5
$\begingroup$

I am trying to polish my second answer to this question in Mathematics Stack Exchange.

The problem is to find the asymptotics of $t$, solution of the implicit equation $$\color{blue}{\left(1-2 x^2\right) \text{erfc}\left(\left(\frac{1}{2}+t\right) x\right)+\text{erfc}\left(\left(\frac{1}{2}-t\right) x\right)=0}\tag 1$$ for large $x >0 $ (then small values of $t$).

I had no problem to arrive to the fact that it is equivalent to find $t$ solution of $$Q=\frac{\sqrt{\pi }\,\, e^{\frac{x^2}{4}} \left(x^2-1\right) \text{erfc}\left(\frac{x}{2}\right)}{2 x^3}=\sum_{n=0}^\infty (-1)^{n}\, \frac{P_n}{n!}\,t^{n+1}\tag 2$$ where $P_n$ is a polynomial of degree $2n$ in $x$.

Now, the problem is related to the power series reversion of $(2)$ truncated to $O(t^{p+1})$

$$t_{(p)}=Q\sum_{n=0}^p T_n\,Q^n \tag 3$$

which would be followed by the series expansion for large $x$ to have $$t_{(p)}=\sum_{n=1}^p \frac {a_n}{x^{2n}}\tag 4$$

The problem is that the leading order of $T_n$ is $x^{2n}$ which makes that $$x^{2n}\,Q^n=1-\frac{3 n}{x^2}+O\left(\frac{1}{x^4}\right)$$ This means that all coefficients $a_n$ depend on $p$. For example, as a function of $p$, coefficient $a_1$ form the sequence $$\left\{1,\frac{3}{2},\frac{11}{6},\frac{25}{12},\frac{137}{60 },\frac{49}{20},\frac{363}{140},\frac{761}{280},\frac{7129 }{2520},\cdots\right\}$$ which seems to correspond to the harmonic number $H_n$. The problem is much worse with the next coefficients.

It seems that I would need to use very large $p$ to obtain a good asymptotics of the asymptotics if I stay with this procedure.

Similarly, using the first iterate of Newton-like methods of order $n$ and continuing witge series expansion $$\left( \begin{array}{cccc} n & a_1 & a_2 & a_3\\ 2 & 1 & -3 & 14 \\ 3 & 2 & -14 & 118 \\ 4 & 3 & -45 & 834 \\ 5 & 4 & -140 & 6604 \\ 6 & 5 & -455 & 59510 \\ 7 & 6 & -1530 & 576450 \\ 8 & 7 & -5201 & 5759978 \\ \end{array} \right)$$

Is there any way to do it even totally changing this process ? Any idea or suggestion would be very welcome.

Edit

Using the approximation $$ \text{erfc}(x)\sim \frac{e^{-x^2}}{x\sqrt{\pi }}$$ we face the problem of solving for $t$ $$\color{blue}{e^{-2 x^2 t}=\frac 1{1-2x^2}\,\,\frac{2t+1}{2t-1}}\tag 5$$ which has an explicit solution in terms of the generalized Lambert function.

This could hide a logarithmic contribution somewhere.

As shown below, the solution of $(5)$ is a quite good approximation of the exact solution. $$\left( \begin{array}{ccc} x & \text{sol. of }(5)& \text{sol. of }(1)\\ 3 & 0.1282499 & 0.1344144 \\ 4 & 0.0952576 & 0.0971005 \\ 5 & 0.0720334 & 0.0726883 \\ 6 & 0.0560754 & 0.0563435 \\ 7 & 0.0448454 & 0.0449680 \\ 8 & 0.0366964 & 0.0367576 \\ 9 & 0.0306099 & 0.0306428 \\ 10 & 0.0259471 & 0.0259658 \\ \end{array} \right)$$

$\endgroup$
6
  • $\begingroup$ How did you get formula two, which separates t,x? I would expect additional assumptions concerning O[x], O[t] $\endgroup$ Commented Jan 2, 2023 at 9:47
  • $\begingroup$ @UlrichNeumann. Just expanding $(1)$ as a series around $t=0$. Term $Q$ is just the first term coefficient divided by the second. $\endgroup$ Commented Jan 2, 2023 at 9:53
  • $\begingroup$ Thanks. Assuming t->0 and x->Infinity I'm missing information concerning Asymptotic of x t. $\endgroup$ Commented Jan 2, 2023 at 9:59
  • $\begingroup$ @UlrichNeumann. $(3)$ is simple and rigorous. Now, the problem comes when going from $(3)$ to $(4)$. May be, I took a wrong approach. Cheers :-) $\endgroup$ Commented Jan 2, 2023 at 10:07
  • 2
    $\begingroup$ Try: Reduce[Exp[-2*x^2 *t] == 1/(1 - 2 x^2)*(Series[(2 t + 1)/(2 t - 1), {t, 0, 1}] // Normal), t] then we have; $$t=-\frac{1}{4}+\frac{W\left(\frac{1}{2} e^{\frac{x^2}{2}} x^2 \left(-1+2 x^2\right)\right)}{2 x^2}$$ $\endgroup$ Commented Jan 3, 2023 at 13:36

