publication . Preprint . 2018

Automatic trajectory recognition in Active Target Time Projection Chambers data by means of hierarchical clustering

Dalitz, Christoph; Ayyad, Yassid; Wilberg, Jens; Aymans, Lukas; Bazin, Daniel; Mittig, Wolfgang;
Open Access English
  • Published: 10 Jul 2018
Abstract
The automatic reconstruction of three-dimensional particle tracks from Active Target Time Projection Chambers data can be a challenging task, especially in the presence of noise. In this article, we propose a non-parametric algorithm that is based on the idea of clustering point triplets instead of the original points. We define an appropriate distance measure on point triplets and then apply a single-link hierarchical clustering on the triplets. Compared to parametric approaches like RANSAC or the Hough transform, the new algorithm has the advantage of potentially finding trajectories even of shapes that are not known beforehand. This feature is particularly im...
Subjects
free text keywords: Physics - Instrumentation and Detectors, Statistics - Machine Learning, Nuclear Experiment
Funded by
NSF| Operation of the NSCL as a National User Facilty & Research Program
Project
  • Funder: National Science Foundation (NSF)
  • Project Code: 1102511
  • Funding stream: Directorate for Mathematical & Physical Sciences | Division of Physics
,
NSF| MRI: Development of an Active Target Time Projection Chamber to Study Reactions Induced by Exotic Beams
Project
  • Funder: National Science Foundation (NSF)
  • Project Code: 0923087
  • Funding stream: Directorate for Mathematical & Physical Sciences | Division of Physics
Download from
17 references, page 1 of 2

[1] M. Thoennessen, B. Sherrill, From isotopes to the stars, Nature 473 (7345) (2011) 25-26. URL http://dx.doi.org/10.1038/473025a

[2] Motobayashi, Tohru, World new facilities for radioactive isotope beams, EPJ Web of Conferences 66 (2014) 01013. doi:10.1051/epjconf/ 20146601013. URL https://doi.org/10.1051/epjconf/20146601013 [OpenAIRE]

[3] S. Beceiro-Novo, et al., Active targets for the study of nuclei far from stability, Progress in Particle and Nuclear Physics 84 (2015) 124 - 165.

[4] J. Bradt, D. Bazin, F. Abu-Nimeh, T. Ahn, Y. Ayyad, S. BeceiroNovo, L. Carpenter, M. Cortesi, M. Kuchera, W. Lynch, W. Mittig, S. Rost, N. Watwood, J. Yurkon, Commissioning of the active-target time projection chamber, Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment 875 (2017) 65 - 79. doi:https://doi.org/10.1016/j.nima.2017.09.013. URL http://www.sciencedirect.com/science/article/pii/ S0168900217309683 [OpenAIRE]

[5] A. Wuosmaa, J. Schi er, B. Back, C. Lister, K. Rehm, A solenoidal spectrometer for reactions in inverse kinematics, Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment 580 (3) (2007) 1290 - 1300. doi:https://doi.org/10.1016/j.nima.2007.07.029. URL http://www.sciencedirect.com/science/article/pii/ S0168900207014490

[6] W. Mittig, S. Beceiro-Novo, A. Fritsch, F. Abu-Nimeh, D. Bazin, T. Ahn, W. Lynch, F. Montes, A. Shore, D. Suzuki, N. Usher, J. Yurkon, J. Kolata, A. Howard, A. Roberts, X. Tang, F. Becchetti, Active target detectors for studies with exotic beams: Present and next future, Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment 784 (2015) 494 - 498, symposium on Radiation Measurements and Applications 2014 (SORMA XV). doi:https://doi.org/10.1016/j.nima.2014.10.048. URL http://www.sciencedirect.com/science/article/pii/ S0168900214012054

[7] W. Mittig, P. Roussel-Chomaz, Results and techniques of measurements with inverse kinematics, Nuclear Physics A 693 (1) (2001) 495 - 513, radioactive Nuclear Beams. doi:https: //doi.org/10.1016/S0375-9474(00)00690-4. URL http://www.sciencedirect.com/science/article/pii/ S0375947400006904 [OpenAIRE]

[8] M. Jeltsch, C. Dalitz, R. Pohle-Fro¨hlich, Hough parameter space regularisation for line detection in 3D, in: International Conference on Computer Vision Theory and Applications (VISAPP), 2016, pp. 345-352.

