An open-source quantum software package combines reusable algorithms, composable building blocks, and multiple execution backends to reduce development effort across quantum computing applications.
Fujitsu has released Open Quantum Application Research Package (OpenQARP), v0.1.0, an open-source quantum application development software package designed to simplify the implementation and testing of quantum algorithms. Released on September 15, 2026, the software is available under the Apache License 2.0 and is aimed at researchers and developers working on quantum applications.
OpenQARP provides more than 70 composable software building blocks and over 20 ready-to-run quantum algorithms. The components cover functions ranging from quantum state preparation and ansatz layers to the Quantum Fourier Transform. Developers can combine these blocks according to application requirements instead of implementing complete algorithms from scratch.
The key features are:
- Apache License 2.0 open-source distribution
- Python-based development environment
- 70+ reusable software building blocks
- 20+ pre-built quantum algorithms
- GitHub-based collaborative development
The package also incorporates Fujitsu-developed algorithms intended to improve the efficiency of quantum computations. These include the Unitary pair Coupled Cluster Doubles algorithm for reducing quantum circuit depth during initial-state preparation in quantum chemistry calculations, and Density of States Quantum Phase Estimation, which addresses the complexity of preparing input states for quantum phase estimation.
A key benefit is reduced programming effort. In Fujitsu’s quantum chemistry research, an implementation based on the ADAPT-VQE algorithm that previously required about 130 lines of Python code was reduced to fewer than 40 lines using OpenQARP components. This can allow researchers to spend more time evaluating algorithms and application results rather than building underlying software routines.
OpenQARP supports execution across different computing environments. It can run on standard Python-compatible PCs and can integrate with the NVIDIA CUDA-Q platform as a backend for GPU-accelerated quantum-classical computing. It is also compatible with Fujitsu’s 40-qubit state-vector quantum simulator, which operates on an HPC environment comprising 1,024 Fujitsu Supercomputer PRIMEHPC FX700 systems equipped with A64FX processors.
Potential applications include quantum chemistry, materials research, financial optimisation, healthcare, and drug discovery, where quantum algorithms are being explored for computationally intensive problems.
The software had previously been provided in beta form to more than 80 organisations through joint research activities and Fujitsu’s Quantum Simulator Challenge. Fujitsu plans to expand execution-environment support, including simulation environments based on its STAR architecture research.
