Determination of time zero from a charged particle detector

• US 20080228418A1
• Filed: 10/24/2007
• Published: 09/18/2008
• Est. Priority Date: 10/27/2006
• Status: Active Grant

• Current Assignee: TRIAD National Security, LLC
• Original Assignee: Los Alamos National Security LLC (Government of the United States of America)
• Inventors: Green, Jesse Andrew
• Granted Patent: US 7,908,121 B2
• Time in Patent Office: Days
• US Class Current: 702/81
• CPC Class Codes: G01N 23/20 by using diffraction of the radiation by the materials, e.g. for investigating crystal structure; by using scattering of the radiation by the materials, e.g. for investigating non-crystalline materials; by using reflection of the radiation by the materials
• CPC Class Codes: G01N 23/207 Diffractometry using detectors, e.g. using a probe in a central position and one or more displaceable detectors in circumferential positions
• CPC Class Codes: G01V 5/222 measuring scattered radiation
• CPC Class Codes: G01V 5/26 Passive interrogation, i.e. by measuring radiation emitted by objects or goods
• CPC Class Codes: G06F 17/18 for evaluating statistical data , e.g. average values, frequency distributions, probability functions, regression analysis forecasting specially adapted for a specific administrative, business or logistic context G06Q10/04

Abstract

A method, system and computer program is used to determine a linear track having a good fit to a most likely or expected path of charged particle passing through a charged particle detector having a plurality of drift cells. Hit signals from the charged particle detector are associated with a particular charged particle track. An initial estimate of time zero is made from these hit signals and linear tracks are then fit to drift radii for each particular time-zero estimate. The linear track having the best fit having the best fit is then search and selected and errors in fit and tracking parameters computed. The use of large and expensive fast detectors needed to time zero in the charged particle detectors can be avoided by adopting this method and system.

Claims

1. A method for reconstructing the trajectory of a charged particle passing through a charged particle detector having a plurality of drift cells, said method comprising:

(a) obtaining hit signals representing identifiers of drift cells hit by charged particles and corresponding hit times;

(b) grouping in-time drift cell hits identified as being associated with a track of a particular charged particle passing through said detector;

(c) initially estimating time zero for said particular charged particle;

(d) determining drift radii based on estimates of time zero, drift time conversion data and the time of the hit;

(e) fitting linear tracks to drift radii corresponding to a particular time-zero; and

(f) searching and selecting a time-zero value associated with the best of the track fits performed for particular charged particle and computing error in time-zero and tracking parameters.

2. The method of claim 1, wherein said charged particle comprises a muon.

3. The method of claim 1, wherein initially estimating time zero for said particular charged particle comprises

initially estimating time zero for said particular charged particle from said grouped hits.

4. The method of claim 1, wherein obtaining hit signals representing identifiers of drift cells hit by charged particles and corresponding hit times comprises

reading times of said drift cell hits;

reading corresponding drift cell channel numbers; and

optionally

subtracting times to account for propagation delay and/or approximate time of flight of particular charged particle.

5. The method of claim 4, wherein grouping in-time drift cell hits identified as being associated with a track of a particular charged particle passing through said detector comprises

grouping hit times within a predetermined time window associated with said track;

and

including only those hits most likely to be part of the particular charged particle track.

6. The method of claim 1, wherein initially estimating time zero for said particular charged particle comprises

determining the metric based upon hit times of said grouped hits;

and

subtracting a constant from the metric hit time.

7. The method of claim 6, wherein determining the metric hit time comprises

determining the median hit time of said grouped hits.

8. The method of claim 1, wherein fitting linear tracks to drift radii corresponding to a particular time-zero includes fitting said tracks to drift radii using linear regression formulas or an iterative fit in order to minimizes the aggregate distance from a track to anode wire of the drift cell.

9. The method of claim 1, wherein determining drift radii based on estimates of time zero, drift time conversion data and the time of the hit comprises

subtracting each hit time of the grouped hits from said initial estimate of time zero to determine each drift time of each hit;

and

converting said drift times to radii based on predetermined experimental/theoretical drift time to drift distance data stored in a database.

10. The method of claim 1, wherein obtaining hit signals representing identifiers of drift cells hit by charged particles and corresponding hit times comprises

obtaining hit signals from a first set of drift cells positioned on a side of an object volume to measure the position of incoming charged particles entering the object volume;

said first set of drift cells having drift cells configured in a first component direction and in a second component direction; and

obtaining hit signals from a second set of drift cells positioned on a side of an object volume to measure the position of outgoing charged particles exiting the object volume;

said second set of drift cells having drift cells configured in a first component direction and in a second component direction.

11. The method of claim 10, further comprising

determining if said grouped hits include at least three hit signals from said first set drift cells positioned in a first component direction and at least three hit signals from said first set drift cells positioned in a second component direction;

determining if said grouped hits include at least three hit signals from said second set drift cells positioned in a first component direction and at least three hit signals from said second set drift cells positioned in a second component direction; and

grouping in-time drift cell hits identified as being associated with a next track of a particular charged particle passing through said detector in response to determining said grouped hits do not include each of said at least three hit signals.

12. The method of claim 10, wherein fitting linear tracks to drift radii corresponding to a particular time-zero includes

fitting linear tracks of charged particles passing through said first set and said second set of drift cells, respectively, using obtained drift radii;

and

wherein searching and selecting a time-zero value associated with the best of the track fits performed for particular charged particle and computing error in time-zero and tracking parameters comprises

estimating each next time zero from track fits for said first and second drift cell sets; and

for each next time zero, determining drift radii based on estimates of time zero, drift time conversion data and the time of the hit, and fitting linear tracks to drift radii corresponding to time-zero until a substantially linear track having a best fit to most likely or expected path of charged particle passing through detector is obtained.

