New semi-automatic method for reaction product charge and mass identification in heavy-ion collisions at Fermi energies
This article presents a new semi-automatic method for charge and mass identification of charged nuclear fragments using either Δ E − E correlations between measured energy losses in two successive detectors or correlations between charge signal amplitude and rise time in a single silicon detector, d...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Gruyer, D. [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2017transfer abstract |
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| Umfang: |
6 |
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| Übergeordnetes Werk: |
Enthalten in: The efficacy of EEG-biofeedback for acute pain management, a randomized sham-controlled study of a tailored protocol - Ide, C.V. ELSEVIER, 2017, a journal on accelerators, instrumentation and techniques applied to research in nuclear and atomic physics, materials science and related fields in physics, Amsterdam |
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| Übergeordnetes Werk: |
volume:847 ; year:2017 ; day:1 ; month:03 ; pages:142-147 ; extent:6 |
| Links: |
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| DOI / URN: |
10.1016/j.nima.2016.11.062 |
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ELV025145371 |
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| 245 | 1 | 0 | |a New semi-automatic method for reaction product charge and mass identification in heavy-ion collisions at Fermi energies |
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| 520 | |a This article presents a new semi-automatic method for charge and mass identification of charged nuclear fragments using either Δ E − E correlations between measured energy losses in two successive detectors or correlations between charge signal amplitude and rise time in a single silicon detector, derived from digital pulse shape analysis techniques. In both cases different nuclear species (defined by their atomic number Z and mass number A) can be visually identified from such correlations if they are presented as a two-dimensional histogram (‘identification matrix’), in which case correlations for different species populate different ridge lines (‘identification lines’) in the matrix. The proposed algorithm is based on the identification matrix's properties and uses as little information as possible on the global form of the identification lines, making it applicable to a large variety of matrices. Particular attention has been paid to the implementation in a suitable graphical environment, so that only two mouse-clicks are required from the user to calculate all initialization parameters. Example applications to recent data from both INDRA and FAZIA telescopes are presented. | ||
| 520 | |a This article presents a new semi-automatic method for charge and mass identification of charged nuclear fragments using either Δ E − E correlations between measured energy losses in two successive detectors or correlations between charge signal amplitude and rise time in a single silicon detector, derived from digital pulse shape analysis techniques. In both cases different nuclear species (defined by their atomic number Z and mass number A) can be visually identified from such correlations if they are presented as a two-dimensional histogram (‘identification matrix’), in which case correlations for different species populate different ridge lines (‘identification lines’) in the matrix. The proposed algorithm is based on the identification matrix's properties and uses as little information as possible on the global form of the identification lines, making it applicable to a large variety of matrices. Particular attention has been paid to the implementation in a suitable graphical environment, so that only two mouse-clicks are required from the user to calculate all initialization parameters. Example applications to recent data from both INDRA and FAZIA telescopes are presented. | ||
| 650 | 7 | |a Silicon detector |2 Elsevier | |
| 650 | 7 | |a Computer data analysis |2 Elsevier | |
| 650 | 7 | |a Charged particle identification |2 Elsevier | |
| 700 | 1 | |a Bonnet, E. |4 oth | |
| 700 | 1 | |a Chbihi, A. |4 oth | |
| 700 | 1 | |a Frankland, J.D. |4 oth | |
| 700 | 1 | |a Barlini, S. |4 oth | |
| 700 | 1 | |a Borderie, B. |4 oth | |
| 700 | 1 | |a Bougault, R. |4 oth | |
| 700 | 1 | |a Dueñas, J.A. |4 oth | |
| 700 | 1 | |a Galichet, E. |4 oth | |
| 700 | 1 | |a Kordyasz, A. |4 oth | |
| 700 | 1 | |a Kozik, T. |4 oth | |
| 700 | 1 | |a Le Neindre, N. |4 oth | |
| 700 | 1 | |a Lopez, O. |4 oth | |
| 700 | 1 | |a Pârlog, M. |4 oth | |
| 700 | 1 | |a Pastore, G. |4 oth | |
| 700 | 1 | |a Piantelli, S. |4 oth | |
| 700 | 1 | |a Valdré, S. |4 oth | |
| 700 | 1 | |a Verde, G. |4 oth | |
| 700 | 1 | |a Vient, E. |4 oth | |
