# Wikipedia

en.m.wikipedia.orgModern calculus was developed in 17th-century Europe by Isaac Newton and Gottfried Wilhelm Leibniz (independently of each other, first publishing around the same time) but elements of it have appeared in ancient Greece, then (alphabetically) in China and the Middle East, and still later again in medieval Europe and in India.

"The calculus was the first achievement of modern mathematics and it is difficult to overestimate its importance. I think it defines more unequivocally than anything else the inception of modern mathematics, and the system of mathematical analysis, which is its logical development, still constitutes the greatest technical advance in exact thinking."

In Europe, the foundational work was a treatise due to Bonaventura Cavalieri, who argued that volumes and areas should be computed as the sums of the volumes and areas of infinitesimally thin cross-sections. The ideas were similar to Archimedes' in *The Method*, but this treatise is believed to have been lost in the 13th century, and was only rediscovered in the early 20th century, and so would have been unknown to Cavalieri. Cavalieri's work was not well respected since his methods could lead to erroneous results, and the infinitesimal quantities he introduced were disreputable at first.

The product rule and chain rule,[14] the notions of higher derivatives and Taylor series,[15] and of analytic functions[*citation needed*] were introduced by Isaac Newton in an idiosyncratic notation which he used to solve problems of mathematical physics. In his works, Newton rephrased his ideas to suit the mathematical idiom of the time, replacing calculations with infinitesimals by equivalent geometrical arguments which were considered beyond reproach. He used the methods of calculus to solve the problem of planetary motion, the shape of the surface of a rotating fluid, the oblateness of the earth, the motion of a weight sliding on a cycloid, and many other problems discussed in his *Principia Mathematica* (1687). In other work, he developed series expansions for functions, including fractional and irrational powers, and it was clear that he understood the principles of the Taylor series. He did not publish all these discoveries, and at this time infinitesimal methods were still considered disreputable.

These ideas were arranged into a true calculus of infinitesimals by Gottfried Wilhelm Leibniz, who was originally accused of plagiarism by Newton.[16] He is now regarded as an independent inventor of and contributor to calculus. His contribution was to provide a clear set of rules for working with infinitesimal quantities, allowing the computation of second and higher derivatives, and providing the product rule and chain rule, in their differential and integral forms. Unlike Newton, Leibniz paid a lot of attention to the formalism, often spending days determining appropriate symbols for concepts.

Today, Leibniz and Newton are usually both given credit for independently inventing and developing calculus. Newton was the first to apply calculus to general physics and Leibniz developed much of the notation used in calculus today. The basic insights that both Newton and Leibniz provided were the laws of differentiation and integration, second and higher derivatives, and the notion of an approximating polynomial series. By Newton's time, the fundamental theorem of calculus was known.

When Newton and Leibniz first published their results, there was great controversy over which mathematician (and therefore which country) deserved credit. Newton derived his results first (later to be published in his *Method of Fluxions*), but Leibniz published his "Nova Methodus pro Maximis et Minimis" first. Newton claimed Leibniz stole ideas from his unpublished notes, which Newton had shared with a few members of the Royal Society. This controversy divided English-speaking mathematicians from continental European mathematicians for many years, to the detriment of English mathematics. A careful examination of the papers of Leibniz and Newton shows that they arrived at their results independently, with Leibniz starting first with integration and Newton with differentiation. It is Leibniz, however, who gave the new discipline its name. Newton called his calculus "the science of fluxions".

Since the time of Leibniz and Newton, many mathematicians have contributed to the continuing development of calculus. One of the first and most complete works on both infinitesimal and integral calculus was written in 1748 by Maria Gaetana Agnesi.[17][18]

In calculus, *foundations* refers to the rigorous development of the subject from axioms and definitions. In early calculus the use of infinitesimal quantities was thought unrigorous, and was fiercely criticized by a number of authors, most notably Michel Rolle and Bishop Berkeley. Berkeley famously described infinitesimals as the ghosts of departed quantities in his book *The Analyst* in 1734. Working out a rigorous foundation for calculus occupied mathematicians for much of the century following Newton and Leibniz, and is still to some extent an active area of research today.

