About
Qrisp is a high-level quantum programming framework that allows for intuitive development of quantum algorithms. It provides a rich set of tools and abstractions to make quantum computing more accessible to developers and researchers. By automating many steps one usually encounters when programming a quantum computer, introducing quantum types, and many more features Qrisp makes quantum programming more user-friendly yet stays performant when it comes to compiling programs to the circuit level.
Features
- Intuitive quantum program design
- High-level quantum programming
- Efficient quantum algorithm implementation
- Extensive documentation and examples
Installation
You can install Qrisp using pip:
pip install qrisp
Qrisp has been confirmed to work with Python version 3.11 & 3.12.
Qrisp is compatible with any QASM-capable quantum backend! In particular, it offers convenient interfaces for using IBM, IQM and AQT quantum computers, and any quantum backend provider is invited to reach out for a tight integration!
If you want to work with IQM quantum computers as a backend, you need to install additional dependencies using
pip install qrisp[iqm]
Documentation
The full documentation, alongside with many tutorials and examples, is available under Qrisp Documentation.
Shor's Algorithm with Qrisp
Shor's algorithm is among the most famous quantum algorithm since it provides a provably exponential speed-up for a practically relevant problem: Facotrizing integers. This is an important application because much of modern cryptography is based on RSA, which heavily relies on integer factorization being insurmountable.
Despite this importance, the amount of software that is actually able to compile the algorithm to the circuit level is extremely limited. This is because a key operation within the algorithm (modular in-place multiplication) is difficult to implement and has strong requirements for the underlying compiler. These problems highlight how the Qrisp programming-model delivers significant advantages to quantum programmers because the quantum part of the algorithm can be expressend within a few lines of code:
from qrisp import QuantumFloat, QuantumModulus, h, QFT, control
def find_order(a, N):
qg = QuantumModulus(N)
qg[:] = 1
qpe_res = QuantumFloat(2*qg.size + 1, exponent = -(2*qg.size + 1))
h(qpe_res)
for i in range(len(qpe_res)):
with control(qpe_res[i]):
qg *= a
a = (a*a)%N
QFT(qpe_res, inv = True)
return qpe_res.get_measurement()
To find out how this can be used to break encryption be sure to check the tutorial.
Qrisp offers much more than just factoring! More examples, like simulating molecules at the quantum level or how to solve the Travelling Salesman Problem, can be found here.
Feedback and Contact
If you have comments, questions or love letters, here is how you can engange with the Qrisp Community and Developers:
- Join the Discussions on Discord.
- Join the bi-weekly Developer Call.
- Ask a question, request a new feature and file a bug with GitHub issues.
- Vote on existing GitHub issues by reacting with a 👍. We regularly check issues with votes!
- Star the repository to show your support.
Authors and Citation
Qrisp is the work of many people.
If you want to cite Qrisp in your work, please use:
@misc{seidel2024qrisp,
title={Qrisp: A Framework for Compilable High-Level Programming of Gate-Based Quantum Computers},
author={Raphael Seidel and Sebastian Bock and René Zander and Matic Petrič and Niklas Steinmann and Nikolay Tcholtchev and Manfred Hauswirth},
year={2024},
eprint={2406.14792},
archivePrefix={arXiv},
primaryClass={quant-ph},
url={https://arxiv.org/abs/2406.14792},
}