Universal Quantum Computational Spectroscopy on a Quantum Chip

TL;DR

This paper introduces a universal quantum spectroscopy method that can analyze both static and dynamic quantum systems, validated on a silicon-photonic chip, revealing phenomena beyond traditional techniques.

Contribution

The work presents a novel, versatile quantum spectroscopy framework capable of handling open, driven, and complex quantum systems, surpassing existing quantum algorithms.

Findings

Successfully reconstructed spectra for diverse quantum systems.

Observed novel phenomena like parity-time symmetry breaking.

Demonstrated superior performance over existing quantum algorithms.

Abstract

Spectroscopy underpins modern scientific discovery across diverse disciplines. While experimental spectroscopy probes material properties through scattering or radiation measurements, computational spectroscopy combines theoretical models with experimental data to predict spectral properties, essential for advancements in physics, chemistry, and materials science. However, quantum systems present unique challenges for computational spectroscopy due to their inherent complexity, and current quantum algorithms remain largely limited to static and closed quantum systems. Here, we present and demonstrate a universal quantum computational spectroscopy framework that lifts these limitations. Through leveraging coherently controlled quantum dynamics, our method efficiently reconstructs the spectral information for both closed and open systems, furtherly for time-dependent driven systems. We experimentally validate this approach using a programmable silicon-photonic quantum processing chip, capable of high-fidelity time-evolution simulations. The versatility of our framework is demonstrated through spectroscopic computations for diverse quantum systems -- including spin systems, non-Hermitian systems, and quantum Floquet systems -- revealing novel phenomena such as parity-time symmetry breaking and topological holonomy that are inaccessible to conventional spectroscopy or quantum eigenstate algorithms. {Furthermore, systematic benchmarking of UQCS against existing quantum algorithms is numerically performed to demonstrate its unprecedented capabilities and superior performance. This work establishes a noise-robust and transformative paradigm for quantum spectral analysis.