[9] M. A. Fischler, R. C. Bolles, Random sample consensus: A paradigm for model fitting with applications to image analysis and automated cartography, in: M. A. Fischler, , O. Firschein (Eds.), Readings in Computer Vision, Morgan Kaufmann, San Francisco (CA), 1987, pp. 726 - 740.

[10] C. Dalitz, T. Schramke, M. Jeltsch, Iterative Hough transform for line detection in 3D point clouds, Image Processing On Line 7 (2017) 184- 196. doi:10.5201/ipol.2017.208.

[11] Y. Ayyad, W. Mittig, D. Bazin, S. Beceiro-Novo, M. Cortesi, Novel particle tracking algorithm based on the random sample consensus model for the active target time projection chamber (AT-TPC), Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment 880 (2018) 166-173.

[12] J. Lezama, G. Randall, J.-M. Morel, R. Grompone von Gioi, An unsupervised algorithm for detecting good continuation in dot patterns, Image Processing On Line 7 (2017) 81-92. doi:10.5201/ipol.2017.176.

[13] AT-TPC experimental program: A list of approved experiments at the nscl can be found here: https://enterprise.nscl.msu.edu/completedexperiments/ (e18027, e18019, e18008, e17504, e17025, e15250, e15238).

[14] D. R. Nygren, Proposal to investigate the feasibility of a novel concept in particle detection, LBL internal report, February 1974.

[15] D. Suzuki, A. Shore, W. Mittig, J. J. Kolata, D. Bazin, M. Ford, T. Ahn, F. D. Becchetti, S. Beceiro Novo, D. Ben Ali, B. Bucher, J. Browne, X. Fang, M. Febbraro, A. Fritsch, E. Galyaev, A. M. Howard, N. Keeley, W. G. Lynch, M. Ojaruega, A. L. Roberts, X. D. Tang, Resonant scattering of 6He: Limits of clustering in 10Be, Phys. Rev. C 87 (2013) 054301. doi:10.1103/PhysRevC.87.054301. URL https://link.aps.org/doi/10.1103/PhysRevC.87. 054301 [OpenAIRE]

17 references, page 1 of 2
Abstract
The automatic reconstruction of three-dimensional particle tracks from Active Target Time Projection Chambers data can be a challenging task, especially in the presence of noise. In this article, we propose a non-parametric algorithm that is based on the idea of clustering point triplets instead of the original points. We define an appropriate distance measure on point triplets and then apply a single-link hierarchical clustering on the triplets. Compared to parametric approaches like RANSAC or the Hough transform, the new algorithm has the advantage of potentially finding trajectories even of shapes that are not known beforehand. This feature is particularly im...
Subjects
free text keywords: Physics - Instrumentation and Detectors, Statistics - Machine Learning, Nuclear Experiment
Funded by
NSF| Operation of the NSCL as a National User Facilty & Research Program
Project
  • Funder: National Science Foundation (NSF)
  • Project Code: 1102511
  • Funding stream: Directorate for Mathematical & Physical Sciences | Division of Physics
,
NSF| MRI: Development of an Active Target Time Projection Chamber to Study Reactions Induced by Exotic Beams
Project
  • Funder: National Science Foundation (NSF)
  • Project Code: 0923087
  • Funding stream: Directorate for Mathematical & Physical Sciences | Division of Physics
Download from
17 references, page 1 of 2

[1] M. Thoennessen, B. Sherrill, From isotopes to the stars, Nature 473 (7345) (2011) 25-26. URL http://dx.doi.org/10.1038/473025a

[2] Motobayashi, Tohru, World new facilities for radioactive isotope beams, EPJ Web of Conferences 66 (2014) 01013. doi:10.1051/epjconf/ 20146601013. URL https://doi.org/10.1051/epjconf/20146601013 [OpenAIRE]

[3] S. Beceiro-Novo, et al., Active targets for the study of nuclei far from stability, Progress in Particle and Nuclear Physics 84 (2015) 124 - 165.

