDF;
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6.
Moduli-dependent Calabi-Yau and SU(3)-structure metrics from Machine Learning / Anderson, Lara B. (Virginia Tech.) ; Gerdes, Mathis (Munich U., ASC) ; Gray, James (Virginia Tech.) ; Krippendorf, Sven (Munich U., ASC) ; Raghuram, Nikhil (Virginia Tech.) ; Ruehle, Fabian (CERN ; Oxford U., Theor. Phys.)
We use machine learning to approximate Calabi-Yau and SU(3)-structure metrics, including for the first time complex structure moduli dependence. Our new methods furthermore improve existing numerical approximations in terms of accuracy and speed [...]
arXiv:2012.04656; CERN-TH-2020-205.- 2021-05-03 - 15 p. - Published in : JHEP 2105 (2021) 013 Article from SCOAP3: scoap3-fulltext - PDF; scoap - PDF; Fulltext: Anderson2021_Article_Moduli-dependentCalabi-YauAndS_2 - PDF; 2012.04656 - PDF;
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7.
Learning to Unknot / Gukov, Sergei (Caltech, Pasadena (main)) ; Halverson, James (Northeastern U.) ; Ruehle, Fabian (CERN ; Oxford U., Theor. Phys.) ; Sułkowski, Piotr (Caltech, Pasadena (main) ; Warsaw U.)
We introduce natural language processing into the study of knot theory, as made natural by the braid word representation of knots. We study the UNKNOT problem of determining whether or not a given knot is the unknot. [...]
arXiv:2010.16263; CALT-2020-046; CERN-TH-2020-179.- 2021-04-23 - 30 p. - Published in : Mach. Learn. Sci. Tech. 2 (2021) 025035 Fulltext: PDF; Fulltext from publisher: PDF;
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Non-Simply-Connected Symmetries in 6D SCFTs / Dierigl, Markus (Pennsylvania U.) ; Oehlmann, Paul-Konstantin (Uppsala U.) ; Ruehle, Fabian (CERN ; Oxford U., Theor. Phys.)
Six-dimensional N=(1,0) superconformal field theories can be engineered geometrically via F-theory on elliptically-fibered Calabi-Yau 3-folds. We include torsional sections in the geometry, which lead to a finite Mordell-Weil group. [...]
arXiv:2005.12929; CERN-TH-2020-081; UUITP-14/20.- 2020-10-27 - 62 p. - Published in : JHEP 2010 (2020) 173 Article from SCOAP3: scoap3-fulltext - PDF; scoap - PDF; Fulltext: PDF;
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9.
Machine Learning and Algebraic Approaches towards Complete Matter Spectra in 4d F-theory / Bies, Martin (Oxford U., Inst. Math.) ; Cvetič, Mirjam (Pennsylvania U. ; Pennsylvania U., Dept. Math. ; Maribor U.) ; Donagi, Ron (Pennsylvania U. ; Pennsylvania U., Dept. Math.) ; Lin, Ling (CERN) ; Liu, Muyang (Pennsylvania U.) ; Ruehle, Fabian (CERN ; Oxford U., Theor. Phys.)
Motivated by engineering vector-like (Higgs) pairs in the spectrum of 4d F-theory compactifications, we combine machine learning and algebraic geometry techniques to analyze line bundle cohomologies on families of holomorphic curves. To quantify jumps of these cohomologies, we first generate 1.8 million pairs of line bundles and curves embedded in $dP_3$, for which we compute the cohomologies. [...]
arXiv:2007.00009; UPR-1305-T; CERN-TH-2020-111.- 2021-01-28 - 67 p. - Published in : JHEP 2101 (2021) 196 Article from SCOAP3: scoap3-fulltext - PDF; scoap - PDF; Fulltext: PDF;
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10.
Data science applications to string theory / Ruehle, Fabian (CERN ; Oxford U., Theor. Phys.)
We first introduce various algorithms and techniques for machine learning and data science. While there is a strong focus on neural network applications in unsupervised, supervised and reinforcement learning, other machine learning techniques are discussed as well. [...]
2020 - 117 p. - Published in : Phys. Rep. 839 (2020) 1-117 Fulltext: PDF;
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