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This research presents a nearly optimal quantum algorithm for estimating Chern numbers, a critical topological invariant used to characterize phases of matter in many-body systems. By leveraging generalized quantum signal processing to coherently accumulate geometric phases, the study establishes provable quantum speedups and defines the computational complexity boundaries for these tasks within the BQP class. These findings provide concrete evidence for quantum advantage in characterizing complex quantum states beyond classical simulation capabilities.
Chern-number estimation: nearly optimal quantum algorithm and provable quantum speedup
arXiv:2609.35978v1 Announce Type: new Abstract: Topological phases of matter are characterized by global properties of quantum states beyond conventional local order parameters. The Chern number is a central invariant in this characterization, linking the geometry of quantum states to robust physical observables and making its determination key to understanding quantum matter. We construct a nearly optimal quantum algorithm for estimating the Chern number of a smooth Hamiltonian family over a two-dimensional parameter torus with a unique, gapped ground state, including interacting many-body systems. The algorithm transports and reuses two ground-state copies prepared at a single reference point and uses generalized quantum signal processing to coherently accumulate geometric phases. It achieves a Hamiltonian-oracle evolution time of $\tilde{O}(L_xL_y/\Delta_{\min}^3)$, where $L_x,L_y$ bound the parameter derivatives of the Hamiltonian and $\Delta_{\min}$ is a known spectral-gap lower bound. We prove a matching worst-case oracle lower bound, even when the Chern number is promised to be zero or one, establishing optimality up to polylogarithmic factors. For local Hamiltonian families with an inverse-polynomial gap and a supplied guiding state, exact Chern-number computation is in $\mathsf{FBQP}$ and is $\mathsf{BQP}$-hard, and merely deciding whether the Chern number is zero or one is already $\mathsf{BQP}$-complete. These results establish how efficiently quantum computers can estimate a quantized topological invariant and provide evidence for quantum advantage in characterizing topological phases.
Abstract:Topological phases of matter are characterized by global properties of quantum states beyond conventional local order parameters. The Chern number is a central invariant in this characterization, linking the geometry of quantum states to robust physical observables and making its determination key to understanding quantum matter. We construct a nearly optimal quantum algorithm for estimating the Chern number of a smooth Hamiltonian family over a two-dimensional parameter torus with a unique, gapped ground state, including interacting many-body systems. The algorithm transports and reuses two ground-state copies prepared at a single reference point and uses generalized quantum signal processing to coherently accumulate geometric phases. It achieves a Hamiltonian-oracle evolution time of $\tilde{O}(L_xL_y/\Delta_{\min}^3)$, where $L_x,L_y$ bound the parameter derivatives of the Hamiltonian and $\Delta_{\min}$ is a known spectral-gap lower bound. We prove a matching worst-case oracle lower bound, even when the Chern number is promised to be zero or one, establishing optimality up to polylogarithmic factors. For local Hamiltonian families with an inverse-polynomial gap and a supplied guiding state, exact Chern-number computation is in $\mathsf{FBQP}$ and is $\mathsf{BQP}$-hard, and merely deciding whether the Chern number is zero or one is already $\mathsf{BQP}$-complete. These results establish how efficiently quantum computers can estimate a quantized topological invariant and provide evidence for quantum advantage in characterizing topological phases.
arXiv:2609.35978 [quant-ph]
(or arXiv:2609.35978v1 [quant-ph] for this version)
https://doi.org/10.48550/arXiv.2609.35978 Focus to learn more arXiv-issued DOI via DataCite (pending registration)
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