User:Pashute/E (mathematical constant)

"Euler's number" redirects here. For γ, a constant in number theory, see Euler–Mascheroni constant. For other uses, see List of things named after Leonhard Euler § Euler's numbers.

Functions f(x) = a^x are shown for several values of a. e is the unique value of a, such that the derivative of f(x) = a^x at the point x = 0 is equal to 1. The blue curve illustrates this case, e^x. For comparison, functions 2^x (dotted curve) and 4^x (dashed curve) are shown; they are not tangent to the line of slope 1 and y-intercept 1 (red).

The number e is an important mathematical constant approximately equal to 2.71828,

e is the base rate of continuous growth which is any growing process in which each newly produced growth, itself grows at the same rate as the original growing object. Compound interest and Cell tissue growth are examples of continuous growth, as are many processes occurring in nature, and studied in economics, statistics, physics, chemistry and biology.^[1]

e^x is the resulting quantity from continuous growth within x periods of time, at a rate of 100% initial growth (meaning that it would double itself withing the period of time, without the additional growth of the produced growth itself), so e is the resulting quantity after a single period of time.

e can be calculated, and defined mathematically in many ways.^[2]

Its definition stemming from continuous growth is:

$e=\lim _{n\to \infty }(1+{\frac {1}{n}})^{n}$

Important to calculus, e can also be defined as the base of the logarithmic function log_ex which has a derivative slope of 1/x. That logarithmic function, which has a derivative of 1/x, is defined as the natural logarithm, marked as ln(x), and is called so because of abundantly occuring continuous growth in nature.

${\frac {\partial }{\partial x}}log_{e}x={\frac {\partial }{\partial x}}lnx={\frac {1}{x}}$

e is also the base of the exponential function e^x with of a derivative slope which is defined by the exponential function itself:

${\frac {\partial }{\partial x}}e^{x}=e^{x}$

The numerical value of e truncated to 50 decimal places is

2.71828182845904523536028747135266249775724709369995... (sequence A001113 in the OEIS).

Definitions and value calculation

The value of e can be calculated in many ways, or: the constant e can be defined mathematically in many ways.

Definition by sequence of additions

The most commonly used calculation of the value of e, also used as a common mathematical definition of e, and stemming from its definition in compound interest, is the limit value of (1 + 1/n)ⁿ as n approaches infinity:

$e=\lim _{n\to \infty }(1+{\frac {1}{n}})^{n}$

which is equivalent to the sum of the series of additions in continual growth: zzz

Definition by series

e can also be calculated as the sum of the infinite series

$e=1+{\frac {1}{1}}+{\frac {1}{1\cdot 2}}+{\frac {1}{1\cdot 2\cdot 3}}+{\frac {1}{1\cdot 2\cdot 3\cdot 4}}+\cdots$

Definition by derivative of the exponential function

e can also be defined as:
The unique real number, such that the value of the derivative (slope of the tangent line) of the function f(x) = e^x at the point x = 0 is equal to 1.

$f'(e^{x})_{x=0}=1$

The function e^x so defined is called the exponential function, and its inverse is the natural logarithm, or logarithm to base e.

Definition by integration of 1/x and the natural logarithm

The natural logarithm of a positive number k can also be defined directly as the area under the curve y = 1/x between x = 1 and x = k, in which case, e is the number whose natural logarithm is 1. There are also more alternative characterizations.

Other names

Sometimes called Euler's number after the Swiss mathematician Leonhard Euler, e is not to be confused with γ—the Euler–Mascheroni constant, sometimes called simply Euler's constant.

The number e is also known as Napier's constant, but Euler's choice of this symbol is said to have been retained in his honor.

Continuous growth

Continuous growth at a constant rate, is a process where:

• Starting with an initial quantity
• This quantity is reproducing itself within a period of time, at a constant rate
• And every newly introduced part of this initial quantity, is reproducing itself as well, at the same rate, immediately as it itself has been produced.

Continuous growth is found in many natural occurring processes, in statistics and in economics, and was discovered by studying compound interest.

