Fundamental theorem of calculus explained

The fundamental theorem of calculus is a theorem that links the concept of differentiating a function (calculating its slopes, or rate of change at each point in time) with the concept of integrating a function (calculating the area under its graph, or the cumulative effect of small contributions). Roughly speaking, the two operations can be thought of as inverses of each other.

The first part of the theorem, the first fundamental theorem of calculus, states that for a continuous function, an antiderivative or indefinite integral can be obtained as the integral of over an interval with a variable upper bound.^[1]

Conversely, the second part of the theorem, the second fundamental theorem of calculus, states that the integral of a function over a fixed interval is equal to the change of any antiderivative between the ends of the interval. This greatly simplifies the calculation of a definite integral provided an antiderivative can be found by symbolic integration, thus avoiding numerical integration.

History

See also: History of calculus.

The fundamental theorem of calculus relates differentiation and integration, showing that these two operations are essentially inverses of one another. Before the discovery of this theorem, it was not recognized that these two operations were related. Ancient Greek mathematicians knew how to compute area via infinitesimals, an operation that we would now call integration. The origins of differentiation likewise predate the fundamental theorem of calculus by hundreds of years; for example, in the fourteenth century the notions of continuity of functions and motion were studied by the Oxford Calculators and other scholars. The historical relevance of the fundamental theorem of calculus is not the ability to calculate these operations, but the realization that the two seemingly distinct operations (calculation of geometric areas, and calculation of gradients) are actually closely related.

From the conjecture and the proof of the fundamental theorem of calculus, calculus as a unified theory of integration and differentiation is started. The first published statement and proof of a rudimentary form of the fundamental theorem, strongly geometric in character,^[2] was by James Gregory (1638–1675).^{[3] [4]} Isaac Barrow (1630–1677) proved a more generalized version of the theorem,^[5] while his student Isaac Newton (1642–1727) completed the development of the surrounding mathematical theory. Gottfried Leibniz (1646–1716) systematized the knowledge into a calculus for infinitesimal quantities and introduced the notation used today.

Geometric meaning/Proof

y = f(x) whose graph is plotted as a curve, one defines a corresponding "area function" x\mapsto A(x) such that is the area beneath the curve between and . The area may not be easily computable, but it is assumed to be well defined.

The area under the curve between and could be computed by finding the area between and, then subtracting the area between and . In other words, the area of this "strip" would be .

There is another way to estimate the area of this same strip. As shown in the accompanying figure, is multiplied by to find the area of a rectangle that is approximately the same size as this strip. So:$$A(x+h)-A(x)\; \backslash approx\; f(x)\; \backslash cdot\; h$$

Dividing by h on both sides, we get:$$\backslash frac\backslash \; \backslash approx\; f(x)$$

This estimate becomes a perfect equality when h approaches 0:$$f(x)\; =\; \backslash lim\_\backslash frac\backslash \; \backslash stackrel\backslash \; A\text{'}(x).$$That is, the derivative of the area function exists and is equal to the original function, so the area function is an antiderivative of the original function.

Thus, the derivative of the integral of a function (the area) is the original function, so that derivative and integral are inverse operations which reverse each other. This is the essence of the Fundamental Theorem.

Physical intuition

Intuitively, the fundamental theorem states that integration and differentiation are inverse operations which reverse each other.

The second fundamental theorem says that the sum of infinitesimal changes in a quantity (the integral of the derivative of the quantity) adds up to the net change in the quantity. To visualize this, imagine traveling in a car and wanting to know the distance traveled (the net change in position along the highway). You can see the velocity on the speedometer but cannot look out to see your location. Each second, you can find how far the car has traveled using, that is, multiplying the current speed (in kilometers or miles per hour) by the time interval (1 second =

\tfrac{ 1 }{ 3600 } hour). By summing up all these small steps, you can approximate the total distance traveled, in spite of not looking outside the car:$$\backslash text\; =\; \backslash sum\; \backslash left(\backslash begin\backslash text\backslash \backslash \; \backslash text\backslash end\backslash right)\; \backslash times\; \backslash left(\backslash begin\backslash text\backslash \backslash \; \backslash text\backslash end\backslash right)=\; \backslash sum\; v\_t\backslash times\; \backslash Delta\; t.$$As \Delta t becomes infinitesimally small, the summing up corresponds to integration. Thus, the integral of the velocity function (the derivative of position) computes how far the car has traveled (the net change in position).

