On a first order transition in QCD with up, down and strange quarks

Guo, Xiao-Yu; Heo, Yonggoo; Lutz, Matthias

doi:10.1140/epjc/s10052-020-7818-9

Cited by 11 publications

(28 citation statements)

References 46 publications

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“…Most striking is the opposite sign in h A , which we interpret as a signal for the importance of strangeness loop effects. This is in line with a striking prediction of the flavor-SU(3) analyses [15,18], which obtained a strangeness sigma term of the isobar σ s −270 MeV, significantly larger in magnitude than its corresponding value for the nucleon with σ s N 45 MeV (here we provide unpublished results from Ref. [18]).…”

Section: Fit To Qcd Lattice Datasupporting

confidence: 89%

“…In general, the region around m π = 375 MeV seems is very interesting, because, when varying M N , M and g A in terms of the pion mass, we find a clear jump. This has been observed before [17,18] in SU(3) and is nicely displayed in Figs. 8 and 9.…”

Section: Fit To Qcd Lattice Datasupporting

confidence: 78%

“…scheme, we consider the various lattice scales as free parameters in our global fit. Such a strategy was successfully used in various global fits to lattice data [15,18,27]. Our results for all lattice scales are shown in Table 2.…”

Section: Fit To Qcd Lattice Datamentioning

confidence: 95%

“…It is illuminating to also compare our set of LEC with results from flavor-SU(3) analyses. Here we focus on the most recent work [18], which achieved a global fit to the baryon octet and decuplet masses as provided by various lattice groups. In Table 4 we collect values that are obtained by a tree-level matching of the flavor-SU(2) with the flavor-SU(3) chiral Lagrangian.…”

Section: Fit To Qcd Lattice Datamentioning

confidence: 99%

“…5, we present the results of the fits of our expressions to the available QCD lattice data for the nucleon and isobar masses and for the axial-vector form factor. We show that the use of on-shell masses in the one-loop expressions results in non-analytic behavior of the masses [17,18] and form factor as function of the pion mass and its dependence on the lattice size. We discuss the quality of the fit and the resulting values of the parameters.…”

Section: Introductionmentioning

confidence: 96%

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On the axial-vector form factor of the nucleon and chiral symmetry

2020

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We consider the chiral Lagrangian with nucleon, isobar, and pion degrees of freedom. The baryon masses and the axial-vector form factor of the nucleon are derived at the one-loop level. We explore the impact of using on-shell baryon masses in the loop expressions. As compared to results from conventional chiral perturbation theory we find significant differences. An application to QCD lattice data is presented. We perform a global fit to the available lattice data sets for the baryon masses and the nucleon axial-vector form factor, and determine the low-energy constants relevant at $$\hbox {N}^3$$ N 3 LO for the baryon masses and at $$\hbox {N}^2$$ N 2 LO for the form factor. Partial finite-volume effects are considered. We point out that the use of on-shell masses in the loops results in non-analytic behavior of the baryon masses and the form factor as function of the pion mass, which becomes prominent for larger lattice volumes than presently used.

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Section: Fit To Qcd Lattice Datasupporting

confidence: 89%

Section: Fit To Qcd Lattice Datasupporting

confidence: 78%

Section: Fit To Qcd Lattice Datamentioning

confidence: 95%

Section: Fit To Qcd Lattice Datamentioning

confidence: 99%

Section: Introductionmentioning

confidence: 96%

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On the axial-vector form factor of the nucleon and chiral symmetry

2020

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Parametric Optimization on HPC Clusters with Geneva

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Berlich

Schwarz

et al. 2023

Comput Softw Big Sci

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Many challenges of today’s science are parametric optimization problems that are extremely complex and computationally intensive to calculate. At the same time, the hardware for high-performance computing is becoming increasingly powerful. Geneva is a framework for parallel optimization of large-scale problems with highly nonlinear quality surfaces in grid and cloud environments. To harness the immense computing power of high-performance computing clusters, we have developed a new networking component for Geneva—the so-called MPI Consumer—which makes Geneva suitable for HPC. Geneva is most prominent for its evolutionary algorithm, which requires repeatedly evaluating a user-defined cost function. The MPI Consumer parallelizes the computation of the candidate solutions’ cost functions by sending them to remote cluster nodes. By using an advanced multithreading mechanism on the master node and by using asynchronous requests on the worker nodes, the MPI Consumer is highly scalable. Additionally, it provides fault tolerance, which is usually not the case for MPI programs but becomes increasingly important for HPC. Moreover, the MPI Consumer provides a framework for the intuitive implementation of fine-grained parallelization of the cost function. Since the MPI Consumer conforms to the standard paradigm of HPC programs, it vastly improves Geneva’s user-friendliness on HPC clusters. This article gives insight into Geneva’s general system architecture and the system design of the MPI Consumer as well as the underlying concepts. Geneva—including the novel MPI Consumer—is publicly available as an open source project on GitHub (https://github.com/gemfony/geneva) and is currently used for fundamental physics research at GSI in Darmstadt, Germany.

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