I'm studying a paper (see citation below) on numerical analysis, and came across this estimate. I am unable to figure out what was done in the final step, and I am not certain if this was just a typo in the paper.
Preliminary information: $\Delta{t}$ is the time step, $n$ is the iteration count from $0$ to final iteration $(N+1)$ such that $T=N\Delta{t}$ is the final time at $n=N+1$, $\vec{u}$ is a solution vector, $\vec{f}$ is a vector of forcing functions, and $E_k$ is the energy at iteration $n = k$. We also have various positive constants $C_1, C_2, C_3, C_a$.
Here is the estimate in the text:
$E_n + \frac{C_a\Delta{t}^2(C_1+C_2)}{1+(C_1+C_2)\Delta{t}}\|\nabla\vec{u}^{n+1}\|^2+\frac{C_a\Delta{t}^2(C_1+C_2)}{3(1+(C_1+C_2)\Delta{t})}\|\nabla\vec{u}^n\|^2$
$\le C_3\|\vec{f}^{n+1}\|^2\Delta{t} + (1 + (C_1 + C_2)\Delta{t})E_{n-1}$
$\le e^{(C_1+C_2)T}E_0 + \frac{C_3}{C_1+C_2}e^{(C_1+C_2)T} \max\limits_{n}\|\vec{f}^{n+1}\|^2$
Here is my attempt at what happened at the last step, before the final inequality:
For clarity, take $X_n = \frac{C_a\Delta{t}^2(C_1+C_2)}{1+(C_1+C_2)\Delta{t}}\|\nabla\vec{u}^{n+1}\|^2+\frac{C_a\Delta{t}^2(C_1+C_2)}{3(1+(C_1+C_2)\Delta{t})}\|\nabla\vec{u}^n\|^2$
Since $X_n \ge 0$, then $E_n \le E_n + X_n$ so
$E_n \le C_3\|\vec{f}^{n+1}\|^2\Delta{t} + (1 + (C_1 + C_2)\Delta{t})E_{n-1}$
Problem: Ignoring the first term on the right, I figured the second term can be bounded as:
$E_n \le \left(1 + (C_1 + C_2)\Delta{t}\right)E_{n-1}$
$\quad\: \le \left(1 + (C_1 + C_2)\Delta{t}\right)^{n-1}E_0$
$\quad\: \le e^{((C_1 + C_2)T}E_0 \qquad$ since $e^{nx} \ge (1+x)^n\ \forall\ n,x\in\mathbb{R}_+$
The parts I can't figure out:
- what happened to the first term i.e. $C_3\|\vec{f}^{n+1}\|^2\Delta{t}$. There should be a sum of the $f$ norms here, so my result had an $n$ in front of the max.
- How to re-combine the results with the omitted $X_n$.
Thanks.
Paper: Chen, Wenbin; Gunzburger, Max; Sun, Dong; Wang, Xiaoming, Efficient and long-time accurate second-order methods for the Stokes-Darcy system, SIAM J. Numer. Anal. 51, No. 5, 2563-2584 (2013). ZBL1282.76094.
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Most recentHere is my attempt at what happened at the last step, just asbefore the answer below came infinal inequality:
EDIT: Most recent attempt, just as the answer below came in:
For clarity, take $X_n = \frac{C_a\Delta{t}^2(C_1+C_2)}{1+(C_1+C_2)\Delta{t}}\|\nabla\vec{u}^{n+1}\|^2+\frac{C_a\Delta{t}^2(C_1+C_2)}{3(1+(C_1+C_2)\Delta{t})}\|\nabla\vec{u}^n\|^2$
I will use following prelimary estimates $\forall\ x,n\in\mathbb{R}_+$. The second employs the first. $(1+x)^n \le e^{nx}$ and $\sum_{k=1}^n(1+x)^k \le n(1+x)^n \le n e^{nx}$ So
So the estimate was $$E_n + X_n \le C_3\Delta{t}\|\vec{f}^{n+1}\|^2+(1 +\ (C_1+C_2)\Delta{t})E_{n-1}$$ $$\le C_3\Delta{t}\left(\frac{1+(C_1+C_2)\Delta{t}}{(C_1+C_2)\Delta{t}}\right)\|\vec{f}^{n+1}\|^2+(1 +\ (C_1+C_2)\Delta{t})E_{n-1}$$ i.e. $$E_n + X_n \le \left(1+(C_1+C_2)\Delta{t}\right)\left(\frac{C_3}{C_1+C_2}\|\vec{f}^{n+1}\|^2+E_{n-1}\right) \tag{1}$$ Since $X_n \ge 0$ we also have $$E_n \le \left(1+(C_1+C_2)\Delta{t}\right)\left(\frac{C_3}{C_1+C_2}\|\vec{f}^{n+1}\|^2+E_{n-1}\right) \tag{2}$$ Using (2) in (1), $$E_n + X_n \le \Bigl(1+(C_1+C_2)\Delta{t}\Bigr)$$ $$\cdot\left(\frac{C_3}{C_1+C_2}\|\vec{f}^{n+1}\|^2 + \Bigl(1+(C_1+C_2)\Delta{t}\Bigr)\left(\frac{C_3}{C_1+C_2}\|\vec{f}^{n}\|^2+E_{n-2}\right)\right)$$ Repeating the process $n-1$ times, $$E_n + X_n \le \frac{C_3}{C_1+C_2}\sum_{k=1}^n \|\vec{f}^{k+1}\|^2 \Bigl(1+(C_1+C_2)\Delta{t}\Bigr)^k+ \Bigl(1+(C_1+C_2)\Delta{t}\Bigr)^n E_0$$ i.e. $$E_n + X_n \le \frac{C_3}{C_1+C_2}\max_n\|\vec{f}^{n+1}\|^2\sum_{k=1}^n \Bigl(1+(C_1+C_2)\Delta{t}\Bigr)^k+ \Bigl(1+(C_1+C_2)\Delta{t}\Bigr)^n E_0$$ Using the first preliminary estimate, $$E_n + X_n \le \frac{C_3}{C_1+C_2}\max_n\|\vec{f}^{n+1}\|^2 n \Bigl(1+(C_1+C_2)\Delta{t}\Bigr)^n+ \Bigl(1+(C_1+C_2)\Delta{t}\Bigr)^n E_0$$ And using the second preliminary estimate, $$E_n + X_n \le \frac{nC_3}{C_1+C_2}\max_n\|\vec{f}^{n+1}\|^2 e^{(C_1+C_2)T}+ e^{(C_1+C_2)T} E_0$$
There is a certain $n$ multiplying the first term, which is not present in the paper.