Several mathematicians, including Maclaurin, tried to prove the soundness of using infinitesimals, but it would not be until 150 years later when, due to the work of Cauchy and Weierstrass, a way was finally found to avoid mere "notions" of infinitely small quantities.[19] The foundations of differential and integral calculus had been laid. In Cauchy's *Cours d'Analyse*, we find a broad range of foundational approaches, including a definition of continuity in terms of infinitesimals, and a (somewhat imprecise) prototype of an (ε, δ)-definition of limit in the definition of differentiation.[20] In his work Weierstrass formalized the concept of limit and eliminated infinitesimals (although his definition can actually validate nilsquare infinitesimals). Following the work of Weierstrass, it eventually became common to base calculus on limits instead of infinitesimal quantities, though the subject is still occasionally called "infinitesimal calculus". Bernhard Riemann used these ideas to give a precise definition of the integral. It was also during this period that the ideas of calculus were generalized to Euclidean space and the complex plane.

In modern mathematics, the foundations of calculus are included in the field of real analysis, which contains full definitions and proofs of the theorems of calculus. The reach of calculus has also been greatly extended. Henri Lebesgue invented measure theory and used it to define integrals of all but the most pathological functions. Laurent Schwartz introduced distributions, which can be used to take the derivative of any function whatsoever.

Limits are not the only rigorous approach to the foundation of calculus. Another way is to use Abraham Robinson's non-standard analysis. Robinson's approach, developed in the 1960s, uses technical machinery from mathematical logic to augment the real number system with infinitesimal and infinite numbers, as in the original Newton-Leibniz conception. The resulting numbers are called hyperreal numbers, and they can be used to give a Leibniz-like development of the usual rules of calculus. There is also smooth infinitesimal analysis, which differs from non-standard analysis in that it mandates neglecting higher power infinitesimals during derivations.

While many of the ideas of calculus had been developed earlier in Greece, China, India, Iraq, Persia, and Japan, the use of calculus began in Europe, during the 17th century, when Isaac Newton and Gottfried Wilhelm Leibniz built on the work of earlier mathematicians to introduce its basic principles. The development of calculus was built on earlier concepts of instantaneous motion and area underneath curves.

Calculus is also used to gain a more precise understanding of the nature of space, time, and motion. For centuries, mathematicians and philosophers wrestled with paradoxes involving division by zero or sums of infinitely many numbers. These questions arise in the study of motion and area. The ancient Greek philosopher Zeno of Elea gave several famous examples of such paradoxes. Calculus provides tools, especially the limit and the infinite series, which resolve the paradoxes.

### Limits and infinitesimalsEdit

Calculus is usually developed by working with very small quantities. Historically, the first method of doing so was by infinitesimals. These are objects which can be treated like real numbers but which are, in some sense, "infinitely small". For example, an infinitesimal number could be greater than 0, but less than any number in the sequence 1, 1/2, 1/3, ... and thus less than any positive real number. From this point of view, calculus is a collection of techniques for manipulating infinitesimals. The symbols *dx* and *dy* were taken to be infinitesimal, and the derivative d y / d x {\displaystyle dy/dx}

was simply their ratio.

The infinitesimal approach fell out of favor in the 19th century because it was difficult to make the notion of an infinitesimal precise. However, the concept was revived in the 20th century with the introduction of non-standard analysis and smooth infinitesimal analysis, which provided solid foundations for the manipulation of infinitesimals.

In the 19th century, infinitesimals were replaced by the epsilon, delta approach to limits. Limits describe the value of a function at a certain input in terms of its values at a nearby input. They capture small-scale behavior in the context of the real number system. In this treatment, calculus is a collection of techniques for manipulating certain limits. Infinitesimals get replaced by very small numbers, and the infinitely small behavior of the function is found by taking the limiting behavior for smaller and smaller numbers. Limits were the first way to provide rigorous foundations for calculus, and for this reason they are the standard approach.

### Differential calculusEdit

Main article: Differential calculus

Tangent line at (*x*, *f*(*x*)). The derivative *f′*(*x*) of a curve at a point is the slope (rise over run) of the line tangent to that curve at that point.

