Skip to content

Tuorui "v1ncent19" Peng

En voyage dans l'espace de Hilbert.

Mathematics & Statistics≈ 2 min readEnglish

Brownian Bridge and Basel Problem

This blog originates from a question in the final exam of Applied Stochastic Process this semester. The question focused on the Karhunen-Loève expansion of Brownian Bridge. Soon I was surprised to find that it provides a derivation for the Basel problem:

∑n=1∞1n2=π26\begin{align} \sum_{n=1}^\infty\dfrac{1}{n^2}=\dfrac{\pi^2}{6} \end{align}

§Brownian Bridge and KL Expansion

A standard bridge is defined as

Bt=Wt−tW1,t∈[0,1]\begin{align} B_t=W_t-tW_1,\quad t\in [0,1] \end{align}

where WtW_t is a standard Wiener Process. Autocorrelation function of BtB_t is

R(s,t)=min⁡{s,t}−st\begin{align} R(s,t)=\min\{s,t\}-st \end{align}

The KL expansion is given by the Mercer's decomposition of R(s,t)R(s,t)

R(s,t)=∑iλiϕi(s)ϕi(t)\begin{align} R(s,t)=\sum_{i}\lambda _i\phi _i(s)\phi _i(t) \end{align}

in which eigen functions ϕi\phi _is are given by

∫01R(s,t)ϕi(s) ds=λiϕi(t)\begin{align} \int _0^1 R(s,t)\phi _i(s) \,\mathrm{d}s = \lambda _i\phi _i(t) \end{align}

§My Solution in the Exam

Here I post my solution in the exam: substitute in the expression of R(s,t)R(s,t)

λiϕi(t)=∫01(min⁡{s,t}−st)ϕi(s) ds=∫0tsϕi(s) ds+t∫t1ϕi(s) ds−t∫01sϕi(s) ds\begin{align} \lambda _i\phi _i(t)=&\int _0^1 (\min\{s,t\}-st)\phi _i(s) \,\mathrm{d}s\\ =&\int _0^t s\phi _i(s) \,\mathrm{d}s + t\int _t^1 \phi _i(s) \,\mathrm{d}s - t\int _0^1 s\phi _i(s) \,\mathrm{d}s \end{align}

take differentiation ddt\dfrac{\mathrm{d}^{} }{\mathrm{d}t^{}} to get

λiddtϕi(t)=tϕi(t)+(∫t1ϕi(s) ds+tϕi(t))−∫01sϕi(s) ds=∫t1ϕi(s) ds−∫01sϕi(s) ds\begin{align} \lambda _i\dfrac{\mathrm{d}^{} }{\mathrm{d}t^{}}\phi_i(t)=& t\phi _i(t) + \left( \int _t^1\phi _i(s) \,\mathrm{d}s + t\phi _i(t) \right) - \int _0^1 s\phi _i(s) \,\mathrm{d}s\\ =&\int _t^1\phi _i(s) \,\mathrm{d}s - \int _0^1 s\phi _i(s) \,\mathrm{d}s \end{align}

one more differentiation ddt\dfrac{\mathrm{d}^{} }{\mathrm{d}t^{}}

λid2dt2ϕi(t)=−ϕi(t)\begin{align} \lambda _i\dfrac{\mathrm{d}^{2} }{\mathrm{d}t^{2}}\phi _i(t) = -\phi _i(t) \end{align}

with boundary condition ϕi(0)=ϕi(1)=0\phi _i(0)=\phi _i(1)=0, which has solution

ϕn(t)=2sin⁡(nπt),λn=(1nπ)2\begin{align} \phi _n(t)=\sqrt{2}\sin(n\pi t),\quad \lambda _n=\left(\dfrac{1}{n\pi}\right)^2 \end{align}

i.e. the Mercer expansion is

R(s,t)=min⁡{s,t}−st=∑n=1∞2n2π2sin⁡(nπs)sin⁡(nπt)\begin{align} R(s,t) = \min\{s,t\}-st = \sum_{n=1}^\infty \dfrac{2}{n^2\pi^2}\sin(n\pi s)\sin(n\pi t) \end{align}

