A VETO detection method and system for shielding cosmic ray muons

Abstract

This invention discloses a VETO detection method and system for shielding cosmic ray muons, specifically relating to the field of cosmic ray muon background shielding. The method includes acquiring response data output by an outer VETO detector within the current observation period; aggregating the response data according to response time order and spatial adjacency; identifying response groups corresponding to the same muon crossing; and outputting muon events. Based on the muon events, the first and last response times, cross-regional propagation order, regional response density, and crossing depth corresponding to each response group are extracted. Corresponding aftereffect markers are generated according to the combination relationships of these parameters. By generating aftereffect markers for muon events and expanding the regional rules, a constrained spatiotemporal correlation is formed between the delayed background and candidate events. Based on this, shielding, observation, and alerting processes are performed in layers, thereby relatively suppressing delayed pseudo-signals and mitigating dead-time diffusion caused by fixed windowing.

Description

Technical Field

[0001] This invention relates to the field of cosmic ray muon background shielding technology, and more specifically, to a VETO detection method and system for shielding cosmic ray muons. Background Technology

[0002] In the field of cosmic ray muon background shielding, the mainstream practice in the industry is to solve the problem of spurious signal interference introduced by muon-related events in the measurement results of the main detector. Usually, plastic scintillators, water Cherenkov or other outer VETO detection structures are deployed on the outside of the main detector to mark muon events that cross the outer layer, and anti-match rejection is performed when the candidate events of the main detector and the marked events of the outer layer meet the preset time match relationship.

[0003] For example, in scenarios involving low count rate, high sensitivity particle detection, or rare event measurement, the system not only needs to filter out the direct interference from the muon itself as much as possible, but also needs to suppress the delayed secondary particle background induced by the muon as much as possible under the constraint of finite dead time. At the same time, it must also meet the hard constraint that the outer VETO structure response time and the candidate event of the main detector can only be correlated based on a finite time window and the shielding range cannot be infinitely expanded.

[0004] However, under this constraint, the mainstream approach will consistently reveal a key bottleneck: the outer VETO can usually only reliably mark the instantaneous event when the muon crosses, but it is difficult to establish a constrained correlation between the subsequent induced delayed background and the candidate events of the main detector. The phenomenon that can be observed in actual operation is that when the anti-coincidence time window is uniformly relaxed, the effective working time of the main detector is significantly squeezed and the false masking increases.

[0005] When a narrow time window is maintained, delayed pseudo-signals that are not eliminated in time will continue to appear, resulting in the long-term coexistence of background residue and measurement distortion. The root cause is that the existing scheme still processes the data according to the logic of single muon hit and fixed time window, and fails to implement differentiated shielding for the evolution of subsequent muon interference.

[0006] Therefore, the technical problem to be solved by this application is: how to establish a constrained correlation between the delayed background generated after the muon crosses and the candidate events of the main detector during the VETO detection process used to shield cosmic ray muons, so as to suppress delayed pseudo-signals while avoiding dead time diffusion caused by fixed windowing. Summary of the Invention

[0007] To overcome the aforementioned deficiencies of the prior art, embodiments of the present invention provide a VETO detection method and system for shielding cosmic ray muons. The method involves extracting post-effect features from muon events identified by an outer-layer VETO detector and expanding them to form partitioning rules. Then, the candidate events of the main detector are spatiotemporally correlated and matched with the partitioning rules to perform differentiated VETO processing, thereby solving the problems mentioned in the background art.

[0008] To achieve the above objectives, the present invention provides the following technical solution: a VETO detection method for shielding cosmic ray muons, comprising:

[0009] S1. Acquire the response data output by the outer VETO detector within the current observation period, aggregate the response data according to the response time order and spatial adjacency, identify the response group corresponding to the same muon crossing, and output the muon event.

[0010] S2. Based on the muon event, extract the first and last response times, cross-regional propagation order, regional response density and traversal depth of each response group, and generate corresponding aftereffect labels according to the combination relationship of the first and last response times, cross-regional propagation order, regional response density and traversal depth.

[0011] S3. Based on the aftereffect marker, determine the basic shielding duration according to the crossing depth, determine the observation extension duration according to the partition response density, determine the warning partition range according to the cross-regional propagation sequence, expand the basic shielding duration, observation extension duration and warning partition range of each partition into partitions, generate the shielding period, observation period and warning period corresponding to each partition, and output the partitioning rules.

[0012] S4. Obtain candidate events output by the main detector, and match the candidate events with the partitioning rules according to the temporal inclusion relationship between the event time and the corresponding time period of each partition, as well as the spatial attribution relationship between the event location and the range of the warning partition, and output the association results.

[0013] S5. Based on the association results, determine whether the candidate event falls into the corresponding partition's blocking period, observation period, or alert period, and determine the VETO processing result of the candidate event according to the processing order of blocking period taking precedence over observation period and observation period taking precedence over alert period.

[0014] In a preferred embodiment, the method further includes: S6, based on the VETO processing results, performing masking and elimination processing on candidate events falling into the masking period, performing observation marking processing on candidate events falling into the observation period, and performing retention output processing on candidate events falling only into the alert period, thereby generating the final VETO detection results.

[0015] In a preferred embodiment, S6 includes:

[0016] S6-1. Obtain the VETO processing results and candidate event data corresponding to the candidate events. Write the candidate events whose VETO processing results are masking and elimination results into the elimination set, write the candidate events whose VETO processing results are observation and labeling results into the observation set, write the candidate events whose VETO processing results are retained output results into the output set, and output the classification results.

[0017] S6-2. Obtain the classification results, delete the corresponding event items in the main detector output record for candidate events in the elimination set, write observation tags in the corresponding event items for candidate events in the observation set, retain the original event items for candidate events in the output set and write the pass tag, and output the handling results.

[0018] S6-3. Obtain the processing results, summarize and retain the original event items in the order of event time, and write them into the candidate events marked and the candidate events marked by observation to generate the final VETO detection results.

[0019] In a preferred embodiment, S1 includes:

[0020] S1-1. Obtain the start time, end time and partition number corresponding to each response data. Arrange the response data in ascending order of start time. Connect the two response data whose end time is greater than or equal to the start time of the next response data into the same time chain. Output the candidate response sequence corresponding to each time chain.

[0021] S1-2. Obtain the partition numbers corresponding to the two response data in each candidate response sequence. Connect the two response data into the same spatial chain according to the following conditions: the previous partition number is the same as the next partition number, or they are adjacent partitions in the partition adjacency list, or there is a connectivity relationship in the partition adjacency list that only passes through one intermediate partition. Output the response group whose time chain and spatial chain are continuous at the same time.

[0022] S1-3. Obtain the sorting order and partition distribution of all response data in each response group. Perform a traversal consistency check by increasing the start time of adjacent two response data in turn and keeping the number of traversals of the corresponding partition in the partition adjacency list non-backflow. The response group that passes the traversal consistency check is determined as the response group corresponding to the same muon traversal, and the muon event is output.

[0023] In a preferred embodiment, S2 includes:

[0024] S2-1. Obtain the start time, end time, and partition number of each response data in the response group corresponding to the muon event. Determine the first start time as the first response time and the last end time as the last response time. Generate the cross-regional propagation order according to the order of the first appearance of each partition number and output the time sequence characteristics.

[0025] S2-2. Obtain the number of responses for each partition within the response group and the position of each partition in the cross-regional propagation order. Divide the number of responses for each partition by the total number of responses in the response group to generate the partition response density for each partition. Generate the traversal depth by the number of partition levels traversed between the first and last partitions in the cross-regional propagation order, and output the density depth feature.

[0026] S2-3. Obtain temporal and density-depth features, concatenate the first response time and the last response time to generate a time period identifier, generate a path identifier by arranging the cross-regional propagation sequence, generate a density identifier by zonal response density according to zonal number, generate a depth identifier by traversal depth, and combine the time period identifier, path identifier, density identifier and depth identifier into the same aftereffect label, and output the aftereffect label.

[0027] In a preferred embodiment, S3 includes:

[0028] S3-1. Obtain the first response time, last response time, cross-regional propagation order, corresponding partition response density and crossing depth from the aftereffect markers. Subtract the first response time from the last response time to generate the crossing duration. Multiply the crossing duration by the crossing depth to generate the basic shielding duration. Multiply the partition response density of each partition by the basic shielding duration to generate the observation extension duration corresponding to each partition. Output the partition duration data.

[0029] S3-2. Obtain the first partition, the last partition, and the intermediate partitions in the cross-regional propagation order. Determine all partitions that are passed sequentially from the first partition to the last partition as primary alert partitions according to the cross-regional propagation order. Determine the adjacent partitions of each primary alert partition in the partition adjacency table as extended alert partitions. Output the set of alert partitions.

