 Differential (infinitesimal)

For other uses of differential in calculus, see differential (calculus), and for more general meanings, see differential.
In calculus, a differential is traditionally an infinitesimally small change in a variable. For example, if x is a variable, then a change in the value of x is often denoted Δx (or δx when this change is considered to be small). The differential dx represents such a change, but is infinitely small. Although, as stated, it is not a precise mathematical concept, it is extremely useful intuitively, and there are a number of ways to make the notion mathematically precise.
The key property of the differential is that if y is a function of x, then the differential dy of y is related to dx by the formula
where dy/dx denotes the derivative of y with respect to x. This formula summarizes the intuitive idea that the derivative of y with respect to x is the limit of the ratio of differences Δy/Δx as Δx becomes infinitesimally small.
There are several approaches for making the notion of differentials mathematically precise.
 Differentials as linear maps. This approach underlies the definition of the derivative and the exterior derivative in differential geometry.^{[1]}
 Differentials as nilpotent elements of commutative rings. This approach is popular in algebraic geometry.^{[2]}
 Differentials in smooth models of set theory. This approach is known as synthetic differential geometry or smooth infinitesimal analysis and is closely related to the algebraic geometric approach, except that ideas from topos theory are used to hide the mechanisms by which nilpotent infinitesimals are introduced.^{[3]}
 Differentials as infinitesimals in hyperreal number systems, which are extensions of the real numbers which contain invertible infinitesimals and infinitely large numbers. This is the approach of nonstandard analysis pioneered by Abraham Robinson.^{[4]}
These approaches are very different from each other, but they have in common the idea to be quantitative, i.e., to say not just that a differential is infinitesimally small, but how small it is.
Contents
History and usage
See also: History of calculusInfinitesimal quantities played a significant role in the development of calculus. Archimedes used them, even though he didn't believe that arguments involving infinitesimals were rigorous.^{[5]} Isaac Newton referred to them as fluxions. However, it was Gottfried Leibniz who coined the term differentials for infinitesimal quantities, and introduced the notation for them which is still used today.
In Leibniz's notation, if x is a variable quantity, then dx denotes an infinitesimally small change in the variable x. Thus, if y is a function of x, then the derivative of y with respect to x is often denoted , which would otherwise be denoted (in the notation of Newton or Lagrange) or y'(x). The use of differentials in this form attracted much criticism, for instance in the famous pamphlet The Analyst by Bishop Berkeley. Nevertheless the notation has remained popular because it suggests strongly the idea that the derivative of a function y(x) is its slope, which may be obtained by taking the limit of the ratio of the change in y over the change in x, as the change in x becomes arbitrarily small. Differentials are also compatible with dimensional analysis, where a differential such as dx has the same dimensions as the variable x.
Differentials are also used in the notation for integrals because an integral can be regarded as an infinite sum of infinitesimally small quantities: the area under a graph is obtained by subdividing the graph into infinitesimally thin strips and summing their areas. In an expression such as
the integral sign (which is a modified long s) denotes the infinite sum, f(x) denotes the 'height' of a thin strip, and the differential dx denotes its arbitrarily thin width.
Differentials as linear maps
There is a simple way to make precise sense of differentials by regarding them as linear maps. One way to explain this point of view is to regard the variable x in an expression such as f(x) as a function on the real line, the standard coordinate or identity map which takes a real number p to itself (x(p) = p): then f(x) denotes the composite of f with x, whose value at p is f(x(p)). The differential df is then a function on the real line whose value at p (usually denoted df_{p}) is not a number, but a linear map from to . Since a linear map from to is given by a 1×1 matrix, it is essentially the same thing as a number, but the change in the point of view allows us to think of df_{p} as an infinitesimal and compare it with the standard infinitesimal dx_{p} which is again just the identity map from to (a 1×1 matrix with entry 1). It may seem fanciful to regard the identity map as an infinitesimal, but it does at least have the property that if is very small, then is very small. The differential df_{p} has the same property, because it is just a multiple of dx_{p}, and this multiple is the derivative by definition. We therefore obtain that , and hence . Thus we recover the idea that is the ratio of the differentials df and dx.
This would just be a trick were it not for the fact that:
 it captures the idea of the derivative of f at p as the best linear approximation to f at p;
 it has many generalizations.
For instance if f is a function from to then we say f is differentiable^{[6]} at if there is a linear map df_{p} from to such that for any , there is a neighbourhood N(p) of p such that for :
We can now use the same trick as in the one dimensional case, and think of the expression as the composite of f with the standard coordinates on (so that x^{j}(p) is the jth component of ). Then the differentials (dx^{1})_{p}, (dx^{2})_{p}, (dx^{n})_{p} (at a point p) form a basis for the vector space of linear maps from to and therefore, if f is differentiable at p, we can write df_{p} as a linear combination of these basis elements:
The coefficients D_{j}f(p) are (by definition) the partial derivatives of f at p with respect to x^{1}, x^{2}, …, x^{n}. Hence, if f is differentiable on all of , we can write, more concisely:
In the onedimensional case this becomes
as before.
This idea generalizes straightforwardly to functions from to . Furthermore, it has the decisive advantage over other definitions of the derivative that it is invariant under changes of coordinates. This means that the same idea can be used to define the differential of smooth maps between smooth manifolds.
Aside: Note that the existence of all the partial derivatives of f(x) at x is a necessary condition for the existence of a differential at x. However it is not a sufficient condition. For counterexamples, see Gâteaux derivative.
