World Library  
Flag as Inappropriate
Email this Article

Second derivative


Second derivative

The second derivative of a quadratic function is constant.

In calculus, the second derivative, or the second order derivative, of a function f is the derivative of the derivative of f. Roughly speaking, the second derivative measures how the rate of change of a quantity is itself changing; for example, the second derivative of the position of a vehicle with respect to time is the instantaneous acceleration of the vehicle, or the rate at which the velocity of the vehicle is changing with respect to time. In Leibniz notation:

\mathbf{a} = \frac{d\mathbf{v}}{dt} = \frac{d^2\boldsymbol{x}}{dt^2}

On the graph of a function, the second derivative corresponds to the curvature or concavity of the graph. The graph of a function with positive second derivative curves upwards, while the graph of a function with negative second derivative curves downwards.


  • Second derivative power rule 1
  • Notation 2
  • Example 3
  • Relation to the graph 4
    • Concavity 4.1
    • Inflection points 4.2
    • Second derivative test 4.3
  • Limit 5
  • Quadratic approximation 6
  • Eigenvalues and eigenvectors of the second derivative 7
  • Generalization to higher dimensions 8
    • The Hessian 8.1
    • The Laplacian 8.2
  • References 9
    • Print 9.1
    • Online books 9.2
  • External links 10

Second derivative power rule

The power rule for the first derivative, if applied twice, will produce the second derivative power rule as follows:



The second derivative of a function f(x)\! is usually denoted f''(x)\!. That is:

f'' = (f')'\!

When using Leibniz's notation for derivatives, the second derivative of a dependent variable y with respect to an independent variable x is written


This notation is derived from the following formula:

\frac{d^2y}{dx^2} \,=\, \frac{d}{dx}\left(\frac{dy}{dx}\right).


Given the function

f(x) = x^3,\!

the derivative of f is the function

f'(x) = 3x^2.\!

The second derivative of f is the derivative of f′, namely

f''(x) = 6x.\!

Relation to the graph

A plot of f(x) = \sin(2x) from -\pi/4 to 5\pi/4. The tangent line is blue where the curve is concave up, green where the curve is concave down, and red at the inflection points (0, \pi/2, and \pi).


The second derivative of a function f measures the concavity of the graph of f. A function whose second derivative is positive will be concave up (sometimes referred to as convex), meaning that the tangent line will lie below the graph of the function. Similarly, a function whose second derivative is negative will be concave down (sometimes called simply “concave”), and its tangent lines will lie above the graph of the function.

Inflection points

If the second derivative of a function changes sign, the graph of the function will switch from concave down to concave up, or vice versa. A point where this occurs is called an inflection point. Assuming the second derivative is continuous, it must take a value of zero at any inflection point, although not every point where the second derivative is zero is necessarily a point of inflection.

Second derivative test

The relation between the second derivative and the graph can be used to test whether a stationary point for a function (i.e. a point where f'(x)=0\!) is a local maximum or a local minimum. Specifically,

  • If \ f^{\prime\prime}(x) < 0 then \ f has a local maximum at \ x.
  • If \ f^{\prime\prime}(x) > 0 then \ f has a local minimum at \ x.
  • If \ f^{\prime\prime}(x) = 0, the second derivative test says nothing about the point \ x, a possible inflection point.

The reason the second derivative produces these results can be seen by way of a real-world analogy. Consider a vehicle that at first is moving forward at a great velocity, but with a negative acceleration. Clearly the position of the vehicle at the point where the velocity reaches zero will be the maximum distance from the starting position – after this time, the velocity will become negative and the vehicle will reverse. The same is true for the minimum, with a vehicle that at first has a very negative velocity but positive acceleration.


It is possible to write a single limit for the second derivative:

f''(x) = \lim_{h \to 0} \frac{f(x+h) - 2f(x) + f(x-h)}{h^2}.

The limit is called the second symmetric derivative.[1][2] Note that the second symmetric derivative may exist even when the (usual) second derivative does not.

The expression on the right can be written as a difference quotient of difference quotients:

\frac{f(x+h) - 2f(x) + f(x-h)}{h^2} = \frac{\frac{f(x+h) - f(x)}{h} - \frac{f(x) - f(x-h)}{h}}{h}.

This limit can be viewed as a continuous version of the second difference for sequences.

