- The paper establishes that a qubit’s Krylov-complexity frequency is ν = h − 2γ_B/T, combining the dynamical field strength with a Berry-phase contribution for closed adiabatic loops.
- The paper shows that nontrivial complexity requires a superposition of instantaneous energy eigenstates, producing a two-dimensional Krylov space, while an eigenstate reference makes the complexity vanish.
- The paper derives K(t) = sin²α sin²([h + φ̇(1 − cosθ)]t/2) for constant parameters and identifies quasi-periodic behavior under selected time-dependent drives, while leaving higher-dimensional and nonunitary cases open.
Summary of the paper
This paper establishes a quantitative connection between Krylov (spread) complexity and the geometric Berry phase in adiabatic quantum dynamics. Working within the (t,t′) formalism for time-dependent Hamiltonians (2608.14325), the authors analyze a single spin system with Hamiltonian H^(t)=h(t)S^⋅n(t) and show that the oscillation frequency of Krylov complexity in a single qubit is ν=h+Ω/T=h−2γB/T, where Ω is the solid angle traced by the field direction and γB the Berry phase. To the authors' knowledge, the dependence of Krylov-complexity dynamics on a geometric phase had not been previously identified.
Krylov complexity in adiabatic dynamics
The central observation concerns the choice of the initial Krylov basis. If the initial basis state is taken to be an instantaneous eigenstate ∣m(t)⟩ of H^(t), the generator (H^(t)−i∂t) annihilates the subspace beyond ∣K0⟩: one finds b1=0, the Krylov space is trivially one-dimensional, and the spread complexity vanishes identically. This reflects the absence of inter-level transitions in adiabatic evolution. The paper's key move is to instead choose a time-dependent superposition of two instantaneous eigenstates,
H^(t)=h(t)S^⋅n(t)0
with H^(t)=h(t)S^⋅n(t)1. The Lanczos recursion then terminates at H^(t)=h(t)S^⋅n(t)2, yielding a two-dimensional Krylov subspace with nontrivial coefficients H^(t)=h(t)S^⋅n(t)3 that depend explicitly on the Berry connections H^(t)=h(t)S^⋅n(t)4 and H^(t)=h(t)S^⋅n(t)5, the mixing angle H^(t)=h(t)S^⋅n(t)6, and its derivatives. This is the structural result on which all subsequent dynamics rests: adiabaticity does not force Krylov complexity to vanish once the reference state is not an energy eigenstate.
Dynamical regimes of the qubit
For a spin-H^(t)=h(t)S^⋅n(t)7 system, the time evolution of H^(t)=h(t)S^⋅n(t)8 exhibits qualitatively distinct behavior depending on the control parameters. With constant parameters (constant H^(t)=h(t)S^⋅n(t)9, ν=h+Ω/T=h−2γB/T0, ν=h+Ω/T=h−2γB/T1, ν=h+Ω/T=h−2γB/T2, and constant angular velocity ν=h+Ω/T=h−2γB/T3), the complexity oscillates harmonically. Numerically, making ν=h+Ω/T=h−2γB/T4 or ν=h+Ω/T=h−2γB/T5 produces progressively denser oscillations, indicating that ν=h+Ω/T=h−2γB/T6 and ν=h+Ω/T=h−2γB/T7 enter the frequency on an equal footing — a fact confirmed analytically below. A linear-in-time ν=h+Ω/T=h−2γB/T8 destroys periodicity and renders the evolution quasi-periodic, whereas a linear ν=h+Ω/T=h−2γB/T9 preserves the periodic behavior. These regimes are consistent with the general expectation that autonomous systems support periodic Krylov dynamics while time-dependent parameters induce quasi-periodicity.
To solve the dynamics analytically, the authors remove the diagonal Lanczos coefficients via the phase redefinition Ω0 and work in the Heisenberg picture. After rescaling, the operators Ω1, Ω2, Ω3 close an exact Ω4 algebra, reducing the Heisenberg equations to a linear system with frequency Ω5, where Ω6. For constant parameters the solution yields the closed form
Ω7
which matches the numerics exactly in the constant-parameter case. The oscillation frequency is therefore
Ω8
When the field precesses at constant polar angle Ω9 through a closed loop of period γB0, the second term becomes the solid angle per period, γB1, and since γB2 for a spin-γB3,
γB4
The γB5-dependent part is directly analogous to Larmor precession; the additive geometric contribution γB6 is the paper's principal new result. Two implications follow immediately. First, Krylov complexity provides a dynamical probe of a topologically invariant quantity: the oscillation frequency encodes the Berry curvature flux through the loop in parameter space. Second, the frequency is measurable in principle through the complexity dynamics, suggesting a route to geometric-phase detection via state-spreading observables. It should be noted that the analytic formula holds only for constant control parameters; the periodic and quasi-periodic regimes with time-dependent γB7, γB8, γB9, or ∣m(t)⟩0 are characterized only numerically.
Limitations and open questions
The construction is restricted to two-dimensional Krylov subspaces generated by a two-level superposition; the authors do not address whether analogous Berry-phase signatures survive in higher-spin systems or in multi-dimensional Krylov spaces where the recursion does not terminate at ∣m(t)⟩1. The analytic frequency relation relies on constant parameters, so its robustness under slow but non-constant driving — where the adiabatic theorem itself requires careful control of nonadiabatic corrections — remains open. The paper also leaves the extension to other geometric-phase settings, notably the Aharonov–Bohm effect, explicitly to future work, and does not examine whether the ∣m(t)⟩2-dependent frequency shift survives in open or nonunitary adiabatic dynamics.
Conclusion
This work demonstrates that Krylov complexity in adiabatic spin dynamics is nontrivial precisely when the Krylov basis is a superposition rather than an eigenstate, and that for a driven qubit the complexity oscillates harmonically with a frequency containing an explicit Berry-phase contribution, ∣m(t)⟩3. The result ties a state-spreading diagnostic to a geometric, topology-dependent phase within an exactly solvable two-dimensional Krylov subspace, and identifies the conditions — constant parameters, closed loops in parameter space — under which the relation holds exactly.