[4] J. Bradt, D. Bazin, F. Abu-Nimeh, T. Ahn, Y. Ayyad, S. BeceiroNovo, L. Carpenter, M. Cortesi, M. Kuchera, W. Lynch, W. Mittig, S. Rost, N. Watwood, J. Yurkon, Commissioning of the active-target time projection chamber, Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment 875 (2017) 65 - 79. doi:https://doi.org/10.1016/j.nima.2017.09.013. URL http://www.sciencedirect.com/science/article/pii/ S0168900217309683 [OpenAIRE]

[5] A. Wuosmaa, J. Schi er, B. Back, C. Lister, K. Rehm, A solenoidal spectrometer for reactions in inverse kinematics, Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment 580 (3) (2007) 1290 - 1300. doi:https://doi.org/10.1016/j.nima.2007.07.029. URL http://www.sciencedirect.com/science/article/pii/ S0168900207014490

[6] W. Mittig, S. Beceiro-Novo, A. Fritsch, F. Abu-Nimeh, D. Bazin, T. Ahn, W. Lynch, F. Montes, A. Shore, D. Suzuki, N. Usher, J. Yurkon, J. Kolata, A. Howard, A. Roberts, X. Tang, F. Becchetti, Active target detectors for studies with exotic beams: Present and next future, Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment 784 (2015) 494 - 498, symposium on Radiation Measurements and Applications 2014 (SORMA XV). doi:https://doi.org/10.1016/j.nima.2014.10.048. URL http://www.sciencedirect.com/science/article/pii/ S0168900214012054

[7] W. Mittig, P. Roussel-Chomaz, Results and techniques of measurements with inverse kinematics, Nuclear Physics A 693 (1) (2001) 495 - 513, radioactive Nuclear Beams. doi:https: //doi.org/10.1016/S0375-9474(00)00690-4. URL http://www.sciencedirect.com/science/article/pii/ S0375947400006904 [OpenAIRE]

[8] M. Jeltsch, C. Dalitz, R. Pohle-Fro¨hlich, Hough parameter space regularisation for line detection in 3D, in: International Conference on Computer Vision Theory and Applications (VISAPP), 2016, pp. 345-352.

[9] M. A. Fischler, R. C. Bolles, Random sample consensus: A paradigm for model fitting with applications to image analysis and automated cartography, in: M. A. Fischler, , O. Firschein (Eds.), Readings in Computer Vision, Morgan Kaufmann, San Francisco (CA), 1987, pp. 726 - 740.

[10] C. Dalitz, T. Schramke, M. Jeltsch, Iterative Hough transform for line detection in 3D point clouds, Image Processing On Line 7 (2017) 184- 196. doi:10.5201/ipol.2017.208.

[11] Y. Ayyad, W. Mittig, D. Bazin, S. Beceiro-Novo, M. Cortesi, Novel particle tracking algorithm based on the random sample consensus model for the active target time projection chamber (AT-TPC), Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment 880 (2018) 166-173.

[12] J. Lezama, G. Randall, J.-M. Morel, R. Grompone von Gioi, An unsupervised algorithm for detecting good continuation in dot patterns, Image Processing On Line 7 (2017) 81-92. doi:10.5201/ipol.2017.176.

[13] AT-TPC experimental program: A list of approved experiments at the nscl can be found here: https://enterprise.nscl.msu.edu/completedexperiments/ (e18027, e18019, e18008, e17504, e17025, e15250, e15238).

[14] D. R. Nygren, Proposal to investigate the feasibility of a novel concept in particle detection, LBL internal report, February 1974.

[15] D. Suzuki, A. Shore, W. Mittig, J. J. Kolata, D. Bazin, M. Ford, T. Ahn, F. D. Becchetti, S. Beceiro Novo, D. Ben Ali, B. Bucher, J. Browne, X. Fang, M. Febbraro, A. Fritsch, E. Galyaev, A. M. Howard, N. Keeley, W. G. Lynch, M. Ojaruega, A. L. Roberts, X. D. Tang, Resonant scattering of 6He: Limits of clustering in 10Be, Phys. Rev. C 87 (2013) 054301. doi:10.1103/PhysRevC.87.054301. URL https://link.aps.org/doi/10.1103/PhysRevC.87. 054301 [OpenAIRE]

17 references, page 1 of 2
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