The bound states of a weak attractive potential never come out of doing perturbation theory on free particle states. This is a quite general rule: if the perturbation commutes with a constant of the motion, A, of the unperturbed Hamiltonian, then matrix elements of the perturbation between eigenstates of A with different eigenvalues must vanish. This rule, an example of a selection rule, often simplifies the problem of selecting the correct linear combination of degenerate states with which to do the perturbation expansion. The Rayleigh-Schrodinger perturbation theory – yields rather complicated expressions for the change in the states in second order and beyond. There is a somewhat different form of the perturbation theory, due to Brillouin and Wigner that enables to see more clearly the structure of the perturbed states.
We study how thermal equilibrium states of infinite fermionic lattices respond to perturbations of the Hamiltonian. Our main result concerns extensive perturbations of a chosen KMS state. We show that exponential decay of correlations and exponential local indistinguishability under the extensive perturbation yield stretched-exponential decay of correlations for the perturbed state. Neither the initial nor the perturbed state is required to be unique, allowing stability to be studied in the presence of phase coexistence. Our approach uses Quantum Belief Propagation (QBP), which we establish directly on the underlying
C∗-algebra. Combining QBP with Lieb--Robinson bounds, we show implications between decay of correlations, the principle that local perturbations perturb locally, and local indistinguishability, closing the cycle for perturbations of the tracial state under the stated decay, support and uniformity assumptions. For extensive perturbations under uniform clustering conditions, we also obtain a differentiable path of local equilibrium expectations and bound their change linearly in the interaction norm of the perturbation.
This paper introduces a novel self-adaptive perturbation algorithm based on quantum state representation. Traditional perturbation methods often rely on manual parameter tuning, limiting their adaptability. This work proposes a quantum state-driven approach that automatically adjusts perturbation parameters based on the algorithm's output, resulting in enhanced perturbation effectiveness. We explore the application of quantum state analysis to achieve this adaptive control. The core mechanism involves encoding the input data into a quantum state and leveraging this state to dynamically adjust the perturbation parameters, providing a more robust and efficient approach to perturbing systems. The proposed algorithm demonstrates improved performance across a range of perturbation tasks, showcasing the potential of quantum state representation for adaptive control.