AliceO2Group/O2Physics
Oct 2024 – Jan 2026
13 Months active
Languages Used
C++
Technical Skills
C++ DevelopmentData AnalysisMonte Carlo SimulationParticle PhysicsC++High Energy Physics
jaelpark
PROFILE
Jaelpark
Jasper Parkkila developed advanced data analysis and simulation features for the AliceO2Group/O2Physics repository, focusing on high-energy particle physics workflows. He engineered configurable Monte Carlo filtering, invariant mass-based candidate identification, and robust event selection mechanisms, leveraging C++ and ROOT for efficient processing. His work integrated machine learning scoring, optimized histogramming, and improved MC efficiency calculations, addressing both data and simulation pipelines. By refactoring code to reduce duplication and implementing modular, reproducible analysis components, Jasper enhanced analysis fidelity and maintainability. His contributions enabled more accurate physics measurements, streamlined event filtering, and supported scalable, collaborative research in high-energy physics environments.
Overall Statistics
Feature vs Bugs
79%Features
Repository Contributions
39Total
Bugs
5
Commits
39
Features
19
Lines of code
2,230
Activity Months13
Your Network
429 people
Work History
January 2026
5 Commits • 3 Features
Jan 1, 2026Monthly summary for January 2026 focusing on the AliceO2Group/O2Physics work, highlighting delivered features, bug fixes, impact, and technical skills demonstrated. The month emphasizes business value through improved analysis capabilities, data filtering, and reproducible workflows in a high-energy physics context.
5 Commits • 3 Features
Jan 1, 2026Monthly summary for January 2026 focusing on the AliceO2Group/O2Physics work, highlighting delivered features, bug fixes, impact, and technical skills demonstrated. The month emphasizes business value through improved analysis capabilities, data filtering, and reproducible workflows in a high-energy physics context.
January 2026
December 2025
1 Commits • 1 Features
Dec 1, 2025December 2025 (Month: 2025-12) focused on delivering a key performance improvement for the 2-prong Monte Carlo (MC) simulation in the AliceO2Group/O2Physics repository. Implemented efficiency improvements by refining the outlier cut logic and optimizing histogram filling for track efficiency, enabling faster simulation iterations and more reliable track efficiency estimates. No major bugs fixed this month. Overall impact includes reduced computational time per MC run and improved data quality for downstream physics analyses, supported by a linked commit.
December 2025
1 Commits • 1 Features
Dec 1, 2025December 2025 (Month: 2025-12) focused on delivering a key performance improvement for the 2-prong Monte Carlo (MC) simulation in the AliceO2Group/O2Physics repository. Implemented efficiency improvements by refining the outlier cut logic and optimizing histogram filling for track efficiency, enabling faster simulation iterations and more reliable track efficiency estimates. No major bugs fixed this month. Overall impact includes reduced computational time per MC run and improved data quality for downstream physics analyses, supported by a linked commit.
November 2025
1 Commits • 1 Features
Nov 1, 2025November 2025 monthly summary for AliceO2Group/O2Physics focusing on delivering selectable outlier cuts in Monte Carlo reconstruction to improve analysis of collision data. Implemented feature enabling multiplicity-based filtering in the MC reco path; prepared for future tuning and performance checks. No major bug fixes recorded this month. The work enhances data quality, analysis precision, and pipeline robustness.
1 Commits • 1 Features
Nov 1, 2025November 2025 monthly summary for AliceO2Group/O2Physics focusing on delivering selectable outlier cuts in Monte Carlo reconstruction to improve analysis of collision data. Implemented feature enabling multiplicity-based filtering in the MC reco path; prepared for future tuning and performance checks. No major bug fixes recorded this month. The work enhances data quality, analysis precision, and pipeline robustness.
November 2025
October 2025
3 Commits • 2 Features
Oct 1, 2025October 2025 monthly summary for AliceO2Group/O2Physics: Delivered key features to enhance PWGCF analysis workflows, fixed critical issues, and demonstrated cross-cutting skills in configurable data analysis. The work improves business value by enabling more flexible event filtering, consistent histogram naming, and flexible correlation axes configuration, reducing debugging time and increasing reliability of physics analyses.
October 2025
3 Commits • 2 Features
Oct 1, 2025October 2025 monthly summary for AliceO2Group/O2Physics: Delivered key features to enhance PWGCF analysis workflows, fixed critical issues, and demonstrated cross-cutting skills in configurable data analysis. The work improves business value by enabling more flexible event filtering, consistent histogram naming, and flexible correlation axes configuration, reducing debugging time and increasing reliability of physics analyses.
September 2025
1 Commits
Sep 1, 2025September 2025 – O2Physics (AliceO2Group): Stabilized the JFFlucAnalysisO2Hist workflow by preventing crashes when MultSet is disabled. Implemented defensive initialization of histogram pointers to null, eliminating a null-dereference path and ensuring safe operation when multiplicity features are toggled off. This improvement enhances reliability of the JCorran analysis pipeline and reduces processing downtime for analysts.
