Oscillator-qubit generalized quantum signal processing for vibronic models: a case study of uracil cation
Jungsoo Hong, Seong Ho Kim, Seung Kyu Min, Joonsuk Huh
TL;DR
This work introduces oscillator–qubit generalized quantum signal processing (OQ-GQSP), a compiler that synthesizes arbitrary nonlinear bosonic phase gates for hybrid oscillator–qubit quantum processors and enables efficient simulation of anharmonic vibronic dynamics. By combining inverted unary electronic-state encoding, multi-controlled displacement gates for off-diagonal couplings, and OQ-GQSP for diagonal anharmonic potentials, the method preserves bosonic modes in their native space while incorporating complex potentials via Fourier/Laurent approximations. Numerical demonstrations on the uracil cation show accurate state preparation and nonadiabatic dynamics with controllable resource costs, highlighting advantages over fully discrete encodings and identifying trade-offs between circuit depth and shot overhead due to probabilistic success. The approach provides a constructive middle ground between analog and digital vibronic simulators, with potential extensions to multivariate QSP and hardware-aware error mitigation for near-term devices.
Abstract
Hybrid oscillator-qubit processors have recently demonstrated high-fidelity control of both continuous- and discrete-variable information processing. However, most of the quantum algorithms remain limited to homogeneous quantum architectures. Here, we present a compiler for hybrid oscillator-qubit processors, implementing state preparation and time evolution. In hybrid oscillator-qubit processors, this compiler invokes generalized quantum signal processing (GQSP) to constructively synthesize arbitrary bosonic phase gates with moderate circuit depth O(log(1/{\varepsilon})). The approximation cost is scaled by the Fourier bandwidth of the target bosonic phase, rather than by the degree of nonlinearity. Armed with GQSP, nonadiabatic molecular dynamics can be decomposed with arbitrary-phase potential propagators. Compared to fully discrete encodings, our approach avoids the overhead of truncating continuous variables, showing linear dependence on the number of vibration modes while trading success probability for circuit depth. We validate our method on the uracil cation, a canonical system whose accurate modeling requires anharmonic vibronic models, estimating the cost for state preparation and time evolution.
