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Leibniz Alternating Series Test and Conditional Convergence

An alternating series converges if its terms shrink monotonically to 0; combine with absolute convergence to label it absolutely, conditionally, or divergent.

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The setup

An alternating series has the form

∑n=1∞(−1)nbnor∑n=1∞(−1)n−1bn,bn>0,\sum_{n=1}^{\infty} (-1)^{n} b_n \quad\text{or}\quad \sum_{n=1}^{\infty} (-1)^{n-1} b_n,\qquad b_n > 0,

so consecutive terms flip sign. The Leibniz (alternating series) test gives a remarkably cheap convergence criterion.

Theorem (Leibniz test)

The series ∑(−1)nbn\sum (-1)^{n} b_n converges provided all three hold from some index NN onward:

  1. Positive: bn>0b_n > 0,
  2. Monotone decreasing: bn+1≤bnb_{n+1} \le b_n,
  3. Vanishing: lim⁡n→∞bn=0\displaystyle\lim_{n\to\infty} b_n = 0.

If condition 3 fails (bn↛0b_n \not\to 0), the term test already forces divergence. Conditions 1-2 only need to hold eventually (for large nn); the first finitely many terms never affect convergence.

A bonus: the partial sums bracket the true sum, giving the error bound ∣S−SN∣≤bN+1\left|S - S_N\right| \le b_{N+1} — the first omitted term.

Absolute vs. conditional convergence

Convergence by Leibniz does not mean the series converges absolutely. Classify in two passes:

Test on ∑∣an∣\sum \vert a_n\vert Test on ∑an\sum a_n Verdict
converges (converges automatically) absolutely convergent
diverges converges (e.g. Leibniz) conditionally convergent
diverges diverges divergent

So the recipe is: first check ∑∣an∣=∑bn\sum |a_n| = \sum b_n. If it converges, you are done (absolute). If it diverges, fall back to the Leibniz test on the signed series to decide between conditional and divergent.

How to apply (checklist)

  1. Expose the sign. Rewrite the numerator so the alternation is explicit. A common konkur trick: sin⁡ ⁣((n+12)π)=cos⁡(nπ)=(−1)n\sin\!\big((n+\tfrac12)\pi\big) = \cos(n\pi) = (-1)^n, and cos⁡(nπ)=(−1)n\cos(n\pi) = (-1)^n.
  2. Isolate bnb_n (the positive magnitude) and verify bn↓0b_n \downarrow 0 for Leibniz.
  3. Test ∑bn\sum b_n for absolute convergence (p-test, comparison, integral test).
  4. Combine via the table above.

Worked mini-example

Classify ∑n=2∞(−1)nn\displaystyle\sum_{n=2}^{\infty} \frac{(-1)^{n}}{\sqrt{n}}.

  • bn=1nb_n = \dfrac{1}{\sqrt{n}} is positive, decreasing, and →0\to 0, so by Leibniz the series converges.
  • Absolute values: ∑1n=∑n−1/2\sum \dfrac{1}{\sqrt{n}} = \sum n^{-1/2} is a pp-series with p=12≤1p=\tfrac12 \le 1, so it diverges.

Converges but not absolutely ⇒\Rightarrow conditionally convergent.

The same logic settles ∑(−1)nln⁡(ln⁡n)\sum \dfrac{(-1)^n}{\ln(\ln n)}: bn=1/ln⁡(ln⁡n)↓0b_n=1/\ln(\ln n)\downarrow 0 (Leibniz converges), yet ln⁡(ln⁡n)\ln(\ln n) grows so slowly that ∑1/ln⁡(ln⁡n)\sum 1/\ln(\ln n) diverges by comparison with the harmonic series — hence again conditional.

Exam trick: Leibniz only certifies convergence of the signed series; it says nothing about absolute convergence. Whenever a question asks for the exact type, you must run a second test on ∑∣an∣\sum |a_n|. Skipping that step is how the 'absolutely convergent' distractor steals points from a series that is merely conditional.

فرمول‌های کلیدی

Alternating series (general form)
∑n=1∞(−1)nbn,bn>0\sum_{n=1}^{\infty} (-1)^{n} b_n,\qquad b_n > 0

Terms alternate in sign; b_n is the positive magnitude of the n-th term.

Leibniz test conditions
bn>0,bn+1≤bn,lim⁡n→∞bn=0  ⇒  ∑(−1)nbn convergesb_n > 0,\quad b_{n+1} \le b_n,\quad \lim_{n\to\infty} b_n = 0 \;\Rightarrow\; \sum (-1)^n b_n \text{ converges}

Positive, eventually decreasing, vanishing magnitudes guarantee convergence of the alternating series.

Alternating series remainder bound
∣S−∑k=1N(−1)kbk∣≤bN+1\left| S - \sum_{k=1}^{N} (-1)^{k} b_k \right| \le b_{N+1}

Truncation error is at most the first omitted term's magnitude.

Conditional convergence criterion
∑an converges  ∧  ∑∣an∣ diverges  ⇒  conditionally convergent\sum a_n \text{ converges} \;\wedge\; \sum |a_n| \text{ diverges} \;\Rightarrow\; \text{conditionally convergent}

Convergence of the signed series together with divergence of its absolute series defines conditional convergence.

#alternating-series#leibniz-test#conditional-convergence#absolute-convergence#series

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