Numerical solution of the Mukhanov-Sasaki equation

In summary, the conversation discusses solving the Mukhanov equation numerically in Mathematica, which involves dealing with the number of efolds and the Hubble slow roll parameters. The solution of the equation gives the power spectrum, which is evaluated using the inflaton's equation. To initialize the largest-scale modes, the Bunch-Davies vacuum is assumed and the value of N is determined based on the desired k for the CMB quadrupole to exit the horizon.
  • #1
Rafid Mahbub
2
0
Hi,

I am trying to figure out how to solve the Mukhanov equation numerically in Mathematica, but have some problems dealing with it. In terms of the number of efolds, the Fourier modes satisfy the following ODE in terms of the Hubble slow roll parameters:

$$ \frac{d^{2}u_{k}}{dN^{2}}+(1-\epsilon_{H})\frac{du_{k}}{dN}+\left[ \frac{k^{2}}{\mathcal{H}}+(1+\epsilon_{H}-\eta_{H})(\eta_{H}-2)-\frac{d}{dN}(\epsilon_{H}-\eta_{H}) \right]u_{k}=0 $$
the solutions of which give the power spectrum $$ \mathcal{P}_{\mathcal{R}}=\frac{k^{3}}{2\pi^{2}}|\frac{u_{k}}{z}|^{2}_{k<<\mathcal{H}} $$
Now the Hubble slow roll parameters depend on the solution of the inflaton's equation which I know how to solve. I am a bit concerned in how to deal with ##k## in the Mukhanov equation and then in the evaluation of the power spectrum. For this problem, the usual Bunch-Davies vacuum is assumed in the asymptotic past-
$$ u_{k}\rightarrow \frac{e^{-ik\tau}}{\sqrt{2k}} $$
 
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  • #2
Suppose you want the largest-scale modes (##k## corresponding to the CMB quadrupole) to be exiting the horizon at ##N=60##. To initialize these largest-scale modes, go back in time until you are "close" to the BD limit, say, when ##k = 100aH##. The corresponding value of ##N## should be your ##N_i## in the mode equation for that ##k##.
 
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FAQ: Numerical solution of the Mukhanov-Sasaki equation

What is the Mukhanov-Sasaki equation and why is it important in numerical solutions?

The Mukhanov-Sasaki equation is a fundamental equation in cosmology that describes the evolution of primordial perturbations in the early universe. It is important in numerical solutions because it allows us to study the growth of these perturbations and their impact on the formation of large-scale structures, such as galaxies and clusters.

How is the Mukhanov-Sasaki equation derived?

The Mukhanov-Sasaki equation is derived from the Einstein field equations, which describe the dynamics of spacetime in the presence of matter and energy. It is a second-order differential equation that arises from linearizing the field equations around a homogeneous and isotropic background.

What are the main challenges in numerically solving the Mukhanov-Sasaki equation?

One of the main challenges in numerically solving the Mukhanov-Sasaki equation is the large range of scales involved. This means that a high-resolution numerical approach is needed to accurately capture the evolution of the perturbations. Additionally, the Mukhanov-Sasaki equation is a stiff equation, which can make it computationally expensive to solve.

What numerical methods are commonly used to solve the Mukhanov-Sasaki equation?

Finite difference methods, spectral methods, and pseudospectral methods are commonly used to solve the Mukhanov-Sasaki equation. These methods involve discretizing the equation and solving it using numerical techniques, such as Euler's method or Runge-Kutta methods.

What are some applications of numerical solutions of the Mukhanov-Sasaki equation?

Numerical solutions of the Mukhanov-Sasaki equation have various applications in cosmology, such as predicting the power spectrum of primordial perturbations, studying the formation of large-scale structures, and testing different cosmological models. They are also used in simulations of the early universe, such as inflationary models, to understand the origin of the universe's structure.

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