Phenomenological Constraints on the Transport Properties of QCD Matter with Data-Driven Model Averaging
| dc.contributor.author | Roland, Gunther | |
| dc.contributor.author | Chen, Y. | |
| dc.date.accessioned | 2022-04-27T15:42:19Z | |
| dc.date.available | 2022-04-27T15:42:19Z | |
| dc.date.issued | 2021 | |
| dc.identifier.uri | https://hdl.handle.net/1721.1/142131 | |
| dc.description.abstract | Using combined data from the Relativistic Heavy Ion and Large Hadron Colliders, we constrain the shear and bulk viscosities of quark-gluon plasma (QGP) at temperatures of ∼150-350 MeV. We use Bayesian inference to translate experimental and theoretical uncertainties into probabilistic constraints for the viscosities. With Bayesian model averaging we propagate an estimate of the model uncertainty generated by the transition from hydrodynamics to hadron transport in the plasma's final evolution stage, providing the most reliable phenomenological constraints to date on the QGP viscosities. | en_US |
| dc.language.iso | en | |
| dc.publisher | American Physical Society (APS) | en_US |
| dc.relation.isversionof | 10.1103/PHYSREVLETT.126.242301 | en_US |
| dc.rights | Creative Commons Attribution 4.0 International license | en_US |
| dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | en_US |
| dc.source | APS | en_US |
| dc.title | Phenomenological Constraints on the Transport Properties of QCD Matter with Data-Driven Model Averaging | en_US |
| dc.type | Article | en_US |
| dc.identifier.citation | Roland, Gunther. 2021. "Phenomenological Constraints on the Transport Properties of QCD Matter with Data-Driven Model Averaging." Physical Review Letters, 126 (24). | |
| dc.contributor.department | Massachusetts Institute of Technology. Laboratory for Nuclear Science | |
| dc.contributor.department | Massachusetts Institute of Technology. Department of Physics | |
| dc.relation.journal | Physical Review Letters | en_US |
| dc.eprint.version | Final published version | en_US |
| dc.type.uri | http://purl.org/eprint/type/JournalArticle | en_US |
| eprint.status | http://purl.org/eprint/status/PeerReviewed | en_US |
| dc.date.updated | 2022-04-27T15:29:32Z | |
| dspace.orderedauthors | Everett, D; Ke, W; Paquet, J-F; Vujanovic, G; Bass, SA; Du, L; Gale, C; Heffernan, M; Heinz, U; Liyanage, D; Luzum, M; Majumder, A; McNelis, M; Shen, C; Xu, Y; Angerami, A; Cao, S; Chen, Y; Coleman, J; Cunqueiro, L; Dai, T; Ehlers, R; Elfner, H; Fan, W; Fries, RJ; Garza, F; He, Y; Jacak, BV; Jacobs, PM; Jeon, S; Kim, B; Kordell, M; Kumar, A; Mak, S; Mulligan, J; Nattrass, C; Oliinychenko, D; Park, C; Putschke, JH; Roland, G; Schenke, B; Schwiebert, L; Silva, A; Sirimanna, C; Soltz, RA; Tachibana, Y; Wang, X-N; Wolpert, RL | en_US |
| dspace.date.submission | 2022-04-27T15:29:33Z | |
| mit.journal.volume | 126 | en_US |
| mit.journal.issue | 24 | en_US |
| mit.license | PUBLISHER_CC | |
| mit.metadata.status | Authority Work and Publication Information Needed | en_US |
