A comparison of spectral reconstruction methods applied to non-zero temperature NRQCD meson correlation functions

Spriggs, Thomas; Aarts, Gert; Allton, Chris; Burns, Timothy J.; D'Arcy, Rachel Horohan; Jäger, Benjamin; Kim, Seyong; Lombardo, Maria-Paola; Offler, Sam; Page, Ben; Ryan, Sinéad M.; Skullerud, Jon-Ivar

doi:10.1051/epjconf/202225805011

Cited by 7 publications

(9 citation statements)

References 11 publications

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“…Lattice QCD is a powerful such approach, and numerical computations of the correlation functions in eq. (1.1) have led to significant JHEP10(2022)161 advancement in the understanding of finite-temperature phenomena [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17]. On the lattice it is the spatial correlators, integrated over the orthogonal directions, that are accessible over the largest distances and hence contain the most information about the thermal system.…”

Section: Introductionmentioning

confidence: 99%

Pion spectral properties above the chiral crossover of QCD

Lowdon

Philipsen

2022

J. High Energ. Phys.

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Spectral functions encode a wealth of information about the dynamics of any given system, and the determination of their non-perturbative characteristics is a long-standing problem in quantum field theory. Whilst numerical simulations of lattice QCD provide ample data for various Euclidean correlation functions, the inversion required to extract spectral functions is an ill-posed problem. In this work, we pursue previously established constraints imposed by field locality at finite temperature T, namely that spectral functions possess a non-perturbative representation which generalises the well-known Källén-Lehmann spectral form to T > 0. Using this representation, we analyse lattice QCD data of the spatial pseudo-scalar correlator in the temperature range 220–960 MeV, and obtain an analytic expression for the corresponding spectral function, with parameters fixed by the data. From the structure of this spectral function we find evidence for the existence of a distinct pion state above the chiral pseudo-critical temperature Tpc, and contributions from its first excitation, which gradually melt as the temperature increases. As a non-trivial test, we find that the extracted spectral function reproduces the corresponding temporal lattice correlator data for T = 220 MeV.

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Section: Introductionmentioning

confidence: 99%

Pion spectral properties above the chiral crossover of QCD

Lowdon

Philipsen

2022

J. High Energ. Phys.

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“…Such a comparison is shown in the upper panel. It was found [22] that an extrapolation to τ 2 = ∞ at the lowest temperature gave a width consistent with zero. The bottom panel shows the width as function of temperature using the same fit window for all T ; we see no change below T c and an increase of up to 60 MeV at T = 300 MeV.…”

Section: Beauty Hadronsmentioning

confidence: 97%

“…Some results from this investigation have been presented in Ref. [22]. The left hand plot shows spectral functions obtained using the BR method for selected temperatures, compared to the spectral functions ρ rec (ω) obtained from correlators at the lowest available .…”

Section: Beauty Hadronsmentioning

confidence: 99%

“…The right hand panel of fig. 4 shows the Υ width determined from fits to the correlators using a Gaussian Ansatz for the spectral function [22]. Both the mass and the width are found to depend strongly on the fit window used, so a comparison of results using the same fit window at different temperatures is mandatory to disentangle real physical effects from this artefact.…”

Section: Beauty Hadronsmentioning

confidence: 99%

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Hadrons at high temperature: An update from the FASTSUM collaboration

et al. 2022

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“…Our hunch is that the generation of decorrelated configurations in LQCD using methods such as normalizing flows [46] will be one of the first successes beyond the examples of predicting expensive to calculate correlation functions in terms of cheaper ones as discussed in [40]. Another exciting application of ML in the analysis of data is to estimate the real-time spectral function from lattice data for the Euclidean 2-point function [41,49,50,42], a notoriously difficult problem since the latter is the Laplace transform of the former.…”

Section: Contrasting Two Black Boxes: Lattice Qcd and MLmentioning

confidence: 99%

AI and Theoretical Particle Physics

Gupta¹,

Bhattacharya²,

Yoon³

2022

Preprint

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Theoretical particle physicists continue to push the envelope in both high performance computing and in managing and analyzing large data sets. For example, the goals of sub-percent accuracy in predictions of quantum chromodynamics (QCD) using large scale simulations of lattice QCD and in finding signals of rare events and new physics in exabytes of data produced by experiments at the high luminosity large hadron collider (LHC) require new tools beyond just developments in hardware. Machine learning and artificial intelligence offer the promise of dramatically reducing the computational cost and time. This chapter reviews selected areas where AI/ML tools could have a major impact, provides an overview of the challenges, and discusses how new ideas such as normalizing flows can speed up the generation of gauge configurations needed in lattice QCD calculations; the growth of ML in surrogate models and pattern matching to reduce the cost of event generators and in the analysis of experimental data; and in the search for viable vacua in the landscape of string theories. While such approaches transform aspects of particle theory into computational problems, and thus black boxes, we argue that physics-aware development of these tools combined with algorithms that ensure that the results are bias free will continue to require a deep understanding of the physics. We see this broader transformation as akin to formulating and extracting observables from simulations of lattice QCD, a numerical integration of the path integral formulation of QCD that nevertheless requires a deep understanding of the underlying quantum field theory, the standard model of particle physics and effective field theory methods.

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A comparison of spectral reconstruction methods applied to non-zero temperature NRQCD meson correlation functions

Cited by 7 publications

References 11 publications

Pion spectral properties above the chiral crossover of QCD

Pion spectral properties above the chiral crossover of QCD

Hadrons at high temperature: An update from the FASTSUM collaboration

AI and Theoretical Particle Physics

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