[0030] In a preferred embodiment, S3 further includes:

[0031] S3-3. Obtain partition duration data, alert partition set, and last response time. Use the last response time as the starting point of the shielding period for each partition, the sum of the last response time and the basic shielding duration as the ending point of the shielding period for each partition, the ending point of the shielding period as the starting point of the observation period for each partition, and the sum of the ending point of the shielding period and the corresponding extended observation duration as the ending point of the observation period for each partition. Determine each primary alert partition and each extended alert partition within the range from the first response time to the end of the observation period as the corresponding partition for the alert period. Generate the shielding period, observation period, and alert period for each partition, and output the partitioning rules.

[0032] In a preferred embodiment, S4 includes:

[0033] S4-1. Obtain the event time and event location corresponding to the candidate event, and determine the event partition corresponding to the candidate event in the main detector partition mapping table according to the event location, and output the event attribution data;

[0034] S4-2. Obtain the blocking period, observation period and alert period corresponding to each partition in the event attribution data and partitioning rules. Compare the start and end intervals of the event time with the blocking period and observation period corresponding to the event partition. Compare the partition attribution of the event partition with the main alert partition and extended alert partition corresponding to the alert period. Output the spatiotemporal matching data.

[0035] S4-3. Obtain spatiotemporal matching data. When the event time falls within the shielding period corresponding to the event partition, determine the association between the candidate event and the shielding period. When the event time does not fall within the shielding period but falls within the observation period corresponding to the event partition, determine the association between the candidate event and the observation period. When the event partition belongs to the main alert partition or extended alert partition corresponding to the alert period, determine the association between the candidate event and the alert period. Output the association results.

[0036] In a preferred embodiment, S5 includes:

[0037] S5-1. Obtain the association results corresponding to the candidate events, extract the association markers for the shielded period, the observation period, and the warning period, and write them into the processing sequence in the order of the association markers for the shielded period, the observation period, and the warning period, and output the period determination sequence.

[0038] S5-2. Obtain the time period determination sequence, determine the target time period type corresponding to the candidate event according to the first occurrence mark in the processing sequence, and determine the target time period type as the shielded time period when the shielded time period association mark exists, determine the target time period type as the observation time period when the shielded time period association mark does not exist and the observation time period association mark exists, and determine the target time period type as the warning time period when neither the shielded time period association mark nor the observation time period association mark exists and the warning time period association mark exists. Output the target time period type.

[0039] S5-3. Obtain the target time period type, determine the candidate events with the target time period type as the masking time period as the masking and elimination result, determine the candidate events with the target time period type as the observation time period as the observation and marking result, determine the candidate events with the target time period type as the warning time period as the retained output result, and output the VETO processing result of the candidate events.

[0040] A VETO detection system for shielding cosmic ray muons includes:

[0041] The event aggregation module acquires the response data output by the outer VETO detector within the current observation period, aggregates the response data according to the response time order and spatial adjacency, identifies the response group corresponding to the same muon crossing, and outputs the muon event.

[0042] The tag generation module extracts the first and last response times, cross-regional propagation order, regional response density, and traversal depth of each response group based on the muon event, and generates corresponding aftereffect tags according to the combination relationship of the first and last response times, cross-regional propagation order, regional response density, and traversal depth.

[0043] The rule generation module, based on aftereffect markers, determines the basic shielding duration according to the crossing depth, the observation extension duration according to the partition response density, and the warning partition range according to the cross-regional propagation order. It then expands the basic shielding duration, observation extension duration, and warning partition range of each partition to generate the shielding period, observation period, and warning period corresponding to each partition, and outputs the partition rules.

[0044] The association matching module obtains candidate events output by the main detector, and performs association matching between the candidate events and the partition rules according to the temporal inclusion relationship between the event time and the corresponding time period of each partition, as well as the spatial belonging relationship between the event location and the range of the warning partition, and outputs the association results.

[0045] The result determination module determines whether the candidate event falls into the corresponding partition's blocking period, observation period, or alert period based on the association results, and determines the VETO processing result of the candidate event according to the processing order of blocking period taking precedence over observation period and observation period taking precedence over alert period.

[0046] The results output module performs masking and elimination processing on candidate events falling into the masking period, observation and marking processing on candidate events falling into the observation period, and retention and output processing on candidate events falling only into the alert period, based on the VETO processing results, to generate the final VETO detection results.

[0047] The technical effects and advantages of this invention are as follows:

[0048] 1. By labeling the post-effects of muon events and expanding the partitioning rules, a constrained spatiotemporal relationship is formed between the delayed background and the candidate events. Based on this, layered masking, observation and alerting processes are performed, thereby relatively suppressing delayed pseudo-signals and alleviating the dead time diffusion caused by fixed windowing.

[0049] 2. By identifying the response group corresponding to the same muon crossing according to the response time order, spatial adjacency relationship and crossing consistency, the possibility of irrelevant responses being mistakenly merged into muon events can be relatively reduced, thus providing a more stable data foundation for subsequent extraction of the first and last moments, determination of the propagation order and generation of partitioning rules;

[0050] 3. By generating the basic shielding duration, observation extension duration, and alert zone range based on the crossing depth, zone response density, and cross-zone propagation sequence, differentiated follow-up actions can be performed on different zones, thereby improving the targeting of candidate event screening and reducing unnecessary overall shielding range. Attached Figure Description

[0051] Figure 1 This is a flowchart of the method steps of the present invention.

[0052] Figure 2 This is a system module diagram of the present invention. Detailed Implementation

[0053] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0054] Refer to the instruction manual appendix Figure 1-2 The present invention provides a VETO detection method for shielding cosmic ray muons, comprising:

[0055] S1. Acquire the response data output by the outer VETO detector within the current observation period, aggregate the response data according to the response time order and spatial adjacency, identify the response group corresponding to the same muon crossing, and output the muon event.

[0056] In this embodiment, the outer VETO detector outputs multiple discrete response data within the same observation period. Each response data typically carries at least a start time, an end time, and a partition number, used to characterize the response process detected in a certain partition within the corresponding time period. Since the same muon crossing may propagate continuously along adjacent partitions and form consecutive response records in different partitions, a single response data cannot be directly regarded as an independent event. Instead, it needs to be initially merged according to temporal continuity, then further filtered by combining spatial continuity, and finally, a crossing consistency check is used to remove pseudo-continuous sequences caused by noise disturbances, local crosstalk, or irrelevant particle triggers, thereby obtaining muon events that can be used for subsequent processing. This implementation process is not simply a mechanical merging of responses that are close in time or adjacent in location, but rather first constructs a time chain, then constructs a spatial chain based on the time chain, and confirms the response data set that simultaneously satisfies temporal continuity, spatial continuity, and crossing consistency, so as to ensure that the output results can both cover the continuous responses formed by real muon crossings and avoid misclassifying irrelevant responses as the same muon event. This implementation process includes the following steps:

[0057] First, acquire all response data output by the inner and outer VETO detectors during the current observation period, and read the start time, end time, and partition number from each response data. The start time can be the moment when the pulse corresponding to the response data first exceeds the acquisition baseline, the end time can be the moment when the pulse returns to the acquisition end baseline, and the partition number can be the number of the detector partition to which the response data belongs in the pre-established partition number table in the system. Sort all response data in ascending order of start time. If two response data have the same start time, place the response data with the earlier end time first to ensure a unique subsequent connection order. After sorting, starting from the first response data in the sorted result, take it as the start data of the current time chain, and then sequentially determine whether the start time of the next response data is less than or equal to the end time of the current response data. If so, it means that the two response data are in the same time chain. If there is overlap or a beginning-end connection in time, two response data points are connected into the same time chain. The latter is then used as the new current response data point, and the same judgment is made with the next response data point. If the condition is not met, the current time chain is terminated, and the above process is repeated with the next response data point that has not yet been assigned to any time chain as the new starting data point, until all response data points are connected. This can output multiple time chains, each corresponding to a candidate response sequence. For example, if the time intervals of three response data points are 10 nanoseconds to 16 nanoseconds, 15 nanoseconds to 21 nanoseconds, and 21 nanoseconds to 25 nanoseconds, the first two are connected due to time overlap, and the latter two are also connected because the end time of the former is equal to the start time of the latter. Therefore, the three response data points together constitute the same candidate response sequence. If the fourth response data point starts at 29 nanoseconds, there is no time connection between it and the aforementioned sequence, and it should be used as the starting data point of another time chain.

