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CRC Press eBooks

4 Proof of the Adiabatic Theorem

L.D. Faddeev, L.A. Khalfin, I.V. Komarov

Published May 21, 2004• 2 citations
Publisher

Abstract

In old quantum mechanics the adiabatic theorem established by Ehrenfest had the meaning that the quantized action variables J = n are invariant relative to an infinitely slow (adiabatic) change of a mechanical system.1 From this one can guess that if the system is in a state with definite quantum numbers before the adiabatic change started, then after the changes it will be characterized by the same quantum numbers.

DOI
10.1201/9780203643204-12

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The adiabatic theorem is a powerful result concerning the evolution of quantum mechanical systems. Intuitively, it states the following: suppose we want to study the evolution of a quantum mechanical system governed by a given Hamiltonian \(\mathcal H\) (Def. 6.1), and the initial state of the system is the eigenstate of \(\mathcal H\) corresponding to its lowest eigenvalue. The laws of quantum physics tell us that the evolution of the system over time follows the Schrüdinger equation, Eq. (6.1). Suppose now that the Hamiltonian is not fixed, but rather, it changes very slowly over time, so that the evolution of the system is described by the differential equation \(i\,\frac{\mathrm{d} | \psi(t) \rangle}{\mathrm{d}t} = \mathcal{H}(t) | \psi(t) \rangle\), and \(\mathcal{H}(t)\) is slowly changing. If, for any value of the time parameter \(t\), there is always a gap between the lowest eigenvalue of \(\mathcal{H}(t)\) and all other eigenvalues, then the adiabatic theorem asserts that the state of the system always remains in an eigenstate with the lowest eigenvalue throughout the evolution. One specific case of interest in this chapter occurs when the time-dependent Hamiltonian \(\mathcal{H}(t)\) varies from an initial (time-independent) Hamiltonian \(\mathcal{H}_{\mathrm{I}}\) to a final Hamiltonian \(\mathcal{H}_{\mathrm{F}}\). If the change happens slowly, and the initial state of the system is an eigenstate of \(\mathcal{H}_{\mathrm{I}}\) with minimum eigenvalue, the adiabatic theorem asserts that the evolution eventually leads to the eigenstate with minimum eigenvalue of the final Hamiltonian \(\mathcal{H}_{\mathrm{F}}\). This result can be used for optimization: imagine that the initial Hamiltonian encodes an easy problem for which we can construct the eigenstate with minimum eigenvalue, and the final Hamiltonian encodes a difficult optimization problem whose solution is given by the eigenstate with minimum eigenvalue. By the adiabatic theorem, evolving the eigenstate of the initial Hamiltonian while slowly changing the Hamiltonian into the final one leads to the solution of the difficult optimization problem. Of course we need to know how slowly \(\mathcal{H}_{\mathrm{I}}\) should be changed into \(\mathcal{H}_{\mathrm{F}}\). The adiabatic theorem is at the heart of the quantum approximate optimization algorithm (QAOA), a framework that has been widely used to implement optimization algorithms on existing quantum hardware, because it has low requirements of quantum resources–although it does not guarantee improvements over classical algorithms in general. In this chapter we first discuss the adiabatic theorem, and then give an overview of QAOA.