Algebraic geometry
In algebraic geometry, differentials and other infinitesimal notions are handled in a very explicit way by accepting that the coordinate ring or structure sheaf of a space may contain nilpotent elements. The simplest example is the ring of dual numbers R[ε], where ε^{2} = 0.
This can be motivated by the algebrogeometric point of view on the derivative of a function f from R to R at a point p. For this, note first that f−f(p)1 (where 1 is the identity function) belongs to the ideal I_{p} of functions on R which vanish at p. If the derivative f vanishes at p, then f−f(p)1 belongs to the square I_{p}^{2} of this ideal. Hence the derivative of f at p may be captured by the equivalence class [f−f(p)1] in the quotient space I_{p}/I_{p}^{2}, and the 1jet of f (which encodes its value and its first derivative) is the equivalence class of f in the space of all functions modulo I_{p}^{2}. Algebraic geometers regard this equivalence class as the restriction of f to a thickened version of the point p whose coordinate ring is not R (which is the quotient space of functions on R modulo I_{p}) but R[ε] which is the quotient space of functions on R modulo I_{p}^{2}. Such a thickened point is a simple example of a scheme.^{[2]}
Synthetic differential geometry
A third approach to infinitesimals is the method of synthetic differential geometry^{[7]} or smooth infinitesimal analysis.^{[8]} This is closely related to the algebraicgeometric approach, except that the infinitesimals are more implicit and intuitive. The main idea of this approach is to replace the category of sets with another category of smoothly varying sets which is a topos. In this category, one can define the real numbers, smooth functions, and so on, but the real numbers automatically contain nilpotent infinitesimals, so these do not need to be introduced by hand as in the algebraic geometric approach. However the logic in this new category is not identical to the familiar logic of the category of sets: in particular, the law of the excluded middle does not hold. This means that settheoretic mathematical arguments only extend to smooth infinitesimal analysis if they are constructive (e.g., do not use proof by contradiction). Some regard this disadvantage as a positive thing, since it forces one to find constructive arguments wherever they are available.
Nonstandard analysis
The final approach to infinitesimals again involves extending the real numbers, but in a less drastic way. In the nonstandard analysis approach there are no nilpotent infinitesimals, only invertible ones, which may be viewed as the reciprocals of infinitely large numbers.^{[4]} Such extensions of the real numbers may be constructed explicitly using equivalence classes of sequences of real numbers, so that, for example, the sequence (1, 1/2, 1/3, ..., 1/n, ...) represents an infinitesimal. The firstorder logic of this new set of hyperreal numbers is the same as the logic for the usual real numbers, but the completeness axiom (which involves secondorder logic) does not hold. Nevertheless, this suffices to develop an elementary and quite intuitive approach to calculus using infinitesimals, see transfer principle.
Notes
 ^ Darling 1994.
 ^ ^{a} ^{b} Eisenbud & Harris 1998.
 ^ See Kock 2006 and Moerdijk & Reyes 1991.
 ^ ^{a} ^{b} See Robinson 1996 and Keisler 1986.
 ^ Boyer 1991.
 ^ See, for instance, Apostol 1967.
 ^ See Kock 2006 and Lawvere 1968.
 ^ See Moerdijk & Reyes 1991 and Bell 1998.
References
 Apostol, Tom M. (1967), Calculus (2nd ed.), Wiley, ISBN 0471000051 and 0471000078.
 Bell, John L. (1998), Invitation to Smooth Infinitesimal Analysis, http://publish.uwo.ca/~jbell/invitation%20to%20SIA.pdf.
 Boyer, Carl B. (1991), "Archimedes of Syracuse", A History of Mathematics (2nd ed.), John Wiley & Sons, Inc., ISBN 0471543977.
 Darling, R. W. R. (1994), Differential forms and connections, Cambridge, UK: Cambridge University Press, ISBN 0521468000.
 Eisenbud, David; Harris, Joe (1998), The Geometry of Schemes, SpringerVerlag, ISBN 0387986375
 Keisler, H. Jerome (1986), Elementary Calculus: An Infinitesimal Approach (2nd ed.), http://www.math.wisc.edu/~keisler/calc.html.
 Kock, Anders (2006), Synthetic Differential Geometry (2nd ed.), Cambridge University Press, http://home.imf.au.dk/kock/sdg99.pdf.
 Lawvere, F.W. (1968), Outline of synthetic differential geometry (published 1998), http://www.acsu.buffalo.edu/~wlawvere/SDG_Outline.pdf.
 Moerdijk, I.; Reyes, G.E. (1991), Models for Smooth Infinitesimal Analysis, SpringerVerlag.
 Robinson, Abraham (1996), Nonstandard analysis, Princeton University Press, ISBN 9780691044903.
See also
Infinitesimals History Adequality · Infinitesimal calculus · Leibniz's notation · Integral sign · Criticism of nonstandard analysis · The Analyst · The Method of Mechanical Theorems · Cavalieri's principleRelated branches of mathematics Formalizations of infinitesimal quantities Individual concepts Standard part function · Transfer principle · Hyperinteger · Increment theorem · Monad · Internal set · LeviCivita field · Hyperfinite set · Law of Continuity · OverspillScientists Infinitesimals in physics and engineering Textbooks Analyse des Infiniment Petits · Elementary CalculusCategories:
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