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Curvature of the pseudocritical line in the QCD phase diagram from mesonic lattice correlation functions
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Chris Allton ,
Ryan Bignell ,
Benjamin Jäger ,
Seung-il Nam ,
Seyong Kim ,
Jon-Ivar Skullerud ,
Liang-Kai Wu
Physical Review D, Volume: 112, Issue: 11
Swansea University Authors:
Antonio Smecca, Gert Aarts , Chris Allton , Ryan Bignell
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DOI (Published version): 10.1103/wjm8-4smh
Abstract
In the QCD phase diagram, the dependence of the pseudo-critical temperature, T_pc, on the baryon chemical potential, mu_B, is of fundamental interest. The variation of T_pc with mu_B is normally captured by kappa, the coefficient of the leading (quadratic) term of the polynomial expansion of T_pc wi...
| Published in: | Physical Review D |
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| ISSN: | 2470-0010 2470-0029 |
| Published: |
American Physical Society (APS)
2025
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| Online Access: |
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| URI: | https://cronfa.swan.ac.uk/Record/cronfa71412 |
| Abstract: |
In the QCD phase diagram, the dependence of the pseudo-critical temperature, T_pc, on the baryon chemical potential, mu_B, is of fundamental interest. The variation of T_pc with mu_B is normally captured by kappa, the coefficient of the leading (quadratic) term of the polynomial expansion of T_pc with mu_B. In this work, we present the first calculation of kappa using hadronic quantities. Simulating N_f=2+1 flavours of Wilson fermions on Fastsum ensembles, we calculate the O(mu_B^2) correction to mesonic correlation functions. By demanding degeneracy in the vector and axial-vector channels we obtain T_pc(mu_B) and hence kappa. While lacking a continuum extrapolation and being away from the physical point, our results are consistent with previous works using thermodynamic observables (renormalised chiral condensate, strange quark number susceptibility) from lattice QCD simulations with staggered fermions. |
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| College: |
Faculty of Science and Engineering |
| Funders: |
This work is supported by the UKRI Science and Technology Facilities Council (STFC) Consolidated Grant No. ST/X000648/1. We are grateful to Supercomputing Wales for the use of their computing resources and to the Swansea Academy for Advanced Computing for support. R. B. acknowledges support from a Science Foundation Ireland Frontiers for the Future Project award with Grant No. SFI-21/FFP-P/10186. This work used the DiRAC Data Intensive service (DIaL2 / DIaL2.5) at the University of Leicester, managed by the University of Leicester Research Computing Service on behalf of the STFC DiRAC HPC Facility ([59]). The DiRAC service at Leicester was funded by BEIS, UKRI and STFC capital funding and STFC operations grants. It also used the DiRAC Blue Gene Q Shared Petaflop system at the University of Edinburgh, operated by the Edinburgh Parallel Computing Centre on behalf of the STFC DiRAC HPC Facility ([59]). This equipment was funded by BIS National E-infrastructure Capital Grant No. ST/K000411/1, STFC Capital Grant No. ST/H008845/1, and STFC DiRAC Operations Grants No. ST/K005804/1 and No. ST/K005790/1. DiRAC is part of the National E-Infrastructure. This work used the computing resources of the Irish Centre for High-End Computing (ICHEC). This work was performed using the PRACE Marconi-KNL resources hosted by CINECA, Italy. We acknowledge EuroHPC Joint Undertaking for awarding the project EHPC-EXT-2023E01-010 access to LUMI-C, Finland. S. K. is supported by the National Research Foundation of Korea under Grant No. NRF-2021R1A2C1092701 funded by the Korean government (MEST) and by the Institute of Information & Communication Technology Planning & Evaluation grant funded by the Korean government (Ministry of Science and ICT) (Grant No. IITP-2024-RS-2024-00437191). |
| Issue: |
11 |