- Library Home /
- Search Collections /
- Open Collections /
- Browse Collections /
- BIRS Workshop Lecture Videos /
- Machine Learning for string vacua
Open Collections
BIRS Workshop Lecture Videos
BIRS Workshop Lecture Videos
Machine Learning for string vacua Ruehle, Fabian
Description
In string theory, we face a gigantic number of backgrounds, each of which comes with different implications for particle physics and cosmology.
On top of this, every backgrounds has a huge number of possible vacua or near-vacua. We describe the computational complexity of the
challenges associated with both finding a viable background and finding vacua for this background, and apply machine learning to study a
small subset of them.
Item Metadata
| Title |
Machine Learning for string vacua
|
| Creator | |
| Publisher |
Banff International Research Station for Mathematical Innovation and Discovery
|
| Date Issued |
2019-05-03T09:00
|
| Description |
In string theory, we face a gigantic number of backgrounds, each of which comes with different implications for particle physics and cosmology.
On top of this, every backgrounds has a huge number of possible vacua or near-vacua. We describe the computational complexity of the
challenges associated with both finding a viable background and finding vacua for this background, and apply machine learning to study a
small subset of them.
|
| Extent |
33.0 minutes
|
| Subject | |
| Type | |
| File Format |
video/mp4
|
| Language |
eng
|
| Notes |
Author affiliation: CERN
|
| Series | |
| Date Available |
2019-10-31
|
| Provider |
Vancouver : University of British Columbia Library
|
| Rights |
Attribution-NonCommercial-NoDerivatives 4.0 International
|
| DOI |
10.14288/1.0384826
|
| URI | |
| Affiliation | |
| Peer Review Status |
Unreviewed
|
| Scholarly Level |
Postdoctoral
|
| Rights URI | |
| Aggregated Source Repository |
DSpace
|
Item Media
Item Citations and Data
Rights
Attribution-NonCommercial-NoDerivatives 4.0 International