Society for Industrial and Applied Mathematics eBooks•Dec 17, 2025•0 citations
In old quantum mechanics the adiabatic theorem established by Ehrenfest had the meaning that the quantized action variables J = n are invariant relative to an infinitely slow (adiabatic) change of a mechanical system.1 From this one can guess that if the system is in a state with definite quantum numbers before the adiabatic change started, then after the changes it will be characterized by the same quantum numbers.
Abstract The postulate of the existence of stationary states in multiply periodic dynamical systems requires that if the condition of such a system, when quantised, is changed in any way by the application of an external field or by the alteration of one of the internal constraints, the new state of the system must also be correctly quantised. It follows that the laws of classical mechanics cannot in general be true, even approximately, during the transition. There is one kind, of change, however, during which one may expect the classical laws to hold, namely, the so-called adiabatic change, which takes place infinitely slowly and regularly, so that the system practically remains multiply periodic all the time. In this case the quantum numbers cannot change, and it should be possible to deduce from the classical laws that the quantum integrals remain invariant. This was attempted by Burgers, who showed that they are invariant provided there are no linear relations of the type Σrmrωr = 0 (1) between the frequencies ωr, of the system, where the mr are integers. In general, however, the frequencies will alter during the adiabatic change, and in so doing will pass through an infinity of values for which relations such as (1) hold. A closer investigation is therefore necessary, as was pointed out by Burgers himself. In the following work, conditions which are rigorously sufficient to ensure the invariance of the quantum integrals, are obtained in such a form that it is possible for one to see whether they are satisfied or not without having to integrate the equations of adiabatic motion.
We examine the development of the concept of parametric invariance in classical mechanics, quantum mechanics, statistical mechanics, and thermodynamics, and particularly its relation to entropy. The parametric invariance was used by Ehrenfest as a principle related to the quantization rules of the old quantum mechanics. It was also considered by Rayleigh in the determination of pressure caused by vibration, and the general approach we follow here is based on his. Specific calculation of invariants in classical and quantum mechanics are determined. The Hertz invariant, which is a volume in phase space, is extended to the case of a variable number of particles. We show that the slow parametric change leads to the adiabatic process, allowing the definition of entropy as a parametric invariance.
The quantum adiabatic theorem is a widely applied result in quantum mechanics. However, recently, counterexamples were produced, indicating that the transition probabilities in some systems do not converge as predicted by the adiabatic theorem [K. P. Marzlin and B. C. Sanders, Phys. Rev. Lett. 93, 160408 (2004)]. In this paper, we examine a proof of the adiabatic theorem, paying specific attention to the validity of the assumptions made in the proof. We show that the convergence of the transition probabilities is path dependent when the change in the Hamiltonian is large. Finally, we consider the application of this reformulated form of the adiabatic theorem to the adiabatic evolution paradigm in quantum computation.
We formulate the theory of shortcuts to adiabaticity in classical mechanics. For a reference Hamiltonian, the counterdiabatic term is constructed from the dispersionless Korteweg-de Vries (KdV) hierarchy. Then the adiabatic theorem holds exactly for an arbitrary choice of time-dependent parameters. We use the Hamilton-Jacobi theory to define the generalized action. The action is independent of the history of the parameters and is directly related to the adiabatic invariant. The dispersionless KdV hierarchy is obtained from the classical limit of the KdV hierarchy for the quantum shortcuts to adiabaticity. This correspondence suggests some relation between the quantum and classical adiabatic theorems.
The adiabatic theorem is a powerful result concerning the evolution of quantum mechanical systems. Intuitively, it states the following: suppose we want to study the evolution of a quantum mechanical system governed by a given Hamiltonian H\mathcal HH (Def. 6.1), and the initial state of the system is the eigenstate of H\mathcal HH corresponding to its lowest eigenvalue. The laws of quantum physics tell us that the evolution of the system over time follows the Schrüdinger equation, Eq. (6.1). Suppose now that the Hamiltonian is not fixed, but rather, it changes very slowly over time, so that the evolution of the system is described by the differential equation i d∣ψ(t)⟩dt=H(t)∣ψ(t)⟩i\,\frac{\mathrm{d} | \psi(t) \rangle}{\mathrm{d}t} = \mathcal{H}(t) | \psi(t) \rangleidtd∣ψ(t)⟩​=H(t)∣ψ(t)⟩, and H(t)\mathcal{H}(t)H(t) is slowly changing. If, for any value of the time parameter ttt, there is always a gap between the lowest eigenvalue of H(t)\mathcal{H}(t)H(t) and all other eigenvalues, then the adiabatic theorem asserts that the state of the system always remains in an eigenstate with the lowest eigenvalue throughout the evolution. One specific case of interest in this chapter occurs when the time-dependent Hamiltonian H(t)\mathcal{H}(t)H(t) varies from an initial (time-independent) Hamiltonian HI\mathcal{H}_{\mathrm{I}}HI​ to a final Hamiltonian HF\mathcal{H}_{\mathrm{F}}HF​. If the change happens slowly, and the initial state of the system is an eigenstate of HI\mathcal{H}_{\mathrm{I}}HI​ with minimum eigenvalue, the adiabatic theorem asserts that the evolution eventually leads to the eigenstate with minimum eigenvalue of the final Hamiltonian HF\mathcal{H}_{\mathrm{F}}HF​. This result can be used for optimization: imagine that the initial Hamiltonian encodes an easy problem for which we can construct the eigenstate with minimum eigenvalue, and the final Hamiltonian encodes a difficult optimization problem whose solution is given by the eigenstate with minimum eigenvalue. By the adiabatic theorem, evolving the eigenstate of the initial Hamiltonian while slowly changing the Hamiltonian into the final one leads to the solution of the difficult optimization problem. Of course we need to know how slowly HI\mathcal{H}_{\mathrm{I}}HI​ should be changed into HF\mathcal{H}_{\mathrm{F}}HF​. The adiabatic theorem is at the heart of the quantum approximate optimization algorithm (QAOA), a framework that has been widely used to implement optimization algorithms on existing quantum hardware, because it has low requirements of quantum resources–although it does not guarantee improvements over classical algorithms in general. In this chapter we first discuss the adiabatic theorem, and then give an overview of QAOA.