What is it?
: the values can be made as close to as we like by taking close enough to (but not equal). Derivatives, integrals and continuity are all defined as limits.
Why does it exist?
Some of the most important quantities are of the form : the slope at , the average speed over a zero-length interval. We cannot plug in the value, but we can ask what the expression approaches. The limit is the tool that makes "instantaneous" and "infinitely thin" rigorous.
Intuition
A game between two players. The skeptic names a tolerance around (a horizontal band); you must answer with a (a vertical band around ) such that the graph, over the vertical band minus the point itself, stays inside the horizontal band. If you can always answer, the limit is . What happens exactly at is irrelevant — need not even be defined there.
Formal definition
Equivalently (Heine): for every sequence with , .
Formulas
- limit laws (when both limits exist)
How is it computed?
- Try substitution: if is continuous at , the limit is .
- If you get , simplify: factor, rationalize, or use known limits and equivalences.
- Still stuck: L'Hôpital's rule or a Taylor expansion.
- To show a limit does not exist, find two sequences with different limits of .
Example
is , but for , so the limit is . Numerically, evaluating at in floating point gives a value off by about : the subtraction cancels almost all significant digits.
Why does it matter?
Every concept from here on — continuity, derivative, integral, series, convergence of algorithms — is a limit. And the example above shows the computational twist: a limit is a statement about exact arithmetic, and a computer that tries to approach it literally (tiny ) runs into rounding error.
Where it shows up in computing
Asymptotic comparisons of running times are limits as .
Approaching a limit with tiny steps in floating point triggers catastrophic cancellation.
Where is it used?
Computing topics reachable from here, through the chain of ideas that leads to them:
λ Scientific computing and algorithms
- Limits at infinity→Algorithm analysis and complexity★★★★★
- Derivative→Differentiation rules→Symbolic computation (CAS)★★★★★
- Derivative→Newton's method→Scientific computing★★★★★
- Riemann sums→Definite integral→Monte Carlo methods★★★★★
- Derivative→Differential and linear approximation→Conditioning→Numerical stability→Floating point (IEEE 754)★★★★★
3D Computer graphics
- Riemann sums→Definite integral→The rendering equation★★★★★
- Derivative→Partial derivatives→Gradient→Surface normals★★★★★
- Derivative→Partial derivatives→Gradient→Signed distance fields and ray marching★★★★★
- Derivative→Higher-order derivatives→Curvature (basic differential geometry)→Mesh processing (discrete differential geometry)★★★★★
- Derivative→Partial derivatives→Gradient→Surface normals→Lighting and shading★★★★★
- Derivative→Partial derivatives→Gradient→Surface normals→Ray tracing★★★★★
- +1
⚙ Robotics and control
- Derivative→Kinematics: position, velocity, acceleration★★★★★
- Derivative→Kinematics: position, velocity, acceleration→Robot Jacobian (velocity kinematics)★★★★★
- Derivative→Kinematics: position, velocity, acceleration→Robot dynamics★★★★★
- Derivative→Ordinary differential equations→Control theory★★★★★
- Derivative→Kinematics: position, velocity, acceleration→Robot Jacobian (velocity kinematics)→Inverse kinematics★★★★★
- Derivative→Kinematics: position, velocity, acceleration→Robot dynamics→Trajectory optimization and MPC★★★★★
- +2
⚛ Physics and simulation
- Derivative→Physics engines★★★★★
- Derivative→Ordinary differential equations→Classical mechanics★★★★★
- Derivative→Ordinary differential equations→Population and epidemic models★★★★★
- Derivative→Physics engines→N-body gravitational simulation★★★★★
- Derivative→Numerical differentiation→Heat equation and diffusion★★★★★
- Derivative→Physics engines→Fluid dynamics and CFD★★★★★
- +4
∿ Signals, media and vision
- Continuity→Interpolation→Image processing and computer vision★★★★★
- Limits at infinity→Improper integrals→Fourier transform→Signal processing★★★★★
- Limits at infinity→Improper integrals→Fourier transform→Sampling theorem (Nyquist–Shannon)★★★★★
- Limits at infinity→Improper integrals→Fourier transform→Fast Fourier transform (FFT)★★★★★
- Riemann sums→Definite integral→Convolution→Digital filters★★★★★
- Continuity→Interpolation→Image processing and computer vision→Media compression (JPEG, MP3, video)★★★★★
- +1
What depends on it
Exercises
Compute .
Hint
Multiply and divide by .
Solution
.
Why does not exist? Describe the graph.
Solution
The graph oscillates between and infinitely often near 0. Along the values are ; along they are . Two sequences, two different limits.