[0058] After obtaining each candidate response sequence, a spatial continuity check is performed on each candidate response sequence. Specifically, the partition numbers corresponding to the two consecutive response data in the candidate response sequence are first read, and then the spatial relationship between the two partitions is queried from the partition adjacency table pre-stored in the system. The partition adjacency table can be established according to the actual structure and layout of the outer VETO detector. For example, the adjacent partitions on the same side, the adjacent partitions at corners, and the partitions that can be reached by passing through a transition partition are stored as entries. For any two consecutive response data in the candidate response sequence, if the partition number of the preceding partition is the same as the partition number of the following partition, it means that the muon forms a continuous response in the same partition and can be directly connected. If the two partitions are adjacent partitions in the partition adjacency table, it means that the muon response propagates along the directly adjacent partition and can also be directly connected. If the two partitions are not directly adjacent in the partition adjacency table, but there is a connectivity relationship that only passes through an intermediate partition, it means that a single partition crossing is allowed between the two partitions, and the two response data are also connected into the same spatial chain. The concept of "connectivity through only one intermediate partition" can be determined by querying the set of adjacent partitions of the preceding partition and determining whether there exists an intermediate partition in that set that is adjacent to the following partition. If the preceding and following response data are neither the same nor adjacent, and there is no connectivity through only one intermediate partition, it means that although the candidate response sequence is continuous in time, it does not have a reasonable path for the same muon traversal in spatial propagation and should be truncated at that point, no longer being processed as the same spatial chain. After completing the spatial check of all preceding and following response data for each candidate response sequence, the set of response data that are both temporally and spatially continuous is determined as the response group. For example, if the partition numbers corresponding to a candidate response sequence are A3, A4, and B4, then A3 and A4 are adjacent partitions, and A4 and B4 are also adjacent partitions, and this sequence can be considered as the same response group. If the partition numbers of another candidate response sequence are C1 and E4, then the two are neither adjacent nor have a connectivity through only one intermediate partition, and therefore cannot be connected as the same response group.

[0059] After obtaining the response groups, a consistency check needs to be performed on each response group to eliminate pseudo-combinations that, although satisfying temporal and spatial continuity, do not conform to the characteristics of a single muon crossing propagation. Specifically, the order of all response data within the response group in the sorting results and the partition distribution corresponding to each response data are first read, and the start times of adjacent two response data are checked one by one according to the sorting order to see if they increase sequentially. If the start time of the later response data is less than the start time of the earlier response data, it indicates that the formation order within the response group has reversed, which does not conform to the characteristic of a single muon crossing continuously advancing along the path. Based on the characteristics of the response group, it should be determined that the response group has failed the consistency check. For response groups whose time order increases sequentially, the number of traversals between the partitions corresponding to two adjacent response data sets is calculated using the partition adjacency list. This number of traversals can be taken as the number of edges traversed by the shortest connected path between the two partitions; for example, the number of traversals between the same partition is 0, the number of traversals between directly adjacent partitions is 1, and the number of traversals between partitions passing through only one intermediate partition is 2. Subsequently, these number of traversals are checked sequentially along the direction of the response group arrangement to ensure that there is no backtracking. "No backtracking" means that the partition corresponding to the current response data does not return to a previously left-away distant partition. There should be no obvious reversal in the path direction. In actual execution, the first partition appearing in the response group can be used as the starting reference partition, and the shortest path level of each response data relative to the starting reference partition should be accumulated and recorded according to the arrangement direction. If the level value of a later response data is less than the level value of the previous response data, it indicates that the path has bounced back, and the response group should be judged to have failed the consistency check. If the level value remains unchanged, it indicates that the response continues to advance in the same direction, and it can be judged to have satisfied the traversal consistency. For example, if the partition sequence of a response group is D2, D3, D4, E4, then relative to the starting reference partition... The hierarchical values ​​of zone D2 are 0, 1, 2, 3, which indicates continuous progress and can pass the check. If the partition sequence of a response group is D2, D3, D2, D4, then the hierarchical values ​​are 0, 1, 0, 2, where the third response data reverts to the D2 partition that has already been left, which is a jump and should be removed. For response groups that pass the consistency check, they are identified as response groups corresponding to the same muon traversal, and the start time of the first response data, the end time of the last response data, the sequence of all partition numbers, and the number of response data in the response group are written into the same event record as the output muon event for subsequent steps to call.

[0060] Through the above implementation process, the discrete response data output by the outer VETO detector can be filtered layer by layer according to unified, clear and executable temporal connection rules, spatial connection rules and crossing consistency rules. This ensures that the final muon events have clear formation basis and stable path meaning, thereby avoiding mistaking responses that only overlap in time for the same crossing event, and also avoiding forcibly splicing scattered responses with no reasonable propagation relationship in space into muon events. Furthermore, since the muon events are output after the temporal chain construction, spatial chain construction and consistency check are completed, the subsequent steps have a unified data source and a clear calculation starting point when extracting the first and last response times, cross-regional propagation order, regional response density and crossing depth. This is conducive to ensuring the terminology consistency and execution closure of the entire processing chain.

[0061] In practical applications: For example, an outer VETO detector is divided into 16 zones. Within a certain observation period, zone A1 outputs the first response data from 102 nanoseconds to 110 nanoseconds, zone A2 outputs the second response data from 108 nanoseconds to 116 nanoseconds, zone B2 outputs the third response data from 115 nanoseconds to 122 nanoseconds, and zone D4 outputs the fourth response data from 140 nanoseconds to 145 nanoseconds. The system first sorts the data by their start times, then connects the first three response data into the same time chain because they are consecutive in time, while the fourth response data forms a separate time chain because there is a time gap between it and the third response data. Subsequently, based on the zone adjacency list, it is determined that A1 and A2 are adjacent, and A2 and B2 are adjacent. Therefore... The first three response data sets satisfy both temporal and spatial continuity and are grouped into the same response group. The time chain corresponding to D4 is retained separately because there is no consecutive data before and after it. Next, a consistency check is performed on the response groups corresponding to A1, A2, and B2 to confirm that their start times increase sequentially and the partition levels advance continuously from A1 to A2 to B2 without any backsliding. Therefore, this response group is identified as the response group corresponding to the same muon crossing and is output as a muon event. The fourth response data set does not form a multi-partition continuous advancement relationship and can be retained as an independent short-range response according to the actual system settings or not participate in the determination of the same muon crossing event in the future. In this way, the system can complete the identification of muon events with a reproducible execution flow during actual detection operation.

[0062] S2. Based on the muon event, extract the first and last response times, cross-regional propagation order, regional response density and traversal depth of each response group, and generate corresponding aftereffect labels according to the combination relationship of the first and last response times, cross-regional propagation order, regional response density and traversal depth.

[0063] In this embodiment, the purpose of S2 is to further transform the identified muon events into aftereffect markers that can be directly invoked for subsequent masking period expansion and partition rule generation. The muon event output in the previous step is essentially a response group that satisfies temporal continuity, spatial continuity, and cross-regional consistency. However, this response group is still a raw set composed of multiple response data and cannot be directly used for subsequent duration calculation and partition expansion. Therefore, it is necessary to extract core features that can characterize the subsequent impact range of this muon cross-regional event. In specific processing, the first response time, the last response time, and the cross-regional propagation order are first determined from the response group. Then, based on this, the partition response density of each partition and the cross-regional depth corresponding to the entire propagation path are calculated. Finally, the aforementioned results are written into the same marker structure in a unified order to form aftereffect markers, so as to ensure that the source of the fields is clear, the calculation chain is closed, and the processing caliber between different muon events is consistent when called in subsequent steps. This implementation process includes the following steps:

[0064] First, obtain the start time, end time, and partition number of all response data within the response group corresponding to the Muon event, and then re-confirm the sorting order of each response data in the response group according to the start time in ascending order; if two response data have the same start time, the response data with the earlier end time is placed first; after sorting, the start time of the first response data in the sorted result is determined as the first response time, and the largest value of the end time among all response data is determined as the last response time; then, generate the cross-regional propagation order according to the order in which each partition number first appears in the sorted result, specifically, reading the partitions one by one from front to back along the sorted result. The partition number is written into the propagation order queue when it first appears. If the same partition number appears again, it will not be written again. This results in an ordered partition sequence that reflects the cross-partition propagation path of the muon event. The first response time, the last response time, and the cross-partition propagation order are output as time-series features. For example, if the partition numbers of four response data in a response group are A1, A2, A2, and B2 after being sorted by time, the first response time is the start time of the first response data, the last response time is the end time of the fourth response data, and the cross-partition propagation order is recorded as A1, A2, and B2, without repeating the second occurrence of A2.

