Solve transcendental equation : $\tanh(\alpha x) =\arctan(x)$, at $0<\alpha-1 \ll 1$ and at $\alpha\gg 1$?

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To solve this transcendental equations approximately :

Preivous: $\tanh(\alpha x) =\arctan(x)$, at $0<\alpha-1 \leq 1$ and at $\alpha\geq 1$.

Edit: $\tanh(\alpha x) =\arctan(x)$, at $0<\alpha-1 \ll 1$ and at $\alpha\gg 1$.

I need hint on how to start? I'm thinking to use Newton's Method of Iteration but don't know how?

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To solve $f(x)=0$ with$$f(x):=\tanh(\alpha x)-\arctan x\implies x-\frac{f}{f^\prime}=x-\frac{\tanh(\alpha x)-\arctan x}{\alpha\operatorname{sech}^2(\alpha x)-\tfrac{1}{1+x^2}}$$by Newton-Raphson, you just need a suitable choice of $x_0$. There's an obvious root at $x=0$ but, as we're not interested in that, we seek positive roots ($f$ is odd, so there's no point looking for negative ones; their locations follow from finding the positive ones). Indeed, for $\alpha>1$ we have a small-$x>0$ behaviour $f\sim(\alpha-1)x>0$, but $\lim_{x\to\infty}f(x)=1-\pi/2<0$, so some positive root exists.

We want $x_0$ to approximate this, so we don't converge to $x_0$ instead. For small $x$,$$\frac{f(x)}{x}\approx\alpha-1-\tfrac13(\alpha^3-1)x^2,$$which is $0$ at $x=x^\ast:=\frac{3}{\alpha^2+\alpha+1}$. @LutzLehmann, who has found this is too small a choice of $x_0$ for $\alpha-1\ll1$, has suggested $x_0=\tan1$, for which $\tanh(\alpha x)\approx1=\arctan x$. For $\alpha\gg1$, I expect $x_0=x^\ast$ to still be unhelpfully small.

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We can have an extremely good estimate of the zero of function $$f(x)=\tanh (a x)-\tan ^{-1}(x)$$ making one iteration of Halley's mathod starting with $x_0=k$.

We have $$f(k)=\tanh (a k)-\tan ^{-1}(k)$$ $$f'(k)=a\, \text{sech}^2(a k)-\frac{1}{k^2+1}$$ $$f''(k)=\frac{2 k}{\left(k^2+1\right)^2}-2 a^2 \tanh (a k)\, \text{sech}^2(a k)$$ $$x_1=k+\frac{2\, f(k)\, f'(k)}{f(k) \,f''(k)-2 f'(k)^2}$$

After @Lutz Lehmann's comment, choose $k=\tan(1)$.

Some results

$$\left( \begin{array}{ccc} a & \text{estimation }& \text{solution} \\ 2 & 1.5432449040615292748 & 1.5432446279235773240 \\ 3 & 1.5568066556972442438 & 1.5568066556883083119 \\ 4 & 1.5573811263977578542 & 1.5573811263977572906 \\ 5 & 1.5574065442653326711 & 1.5574065442653326711 \end{array} \right)$$

For small values of $a$ $$\left( \begin{array}{ccc} a & \text{estimation }& \text{solution} \\ 1.1 & 1.1525726521622667697 & 1.1296349644856700163 \\ 1.2 & 1.3059331878896915304 & 1.3018024399310428716 \\ 1.3 & 1.3927625406966437033 & 1.3917949581555723633 \\ 1.4 & 1.4460683663131917454 & 1.4458089619371594747 \\ 1.5 & 1.4804871094885072890 & 1.4804115807485915832 \\ 1.6 & 1.5034696046136527262 & 1.5034463799965303017 \\ 1.7 & 1.5191789474986005266 & 1.5191715316939800960 \\ 1.8 & 1.5300991535713895614 & 1.5300967212675288608 \\ 1.9 & 1.5377849843609131701 & 1.5377841708190835133 \\ 2.0 & 1.5432449040615292748 & 1.5432446279235773240 \end{array} \right)$$

But, for small values of $a$, a Taylor expansion followed by a series reversion leads to $$x=1+t+\frac{ \left(4 a^2 \tanh ^3(a)-4 a^2 \tanh (a)+1\right)}{2 \left(-2 a+2 a \tanh ^2(a)+1\right)}t^2+O\left(t^3\right)$$ where $t=\frac{\pi -4 \tanh (a)}{4 a \text{sech}^2(a)-2}$