Tuning Monte Carlo Generators: The Perugia Tunes (1005.3457v5)

Abstract: We present 9 new tunes of the pT-ordered shower and underlying-event model in PYTHIA 6.4. These "Perugia" tunes update and supersede the older "S0" family. The data sets used to constrain the models include hadronic Z0 decays at LEP, Tevatron minimum-bias data at 630, 1800, and 1960 GeV, Tevatron Drell-Yan data at 1800 and 1960 GeV, and SPS min-bias data at 200, 546, and 900 GeV. In addition to the central parameter set, called "Perugia 0", we introduce a set of 8 related "Perugia Variations" that attempt to systematically explore soft, hard, parton density, and colour structure variations in the theoretical parameters. Based on these variations, a best-guess prediction of the charged track multiplicity in inelastic, nondiffractive minimum-bias events at the LHC is made. Note that these tunes can only be used with PYTHIA 6, not with PYTHIA 8. Note: this report was updated in March 2011 with a new set of variations, collectively labeled "Perugia 2011", that are optimized for matching applications and which also take into account some lessons from the early LHC data. In order not to break the original text, these are described separately in Appendix B. Note 2: a subsequent "Perugia 2012" update is described in Appendix C.

• The paper introduces refined Monte Carlo tuning with Perugia Tunes to improve the accuracy of hadronic event simulations.
• It details methodological updates including pₜ-ordered showers, optimized color reconnections, and CTEQ5L PDF adjustments validated against collider data.
• It examines systematic uncertainties through Perugia variations, setting a robust framework for reliable extrapolations to LHC energies.

Analysis of the Perugia Tunes for Monte Carlo Event Generators

The paper "Tuning Monte Carlo Generators: The Perugia Tunes" by P.Z. Skands elucidates a series of systematic updates to the $p_\perp$-ordered shower and underlying-event model in Pythia 6.4, termed collectively as "Perugia Tunes." This collection supersedes the previous "S0" family of tunes, offering refined parameter sets to improve the modeling of hadronic events, with constraints derived from multiple data sets including those from LEP, Tevatron, and SPS.

The importance of tuning Monte Carlo models lies in their capacity to simulate complex collider environments with high fidelity, essential for testing theoretical predictions against experimental data. In this context, the Perugia tunes seek to enhance the predictive reliability of the Pythia framework, particularly targeting extrapolations to LHC energies. The tunes emphasize several key areas such as factorization and infrared safety, which are critical for translating perturbative theoretical calculations into physically measurable quantities.

The central tune, "Perugia 0," implements a variety of updates such as using CTEQ5L PDF sets and adjusting color reconnections to achieve balanced agreements with Tevatron data as seen in CDF and D$\O$ measurements of Drell-Yan pairs and minimum-bias events. Key adjustments include aligning the $\Lambda_\text{CMW}$ value for improved Drell-Yan $p_\perp$ agreement and modifying color reconnection models to better fit charged track multiplicity and underlying-event distributions.

The research also introduces "Perugia variations" to explore systematic theoretical uncertainties. The "HARD" and "SOFT" tunes examine different amounts of initial-state and final-state radiation, color reconnections, and other non-perturbative effects, presenting a spectrum of predictability for collider event characteristics like track multiplicities and $p_\perp$ distributions.

Practical implications of this work lie in the detailed modeling of collider data, offering a nuanced understanding of quantum chromodynamics in high-energy environments. Theoretical implications extend to refining models of particle production and interactions at the microscopic scale. As experiments at LHC continue to probe unexplored energy regimes, these tunes play a crucial role in facilitating accurate comparisons between data and theoretical expectations.

Future extensions of the work, as highlighted in the "2011" and "2012" updates, include further alignment with LHC data and additional variations like the implementation of alternative PDF sets, increased strangeness, and color reconnection modeling. These systematic updates offer a diversified approach, addressing potential discrepancies observed in LHC preliminary results, and propose variations such as the "Perugia 2012" tunes to comprehensively cover possible theoretical variation.

In summary, the Perugia Tunes constitute a targeted effort to enhance the fidelity of Monte Carlo simulations via meticulous parameter tuning, aiming for robust and flexible models that scale consistently from existing collider energies to those of the LHC and beyond. This work represents a significant contribution to the ongoing development and assessment of collider event generators within the high-energy physics community.