[0065] After obtaining the temporal characteristics, the response counts for each partition within the response group and the position of each partition in the cross-regional propagation order are further obtained to calculate the partition response density and traversal depth. Specifically, the total number of response data entries in the response group is first counted, which is taken as the total number of responses. Then, the number of times each partition number appears in the response group is counted, which is taken as the response count for the corresponding partition. For each partition, the partition response density is obtained by dividing the response count of that partition by the total number of responses. This value can be stored directly as a fraction or converted to decimal form, as long as it remains consistent within the same system. Afterward, the first and last partitions are determined according to the cross-regional propagation order, and the traversal depth between the first and last partitions is calculated using the partition adjacency list. The number of partition levels traversed is used as the traversal depth. This partition level number can be calculated based on the number of edges traversed by the shortest connected path. For example, if the first and last partitions are the same, the traversal depth is recorded as 0; if they are directly adjacent, it is recorded as 1; if they require an intermediate partition to be connected, it is recorded as 2. If the cross-partition propagation order is A1, A2, B2, and A1 is adjacent to A2 and A2 is adjacent to B2, then the first partition A1 and the last partition B2 are connected through two levels, and the traversal depth is recorded as 2. If A1 appears once, A2 appears twice, and B2 appears once in a response group, with a total response count of 4, then the partition response density of A1 is 1 / 4, the partition response density of A2 is 2 / 4, and the partition response density of B2 is 1 / 4. After completing the above calculations, the density depth feature is output.

[0066] After obtaining the temporal and density-depth features, a unified aftereffect marker is further generated. Specifically, the first and last response times are written into the same time field in chronological order to form a time period identifier; the partition numbers in the cross-regional propagation sequence are written into the same path field in order to form a path identifier; the partition response densities of each partition are written into the same density field according to their partition numbers to form a density identifier; and the traversal depth is written into the depth field to form a depth identifier. Then, the time period identifier, path identifier, density identifier, and depth identifier are combined into a single aftereffect marker in a fixed order, and this aftereffect marker is output... The output is used for subsequent calculations of basic shielding duration, observation extension duration, and alert zone range. During actual writing, the aftereffect markers can be organized as multiple fields in the same event record or as multiple attributes in the same storage object, but the field order and meaning should remain consistent within the same implementation. For example, for the aforementioned response group, the first and last response times can be written as 102 nanoseconds to 122 nanoseconds, the path identifier as A1-A2-B2, the density identifier as A1:1 / 4, A2:2 / 4, B2:1 / 4, and the depth identifier as 2, thus forming a complete aftereffect marker.

[0067] Through the above implementation process, the original scattered temporal, spatial, and partitioned response information in the response group can be organized into a unified and clearly sourced aftereffect marker. This allows subsequent steps to directly complete time-period calculations and partition expansion without repeatedly tracing back to the original response data. It also ensures consistency in input fields and calculation methods for different muon events in subsequent processing. Since the first response time, last response time, cross-regional propagation order, partitioned response density, and traversal depth all have clear value bases, it effectively avoids problems such as abstract terminology, unclear field sources, or broken calculation processes. In practical applications: for example, a response group corresponding to a muon event contains four response data points, with partition numbers A1, A2, A2, and B2 after time sorting, and starting times of 102 nanoseconds, 108 nanoseconds, and 11 nanoseconds respectively. The time intervals are 5 nanoseconds and 118 nanoseconds, with end times of 110 nanoseconds, 116 nanoseconds, 119 nanoseconds, and 122 nanoseconds respectively. Therefore, the first response time is taken as 102 nanoseconds, and the last response time is taken as 122 nanoseconds. The cross-region propagation order is A1, A2, B2. The total number of responses is 4, with A1 appearing once, A2 appearing twice, and B2 appearing once. Therefore, the partition response densities are 1 / 4, 2 / 4, and 1 / 4 respectively. The shortest connected path from A1 to B2 is calculated using the partition adjacency list, which involves two levels of connections and a traversal depth of 2. Finally, 102 nanoseconds to 122 nanoseconds are written as time interval identifiers, A1-A2-B2 are written as path identifiers, A1:1 / 4, A2:2 / 4, and B2:1 / 4 are written as density identifiers, and 2 is written as a depth identifier. These are combined in a fixed order to form the same aftereffect marker for direct use in subsequent steps.

[0068] S3. Based on the aftereffect marker, determine the basic shielding duration according to the crossing depth, determine the observation extension duration according to the partition response density, determine the warning partition range according to the cross-regional propagation sequence, expand the basic shielding duration, observation extension duration and warning partition range of each partition into partitions, generate the shielding period, observation period and warning period corresponding to each partition, and output the partitioning rules.

[0069] In this embodiment, the purpose of step S3 is to convert a muon event into a directly executable partitioning rule based on the aftereffect marker, so that subsequent candidate events can be matched with the shielding period, observation period, and alert period according to a unified standard. The aftereffect marker output in the previous step has given the first response time, the last response time, the cross-regional propagation order, the corresponding partition response density, and the crossing depth of each partition. However, these fields are still feature results and have not yet been expanded into time period rules that can be directly applied to each partition. Therefore, this implementation process first uses the first response time and the last response time to calculate the crossing duration, then combines the crossing depth to generate the basic shielding duration, and combines the corresponding partition response density of each partition to generate the corresponding observation extension duration of each partition. Subsequently, the main alert partition and the extended alert partition are determined according to the cross-regional propagation order and the partition adjacency list. Finally, based on the last response time, the basic shielding duration and the observation extension duration are expanded by partition to form the shielding period, observation period, and alert period corresponding to each partition, thereby outputting the partitioning rule. This implementation process includes the following steps:

[0070] First, the initial response time, final response time, cross-regional propagation order, partition response density, and traversal depth of each partition are obtained from the aftereffect markers, and partition duration data is generated based on these fields. In practice, the span duration is obtained by subtracting the initial response time from the final response time. The span duration characterizes the actual time span of the muon event from the appearance of the first response to the end of the last response. Then, the span duration is multiplied by the traversal depth to obtain the basic shielding duration. Here, the traversal depth uses the number of partition levels generated in the previous step, thus the basic shielding duration can simultaneously reflect both the time span and path depth. Afterward, for each partition in the cross-regional propagation order, the partition response density corresponding to that partition is read, and the data is used to generate partition duration data. The partition response density of a partition is multiplied by the base shielding duration to obtain the observation extension duration corresponding to that partition. If a partition does not appear in the current aftereffect marking, it is not included in the current observation extension duration calculation. After completing the above calculation, the base shielding duration and the observation extension duration corresponding to each partition are written into the same partition duration record as partition duration data output. For example, if the first response time is 102 nanoseconds and the last response time is 122 nanoseconds, then the traversal duration is 20 nanoseconds. If the traversal depth is 2, then the base shielding duration is 40 nanoseconds. If the partition response densities of partitions A1, A2, and B2 are 1 / 4, 2 / 4, and 1 / 4, respectively, then the corresponding observation extension durations are 10 nanoseconds, 20 nanoseconds, and 10 nanoseconds, respectively.

[0071] After obtaining the partition duration data, the first, last, and intermediate partitions in the cross-regional propagation order are further retrieved, and a set of alert partitions is generated. Specifically, the partition numbers are read sequentially according to the cross-regional propagation order, the partition at the beginning of the sequence is determined as the first partition, the partition at the end of the sequence is determined as the last partition, and the remaining partitions between the first and last partitions are determined as intermediate partitions. Then, according to the cross-regional propagation order, all partitions passed sequentially from the first to the last partition are determined as the main alert partitions. Since the cross-regional propagation order itself is given in the order of first appearance, the main alert partitions can directly use all partition numbers in this order. Next, for each main alert partition, the adjacent partitions are read from the partition adjacency table pre-established by the system, and... These adjacent partitions are identified as extended alert partitions. If an adjacent partition already belongs to a primary alert partition, it is not written to the extended alert partition again. If an extended alert partition is obtained by repeated queries from multiple primary alert partitions, it is retained only once. The primary alert partitions and extended alert partitions obtained in this way together form the alert partition set and serve as the basis for the spatial range output of the subsequent alert period. For example, if the cross-regional propagation order is A1, A2, B2, then A1, A2, and B2 are all primary alert partitions. If the partition adjacency table shows that the adjacent partitions of A1 are A2 and B1, the adjacent partitions of A2 are A1, B2, and A3, and the adjacent partitions of B2 are A2, B1, and B3, then after removing A1, A2, and B2 which already belong to the primary alert partitions, B1, A3, and B3 can be identified as extended alert partitions.

