About
We present a new Monte Carlo that generates events based on statistics specified with any 1-point and 2-point function, including arbitrary correlations. Such a code can be useful for quickly generating events when analytic formulas are known (for example from recent derivations of CGC fluctuations), and for use in Bayesian analyses, where the initial state can be characterized by physical-meaningful parameter such as mean energy density, variance, skewness, correlation length, etc. We use the new code to perform investigations of CGC fluctuations. We study the effect of model parameters such as saturation scale and regulators (both infrared and ultraviolet), as well as the effects of higher-order fluctuations, which are currently unknown. This provides useful information, even beyond the particular model, of how such fluctuation and correlation properties can appear in observable quantities. We investigate how correlated and uncorrelated events compare, and quantify the sensitivity of relevant properties such as eccentricities $\varepsilon_n$ to correlation lengths.
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The talk
Credits and licence
- Institution
- CERN
- Department
- Conferences
- Speaker
- Rodrigo Franco
- Year
- 2021
- Language
- English
- Subjects
- Earth and environment
- Source
- CERN
- Licence
- CERN, as CERN states it. CERN's terms
- Attribution
- © CERN. CERN provides its audiovisual media free of charge for educational and informational use, credited to CERN; this lecture is shown in CERN's own player.
- Who can watch
- CERN gives no rating. Invisible Network shows it to Tweens profiles and older, judged from what the source says about it. How courses are placed