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10.1016/j.nima.2016.11.062 doi GBV00000000000101A.pica (DE-627)ELV025145371 (ELSEVIER)S0168-9002(16)31230-X DE-627 ger DE-627 rakwb eng 530 530 DE-600 610 VZ 44.90 bkl Gruyer, D. verfasserin aut New semi-automatic method for reaction product charge and mass identification in heavy-ion collisions at Fermi energies 2017transfer abstract 6 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier This article presents a new semi-automatic method for charge and mass identification of charged nuclear fragments using either Δ E − E correlations between measured energy losses in two successive detectors or correlations between charge signal amplitude and rise time in a single silicon detector, derived from digital pulse shape analysis techniques. In both cases different nuclear species (defined by their atomic number Z and mass number A) can be visually identified from such correlations if they are presented as a two-dimensional histogram (‘identification matrix’), in which case correlations for different species populate different ridge lines (‘identification lines’) in the matrix. The proposed algorithm is based on the identification matrix's properties and uses as little information as possible on the global form of the identification lines, making it applicable to a large variety of matrices. Particular attention has been paid to the implementation in a suitable graphical environment, so that only two mouse-clicks are required from the user to calculate all initialization parameters. Example applications to recent data from both INDRA and FAZIA telescopes are presented. This article presents a new semi-automatic method for charge and mass identification of charged nuclear fragments using either Δ E − E correlations between measured energy losses in two successive detectors or correlations between charge signal amplitude and rise time in a single silicon detector, derived from digital pulse shape analysis techniques. In both cases different nuclear species (defined by their atomic number Z and mass number A) can be visually identified from such correlations if they are presented as a two-dimensional histogram (‘identification matrix’), in which case correlations for different species populate different ridge lines (‘identification lines’) in the matrix. The proposed algorithm is based on the identification matrix's properties and uses as little information as possible on the global form of the identification lines, making it applicable to a large variety of matrices. Particular attention has been paid to the implementation in a suitable graphical environment, so that only two mouse-clicks are required from the user to calculate all initialization parameters. Example applications to recent data from both INDRA and FAZIA telescopes are presented. Silicon detector Elsevier Computer data analysis Elsevier Charged particle identification Elsevier Bonnet, E. oth Chbihi, A. oth Frankland, J.D. oth Barlini, S. oth Borderie, B. oth Bougault, R. oth Dueñas, J.A. oth Galichet, E. oth Kordyasz, A. oth Kozik, T. oth Le Neindre, N. oth Lopez, O. oth Pârlog, M. oth Pastore, G. oth Piantelli, S. oth Valdré, S. oth Verde, G. oth Vient, E. oth Enthalten in North-Holland Publ. Co Ide, C.V. ELSEVIER The efficacy of EEG-biofeedback for acute pain management, a randomized sham-controlled study of a tailored protocol 2017 a journal on accelerators, instrumentation and techniques applied to research in nuclear and atomic physics, materials science and related fields in physics Amsterdam (DE-627)ELV000874671 volume:847 year:2017 day:1 month:03 pages:142-147 extent:6 https://doi.org/10.1016/j.nima.2016.11.062 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA 44.90 Neurologie VZ AR 847 2017 1 0301 142-147 6 045F 530 |
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10.1016/j.nima.2016.11.062 doi GBV00000000000101A.pica (DE-627)ELV025145371 (ELSEVIER)S0168-9002(16)31230-X DE-627 ger DE-627 rakwb eng 530 530 DE-600 610 VZ 44.90 bkl Gruyer, D. verfasserin aut New semi-automatic method for reaction product charge and mass identification in heavy-ion collisions at Fermi energies 2017transfer abstract 6 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier This article presents a new semi-automatic method for charge and mass identification of charged nuclear fragments using either Δ E − E correlations between measured energy losses in two successive detectors or correlations between charge signal amplitude and rise time in a single silicon detector, derived from digital pulse shape analysis techniques. In both cases different nuclear species (defined by their atomic number Z and mass number A) can be visually identified from such correlations if they are presented as a two-dimensional histogram (‘identification matrix’), in which case correlations for different species populate different ridge lines (‘identification lines’) in the matrix. The proposed algorithm is based on the identification matrix's properties and uses as little information as possible on the global form of the identification lines, making it applicable to a large variety of matrices. Particular attention has been paid to the implementation in a suitable graphical environment, so that only two mouse-clicks are required from the user to calculate all initialization parameters. Example applications to recent data from both INDRA and FAZIA telescopes are presented. This article presents a new semi-automatic method for charge and mass identification of charged nuclear fragments using either Δ E − E correlations between measured energy losses in two successive detectors or correlations between charge signal amplitude and rise time in a single silicon detector, derived from digital pulse shape analysis techniques. In both cases different nuclear species (defined by their atomic number Z and mass number A) can be visually identified from such correlations if they are presented as a two-dimensional histogram (‘identification matrix’), in which case correlations for different species populate different ridge lines (‘identification lines’) in the matrix. The proposed algorithm is based on the identification matrix's properties and uses as little information as possible on the global