[0072] After obtaining the partition duration data and the set of alert partitions, the final response time is further obtained, and the shielding period, observation period, and alert period corresponding to each partition are generated according to a unified time series benchmark. Specifically, the final response time is used as the starting point of the shielding period corresponding to each partition, and the sum of the final response time and the basic shielding duration is used as the ending point of the shielding period corresponding to each partition, thus obtaining the shielding period uniformly applicable to each partition under the influence of this Muzi event. Subsequently, the ending point of the shielding period corresponding to each partition is used as the starting point of the observation period corresponding to that partition, and the sum of the ending point of the shielding period corresponding to that partition and the observation extension duration corresponding to that partition is used as the ending point of the observation period corresponding to that partition, thus obtaining the observation period expanded by partition. Afterwards, the first response time is used as the starting benchmark of the alert period, and each main alert partition and each extended alert partition is determined as the corresponding partition of the alert period within the range from the first response time to the end point of the corresponding observation period. Here, the "end point of the corresponding observation period" can be taken separately for each partition, that is, each partition in the main alert partition and the extended alert partition uses its own observation period end point as the alert period for this partition. The end time of the warning range; for partitions that only belong to the extended warning partition but do not participate in the partition response density calculation, the end of the basic shielding period can be taken as the end of the observation period, thereby ensuring that such partitions have at least the same warning coverage as the basic shielding duration; after completing the above processing, the shielding period, observation period and warning period corresponding to each partition are uniformly written into the partition rules for output; for example, in the above example, the last response time is 122 nanoseconds and the basic shielding duration is 40 nanoseconds, then the shielding period of the three partitions A1, A2 and B2 is 12 nanoseconds. The observation period for A1 is 162 nanoseconds to 172 nanoseconds, for A2 it is 162 nanoseconds to 182 nanoseconds, and for B2 it is 162 nanoseconds to 172 nanoseconds. The main alert zones A1, A2, and B2, as well as the extended alert zones B1, A3, and B3, can all enter the alert range starting 102 nanoseconds from the first response time. The alert endpoints for A1, A2, and B2 are 172 nanoseconds, 182 nanoseconds, and 172 nanoseconds, respectively, while the corresponding alert endpoints for B1, A3, and B3 can be 162 nanoseconds.

[0073] Through the above implementation process, the feature fields in the aftereffect labeling can be further expanded into partitioning rules with clear start and end times and clear partition affiliations. This allows subsequent candidate events to no longer rely on abstract judgments but can be directly matched item by item with the partitioning rules based on the event time and event location. Simultaneously, the basic shielding duration is determined by the crossing duration and crossing depth, the observation extension duration is further expanded by the partition response density corresponding to each partition, and the alert partition range is limited by the cross-regional propagation order and partition adjacency relationship. Therefore, the entire rule generation chain has a clear data source and continuous computational relationship. In practical applications: for example, in a certain aftereffect labeling, the initial response time is 102 nanoseconds, the final response time is 122 nanoseconds, the cross-regional propagation order is A1, A2, B2, and the partition response densities corresponding to A1, A2, and B2 are 1 / 4, 2, and 2, respectively. With a crossing depth of 2, the system first calculates the crossing time as 20 nanoseconds and the basic shielding time as 40 nanoseconds. Then, it obtains the observation extension times for A1, A2, and B2 as 10 nanoseconds, 20 nanoseconds, and 10 nanoseconds, respectively. Subsequently, based on the cross-regional propagation order, A1, A2, and B2 are determined as the primary alert partitions, and B1, A3, and B3 are determined as extended alert partitions based on the partition adjacency list. Finally, the shielding time periods for A1, A2, and B2 are uniformly determined to be 122 nanoseconds to 162 nanoseconds, and the observation time periods are determined to be 162 nanoseconds to 172 nanoseconds, 162 nanoseconds to 182 nanoseconds, and 162 nanoseconds to 172 nanoseconds, respectively. The alert time periods for A1, A2, B2, B1, A3, and B3 from 102 nanoseconds to their respective endpoints are written into the alert time periods, thus forming partitioning rules that can be directly used for candidate event matching.

[0074] S4. Obtain candidate events output by the main detector, and match the candidate events with the partitioning rules according to the temporal inclusion relationship between the event time and the corresponding time period of each partition, as well as the spatial attribution relationship between the event location and the range of the warning partition, and output the association results.

[0075] In this embodiment, the purpose of step S4 is to match the candidate events output by the main detector with the partitioning rules generated in the previous step to determine whether the candidate event is affected by the aftereffects of the current muon event. The previous step has given the shielding period, observation period, and alert period corresponding to each partition, but these rules still need to be correlated with the actual candidate events on the main detector side in order to provide a direct basis for the subsequent VETO processing result determination. Therefore, this implementation process first determines the event partition to which the candidate event belongs based on the event location, then compares the event time with the shielding period and observation period corresponding to the event partition one by one, and at the same time compares the event partition with the main alert partition and extended alert partition corresponding to the alert period one by one. Finally, the correlation results are output in a unified order to ensure that the candidate event can be clearly distinguished as falling into the shielding period, observation period, or alert period during subsequent processing. This implementation process includes the following steps:

[0076] First, obtain the event time and event location corresponding to the candidate event. Then, determine the event partition corresponding to the candidate event in the main detector partition mapping table based on the event location, and output the event attribution data. In specific execution, the event time can be directly obtained from the timestamp generated by the main detector for that candidate event, and the event location can be obtained from the reconstructed location coordinates of the main detector, or from location identifiers such as layer number, channel number, and element number recorded internally by the main detector. When the event location is in coordinate form, the coordinates can be compared with the partition boundaries pre-divided by the main detector to determine the partition range it falls into. When the event location uses discrete identifiers such as layer number, channel number, and element number, it can be directly obtained from the main detector partition mapping table. The corresponding partition number is obtained by looking up the partition mapping table of the main detector. The partition mapping table of the main detector can be pre-established by the structural layout of the main detector and is used to record the correspondence between each position area of ​​the main detector and the unified partition number. If the position of a candidate event happens to be on the boundary line of an adjacent partition, its unique event partition can be determined according to the boundary assignment direction agreed upon by the system in advance. For example, it can be uniformly assigned to the partition with the smaller number or uniformly assigned to the partition corresponding to the center point of the event coordinates, so as to ensure that the assignment of similar boundary events is consistent. After completing the above processing, the event time, event position and event partition are written into the same event assignment record as the event assignment data output.

[0077] After obtaining the event attribution data, the process further retrieves the blocking time period, observation time period, and alert time period corresponding to each partition in the event attribution data and partitioning rules, and performs spatiotemporal matching. Specifically, the event time and event partition are first read from the event attribution data, and then the blocking time period and observation time period corresponding to the event partition are queried in the partitioning rules. Subsequently, the event time is compared with the start and end points of the blocking time period and the start and end points of the observation time period corresponding to the event partition. In actual comparison, the method of "start point less than or equal to event time and event time less than or equal to end point" can be used to determine whether the event time falls into the corresponding time period, thereby avoiding the problem of the start and end boundary times not being able to be assigned. After completing the time comparison, the partition corresponding to the alert time period in the partitioning rules is read, and it is determined whether the event partition belongs to the main alert partition or the extended alert partition corresponding to the alert time period. The partition attribution comparison here can be directly performed by... The system determines whether the partition numbers are the same: if the event partition number exists in the main alert partition list, it is determined that it matches the main alert partition; if the event partition number exists in the extended alert partition list, it is determined that it matches the extended alert partition; if neither exists, it is determined that it does not belong to the partition range covered by the current alert period. After completing the above time comparison and partition comparison, the matching results of the shielded period, the matching results of the observation period, and the matching results of the alert period partition are written into the same record as spatiotemporal matching data output. For example, if the event time of a candidate event is 168 nanoseconds and the event partition is A2, and the shielded period corresponding to A2 in the partitioning rules is from 122 nanoseconds to 162 nanoseconds and the observation period is from 162 nanoseconds to 182 nanoseconds, and A2 belongs to the main alert partition, then the candidate event does not match the shielded period in time, matches the observation period, and matches the alert period coverage partition in space.

[0078] After obtaining the spatiotemporal matching data, further association results are generated. Specifically, first, it is checked whether the event time falls within the shielded period corresponding to the event partition. If it does, the candidate event is directly associated with the shielded period. If the event time does not fall within the shielded period, it is checked whether it falls within the observation period corresponding to the event partition. If it does, the candidate event is associated with the observation period. If the event time falls neither within the shielded period nor the observation period, it is checked whether the event partition belongs to the main alert partition or the extended alert partition corresponding to the alert period. If it does, the candidate event is associated with the alert period. The order of judgment here—shielded period, then observation period, and then alert period—is adopted because the shielded period and observation period depend on both time and partition conditions, and have higher priority than the alert period, which only reflects the spatial alert range. The sequentially output association results can be directly used for the next step of VETO processing result determination. If a candidate event does not meet the above three checks, its association result can be recorded as unrelated so that it can be directly retained in the subsequent processing. After processing is completed, the association type corresponding to the candidate event is written into the association result for output. For example, the aforementioned candidate event with an event time of 168 nanoseconds and an event partition of A2 is determined to be associated with the observation period of A2 because it does not fall into the shielding period of A2 but falls into the observation period of A2. If another candidate event has an event time of 150 nanoseconds and an event partition of B1, and B1 belongs to the extended alert partition and has not been expanded into an observation period, it can first be determined whether it falls into the general shielding coverage area. If it does not fall into the coverage area, it is determined to be associated with the alert period because its event partition belongs to the extended alert partition.

