PyHEP.dev 2024 - "Python in HEP" Developer's Workshop

Session

Kick-off talks

Aug 26, 2024, 9:30 AM

Aachen, Germany

25. Self-introduction: Eduardo Rodrigues

Eduardo Rodrigues (University of Liverpool (GB))

8/26/24, 9:30 AM

26. Self-introduction: Juraj Smiesko

Juraj Smiesko (CERN)

8/26/24, 9:37 AM

27. Self-introduction: Jan Bürger

Jan Bürger (ErUM-Data-Hub)

8/26/24, 9:44 AM

48. Self-introduction: Jim Pivarski

Jim Pivarski (Princeton University)

8/26/24, 9:51 AM

49. Self-introduction: Lino Oscar Gerlach

Lino Oscar Gerlach (Princeton University (US))

8/26/24, 9:58 AM

50. Self-introduction: Josue Molina

Josue Molina

8/26/24, 10:05 AM

51. Self-introduction: Ianna Osborne

Ianna Osborne (Princeton University)

8/26/24, 10:12 AM

52. Self-introduction: Máté Farkas

Mate Farkas (Rheinisch Westfaelische Tech. Hoch. (DE))

8/26/24, 10:19 AM

53. Self-introduction: Yaroslav Nikitenko

Yaroslav Nikitenko

8/26/24, 10:26 AM

23. Fast end-to-end analysis pipelines for the HL-LHC

Alexander Held (University of Wisconsin Madison (US)), Oksana Shadura (University of Nebraska Lincoln (US))

8/26/24, 10:40 AM

We provide an overview of two ongoing projects that aim to ensure the availability of fast and user-friendly solutions for physics analysis pipelines towards the HL-LHC. The Analysis Grand Challenge (AGC) defines an analysis task that captures relevant physics analysis workflow aspects. A variety of implementations have been developed for this task, allowing to probe user experience and...

29. Self-introduction: Peter Fackeldey

Manfred Peter Fackeldey (RWTH Aachen University (DE))

8/27/24, 9:00 AM

40. Self-introduction: Stefan Fröse

Stefan Fröse (ErUM-Data-Hub)

8/27/24, 9:01 AM

30. Self-introduction: Matthew Feickert

Matthew Feickert (University of Wisconsin Madison (US))

8/27/24, 9:07 AM

31. Self-introduction: Jonas Eschle

Jonas Eschle (Syracuse University (US))

8/27/24, 9:14 AM

33. Self-introduction: Alexander Held

Alexander Held (University of Wisconsin Madison (US))

8/27/24, 9:21 AM

35. Self-introduction: Giordon Holtsberg Stark

Dr Giordon Holtsberg Stark (University of California,Santa Cruz (US))

8/27/24, 9:28 AM

32. Self-introduction: Marcel Rieger

Marcel Rieger (Hamburg University (DE))

8/27/24, 9:35 AM

56. Self-introduction: Jonas Eppelt

Jonas Eppelt (Karlsruher Insititute of Technology (KIT))

8/27/24, 9:42 AM

57. Self-introduction: Alexander Heidelbach

Alexander Heidelbach

8/27/24, 9:49 AM

55. Self-introduction: Vincenzo Eduardo Padulano

Dr Vincenzo Eduardo Padulano (CERN)

8/27/24, 9:55 AM

17. An overview of the fitting ecosystem

Jonas Eschle (Syracuse University (US))

8/27/24, 10:02 AM

This talk will give a broad overview on the fitting that we're doing in
HEP. On one hand, the talk will cover the variety of fits in HEP, the
different needs and types of inference as well as efforts for
serialization and standardization. On the other hand, the relevant
libraries will be covered, that is zfit, pyhf, hepstats iminuit and
Python packages like SciPy and how they work...

20. evermore: differentiable (binned) likelihoods in JAX

Manfred Peter Fackeldey (RWTH Aachen University (DE))

8/27/24, 10:32 AM

I'd like to present evermore (https://github.com/pfackeldey/evermore) that focusses in efficiently building and evaluating likelihoods typically for HEP. Currently, it focusses on binned template fits.
It supports autodiff, JIT-compilation and vectorization of full fits (even on GPUs).

54. Plothist - integrating with other histogram libraries (Remote talk)

Cyrille Praz, Tristan Fillinger (KEK / IPNS)

8/28/24, 9:00 AM

34. Self-introduction: Saransh Copra

Saransh Chopra (Princeton University (US))

8/28/24, 9:20 AM

37. Self-introduction: Oksana Shadura

Oksana Shadura (University of Nebraska Lincoln (US))

8/28/24, 9:27 AM

38. Self-introduction: Nikolai Hartmann

Nikolai Hartmann (Ludwig Maximilians Universitat (DE))

8/28/24, 9:33 AM

18. b2luigi — bringing batch 2 luigi!

