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Kalman Filter Track Fits and Track Breakpoint Analysis

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Pierre Astier, Alessandro Cardini, Robert D. Cousins, Antoine Letessier-Selvon, Boris A. Popov, Tatiana Vinogradova

Data Analysis, Statistics and Probability · Submitted 16 Dec 1999

abstract compiled · 2026-09-23 · no language-model review

The authors' main claim We show how complete fits to the entire track, with breakpoint parameters added, can be easily obtained from the information from unbroken fits.

how it is stated · asserted 0.98 read the record →

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arXiv IDphysics/9912034 (version 1)
Pith IDK2OYGMVQ, Pith's permanent record of this paper and its review
CitationAlessandro Cardini, Antoine Letessier-Selvon, Boris A. Popov, Pierre Astier, Robert D. Cousins, Tatiana Vinogradova. "Kalman Filter Track Fits and Track Breakpoint Analysis." arXiv:physics/9912034 (1999). https://pith.science/paper/K2OYGMVQ
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The compiled record

The paper's own sentences, arranged. Each label is drawn from a closed vocabulary; the number beside it is the probability the classifier gave that label. Numbers in the tables are the authors', checked by code. No sentence in this record was written by a model.

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Compiled by classifier-1.13.0 via TypeSafe API, question bank abstract-p1-20260923, 2026-09-23: 1 request, 4,887 input tokens.

What the abstract itself states, as probabilities: claims first 0.04 · states limitation 0.06 · human participants 0.02 · controlled comparison 0.09 · randomized assignment 0.01 · states quantitative result 0.05 · compares with prior results 0.54 · mentions code or data availability 0.02.

The abstract, sentence by sentence

arXiv listing abstract v1. Results and the main claim are underlined; .

We give an overview of track fitting using the Kalman filter method in the NOMAD detector at CERN, and emphasize how the wealth of by-product information can be used to analyze track breakpoints (discontinuities in track parameters caused by scattering, decay, etc.). After reviewing how this information has been previously exploited by others, we describe extensions which add power to breakpoint detection and characterization. We show how complete fits to the entire track, with breakpoint parameters added, can be easily obtained from the information from unbroken fits. Tests inspired by the Fisher F-test can then be used to judge breakpoints. Signed quantities (such as change in momentum at the breakpoint) can supplement unsigned quantities such as the various chisquares. We illustrate the method with electrons from real data, and with Monte Carlo simulations of pion decays.

background contribution method result interpretation main claim

What the classifier reports for each sentence. The number is the probability it gave the label.
#sentencerolethe authors' own workstates the main conclusionstrength
s0 We give an overview of track fitting using the Kalman filter method in the NOMAD detector at CERN, and emphasize how the wealth of by-product information can be used to analyze track breakpoints (discontinuities in track parameters caused by scattering, decay, etc.). contribution 0.61 0.54 0.19 asserted 0.95
s1 After reviewing how this information has been previously exploited by others, we describe extensions which add power to breakpoint detection and characterization. contribution 0.69 0.52 0.07 asserted 0.88
s2 We show how complete fits to the entire track, with breakpoint parameters added, can be easily obtained from the information from unbroken fits. method 0.67 0.86 0.21 asserted 0.98
s3 Tests inspired by the Fisher F-test can then be used to judge breakpoints. method 0.92 0.55 0.11 asserted 0.56
s4 Signed quantities (such as change in momentum at the breakpoint) can supplement unsigned quantities such as the various chisquares. method 0.83 0.55 0.07 asserted 0.55
s5 We illustrate the method with electrons from real data, and with Monte Carlo simulations of pion decays. method 0.70 0.92 0.07 asserted 1.00

What kind of paper the classifier reports this is: method or tool 1.00 · evidence from analysis of existing data 0.80.

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  • figures and tables
  • references and citing sentences
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  • P abstract
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  • S sections
  • T body sentences
  • C citations
  • R cross-paper relations

Every quoted sentence on this record is the authors'. Every label is from Pith's closed vocabulary, with the probability shown beside it. Every number in the measurements table is the authors', checked by code. Record as JSON

The paper
Original abstract

We give an overview of track fitting using the Kalman filter method in the NOMAD detector at CERN, and emphasize how the wealth of by-product information can be used to analyze track breakpoints (discontinuities in track parameters caused by scattering, decay, etc.). After reviewing how this information has been previously exploited by others, we describe extensions which add power to breakpoint detection and characterization. We show how complete fits to the entire track, with breakpoint parameters added, can be easily obtained from the information from unbroken fits. Tests inspired by the Fisher F-test can then be used to judge breakpoints. Signed quantities (such as change in momentum at the breakpoint) can supplement unsigned quantities such as the various chisquares. We illustrate the method with electrons from real data, and with Monte Carlo simulations of pion decays.

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