7. Adiabatic Approximation
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Slowly varying Hamiltonians: system tracks instantaneous eigenstates.
The Adiabatic Theorem
If Hamiltonian changes slowly enough:
Then system initially in $|\psi_n(0)\rangle$ remains in $|\psi_n(t)\rangle$:
Instantaneous eigenstate with phase factor
Dynamic Phase
Accumulated phase from energy evolution:
Standard SchrΓΆdinger phase - same as for time-independent case
Geometric (Berry) Phase
Additional phase for cyclic evolution $\hat{H}(T) = \hat{H}(0)$:
Geometric phase - depends only on path in parameter space, not on rate
Total phase after cycle:
Adiabaticity Condition
Change must be slow compared to level spacing:
Transition amplitudes to other states remain negligible
Alternatively, characteristic time $\tau$ of change:
Example: Particle in Expanding Box
Box length increases slowly: $L(t)$
Instantaneous energy:
If expansion is adiabatic:
- Quantum number $n$ remains constant
- Energy decreases as $L^{-2}$
- Wave function adjusts: $\psi_n(x,t) = \sqrt{2/L(t)}\sin(n\pi x/L(t))$
Example: Spin in Rotating Field
Magnetic field $\vec{B}(t)$ rotates slowly
Hamiltonian:
If rotation is adiabatic:
- Spin remains aligned (or anti-aligned) with field
- Picks up geometric Berry phase
- For spin-1/2: $\gamma = \Omega(1 - \cos\theta)/2$ where $\Omega$ is solid angle traced
Landau-Zener Transitions
When levels approach crossing:
Transition probability (Landau-Zener formula):
Slow passage ($\alpha \to 0$): adiabatic, $P \to 0$
Fast passage ($\alpha \to \infty$): diabatic, $P \to 1$
Born-Oppenheimer Approximation
Molecular physics application:
- Nuclei move slowly ($m_n \gg m_e$)
- Electrons adjust instantaneously to nuclear positions
- Separate electronic and nuclear motion
Electronic Hamiltonian at fixed nuclear positions $\vec{R}$:
Nuclear motion on potential energy surface $E_{el}(\vec{R})$
Quantum Annealing
Computational method based on adiabatic evolution:
Step 1: Start with simple Hamiltonian $\hat{H}_0$ (easy ground state)
Step 2: Evolve adiabatically to problem Hamiltonian $\hat{H}_p$:
Step 3: System ends in ground state of $\hat{H}_p$ (solution)
Used in D-Wave quantum computers for optimization problems
Adiabatic Quantum Computation
Alternative to gate-based quantum computing:
- Encode problem in Hamiltonian
- Solution = ground state
- Adiabatic evolution finds solution
- Provably equivalent to gate model (with polynomial overhead)
Key challenge: maintaining adiabaticity while avoiding exponentially small gaps
Shortcuts to Adiabaticity
Modern techniques to speed up adiabatic processes:
- Counterdiabatic driving: Add compensating terms to Hamiltonian
- Optimal control: Design time-dependent parameters for fast transfer
- Transitionless driving: Engineer Hamiltonian to suppress transitions
Goal: achieve adiabatic-like results in shorter time
Applications
- Molecular dynamics: Born-Oppenheimer separation
- Cold atoms: State preparation in optical lattices
- Quantum computing: Adiabatic algorithms, quantum annealing
- Topological phases: Berry phase in band structure
- Quantum control: STIRAP (stimulated Raman adiabatic passage)
- Cosmology: Particle production in expanding universe