The first fundamental theorem says that the value of any function is the rate of change (the derivative) of its integral from a fixed starting point up to any chosen end point. Continuing the above example using a velocity as the function, you can integrate it from the starting time up to any given time to obtain a distance function whose derivative is that velocity. (To obtain your highway-marker position, you would need to add your starting position to this integral and to take into account whether your travel was in the direction of increasing or decreasing mile markers.)

Formal statements

There are two parts to the theorem. The first part deals with the derivative of an antiderivative, while the second part deals with the relationship between antiderivatives and definite integrals.

First part

This part is sometimes referred to as the first fundamental theorem of calculus.

Let be a continuous real-valued function defined on a closed interval . Let be the function defined, for all in, by$$F(x)\; =\; \backslash int\_a^x\; f(t)\backslash ,\; dt.$$

Then is uniformly continuous on and differentiable on the open interval, and$$F\text{'}(x)\; =\; f(x)$$for all in so is an antiderivative of .

Corollary

The fundamental theorem is often employed to compute the definite integral of a function

f for which an antiderivative F is known. Specifically, if f is a real-valued continuous function on [a,b] and F is an antiderivative of f in [a,b] , then$$\backslash int\_a^b\; f(t)\backslash ,\; dt\; =\; F(b)-F(a).$$

The corollary assumes continuity on the whole interval. This result is strengthened slightly in the following part of the theorem.

Second part

This part is sometimes referred to as the second fundamental theorem of calculus or the Newton–Leibniz theorem.

Let

f be a real-valued function on a closed interval [a,b] and F a continuous function on [a,b] which is an antiderivative of f in (a,b) :$$F\text{'}(x)\; =\; f(x).$$

If

f is Riemann integrable on [a,b] then$$\backslash int\_a^b\; f(x)\backslash ,dx\; =\; F(b)\; -\; F(a).$$

The second part is somewhat stronger than the corollary because it does not assume that

f is continuous.

When an antiderivative

F of f exists, then there are infinitely many antiderivatives for f , obtained by adding an arbitrary constant to F . Also, by the first part of the theorem, antiderivatives of f always exist when f is continuous.

Proof of the first part

For a given function, define the function as$$F(x)\; =\; \backslash int\_a^x\; f(t)\; \backslash ,dt.$$

For any two numbers and in, we have

the latter equality resulting from the basic properties of integrals and the additivity of areas.

According to the mean value theorem for integration, there exists a real number

c \in [x _{1,} x _{1} + \Delta x] such that$$\backslash int\_^\; f(t)\; \backslash ,dt\; =\; f(c)\backslash cdot\; \backslash Delta\; x.$$

It follows that$$F(x\_1\; +\; \backslash Delta\; x)\; -\; F(x\_1)\; =\; f(c)\backslash cdot\; \backslash Delta\; x,$$and thus that$$\backslash frac\; =\; f(c).$$

Taking the limit as

\Delta x \to 0 , and keeping in mind that c \in [x _{1,} x _{1} + \Delta x], one gets $$\backslash lim\_\; \backslash frac\; =\; \backslash lim\_\; f(c),$$that is, $$F\text{'}(x\_1)\; =\; f(x\_1),$$according to the definition of the derivative, the continuity of, and the squeeze theorem.^[6]

Proof of the corollary

Suppose is an antiderivative of, with continuous on . Let$$G(x)\; =\; \backslash int\_a^x\; f(t)\backslash ,\; dt.$$

By the first part of the theorem, we know is also an antiderivative of . Since the mean value theorem implies that is a constant function, that is, there is a number such that for all in . Letting, we have$$F(a)\; +\; c\; =\; G(a)\; =\; \backslash int\_a^a\; f(t)\backslash ,\; dt\; =\; 0,$$which means . In other words,, and so$$\backslash int\_a^b\; f(x)\backslash ,\; dx\; =\; G(b)\; =\; F(b)\; -\; F(a).$$

Proof of the second part

This is a limit proof by Riemann sums.