Differential calculus is the study of the definition, properties, and applications of the derivative of a function. The process of finding the derivative is called *differentiation*. Given a function and a point in the domain, the derivative at that point is a way of encoding the small-scale behavior of the function near that point. By finding the derivative of a function at every point in its domain, it is possible to produce a new function, called the *derivative function* or just the *derivative* of the original function. In mathematical jargon, the derivative is a linear operator which inputs a function and outputs a second function. This is more abstract than many of the processes studied in elementary algebra, where functions usually input a number and output another number. For example, if the doubling function is given the input three, then it outputs six, and if the squaring function is given the input three, then it outputs nine. The derivative, however, can take the squaring function as an input. This means that the derivative takes all the information of the squaring function—such as that two is sent to four, three is sent to nine, four is sent to sixteen, and so on—and uses this information to produce another function. (The function it produces turns out to be the doubling function.)

The most common symbol for a derivative is an apostrophe-like mark called prime. Thus, the derivative of the function of *f* is *f′*, pronounced "f prime." For instance, if *f*(*x*) = *x*2 is the squaring function, then *f′*(*x*) = 2*x* is its derivative, the doubling function.

If the input of the function represents time, then the derivative represents change with respect to time. For example, if *f* is a function that takes a time as input and gives the position of a ball at that time as output, then the derivative of *f* is how the position is changing in time, that is, it is the velocity of the ball.

If a function is linear (that is, if the graph of the function is a straight line), then the function can be written as *y* = *mx* + *b*, where *x* is the independent variable, *y* is the dependent variable, *b* is the *y*-intercept, and:

m = rise run = change in y change in x = Δ y Δ x . {\displaystyle m={\frac {\text{rise}}{\text{run}}}={\frac {{\text{change in }}y}{{\text{change in }}x}}={\frac {\Delta y}{\Delta x}}.}

This gives an exact value for the slope of a straight line. If the graph of the function is not a straight line, however, then the change in *y* divided by the change in *x* varies. Derivatives give an exact meaning to the notion of change in output with respect to change in input. To be concrete, let *f* be a function, and fix a point *a* in the domain of *f*. (*a*, *f*(*a*)) is a point on the graph of the function. If *h* is a number close to zero, then *a* + *h* is a number close to *a*. Therefore, (*a* + *h*, *f*(*a* + *h*)) is close to (*a*, *f*(*a*)). The slope between these two points is

m = f ( a + h ) − f ( a ) ( a + h ) − a = f ( a + h ) − f ( a ) h . {\displaystyle m={\frac {f(a+h)-f(a)}{(a+h)-a}}={\frac {f(a+h)-f(a)}{h}}.}

This expression is called a *difference quotient*. A line through two points on a curve is called a *secant line*, so *m* is the slope of the secant line between (*a*, *f*(*a*)) and (*a* + *h*, *f*(*a* + *h*)). The secant line is only an approximation to the behavior of the function at the point *a* because it does not account for what happens between *a* and *a* + *h*. It is not possible to discover the behavior at *a* by setting *h* to zero because this would require dividing by zero, which is undefined. The derivative is defined by taking the limit as *h* tends to zero, meaning that it considers the behavior of *f* for all small values of *h* and extracts a consistent value for the case when *h* equals zero:

lim h → 0 f ( a + h ) − f ( a ) h . {\displaystyle \lim _{h\to 0}{f(a+h)-f(a) \over {h}}.}

Geometrically, the derivative is the slope of the tangent line to the graph of *f* at *a*. The tangent line is a limit of secant lines just as the derivative is a limit of difference quotients. For this reason, the derivative is sometimes called the slope of the function *f*.

Here is a particular example, the derivative of the squaring function at the input 3. Let *f*(*x*) = *x*2 be the squaring function.