Please note that the existence of the above limit does not mean that the function f has a second derivative. The limit above just gives a possibility for calculating the second derivative but does not provide a definition. As a counterexample look on the sign function \sgn(x) which is defined through

\sgn(x) = \begin{cases} -1 & \text{if } x < 0, \\ 0 & \text{if } x = 0, \\ 1 & \text{if } x > 0. \end{cases}

The sign function is not continuous at zero and therefore the second derivative for x=0 does not exist. But the above limit exists for x=0:

\begin{align} \lim_{h \to 0} \frac{\sgn(0+h) - 2\sgn(0) + \sgn(0-h)}{h^2} &= \lim_{h \to 0} \frac{1 - 2\cdot 0 + (-1)}{h^2} \\ &= \lim_{h \to 0} \frac{0}{h^2} \\ &= 0 \end{align}

Quadratic approximation

Just as the first derivative is related to linear approximations, the second derivative is related to the best quadratic approximation for a function f. This is the quadratic function whose first and second derivatives are the same as those of f at a given point. The formula for the best quadratic approximation to a function f around the point x = a is

f(x) \approx f(a) + f'(a)(x-a) + \tfrac12 f''(a)(x-a)^2.

This quadratic approximation is the second-order Taylor polynomial for the function centered at x = a.

Eigenvalues and eigenvectors of the second derivative

For many combinations of boundary conditions explicit formulas for eigenvalues and eigenvectors of the second derivative can be obtained. For example, assuming x \in [0,L] and homogeneous Dirichlet boundary conditions, i.e., v(0)=v(L)=0, the eigenvalues are \lambda_j = -\frac{j^2 \pi^2}{L^2} and the corresponding eigenvectors (also called eigenfunctions) are v_j(x) = \sqrt{\frac{2}{L}} \sin\left(\frac{j \pi x}{L}\right) . Here, v''_j(x) = \lambda_j v_j(x), \, j=1,\ldots,\infty.

For other well-known cases, see the main article eigenvalues and eigenvectors of the second derivative.

Generalization to higher dimensions

The Hessian

The second derivative generalizes to higher dimensions through the notion of second partial derivatives. For a function f:R3 → R, these include the three second-order partials

\frac{\part^2 f}{\part x^2}, \; \frac{\part^2 f}{\part y^2}, \text{ and }\frac{\part^2 f}{\part z^2}

and the mixed partials

\frac{\part^2 f}{\part x \, \part y}, \; \frac{\part^2 f}{\part x \, \part z}, \text{ and }\frac{\part^2 f}{\part y \, \part z}.

If the function's image and domain both have a potential, then these fit together into a symmetric matrix known as the Hessian. The eigenvalues of this matrix can be used to implement a multivariable analogue of the second derivative test. (See also the second partial derivative test.)

The Laplacian

Another common generalization of the second derivative is the Laplacian. This is the differential operator \nabla^2 defined by

\nabla^2 f = \frac{\part^2 f}{\part x^2}+\frac{\part^2 f}{\part y^2}+\frac{\part^2 f}{\part z^2}.

The Laplacian of a function is equal to the divergence of the gradient.


  1. ^
  2. ^


Online books

External links

  • Discrete Second Derivative from Unevenly Spaced Points
This article was sourced from Creative Commons Attribution-ShareAlike License; additional terms may apply. World Heritage Encyclopedia content is assembled from numerous content providers, Open Access Publishing, and in compliance with The Fair Access to Science and Technology Research Act (FASTR), Wikimedia Foundation, Inc., Public Library of Science, The Encyclopedia of Life, Open Book Publishers (OBP), PubMed, U.S. National Library of Medicine, National Center for Biotechnology Information, U.S. National Library of Medicine, National Institutes of Health (NIH), U.S. Department of Health & Human Services, and, which sources content from all federal, state, local, tribal, and territorial government publication portals (.gov, .mil, .edu). Funding for and content contributors is made possible from the U.S. Congress, E-Government Act of 2002.
Crowd sourced content that is contributed to World Heritage Encyclopedia is peer reviewed and edited by our editorial staff to ensure quality scholarly research articles.
By using this site, you agree to the Terms of Use and Privacy Policy. World Heritage Encyclopedia™ is a registered trademark of the World Public Library Association, a non-profit organization.

Copyright © World Library Foundation. All rights reserved. eBooks from Project Gutenberg are sponsored by the World Library Foundation,
a 501c(4) Member's Support Non-Profit Organization, and is NOT affiliated with any governmental agency or department.