form of the identification lines, making it applicable to a large variety of matrices. Particular attention has been paid to the implementation in a suitable graphical environment, so that only two mouse-clicks are required from the user to calculate all initialization parameters. Example applications to recent data from both INDRA and FAZIA telescopes are presented. Silicon detector Elsevier Computer data analysis Elsevier Charged particle identification Elsevier Bonnet, E. oth Chbihi, A. oth Frankland, J.D. oth Barlini, S. oth Borderie, B. oth Bougault, R. oth Dueñas, J.A. oth Galichet, E. oth Kordyasz, A. oth Kozik, T. oth Le Neindre, N. oth Lopez, O. oth Pârlog, M. oth Pastore, G. oth Piantelli, S. oth Valdré, S. oth Verde, G. oth Vient, E. oth Enthalten in North-Holland Publ. Co Ide, C.V. ELSEVIER The efficacy of EEG-biofeedback for acute pain management, a randomized sham-controlled study of a tailored protocol 2017 a journal on accelerators, instrumentation and techniques applied to research in nuclear and atomic physics, materials science and related fields in physics Amsterdam (DE-627)ELV000874671 volume:847 year:2017 day:1 month:03 pages:142-147 extent:6 https://doi.org/10.1016/j.nima.2016.11.062 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA 44.90 Neurologie VZ AR 847 2017 1 0301 142-147 6 045F 530 |
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10.1016/j.nima.2016.11.062 doi GBV00000000000101A.pica (DE-627)ELV025145371 (ELSEVIER)S0168-9002(16)31230-X DE-627 ger DE-627 rakwb eng 530 530 DE-600 610 VZ 44.90 bkl Gruyer, D. verfasserin aut New semi-automatic method for reaction product charge and mass identification in heavy-ion collisions at Fermi energies 2017transfer abstract 6 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier This article presents a new semi-automatic method for charge and mass identification of charged nuclear fragments using either Δ E − E correlations between measured energy losses in two successive detectors or correlations between charge signal amplitude and rise time in a single silicon detector, derived from digital pulse shape analysis techniques. In both cases different nuclear species (defined by their atomic number Z and mass number A) can be visually identified from such correlations if they are presented as a two-dimensional histogram (‘identification matrix’), in which case correlations for different species populate different ridge lines (‘identification lines’) in the matrix. The proposed algorithm is based on the identification matrix's properties and uses as little information as possible on the global form of the identification lines, making it applicable to a large variety of matrices. Particular attention has been paid to the implementation in a suitable graphical environment, so that only two mouse-clicks are required from the user to calculate all initialization parameters. Example applications to recent data from both INDRA and FAZIA telescopes are presented. This article presents a new semi-automatic method for charge and mass identification of charged nuclear fragments using either Δ E − E correlations between measured energy losses in two successive detectors or correlations between charge signal amplitude and rise time in a single silicon detector, derived from digital pulse shape analysis techniques. In both cases different nuclear species (defined by their atomic number Z and mass number A) can be visually identified from such correlations if they are presented as a two-dimensional histogram (‘identification matrix’), in which case correlations for different species populate different ridge lines (‘identification lines’) in the matrix. The proposed algorithm is based on the identification matrix's properties and uses as little information as possible on the global form of the identification lines, making it applicable to a large variety of matrices. Particular attention has been paid to the implementation in a suitable graphical environment, so that only two mouse-clicks are required from the user to calculate all initialization parameters. Example applications to recent data from both INDRA and FAZIA telescopes are presented. Silicon detector Elsevier Computer data analysis Elsevier Charged particle identification Elsevier Bonnet, E. oth Chbihi, A. oth Frankland, J.D. oth Barlini, S. oth Borderie, B. oth Bougault, R. oth Dueñas, J.A. oth Galichet, E. oth Kordyasz, A. oth Kozik, T. oth Le Neindre, N. oth Lopez, O. oth Pârlog, M. oth Pastore, G. oth Piantelli, S. oth Valdré, S. oth Verde, G. oth Vient, E. oth Enthalten in North-Holland Publ. Co Ide, C.V. ELSEVIER The efficacy of EEG-biofeedback for acute pain management, a randomized sham-controlled study of a tailored protocol 2017 a journal on accelerators, instrumentation and techniques applied to research in nuclear and atomic physics, materials science and related fields in physics Amsterdam (DE-627)ELV000874671 volume:847 year:2017 day:1 month:03 pages:142-147 extent:6 https://doi.org/10.1016/j.nima.2016.11.062 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA 44.90 Neurologie VZ AR 847 2017 1 0301 142-147 6 045F 530 |