To begin, we recall the mean value theorem. Stated briefly, if is continuous on the closed interval and differentiable on the open interval, then there exists some in such that$$F\text{'}(c)(b\; -\; a)\; =\; F(b)\; -\; F(a).$$

Let be (Riemann) integrable on the interval, and let admit an antiderivative on such that is continuous on . Begin with the quantity . Let there be numbers such that

It follows that$$F(b)\; -\; F(a)\; =\; F(x\_n)\; -\; F(x\_0).$$

Now, we add each along with its additive inverse, so that the resulting quantity is equal:

The above quantity can be written as the following sum:

The function is differentiable on the interval and continuous on the closed interval ; therefore, it is also differentiable on each interval and continuous on each interval . According to the mean value theorem (above), for each there exists a

c _{i} in such that$$F(x\_i)\; -\; F(x\_)\; =\; F\text{'}(c\_i)(x\_i\; -\; x\_).$$

Substituting the above into, we get$$F(b)\; -\; F(a)\; =\; \backslash sum\_^n\; [F\text{'}(c\_i)(x\_i\; -\; x\_\{i-1\})].$$

The assumption implies

F'(c _{i)} = f(c _{i).} Also, x _{i} - x _{i-1} can be expressed as \Delta x of partition i .

We are describing the area of a rectangle, with the width times the height, and we are adding the areas together. Each rectangle, by virtue of the mean value theorem, describes an approximation of the curve section it is drawn over. Also

\Delta x _{i} need not be the same for all values of, or in other words that the width of the rectangles can differ. What we have to do is approximate the curve with rectangles. Now, as the size of the partitions get smaller and increases, resulting in more partitions to cover the space, we get closer and closer to the actual area of the curve.

By taking the limit of the expression as the norm of the partitions approaches zero, we arrive at the Riemann integral. We know that this limit exists because was assumed to be integrable. That is, we take the limit as the largest of the partitions approaches zero in size, so that all other partitions are smaller and the number of partitions approaches infinity.

So, we take the limit on both sides of . This gives us$$\backslash lim\_\; F(b)\; -\; F(a)\; =\; \backslash lim\_\; \backslash sum\_^n\; [f(c\_i)(\backslash Delta\; x\_i)].$$

Neither nor is dependent on

\|\Delta x _{i\|} , so the limit on the left side remains .$$F(b)\; -\; F(a)\; =\; \backslash lim\_\; \backslash sum\_^n\; [f(c\_i)(\backslash Delta\; x\_i)].$$

The expression on the right side of the equation defines the integral over from to . Therefore, we obtain$$F(b)\; -\; F(a)\; =\; \backslash int\_a^b\; f(x)\backslash ,dx,$$which completes the proof.

Relationship between the parts

As discussed above, a slightly weaker version of the second part follows from the first part.

Similarly, it almost looks like the first part of the theorem follows directly from the second. That is, suppose is an antiderivative of . Then by the second theorem, $G(x)\; -\; G(a)\; =\; \backslash int\_a^x\; f(t)\; \backslash ,\; dt$. Now, suppose $F(x)\; =\; \backslash int\_a^x\; f(t)\backslash ,\; dt\; =\; G(x)\; -\; G(a)$. Then has the same derivative as, and therefore . This argument only works, however, if we already know that has an antiderivative, and the only way we know that all continuous functions have antiderivatives is by the first part of the Fundamental Theorem.For example, if, then has an antiderivative, namely$$G(x)\; =\; \backslash int\_0^x\; f(t)\; \backslash ,\; dt$$and there is no simpler expression for this function. It is therefore important not to interpret the second part of the theorem as the definition of the integral. Indeed, there are many functions that are integrable but lack elementary antiderivatives, and discontinuous functions can be integrable but lack any antiderivatives at all. Conversely, many functions that have antiderivatives are not Riemann integrable (see Volterra's function).

