Peking University Quantum Chip Computes Spectroscopy for Open Quantum Systems

Researchers at Peking University have demonstrated a quantum chip capable of generalized quantum computational spectroscopy, published July 11, 2026, and moving beyond the limitations of previous quantum algorithms largely restricted to static and closed quantum systems. The team, led by Jianwei Wang (orcid. org/0000-0003-1313-9266), utilizes an ancilla-assisted Hadamard test quantum circuit to reconstruct the quantum autocorrelation function, enabling spectroscopic analysis of systems previously considered too complex to model. This new method is applicable to a broad range of quantum systems, including those that are open and subject to time-dependent forces, addressing a core challenge in fields like physics, chemistry, and materials science. The research establishes a noise-robust methodology for quantum spectral analysis and reveals novel phenomena inaccessible to conventional methods.

The team, led by Jianwei Wang, demonstrated a quantum chip capable of analyzing previously inaccessible open and time-dependent driven systems. This was achieved through reconstructing the quantum autocorrelation function, which relies on an ancilla-assisted Hadamard test quantum circuit, a specific methodology that allows for a more comprehensive analysis of quantum behavior. This versatility was demonstrated through spectroscopic computations revealing phenomena like parity-time symmetry breaking and topological holonomy, which are difficult to observe using conventional methods or existing quantum algorithms. The researchers leveraged arbitrary controlled quantum dynamics and an efficient classical noise-mitigation strategy on a programmable silicon-photonic quantum processing chip to achieve high-fidelity time-evolution simulations.

The silicon-photonics platform was specifically chosen for its capacity to perform high-fidelity time-evolution simulations, crucial for accurately modeling quantum dynamics. Beyond the hardware, the team integrated an efficient classical noise-mitigation strategy, addressing a persistent challenge in quantum computation. This is particularly important when simulating open and time-dependent driven quantum systems, which previously posed significant hurdles for spectral analysis. Funding for the project came from multiple sources, including the National Natural Science Foundation of China (grant nos. 12325410, 62235001, 11834010) and the Quantum Science and Technology-National Science and Technology Major Project (grant nos. 2021ZD0301500, 2024ZD0302401), highlighting the collaborative nature of this advancement.

These observations highlight the potential for uncovering new insights in physics, chemistry, and materials science, fields heavily reliant on understanding spectral properties. This work demonstrates a collaborative effort to push the boundaries of quantum computation and may lead to further advancements in these areas.