Numerical Integration of Langevin Equation

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Can anyone explain to me why the gaussian white noise term is multiplied by the square root of the time differential when we turn the Langevin differential equation into a finite difference equation for the purposes of integration?

http://pre.aps.org/pdf/PRE/v50/i6/p4404_1

The step I don't understand is the change in the last term in going from equation 3 to 4.

Any help would be greatly appreciated, thanks!
 
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equation 3:
Stochastic partial differential equation: d rho(i,t)/dt = a rho(i,t) - b rho^2 + D times the discrete Laplacian of rho, plus noise term eta(i,t).


equation 4:
Discrete-time stochastic update equation: rho(i,t+Δt) − rho(i,t) = [a rho(i,t) − b rho(i,t)² + D ∇̃² rho(i,t)] Δt + sqrt(rho(i,t) Δt) Y(i,t), with the square-root term on a second line.


Here are the two equations. Thanks for your help!