For example, starting off initially with a crystal of 1 gram (1000 milligrams), that is growing at a constant rate, which would, within 1 second (or 1000 milliseconds) double itself in size to 2 grams. Each millisecond, 1 milligram is added to the crystal so that after 1000 milliseconds we would have the extra expected 1000 milligrams. But since the crystal grows continually, after the first millisecond, the additional milligram grown till now is itself growing (and would double itself within a full second). Thus, after 2 milliseconds, we have:

• The initial 1 gram (result = 1 + ...)
• and the expected milligram from the initial crystal, added at stage 1: ...+ 1/1000_{of original} so: ... + 0.001
• and the expected milligram from the initial crystal, added now: ...+ 1/1000_{of original} so: ... + 0.001
• and an extra growth from the first additional growth (... + 1/1000 × 0.001_{a_1}) = ... + 0.00001)

Each millisecond adds a small extra amount over the original growth, so that at the end of a whole second, instead of receiving 2, we receive a bit more.

The resulting quantity after continuous growth at any rate and at any number of periods can be figured by e^x = e^pr, where p is the number of periods and r is the rate of growth.^[3]

Thus, in one single period, e^x represents the final quantity at rate x. (x = 1 means 100% growth, where the initial quantity is doubling itself within the period).^[4]

Also, at a constant 100% rate of growth, e^x represents the final quantity after x periods of time.^[5]

Since e is the base of the natural logarithm, x = ln(y) will find the number of periods of growth x, for a given quantity y growing at the rate of 100% per period. (y=e^x)

Continuous growth calculation

During continuous growth a small quantity of 1⁄n × the current quantity is being added to the existing quantity, in each and every fraction of the time.

• n is the number of stages within the period.

In a period with four stages, and starting with the initial quantity of 1, growing at the rate of 100%:

• At each stage we add a₁ = 1/4 = 0.25.
• At each stage starting with stage n=2, we add a₂₊ = 1/4 × a₁ = 1/16 = 0.0625. This is the growth of the addition to stage 1.
• At each stage starting with stage n=3, we add a₃₊ = 1/4 × a₂ = 1/32 = 0.03125. This is the growth of the addition to stage 2.
• At the last stage n=4, we add a₄₊ = 1/4 × a₃ = 1/64 = 0.015625.

So the result is:

• result = 1 + (4 × 1/4) + (3 × 1/16) + (2 × 1/32) + 1/64 = 2+17/64 = 2.265625

For continuous growth we define n as approaching infinity, and 1⁄n represents an infinitely small stage in time.

A process doubling itself within the period of time is said to grow at a 100% rate, and in each fractional stage (of time 1⁄n) it is growing by 1⁄n × c where c is the current quantity until this stage.

We start with the initial quantity, {{{1}}}.

• At stage n=1 we add a₁ = 1⁄n × i₀ = 1⁄n}}, the growth of the initial quantity.
• At stage n=2 we add a₂ = 1⁄n × (1 + a₁ = 1⁄n + 1⁄n² }}
• At stage n=3 we add a₃ = 1⁄n × (1 + a₂ = 1⁄n + 1⁄n² + 1⁄n³}}

At stage n we have the resulting growth:

$e=1+n\cdot {\frac {1}{n}}+(n-1){\frac {1}{n}}^{2}+...+2{\frac {1}{n}}^{n-1}+{\frac {1}{n}}^{n}$

which is the same as:

$e=\lim _{n\to \infty }(1+{\frac {1}{n}})^{n}$

During each fractional stage in time, the given quantity is more than doubling itself, because the extra growth is doubling itself as well, approaching in total 2.72 times the original quantity.

Importance and Features

The number e is of eminent importance in mathematics, alongside 0, 1, π and i. All five of these numbers play important and recurring roles across mathematics, and are the five constants appearing in one formulation of Euler's identity.

Like the constant π, e is irrational: it is not a ratio of integers; and it is transcendental: it is not a root of any non-zero polynomial with rational coefficients.

