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A Comparative Study of Regression Methods for Solving the Timepix Calibration Task.

Jan Broulím1,2, Matěj Prokop1, Libor Nouzák2

  • 1Czech Technical University, Jugoslavskych Partyzanu 1580/3, 16000 Prague, Czech Republic.

Sensors (Basel, Switzerland)
|November 13, 2025
PubMed
Summary

This study optimizes energy calibration for Timepix detectors using iterative algorithms. Novel methods improve the mapping of Time-over-Threshold data to accurate energy measurements.

Keywords:
Levenberg–MarquardtTimepixTimepix3Timepix4calibrationoptimization algorithmsregressionvariable projection

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Area of Science:

  • Physics
  • Instrumentation
  • Data Analysis

Background:

  • Timepix-type detectors are crucial for particle detection.
  • Accurate energy calibration is essential for Timepix data interpretation.
  • The Time-over-Threshold (ToT) mode requires non-linear energy mapping.

Purpose of the Study:

  • To investigate and improve the energy calibration model for Timepix detectors.
  • To enhance the convergence properties of iterative algorithms for calibration.
  • To introduce a novel partial linearization method for the calibration problem.

Main Methods:

  • Modification of Gradient-Descent, Gauss-Newton, and Levenberg-Marquardt algorithms.
  • Application of the variable projection method for partial linearization.
  • Testing and comparison of modified iterative algorithms and the novel method.

Main Results:

  • Improved convergence properties for modified iterative algorithms.
  • Successful implementation of a partially linearized calibration model.
  • Demonstration of the effectiveness of the novel calibration approach.

Conclusions:

  • The modified iterative algorithms offer enhanced performance for Timepix energy calibration.
  • The proposed partial linearization method provides a novel and effective approach.
  • This work contributes to more accurate energy measurements from Timepix detectors.