Overview

CERN ROOT is a data analysis framework widely used in particle physics and high-energy physics experiments. Installing ROOT on Windows can sometimes be confusing for beginners(I spent hours to download and install it for my first time), so this guide summarizes two working installation methods to make it easier:

  1. Precompiled Windows Binary (recommended for beginners)
  2. Conda Installation (recommended for scientific Python workflows)

Both methods are explained below.

Table of Contents

  1. Overview
  2. Method 1 — Install Using the Official Windows Binary
  3. Method 2 — Install Using Conda
  4. Method Comparison
  5. Typical ROOT Workflow
  6. Example ROOT Script
  7. Installation Test
  8. Common Issues
  9. Using CERN ROOT with Jupyter Notebook
  10. Useful ROOT Resources

Method 1 — Install Using the Official Windows Binary

(Recommended for beginners, I personally use this)

1. Download ROOT

Go to the official ROOT download page:

https://root.cern/download

Look for a Windows installer with a name similar to:

root_v6.xx.xx.win64.pythonXXX.vcXX.exe

Example:

root_v6.36.08.win64.python311.vc17.exe

Download the .exe file.

2. Install Visual Studio (Required)

Before installing ROOT, install Visual Studio Community.

During installation select:

Desktop development with C++

ROOT depends on the Microsoft C++ compiler provided by this package.

Download Visual Studio here:

https://visualstudio.microsoft.com/

3. Install ROOT

Run the .exe installer you downloaded.

Install ROOT to a simple directory such as:

C:\root

Avoid installing into directories with spaces in the path.

4. Initialize ROOT

Open:

Visual Studio Developer Command Prompt

Run:

C:\root\bin\thisroot.bat

This script sets the environment variables required for ROOT.

5. Start ROOT

Run:

root

You should see something like:

Welcome to ROOT 6.xx
root [0]

This means ROOT has started successfully.

6. Test the Installation

Inside the ROOT prompt run:

TBrowser b;

A graphical ROOT browser window should open.

If it does, the installation is working correctly.

Method 2 — Install Using Conda

(Often easier for students already using Python or Jupyter)

ROOT can also be installed using Conda from the conda-forge repository.

1. Install Conda

Install either:

  • Anaconda
    or
  • Miniconda

https://www.anaconda.com/download

2. Configure Conda

Open Anaconda Prompt and run:

conda config --set channel_priority strict
conda config --set solver libmamba

3. Create a ROOT Environment

conda create -n root_env -c conda-forge root

4. Activate the Environment

conda activate root_env

5. Start ROOT

root

Method Comparison

Method Advantages When to Use
Windows Binary Most stable Beginners
Conda Easy integration with Python and Jupyter Data analysis workflows

Typical ROOT Workflow

Most physicists use ROOT in one of these ways.

Interactive ROOT

root

Run ROOT scripts

root myscript.C

Python + ROOT

ROOT also provides Python bindings commonly used with Jupyter notebooks.

Example ROOT Script

Create a file called hello.C

#include <iostream>

void hello() {
    std::cout << "Hello ROOT!" << std::endl;
}

Run it with:

root hello.C

Installation Test

To confirm everything works correctly:

root

Then run:

TBrowser b;

A ROOT graphical browser should appear.

Common Issues

ROOT command not recognized

Run the environment setup again:

C:\root\bin\thisroot.bat

Note:
If ROOT is installed using the Windows binary method, you may need to run this command every time you open a new terminal.

Visual Studio not installed

ROOT requires the Microsoft C++ compiler.

Install Desktop development with C++ in Visual Studio.

Using CERN ROOT with Jupyter Notebook

Many physicists prefer to use ROOT inside Jupyter Notebook because it allows combining:

  • C++ or Python analysis code
  • plots
  • documentation
  • data visualization

This workflow is commonly used in research environments and physics labs.

Method 1 — Python + ROOT (Recommended)

The easiest way to use ROOT with Jupyter is through PyROOT, which allows Python to call ROOT libraries.

Install ROOT with Conda

conda create -n root_env -c conda-forge root

Activate the environment:

conda activate root_env

Install Jupyter

If Jupyter is not installed:

conda install jupyter

Launch Jupyter

jupyter notebook

or

jupyter lab

A browser window will open.

Test ROOT in Python

Create a notebook and run:

import ROOT

h = ROOT.TH1F("h","Example Histogram",100,-4,4)

for i in range(10000):
    h.Fill(ROOT.gRandom.Gaus())

c = ROOT.TCanvas()
h.Draw()
c.Draw()

You should see a histogram generated by ROOT.

Method 2 — C++ ROOT Kernel for Jupyter (Optional)

ROOT also supports running C++ directly inside Jupyter using the ROOT interpreter.

Run:

root --notebook

ROOT will register its kernel with Jupyter.

After this you will see a ROOT C++ kernel option when creating a new notebook.

Example ROOT Notebook Code

TH1F h("h","Gaussian",100,-4,4);

for(int i=0;i<10000;i++)
{
    h.Fill(gRandom->Gaus());
}

h.Draw();

Useful ROOT Resources

Official installation page:

https://root.cern/install

ROOT download page:

https://root.cern/download

ROOT documentation:

https://root.cern/doc