History

The first references to the constant were published in 1618 in the table of an appendix of a work on logarithms by John Napier. However, this did not contain the constant itself, but simply a list of logarithms calculated from the constant. It is assumed that the table was written by William Oughtred. The discovery of the constant itself is credited to Jacob Bernoulli, who attempted to find the value of the following expression (which is in fact e):

$\lim _{n\to \infty }\left(1+{\frac {1}{n}}\right)^{n}$

The first known use of the constant, represented by the letter b, was in correspondence from Gottfried Leibniz to Christiaan Huygens in 1690 and 1691. Leonhard Euler introduced the letter e as the base for natural logarithms, writing in a letter to Christian Goldbach of 25 November 1731. Euler started to use the letter e for the constant in 1727 or 1728, in an unpublished paper on explosive forces in cannons, and the first appearance of e in a publication was Euler's Mechanica (1736). While in the subsequent years some researchers used the letter c, e was more common and eventually became the standard.

Applications

Compound interest

The effect of earning 20% annual interest on an initial $1,000 investment at various compounding frequencies

Jacob Bernoulli discovered this constant by studying a question about compound interest:

An account starts with $1.00 and pays 100 percent interest per year. If the interest is credited once, at the end of the year, the value of the account at year-end will be $2.00. What happens if the interest is computed and credited more frequently during the year?

If the interest is credited twice in the year, the interest rate for each 6 months will be 50%, so the initial $1 is multiplied by 1.5 twice, yielding $1.00×1.5² = $2.25 at the end of the year. Compounding quarterly yields $1.00×1.25⁴ = $2.4414..., and compounding monthly yields $1.00×(1+1/12)¹² = $2.613035... If there are n compounding intervals, the interest for each interval will be 100%/n and the value at the end of the year will be $1.00×(1 + 1/n)ⁿ.

Bernoulli noticed that this sequence approaches a limit (the force of interest) with larger n and, thus, smaller compounding intervals. Compounding weekly (n = 52) yields $2.692597..., while compounding daily (n = 365) yields $2.714567..., just two cents more. The limit as n grows large is the number that came to be known as e; with continuous compounding, the account value will reach $2.7182818.... More generally, an account that starts at $1 and offers an annual interest rate of R will, after t years, yield e^Rt dollars with continuous compounding. (Here R is a fraction, so for 5% interest, R = 5/100 = 0.05)

Bernoulli trials

The number e itself also has applications to probability theory, where it arises in a way not obviously related to exponential growth. Suppose that a gambler plays a slot machine that pays out with a probability of one in n and plays it n times. Then, for large n (such as a million) the probability that the gambler will lose every bet is (approximately) 1/e. For n = 20 it is already 1/2.72.

This is an example of a Bernoulli trials process. Each time the gambler plays the slots, there is a one in one million chance of winning. Playing one million times is modelled by the binomial distribution, which is closely related to the binomial theorem. The probability of winning k times out of a million trials is;

${\binom {10^{6}}{k}}\left(10^{-6}\right)^{k}(1-10^{-6})^{10^{6}-k}.$

In particular, the probability of winning zero times (k = 0) is

$\left(1-{\frac {1}{10^{6}}}\right)^{10^{6}}.$

This is very close to the following limit for 1/e:

${\frac {1}{e}}=\lim _{n\to \infty }\left(1-{\frac {1}{n}}\right)^{n}.$

Derangements

Another application of e, also discovered in part by Jacob Bernoulli along with Pierre Raymond de Montmort is in the problem of derangements, also known as the hat check problem: n guests are invited to a party, and at the door each guest checks his hat with the butler who then places them into n boxes, each labelled with the name of one guest. But the butler does not know the identities of the guests, and so he puts the hats into boxes selected at random. The problem of de Montmort is to find the probability that none of the hats gets put into the right box. The answer is:

$p_{n}=1-{\frac {1}{1!}}+{\frac {1}{2!}}-{\frac {1}{3!}}+\cdots +{\frac {(-1)^{n}}{n!}}=\sum _{k=0}^{n}{\frac {(-1)^{k}}{k!}}.$

As the number n of guests tends to infinity, p_n approaches 1/e. Furthermore, the number of ways the hats can be placed into the boxes so that none of the hats is in the right box is n!/e rounded to the nearest integer, for every positive n.