§Basel Problem

What makes it interesting is that we can consider the function value R(1/2,1/2)R(1/2,1/2)

R(12,12)=14=∑n=1∞2n2π2sin⁡(nπ2)sin⁡(nπ2)=∑n∈odd∞2n2π2=2π2(112+132+152+…)\begin{align} R(\dfrac{1}{2},\dfrac{1}{2})=\dfrac{1}{4}=&\sum_{n=1}^\infty \dfrac{2}{n^2\pi^2}\sin(\dfrac{n\pi}{2})\sin(\dfrac{n\pi}{2})\\ =&\sum_{n\in\text{odd}}^\infty \dfrac{2}{n^2\pi^2}\\ =&\dfrac{2}{\pi^2}\left(\dfrac{1}{1^2}+\dfrac{1}{3^2}+\dfrac{1}{5^2}+\ldots \right) \end{align}

On the other hand notice that

14∑n=1∞1n2=∑n=1∞1(2n)2=(122+142+162+…)\begin{align} \dfrac{1}{4}\sum_{n=1}^\infty \dfrac{1}{n^2} = \sum_{n=1}^\infty \dfrac{1}{(2n)^2}=\left(\dfrac{1}{2^2}+\dfrac{1}{4^2}+\dfrac{1}{6^2}+\ldots \right) \end{align}

we have

∑n=1∞1n2−14∑n=1∞1n2=(112+122+132+…)−(122+142+162+…)=(112+132+152+…)=π28⇒∑n=1∞1n2=43π28=π26\begin{align} \sum_{n=1}^\infty \dfrac{1}{n^2}-\dfrac{1}{4}\sum_{n=1}^\infty \dfrac{1}{n^2} = & \left(\dfrac{1}{1^2}+\dfrac{1}{2^2}+\dfrac{1}{3^2}+\ldots \right) - \left(\dfrac{1}{2^2}+\dfrac{1}{4^2}+\dfrac{1}{6^2}+\ldots \right)\\ =&\left(\dfrac{1}{1^2}+\dfrac{1}{3^2}+\dfrac{1}{5^2}+\ldots \right)=\dfrac{\pi^2}{8}\\ \Rightarrow \sum_{n=1}^\infty \dfrac{1}{n^2}=& \dfrac{4}{3}\dfrac{\pi^2}{8} = \dfrac{\pi^2}{6} \end{align}

§Appendix: Euler's Method

Euler studied the function sincπt=sin⁡πtπt\mathrm{sinc} \pi t=\dfrac{\sin \pi t}{\pi t}, which has roots at ±1,±2,±3,…\pm 1,\pm 2,\pm 3,\ldots, which means the polynomial form of sincπt\mathrm{sinc}\pi t should looks like

sin⁡πtπt=(1+t)(1−t)(1+t2)(1−t2)…=(1−t2)(1−t24)…=1−t2∑n=1∞1n2+o(t2)\begin{align} \dfrac{\sin \pi t}{\pi t} =& (1+t)(1-t)(1+\dfrac{t}{2})(1-\dfrac{t}{2})\ldots\\ =&(1-t^2)(1-\dfrac{t^2}{4})\ldots \\ =&1- t^2\sum_{n=1}^\infty \dfrac{1}{n^2} + o(t^2) \end{align}

according to taylor series, it should also have expansion of the form

sin⁡πtπt=πt−16(πt)3+o(t3)πt=1−π26t2+o(t2)\begin{align} \dfrac{\sin \pi t}{\pi t} =&\dfrac{\pi t - \dfrac{1}{6}(\pi t)^3 + o(t^3)}{\pi t} = 1 - \dfrac{\pi^2}{6}t^2+o(t^2) \end{align}

by comparing the t2t^2 term we obtain that

∑n=1∞1n2=π26\begin{align} \sum_{n=1}^\infty \dfrac{1}{n^2} = \dfrac{\pi^2}{6} \end{align}