Examples

Computing a particular integral

Suppose the following is to be calculated:$$\backslash int\_2^5\; x^2\backslash ,\; dx.$$

Here,

f(x) = x ^{2} and we can use $F(x)\; =\; \backslash fracx^3$ as the antiderivative. Therefore:$$\backslash int\_2^5\; x^2\backslash ,\; dx\; =\; F(5)\; -\; F(2)\; =\; \backslash frac\; -\; \backslash frac\; =\; \backslash frac\; -\; \backslash frac\; =\; \backslash frac\; =\; 39.$$

Using the first part

Suppose$$\backslash frac\; \backslash int\_0^x\; t^3\backslash ,\; dt$$is to be calculated. Using the first part of the theorem with

f(t) = t ^{3} gives$$\backslash frac\; \backslash int\_0^x\; t^3\backslash ,\; dt\; =\; f(x)=\; x^3.$$

This can also be checked using the second part of the theorem. Specifically, $F(t)\; =\; \backslash fract^4$ is an antiderivative of

f(t) , so$$\backslash frac\; \backslash int\_0^x\; t^3\backslash ,\; dt\; =\; \backslash frac\; F(x)\; -\; \backslash frac\; F(0)\; =\; \backslash frac\; \backslash frac\; =\; x^3.$$

An integral where the corollary is insufficient

SupposeThen

f(x) is not continuous at zero. Moreover, this is not just a matter of how f is defined at zero, since the limit as x\to 0 of f(x) does not exist. Therefore, the corollary cannot be used to compute$$\backslash int\_0^1\; f(x)\backslash ,\; dx.$$But consider the functionNotice that F(x) is continuous on [ 0 , 1 ] (including at zero by the squeeze theorem), and F(x) is differentiable on ( 0 , 1 ) with F'(x) = f(x). Therefore, part two of the theorem applies, and$$\backslash int\_0^1\; f(x)\backslash ,\; dx=F(1)-F(0)=\backslash sin(1).$$

Theoretical example

The theorem can be used to prove that$$\backslash int\_a^b\; f(x)\; dx\; =\; \backslash int\_a^c\; f(x)\; dx+\backslash int\_c^b\; f(x)\; dx.$$

Since, the result follows from, $$F(b)-F(a)\; =\; F(c)-F(a)+F(b)-F(c).$$

Generalizations

The function does not have to be continuous over the whole interval. Part I of the theorem then says: if is any Lebesgue integrable function on and is a number in such that is continuous at, then$$F(x)\; =\; \backslash int\_a^x\; f(t)\backslash ,\; dt$$

is differentiable for with . We can relax the conditions on still further and suppose that it is merely locally integrable. In that case, we can conclude that the function is differentiable almost everywhere and almost everywhere. On the real line this statement is equivalent to Lebesgue's differentiation theorem. These results remain true for the Henstock–Kurzweil integral, which allows a larger class of integrable functions.

In higher dimensions Lebesgue's differentiation theorem generalizes the Fundamental theorem of calculus by stating that for almost every, the average value of a function over a ball of radius centered at tends to as tends to 0.

Part II of the theorem is true for any Lebesgue integrable function, which has an antiderivative (not all integrable functions do, though). In other words, if a real function on admits a derivative at every point of and if this derivative is Lebesgue integrable on, then$$F(b)\; -\; F(a)\; =\; \backslash int\_a^b\; f(t)\; \backslash ,\; dt.$$

This result may fail for continuous functions that admit a derivative at almost every point, as the example of the Cantor function shows. However, if is absolutely continuous, it admits a derivative at almost every point, and moreover is integrable, with equal to the integral of on . Conversely, if is any integrable function, then as given in the first formula will be absolutely continuous with almost everywhere.