2 Answers 2

3
$\begingroup$

Solving for $t$ $$\color{blue}{e^{-2 x^2 t}=\frac 1{1-2x^2}\,\,\frac{2t+1}{2t-1}}\tag 5$$ We use the approximation $\frac{2t+1}{2t-1}$ at zero.

aprox = Series[(2 t + 1)/(2 t - 1), {t, 0, 1}] // Normal

R = Reduce[Exp[-2*x^2 *t] == 1/(1 - 2 x^2)*aprox, t]

R[[3, 4]] /. C[1] -> 0 // Expand

(*t == -(1/4) + ProductLog[2 E^(x^2/2) x^2 (-(1/4) + x^2/2)]/(2 x^2)*)
$\endgroup$
6
  • $\begingroup$ Great solution ! For the last table in my answer, this gives $$\{0.133613,0.0970609,0.0727293,0.0563794,0.0449921,0.0367731,0.0306 528,0.0259723\}$$ $\endgroup$ Commented Jan 3, 2023 at 14:33
  • $\begingroup$ You are welcome. :) $\endgroup$ Commented Jan 3, 2023 at 14:37
  • $\begingroup$ Equation (5) might be solved analytically (exact) too : x == Sqrt[(t - ProductLog[-1, -((E^t t (1 + 2 t))/(1 - 2 t))])/(2 t)] $\endgroup$ Commented Jan 3, 2023 at 16:11
  • $\begingroup$ @UlrichNeumann . OP want solving for t not for x ? $\endgroup$ Commented Jan 3, 2023 at 16:14
  • $\begingroup$ @MariuszIwaniuk That is of course true, but your solution doesn't work if you take higher order series expansion for aprox! $\endgroup$ Commented Jan 3, 2023 at 16:21
2
$\begingroup$

After @MariuszIwaniuk's comment and answer

$$e^{-2 x^2 t}=\frac 1{1-2x^2}\,\,\frac{2t+1}{2t-1}\sim \frac {1+4t}{2x^2-1}\quad \implies \quad t=-\frac 14+\frac 1{2x^2}W\left(\frac{1}{2} e^{\frac{x^2}{2}} x^2 \left(2 x^2-1\right)\right)$$ Using the expansions for large argument $$L_1=\log\left(\frac{1}{2} e^{\frac{x^2}{2}} x^2 \left(2 x^2-1\right)\right)=\frac {x^2}2+4 \log (x)-\frac{1}{2 x^2}+O\left(\frac{1}{x^4}\right)$$ $$L_2=\log \left(\log\left(\frac{1}{2} e^{\frac{x^2}{2}} x^2 \left(2 x^2-1\right)\right)\right)=2\log(x)-\log(2)+\frac{8 \log (x)}{x^2}+O\left(\frac{1}{x^4}\right)$$ $$L_1-L_2+\frac {L_2}{L_1}=\frac{x^2}2+2\log(x)+\log(2)-\frac{8 \log (x)+4 \log (2)+1}{2 x^2}$$

$$\color{blue}{t=\frac{\log (x)}{x^2}+\frac{\log (2)}{2 x^2}-\frac{2 \log (x)}{x^4}-\frac{4 \log (2)+1}{4 x^4}+\cdots}$$ Using the exact solutions of the original equation $$\left(1-2 x^2\right) \text{erfc}\left(\left(\frac{1}{2}+t\right) x\right)+\text{erfc}\left(\left(\frac{1}{2}-t\right) x\right)=0$$ and curve fitting the model $$t=a\frac{\log (x)}{x^2}+\frac{b}{2 x^2}-c \frac{ \log (x)}{x^4}-\frac{d}{4 x^4}$$ for $10 \leq x \leq 100$

$$\begin{array}{l|lll} \text{} & \text{Estimate} & \text{Std Error} & \text{Confidence Interval} \\ \hline a & \color{red}{+0.99945} & 0.000010 & \{+0.99943,+0.99947\} \\ b & \color{red}{+0.69808} & 0.000084 & \{+0.69791,+0.69824\} \\ c & +2.57442 & 0.003419 & \{+2.56770,+2.58114\} \\ d & -2.19752 & 0.024778 & \{-2.24625,-2.14879\} \\ \end{array}$$

The mean and maximum absolute errors are $1.29\times 10^{-8}$ and $1.09\times 10^{-7}$ $\color{red}{\large (!!)}$.

Using

$$t_0=\frac{\log (x)}{x^2}+\frac{\log (2)}{2 x^2}$$ the first iterate of Newton method applied to the original equation gives (again) $$t_1=\frac{\log (x)}{x^2}+\frac{\log (2)}{2 x^2}-\frac{2 \log (x)}{x^4}-\frac{4 \log (2)+1}{4 x^4}$$ which, by Darboux theorem, is an underestimate of the solution (for $x=10$, $t_1=0.0259368$ while the solution is $t=0.0259658$) while $t_0$ is an overestimate of it.

$\endgroup$

Your Answer

By clicking “Post Your Answer”, you agree to our terms of service and acknowledge you have read our privacy policy.

Not the answer you're looking for? Browse other questions tagged or ask your own question.