[0079] Through the above implementation process, a clear one-to-one correspondence can be established between candidate events on the main detector side and the partitioning rules. This ensures that each candidate event has a clear time period and partitioning basis before entering subsequent VETO processing, thus avoiding rough judgment based solely on a single time window or spatial range. Furthermore, since event partitioning is determined through the main detector partitioning mapping table, the shielding period and observation period are determined by comparing start and end intervals, and the alert period is determined by comparing the main alert partition and the extended alert partition, the entire association matching process has clear data input, clear comparison methods, and clear output results, ensuring the closed processing chain of subsequent steps. In practical applications: for example, in the partitioning rules corresponding to a certain muon event, the shielding periods for A1, A2, and B2 are all 122 nanoseconds to 162 nanoseconds, the observation period for A1 is 162 nanoseconds to 172 nanoseconds, the observation period for A2 is 162 nanoseconds to 182 nanoseconds, and the observation period for B2 is... The observation period is from 162 nanoseconds to 172 nanoseconds. The main alert zones are A1, A2, and B2, and the extended alert zones are B1, A3, and B3. If the main detector outputs a candidate event with an event time of 168 nanoseconds and the event location is determined to be A2 by the main detector zone mapping table, the system first determines that the 168 nanoseconds do not fall within the shielding period of 122 nanoseconds to 162 nanoseconds in A2, and then determines that the 168 nanoseconds fall within the observation period of 162 nanoseconds to 182 nanoseconds in A2, thus outputting the result of associating the candidate event with the observation period. If another candidate event has an event time of 170 nanoseconds and the event location is determined to be B1, the system determines that the event time does not correspond to the observation period of B1, but B1 belongs to the extended alert zone, so the result of associating the candidate event with the alert period is output. If there is yet another candidate event with an event time of 190 nanoseconds and the event location is determined to be C4, and C4 does not belong to the main alert zone or the extended alert zone, then no association result is output.

[0080] S5. Based on the association results, determine whether the candidate event falls into the corresponding partition's blocking period, observation period, or alert period, and determine the VETO processing result of the candidate event according to the processing order of blocking period taking precedence over observation period and observation period taking precedence over alert period.

[0081] In this embodiment, the purpose of step S5 is to uniformly merge and prioritize the association results of candidate events, thereby outputting a unique VETO processing result. The previous step has already completed the association matching between candidate events and the blocking period, observation period, and alert period, but the association results themselves are still item-by-item judgment results and have not yet been transformed into a processing conclusion that can be directly executed. Therefore, this implementation process first extracts the blocking period association marker, observation period association marker, and alert period association marker from the association results and writes them into the processing sequence in a fixed order. Then, it determines the target period type corresponding to the candidate event based on the association marker that appears first in the processing sequence. Finally, it outputs the corresponding VETO processing result according to the target period type to ensure that the same candidate event always obtains a unique processing conclusion according to the same priority order when there are multiple possible associations. This implementation process includes the following steps:

[0082] First, obtain the association results corresponding to the candidate events, and extract the shielding period association marker, observation period association marker, and alert period association marker from these results. In practice, the association results output in the previous step can be parsed into three Boolean states or three existence states: when a candidate event is determined to be associated with a shielding period, the shielding period association marker is marked as existing; when a candidate event is determined to be associated with an observation period, the observation period association marker is marked as existing; when a candidate event is determined to be associated with an alert period, the alert period association marker is marked as existing; markers not determined to be associated are marked as non-existent. Subsequently, the shielding period association marker, observation period association marker, and alert period association marker are written into the processing in the order listed. The processing sequence can be stored as a fixed-length sequential field or a three-digit sequential list, as long as the order remains consistent within the same implementation. If a certain associated marker does not exist, an empty value or a non-existent marker is written in the corresponding position. If it exists, the corresponding time period name or corresponding number is written. After writing, the time period determination sequence is output. For example, when a candidate event is only associated with the observation time period, the processing sequence can be written as "empty, observation time period, empty". When a candidate event is associated with the shielded time period, even if its event partition also belongs to the alert partition, the processing sequence can still be written as "shielded time period, empty, alert time period" or "shielded time period, empty, empty", and subsequent processing will be based on the first occurrence of the marker.

[0083] After obtaining the time period determination sequence, the target time period type corresponding to the candidate event is further determined based on the first occurrence of the markers in the processing sequence. Specifically, starting from the first position of the processing sequence, the sequence is read sequentially. First, it checks whether the masking time period association marker exists. If it exists, the target time period type is directly determined as the masking time period, and subsequent markers are not checked. If the masking time period association marker does not exist, the observation time period association marker is checked. If the observation time period association marker exists, the target time period type is determined as the observation time period. If neither the masking time period association marker nor the observation time period association marker exists, the alert time period association marker is checked. If the alert time period association marker exists, the target time period type is determined as the alert time period. If none of the three associated markers exist, the target time period type can be recorded as "no time period type," indicating that the candidate event is not constrained by the current partitioning rules. The purpose of adopting the above order is to ensure that the shielded time period takes precedence over the observation time period, and the observation time period takes precedence over the alert time period, thereby avoiding processing conflicts when the same candidate event has multiple spatiotemporal coverages. After the determination is completed, the determined target time period type will be output. For example, when the time period determination sequence of a candidate event is "shielded time period, observation time period, alert time period," the system only takes the first shielded time period as the target time period type. When the time period determination sequence of a candidate event is "empty, observation time period, alert time period," the observation time period is taken as the target time period type.

[0084] After obtaining the target time period type, VETO processing results for candidate events are further generated based on the target time period type. Specifically, candidate events with a target time period type of "masked time period" are identified as masked and eliminated results, candidate events with a target time period type of "observation time period" are identified as observation and marked results, and candidate events with a target time period type of "alert time period" are identified as retained output results. If the target time period type is "no time period type," the candidate event can also be identified as a retained output result, or it can be marked separately as an unrelated retained result in the system, as long as the subsequent output criteria remain consistent. Here, "masked and eliminated results" indicates that the candidate event will be included in the subsequent output results. Candidate events are not retained as valid detection events; the observation tagging result indicates that the candidate event is temporarily retained but an observation tag is added; the retained output result indicates that the candidate event is not eliminated and continues to be output as the original event; after completing the above mapping, the candidate event number and the corresponding VETO processing result are written into the result record for output; for example, if the target time period type of a candidate event is a masked time period, its VETO processing result is written as the masked elimination result; if the target time period type of another candidate event is an observation time period, its VETO processing result is written as the observation tagging result; if another candidate event is only associated with a warning time period, its VETO processing result is written as the retained output result;

[0085] Through the above implementation process, the itemized association results of candidate events can be compressed into a unique and clear VETO processing result, eliminating the need for subsequent execution steps to repeatedly judge multiple time period conditions, thus ensuring a concise processing chain and consistent standards. Furthermore, by first writing the processing sequence, then determining the target time period type in a fixed order, and finally mapping it to the VETO processing result, the priority relationship between the masked time period, observation time period, and alert time period can be explicitly implemented, avoiding inconsistent results for the same candidate event under different coverage relationships. In practical applications: for example, if the association result of a candidate event shows that it is associated with the observation time period and the event partition belongs to the extended alert partition, then the three association markers extracted by the system are, in order, that the masked time period association marker does not exist, the observation ... If the observation period association marker exists and the warning period association marker exists, they are written into the period determination sequence. Then, the sequence is read in sequence. Since the shielded period association marker does not exist and the observation period association marker exists, the target period type is determined to be the observation period, and the observation marker result is further output. For example, if the association result of another candidate event shows that its event time has fallen into the shielded period and the event partition also belongs to the main warning partition, then the system first writes the shielded period association marker into the processing sequence, and then writes the warning period association marker. Since the shielded period association marker appears first, the target period type is directly determined to be the shielded period, and the shielding and removal result is output. In this way, different candidate events can obtain a unique VETO processing result according to a unified order.

[0086] S6. Based on the VETO processing results, perform masking and elimination processing on candidate events that fall into the masking period, perform observation and marking processing on candidate events that fall into the observation period, and perform output retention processing on candidate events that only fall into the alert period to generate the final VETO detection results.

