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Evaluating Analysis Description Language Concept as a First Introduction to Analysis in Particle Physics

The fifth edition of the 'Computing Applications in Particle Physics' school was held on 3-7 February 2020, at Istanbul University, Turkey. This particular edition focused on the processing of the (pseudo) data from the Large Hadron Collider collisions using an Analysis Description Language, namely CutLang. 24 undergraduate and 6 graduate students were initiated to collider data analysis during the school. After 3 days of lectures and exercises, the students were grouped into teams of 3 or 4 and each team was assigned a public analysis note from ATLAS or CMS experiments. After 1.5 days of independent study, each team was able to reproduce the assigned analysis using CutLang.


Introduction
The utilization of computational tools for doing research in particle and accelerator physics is an essential requirement and it is often omitted in the curricula of Turkish universities. Based on the experiences of the academics working in these two fields, the "Computing Applications in Accelerator and Particle Physics" school in Turkey (Turkish: HPFBU) was conceived in 2008 [1] as a one-intensive-week event for graduate students. It aimed to educate new generations of scientists through a very hands-on attitude, providing them with skills that are readily applicable, training them by compelling them to actually perform research tasks.
The school has evolved over the years, targeting different sections of the Turkish student pool and updating itself to keep in touch with the latest developments in the field. Its fifth iteration, focused on data analysis of the Large Hadron Collider (LHC) data, was held between 3-7 February 2020, and targeted mostly undergraduate students, along with a few embedded graduate students. To ease their task, especially for the pre-literate ones in terms of computer programming languages, and to separate the physics analysis algorithm from the computational part, it was decided to introduce the Analysis Description Language, ADL, [2] concept.
The ADL concept uses a plain text file containing blocks with a keyword-value structure. The blocks make clear the separation of analysis components such as object definitions, variable definitions, and event selections while the keywords specify analysis concepts and operations. The syntax includes mathematical and logical operations, comparison and optimization operators, reducers, four-vector algebra and common HEP-specific functions (e.g. ∆φ, ∆R, etc.). ADL files can refer to self-contained functions encapsulating variables with complex algorithms (e.g. M T 2 , aplanarity, etc.) or non-analytic variables (e.g. efficiency tables, machine learning discriminators, etc.).
Not having the necessity to write or compile code, combined with the simple, human-readable nature of ADL syntax makes it a practical construct for quickly performing phenomenological and educational analyses as the ones in the school.

Student Selection
Although the school had so far accepted graduate students only, this year, to test a new idea, participants were selected amongst the undergraduate students from physics and engineering departments of various universities.
About 132 applications were received and 24 undergraduate, 3 MSc and 3 PhD students were accepted after consideration of their GPAs, resumes, reference letters and their scores on a simple web-based quiz focusing on the very basics of particle physics. About one third of the students were affiliated with some engineering department. No prior computer, programming or operating system knowledge requirements were imposed during the selection process.

Logistics
The event took place in the main campus of Istanbul University, Astronomy and Spaces Sciences Department, Turkey. Istanbul University's participation to CERN related activities started in 1977. Currently, the university takes part in the ATLAS and CMS experiments through the members of the physics department.
The student dormitories of the university were allocated to participating students (including those who normally reside nearby) to allow the discussions and peer-to-peer education to continue up to as late as possible hours. The lectures were both recorded and broadcast live on the internet [3]. The computing exercises were conducted in the allocated computer room with 15 desktop machines. Students who wanted to use their own laptop computers were requested to have downloaded a virtual computer image and installed the Virtual Box host application [4] before attending the exercise sessions.

Lecture Contents
The lectures start with the basics of elementary particles and introduce the necessary physics and mathematics background for understanding the data analysis in particle physics. The relevant computer software used in the field are presented followed by some hands-on training on their utilization. Recently, utilization of dedicated analysis languages instead of general purpose languages (e.g. C++ or Python) is becoming popular as it allows physicists to become faster and more efficient in designing analyses. Using such a language, CutLang, object selection, object reconstruction and event selection concepts are shown through examples. The main goal is presented as being able to analyse the Monte Carlo pseudodata and real data from the LHC experiments (obtained through the open data initiative). Towards that goal, the statistical techniques used in particle physics are also presented.

Introduction to Analysis
This lecture starts from the basics of elementary particles and interactions. The most relevant concepts for experimental research are presented, such as the process cross sections and branching fractions. Particle detectors are then introduced as a means of observing known particles and searching for new particles. The concept of a particle jet is discussed at this stage. For understanding the particle collision concept, the kinematics variables and hard scattering are discussed in detail. At this stage, the invariant mass idea is presented with examples from Z and W bosons, which motivates the teaching of concepts such as transverse momentum, pseudorapidity and missing energy.

