Leibniz Series

The partial sums overshoot the target, then undershoot it, closing in from both sides. It is a sandwich that keeps tightening.

Add one term and you jump past the target; the next term pulls you back. The back-and-forth swing shrinks every time. So the target always sits between two neighboring partial sums. That gap is exactly the error bound.

For example, a ⚽ ball rolls past a line, comes back, and crosses it again. Each crossing overshoots by less than the one before. The ball has no choice but to settle on the line.

π4=1−13+15−17+⋯\frac{\pi}{4}=1-\frac{1}{3}+\frac{1}{5}-\frac{1}{7}+\cdots
∣SN−π4∣≤12N+1\left|S_N-\frac{\pi}{4}\right|\le\frac{1}{2N+1}

Examples & Exercises

With SN:=∑k=0N(−1)k2k+1S_N := \sum_{k=0}^{N} \frac{(-1)^k}{2k+1}, prove the alternating-series error bound ∣SN−π4∣≤12N+3\left|S_N - \frac{\pi}{4}\right| \le \frac{1}{2N+3}.

∣L−SN∣≤∣SN+1−SN∣=aN+1=12N+3,SN=∑k=0N(−1)k2k+1|L - S_N| \le |S_{N+1} - S_N| = a_{N+1} = \frac{1}{2N+3}, \qquad S_N = \sum_{k=0}^{N} \frac{(-1)^k}{2k+1}
N=12N = 12 (13 terms): error ≤1/27≈0.037\le 1/27 \approx 0.037 — squeezed from both sides.
Show proof
  1. Put ak=12k+1↓0a_k = \frac{1}{2k+1} \downarrow 0 and SN=∑k=0N(−1)kakS_N = \sum_{k=0}^{N} (-1)^k a_k.

    Prove the nesting by paired differences: S2m+2−S2m=−a2m+1+a2m+2=−(a2m+1−a2m+2)≤0S_{2m+2} - S_{2m} = -a_{2m+1} + a_{2m+2} = -(a_{2m+1} - a_{2m+2}) \le 0, so the even partial sums (S2m)(S_{2m}) decrease; and for m≥1m \ge 1, S2m+1−S2m−1=a2m−a2m+1≥0S_{2m+1} - S_{2m-1} = a_{2m} - a_{2m+1} \ge 0, so the odd partial sums (S2m+1)(S_{2m+1}) increase.

    Also S2m−S2m+1=a2m+1>0S_{2m} - S_{2m+1} = a_{2m+1} > 0.

  2. The sequence (S2m)(S_{2m}) is decreasing and bounded below by the odd sums, and (S2m+1)(S_{2m+1}) is increasing and bounded above, so both converge.

    The gap S2m−S2m+1=a2m+1→0S_{2m} - S_{2m+1} = a_{2m+1} \to 0, so both limits equal a common LL, with S2m+1≤L≤S2mS_{2m+1} \le L \le S_{2m} for every mm.

    Hence LL always lies between two consecutive partial sums, and ∣L−SN∣≤∣SN+1−SN∣=aN+1|L - S_N| \le |S_{N+1} - S_N| = a_{N+1}.

    Here aN+1=12(N+1)+1=12N+3a_{N+1} = \frac{1}{2(N+1)+1} = \frac{1}{2N+3}.

  3. Identify the limit: this series is the arctan series of the problem below at x=1x = 1, so by Abel continuity its sum is arctan⁡1=π4\arctan 1 = \frac{\pi}{4}. That is, L=π4L = \frac{\pi}{4}, hence ∣SN−π4∣≤12N+3\left|S_N - \frac{\pi}{4}\right| \le \frac{1}{2N+3}.

How many terms suffice to guarantee three correct decimal places?

Use SN=∑k=0N(−1)k2k+1S_N = \sum_{k=0}^{N} \frac{(-1)^k}{2k+1} from the previous problem and its error bound to give a sufficient number.

12N+3<0.0005  ⟺  N≥999(1000 terms suffice)\frac{1}{2N+3} < 0.0005 \iff N \ge 999 \quad \text{(1000 terms suffice)}
Even with 60 terms only two decimals — very slow convergence.
Show proof
  1. Three correct decimals (rounding) requires error <0.0005< 0.0005.

  2. The error bound gives the sufficient condition 12N+3<0.0005\frac{1}{2N+3} < 0.0005, i.e. 2N+3>20002N + 3 > 2000, N>998.5N > 998.5.

    So N≥999N \ge 999 suffices.

    Check: at N=999N = 999, 12001≈0.00049975<0.0005\frac{1}{2001} \approx 0.00049975 < 0.0005; at N=998N = 998 the bound is 11999≈0.00050025>0.0005\frac{1}{1999} \approx 0.00050025 > 0.0005, so this bound does not guarantee the accuracy there (that does not mean the actual error is larger).

  3. So N=999N = 999, i.e. 1000 terms (k=0,…,999k = 0, \dots, 999), suffice to guarantee the accuracy — this is a sufficient guarantee, not a claim of minimality. The notorious slowness of the Leibniz series.

Derive arctan⁡x=∑k=0∞(−1)kx2k+12k+1\arctan x = \sum_{k=0}^{\infty}\frac{(-1)^k x^{2k+1}}{2k+1} for ∣x∣<1|x| < 1, giving the Leibniz series at x=1x = 1. (The final step uses Abel's theorem, taken as known.)

arctan⁡x=∫0xdt1+t2=∑k=0∞(−1)kx2k+12k+1\arctan x = \int_0^x \frac{dt}{1+t^2} = \sum_{k=0}^{\infty}\frac{(-1)^k x^{2k+1}}{2k+1}
Where the series comes from: the power series of arctan⁡\arctan at x=1x = 1.
Show proof
  1. For ∣t∣<1|t| < 1, 11+t2=∑k=0∞(−t2)k\frac{1}{1+t^2} = \sum_{k=0}^{\infty}(-t^2)^k (geometric series).

  2. For fixed ∣x∣<1|x| < 1, every tt between 00 and xx satisfies ∣(−t2)k∣=∣t∣2k≤∣x∣2k\lvert (-t^2)^k \rvert = \lvert t \rvert^{2k} \le \lvert x \rvert^{2k}, and ∑k∣x∣2k\sum_k \lvert x \rvert^{2k} is a convergent geometric series, so the Weierstrass M-test gives uniform convergence on that interval.

    Hence termwise integration is legitimate: for 0≤x<10 \le x < 1, arctan⁡x=∫0x∑k=0∞(−1)kt2k dt=∑k=0∞(−1)kx2k+12k+1\arctan x = \int_0^x \sum_{k=0}^{\infty}(-1)^k t^{2k}\,dt = \sum_{k=0}^{\infty}\frac{(-1)^k x^{2k+1}}{2k+1}.

    For x<0x < 0 the interval flips: the same bound holds on [x,0][x, 0], ∫0x=−∫x0\int_0^x = -\int_x^0, and both sides are odd functions, so the same formula holds.

  3. Substituting x=1x = 1 involves a conditionally convergent series, so Abel's theorem is needed — taken as known, it gives arctan⁡1=π4\arctan 1 = \frac{\pi}{4} as the Leibniz series.

7. Series