Particle & Nuclear Physics

Language Requirement(s): Python | Usage Requirements: Internet Connection

This website presents a series of activities that walk through the particle identification (PID) process, which aims to determine what particles interacted with the various detectors in particle physics experiments. These activities are designed for high school and early undergraduate students, and the only required knowledge is python, though high school level physics may be helpful as well.

Contributor: Ricky Dube, Indiana University - Bloomington

Language Requirement(s): Python | Usage Requirements: Internet Connection

Particle Physics Playground is a collection of Jupyter notebooks that guide students through analyses of real particle physics data from the CMS, BaBar, CLEO, and IceCube experiments. The provided data is in a simplified format that makes it extremely easy to work with, especially when combined with the functions provided by the particle_physics_simplified and h5hep packages.

Contributor: Ricky Dube, Indiana University - Bloomington

Language Requirement(s): None | Usage Requirements: Internet Connection

Using the community hub, you can search literature, authors, jobs, seminars, conferences, institutions, experiments, journals, and data relevant to the field of high energy physics. This resource is helpful to find articles relating to specific experiments and authors in high energy physics.

Contributor: Robert C. Laughlin, Indiana University - Bloomington

Language Requirement(s): None | Usage Requirements: Internet Connection

The NOvA live event display allows users to view charged particle tracks within the NOvA near and far detectors in real time. Updated every 15 seconds, view particle tracks from a top and side perspective of the detector, as well as time spectra.

Contributor: Hannah LeMoine, Indiana University - Bloomington

Usage Requirements: Internet connection for online database.

Used by physicists around the world, the Particle Data Group (PDG) maintains and publishes summary tables of particle masses, charges, full decay widths, decay modes, and more for fundamental and composite particles. Additionally the PDG contains tables for physical constants and reviews for the Standard Model, detectors, probability/ statistics, and major experimental results.

Contributor: Robert Laughlin, Indiana University - Bloomington

Language Requirement(s): C++, Python | Usage Requirements: A C++ compiler, installation of Geant4

MinGLE, a Mini Geant4 Learning Example, uses minimal C++ coding (less than 70 lines of code) to demonstrate the usage of 10 essential Geant4 components step by step. It is not tied to any specific experiment or third party library, making it a clean template to start your own Geant4 applications. More information can be found in the manuscript here.

Contributor: Prof. Jing Liu, University of South Dakota

Language Requirement(s): GitHub, Python | Usage Requirements: Python IDE, Git

Linear response theory is a well-established method for exploring excitations of many-body systems. The Quasiparticle Random-Phase Approximation (QRPA), in particular, provides a powerful microscopic framework but is limited by high computational costs. This work presents two complementary QRPA surrogate models that achieve 0.1%–1% accuracy while offering a six to seven order-of-magnitude speedup over state-of-the-art solvers. These emulators enable large-scale studies and Bayesian calibration of computationally expensive physics models. The associated GitHub for these models consists of emulators reflecting the methodologies described in here.

Contributor: Crystal Killian, Indiana University

A go-to hub for tutorials on almost every basic computationl skill you may need to analyze particle physics data or run simulations. Featuring tutorials on basic skills, such as navigating UNIX Shells in terminal, SSH, Python, etc., as well as advanced topics like pyhf, machine learning, and software engineering.

Contributor: Amelia Binau, Indiana University - Bloomington

Language Requirement(s): Python. Usage Requirements: Python-compatible IDE, Jupyter Notebooks, Internet Connection

This resource provides data, plots, and code for the experimental limits on axions, a dark matter candidate.

Contributor: Robert C. Laughlin, Indiana University - Bloomington

Language Requirement(s): Python. Usage Requirements: Python-compatible IDE, Jupyter Notebooks

One of my personal favorites. This fairly plug-and-play Python package allows the user to run popular hadronic collision event generators/simulations. What are possible outcomes of proton-proton collisions at a certain energy? Run PYTHIA 8.3, SIBYLL-2.3d, EPOS-LHC, QGSJet-III, and more without the cumbersome FORTRAN. Chromo's authors provide a variety of examples to play around with.

Contributor: Amelia Binau, Indiana University - Bloomington

Language Requirement(s): Various languages required for setup, requires a ROOT environment & use of XML files. Usage Requirements: ROOT environment, Terminal & Bash, XML files, some Python

Tailored mostly to modeling and analysis of neutrino oscillation for MicroBooNE and SBND experiments, PROfit is a fitting framework written mostly in C++ and executable using XML files. Check the associated GitHub's Wiki for instructions for use as well as tutotrials (including an XML tutorial).

Contributor: Anthony Kelly, Indiana University - Bloomington

Language Requirement(s): Primarily C++ and ROOT, dependent on use of Geant4 and a variety of event generators. Usage Requirements: ROOT environment, Terminal & Bash, ROOT & artROOT

LArSoft is a suite of software and simulation tools designed for analysis of liquid argon time projection chamber (LArTPC) data, including major neutrino experiments such as ICARUS, DUNE, and MicroBooNE. Its workflow is four-tiered: event generation, Geant4 simulation, detector propagation, and reconstruction. LArSoft is a complex system for intense neutrino data analysis that requires familiarity with many languages and data structures commonly used in neutrino particle physics and the Fermilab computational system, including artROOT files. It interfaces with other neutrino analysis and reconstruction software such as Pandora. The LArSoft Collaboration website offers a plethora of resources, though some of them may be restricted to Fermilab users only. Otherwise, it's completely free to use and well-documented!

