  Quantum computer simulation software is an integral tool for the research
efforts in the quantum computing community. An important aspect is the
efficiency of respective frameworks, especially for training variational
quantum algorithms. Focusing on the widely used Qiskit software environment, we
develop the qiskit-torch-module. It improves runtime performance by two orders
of magnitude over comparable libraries, while facilitating low-overhead
integration with existing codebases. Moreover, the framework provides advanced
tools for integrating quantum neural networks with PyTorch. The pipeline is
tailored for single-machine compute systems, which constitute a widely employed
setup in day-to-day research efforts.