The conditions of this theorem may again be relaxed by considering the integrals involved as Henstock–Kurzweil integrals. Specifically, if a continuous function admits a derivative at all but countably many points, then is Henstock–Kurzweil integrable and is equal to the integral of on . The difference here is that the integrability of does not need to be assumed.

The version of Taylor's theorem that expresses the error term as an integral can be seen as a generalization of the fundamental theorem.

There is a version of the theorem for complex functions: suppose is an open set in and is a function that has a holomorphic antiderivative on . Then for every curve, the curve integral can be computed as$$\backslash int\_\backslash gamma\; f(z)\; \backslash ,dz\; =\; F(\backslash gamma(b))\; -\; F(\backslash gamma(a)).$$

The fundamental theorem can be generalized to curve and surface integrals in higher dimensions and on manifolds. One such generalization offered by the calculus of moving surfaces is the time evolution of integrals. The most familiar extensions of the fundamental theorem of calculus in higher dimensions are the divergence theorem and the gradient theorem.

One of the most powerful generalizations in this direction is the generalized Stokes theorem (sometimes known as the fundamental theorem of multivariable calculus):^[7] Let be an oriented piecewise smooth manifold of dimension and let

\omega be a smooth compactly supported -form on . If denotes the boundary of given its induced orientation, then$$\backslash int\_M\; d\backslash omega\; =\; \backslash int\_\; \backslash omega.$$

Here is the exterior derivative, which is defined using the manifold structure only.

The theorem is often used in situations where is an embedded oriented submanifold of some bigger manifold (e.g.) on which the form

\omega is defined.

The fundamental theorem of calculus allows us to pose a definite integral as a first-order ordinary differential equation.$$\backslash int\_a^b\; f(x)\backslash ,\; dx$$can be posed as$$\backslash frac=f(x),\backslash ;\backslash ;\; y(a)=0$$with

y(b) as the value of the integral.

See also

• Differentiation under the integral sign
• Telescoping series
• Fundamental theorem of calculus for line integrals
• Notation for differentiation

References

Bibliography

• .
• .
• .

Further reading

• .
• .
• Malet, A., Studies on James Gregorie (1638-1675) (PhD Thesis, Princeton, 1989).
• Hernandez Rodriguez, O. A.; Lopez Fernandez, J. M. . "Teaching the Fundamental Theorem of Calculus: A Historical Reflection", Loci: Convergence (MAA), January 2012.
• .
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External links

• • James Gregory's Euclidean Proof of the Fundamental Theorem of Calculus at Convergence
• Isaac Barrow's proof of the Fundamental Theorem of Calculus
• Fundamental Theorem of Calculus at imomath.com
• Alternative proof of the fundamental theorem of calculus
• Fundamental Theorem of Calculus MIT.
• Fundamental Theorem of Calculus Mathworld.

Notes and References

1. Web site: Weisstein . Eric W. . First Fundamental Theorem of Calculus . 2024-04-15 . mathworld.wolfram.com . en.
2. Malet. Antoni. James Gregorie on tangents and the "Taylor" rule for series expansions. Springer-Verlag. 1993. Archive for History of Exact Sciences. 46. 2. 97–137. 10.1007/BF00375656. 120101519. Gregorie's thought, on the other hand, belongs to a conceptual framework strongly geometrical in character. (page 137).
3. See, e.g., Marlow Anderson, Victor J. Katz, Robin J. Wilson, Sherlock Holmes in Babylon and Other Tales of Mathematical History, Mathematical Association of America, 2004, p. 114.
4. Book: Gregory, James . Geometriae Pars Universalis . Patavii: typis heredum Pauli Frambotti . 1668 . .
5. Book: Child . James Mark . Barrow . Isaac. The Geometrical Lectures of Isaac Barrow . 1916 . Chicago: Open Court Publishing Company.
6. .
7. Book: Spivak, M.. Calculus on Manifolds (book). Calculus on Manifolds. W. A. Benjamin. 1965. 978-0-8053-9021-6. New York. 124–125.