1 Commits
Sep 1, 2025September 2025 – O2Physics (AliceO2Group): Stabilized the JFFlucAnalysisO2Hist workflow by preventing crashes when MultSet is disabled. Implemented defensive initialization of histogram pointers to null, eliminating a null-dereference path and ensuring safe operation when multiplicity features are toggled off. This improvement enhances reliability of the JCorran analysis pipeline and reduces processing downtime for analysts.
September 2025
August 2025
7 Commits • 2 Features
Aug 1, 2025August 2025 monthly summary for O2Physics development. Objective focused on stabilizing data processing, expanding analysis capabilities, and improving performance. Delivered robust MC data handling, new efficiency correction capabilities, and scalable multiplicity/correlation analysis infrastructure. Results support more reliable physics studies, faster feedback loops, and clearer traceability of work through commit-level changes.
August 2025
7 Commits • 2 Features
Aug 1, 2025August 2025 monthly summary for O2Physics development. Objective focused on stabilizing data processing, expanding analysis capabilities, and improving performance. Delivered robust MC data handling, new efficiency correction capabilities, and scalable multiplicity/correlation analysis infrastructure. Results support more reliable physics studies, faster feedback loops, and clearer traceability of work through commit-level changes.
July 2025
7 Commits • 3 Features
Jul 1, 2025Monthly performance summary for 2025-07 focusing on O2Physics (AliceO2Group). Key features delivered include 2-prong Monte Carlo processing and identification improvements, D0 MC candidate processing with ML probability integration, and MC data processing support for the JCorran analysis. These efforts strengthen MC realism, data-model alignment, and analysis pipelines.
7 Commits • 3 Features
Jul 1, 2025Monthly performance summary for 2025-07 focusing on O2Physics (AliceO2Group). Key features delivered include 2-prong Monte Carlo processing and identification improvements, D0 MC candidate processing with ML probability integration, and MC data processing support for the JCorran analysis. These efforts strengthen MC realism, data-model alignment, and analysis pipelines.
July 2025
June 2025
2 Commits • 1 Features
Jun 1, 2025June 2025, AliceO2Group/O2Physics: Delivered two key updates to MC processing that improve the accuracy and reliability of MC-based efficiency estimates for D0 analyses. A bug fix corrects MC particle indexing in the 2-prong filter and improves handling of fake tracks, eliminating a source of biased efficiency results. A feature update refactors MC processing to focus on D0 decays for efficiency calculations, introduces a dedicated efficiency bin, and adds a prompt-particle flag to further improve estimation accuracy. These changes enhance the fidelity of physics measurements, reduce systematic biases, and demonstrate robust C++ refactoring, MC processing, and efficiency design skills. Business value: more trustworthy efficiency metrics leading to more credible physics results and easier cross-checks for future analyses.
June 2025
2 Commits • 1 Features
Jun 1, 2025June 2025, AliceO2Group/O2Physics: Delivered two key updates to MC processing that improve the accuracy and reliability of MC-based efficiency estimates for D0 analyses. A bug fix corrects MC particle indexing in the 2-prong filter and improves handling of fake tracks, eliminating a source of biased efficiency results. A feature update refactors MC processing to focus on D0 decays for efficiency calculations, introduces a dedicated efficiency bin, and adds a prompt-particle flag to further improve estimation accuracy. These changes enhance the fidelity of physics measurements, reduce systematic biases, and demonstrate robust C++ refactoring, MC processing, and efficiency design skills. Business value: more trustworthy efficiency metrics leading to more credible physics results and easier cross-checks for future analyses.
April 2025
1 Commits • 1 Features
Apr 1, 2025Month: 2025-04. This period focused on delivering a new invariant-mass-based 2-prong candidate identification method in the O2Physics module, with configurable masses, particle identification (PID), and invariant mass cuts, plus an integrated track sigma evaluation. The implementation supports both data and Monte Carlo (MC) workflows and is designed for easy extension across analyses. No critical regressions were observed in related code paths; maintenance windows were kept short through clear commit-level ownership and documentation of the new method.
1 Commits • 1 Features
Apr 1, 2025Month: 2025-04. This period focused on delivering a new invariant-mass-based 2-prong candidate identification method in the O2Physics module, with configurable masses, particle identification (PID), and invariant mass cuts, plus an integrated track sigma evaluation. The implementation supports both data and Monte Carlo (MC) workflows and is designed for easy extension across analyses. No critical regressions were observed in related code paths; maintenance windows were kept short through clear commit-level ownership and documentation of the new method.
April 2025
March 2025
4 Commits • 1 Features
Mar 1, 2025March 2025 monthly summary for AliceO2Group/O2Physics: Delivered a feature-rich PWGCF 2-prong correlation analysis with ML scoring and track efficiency, enabling unified 2-prong processing via template-based paths, ML-based selections for same-event and mixed-event correlations, and histogram-level ML score filtering for invariant mass. Completed a refactor to reduce correlations code duplication, improving maintainability and reducing technical debt. Implemented ML scoring integration across the correlation workflow and histogram processing to support MC track efficiency analyses and more robust physics results. Demonstrated business value by enabling more accurate data selections, faster analysis turnaround, and clearer traceability through commit-driven changes.