Alexander Heidelbach, Jonas Eppelt (Karlsruher Insititute of Technology (KIT))

8/28/24, 9:40 AM

Workflow managers help structure the code of pipelined jobs by defining and managing dependencies between tasks in a clear and easy-to-understand fashion. This abstraction allows independent tasks to be automatically parallelised more independently of computing systems. Additionally, workflow managers help keep track of different tasks’ outputs and inputs.

b2luigi is an extension of the...

22. End-to-end workflow automation: updates of the luigi analysis workflow package

Marcel Rieger (Hamburg University (DE))

8/28/24, 10:00 AM

Physicists performing data analyses are usually required to steer their individual, complex workflows manually, frequently involving job submission in several stages and interaction with distributed storage systems by hand. This process is not only time-consuming and error-prone, but also leads to undocumented relations between particular workloads, rendering the steering of an analysis a...

19. waluigi - Beyond luigi

Benjamin Fischer (RWTH Aachen University (DE))

8/28/24, 10:20 AM

Workflows for research in HEP experiments are not only quite complex but also require sufficient flexibility to adapt to changes in structuring, conditions, methodologies, and research interests. This holds especially true in the physics analyses extracting the results and measurements.
Here, the use of workflows systems, specifically Luigi, have shown to be of great use to manage and...

21. offloading @ coffea

Benjamin Fischer (RWTH Aachen University (DE))

8/28/24, 10:40 AM

Offloading resource intensive tasks, i.e.:
- histograms (accumulation) - memory intensive
- DL algorithms - compute intensive

60. Job openings in the ROOT team

Dr Vincenzo Eduardo Padulano (CERN)

8/29/24, 9:00 AM

36. Self-introduction: Benjamin Fischer

Benjamin Fischer (RWTH Aachen University (DE))

8/29/24, 9:05 AM

39. Self-introduction: Azzah Alshehri

Azzah Aziz Alshehri (University of Glasgow (GB))

8/29/24, 9:12 AM

14. File synchronization between Linux systems in Python with yarsync

Yaroslav Nikitenko

8/29/24, 9:25 AM

Yet Another Rsync is a Python wrapper around a well-established Linux tool rsync with a simple and familiar interface of git. Python allows us to create a higher-level instrument, which is safer and sometimes more efficient than the original binary.

While many data analysts today heavily use databases and rely on cloud computing, other approaches have also their benefits. Many...

13. Architectural framework for data analysis Lena

Yaroslav Nikitenko

8/29/24, 9:45 AM

The term «architecture» in software has numerous definitions. Ultimately it defines whether your analysis code will be extensible and maintainable. We propose an architecture based on the functional style and separation of data, logic and presentation. It is implemented in a free software framework Lena.

Lena is a general data analysis framework in Python, named after a great...

16. FCCAnalyses: A Framework for Future Circular Collider Physics Performance Studies

Juraj Smiesko (CERN)

8/29/24, 10:05 AM

Physics performance analyses provide essential input for defining detector requirements in the Future Circular Collider (FCC) project. To streamline these analyses, we employ FCCAnalyses, a software framework built on top of the ROOT DataFrame.

Among the functionalities offered by the FCCAnalyses are:
* Standard set of RDataFrame EDM4hep functions: Events can be analysed directly in the...

12. Bridging Python and Julia for Enhanced Data Analysis

Ianna Osborne (Princeton University)

8/29/24, 10:25 AM

Let’s discuss the exciting world of combining Python and Julia for data analysis for high-energy physics (HEP) and other data-intensive fields.

We'll kick things off with a quick overview of why Python is so popular for data analysis and introduce Julia, which is making waves with its incredible performance and suitability for scientific computing.

Next, I'll show you how we can get the...

24. A Deep Dive into PocketCoffea

Mate Farkas (Rheinisch Westfaelische Tech. Hoch. (DE))

8/29/24, 10:45 AM

PocketCoffea is a python columnar analysis framework based on coffea for CMS NanoAOD events. It provides a workflow for HEP analyses using a combination of customizable abstractions and configuration files. The package features dataset query automatisation, jet calibration, data processing, histogramming and plotting. PocketCoffea also provides support for code execution on various remote...

41. Self-introduction:

42. Self-introduction:

43. Self-introduction:

44. Self-introduction:

45. Self-introduction:

46. Self-introduction:

47. Self-introduction:

28. Self-introduction: Niclas Eich

Niclas Eich (Rheinisch Westfaelische Tech. Hoch. (DE))