13. The method of claim 10, wherein fitting linear tracks to drift radii corresponding to a particular time-zero includes

fitting linear tracks of charged particles passing through said first and second sets of drift cells, respectively, to obtained drift radii;

and

wherein searching and selecting a time-zero value associated with the best of the track fits performed for particular charged particle and computing error in time-zero and tracking parameters comprises

determining a minimum value of chi-square based on track fits for said first set and second set of drift cells and said drift radii;

adding together chi-squares for fitted tracks to determine total chi-square;

storing chi-square value for each estimate of value of time-zero;

performing a search to determine time-zero corresponding to the lowest estimated value of chi-square; and

determining a parabolic fit to at least three lowest points to determine error of time-zero selection; and

determine linear track using correct time-zero selection.

14. A system for reconstructing the trajectory of at least one charged particle passing through a detector having a plurality of drift cells, said system comprising a controller adapted and arranged to:

(a) obtain hit signals representing identifiers of drift cells hit by charged particles and corresponding hit times;

(b) group in-time drift cell hits identified as being associated with a track of a particular charged particle passing through said detector;

(c) initially estimate time zero for said particular charged particle;

(d) determine drift radii based on estimates of time zero, drift time conversion data and time of the hit;

(e) fit linear tracks to drift radii corresponding to a particular time-zero; and

(f) search and select a time-zero value associated with the best of the track fits performed for particular charged particle and compute error in time-zero and tracking parameters.

15. The system of claim 14, wherein said charged particle comprises a cosmic ray charged particle.

16. The system of claim 14, further comprising a charged particle detector operably coupled to said controller, said charged particle detector having a first set of drift cells positioned on one side of an object receiving volume to measure positions of incoming charged particles entering the object volume, and having a second set of drift cells positioned on another side of the object volume to measure positions of outgoing charged particles exiting the object volume;

and

wherein said controller is adapted and arranged to receive hit signals and corresponding hit times from said first set of drift cells and said second set of drift cells.

17. The system of claim 16, wherein said controller is adapted and arranged to:

fit linear tracks of charged particles passing through said first set and said second set of drift cells, respectively, to obtained drift radii;

determine a minimum value of chi-square based on track fits for said first and second sets of drift cells and said drift radii;

add together chi-squares for said fitted tracks to determine total chi-square;

store chi-square value for each estimate of value of time-zero;

perform a search to determine time-zero corresponding to the lowest estimated value of chi-square;

determine a parabolic fit to at least three lowest points to determine error of time-zero selection; and

determine linear track using correct time-zero selection.

18. The system of claim 14, wherein said controller is adapted and arranged to

group hit times within a predetermined time window associated with said track;

and

include only those hits most likely to be part of the particular charged particle track.

19. The system of claim 18, wherein said controller is adapted and arranged to

determine the metric based upon hit times of said grouped hits;

and subtract a constant from the metric hit time in order to provide an initially estimate time zero.

20. The system of claim 18, wherein said controller is adapted and arranged to

subtract each hit time of the grouped hits from said initial estimate of time zero to determine each drift time of each hit;

and

convert said drift times to radii based on predetermined experimental/theoretical drift time to drift distance data stored in a database.

21. A computer program product comprising:

a computer-usable data carrier storing instructions that, when executed by a computer, cause the computer to perform a method for reconstructing the trajectory of a charged particle passing through a detector having a plurality of drift cells, said method comprising;

(a) obtaining hit signals representing identifiers of drift cells hit by charged particles and corresponding hit times;

(b) grouping in-time drift cell hits identified as being associated with a track of a particular charged particle passing through said detector;

(c) initially estimating time zero for said particular charged particle;

(d) determining drift radii based on estimates of time zero, drift time conversion data and the time of the hit;

(e) fitting linear tracks to drift radii corresponding to a particular time-zero; and

(f) searching and selecting a time-zero value associated with the best of the track fits performed for particular charged particle and computing error in time-zero and tracking parameters.

22. The computer program of claim 21, wherein initially estimating time zero for said particular charged particle comprises

initially estimating time zero for said particular charged particle from said grouped hits.

23. The computer program of claim 21, wherein determining drift radii based on estimates of time zero, drift time conversion data and the time of the hit comprises

subtracting each hit time of the grouped hits from said initial estimate of time zero to determine each drift time of each hit;

converting said drift times to radii based on predetermined experimental/theoretical drift time to drift distance data stored in a database.

24. The computer program of claim 21, wherein fitting linear tracks to drift radii corresponding to a particular time-zero includes

fitting linear tracks of charged particles passing through first and second sets of drift cells, respectively, using obtained drift radii;

wherein searching and selecting a time-zero value associated with the best of the track fits performed for particular charged particle and computing error in time-zero and tracking parameters comprises

determining a minimum value of chi-square based on track fits for first and second sets of drift cells and said drift radii;

adding together chi-squares for fitted tracks to determine total chi-square;

storing chi-square value for each estimate of value of time-zero;

performing a search to determine time-zero corresponding to the lowest estimated value of chi-square; and

determining a parabolic fit to at least three lowest points to determine error of time-zero selection; and

determine linear track using correct time-zero selection.

25. A system for reconstructing the trajectory of a charged particle, includes a first set of position sensitive detectors located on a first side of an object volume to measure positions and angles of incident charged particles towards the object volume;

a second set of position sensitive detectors located on a second side of the object volume opposite to the first side to measure positions and angles of outgoing charged particles exiting the object volume; and

a signal processing unit configured to receive data of measured signals from the first set of position sensitive detectors and measured signals from the second set of position sensitive detectors and determine the trajectory of charged particles passing through said object volume from said signals.