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Quantum computing promises to solve certain complex problems far
beyond the reach of today’s classical computers. However, quantum
systems are extremely sensitive to noise both random fluctuations
and systematic control errors which can quickly degrade their
performance. In this work, we develop a set of scalable tools to detect and suppress such errors across different types of quantum hardware, including superconducting qubits, trapped ions, and diamond-based nitrogen-vacancy (NV) centers. Our methods rely on
monitoring how quantum states evolve over time and identifying
signatures that reveal whether errors have occurred. We also uncover a
subtle error introduced by a commonly used error-mitigation strategy
and analyze its impact. Finally, we demonstrate a robust technique for accurately characterizing noise even in environments where memory effects (non-Markovianity) are present. Together, our results offer a practical and platform-independent approach for improving the
reliability of current and near-future quantum computers. |