The derivative *f′*(*x*) of a curve at a point is the slope of the line tangent to that curve at that point. This slope is determined by considering the limiting value of the slopes of secant lines. Here the function involved (drawn in red) is *f*(*x*) = *x*3 − *x*. The tangent line (in green) which passes through the point (−3/2, −15/8) has a slope of 23/4. Note that the vertical and horizontal scales in this image are different.

f ′ ( 3 ) = lim h → 0 ( 3 + h ) 2 − 3 2 h = lim h → 0 9 + 6 h + h 2 − 9 h = lim h → 0 6 h + h 2 h = lim h → 0 ( 6 + h ) = 6. {\displaystyle {\begin{aligned}f'(3)&=\lim _{h\to 0}{(3+h)^{2}-3^{2} \over {h}}\\&=\lim _{h\to 0}{9+6h+h^{2}-9 \over {h}}\\&=\lim _{h\to 0}{6h+h^{2} \over {h}}\\&=\lim _{h\to 0}(6+h)\\&=6.\end{aligned}}}

The slope of the tangent line to the squaring function at the point (3, 9) is 6, that is to say, it is going up six times as fast as it is going to the right. The limit process just described can be performed for any point in the domain of the squaring function. This defines the *derivative function* of the squaring function, or just the *derivative* of the squaring function for short. A similar computation to the one above shows that the derivative of the squaring function is the doubling function.

### Leibniz notationEdit

A common notation, introduced by Leibniz, for the derivative in the example above is

y = x 2 d y d x = 2 x . {\displaystyle {\begin{aligned}y&=x^{2}\\{\frac {dy}{dx}}&=2x.\end{aligned}}}

In an approach based on limits, the symbol *dy*/*dx* is to be interpreted not as the quotient of two numbers but as a shorthand for the limit computed above. Leibniz, however, did intend it to represent the quotient of two infinitesimally small numbers, *dy* being the infinitesimally small change in *y* caused by an infinitesimally small change *dx* applied to *x*. We can also think of *d*/*dx* as a differentiation operator, which takes a function as an input and gives another function, the derivative, as the output. For example:

d d x ( x 2 ) = 2 x . {\displaystyle {\frac {d}{dx}}(x^{2})=2x.}

In this usage, the *dx* in the denominator is read as "with respect to *x*". Even when calculus is developed using limits rather than infinitesimals, it is common to manipulate symbols like *dx* and *dy* as if they were real numbers; although it is possible to avoid such manipulations, they are sometimes notationally convenient in expressing operations such as the total derivative.

### Integral calculusEdit

Main article: Integral

*Integral calculus* is the study of the definitions, properties, and applications of two related concepts, the *indefinite integral* and the *definite integral*. The process of finding the value of an integral is called *integration*. In technical language, integral calculus studies two related linear operators.

The *indefinite integral*, also known as the *antiderivative*, is the inverse operation to the derivative. *F* is an indefinite integral of *f* when *f* is a derivative of *F*. (This use of lower- and upper-case letters for a function and its indefinite integral is common in calculus.)

The *definite integral* inputs a function and outputs a number, which gives the algebraic sum of areas between the graph of the input and the x-axis. The technical definition of the definite integral involves the limit of a sum of areas of rectangles, called a Riemann sum.

A motivating example is the distances traveled in a given time.

D i s t a n c e = S p e e d ⋅ T i m e {\displaystyle \mathrm {Distance} =\mathrm {Speed} \cdot \mathrm {Time} }

If the speed is constant, only multiplication is needed, but if the speed changes, a more powerful method of finding the distance is necessary. One such method is to approximate the distance traveled by breaking up the time into many short intervals of time, then multiplying the time elapsed in each interval by one of the speeds in that interval, and then taking the sum (a Riemann sum) of the approximate distance traveled in each interval. The basic idea is that if only a short time elapses, then the speed will stay more or less the same. However, a Riemann sum only gives an approximation of the distance traveled. We must take the limit of all such Riemann sums to find the exact distance traveled.

Constant Velocity

Integration can be thought of as measuring the area under a curve, defined by *f*(*x*), between two points (here *a* and *b*).