Analysis Structure
This lecture is envisaged as a practical approach to HEP analysis concepts. It starts with an overview of quantum field theory and Feynman diagrams to later cover quantum electrodynamics, quantum chromodynamics and weak interactions. Once a collision event is defined, the main steps of data analysis are presented: 1) to define a signal and to design a search channel, 2) to define a trigger for signal events (the trigger concept is introduced at this stage.), 3) to reconstruct new objects and eventually signal events, 4) to estimate the contribution from background events (the background concept is introduced at this stage.) 5) statistical analysis. The systematic uncertainties are also introduced to properly interpret the experimental results. Details of these concepts are left to the following lectures.

Introduction to ROOT
This lecture starts with an introduction to Linux and terminal commands. After all, a minimum command line literacy is needed to edit a file, to look at a histogram etc. The rest of the lecture introduces ROOT, its command line interface, simple calculations using the command line, graphics focusing on histograms and functions. These concepts are enforced through exercises executed with simple macros. Second part of the lecture brings more advanced concepts like error representation, histogram operations (normalization, scaling etc) and finally reading from and writing into the root files.

Introduction to CutLang: summary
This lecture covers a particular analysis description language (ADL) and its runtime interpreter. During the school, CutLang [1, 5], a runtime interpreter written in C++ and based on ROOT [6] classes for Lorentz vector operations and histogramming, was used. CutLang is able to operate directly on events without the need for compilation. It uses automatically generated dictionaries and grammar rules based on Unix tools Lex and Yacc [7]. The typical output of an analysis in CutLang is a file containing surviving events and histograms which can be used for statistical analysis. The lecture covers the basic steps of data analysis using examples and exercises executed using CutLang.

Introduction to Probabilities and Statistics
Probabilities and Poisson statistics were introduced via real life examples such as proton decay, German rocket hits to London during WWII, etc. Exercises were built on rudimentary use of previous knowledge (like the basic use of ROOT macros). Bayesian and frequentist statistical methods were discussed to introduce hypothesis testing. False positives and negatives were discussed together with χ 2 distribution for decision making within the context of particle physics analysis. Concepts like particle identification and limit setting were presented as relevant examples. Finally a simple limit setting software, TLimit from ROOT, was shown with a working example.

Particle Reconstruction
The first part of the lecture starts with the details of ATLAS and CMS detectors to focus on particle isolation, identification and reconstruction. Methods such as Particle Flow are discussed, as well as particle tracking and vertex identification. The performance of various LHC tracking detectors are compared and discussed. Accumulating on previous knowledge, muon and b-jet identification methods using track fitting and χ 2 minimisation are presented. Finally electromagnetic calorimeters are introduced within the context of electron, photon and tau reconstruction and identification. The second part of the lecture is solely dedicated to jet reconstruction. It aims to familiarize the student with the strong interactions, hadronic collisions and jet structure. To that end, it also reviews parton distribution functions and hard scattering. Details of jet reconstruction algorithms like cone, kT and antikT are presented. Finally sub-jets, jet-charge and jet energy calibration concepts are discussed.

Introduction to Systematic Uncertainties
After introducing the concept of uncertainties, accuracy and precision, the main uncertainty sources are discussed: detector simulation and reconstruction, event recording and trigger and HEP theory. Details of the experimental uncertainties are elaborated: detector calibration, efficiency, and resolution. Their impact is discussed from both physics and statistics point of views. The concept of nuisance parameter is introduced for simple application in frequentist and bayesian statistics. PDFs are presented as an example to theory uncertainties. Simple exercises are performed using ROOT's TLimit function to enforce learning.

BSM review
After a brief review of the shortcomings of the Standard Model, its four pillars are presented: the particle content, the forces, the symmetry group and the dimensions of space-time. Possible modifications for each of these four items are discussed as well as the possible solutions to the Standard Model's shortcomings. For each case, searches from the LHC experiments and the limits for various models together with important model parameters are shown. Finally future accelerators and research plans are summarized to motivate the students.

Presentation Tips
Some tips on how to present results, how to display data, and how to prepare clear slides are discussed. Examples from ugly and cumbersome slides are given to show what not to do. Emphasis is given to make the presentation short and not go overtime and to give one single message that the listeners should take home.

