4.4.2 · D1Multivariable Calculus

Foundations — Limits and continuity in 2D — path-dependence issue

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This page is a toolbox. We open every drawer, name every tool in plain words, draw the picture it stands for, and say why the parent topic the path-dependence note cannot work without it. Read top to bottom — each item is built only from the ones above it.


1. The point in the plane:

Figure — Limits and continuity in 2D — path-dependence issue

Picture: the burnt-orange dot sits at . Walk units along the horizontal axis, then units up. One pair = one location.

Why the topic needs it: the whole subject asks what happens to a machine's output as the input point slides toward a special target point . Without a way to name points, we can't even talk about "sliding toward."


2. The target point and the arrow

Here is a fixed spot we care about (often the origin ), while is the wandering point that closes in on it.


3. The function of two inputs:

Picture: think of as the height of a landscape above the flat sheet. Every ground position has a terrain height floating above it.

Why the topic needs it: the "limit" question is "as I walk toward the target on the ground, does the terrain height settle to one number?" No two-input function, no question.


4. Distance in 2D:

This is the single most important symbol in the parent note, so we build it slowly.

How the formula is born — the right triangle. Go from to in two steps: first move horizontally a gap of , then vertically a gap of . These two moves are the two legs of a right triangle; the straight arrow between the points is its hypotenuse.

Figure — Limits and continuity in 2D — path-dependence issue

Pythagoras says (leg)² + (leg)² = (hypotenuse)². So

  • We square each gap so that a negative gap (moving left or down) counts the same as a positive one — length can't be negative.
  • We take the square root at the end to undo the squaring and return to honest length units.

Why the topic needs it: the definition of a limit says the input must be within some small radius of the target. This formula is that "within distance." (We name that radius in item 7.)


5. Absolute value: and the candidate value

Why the topic needs it: measures how far the output is from the candidate answer , regardless of whether it overshoots or undershoots. It is the output-side twin of the input-side distance in item 4.


6. The open disk — the picture of "close in every direction"

Figure — Limits and continuity in 2D — path-dependence issue

Picture: a filled circle (minus its edge and its exact centre). Every ray, every spiral, every zig-zag toward eventually lives inside this disk.


7. The Greek dials: (epsilon) and (delta)

Why the topic needs it: paths can only ever disprove a limit. To prove one exists you must win the game on the whole disk. These two symbols are the referee's rulebook.


8. Slope and the line

The line through with slope is . Different picks a different straight road into the target.

Why the topic needs it: the cheapest paths to test are straight lines. Sweeping over all values tests infinitely many directions at once — and if the answer still depends on , the limit is already dead (Worked Example 1 in the parent note).


9. Polar coordinates: and

Figure — Limits and continuity in 2D — path-dependence issue

Picture: the deep-teal arrow has length and swings through angle . The tip's shadow on the horizontal axis is (that's ); its height is (that's ).


10. The squeeze idea and the bound

Why the topic needs it: it is the only honest way to conclude a limit exists (parent Worked Example 3).


11. Degree / homogeneity (the "why the slope survived" tool)


Prerequisite map

Ordered pair x y

Function f of x y

2D distance via Pythagoras

Absolute value and candidate L

Epsilon output tolerance

Open disk radius rho

Every direction must agree

Epsilon Delta game

Slope m and lines

Polar r and theta

Squeeze and bounds

Prove a limit exists

Degree counting

Forecast the answer

Path dependence issue


Equipment checklist

Test yourself — you should be able to answer each before reading the parent note.

What do the two numbers in tell you?
How far right/left () and how far up/down () — one exact spot on the plane.
What does the arrow in mean, and why never "="?
The wandering point creeps toward the fixed target without landing on it, because may be undefined right at the target.
Where does come from?
Pythagoras on the right triangle whose legs are the horizontal gap and vertical gap ; it's the length of the straight arrow between the points.
Why square the gaps and then take a root?
Squaring kills the sign so left/down count like right/up; the root returns to honest length units.
What is in a limit statement?
The candidate landing value — the single number we hope the output settles to, tested via .
What is an open disk ?
All points nearer than to the target, excluding the rim and the centre itself.
Why is a disk (not an interval) the source of all the trouble?
A disk has infinitely many approach directions, so a single value must work no matter how you sneak in.
Which of controls the output, which the input?
= output tolerance around ; = input radius around .
What is the line through with slope ?
; sweeping tests all straight directions at once.
Translate : what do and measure?
= distance from origin (how close), = direction (from which way).
What does leftover as signal?
Direction-dependence, i.e. the limit does not exist.
What tool proves a limit exists, and why can't paths do it?
A shrinking bound via the Squeeze Theorem; paths test only some routes, a bound covers the whole disk.
What does the degree of a term count, and why care?
Sum of the powers of and ; equal degrees cancel size and leave direction (danger), higher top degree forces .

Connections

  • Multivariable Calculus — parent chapter this toolbox feeds
  • Epsilon-Delta Definition — the challenge game in full
  • Polar Coordinates — the language for approaching the origin
  • Squeeze Theorem — the bound-based tool to prove existence
  • Continuity in 1D — the 1D story this generalises
  • Partial Derivatives — built from limits along axis directions
  • Differentiability in 2D — needs the continuity these foundations support