Asymptotics

The number e occurs naturally in connection with many problems involving asymptotics. A prominent example is Stirling's formula for the asymptotics of the factorial function, in which both the numbers e and π enter:

$n!\sim {\sqrt {2\pi n}}\,\left({\frac {n}{e}}\right)^{n}.$

A particular consequence of this is

$e=\lim _{n\to \infty }{\frac {n}{\sqrt[{n}]{n!}}}$.

e in calculus

The natural log at (x-axis) e, ln(e), is equal to 1

The principal motivation for introducing the number e, particularly in calculus, is to perform differential and integral calculus with exponential functions and logarithms. A general exponential function y = a^x has derivative given as the limit:

${\frac {d}{dx}}a^{x}=\lim _{h\to 0}{\frac {a^{x+h}-a^{x}}{h}}=\lim _{h\to 0}{\frac {a^{x}a^{h}-a^{x}}{h}}=a^{x}\left(\lim _{h\to 0}{\frac {a^{h}-1}{h}}\right).$

The limit on the far right is independent of the variable x: it depends only on the base a. When the base is e, this limit is equal to one, and so e is symbolically defined by the equation:

${\frac {d}{dx}}e^{x}=e^{x}.$

Consequently, the exponential function with base e is particularly suited to doing calculus. Choosing e, as opposed to some other number, as the base of the exponential function makes calculations involving the derivative much simpler.

Another motivation comes from considering the base-a logarithm. Considering the definition of the derivative of log_a x as the limit:

${\frac {d}{dx}}\log _{a}x=\lim _{h\to 0}{\frac {\log _{a}(x+h)-\log _{a}(x)}{h}}={\frac {1}{x}}\left(\lim _{u\to 0}{\frac {1}{u}}\log _{a}(1+u)\right),$

where the substitution u = h/x was made in the last step. The last limit appearing in this calculation is again an undetermined limit that depends only on the base a, and if that base is e, the limit is one. So symbolically,

${\frac {d}{dx}}\log _{e}x={\frac {1}{x}}.$

The logarithm in this special base is called the natural logarithm and is represented as ln; it behaves well under differentiation since there is no undetermined limit to carry through the calculations.

There are thus two ways in which to select a special number a = e. One way is to set the derivative of the exponential function a^x to a^x, and solve for a. The other way is to set the derivative of the base a logarithm to 1/x and solve for a. In each case, one arrives at a convenient choice of base for doing calculus. In fact, these two solutions for a are actually the same, the number e.

Alternative characterizations

The area between the x-axis and the graph y = 1/x, between x = 1 and x = e is 1.

See also: Representations of e

Other characterizations of e are also possible: one is as the limit of a sequence, another is as the sum of an infinite series, and still others rely on integral calculus. So far, the following two (equivalent) properties have been introduced:

1. The number e is the unique positive real number such that

${\frac {d}{dt}}e^{t}=e^{t}.$

2. The number e is the unique positive real number such that

${\frac {d}{dt}}\log _{e}t={\frac {1}{t}}.$

The following three characterizations can be proven equivalent:

3. The number e is the limit

$e=\lim _{n\to \infty }\left(1+{\frac {1}{n}}\right)^{n}$

Similarly:

$e=\lim _{x\to 0}\left(1+x\right)^{\frac {1}{x}}$

4. The number e is the sum of the infinite series

$e=\sum _{n=0}^{\infty }{\frac {1}{n!}}={\frac {1}{0!}}+{\frac {1}{1!}}+{\frac {1}{2!}}+{\frac {1}{3!}}+{\frac {1}{4!}}+\cdots$

where n! is the factorial of n.