Short Exercises
This is a set of short but complete exercises to get used to ROOT file manipulation, ADL file writing, CutLang utilization and histogram interpretation.
The first example is the Drell-Yan process of pp → Z → e + e − . The final state is two opposite-sign "electrons". First, events are required to have at least two electron candidates, and then requirement for opposite-sign electric charge is applied. After each selection, a Z boson candidate is reconstructed from the two highest p T electrons, and its mass is plotted. The ADL file for this example is: As the second example, the Drell-Yan process of pp → Z → µ + µ − has been considered. The events are required to have at least two muons with the opposite-sign electric charge. After each selection, the Z candidate mass is plotted. The ADL file for this process is similar to the second example.
The third example is the Drell-Yan process of pp → Z → µ + µ − /e + e − . Since the final state is two opposite sign same flavour muons or electrons, events are categorised into the ee and µµ channels. At least two leptons are required to exist in the final state before the OS-SF criteria. The ADL file for this study can be written as: In the fourth example, the same Drell-Yan process of the previous example has been elaborated to specify "good" leptons. The leptons are defined as the union of electrons and muons. The good leptons are defined based on the cuts on their transverse momenta (p T > 25 GeV) and pseudorapidity (|η| < 2.5). The students are expected to use CutLang syntax to find the best lepton combination to reconstruct a Z-boson candidate and they plot its invariant mass to comment on the decay width and eventually production cross section.
As the fifth example, the pp → W → µν process has been studied. The neutrino in the final state is assumed to have been measured as the missing transverse energy (MET), which, combined with the charged lepton, is used to reconstruct the W -boson candidate. In this case, the Lorentz vector from MET, METLV, is defined as (M ET, M ET x , M ET y , 0). Afterwards, the p T of the muon and the W candidate mass are plotted. The ADL file for this example is: The sixth example is the process pp → W W → µνjj . The final state consisted of a muon, two jets and MET. Initially both leptonically and hadronically decaing W bosons are defined. The event selection starts with a requirement of at least one muon and sufficiently large MET (> 20 GeV). The events are also required to have at least two jets. Finally, the W boson candidate masses are obtained from the highest momentum physics objects and are plotted for both leptonic and hadronic cases separately. The ADL file for this exercise is: The last short example is the process pp → tt → W W bb → jjjjjj. The final state contains at least six jets. Events are required to have two hadronically reconstructed W bosons and two jets that can be identified as b-jets. Here, first the W s are defined from jets and then the optimal reconstruction is determined using a χ 2 algorithm based on the known mass of the W boson. Next, the top quarks are defined by pairing the reconstructed W bosons and jets. The best pairing is again found via a χ 2 algorithm without using the btagging. After all definitions, at least six jets are required. The MET in the event is expected to be small (< 100 GeV). Finally, the total χ 2 is minimized (χ 2 = 0) to plot the masses of the reconstructed objects. The ADL file for this example is given below:

Team analyses
During the last two days of the event, the students were grouped into teams of 3-4 students. Each group was assigned a particular ATLAS or CMS analysis and was expected to skim through the relevant publication and then write their own ADL files. The assigned analyses are listed below: 6. "Search for supersymmetry in multijet events with missing transverse momentum in proton-proton collisions at 13 TeV", arXiv:1704.07781.
7. "Search for supersymmetry in events with one lepton and multiple jets exploiting the angular correlation between the lepton and the missing transverse momentum in proton-proton collisions at √ s = 13 TeV", arXiv:1709.09814.
8. "Search for new physics in events with two soft oppositely charged leptons and missing transverse momentum in proton-proton collisions at √ s = 13 TeV", arXiv:1801.01846.

Generation of the Pseudo-data
Monte Carlo event samples used for performing the analyses in this school were either produced by the instructors or taken from the CERN LHC Open Data portal [8]. Signal samples used in the SUSY exercises were generated using Pythia8. Signal models, consisting of several gluino, top squark or EW gaugino pair production benchmarks were defined by SUSY Les Houches Accord files. Signal and SM background samples in dijet and dilepton resonances analyzes were also produced using Pythia8. Detector response for all signal samples was modelled with the Delphes detector simulator using the default ATLAS or CMS detector cards. Background samples including tt+jets, W +jets, etc were directly taken from the ATLAS open data.

Student Presentations
The students, after their independent analysis training, were expected to work as a team and prepare a short presentation. It is very important that each member of the team presents some aspect of the analysis, even with 2-3 slides. Public speaking and being able to defend the analysis algorithm or results in front of one's peers is an important part of HEP carrier.

An example analysis
Below is the final ADL file, for duplicating the analysis in the "Search for supersymmetry in events with one lepton and multiple jets" paper as written by group 7. It contains three sections: the first one defines new objects, the second defines new event variables, and finally the last section contains the selection algorithms for signal regions with and without b-jets.

Conclusions
On the whole, the school reached its goal of engaging the students in particle physics data analysis and they showed clear progress. The introductory level HEP data analysis, including the associated concepts of MC techniques and statistical methods is an appropriate topic to for junior and senior-level university students if the computer and programming technicalities can be surmounted. The utilization of the Analysis Description Language concept has helped greatly by bypassing the programming related difficulties especially for those that had never programmed before. Finally we would like to encourage other particle physicists to engage undergraduate students with similar schools and eventually use the presented material and the ADL concept to tailor their own activities to spread the knowledge about HEP analyses, and to contact us in case there are any questions.