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Long-time behaviour of the correlated random walk system

  • *Corresponding author: Marta Pellicer

    *Corresponding author: Marta Pellicer 
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  • In this work, we consider the so-called correlated random walk system (also known as correlated motion or persistent motion system), used in biological modelling, among other fields, such as chromatography. This is a linear system which can also be seen as a weakly damped wave equation with certain boundary conditions. We are interested in the long-time behaviour of its solutions. To be precise, we will prove that the decay of the solutions to this problem is of exponential form, where the optimal decay rate exponent is given by the dominant eigenvalue of the corresponding operator. This eigenvalue can be obtained as a particular solution of a system of transcendental equations. A complete description of the spectrum of the operator is provided, together with a comprehensive analysis of the corresponding eigenfunctions and their geometry.

    Mathematics Subject Classification: Primary: 35Q92, 35L40, 35B40, 35P05.

    Citation:

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  • Figure 1.  Some eigenfunctions for $ S = 0.8 $, real and imaginary parts respect to $ x\in[-1/2, 1/2] $. From left to right, and up to down, plots from $ u_0, v_0 $, and real and imaginary part of $ u_{n, 1}, v_{n, 1} $ for $ n = 2, 4 $ (symmetric case, top), and $ n = 1, 3 $ (antisymmetric case, bottom). In all cases, the blue-cross line corresponds to $ u_{n, 1} $, and the red-circle one to $ v_{n, 1} $. The plots for the corresponding $ (u_{n, 2}, v_{n, 2}) $ are similar, so we do not include them. In these graphs, we can also see the oscillatory behaviour of the $ n $-th eigenfunction, described in Proposition 2.10 below

    Figure 2.  $ \nu_{n, j}(S) $ (up) and $ \lambda_{n, j}(S) $ (bottom) in the complex plane for $ j = 1, 2, \ n = 0, 1, 2, 3, 4 $ (from left to right in the top row, and from the real axis up (or down), in the bottom row). We have $ S\in(0, 2] $ (first column) and $ S\in(0, 0.5] $ (second column). Note that the eigenvalues overlap on the real line. Also, as $ S $ increases, the values of $ \nu_{n, j}(S) $ and $ \lambda_{n, j}(S) $ become non-real, and $ \lambda_{n, j}(S) $ tend to $ -\infty\pm i\infty $

    Figure 3.  $ {{ \rm{Re}}}(\lambda_{n, j}(S)) $ (top) and $ {{ \rm{Im}}}(\lambda_{n, j}(S)) $ (bottom) for $ j = 1, 2, \ n = 0, 1, 2, 3, 4 $ (top to down), with $ S\in(0, 2] $ (first column) and $ S\in(0, 0.5] $ (second column). Again, increasing $ S $ makes the values of $ \lambda_{n, j}(S) $, $ n\geq 1 $, become non-real and $ \lambda_0(S) $ and $ {{ \rm{Re}}}(\lambda_{n, j}(S)) $, $ n\geq 1 $, decrease to $ -\infty $. In this sense, we say that $ S $ is, indeed, a dissipative parameter: the larger it is, the faster the solutions tend to 0

    Figure 4.  Intersections of the graphs of $ \sin x $, and $ Sx $ and $ -Sx $ for different values of $ S>0 $

    Figure 5.  Graph of the function $ y(x) $ for $ S = 0.05 $. We observe that it is well defined and has a minimum in each $ \left(n\pi, (n+1)\pi\right) $ from $ n\geq 6 $ (which corresponds to $ \nu_{n, j}\notin\mathbb{R} $). The blue continuous line corresponds to the function obtained using (12), and the red discontinuous one corresponds to (13)

    Figure 6.  From left to right and from top to bottom, eigenfunctions $ (u_{n, 1}, v_{n, 1}) $, $ n = 1, 2, 3, 4 $ for $ S = 0.8 $ in the complex plane. In all cases, the blue cross line corresponds to $ u_{n, 1} $, and the red circle one to $ v_{n, 1} $ We can see that the $ n $-th eigenfunction makes $ n $ complete half-turns. The plots for the corresponding $ (u_{n, 2}, v_{n, 2}) $ are similar

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