An antiderivative reverses differentiation: F is an antiderivative of f on an interval K when F′=f on K, written ∫f(x)dx=F(x)+C. On an interval, any two antiderivatives of the same f differ only by a constant — a fact proved with the Mean Value Theorem — and two systematic techniques, substitution (∫f(g(x))g′(x)dx=F(g(x))+C) and integration by parts (∫udv=uv−∫vdu), turn the derivative rules you already know (chain rule, product rule) into tools for finding antiderivatives, with direct uses in kinematics: recovering position from velocity and velocity from acceleration.
IntuitionRunning the derivative backward: from velocity to position
A speedometer tells you v(t), how fast you are going; an odometer tells you s(t), how far you have travelled. Differentiation goes one way, s↦v: v(t)=s′(t). The antiderivative asks the reverse question: given only the speed readings v(t), can you reconstruct the position s(t)? Since differentiating undoes a shift by a constant (dxd(x2+5)=dxd(x2+100)=2x), reversing it can only recover s up to an unknown constant — exactly how much distance had already been covered before you started watching the speedometer.
A cubic curve representing one antiderivative F(x); a slider for the constant d shifts the entire curve up or down without changing its shape.
One member, F(x)≈3x3−x2+x, of the family of antiderivatives of f(x)=x2−2x+1=(x−1)2. Dragging the constant term d shifts the whole curve vertically without changing its slope anywhere — because the derivative of a constant is 0 — which is exactly why every vertical shift of F is also a valid antiderivative of the same f.
SchoolDefinition of the antiderivative
Definition: Antiderivative on an interval
Let f be defined on an interval K. A function F is an antiderivative (or primitive) of f on K if F is differentiable at every x∈K and F′(x)=f(x),x∈K. The collection of all antiderivatives of f on K is called the indefinite integral of f, written ∫f(x)dx=F(x)+C, where C ranges over all real constants; ∫ is the integral sign, f(x) the integrand, and dx marks x as the variable of integration.
F′(x)=f(x),x∈K
Linearity. Antiderivatives inherit the two linearity rules of differentiation: ∫[f(x)±g(x)]dx=∫f(x)dx±∫g(x)dx, and pulling out a nonzero constant factor, ∫kf(x)dx=k∫f(x)dx(k=0). These let you find the antiderivative of a sum or scalar multiple term by term, exactly as with derivatives.
∫f(x)dx=F(x)+C
Basic table of antiderivatives
f(x)
∫f(x)dx
Condition
xn
n+1xn+1+C
n=−1
x1
ln∣x∣+C
x=0
ex
ex+C
always
cosx
sinx+C
always
sinx
−cosx+C
always
cos2x1
tanx+C
x=2π+kπ
UndergraduateUniqueness, substitution, and integration by parts
If F and G are both antiderivatives of f on an interval K, then there is a constant C such that G(x)=F(x)+C for all x∈K.
Why is it true?
If two cars drive along the same road with identical speed at every instant, they cannot drift apart or come together — the distance between them stays fixed forever. Here F and G are the two cars' positions and f is their shared speed; the theorem says the "gap" G−F must be a constant. Crucially this needs K to be a single interval: on two separate intervals, the gap could jump to a different constant on each piece, since you never have to physically travel from one piece to the other.
Proof
Define H(x)=G(x)−F(x) for x∈K. Since F and G are both antiderivatives of f, H′(x)=G′(x)−F′(x)=f(x)−f(x)=0 for every x∈K: H is differentiable on K with derivative identically zero.
Take any two points x1<x2 in K (possible since K is an interval, so the whole segment [x1,x2] lies in K). H is differentiable, hence continuous, on [x1,x2], so the Mean Value Theorem (Lagrange) applies: there is ξ∈(x1,x2) with H(x2)−H(x1)=H′(ξ)(x2−x1)=0, using H′(ξ)=0.
Hence H(x2)=H(x1) for every pair x1<x2 in K: H takes the same value everywhere on K, say H(x)=C for all x∈K. Substituting back, G(x)−F(x)=C, i.e. G(x)=F(x)+C, which is exactly the claim.
If F is an antiderivative of f and g is differentiable, then ∫f(g(x))g′(x)dx=F(g(x))+C.
Why is it true?
