L2 ICFP

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Interfaces and manifolds

Many physical systems are governed by elastic manifolds embedded in a higher-dimensional medium. Typical examples include domain walls in ferromagnets, dislocations in crystals, vortex lines in superconductors, and propagating fronts.

We introduce the following notation:

  • d: internal dimension of the manifold
  • N: dimension of the displacement (or height) field
  • D: dimension of the embedding space

These satisfy D=d+N

Two important cases are:

  • Interfaces (N=1):

The configuration is described by a scalar height field h(r→,t), where r→∈ℝd is the internal coordinate.

  • Directed polymers (d=1):

The configuration is described by a vector function x→(t) embedded in D=1+N dimensions.

Remark. With this notation, a one-dimensional interface (d=1, N=1) can be viewed both as an interface and as a directed polymer.

In this lecture we focus on thermal interfaces.

Thermal interfaces: Langevin dynamics

We consider an interface at thermal equilibrium at temperature T. Two assumptions are made:

  • Overhangs and pinch-off are neglected, so h(r→,t) is single-valued.
  • The dynamics is overdamped; inertial effects are neglected.

The Langevin equation of motion reads ∂th(r→,t)=−μδEpotδh(r→,t)+η(r→,t).

Here μ is the mobility and η(r→,t) is a Gaussian thermal noise, with ⟨η(r→,t)⟩=0,⟨η(r→,t)η(r→′,t′)⟩=2dDδd(r→−r→′)δ(t−t′).

The diffusion constant is fixed by the Einstein relation D=μkBT.

In the following we set μ=kB=1.

Elastic energy and Edwards–Wilkinson equation

The elastic energy associated with surface tension can be written as Epot=ν∫ddr1+(∇h)2≃const.+ν2∫ddr(∇h)2, where ν is the stiffness.

Keeping only the lowest-order term in gradients, the equation of motion becomes the Edwards–Wilkinson (EW) equation: ∂th(r→,t)=ν∇2h(r→,t)+η(r→,t).

Symmetries and scaling invariance

The EW equation is invariant under global height shifts h(r→,t)→h(r→,t)+c. This symmetry forbids any local term depending on the absolute height and ensures the absence of a characteristic length scale, leading to scale invariance of the form h(br→,bzt)∼in lawbαh(r→,t), where z is the dynamical exponent and α the roughness exponent.

A simple dimensional analysis gives bα−z∂th=bα−2∇2h+b−d/2−z/2η.

From this one finds z=2,α=2−d2.

Thus the interface is rough for d<2 and marginal at d=2.

Solution in Fourier space

We now focus on a one-dimensional interface (d=1) of size L with periodic boundary conditions. We use the Fourier decomposition h^q(t)=1L∫0Ldxeiqxh(x,t),h(x,t)=∑qe−iqxh^q(t), with wavevectors q=2πnL,n=…,−1,0,1,…

For these discrete wavevectors, the Fourier modes satisfy the orthogonality relation ∫0Ldxei(q1+q2)x=Lδq1,−q2.

Assuming a spatially and temporally white noise, ⟨η(x,t)η(x′,t′)⟩=2Tδ(x−x′)δ(t−t′), one finds that the Fourier components of the noise satisfy ⟨ηq1(t′)ηq2(t)⟩=2TLδq1,−q2δ(t−t′).

With these definitions, the Edwards–Wilkinson equation becomes diagonal in Fourier space: ∂th^q(t)=−νq2h^q(t)+ηq(t).

The solution of this linear equation is h^q(t)=h^q(0)e−νq2t+∫0tdse−νq2(t−s)ηq(s).

Assuming a flat initial condition, h^q(0)=0, one finds ⟨h^q(t)h^−q(t)⟩={T(1−e−2νq2t)Lνq2,q≠0,2TLt,q=0.

The mode q=0 corresponds to the spatial average of the height, i.e.\ to the center-of-mass position of the interface. Its fluctuations grow diffusively, ⟨h^0(t)2⟩=2TLt, with a diffusion constant proportional to 1/L, reflecting the fact that the interface is composed of L degrees of freedom.

The modes with q≠0 describe internal fluctuations of the interface. The relaxation time of a mode of wavevector q scales as τq∼1νq2.

Since q has the dimension of an inverse length, this relaxation time suggests the existence of a growing dynamical length scale ℓ(t)∼t1/z,z=2, such that modes with wavelength smaller than ℓ(t) (i.e. q≫1/ℓ(t)) have already equilibrated, while at longer wavelengths the interface still retains memory of the initial flat condition. Form dimensional analysis, the equilibrium decay ∼1/(Lq2) is consistent with the roughness exponent α=1/2, as expected for the Edwards–Wilkinson universality class in one dimension.

Width of the interface

The squared width of the interface is defined as w2(t)=∫0LdrL[h(r,t)−∫0LdrLh(r,t)]2.

Using the Fourier decomposition and Parseval’s theorem, one finds w2(t)=∑q≠0|h^q(t)|2.

Taking the average over the thermal noise yields ⟨w2(t)⟩=TLν∑q≠01−e−2νq2tq2.

For periodic boundary conditions, with q=2πn/L, this can be rewritten as ⟨w2(t)⟩=TL2π2ν∑n=1∞1−e−8π2νtn2/L2n2.

Long-time behavior

At long times, t≫L2, all modes have relaxed and the exponential term can be neglected. One obtains ⟨w2(t)⟩∼TL2π2ν∑n=1∞1n2=TνL12.

Thus the width saturates at a value proportional to the system size.

Short-time behavior

At short times, t≪L2, the sum can be approximated by an integral. Replacing ∑n→L2π∫dq, one finds ⟨w2(t)⟩≃Tν∫0∞dq2π1−e−2νq2tq2.

Evaluating the integral gives ⟨w2(t)⟩∼T2tπν,t≪L2.