Welcome to Qdislib!

Qdislib is a Python library designed for scalable quantum circuit execution using circuit cutting techniques. It enables the simulation of large quantum circuits by splitting them into smaller, manageable subcircuits that can be executed independently—either on classical simulators, GPUs, or quantum hardware.

Qdislib is built on top of the PyCOMPSs parallel runtime, allowing seamless distributed execution of quantum workloads across CPUs, GPUs, and QPUs.

With Qdislib, researchers and developers can:

• Perform gate and wire cutting to decompose complex quantum circuits.

• Leverage GPU acceleration using Qiskit Aer, cuQuantum or Qibojit.

• Submit subcircuits to remote QPUs like IBM Quantum.

• Work with circuits defined in both Qibo and Qiskit.

• Automatically identify good cut points with find_cut.

• Extract and manipulate subcircuits independently.

Whether you’re targeting HPC systems, hybrid quantum-classical setups, or constrained simulators, Qdislib is a flexible and modular tool to bridge the gap between current hardware limitations and large-scale quantum algorithm design.

Explore the sections below to get started with installation, quickstart examples, user guides, API references, and more.

Qdislib has been implemented on top of PyCOMPSs programming model, and it is being developed by the Workflows and Distributed Computing group of the Barcelona Supercomputing Center.

Start with our notebooks!

📓 Qdislib Example Notebook with PyCOMPSs

📓 Qdislib Hello World! Serial Mode

📓 Qdislib with IBM Quantum Cloud

Documentation

• Quickstart

• User guide

• API Reference

• Modules

• Examples

• Development

• Glossary

Contents:

• API Reference
  • Qdislib.api: Quantum Distributed Library API
  • Qdislib.core.cutting_algorithms: Circuit Cutting
  • Qdislib.core.graph_algorithms: Graph Algorithms
  • Qdislib.core.find_cut: Find Cut Circuit Cutting
  • Qdislib.core.qubit_mapping: Circuit mapping to Quantum chip architecture
  • Qdislib.utils: Utility functions
• Developer’s guide
  • Contributing
  • Drafting new releases
• Examples
  • 📓 Qdislib Example Notebook with PyCOMPSs
  • 📓 Qdislib Hello World! Serial Mode
  • 📓 Qdislib with IBM Quantum Cloud
• Glossary of terms
• Qdislib
  • Qdislib package
• Quickstart guide
  • Manual installation
• User guide
  • Example
  • How to run Qdislib
  • Algorithms
  • Resource Allocation
  • Using GPUs

Source code

The source code of Qdislib is available online at Github.

Support

If you have questions or issues about the Qdislib you can join us in Slack.

Alternatively, you can send us an e-mail to support-compss@bsc.es.

Citing dislib

If you use Qdislib in a scientific publication, we would appreciate citations to the following paper:

M. Tejedor, B. Casas, J. Conejero, A. Cervera-Lierta and R. M. Badia, “Distributed Quantum Circuit Cutting for Hybrid Quantum-Classical High-Performance Computing” in https://arxiv.org/abs/2505.01184, 2025, pp. 1-12

Bibtex

@inproceedings{Qdislib,
            title       = {{Distributed Quantum Circuit Cutting for Hybrid Quantum-Classical High-Performance Computing}},
            author      = {Mar Tejedor and Berta Cervera and Javier Conejero and Alba Cervera-Lierta and Rosa M. Badia},
            booktitle   = {https://arxiv.org/abs/2505.01184},
            pages       = {1-12},
            year        = {2025},
 }

Indices and tables

• Index

• Module Index

• Search Page