Quantum State Tomography (qtomos)

Quantum State Tomography is the process of completely characterizing the quantum state of a system by performing a series of measurements on identical copies of the state. It allows us to mathematically reconstruct the density matrix, which fully describes the system.

This toolset is specifically designed for SpinQ NMR quantum computers and has been successfully tested on the Triangulum (3-qubit) system.

Quantum State Tomography is generally a two-phase process:

1. Data Acquisition: Run quantum circuits on a simulator or real hardware to gather measurement statistics for a complete set of observables. In this toolset, we specifically use the complete set of tensor products of the non-identity Pauli matrices ($X, Y, Z$).
2. State Reconstruction: Use the acquired measurement data to mathematically reconstruct the density matrix of the quantum state.

Features

• Multi-backend support: Run acquisitions seamlessly on a simulator (sim) or directly on actual quantum hardware (qpu).
• Granular Control: Measure single observables (e.g., XX) or effortlessly execute an automated sequence covering all permutations for full tomographic reconstruction.
• Customizable Circuits: Dynamically load pre-defined state preparation circuits (GHZ, Phi+, W, Random) from the catalog or define your own.
• Structured JSON Output: Measurements are paired with timestamps, counts, runtime configurations, and the compiled QASM logic.

Quickstart

You can install qtomos directly from PyPI:

pip install qtomos

Documentation

Depending on your use case, refer to the following dedicated guides:

• 📖 CLI Usage Guide: Learn how to perform tomography directly from your terminal using the acquire command.
• 📓 Jupyter Notebook Guide: Learn how to import and use the programmatic APIs within Python scripts and Jupyter Notebooks.
• 🛠️ Developer Guide: Learn how to set up the repository for local development, run tests, and understand the project structure.