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High Energy Physics
ROOT v6.x
CERN Data Analysis Framework
ROOT is the central data analysis framework for high-energy physics, developed at CERN and used by virtually every major collider experiment in the world. It was built to handle petabyte-scale datasets from experiments like ATLAS and CMS at the LHC. ROOT provides histogramming, fitting, statistical tools, and a columnar data format (TTree/RNTuple) that has become the standard for HEP data storage.
ROOT provides pre-built binaries for Linux, macOS, and Windows, as well as Conda packages and Docker images. Visit the official install page to choose your platform.
Key Features
TTree / RNTuple
Columnar data storage format — the universal container for HEP event data, optimized for petabyte-scale I/O.
RDataFrame
Modern declarative interface for parallel, lazy analysis over TTrees with automatic multi-threading.
Histogramming & Fitting
Full suite of 1D/2D/3D histograms with built-in fitting using Minuit2.
Cling Interpreter
Interactive C++ interpreter lets you prototype analysis code without a compile/run loop.
PyROOT
Python bindings giving full access to all ROOT classes from Python, with NumPy/Pandas interop.
Statistical Tools
RooFit for likelihood models, RooStats for hypothesis testing, TMVA for multivariate analysis.
What It's Used For
- Analyzing collision data from the LHC experiments
- Fitting invariant mass spectra to extract particle properties
- Statistical hypothesis testing and limit setting
- Building and reading columnar HEP datasets (TTree, RNTuple)
- Fast C++ scripting via the Cling interpreter