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Advancements in software developments


Presently, \(\gamma \)-ray tracking in germanium segmented detectors is realised by applying two advanced, complex algorithms. While they have already triggered an intensive R &D, they are still subject to further improvements. Running the common code for these core algorithms in both the online/real-time and offline data pipelines posed significant challenges. These were addressed in current production software, but also require continued attention in view of significant on-going paradigm shifts in both hardware and software technology. This review paper gives an overview of the various software components produced so far by the AGATA collaboration. It provides hints of what is foreseen for the next phases of the project up to its full configuration namely with 180 capsules in the array.

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Data Availability

This manuscript has associated data in a data repository. [Authors’ comment: Data access is governed by the AGATA Data Policy (].


  1. A. Boston et al., AGATA PSA review chapter (Topical Issue xref). AC_7c4e6a5494d6fa3624a6b34de562c441

  2. F. Crespi et al., AGATA: Performance of \(\gamma \)-ray tracking and associated algorithms (Topical Issue xref).

  3. A. Gadea et al., Nucl. Inst. and Meth. A 654, 88 (2011).

    Article  ADS  Google Scholar 

  4. C. Domingo-Pardo et al., Nucl. Inst. and Meth. A 694, 297 (2012).

    Article  ADS  Google Scholar 

  5. E. Clément et al., Nucl. Inst. and Meth. A 855, 1 (2017).

    Article  ADS  Google Scholar 

  6. J. Valiente-Dobón et al., Nucl. Inst. and Meth. A 1049, 168040 (2023).

    Article  Google Scholar 

  7. J. Collado et al., AGATA Phase 2 Advancements on Front-End Electronics (Topical Issue xref).

  8. X. Grave, et al., 14th IEEE-NPSS Real Time Conference, 5 (2005)

  9. The AGAPRO library,

  10. The ADF library,

  11. M. Bellato et al., J. Instrum. 8, P07003 (2013).

    Article  Google Scholar 

  12. B. Bruyneel et al., Eur. Phys. J. A 49, 61 (2013).

  13. S. Akkoyun et al., Nucl. Inst. and Meth. A 668, 26 (2012).

    Article  ADS  Google Scholar 

  14. F. E. Canet et al., LNL Annual Report 2017 (2017)

  15. Boost C++ Libraries,

  16. R. Brun, F. Rademakers, Nucl. Inst. and Meth. A 389, 81 (1997).

    Article  ADS  Google Scholar 

  17. M. Abadi, et al., “TensorFlow: Large-scale machine learning on heterogeneous systems,” (2015)

  18. F. Chollet et al., “ Keras,” (2015).

  19. F. Pezoa, et al., in Proceedings of the 25th International Conference on World Wide Web (2016) pp. 263–273

  20. K. Varda, Protocol Buffers: Google’s Data Interchange Format, Tech. Rep. (Google, 2008)

  21. flatbuffers,

  22. D. Merkel, Linux journal 2014, 2 (2014).

  23. G. M. Kurtzer, et al., “Singularity,” (2021)

  24. J. Postel, User Datagram Protocol (UDP), Tech. Rep. (1980)

  25. E. Eddy, W., Transmission Control Protocol (TCP), Tech. Rep. (2022)

  26. T. Bova, T. Krivoruchka, Reliable UDP Protocol, Tech. Rep. (1999)

  27. A. Buerger, private communication

  28. A. Korichi et al., Overview of the AGATA DAQ-box : a unified data acquisition system for different experimental conditions (Topical Issue xref).

  29. H. G. Essel, N. Kurz, in IEEE Conference on Real-Time Computer Applications in Nuclear Particle and Plasma Physics (1999) pp. 475–478

  30. V. Brigljevic, et al., in Conference for Computing in High-Energy and Nuclear Physics (2003)

  31. PostgreSQL,

  32. T. Bray, et al., “ Extensible markup language (xml) 1.0 (fifth edition),” (2008)

  33. Memcached,

  34. Redis,

  35. T. Hobson et al., in IEEE/ACM 21st International Symposium on Cluster. Cloud and Internet Computing (CCGrid) 2021, 123–132 (2021).