5. The number e is the unique positive real number such that

$\int _{1}^{e}{\frac {1}{t}}\,dt=1.$

Properties

Calculus

As in the motivation, the exponential function e^x is important in part because it is the unique nontrivial function (up to multiplication by a constant) which is its own derivative

${\frac {d}{dx}}e^{x}=e^{x}$

and therefore its own antiderivative as well:

${\begin{aligned}e^{x}&=\int _{-\infty }^{x}e^{t}\,dt\\[8pt]&=\int _{-\infty }^{0}e^{t}\,dt+\int _{0}^{x}e^{t}\,dt\\[8pt]&=1+\int _{0}^{x}e^{t}\,dt.\end{aligned}}$

Exponential-like functions

See also: Steiner's problem

The global maximum of ${\sqrt[{x}]{x}}$ occurs at x = e.

The global maximum for the function

$f(x)={\sqrt[{x}]{x}}$

occurs at x = e. Similarly, x = 1/e is where the global minimum occurs for the function

$f(x)=x^{x}\,$

defined for positive x. More generally, x = e^−1/n is where the global minimum occurs for the function

$\!\ f(x)=x^{x^{n}}$

for any n > 0. The infinite tetration

$x^{x^{x^{\cdot ^{\cdot ^{\cdot }}}}}$ or ^∞$x$

converges if and only if e^−e ≤ x ≤ e^1/e (or approximately between 0.0660 and 1.4447), due to a theorem of Leonhard Euler.

Number theory

The real number e is irrational. Euler proved this by showing that its simple continued fraction expansion is infinite. (See also Fourier's proof that e is irrational.)

Furthermore, by the Lindemann–Weierstrass theorem, e is transcendental, meaning that it is not a solution of any non-constant polynomial equation with rational coefficients. It was the first number to be proved transcendental without having been specifically constructed for this purpose (compare with Liouville number); the proof was given by Charles Hermite in 1873.

It is conjectured that e is normal, meaning that when e is expressed in any base the possible digits in that base are uniformly distributed (occur with equal probability in any sequence of given length).

Complex numbers

The exponential function e^x may be written as a Taylor series

$e^{x}=1+{x \over 1!}+{x^{2} \over 2!}+{x^{3} \over 3!}+\cdots =\sum _{n=0}^{\infty }{\frac {x^{n}}{n!}}$

Because this series keeps many important properties for e^x even when x is complex, it is commonly used to extend the definition of e^x to the complex numbers. This, with the Taylor series for sin and cos x, allows one to derive Euler's formula:

$e^{ix}=\cos x+i\sin x,\,\!$

which holds for all x. The special case with x = π is Euler's identity:

$e^{i\pi }=-1\,\!$

from which it follows that, in the principal branch of the logarithm,

$\log _{e}(-1)=i\pi .\,\!$

Furthermore, using the laws for exponentiation,

$(\cos x+i\sin x)^{n}=\left(e^{ix}\right)^{n}=e^{inx}=\cos(nx)+i\sin(nx),$

which is de Moivre's formula.

The expression

$\cos x+i\sin x\,$

is sometimes referred to as cis(x).

Differential equations

The general function

$y(x)=Ce^{x}\,$

is the solution to the differential equation:

$y'=y.\,$

Representations

Main article: List of representations of e

The number e can be represented as a real number in a variety of ways: as an infinite series, an infinite product, a continued fraction, or a limit of a sequence. The chief among these representations, particularly in introductory calculus courses is the limit

$\lim _{n\to \infty }\left(1+{\frac {1}{n}}\right)^{n},$

given above, as well as the series

$e=\sum _{n=0}^{\infty }{\frac {1}{n!}}$

given by evaluating the above power series for e^x at x = 1.

Less common is the continued fraction (sequence A003417 in the OEIS).

$e=[2;1,\mathbf {2} ,1,1,\mathbf {4} ,1,1,\mathbf {6} ,1,1,...,\mathbf {2n} ,1,1,...]=[1;\mathbf {0} ,1,1,\mathbf {2} ,1,1,\mathbf {4} ,1,1,...,\mathbf {2n} ,1,1,...],$

which written out looks like

$e=2+{\cfrac {1}{1+{\cfrac {1}{\mathbf {2} +{\cfrac {1}{1+{\cfrac {1}{1+{\cfrac {1}{\mathbf {4} +{\cfrac {1}{1+{\cfrac {1}{1+\ddots }}}}}}}}}}}}}}=1+{\cfrac {1}{\mathbf {0} +{\cfrac {1}{1+{\cfrac {1}{1+{\cfrac {1}{\mathbf {2} +{\cfrac {1}{1+{\cfrac {1}{1+{\cfrac {1}{\mathbf {4} +{\cfrac {1}{1+{\cfrac {1}{1+\ddots }}}}}}}}}}}}}}}}}}.$