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10.1016/j.nima.2016.11.062 doi GBV00000000000101A.pica (DE-627)ELV025145371 (ELSEVIER)S0168-9002(16)31230-X DE-627 ger DE-627 rakwb eng 530 530 DE-600 610 VZ 44.90 bkl Gruyer, D. verfasserin aut New semi-automatic method for reaction product charge and mass identification in heavy-ion collisions at Fermi energies 2017transfer abstract 6 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier This article presents a new semi-automatic method for charge and mass identification of charged nuclear fragments using either Δ E − E correlations between measured energy losses in two successive detectors or correlations between charge signal amplitude and rise time in a single silicon detector, derived from digital pulse shape analysis techniques. In both cases different nuclear species (defined by their atomic number Z and mass number A) can be visually identified from such correlations if they are presented as a two-dimensional histogram (‘identification matrix’), in which case correlations for different species populate different ridge lines (‘identification lines’) in the matrix. The proposed algorithm is based on the identification matrix's properties and uses as little information as possible on the global form of the identification lines, making it applicable to a large variety of matrices. Particular attention has been paid to the implementation in a suitable graphical environment, so that only two mouse-clicks are required from the user to calculate all initialization parameters. Example applications to recent data from both INDRA and FAZIA telescopes are presented. This article presents a new semi-automatic method for charge and mass identification of charged nuclear fragments using either Δ E − E correlations between measured energy losses in two successive detectors or correlations between charge signal amplitude and rise time in a single silicon detector, derived from digital pulse shape analysis techniques. In both cases different nuclear species (defined by their atomic number Z and mass number A) can be visually identified from such correlations if they are presented as a two-dimensional histogram (‘identification matrix’), in which case correlations for different species populate different ridge lines (‘identification lines’) in the matrix. The proposed algorithm is based on the identification matrix's properties and uses as little information as possible on the global form of the identification lines, making it applicable to a large variety of matrices. Particular attention has been paid to the implementation in a suitable graphical environment, so that only two mouse-clicks are required from the user to calculate all initialization parameters. Example applications to recent data from both INDRA and FAZIA telescopes are presented. Silicon detector Elsevier Computer data analysis Elsevier Charged particle identification Elsevier Bonnet, E. oth Chbihi, A. oth Frankland, J.D. oth Barlini, S. oth Borderie, B. oth Bougault, R. oth Dueñas, J.A. oth Galichet, E. oth Kordyasz, A. oth Kozik, T. oth Le Neindre, N. oth Lopez, O. oth Pârlog, M. oth Pastore, G. oth Piantelli, S. oth Valdré, S. oth Verde, G. oth Vient, E. oth Enthalten in North-Holland Publ. Co Ide, C.V. ELSEVIER The efficacy of EEG-biofeedback for acute pain management, a randomized sham-controlled study of a tailored protocol 2017 a journal on accelerators, instrumentation and techniques applied to research in nuclear and atomic physics, materials science and related fields in physics Amsterdam (DE-627)ELV000874671 volume:847 year:2017 day:1 month:03 pages:142-147 extent:6 https://doi.org/10.1016/j.nima.2016.11.062 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA 44.90 Neurologie VZ AR 847 2017 1 0301 142-147 6 045F 530 |
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10.1016/j.nima.2016.11.062 doi GBV00000000000101A.pica (DE-627)ELV025145371 (ELSEVIER)S0168-9002(16)31230-X DE-627 ger DE-627 rakwb eng 530 530 DE-600 610 VZ 44.90 bkl Gruyer, D. verfasserin aut New semi-automatic method for reaction product charge and mass identification in heavy-ion collisions at Fermi energies 2017transfer abstract 6 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier This article presents a new semi-automatic method for charge and mass identification of charged nuclear fragments using either Δ E − E correlations between measured energy losses in two successive detectors or correlations between charge signal amplitude and rise time in a single silicon detector, derived from digital pulse shape analysis techniques. In both cases different nuclear species (defined by their atomic number Z and mass number A) can be visually identified from such correlations if they are presented as a two-dimensional histogram (‘identification matrix’), in which case correlations for different species populate different ridge lines (‘identification lines’) in the matrix. The proposed algorithm is based on the identification matrix's properties and uses as little information as possible on the global form of the identification lines, making it applicable to a large variety of matrices. Particular attention has been paid to the implementation in a suitable graphical environment, so that only two mouse-clicks are required from the user to calculate all initialization parameters. Example applications to recent data from both INDRA and FAZIA telescopes are presented. This article presents a new semi-automatic method for charge and mass identification of charged nuclear fragments using either Δ E − E correlations between measured energy losses in two successive detectors or correlations between charge signal amplitude and rise time in a single silicon detector, derived from digital pulse shape analysis techniques. In both cases different nuclear species (defined by their atomic number Z and mass number A) can be visually identified from such correlations if they are presented as a two-dimensional histogram (‘identification