  36. D. Bazzacco, private communication

  37. The GammaWare library,

  38. A. Paszke, et al., in Advances in Neural Information Processing Systems 32 (Curran Associates, Inc., 2019) pp. 8024–8035

  39. X. Fabian et al., Nucl. Inst. and Meth. A 986, 164750 (2021).

    Article  Google Scholar 

  40. European Open Science Cloud,

  41. M.R. Crusoe et al., Commun. ACM 65, 54–63 (2022).

    Article  Google Scholar 

  42. H. Geissel et al., Nucl. Inst. and Meth. B 204, 71 (2003).

    Article  ADS  Google Scholar 

  43. M. Winkler et al., Nucl. Inst. and Meth. B 266, 4183 (2008).

    Article  ADS  Google Scholar 

  44. A. Stefanini et al., Nuc. Phys. A 701, 217 (2002).

    Article  Google Scholar 

  45. S. Szilner et al., Phys. Rev. C 76, 024604 (2007).

    Article  ADS  Google Scholar 

  46. M. Rejmund et al., Nucl. Inst. and Meth. A 646, 184 (2011).

    Article  ADS  Google Scholar 

  47. Y.H. Kim et al., Eur. Phys. J. A 53, 162 (2017).

    Article  ADS  Google Scholar 

  48. M. Assié et al., Nucl. Inst. and Meth. A 1014, 165743 (2021).

    Article  Google Scholar 

  49. The VAMOS library,

  50. The PRISMA library,

  51. A. Matta et al., J. Phys. G: Nucl. Part. Phys. 43, 045113 (2016).

    Article  ADS  Google Scholar 

  52. AgaSpy,

  53. L. Legeard, “Gru (ganil root utilities),”

  54. Grid File Access Library,

  55. Jupyter Notebooks,

  56. Hierarchical Data Format,

  57. The pandas development team,“pandas-dev/pandas: Pandas,” (2020)

  58. RStudio Team, “Rstudio: Integrated development environment for r,”

  59. M. Zaharia et al., Commun. ACM 59, 56–65 (2016).

    Article  Google Scholar 

  60. Apache Software Foundation, “Hadoop,”

  61. M. Cromaz et al., Nucl. Inst. and Meth. A 462, 519 (2001).

  62. O. Stézowski, C. Finck, D. Prévost, Nucl. Inst. and Meth. A 424, 552 (1999).

  63. InfluxDB,

  64. Grafana,

  65. Elasticsearch,

  66. S. Hochreiter, J. Schmidhuber, Neural Computation 9, 1735 (1997).

  67. M.D. Wilkinson et al., Scientific Data 3, 160018 (2016).

    Article  Google Scholar 

  68. Rucio,

  69. The EURO-LABS project,

  70. S. Chacon, B. Straub, Pro git (Apress, 2014)

  71. GitHub,

  72. GitLab,

  73. Cppcheck,

  74. SonarQube,

  75. Valgrind,

  76. E. Calore, D. Bazzacco, F. Recchia, Nucl. Inst. and Meth. A 719, 1 (2013).

    Article  ADS  Google Scholar 

  77. A. Lopez-Martens et al., Nucl. Inst. and Meth. A 533, 454 (2004).

    Article  ADS  Google Scholar 

  78. CMake,

  79. R. Jabbari et al., in Proceedings of the Scientific Workshop Proceedings of XP2016 (2016)

  80. Software Heritage,

  81. Modular Assembly Quality Analyser and Optimizer: MAQAO,

  82. Control of Accuracy and Debugging for Numerical Applications: CADNA,

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The authors would like to thank the whole AGATA collaboration. The production of all the essential bricks of software, their maintenance and optimisation is the result of a constant and tremendous amount of hard work involving a huge number of people in many European laboratories. Particular thanks go also to the skilled engineering and technical staff at the various host facilities for taking the additional charge of running the system during the physics campaigns. Part of this project has received financial support from the CNRS through the MITI interdisciplinary programs.

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Correspondence to O. Stézowski.

Additional information

Communicated by Nicolas Alamanos.

Y. Aubert: Deceased.

X. Grave: The author is on leave from IJCLab-CNRS

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Stézowski, O., Dudouet, J., Goasduff, A. et al. Advancements in software developments. Eur. Phys. J. A 59, 119 (2023).

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