Performance of two-level sampling for the glueball spectrum in pure gauge theory Article Swipe
Lorenzo Barca
,
Francesco Knechtli
,
Mike Peardon
,
Stefan Schaefer
,
Juan Andrés Urrea-Niño
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.22323/1.453.0030
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.22323/1.453.0030
The computation of the glueball spectrum is particularly challenging due to the rapid decay of the signal-to-noise ratio of the correlation functions. To address this issue, advanced techniques such as gauge link smearing and the variational method are commonly employed to identify the spectrum before the signal diminishes significantly. However, a significant improvement in the signal-to-noise ratio can be achieved by utilising multilevel sampling techniques. In this talk, we present a study of the glueball spectrum in pure gauge theory with a two-level algorithm. Specifically, we explore the relation between noise reduction and the various multilevel parameters, such as the width of the dynamical regions and the number of submeasurements.
Related Topics
Concepts
Glueball
Spectrum (functional analysis)
Noise (video)
Computation
SIGNAL (programming language)
Sampling (signal processing)
Gauge (firearms)
Physics
Signal-to-noise ratio (imaging)
Algorithm
Statistical physics
Mathematics
Computer science
Particle physics
Quantum mechanics
Artificial intelligence
Optics
Materials science
Detector
Image (mathematics)
Metallurgy
Programming language
Meson
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.22323/1.453.0030
- https://pos.sissa.it/453/030/pdf
- OA Status
- gold
- Cited By
- 1
- References
- 17
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4390273644
All OpenAlex metadata
Raw OpenAlex JSON
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https://openalex.org/W4390273644Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.22323/1.453.0030Digital Object Identifier
- Title
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Performance of two-level sampling for the glueball spectrum in pure gauge theoryWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
-
2023Year of publication
- Publication date
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2023-12-27Full publication date if available
- Authors
-
Lorenzo Barca, Francesco Knechtli, Mike Peardon, Stefan Schaefer, Juan Andrés Urrea-NiñoList of authors in order
- Landing page
-
https://doi.org/10.22323/1.453.0030Publisher landing page
- PDF URL
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https://pos.sissa.it/453/030/pdfDirect link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
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goldOpen access status per OpenAlex
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https://pos.sissa.it/453/030/pdfDirect OA link when available
- Concepts
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Glueball, Spectrum (functional analysis), Noise (video), Computation, SIGNAL (programming language), Sampling (signal processing), Gauge (firearms), Physics, Signal-to-noise ratio (imaging), Algorithm, Statistical physics, Mathematics, Computer science, Particle physics, Quantum mechanics, Artificial intelligence, Optics, Materials science, Detector, Image (mathematics), Metallurgy, Programming language, MesonTop concepts (fields/topics) attached by OpenAlex
- Cited by
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1Total citation count in OpenAlex
- Citations by year (recent)
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2024: 1Per-year citation counts (last 5 years)
- References (count)
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- Related works (count)
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10Other works algorithmically related by OpenAlex
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