Open Source Tools

Control Software

DAX is a library that extends the capabilities of ARTIQ while maintaining a vanilla ARTIQ experience. This project was initially created as a framework to develop modular control software for ARTIQ-based quantum control systems. As the project evolved, additional components and utilities were added to the repository. Users can implement modular control software for their ARTIQ projects using the DAX framework or use other components and utilities provided by DAX in existing projects.

Quantum Error Correction

PlanqTN

PlanqTN, hosted on github.com/planqtn/planqtn consists of the planqtn python library and the PlanqTN Studio (https://planqtn.com), an interactive studio to create, manipulate and analyze tensor network-based quantum error correcting codes.

The features are an implementation of the quantum LEGO framework by Charles Cao and Brad Lackey and the quantum LEGO expansion pack: enumerators from tensor networks by Cao, Gullans, Lackey and Wang, but we also integrate with features that automate tensor network contraction with Cotengra and take a unified approach to quantum LEGO, ZX-calculus and graph states.
The detailed documentation is hosted on planqtn.com/docs and including an up to date list of features.
Note: the name is a triple entendre on Planck, quantum and Tensor Networks (TN). It is pronounced "plankton", and was inspired by the fact that each of the little tensors look like a unique plankter. Also, while we love the quantum LEGO name, we did not want to get into trademark problems.

QUITS (Qldpc code circUIT Simulator)

QUITS is a modular and flexible circuit-level simulator for quantum low-density parity check (QLDPC) codes. Its design allows users to freely combine LDPC code constructions, syndrome extraction circuits, decoding algorithms, and noise models, enabling comprehensive and customizable studies of the performance of QLDPC codes under circuit-level noise. QUITS supports several leading QLDPC families, including hypergraph product codes, lifted product codes, and balanced product codes. See arXiv:2504.02673 for a detailed description.

Stochastic Noise Estimation for Detector Error Models

Code estimates detector error models under stochastic Pauli noise using syndromes from memory experiments. Examples include repetition code, surface code, and color code with bare ancilla syndrome extraction as well as repetition code with Steane syndrome extraction. The weights of decoding graphs are learned from averaging correlators of detectors <v_i> and <v_iv_j> across experimental shots. For decoding hypergraphs, given an m-th order hyperedge, we collect up to m-th order detector correlators which are used to estimate the hyperedge rates. For more details see arXiv:2504.20212

msim

The msim framework was developed and shared as part of a research project exploring the coherence in the logical channel of 2D compass codes. The project was used in this research arXiv:2405.09287

The package contains the following features:

implementation of a Majorana mode-based quantum error correction simulator by Bravyi, Engelbrecht, Konig, and Peard (arXiv:1710.02270 , npj Quantum Inf 4, 55 (2018) ) for the rotated surface code
generalization of the Majorana mode simulator to 2D compass codes
generator coefficient framework for CSS codes with k=1, d odd and even weight stabilizer groups
fast, Rust based implementation, allowing simulations up to distance 251 and optimal decoding under coherent noise - see https://ieeexplore.ieee.org/document/10821195/