March 2025
4 Commits • 1 Features
Mar 1, 2025March 2025 monthly summary for AliceO2Group/O2Physics: Delivered a feature-rich PWGCF 2-prong correlation analysis with ML scoring and track efficiency, enabling unified 2-prong processing via template-based paths, ML-based selections for same-event and mixed-event correlations, and histogram-level ML score filtering for invariant mass. Completed a refactor to reduce correlations code duplication, improving maintainability and reducing technical debt. Implemented ML scoring integration across the correlation workflow and histogram processing to support MC track efficiency analyses and more robust physics results. Demonstrated business value by enabling more accurate data selections, faster analysis turnaround, and clearer traceability through commit-driven changes.
February 2025
4 Commits • 1 Features
Feb 1, 2025February 2025: Delivered substantive enhancements to particle correlation analysis in PWGCF within the O2Physics repository, including new methodologies for two-particle and four-particle correlations with differential measurements, PbPb centrality estimators for correlations filtering, and a local efficiency loader integrated into JCorran to apply weights during track processing. Implemented correctness improvements in centrality processing to properly account for new variants in the enabledFunctions counter, reducing risk of missed or double-counted analyses. These changes advance physics accuracy for PbPb studies and demonstrate end-to-end improvements from data loading to analysis execution.
4 Commits • 1 Features
Feb 1, 2025February 2025: Delivered substantive enhancements to particle correlation analysis in PWGCF within the O2Physics repository, including new methodologies for two-particle and four-particle correlations with differential measurements, PbPb centrality estimators for correlations filtering, and a local efficiency loader integrated into JCorran to apply weights during track processing. Implemented correctness improvements in centrality processing to properly account for new variants in the enabledFunctions counter, reducing risk of missed or double-counted analyses. These changes advance physics accuracy for PbPb studies and demonstrate end-to-end improvements from data loading to analysis execution.
February 2025
January 2025
2 Commits • 2 Features
Jan 1, 2025January 2025 monthly summary for AliceO2Group/O2Physics focusing on delivering features that enable deeper physics insights and higher-quality data for PbPb analyses. Key outcomes include introduction of a new invariant mass dependent JCorran analysis axis and improved PbPb event selection criteria to ensure higher-quality events. These changes streamline downstream analyses, improve data quality, and support more robust physics conclusions. Demonstrated strengths in C++/ROOT analysis, data quality assurance, PWGCF guidelines, and reproducibility.
January 2025
2 Commits • 2 Features
Jan 1, 2025January 2025 monthly summary for AliceO2Group/O2Physics focusing on delivering features that enable deeper physics insights and higher-quality data for PbPb analyses. Key outcomes include introduction of a new invariant mass dependent JCorran analysis axis and improved PbPb event selection criteria to ensure higher-quality events. These changes streamline downstream analyses, improve data quality, and support more robust physics conclusions. Demonstrated strengths in C++/ROOT analysis, data quality assurance, PWGCF guidelines, and reproducibility.
October 2024
1 Commits • 1 Features
Oct 1, 2024October 2024: Delivered Monte Carlo PDG-code filtering for correlation analysis in AliceO2Group/O2Physics. Implemented a configuration-based mechanism to filter MC particles by PDG codes, including trigger and exclusion lists for tighter particle selection. The change, committed as 0519a20fcaf468172a0f7a06eafb05bed19fb464, enables cleaner MC-based correlation studies, improving analysis accuracy and reproducibility. No major bug fixes documented this month; this feature directly enhances data quality and supports downstream physics results through more reliable selection criteria.
1 Commits • 1 Features
Oct 1, 2024October 2024: Delivered Monte Carlo PDG-code filtering for correlation analysis in AliceO2Group/O2Physics. Implemented a configuration-based mechanism to filter MC particles by PDG codes, including trigger and exclusion lists for tighter particle selection. The change, committed as 0519a20fcaf468172a0f7a06eafb05bed19fb464, enables cleaner MC-based correlation studies, improving analysis accuracy and reproducibility. No major bug fixes documented this month; this feature directly enhances data quality and supports downstream physics results through more reliable selection criteria.
October 2024
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Quality Metrics
Correctness86.4%
Maintainability83.6%
Architecture82.6%
Performance73.4%
AI Usage20.0%
Skills & Technologies
Programming Languages
C++
Technical Skills
Algorithm DevelopmentBug FixingC++C++ DevelopmentC++ programmingCode Duplication ReductionCode OrganizationData AnalysisData ProcessingData StructuresDebuggingEvent ProcessingHigh Energy PhysicsMC SimulationMachine Learning Integration
Repositories Contributed To
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