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Pointwise Convergence and Why It Loses Continuity

A sequence of functions has many limits hiding inside it — one for each point. We pin down pointwise convergence, build the limit function, and watch a sequence of continuous functions converge to a discontinuous one.

One limit per point

Suppose for each n we have a function f_n defined on a set E. To ask whether the sequence (f_n) converges is really to ask, separately at every point x in E, whether the number sequence f_1(x), f_2(x), f_3(x), … converges. If it does for every x, we say (f_n) converges pointwise, and we define the limit function f by f(x) = lim f_n(x). Nothing more is happening here than a limit of a sequence of real numbers, run once for each fixed x.

Written out with quantifiers, pointwise convergence says: for each x in E and each epsilon > 0, there is an N (which may depend on both x and epsilon) such that |f_n(x) - f(x)| < epsilon for all n >= N. The key phrase is *which may depend on x*. The same epsilon can demand a much larger N at one point than at another. That single loophole is the source of every surprise in this guide.

The famous counterexample

Take E = [0, 1] and f_n(x) = x^n. Each f_n is a polynomial, hence perfectly continuous. Let us compute the pointwise limit and discover that it is not continuous — a clean counterexample to the hope that continuity always survives a limit.

f_n(x) = x^n  on  [0, 1].

Fix a point and take n -> infinity:
  * If 0 <= x < 1:  x^n -> 0   (geometric decay since |x| < 1).
  * If x = 1:       1^n = 1 -> 1.

So the pointwise limit function is
  f(x) = 0   for 0 <= x < 1,
  f(1) = 1.

Every f_n is continuous on [0,1], but f has a jump at x = 1:
  lim_{x -> 1^-} f(x) = 0  ,  f(1) = 1.
The limit of continuous functions is DISCONTINUOUS.
Continuous f_n(x) = x^n, discontinuous pointwise limit.

Why N runs away near the corner

Diagnose the failure with the quantifiers. On [0, 1) the limit is 0, so we need x^n < epsilon. Solving gives n > ln(epsilon)/ln(x). As x climbs toward 1, ln(x) -> 0 from below, so the required n explodes. There is no single N that works for all x at once: that is exactly the missing uniformity, the subject of the next guide.

Need x^n < epsilon = 0.01 on [0,1).

  x = 0.5 :  n > ln(0.01)/ln(0.5)  = 4.605/0.693 ~ 6.6   -> N = 7.
  x = 0.9 :  n > ln(0.01)/ln(0.9)  = 4.605/0.105 ~ 43.7  -> N = 44.
  x = 0.99:  n > ln(0.01)/ln(0.99) = 4.605/0.0101~ 458    -> N = 459.

As x -> 1^-, the required N -> infinity.
No finite N serves the whole interval [0,1): convergence is
NOT uniform, only pointwise.
The threshold N depends on x and blows up near x = 1.