Contributor: Amelia Binau, Indiana University - Bloomington

Language Requirement(s): Requires C++11 or 14 with compiler, Python 3, and CMake. Usage Requirements: Dependent on standard UNIX/Linux environments, relies on ROOT, Boost, and Eigen. Works offline.

Originally developed by the Higgs Physics Analysis Group (PAG), now widely used in CMS. Combine is a tool for making statistical analyses based on a model of expected observations plus a dataset. Such analyses include discovery of new particles and processes, measuring cross-sections, and setting limits on new physics. The package itself helps the user build statistical models of expected observations, run tests on the model and observed data, and then provides tools for validating/inspecting/understanding the model and the tests.

Contributor: Charlotte Knight, Imperial College London, Curator; Neil Ghugare, University of Florida, Writer

Language Requirement(s): Requires C++14/17 compiler and built-in compatability with NVIDIA CUDA C++ bindings. Option Python interface. Usage Requirements: Runs of Linux-based High-Performance Computing nodes or clusers. Requires ROOT 6, MPI/OpenMP for multi-core CPU setups, and a CUDA-compatible environment (NVIDIA GPUs) for accelerated production runs. Works offline.

A high-performance, Markov Chain Monte Carlo (MCMC) fitting framework developed for long-baseline neutrino oscillation experiments like T2K and Hyper-Kamiokande. This framework allows for using massive near- and far-detector datasets, which researchers can use to extract neutrino oscillation parameters and cross-section parameters.

Contributor: Charlotte Knight, Imperial College London, Curator; Neil Ghugare, University of Florida, Writer

Language Requirement(s): Requires C++14/17 with compiler via GCC 8+ or Clang 9+. Usage Requirements: Built using CMake, and requires ROOT 6 along with the jsoncpp and yaml-cpp libraries. Can be run on standard laptop hardware for mini-setups, though HPC resources are required for large-scale analyses. Works offline.

Stands for Generalized and Unified Neutrino Data Analysis Methods (GUNDAM). It is a suite of data analysis and fitting tools for neutrino physics experiments.

Contributor: Charlotte Knight, Imperial College London, Curator; Neil Ghugare, University of Florida, Writer

Language Requirement(s): Requires C++11/14 compiler. Usage Requirements: Built using CMake. Works completely offline across multiple operating systems. Can run on a single laptop CPU core or scale to supercomputers. Optionally relies on CLHEP or pre-downloaded Geant4-Data physics tables.

Geant4 is an open-source toolkit that helps create simulations of radiation through matter or the general passage of particles. The user can set up and simulate any kind of detector or radiatoin source, and then record the chosen output of physical quantites from source particles and other paticle interactions with a material or medium. Its uses are diverse, covering High Energy and Nuclear Physics (HEP/HENP), medical physics, space radiation and satellites, among others.

Contributor: Charlotte Knight, Imperial College London, Curator; Neil Ghugare, University of Florida, Writer

Language Requirement(s): Allows access to ROOT data files, but web-based interactive doesn't require any programming. Usage Requirements: Internet connection.

Arachne allows the user to browse a sample of the MINERνA experiment's neutrino events inside a clean, informative interactive. Users can use theinterfaceto explore histograms of energy and time spectra, as well of cross-sectional and three-dimensional displays of interaction tracks within the MINERνA detector. While some of the links are dead, additional ROOT files and documentation can be foundhereand onarXiv.

Contributor: Hannah LeMoine, Indiana University - Bloomington

Language Requirement(s): Anything compatible with HDF5 file formats. Usage Requirements: Internet connection, compiler compatible with relevant language.

Designed specifically for broad participation in MicroBooNE analysis, this dataset contains one million muon neutrino interactions and one hundred thousand electron neutrino events in the MicroBooNE liquid argon neutrino detector. As stated in this paper, these simulated data are the same as those used in many MicroBooNE physics analyses. These data are saved as HDF5 files for both the muon and electron neutrino samples.

Contributor: Amelia Binau, Indiana University - Bloomington

Language Requirement(s): Python, R or C++. Usage Requirements: Internet connection, compiler compatible with relevant language.

CERN, the European Organization for Nuclear Research, is the organization that oversees operations of the Large Hadron Collider (LHC). In 2013, they began to release data, software, and documentation from the various experiments at the LHC through the CERN Open Data Portal. This portal hosts data and software for physicists at every stage of their careers, which allow you to explore, visualize, and analyze data from the world's largest and highest energy particle collider.

Contributor: Ricky Dube, Indiana University - Bloomington

Language Requirement(s): Python, many files in ASCII format. Usage Requirements: Internet connection, compiler compatible with relevant language.

A compilation of all of the ICECUBE neutrino detector collaboration's open data outputs and corresponding publications. Many sets of open data come with example Jupyter notebooks or Python files. While the means of use & interpretation of data varies between publicized sets, many resources are provided and the organization of open sets of data chronologically allows for easy selection by relevant physics.

Contributor: Amelia Binau, Indiana University - Bloomington

Language Requirement(s): Python, Jupyter Notebooks. Usage Requirements: Internet connection, compiler compatible with relevant language.

The XENON collaboration has conducted a series of dark matter direct detection searches, many of which have open data corresponding to publications listed on their website. Much of this data is accessible through Zenodo or GitHub with Jupyter notebook templates for analyzing recoil spectra & statistical evaluation via signal fits. Some data are also formatted in .csv files.

Contributor: Amelia Binau, Indiana University - Bloomington