Quantum programs provide exponential speedups compared to classical programs in certain areas, But they also inevitably encounter logical faults. Automatically repairing quantum programs is much more challenging than repairing classical programs due to the non-replicability of data, the vast search space of program inputs, and the new programming paradigm. Existing works based on semantic-based or learning-based program repair techniques are fundamentally limited in repairing efficiency and effectiveness. In this work, we propose HornBro, the first work that reduces the exponential overhead of the automated quantum repair to a polynomial complexity. The key insight of HornBro lies in the homotopy-like method, which iteratively switches between the classical part and the quantum part. This approach allows the repair tasks to be efficiently offloaded to the most suitable platforms, enabling a progressive convergence toward the correct program. We start by designing an implication assertion pragma to enable rigorous specifications of quantum program behavior, which helps to automatically generate a quantum test suite. This suite leverages the orthonormal bases of quantum programs to accommodate different encoding schemes. Given a fixed number of test cases, it allows the maximum input coverage of potential counter-example candidates. Then, we develop a Clifford approximation method with SMT-based search to transform the fault localization program into a symbolic reasoning problem. Finally, we offload the computationally intensive repair of gate parameters to quantum hardware by leveraging the differentiability of quantum gates. Experiments suggest that HornBro increases the repair success rate by more than 62.5% compared to the existing repair techniques, supporting more types of quantum bugs. It also achieves 35.7$\times$ speedup in the repair and 99.9% gate reduction of the patch.