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Innovative Algorithms in Statistics: Clusters by Content & Algorithm

Explore the latest advancements in algorithms at ACAT02, covering topics from clusters by content to neural nets and genetic algorithms. Discover examples from the session, such as new tracking and vertexing algorithms, parallel computing, and code development guidelines in HEP. Unveil the application of algorithms in real scenarios, like CMS tracking improvements and online triggers optimization. Get insights into handling large data, adaptive algorithms, and interpreting detector responses. Experience the diverse range of topics discussed at ACAT02, emphasizing the importance of sharing and spreading innovative algorithms for future experiments.

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Innovative Algorithms in Statistics: Clusters by Content & Algorithm

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Presentation Transcript

  1. Session IV: Innovative Algorithms • The Sum • Statistics • Clusters by Content • Clusters by Algorithm • Examples from the session • Interpretation ACAT02

  2. Summary, but How? • Very diverse topics • Almost impossible to summarize: You should have been there. • Solution: Different approaches! ACAT02

  3. Summary: The Sum • Adding it all up • (the transparencies, that is) ACAT02

  4. Summary: Statistics • 3 posters • 15 talks • From about 13 experiments • 4h 20min of oral interaction in room 02 • One overhead projector broken • Doesn’t help either. ACAT02

  5. Summary – For Real • Clusters of posters and talks • Handling of large amounts of data: Compression, many-parameter-problem • Parallel and localized computing algorithms • Interpreting detector responses (particle identification, energy reconstruction, percolation processes, triggers, digital filtering…) • New tracking and vertexing algorithms • Code development guidelines in HEP ACAT02

  6. Algorithms • Algorithmic clusters • Adaptive algorithms, Riemann space tracking • Neural Nets: Improved, applied and studied • Genetic Algorithms: Applied and adopted for parallel computing • Filtering, classical optimizations, compression • ISO-15504 for software management • and many others ACAT02

  7. Example: Tracking • New development by CMS tracking group: Improvement over Kalman fitter seen; fast, robust and precise algorithms. Combined development of new tracking and vertexing algorithms with application for CMS and performance studies See talks by R. Fruehwirth, A. Strandlie, W. Waltenberger ACAT02

  8. Example: NN, Genetic Algorithms • Applications in online triggers: • J.M. de Seixas on removing Atlas TileCal outsiders • S. Abdullin on genetic algorithm for optimizing CMS’s SUSY triggers • Further applications: • V. Vinogradov on LHC online HadCal E reconstruction • M. Bogolyubsky on direct photon ID with ALICE’s photon spectrometer ACAT02

  9. Example: Links Outside • Some had a look outside and returned with news • Some are outside EHEP and told us about it • H.-P. Wellisch on ISO software management standards and their application and feasibility for HEP. It works. “As long as one has the support of Senior Personnel.” • M. Kosov on an chiral invariant phase space event generator for hadrons which can predict e.g. hadron masses, structure functions and cross sections ACAT02

  10. S HEP Huge spread where new and improved algorithms are developed for and applied at, within and outside and into HEP dx  Interpretation • Disclaimer: Personal view, not a result of an algorithm • Future and running experiments highly active in extensions of algorithms, but also development of new ones • Judging from session, highest activity at CERN and in Russia (and their overlap, which seems to be Vienna) ACAT02

  11. Interpretation • Interesting algorithms  “nice to see once” • They should be shared and spread! • common languages (OO helps, too), common software libs, links across experiments, regions, languages and (software) cultures • Sometimes algorithm not recognized to be fundamental, or just the last extra step not taken for the algorithm to be re-usable. + - ACAT02

  12. Interpretation • ACAT plays an important role here: • To discuss and share new algorithms • To remind us that often we don’t write a specific solution, but a more fundamental algorithm for which other users exist • To create links across experiments, countries and even fields of application • To feed authors of algorithms with great shashlik and smooth vodka 3 ACAT02

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