UFO Buster analysis tool A brief introduction / Software layout Martyna Dziadosz TE-MPE-PE | martyna.dziadosz@cern.ch

Presentation plan Motivations UFO Buster Analysis Tool layout diagram functionalities UFO Buster vs. UFO Buster Analysis Tool Summary During today’s presentation I’m going to talk about Project motivation Tool itself, it’s layout and offered functionalities Finally I will move to its comparison with UFO Buster in accordance to the analyzes feature Will finish by summing everything up 10/10/2017 | Schematic overview of UFO Buster analysis tool Martyna Dziadosz

We want an analysis tool which is: Motivation We want an analysis tool which is: Fast Easy Reliable & reproducible Enables advanced analysis Focus on real UFO data All in one place + manual/readme One module for frequent analyses Search for correlations What prompted us for the analysis tool development? So the need of the tool, that will allows fast and easy advanced analysis focused on UFO events independently from UFO Buster software. Which has to be reliable and reproducible. Obtaining mentioned requirements throught the application of certain conditions. We’re focus on only real UFO data. Software wasn;t interferring with the originial UFO data. The tool consist of several, independent from each other moduls, What is more it provide searching for the correlations in UFO events 10/10/2017 | Schematic overview of UFO Buster analysis tool Martyna Dziadosz

Structure of the UFO Buster analysis tool Data Extraction Raw Data Analysis plot UFO event analysis signal shape group like events Collimator Losses correlation with elastic losses (IP7/IP3/IP6) Advanced Analysis statistical analysis (UFO rates etc.) correlations to LHC parameters determination of UFO location access data select only real UFO events (reduce data volume) discard empty files The following slide presents the bigger picture of the UFO Buster analysis tool. As I’ve already have mentioned it contains 4 independent from each other modules: data extraction, raw data analysis, collimator losses and advanced analysis. The 1st one is intendent to access the data and selecting only real once avoiding empty files. 10/10/2017 | Schematic overview of UFO Buster analysis tool Martyna Dziadosz

DATA EXTRACTION ü ü ü Step 1 Access and retrive data Original PM data UFO Buster data PM data .sdds decoding with JAVA REST API ü standard year analysis ü 16L2 area analysis 1st modile is devoted to to access and retrive the data. Here depending n the purpose od the analysis we can either take original UFO Buster Captur Buffer data To proceed with standard year analysis or location analysis OR PM data from which then 16L2 area analysis were conducted ü analysis via locations 10/10/2017 | Schematic overview of UFO Buster analysis tool Martyna Dziadosz

ü RAW DATA ANALYSIS Plot time-resolved UFO event Step 2 RAW DATA ANALYSIS Plot UFO event & compare with UFO Buster output Losses in Gy/s Time (here in 80 µs bits) UFO Buster from capture buffer After data obtainment initial analysis were conducted. First of all to check the corectness of retrive data, Time-resolved UFO event was plot and compared with the UFO Buster display. As we can see from attached plots, the obained results (plot on the left) corresponds to the one from UFO Buster (right hand side) Plot time-resolved UFO event ü 10/10/2017 | Schematic overview of UFO Buster analysis tool Martyna Dziadosz

 ü RAW DATA ANALYSIS Gaussian fitting signal shape analysis Step 2 RAW DATA ANALYSIS Analyse and group UFO events Losses in Gy/s Time (here in 80 µs bits) ONGOING subsequently the analysis of the UFO event (in accordance to its duration, totall losses, max value) were made. Furthermore the Gaussian function was fit in order to observe the time signal changes. Right now work is focused on grouping like events by the FWHD, max and symmertry values, ü  Gaussian fitting signal shape analysis Group events by FWHD, max, symmetry 10/10/2017 | Schematic overview of UFO Buster analysis tool Martyna Dziadosz

ü STATISTICAL ANALYSIS Plot of loss distribution along LHC Step 3 STATISTICAL ANALYSIS on reduced sample size number of UFOs Location in LHC [m] UFO rate vs. time or location number of UFOs The next step are statistical analysis made on reduced sample size. Presented plots of the UFO rate vs time and location. Losses distibution along LHC, which Gives usmore information about area, that are more pronounced to the UFO occurnece Integrated losses[Gy/s] ü Plot of loss distribution along LHC 10/10/2017 | Schematic overview of UFO Buster analysis tool Martyna Dziadosz