[0087] In this embodiment, the purpose of step S6 is to incorporate the VETO processing results obtained in the previous step into the main detector output record, forming the final VETO detection result that can be directly used for subsequent measurement, storage, or analysis. The previous step has already provided a unique VETO processing result for each candidate event, but this result is still a judgment conclusion and has not yet been applied to the actual event record. Therefore, it is necessary to further classify the candidate events according to the processing results and perform deletion, marking, or retention operations respectively. Finally, the results are summarized in a unified order to generate the final output. This implementation process first writes the candidate events into the elimination set, observation set, and output set, then performs processing on the corresponding event items in the main detector output record, and finally summarizes and retains the events in the order of event time to form the final VETO detection result. This implementation process includes the following steps:

[0088] First, the VETO processing results and candidate event data corresponding to the candidate events are obtained, and the candidate events are classified according to the processing results. Specifically, the candidate event data includes at least the event number, event time, event location, and the corresponding event item identifier in the main detector output record. The VETO processing results include at least three categories: masking / removal results, observation / marking results, and retained output results. The system reads the candidate event data and its corresponding VETO processing results one by one. When the VETO processing result of a candidate event is a masking / removal result, the event number and corresponding event item identifier of that candidate event are written into the removal set. When the VETO processing result is an observation / marking result, the... The event number and corresponding event item identifier of the candidate event are written into the observation set; when the VETO processing result is a retained output result, the event number and corresponding event item identifier of the candidate event are written into the output set; the elimination set, observation set, and output set can be stored in the form of a list, queue, or index table, as long as they are kept consistent in the same implementation; after all candidate events are classified, the classification result is output; for example, if there are 5 candidate events in a certain observation period, of which 2 correspond to the masking elimination result, 1 corresponds to the observation mark result, and 2 correspond to the retained output result, then these 5 candidate events are written into the corresponding sets respectively to form the classification result of the observation period;

[0089] After obtaining the classification results, further processing is performed on the corresponding event items in the main detector output record. Specifically, first, candidate events in the elimination set are read, and the corresponding event item is located in the main detector output record according to the event item identifier of each candidate event. After location, the event item is either deleted from the main detector output record or marked as invalid and not included in the output during subsequent aggregation; both methods need to be consistent within the same system. Then, candidate events in the observation set are read, and the corresponding event items in the main detector output record are located, and an observation mark is written to the event item. The observation mark can be directly written to the event status field, or a new one can be created. Add a marker field to record the "observation" status; then read the candidate events in the output set, locate the corresponding event item in the main detector output record, retain the original content of the event item, and write a pass mark in the event item to indicate that the event has passed this VETO process; after completing the above three types of processing, output the processing result; for example, if event number E01 is in the rejection set, then delete the event item corresponding to E01 in the main detector output record; if event number E02 is in the observation set, then retain the original event item E02 and write an observation mark; if event number E03 is in the output set, then retain the original event item E03 and write a pass mark.

[0090] After obtaining the processing results, the final VETO detection results are generated. Specifically, all event items that were not deleted in the processing results are read and reordered in ascending order of event time. If there are multiple event items with the same event time, they can be sorted in ascending order of event number or in the order of the original records from the main detector, as long as the output caliber remains consistent. After sorting, candidate events with the pass mark and original event items and observation mark are retained and summarized in the final output results. The pass mark and observation mark are retained along with the corresponding event items to distinguish between ordinary retained events and events with observation attributes during subsequent analysis. Event items that have been deleted or marked as invalid are not written into the final output results. After summarizing, the final VETO detection results are generated. For example, if, after processing, the remaining event items in a certain observation period include two events with the pass mark and one event with the observation mark, these three event items are written into the same output result in the order of event time to form the final VETO detection results for that observation period.

[0091] Through the above implementation process, the VETO processing results can be accurately incorporated into the main detector output record, ensuring that the final output no longer remains at the decision-making level but forms a set of event results that can be directly used for subsequent measurement processing. Simultaneously, the processing chain of first classifying, then processing, and then summarizing ensures that the processing methods for rejected events, observed events, and retained events are separated and standardized, avoiding unclear output caused by mixed processing of different types of events. In practical applications: for example, within a certain observation period, the main detector outputs four candidate events, numbered E01, E02, E03, and E04, where E01 corresponds to the masking rejection result, E02 corresponds to the observation marking result, and E03... The system first writes E01 into the rejection set, E02 into the observation set, and E03 and E04 into the output set. Then, it deletes the event item corresponding to E01 from the main detector output record, writes an observation mark into the event item corresponding to E02, and writes a pass mark into the event items corresponding to E03 and E04 respectively. Finally, it summarizes the three undeleted event items E02, E03, and E04 in the order of event time to generate the final VETO detection result, where E02 is marked with an observation mark, and E03 and E04 are marked with a pass mark. In this way, the final output result can both reject events that should be blocked and retain observation events that need to be monitored and normal pass events.

[0092] Furthermore, a VETO detection system for shielding cosmic ray muons includes:

[0093] The event aggregation module acquires the response data output by the outer VETO detector within the current observation period, aggregates the response data according to the response time order and spatial adjacency, identifies the response group corresponding to the same muon crossing, and outputs the muon event.

[0094] The tag generation module extracts the first and last response times, cross-regional propagation order, regional response density, and traversal depth of each response group based on the muon event, and generates corresponding aftereffect tags according to the combination relationship of the first and last response times, cross-regional propagation order, regional response density, and traversal depth.

[0095] The rule generation module, based on aftereffect markers, determines the basic shielding duration according to the crossing depth, the observation extension duration according to the partition response density, and the warning partition range according to the cross-regional propagation order. It then expands the basic shielding duration, observation extension duration, and warning partition range of each partition to generate the shielding period, observation period, and warning period corresponding to each partition, and outputs the partition rules.

[0096] The association matching module obtains candidate events output by the main detector, and performs association matching between the candidate events and the partition rules according to the temporal inclusion relationship between the event time and the corresponding time period of each partition, as well as the spatial belonging relationship between the event location and the range of the warning partition, and outputs the association results.

[0097] The result determination module determines whether the candidate event falls into the corresponding partition's blocking period, observation period, or alert period based on the association results, and determines the VETO processing result of the candidate event according to the processing order of blocking period taking precedence over observation period and observation period taking precedence over alert period.

[0098] The results output module performs masking and elimination processing on candidate events falling into the masking period, observation and marking processing on candidate events falling into the observation period, and retention and output processing on candidate events falling only into the alert period, based on the VETO processing results, to generate the final VETO detection results.

[0099] Working Principle: The core idea of ​​this scheme is not to immediately treat every response collected by the outer VETO detector as a muon event that needs to be shielded. Instead, it first reassembles the response data that are sequential and spatially progressive within the same observation period into a true cross-transit response chain, thereby identifying the muon event corresponding to the same muon cross-transit. Then, it extracts the first and last response times, cross-regional propagation order, response proportion of each region, and cross-transit depth from this muon event to generate a post-effect marker, which is used to determine the extent and duration of subsequent interference to the main detector after this muon cross-transit. Based on this aftereffect marker, shielding periods, observation periods, and alert periods are defined for different zones, forming zoning rules. When the main detector outputs a candidate event, the time and location of the candidate event are matched against these zoning rules one by one to determine whether the event should be directly eliminated, retained but marked with an observation marker, or normally retained for output. In other words, this scheme does not use a fixed time window to block all subsequent events indiscriminately, but first restores the muon crossing process, and then processes subsequent events in layers according to the propagation path and the zone response, thereby suppressing subsequent false signals of muons while minimizing unnecessary false shielding.

[0100] For example, in a low-background particle detection scenario, if the outer VETO detector detects consecutive responses in several partitions A1, A2, and B2 at a certain moment, the system will not simply look at whether there is an alarm. Instead, it will first connect these responses in terms of time and space to confirm that they do indeed correspond to the same muon passage. Then, based on this passage path, it will calculate how long the muon event lasted, which partitions it mainly passed through, which partitions had stronger responses, and the depth of the passage. Based on this, it will determine the shielding and observation periods for partitions A1, A2, and B2 in the subsequent period, while also shielding partitions B1, A3, and B2 adjacent to the path. The third-level partition is included in the warning range. In this way, when a new candidate event appears after the main detector, if the event happens to appear in the A2 partition and the time falls within the shielding period, it is directly eliminated; if it appears in the A2 partition but falls within the observation period, it is retained and marked for observation; if the event does not fall in the core path partition, but its location is within the adjacent warning partition, it is retained for output. In this way, the system can distinguish "which events are more suspicious after this muon crossing and which events do not need to be over-processed". In actual operation, it is more suitable for application environments that require long-term stable measurement and cannot accept large-scale dead time expansion.

