One-Shot Structured Pruning of Quantum Neural Networks via $q$-Group Engineering and Quantum Geometric Metrics

This article likely presents a novel method for optimizing quantum neural networks. The title suggests a focus on pruning (removing unnecessary components) to improve efficiency, using mathematical tools like q-group engineering and quantum geometric metrics. The 'one-shot' aspect implies a streamlined pruning process.

• •Focuses on optimizing quantum neural networks.
• •Employs structured pruning techniques.
• •Utilizes q-group engineering and quantum geometric metrics.
• •Suggests a streamlined, 'one-shot' pruning approach.