When velocity is constant, the total distance traveled over the given time interval can be computed by multiplying velocity and time. For example, travelling a steady 50 mph for 3 hours results in a total distance of 150 miles. In the diagram on the left, when constant velocity and time are graphed, these two values form a rectangle with height equal to the velocity and width equal to the time elapsed. Therefore, the product of velocity and time also calculates the rectangular area under the (constant) velocity curve. This connection between the area under a curve and distance traveled can be extended to *any* irregularly shaped region exhibiting a fluctuating velocity over a given time period. If *f*(*x*) in the diagram on the right represents speed as it varies over time, the distance traveled (between the times represented by *a* and *b*) is the area of the shaded region *s*.

To approximate that area, an intuitive method would be to divide up the distance between *a* and *b* into a number of equal segments, the length of each segment represented by the symbol Δ*x*. For each small segment, we can choose one value of the function *f*(*x*). Call that value *h*. Then the area of the rectangle with base Δ*x* and height *h* gives the distance (time Δ*x* multiplied by speed *h*) traveled in that segment. Associated with each segment is the average value of the function above it, *f*(*x*) = *h*. The sum of all such rectangles gives an approximation of the area between the axis and the curve, which is an approximation of the total distance traveled. A smaller value for Δ*x* will give more rectangles and in most cases a better approximation, but for an exact answer we need to take a limit as Δ*x* approaches zero.

The symbol of integration is ∫ {\displaystyle \int }

, an elongated *S* (the *S* stands for "sum"). The definite integral is written as:

∫ a b f ( x ) d x . {\displaystyle \int _{a}^{b}f(x)\,dx.}

and is read "the integral from *a* to *b* of *f*-of-*x* with respect to *x*." The Leibniz notation *dx* is intended to suggest dividing the area under the curve into an infinite number of rectangles, so that their width Δ*x* becomes the infinitesimally small *dx*. In a formulation of the calculus based on limits, the notation

∫ a b ⋯ d x {\displaystyle \int _{a}^{b}\cdots \,dx}

is to be understood as an operator that takes a function as an input and gives a number, the area, as an output. The terminating differential, *dx*, is not a number, and is not being multiplied by *f*(*x*), although, serving as a reminder of the Δ*x* limit definition, it can be treated as such in symbolic manipulations of the integral. Formally, the differential indicates the variable over which the function is integrated and serves as a closing bracket for the integration operator.

The indefinite integral, or antiderivative, is written:

∫ f ( x ) d x . {\displaystyle \int f(x)\,dx.}

Functions differing by only a constant have the same derivative, and it can be shown that the antiderivative of a given function is actually a family of functions differing only by a constant. Since the derivative of the function *y* = *x*2 + *C*, where *C* is any constant, is *y′* = 2*x*, the antiderivative of the latter given by:

∫ 2 x d x = x 2 + C . {\displaystyle \int 2x\,dx=x^{2}+C.}

The unspecified constant *C* present in the indefinite integral or antiderivative is known as the constant of integration.

### Fundamental theoremEdit

Main article: Fundamental theorem of calculus

The fundamental theorem of calculus states that differentiation and integration are inverse operations. More precisely, it relates the values of antiderivatives to definite integrals. Because it is usually easier to compute an antiderivative than to apply the definition of a definite integral, the fundamental theorem of calculus provides a practical way of computing definite integrals. It can also be interpreted as a precise statement of the fact that differentiation is the inverse of integration.

The fundamental theorem of calculus states: If a function *f* is continuous on the interval [*a*, *b*] and if *F* is a function whose derivative is *f* on the interval (*a*, *b*), then

∫ a b f ( x ) d x = F ( b ) − F ( a ) . {\displaystyle \int _{a}^{b}f(x)\,dx=F(b)-F(a).}

Furthermore, for every *x* in the interval (*a*, *b*),

d d x ∫ a x f ( t ) d t = f ( x ) . {\displaystyle {\frac {d}{dx}}\int _{a}^{x}f(t)\,dt=f(x).}

This realization, made by both Newton and Leibniz, who based their results on earlier work by Isaac Barrow, was key to the proliferation of analytic results after their work became known. The fundamental theorem provides an algebraic method of computing many definite integrals—without performing limit processes—by finding formulas for antiderivatives. It is also a prototype solution of a differential equation. Differential equations relate an unknown function to its derivatives, and are ubiquitous in the sciences.

*Source * en.m.wikipedia.org