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Department of Applied Mathematics and Theoretical Physics

Dr Sven Krippendorf

Publications

Detecting symmetries with neural networks
S Krippendorf, M Syvaeri
– Machine Learning: Science and Technology
(2020)
2,
015010
(doi: 10.1088/2632-2153/abbd2d)
GANs for generating EFT models
H Erbin, S Krippendorf
– Physics Letters B
(2020)
810,
135798
(doi: 10.1016/j.physletb.2020.135798)
UV Shadows in EFTs: Accidental Symmetries, Robustness and No‐Scale Supergravity
CP Burgess, M Cicoli, D Ciupke, S Krippendorf, F Quevedo
– Fortschritte Der Physik
(2020)
68,
2000076
(doi: 10.1002/prop.202000076)
Connecting Dualities and Machine Learning
P Betzler, S Krippendorf
– Fortschritte der Physik
(2020)
68,
2000022
(doi: 10.1002/prop.202000022)
Moduli stars
S Krippendorf, F Muia, F Quevedo
– Journal of High Energy Physics
(2018)
2018,
70
(doi: 10.1007/JHEP08(2018)070)
The string soundscape at gravitational wave detectors
IG Garcia, S Krippendorf, J March-Russell
– Physics Letters B
(2018)
779,
348
(doi: 10.1016/j.physletb.2018.02.028)
Searching for axion-like particles with X-ray polarimeters
F Day, S Krippendorf
– Galaxies
(2018)
6,
45
(doi: 10.3390/galaxies6020045)
Oscillons from string moduli
S Antusch, F Cefalà, S Krippendorf, F Muia, S Orani, F Quevedo
– Journal of High Energy Physics
(2018)
2018,
83
(doi: 10.1007/JHEP01(2018)083)
Consistency of Hitomi, XMM-Newton, and Chandra 3.5 keV data from Perseus
JP Conlon, F Day, N Jennings, S Krippendorf, M Rummel
– Physical Review D
(2017)
96,
123009
(doi: 10.1103/physrevd.96.123009)
Projected bounds on ALPs from Athena
JP Conlon, F Day, N Jennings, S Krippendorf, F Muia
– Monthly Notices of the Royal Astronomical Society
(2017)
473,
4932
(doi: 10.1093/mnras/stx2652)
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Research Group

High Energy Physics

Email

slk38@cam.ac.uk

Room

B1.13

Study at Cambridge

About the University

Research at Cambridge