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I am looking for an estimation or an approximation of

$\sum _{k=1}^{n}{\log(k)\binom {n}{k}}$

Any hints will be appreciated. Thank you.

david
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3 Answers3

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For $\log n \ge 2$ $$\sum_{k=1}^n {n \choose k} \log(k) \ge \sum_{k=n/\log n}^n {n \choose k} \log(n/\log n)$$ $$=\sum_{k=1}^n {n \choose k} \log(n/\log n)-\sum_{k=1}^{n/\log n} {n \choose k} \log(n/\log n)$$ $$ \ge \sum_{k=1}^n {n \choose k} \log(n/\log n)-\frac{n/\log n}{n}\sum_{k=1}^n {n \choose k} \log(n/\log n)$$ $$ = \log(n/\log n)2^n- \log(n/\log n) 2^n/\log n$$ $$ = \log(n) 2^n(1-\frac1{\log n})(1-\frac{\log \log n}{\log n})$$ Together with the obvious bound $$\sum_{k=1}^n {n \choose k }\log(k) \le \sum_{k=1}^n {n \choose k }\log(n)=\log(n) 2^n$$ we get $$\frac{\sum_{k=1}^n {n \choose k }\log(k)}{\log(n) 2^n} \in [(1-\frac1{\log n})(1-\frac{\log \log n}{\log n}),1]$$

reuns
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  • Thank you for the answer. Let me check it numerically. – david Oct 30 '19 at 18:23
  • @david What do you mean to check numerically? Those inequalities are true, so no numerical check is required! – mathcounterexamples.net Oct 31 '19 at 08:50
  • @mathcounterexamples.net I think it's pretty obvious what it means. It means to see if the inequalities are true for certain values of the parameters. The statement in your comment just indicates you don't see any reason to "check numerically"; I am confused why you asked "what do you mean to check numerically". In any event, I think numerical checks are important, as humans make mistakes in proofs sometimes. I find your comment of very low quality in many respects. – mathworker21 Nov 16 '19 at 10:43
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I'm continuing the computations by Jack D'Aurizio (following myself). \begin{align}\sum_{k=1}^{n}\binom{n}{k}\ln k&=\sum_{k=1}^{n}\binom{n}{k}\int_0^1\frac{x^{k-1}-1}{\ln x}\,dx\\\color{gray}{[\text{note the sign}]}\quad&=\int_0^1\frac{(1+x)^n-1-(2^n-1)x}{x\ln x}\,dx\\\color{gray}{\text{[integrate by parts]}}\quad&=\int_0^1\big(2^n-1-n(1+x)^{n-1})\ln\ln\frac{1}{x}\,dx\\\color{gray}{[\text{substitute }x=2e^{-t}-1]}\quad&=-(2^n-1)\gamma-2^n n\int_0^{\ln 2}e^{-nt}\ln\ln\frac{1}{2e^{-t}-1}\,dt\\&=\color{blue}{2^n(\ln n-\ln 2-I_n)}+\underbrace{\gamma+2^n n\int_{\ln 2}^{\infty}e^{-nt}\ln 2t\,dt}_{\text{small, can be neglected}},\end{align} $$I_n=n\int_0^{\ln 2}e^{-nt}\varphi(t)\,dt,\qquad\varphi(t)=\ln\left[\frac{1}{2t}\ln\frac{1}{2e^{-t}-1}\right].$$ $I_n$ fits Watson's lemma: $\varphi(t)=\frac{1}{2}t+\frac{3}{8}t^2+\frac{1}{3}t^3+\frac{65}{192}t^4+\frac{67}{180}t^5+\ldots$ gives $$I_n\asymp\frac{1}{2n}+\frac{3}{4n^2}+\frac{2}{n^3}+\frac{65}{8n^4}+\frac{134}{3n^5}+\ldots$$

metamorphy
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Interesting question. Frullani's integral provides an integral representation for $\log(k)$, $$ \log(k) = \int_{0}^{+\infty}\frac{e^{-x}-e^{-kx}}{x}\,dx $$ which in combination with the binomial theorem leads to $$ \begin{eqnarray*}\sum_{k=1}^{n}\log(k)\binom{n}{k} &=& \int_{0}^{+\infty}\left[(2^n-1)e^{-x}-(1+e^{-x})^n+1\right]\frac{dx}{x}\\&=&\int_{0}^{1}\underbrace{\frac{1-(1+t)^n+t(2^n-1)}{t\log(t)}}_{f_n(t)}\,dt.\end{eqnarray*} $$ Most of the mass of the integral comes from the right endpoint of the integration range, and since $$ \lim_{t\to 1^-}f_n(t) = 1+\left(\frac{n}{2}-1\right)2^n,\qquad \lim_{t\to 1^-}f_n'(t) = -\frac{1}{2}+\left(\frac{n^2}{8}-\frac{3n}{8}+\frac{1}{2}\right)2^n $$ we may approximate $$ \int_{0}^{1}f_n(t)\,dt \approx \int_{0}^{1} f_n(1^-)e^{-\frac{f_n'(1^-)}{f_n(1^-)}x}\,dx\approx \frac{2^{n+1}(n-2)^2}{n^2-3n+4}\left(1-e^{-\frac{n^2-3n+4}{4n-8}}\right). $$

Jack D'Aurizio
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  • Thank you, interesting answers. Let me do some numeric calculation to verify your results. – david Oct 30 '19 at 18:22
  • I'm quite sure using Frunalli leads to a better asymptotic than my elementary computation but Jack lose a $\log n$ term (because trivially the sum is $\ge 2^{n-1} \log (n/2)$) – reuns Oct 30 '19 at 18:26
  • @reuns: you're right, this approach leads to a worse approximation than yours. It is much better to exploit the fact that $\log$ is approximately constant on short intervals. – Jack D'Aurizio Oct 30 '19 at 18:33
  • Metamorphy claims a perfect asymptotic https://math.stackexchange.com/questions/711953/sum-of-binomials-times-logarithms with the same starting point as yours – reuns Oct 30 '19 at 18:34
  • @reuns: Indeed I lose accuracy when I replace $f_n(1-t)$ with a function of the form $A e^{-B t}$, metamorphy uses a more general approximation of the $A e^{-B t}\varphi(t)$ kind. – Jack D'Aurizio Oct 30 '19 at 18:44