The SpinPulse Library for the Transpilation and the Noise-Accurate Simulation of Spin Qubit Quantum Computers

We introduce SpinPulse, an open-source Python package for simulating spin qubit-based quantum computers at the pulse level. While previously available simulators are specific to neutral atoms or superconducting platforms, SpinPulse models the specific physics of spin qubits, particularly through the inclusion of non-Markovian noise, enabling realistic simulations of native gates and noise-accurate quantum circuits to support hardware development.

A key feature of our package is its parametrizable, sequential transpilation pipeline. A quantum circuit is first transpiled into the native gate set of our model and then converted to a pulse sequence. This pulse sequence is subsequently integrated numerically in the presence of a simulated noisy experimental environment, enabling the extraction of fidelity metrics for gates and quantum channels. Each step is accessible and customizable through a dedicated API equipped with graphical tools.

Provided examples demonstrate broad applicability and show that SpinPulse can act as a digital twin of spin qubit quantum computers. We showcase workflows including transpilation, pulse-level compilation, hardware benchmarking, quantum error mitigation, and large-scale simulations via integration with the tensor-network library Quimb. We expect SpinPulse to be a valuable open-source tool for the quantum computing community, fostering efforts to devise high-fidelity quantum circuits and improved strategies for quantum error mitigation and correction.