19 research outputs found
Analyzing high energy physics data using database computing: Preliminary report
A proof of concept system is described for analyzing high energy physics (HEP) data using data base computing. The system is designed to scale up to the size required for HEP experiments at the Superconducting SuperCollider (SSC) lab. These experiments will require collecting and analyzing approximately 10 to 100 million 'events' per year during proton colliding beam collisions. Each 'event' consists of a set of vectors with a total length of approx. one megabyte. This represents an increase of approx. 2 to 3 orders of magnitude in the amount of data accumulated by present HEP experiments. The system is called the HEPDBC System (High Energy Physics Database Computing System). At present, the Mark 0 HEPDBC System is completed, and can produce analysis of HEP experimental data approx. an order of magnitude faster than current production software on data sets of approx. 1 GB. The Mark 1 HEPDBC System is currently undergoing testing and is designed to analyze data sets 10 to 100 times larger
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Requirements for a system to analyze HEP events using database computing
We describe the requirements for the design and prototyping of an object-oriented database designed to analyze data in high energy physics. Our goal is to satisfy the data processing and analysis needs of a generic high energy physics experiment to be proposed for the Superconducting SuperCollider (SSC), and requires the collection and analysis of between 10 and 100 million sets of vectors (events), each approximately one megabyte in length. We sketch how this analysis would proceed using an object-oriented database which support the basic data types used in HEP
On the Classification of Dynamical Data Streams Using Novel “Anti–Bayesian” Techniques
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On utilizing weak estimators to achieve the online classification of data streams
Author's accepted version (post-print).Available from 03/09/2021.acceptedVersio