matrix’), in which case correlations for different species populate different ridge lines (‘identification lines’) in the matrix. The proposed algorithm is based on the identification matrix's properties and uses as little information as possible on the global form of the identification lines, making it applicable to a large variety of matrices. Particular attention has been paid to the implementation in a suitable graphical environment, so that only two mouse-clicks are required from the user to calculate all initialization parameters. Example applications to recent data from both INDRA and FAZIA telescopes are presented. Silicon detector Elsevier Computer data analysis Elsevier Charged particle identification Elsevier Bonnet, E. oth Chbihi, A. oth Frankland, J.D. oth Barlini, S. oth Borderie, B. oth Bougault, R. oth Dueñas, J.A. oth Galichet, E. oth Kordyasz, A. oth Kozik, T. oth Le Neindre, N. oth Lopez, O. oth Pârlog, M. oth Pastore, G. oth Piantelli, S. oth Valdré, S. oth Verde, G. oth Vient, E. oth Enthalten in North-Holland Publ. Co Ide, C.V. ELSEVIER The efficacy of EEG-biofeedback for acute pain management, a randomized sham-controlled study of a tailored protocol 2017 a journal on accelerators, instrumentation and techniques applied to research in nuclear and atomic physics, materials science and related fields in physics Amsterdam (DE-627)ELV000874671 volume:847 year:2017 day:1 month:03 pages:142-147 extent:6 https://doi.org/10.1016/j.nima.2016.11.062 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA 44.90 Neurologie VZ AR 847 2017 1 0301 142-147 6 045F 530 |
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New semi-automatic method for reaction product charge and mass identification in heavy-ion collisions at Fermi energies |
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This article presents a new semi-automatic method for charge and mass identification of charged nuclear fragments using either Δ E − E correlations between measured energy losses in two successive detectors or correlations between charge signal amplitude and rise time in a single silicon detector, derived from digital pulse shape analysis techniques. In both cases different nuclear species (defined by their atomic number Z and mass number A) can be visually identified from such correlations if they are presented as a two-dimensional histogram (‘identification matrix’), in which case correlations for different species populate different ridge lines (‘identification lines’) in the matrix. The proposed algorithm is based on the identification matrix's properties and uses as little information as possible on the global form of the identification lines, making it applicable to a large variety of matrices. Particular attention has been paid to the implementation in a suitable graphical environment, so that only two mouse-clicks are required from the user to calculate all initialization parameters. Example applications to recent data from both INDRA and FAZIA telescopes are presented. |
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This article presents a new semi-automatic method for charge and mass identification of charged nuclear fragments using either Δ E − E correlations between measured energy losses in two successive detectors or correlations between charge signal amplitude and rise time in a single silicon detector, derived from digital pulse shape analysis techniques. In both cases different nuclear species (defined by their atomic number Z and mass number A) can be visually identified from such correlations if they are presented as a two-dimensional histogram (‘identification matrix’), in which case correlations for different species populate different ridge lines (‘identification lines’) in the matrix. The proposed algorithm is based on the identification matrix's properties and uses as little information as possible on the global form of the identification lines, making it applicable to a large variety of matrices. Particular attention has been paid to the implementation in a suitable graphical environment, so that only two mouse-clicks are required from the user to calculate all initialization parameters. Example applications to recent data from both INDRA and FAZIA telescopes are presented. |
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This article presents a new semi-automatic method for charge and mass identification of charged nuclear fragments using either Δ E − E correlations between measured energy losses in two successive detectors or correlations between charge signal amplitude and rise time in a single silicon detector, derived from digital pulse shape analysis techniques. In both cases different nuclear species (defined by their atomic number Z and mass number A) can be visually identified from such correlations if they are presented as a two-dimensional histogram (‘identification matrix’), in which case correlations for different species populate different ridge lines (‘identification lines’) in the matrix. The proposed algorithm is based on the identification matrix's properties and uses as little information as possible on the global form of the identification lines, making it applicable to a large variety of matrices. Particular attention has been paid to the implementation in a suitable graphical environment, so that only two mouse-clicks are required from the user to calculate all initialization parameters. Example applications to recent data from both INDRA and FAZIA telescopes are presented. |
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