UFO Buster Analysis Tool vs. access to CaptureBuffer data display - manual UFO event verification (by eye) possibility to look into different BLMs, sectors, RS nice GUI analysis part works relatively slow access to CaptureBuffer & PM data - automated verification of real UFO events - plot losses data possibility to look into different BLMs, sectors, RS advantages for future users - easy, user friendly - independent modules for frequent analysis - .json file to set interesting parameters - fast analysis - python scripts, that enables dedicated analysis depending on needs - documented in a GitLab repository dataset reduction searching for correlation plots enable fast analysis Let’s move to the most interesting part of the following presentation, namely the comparison of UFO Buster & UFO Buster analysis tool functionalities. Here it is very important to mention that those concern the analysis module as Ufo Buster itself is a software intended for UFO event detection. So it’s main application Both provide 10/10/2017 | Schematic overview of UFO Buster analysis tool Martyna Dziadosz

Summary of Achievements ü Reduced data volume → faster analysis ü BLM losses vs time → UFO event visualization ü UFO rate plots → vs time, location or BLM name ü Plot of loss distribution along LHC What is done? ü Gaussian fitting & signal shape analysis 10/10/2017 | Schematic overview of UFO Buster analysis tool Martyna Dziadosz

Conclusion – future needs Functionality validation with big data needed UFO events grouping Advanced, dedicated statistical analysis UFO shape analysis Extension to look at long straight section Analysis for collimators area Eventual analysis of ULO Creation of user-friendly GUI To conclude now we have principally working tool created within usage of Python software. Which has still a way of imporvement and development -> validation with big data as so far the data volume was reduced nad the focus was kept at real UFO events -> currently ongoing UFO events grouping -> advanced analysis -> almost doen UFO shape analysis -.... (read) … to be continued! 10/10/2017 | Schematic overview of UFO Buster analysis tool Document reference

Thank you for your attention.  10/10/2017 | Schematic overview of UFO Buster analysis tool Martyna Dziadosz

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F4 DATA EXTRACTION – (UFO Buster) Step 1 Merge only relevant info into one file F3 & F4 Basic info (timestamp, fill number, machine parameters) UFO BLM + neighbours (losses + DCUM) Time-resolved data (capture buffer) Presented at the previous slides consecutive steps and applied conditions for F1 and F2 yield in a result to creating file F3, which contains necessary for the further steps -> basic informations, such as timestamp, fill number and machine parameters -> registered by BLMs losses for UFO BLM + it’s neighbours and selected BLMs localized in the collimators area F4 excel file (.csv) 10/10/2017 | Schematic overview of UFO Buster analysis tool Martyna Dziadosz

F2 F1 F2 INPUT Condition 1 Condition 2 Condition 3 Condition 4 STABLE beam mode verified UFO Condition 1 F2 for which matching F1 exist Condition 2 F2 losses > threshold (5 * 10-3) Condition 3 2 consecutive points fullfill cond3 Condition 4 10/10/2017 | Schematic overview of UFO Buster analysis tool Martyna Dziadosz

ü F4 DATA EXTRACTION Reduces data volume for quick analysis Step 1 excel file (.csv) Reduces data volume for quick analysis ü As F3 is created only for event fulfilling certain conditions, Data volume has been reduced, what allows for quick analysis 10/10/2017 | Schematic overview of UFO Buster analysis tool Martyna Dziadosz

F1 F2 2 WAYS OUTPUT: EXTRACT find the corresponding file type 2 .sdds ASCII file .sdds binary file EXTRACT DECONVERSION !!! JAVA 1) looking for F2 with the same timestamp and fillnumber 2) go to an appropriate path using fillnumber. Then look for the corresponding F2 using naming convention Fillnumber Timestamp UFO_BLM_Expert_name Dcum [] VerificationLevel beam_mode Expert Name Java objects: String[] header (1D matrix with BLMs names) Int[][] value (2D matrix with all BLMs signal losses) OUTPUT: List of files type F1 for which the exist the corresponding file type F2 07/12/2017 | Schematic overview of UFO Buster analysis tool Martyna Dziadosz

DATA EXTRACTION – (PM REST API) Step 1 DATA EXTRACTION – (PM REST API) Presented at the previous slides consecutive steps and applied conditions for F1 and F2 yield in a result to creating file F3, which contains necessary for the further steps -> basic informations, such as timestamp, fill number and machine parameters -> registered by BLMs losses for UFO BLM + it’s neighbours and selected BLMs localized in the collimators area 10/10/2017 | Schematic overview of UFO Buster analysis tool Martyna Dziadosz

Integrated losses of all UFOs per BLM ROMAN POT AREA Hot spots, where more than one UFO event occured during 2016 LHC-working time Those are mainly the roman pots area, where we can expect such an behaviour 10/10/2017 | Schematic overview of UFO Buster analysis tool Martyna Dziadosz

Appendix – F1 structure 07/12/2017 | Schematic overview of UFO Buster analysis tool Martyna Dziadosz

Appendix – F2 structure 07/12/2017 | Schematic overview of UFO Buster analysis tool Martyna Dziadosz