
Raphaelle Bailhache contributed to the AliceO2Group/O2Physics repository by developing and refining data analysis and simulation features for high-energy particle physics workflows. Over six months, Raphaelle implemented enhancements such as phi-angle track filtering, maximum transverse momentum cuts, and event selection logic within the SkimmerOTS structure, all using C++ and configuration files. These changes improved the precision and efficiency of particle selection and event processing, supporting more reliable and reproducible analyses. By addressing normalization bugs and expanding heavy-flavor simulation configurations, Raphaelle demonstrated strong skills in C++ development, data filtering, and Monte Carlo simulation, delivering maintainable solutions that improved analysis quality and workflow traceability.

For 2025-12, delivered a feature enhancement in AliceO2Group/O2Physics: Event Selection Enhancement in SkimmerOTS. By integrating collision selection logic into the skimmerOTS structure, the event processing path became more accurate and trigger handling more reliable, contributing to robust data processing and downstream trigger pipelines. No major bugs were reported this month; work focused on feature integration, code quality, and maintainability.
For 2025-12, delivered a feature enhancement in AliceO2Group/O2Physics: Event Selection Enhancement in SkimmerOTS. By integrating collision selection logic into the skimmerOTS structure, the event processing path became more accurate and trigger handling more reliable, contributing to robust data processing and downstream trigger pipelines. No major bugs were reported this month; work focused on feature integration, code quality, and maintainability.
Monthly summary for 2025-11: Delivered a high-impact feature in O2Physics to improve data quality and analysis efficiency, with clean, well-documented commits and clear business value.
Monthly summary for 2025-11: Delivered a high-impact feature in O2Physics to improve data quality and analysis efficiency, with clean, well-documented commits and clear business value.
In July 2025, delivered a focused feature in AliceO2Group/O2Physics that enhances track filtering by phi angle. The new options support mirroring the phi range and rejecting specific phi intervals, enabling more granular and flexible event filtering for PWGEM analyses. This directly improves the precision of physics selections, reduces noise, and enhances reproducibility of results. The change is implemented via commit 2d0c61bea28628e60b75ca25c900969d28bcd434 ([PWGEM] Add the possibility to select Phi regions, #11978).
In July 2025, delivered a focused feature in AliceO2Group/O2Physics that enhances track filtering by phi angle. The new options support mirroring the phi range and rejecting specific phi intervals, enabling more granular and flexible event filtering for PWGEM analyses. This directly improves the precision of physics selections, reduces noise, and enhances reproducibility of results. The change is implemented via commit 2d0c61bea28628e60b75ca25c900969d28bcd434 ([PWGEM] Add the possibility to select Phi regions, #11978).
May 2025 achievements centered on improving heavy flavor (HF) simulation fidelity and stability across O2Physics and O2DPG. Key features delivered: in O2DPG, new 13 TeV HF cocktail configurations for beauty and charm in Pythia8, including forced decays, color reconnection and string fragmentation parameters, plus expanded energy setups (pp502, pp536) to broaden HF coverage. Major bug fixes: in O2Physics, refactored HF cocktail filtering to PDG-code ranges to ensure only open charm/beauty semileptonic decays and exclusion of quarkonia; in O2DPG, reverted forced open-beauty decays back to a general semileptonic charm decay to restore default behavior. Overall impact: improved physics purity and realism, enhanced configurability and reproducibility of HF event simulations, and reduced risk of unintended decays. Technologies/skills demonstrated: PDG-code based filtering, refactoring from string logic to numeric range checks, Pythia8 HF cocktail configuration, energy-scoped HF channels, and disciplined version-control changes.
May 2025 achievements centered on improving heavy flavor (HF) simulation fidelity and stability across O2Physics and O2DPG. Key features delivered: in O2DPG, new 13 TeV HF cocktail configurations for beauty and charm in Pythia8, including forced decays, color reconnection and string fragmentation parameters, plus expanded energy setups (pp502, pp536) to broaden HF coverage. Major bug fixes: in O2Physics, refactored HF cocktail filtering to PDG-code ranges to ensure only open charm/beauty semileptonic decays and exclusion of quarkonia; in O2DPG, reverted forced open-beauty decays back to a general semileptonic charm decay to restore default behavior. Overall impact: improved physics purity and realism, enhanced configurability and reproducibility of HF event simulations, and reduced risk of unintended decays. Technologies/skills demonstrated: PDG-code based filtering, refactoring from string logic to numeric range checks, Pythia8 HF cocktail configuration, energy-scoped HF channels, and disciplined version-control changes.
April 2025: Targeted improvements to O2Physics Beauty/Charm analysis normalization, focusing on data quality and robust physics conclusions for heavy-flavor measurements.
April 2025: Targeted improvements to O2Physics Beauty/Charm analysis normalization, focusing on data quality and robust physics conclusions for heavy-flavor measurements.
March 2025 monthly summary for AliceO2Group/O2Physics: Delivered a feature to simplify quark data collection within the PWGEM task by removing histogram weights. No major bugs fixed this month. Overall impact includes streamlined data collection, improved maintainability, and clearer data-processing provenance. Technologies demonstrated include C++/ROOT histogram handling, PWGEM workflow, and Git-based change tracking (commit 6585df1db7d9805798b588d68255c905b5b5ff07).
March 2025 monthly summary for AliceO2Group/O2Physics: Delivered a feature to simplify quark data collection within the PWGEM task by removing histogram weights. No major bugs fixed this month. Overall impact includes streamlined data collection, improved maintainability, and clearer data-processing provenance. Technologies demonstrated include C++/ROOT histogram handling, PWGEM workflow, and Git-based change tracking (commit 6585df1db7d9805798b588d68255c905b5b5ff07).
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