This continued fraction for e converges three times as quickly:

$e=[1;0.5,12,5,28,9,44,13,\ldots ,4(4n-1),(4n+1),\ldots ],$

which written out looks like

$e=1+{\cfrac {2}{1+{\cfrac {1}{6+{\cfrac {1}{10+{\cfrac {1}{14+{\cfrac {1}{18+{\cfrac {1}{22+{\cfrac {1}{26+\ddots \,}}}}}}}}}}}}}}.$

Many other series, sequence, continued fraction, and infinite product representations of e have been developed.

Stochastic representations

In addition to exact analytical expressions for representation of e, there are stochastic techniques for estimating e. One such approach begins with an infinite sequence of independent random variables X₁, X₂..., drawn from the uniform distribution on [0, 1]. Let V be the least number n such that the sum of the first n samples exceeds 1:

$V=\min {\left\{n\mid X_{1}+X_{2}+\cdots +X_{n}>1\right\}}.$

Then the expected value of V is e: E(V) = e.

Known digits

The number of known digits of e has increased dramatically during the last decades. This is due both to the increased performance of computers and to algorithmic improvements.

Number of known decimal digits of e

Date	Decimal digits	Computation performed by
1748	23	Leonhard Euler
1853	137	William Shanks
1871	205	William Shanks
1884	346	J. Marcus Boorman
1949	2,010	John von Neumann (on the ENIAC)
1961	100,265	Daniel Shanks and John Wrench
1978	116,000	Stephen Gary Wozniak (on the Apple II)
1994 April 1	1,000,000	Robert Nemiroff & Jerry Bonnell
1999 November 21	1,250,000,000	Xavier Gourdon
2000 July 16	3,221,225,472	Colin Martin & Xavier Gourdon
2003 September 18	50,100,000,000	Shigeru Kondo & Xavier Gourdon
2007 April 27	100,000,000,000	Shigeru Kondo & Steve Pagliarulo
2009 May 6	200,000,000,000	Rajesh Bohara & Steve Pagliarulo
2010 July 5	1,000,000,000,000	Shigeru Kondo & Alexander J. Yee

In computer culture

In contemporary internet culture, individuals and organizations frequently pay homage to the number e.

For example, in the IPO filing for Google, in 2004, rather than a typical round-number amount of money, the company announced its intention to raise $2,718,281,828, which is e billion dollars to the nearest dollar. Google was also responsible for a billboard that appeared in the heart of Silicon Valley, and later in Cambridge, Massachusetts; Seattle, Washington; and Austin, Texas. It read "{first 10-digit prime found in consecutive digits of e}.com". Solving this problem and visiting the advertised web site (now defunct) led to an even more difficult problem to solve, which in turn led to Google Labs where the visitor was invited to submit a resume. The first 10-digit prime in e is 7427466391, which starts as late as at the 99th digit.

In another instance, the computer scientist Donald Knuth let the version numbers of his program Metafont approach e. The versions are 2, 2.7, 2.71, 2.718, and so forth. Similarly, the version numbers of his TeX program approach π.

Further reading

• Maor, Eli; e: The Story of a Number, ISBN 0-691-05854-7
• Commentary on Endnote 10 of the book Prime Obsession for another stochastic representation

External links

• An Intuitive Guide To Exponential Functions &e for the non-mathematician
• The number e to 1 million places and 2 and 5 million places (link obsolete)
• e Approximations – Wolfram MathWorld
• Earliest Uses of Symbols for Constants Jan. 13, 2008
• "The story of e", by Robin Wilson at Gresham College, 28 February 2007 (available for audio and video download)
• e Search Engine 2 billion searchable digits of e, π and √2

Category:Transcendental numbers Category:Mathematical constants *