Substitution is nothing but the chain rule read backward: differentiating a composite function F(g(x)) produces exactly the pattern "outer derivative times inner derivative," f(g(x))g′(x). So whenever an integrand already has this exact shape, recognizing u=g(x) turns a hard-looking integral in x into an easy one in u.
Proof
Define Φ(x)=F(g(x)). By the chain rule, since F′=f, Φ′(x)=F′(g(x))⋅g′(x)=f(g(x))g′(x).
This says exactly that Φ is differentiable with derivative f(g(x))g′(x) at every x in the domain — i.e. Φ is, by definition, an antiderivative of f(g(x))g′(x).
By the uniqueness theorem above, every antiderivative of f(g(x))g′(x) differs from Φ by a constant, so ∫f(g(x))g′(x)dx=Φ(x)+C=F(g(x))+C, as claimed. In practice one writes u=g(x), du=g′(x)dx, reducing the left side to ∫f(u)du=F(u)+C before substituting u=g(x) back at the end.
If u=u(x) and v=v(x) are differentiable on an interval K, then ∫udv=uv−∫vdu, i.e. ∫u(x)v′(x)dx=u(x)v(x)−∫u′(x)v(x)dx.
Why is it true?
Integration by parts reverses the product rule: it does not remove the integral, but it shifts the derivative from one factor (v) onto the other (u), which is exactly the right move when u becomes simpler after differentiating (like u=x becoming u′=1) while v′ stays easy to antidifferentiate — turning a hard product like ∫xexdx into an easy one.
Proof
By the product rule, (uv)′=u′v+uv′. Rearranging, uv′=(uv)′−u′v.
Take the antiderivative (with respect to x, on K) of both sides. On the right, (uv)′ obviously has antiderivative uv itself (up to a constant, by the uniqueness theorem), so ∫uv′dx=∫(uv)′dx−∫u′vdx=uv−∫u′vdx.
Writing dv=v′(x)dx and du=u′(x)dx turns this into the compact mnemonic form ∫udv=uv−∫vdu. In practice, one factor is chosen as u (to be differentiated) and the rest as dv (to be antidifferentiated), typically preferring to differentiate the factor that simplifies (polynomial, logarithm) and antidifferentiate the factor that stays manageable (ex, sinx, cosx).
UndergraduateReal-World Applications and Worked Examples
Antiderivatives are the mathematical engine of kinematics: since v(t)=s′(t) and a(t)=v′(t)=s′′(t), going backward — antidifferentiating acceleration to recover velocity, then antidifferentiating velocity to recover position — is exactly how engineers compute how far a braking car travels before stopping, or how high a rocket climbs given its thrust profile, whenever only the acceleration (from Newton's second law, F=ma) is known directly.
Example: Braking distance from a velocity function
A car brakes with velocity v(t)=20−8t (in m/s, t in seconds) until it stops. Given s(0)=0, find s(t) and compute the braking distance (the position when the car stops).
Solution
Since v=s′, s is an antiderivative of v: s(t)=20t−4t2 term by term, plus a constant C; s(0)=0 forces C=0, so s(t)=20t−4t2.
The car stops when v(t)=0: 20−8t=0⇒t=2.5s.
The braking distance is the position reached at that stopping time: s(2,5)=20(2,5)−4(2,5)2=50−25=25m. So the car travels 25 meters after the brakes are applied.
Example: Altitude of a rocket from its acceleration
A model rocket accelerates upward with a(t)=6t (m/s²) for 0≤t≤10 s, starting from rest at the ground (v(0)=0, s(0)=0). Find its altitude s(t) and its altitude at t=10 s.
Solution
Antidifferentiate the acceleration to get velocity: ∫6tdt=3t2+C1; since v(0)=0, C1=0, so v(t)=3t2.
Antidifferentiate the velocity to get position: ∫3t2dt=t3+C2; since s(0)=0, C2=0, so s(t)=t3.
At t=10: s(10)=1000m — the rocket has climbed one kilometer, entirely recovered from the acceleration profile by two successive antidifferentiations.
ResearchAntiderivatives at the research frontier
Compute ∫(3x2−4x+5)dx.
Using substitution, compute ∫2xcos(x2)dx.
Using integration by parts, compute ∫xexdx.
An object has velocity v(t)=6t2−4t (m/s) and position s(0)=1 (m). What is s(1)?