[0101] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A VETO detection method for shielding cosmic ray muons, characterized in that, include: S1. Acquire the response data output by the outer VETO detector within the current observation period, aggregate the response data according to the response time order and spatial adjacency, identify the response group corresponding to the same muon crossing, and output the muon event. S2. Based on the muon event, extract the first and last response times, cross-regional propagation order, regional response density, and traversal depth corresponding to each response group, and generate corresponding aftereffect labels according to the combination relationship of the first and last response times, cross-regional propagation order, regional response density, and traversal depth; including: S2-1. Obtain the start time, end time, and partition number of each response data in the response group corresponding to the muon event. Determine the first start time as the first response time and the last end time as the last response time. Generate the cross-regional propagation order according to the order of the first appearance of each partition number and output the time sequence characteristics. S2-2. Obtain the number of responses for each partition within the response group and the position of each partition in the cross-regional propagation order. Divide the number of responses for each partition by the total number of responses in the response group to generate the partition response density for each partition. Generate the traversal depth by the number of partition levels traversed between the first and last partitions in the cross-regional propagation order, and output the density depth feature. S2-3. Obtain time-series features and density-depth features. Concatenate the first response time and the last response time to generate a time period identifier. Generate a path identifier by arranging the cross-regional propagation sequence in order. Generate a density identifier by arranging the partition response density according to the partition number. Generate a depth identifier by traversing the depth. Combine the time period identifier, path identifier, density identifier and depth identifier into the same aftereffect label in the order of time period identifier, path identifier, density identifier and depth label, and output the aftereffect label. S3. Based on the aftereffect marker, determine the basic shielding duration according to the crossing depth, determine the observation extension duration according to the partition response density, determine the warning partition range according to the cross-regional propagation sequence, expand the basic shielding duration, observation extension duration and warning partition range of each partition into partitions, generate the shielding period, observation period and warning period corresponding to each partition, and output the partitioning rules. S4. Obtain candidate events output by the main detector, and match the candidate events with the partitioning rules according to the temporal inclusion relationship between the event time and the corresponding time period of each partition, as well as the spatial attribution relationship between the event location and the range of the warning partition, and output the association results. S5. Based on the association results, determine whether the candidate event falls into the corresponding partition's blocking period, observation period, or alert period, and determine the VETO processing result of the candidate event according to the processing order of blocking period taking precedence over observation period and observation period taking precedence over alert period.

2. The VETO detection method for shielding cosmic ray muons according to claim 1, characterized in that: Also includes: S6. Based on the VETO processing results, perform masking and elimination processing on candidate events that fall into the masking period, perform observation and marking processing on candidate events that fall into the observation period, and perform retention and output processing on candidate events that only fall into the alert period to generate the final VETO detection results.

3. The VETO detection method for shielding cosmic ray muons according to claim 2, characterized in that: S6 includes: S6-1. Obtain the VETO processing results and candidate event data corresponding to the candidate events. Write the candidate events whose VETO processing results are masking and elimination results into the elimination set, write the candidate events whose VETO processing results are observation and labeling results into the observation set, write the candidate events whose VETO processing results are retained output results into the output set, and output the classification results. S6-2. Obtain the classification results, delete the corresponding event items in the main detector output record for candidate events in the elimination set, write observation tags in the corresponding event items for candidate events in the observation set, retain the original event items for candidate events in the output set and write the pass tag, and output the handling results. S6-3. Obtain the processing results, summarize and retain the original event items in the order of event time, and write them into the candidate events marked and the candidate events marked by observation to generate the final VETO detection results.

4. The VETO detection method for shielding cosmic ray muons according to claim 3, characterized in that: S1 includes: S1-1. Obtain the start time, end time and partition number corresponding to each response data. Arrange the response data in ascending order of start time. Connect the two response data whose end time is greater than or equal to the start time of the next response data into the same time chain. Output the candidate response sequence corresponding to each time chain. S1-2. Obtain the partition numbers corresponding to the two response data in each candidate response sequence. Connect the two response data into the same spatial chain according to the following conditions: the previous partition number is the same as the next partition number, or they are adjacent partitions in the partition adjacency list, or there is a connectivity relationship in the partition adjacency list that only passes through one intermediate partition. Output the response group whose time chain and spatial chain are continuous at the same time. S1-3. Obtain the sorting order and partition distribution of all response data in each response group. Perform a traversal consistency check by increasing the start time of adjacent two response data in turn and keeping the number of traversals of the corresponding partition in the partition adjacency list non-backflow. The response group that passes the traversal consistency check is determined as the response group corresponding to the same muon traversal, and the muon event is output.

5. A VETO detection method for shielding cosmic ray muons according to claim 4, characterized in that: S3 includes: S3-1. Obtain the first response time, last response time, cross-regional propagation order, corresponding partition response density and crossing depth in the aftereffect markers. Subtract the first response time from the last response time to generate the crossing duration. Multiply the crossing duration by the crossing depth to generate the basic shielding duration. Multiply the partition response density of each partition by the basic shielding duration to generate the observation extension duration corresponding to each partition. Output the partition duration data. S3-2. Obtain the first partition, the last partition, and the intermediate partitions in the cross-regional propagation order. Determine all partitions that are passed sequentially from the first partition to the last partition as primary alert partitions according to the cross-regional propagation order. Determine the adjacent partitions of each primary alert partition in the partition adjacency table as extended alert partitions. Output the set of alert partitions.

6. A VETO detection method for shielding cosmic ray muons according to claim 5, characterized in that: S3 further includes: S3-3. Obtain partition duration data, alert partition set, and last response time. Use the last response time as the starting point of the shielding period for each partition, the sum of the last response time and the basic shielding duration as the ending point of the shielding period for each partition, the ending point of the shielding period as the starting point of the observation period for each partition, and the sum of the ending point of the shielding period and the corresponding extended observation duration as the ending point of the observation period for each partition. Determine each primary alert partition and each extended alert partition within the range from the first response time to the end of the observation period as the corresponding partition for the alert period. Generate the shielding period, observation period, and alert period for each partition, and output the partitioning rules.

7. A VETO detection method for shielding cosmic ray muons according to claim 6, characterized in that: S4 includes: S4-1. Obtain the event time and event location corresponding to the candidate event, and determine the event partition corresponding to the candidate event in the main detector partition mapping table according to the event location, and output the event attribution data; S4-2. Obtain the blocking period, observation period and alert period corresponding to each partition in the event attribution data and partitioning rules. Compare the start and end intervals of the event time with the blocking period and observation period corresponding to the event partition. Compare the partition attribution of the event partition with the main alert partition and extended alert partition corresponding to the alert period. Output the spatiotemporal matching data. S4-3. Obtain spatiotemporal matching data. When the event time falls within the shielding period corresponding to the event partition, determine the association between the candidate event and the shielding period. When the event time does not fall within the shielding period but falls within the observation period corresponding to the event partition, determine the association between the candidate event and the observation period. When the event partition belongs to the main alert partition or extended alert partition corresponding to the alert period, determine the association between the candidate event and the alert period. Output the association results.

8. A VETO detection method for shielding cosmic ray muons according to claim 7, characterized in that: S5 includes: S5-1. Obtain the association results corresponding to the candidate events, extract the association markers for the shielded period, the observation period, and the warning period, and write them into the processing sequence in the order of the association markers for the shielded period, the observation period, and the warning period, and output the period determination sequence. S5-2. Obtain the time period determination sequence, determine the target time period type corresponding to the candidate event according to the first occurrence mark in the processing sequence, and determine the target time period type as the shielded time period when the shielded time period association mark exists, determine the target time period type as the observation time period when the shielded time period association mark does not exist and the observation time period association mark exists, and determine the target time period type as the warning time period when neither the shielded time period association mark nor the observation time period association mark exists and the warning time period association mark exists. Output the target time period type. S5-3. Obtain the target time period type, determine the candidate events with the target time period type as the masking time period as the masking and elimination result, determine the candidate events with the target time period type as the observation time period as the observation and marking result, determine the candidate events with the target time period type as the warning time period as the retained output result, and output the VETO processing result of the candidate events.

9. A VETO detection system for shielding cosmic ray muons, characterized in that, A VETO detection method for shielding cosmic ray muons according to claim 1 includes: The event aggregation module acquires the response data output by the outer VETO detector within the current observation period, aggregates the response data according to the response time order and spatial adjacency, identifies the response group corresponding to the same muon crossing, and outputs the muon event. The tag generation module extracts the first and last response times, cross-regional propagation order, regional response density, and traversal depth of each response group based on the muon event, and generates corresponding aftereffect tags according to the combination relationship of the first and last response times, cross-regional propagation order, regional response density, and traversal depth. The rule generation module, based on aftereffect markers, determines the basic shielding duration according to the crossing depth, the observation extension duration according to the partition response density, and the warning partition range according to the cross-regional propagation order. It then expands the basic shielding duration, observation extension duration, and warning partition range of each partition to generate the shielding period, observation period, and warning period corresponding to each partition, and outputs the partition rules. The association matching module obtains candidate events output by the main detector, and performs association matching between the candidate events and the partition rules according to the temporal inclusion relationship between the event time and the corresponding time period of each partition, as well as the spatial belonging relationship between the event location and the range of the warning partition, and outputs the association results. The result determination module determines whether the candidate event falls into the corresponding partition's blocking period, observation period, or alert period based on the association results, and determines the VETO processing result of the candidate event according to the processing order of blocking period taking precedence over observation period and observation period taking precedence over alert period. The results output module performs masking and elimination processing on candidate events falling into the masking period, observation and marking processing on candidate events falling into the observation period, and retention and output processing on candidate events falling only into the alert period, based on the VETO processing results, to generate the final VETO detection results.

Images