Testing latest pari + WASM + node.js... and it works?! Wow.
License: GPL3
ubuntu2004
Function: sumnummonieninit Section: sums C-Name: sumnummonieninit Prototype: DGDGDGp Help: sumnummonieninit({asymp},{w},{n0 = 1}): initialize tables for Monien summation of a series with positive terms. Doc: initialize tables for Monien summation of a series $\sum_{n\geq n_0} f(n)$ where $f(1/z)$ has a complex analytic continuation in a (complex) neighbourhood of the segment $[0,1]$. By default, assume that $f(n) = O(n^{-2})$ and has a nonzero asymptotic expansion $$f(n) = \sum_{i\geq 2} a_i / n^i$$ at infinity. Note that the sum starts at $i = 2$! The argument \kbd{asymp} allows to specify different expansions: \item a real number $\beta > 0$ means $$f(n) = \sum_{i\geq 1} a_i / n^{i + \beta}$$ (Now the summation starts at $1$.) \item a vector $[\alpha,\beta]$ of reals, where we must have $\alpha > 0$ and $\alpha + \beta > 1$ to ensure convergence, means that $$f(n) = \sum_{i\geq 1} a_i / n^{\alpha i + \beta}$$ Note that $\kbd{asymp} = [1, \beta]$ is equivalent to $\kbd{asymp}=\beta$. \bprog ? \p57 ? s = sumnum(n = 1, sin(1/sqrt(n)) / n); \\ reference point ? \p38 ? sumnummonien(n = 1, sin(1/sqrt(n)) / n) - s %2 = -0.001[...] \\ completely wrong ? t = sumnummonieninit(1/2); \\ f(n) = sum_i 1 / n^(i+1/2) ? sumnummonien(n = 1, sin(1/sqrt(n)) / n, t) - s %3 = 0.E-37 \\ now correct @eprog\noindent (As a matter of fact, in the above summation, the result given by \kbd{sumnum} at \kbd{\bs p38} is slighly incorrect, so we had to increase the accuracy to \kbd{\bs p57}.) The argument $w$ is used to sum expressions of the form $$ \sum_{n\geq n_0} f(n) w(n),$$ for varying $f$ \emph{as above}, and fixed weight function $w$, where we further assume that the auxiliary sums $$g_w(m) = \sum_{n\geq n_0} w(n) / n^{\alpha m + \beta} $$ converge for all $m\geq 1$. Note that for nonnegative integers $k$, and weight $w(n) = (\log n)^k$, the function $g_w(m) = \zeta^{(k)}(\alpha m + \beta)$ has a simple expression; for general weights, $g_w$ is computed using \kbd{sumnum}. The following variants are available \item an integer $k \geq 0$, to code $w(n) = (\log n)^k$; \item a \typ{CLOSURE} computing the values $w(n)$, where we assume that $w(n) = O(n^\epsilon)$ for all $\epsilon > 0$; \item a vector $[w, \kbd{fast}]$, where $w$ is a closure as above and \kbd{fast} is a scalar; we assume that $w(n) = O(n^{\kbd{fast}+\epsilon})$; note that $\kbd{w} = [w, 0]$ is equivalent to $\kbd{w} = w$. Note that if $w$ decreases exponentially, \kbd{suminf} should be used instead. The subsequent calls to \kbd{sumnummonien} \emph{must} use the same value of $n_0$ as was used here. \bprog ? \p300 ? sumnummonien(n = 1, n^-2*log(n)) + zeta'(2) time = 328 ms. %1 = -1.323[...]E-6 \\ completely wrong, f does not satisfy hypotheses ! ? tab = sumnummonieninit(, 1); \\ codes w(n) = log(n) time = 3,993 ms. ? sumnummonien(n = 1, n^-2, tab) + zeta'(2) time = 41 ms. %3 = -5.562684646268003458 E-309 \\ now perfect ? tab = sumnummonieninit(, n->log(n)); \\ generic, slower time = 9,808 ms. ? sumnummonien(n = 1, n^-2, tab) + zeta'(2) time = 40 ms. %5 = -5.562684646268003458 E-309 \\ identical result @eprog