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[[Image:Circle Area.svg|thumb|Area of the circle = π × area of the shaded square]]
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'''Pi''', denoted by the Greek letter '''π''', is a [[mathematical constant]] with the approximate value 3.14159. In [[Euclidean geometry]], π represents the proportion between the circumference and the diameter of any [[circle]], or equivalently, the proportion between a circle's area and the square of its radius. This proportion is also found in many other geometrical objects, such as spheres and cones. Pi has further uses in many other areas of mathematics.
{{dambigbox|text='''Pi''' redirects here; for other uses, see [[pi (disambiguation)]].}}


Pi is an ''[[irrational number]]'', which means that it cannot be expressed exactly as a ratio of integers, and ''[[transcendental number|transcendental]]'', meaning that it does not satisfy any [[algebraic equation]]. Since it is irrational, π cannot be written as a finite or periodically repeating decimal. The first 50 digits after the decimal point are
'''Pi''', denoted by the lower-case [[Greek alphabet|Greek letter]] π, is a [[mathematical constant]] that is approximately equal to 3.14159. In [[Euclidean geometry]], π represents the ratio between the circumference and the diameter of any [[circle]], or equivalently, the ratio between a circle's area and the square of its radius. This ratio is also found in many other geometrical objects, such as spheres and cones. Pi has further uses in many other areas of mathematics.


:3.14159 26535 89793 23846 26433 83279 50288 41971 69399 37510 ...
Pi is an ''[[irrational number]]'', which means that it cannot be expressed exactly as a ratio of integers, and ''[[transcendental number|transcendental]]'', meaning that it does not satisfy any [[algebraic equation]] with rational coefficients. The latter property implies that <math>\pi</math> is not [[constructible]]: in particular, the problem of [[squaring the circle]] in a finite number of steps using a [[compass and straightedge]] is impossible. Since <math>\pi</math> is irrational, it cannot be written as a finite or periodically repeating decimal. Showing the first 50 digits after the decimal point, &pi; is equal to
 
:3.14159 26535 89793 23846 26433 83279 50288 41971 69399 37510


==Early geometrical study==
==Early geometrical study==


The fact that the ratio of the circumference to the diameter of a circle is the same for all circles, and that it is slightly more than 3, was known to ancient Egyptian, Babylonian, Indian and Greek geometers. Preserved documents do not refer to the number explicitly, but contain approximations for &pi; as part of methods for calculating circumference or area. A Babylonian stone tablet from 1900 BC uses the proportion 25/8 = 3.125, and an Egyptian document from the same time gives the ratio (16/9)<sup>2</sup> &asymp; 3.16. The ancient Indian text ''[[Shatapatha Brahmana]]'' gives &pi; as 339/108 &asymp; 3.139. All of these values differ from the true value by less than one percent. The [[Books of Kings]] (600 BC) appears to suggest &pi; = 3, which is notably worse than other estimates available at the time, although it is disputed whether the text suggests an exact value.
The fact that the ratio of the circumference to the diameter of a circle is the same for all circles, and that it is slightly more than 3, was known to ancient Egyptian, Babylonian, Indian and Greek geometers. Preserved documents do not refer to the number explicitly, but contain approximations for <math>\scriptstyle\pi</math> as part of methods for calculating circumference or area. A Babylonian stone tablet from 1900 BC uses the proportion 25/8 = 3.125, and an Egyptian document from the same time gives the ratio <math>\scriptstyle(16/9)^2\,\approx\, 3.16</math>. The ancient Indian text ''[[Shatapatha Brahmana]]'' gives <math>\scriptstyle\pi</math> as <math>\scriptstyle 339/108\,\approx\, 3.139</math>. All of these values differ from the true value by less than one percent. The [[Books of Kings]] (600 BC) appears to suggest <math>\scriptstyle\pi\, =\, 3</math>, which is notably worse than other estimates available at the time, although it is disputed whether the text suggests an exact value.


[[Archimedes]] (287&ndash;212 BC), in whose honor &pi; is sometimes called ''Archimedes' constant'', was the first to treat the number with mathematical rigor. He knew how to calculate the circumference of a [[regular polygon]], and realized that a polygon inscribed in a circle has a smaller circumference than the circle whereas a circumscribed polygon has a greater circumference. By calculating the circumferences of two 96-sided polygons, one slightly smaller than a unit circle and the other slightly larger, he rigorously proved the bounds 223/71 < π < 22/7. Taking the average of the bounds yields the approximation π ≈ 3.1419. The method of Archimedes is the first known [[algorithm]] for calculating &pi; with arbitrary accuracy.
[[Archimedes]] (287&ndash;212 BC), in whose honor <math>\scriptstyle\pi</math> is sometimes called ''Archimedes' constant'', was the first to treat the number with mathematical rigor. He knew how to calculate the circumference of a [[regular polygon]], and realized that a polygon inscribed in a circle has a smaller circumference than the circle whereas a circumscribed polygon has a greater circumference. By calculating the circumferences of two 96-sided polygons, one slightly smaller than a unit circle and the other slightly larger, he rigorously proved the bounds <math>\scriptstyle 223/71\, <\, \pi\, <\, 22/7</math>. Taking the average of the bounds yields the approximation <math>\scriptstyle\pi\, \approx\, 3.1419</math>. The method of Archimedes is the first known [[algorithm]] for calculating <math>\scriptstyle\pi</math> with arbitrary accuracy.


In the following centuries, most significant mathematical development took place in India and China. Around 480, the Chinese mathematician [[Zu Chongzhi]] gave the approximation π = 355/113, and showed that 3.1415926 < π < 3.1415927, which would stand as the most accurate value for π over the next 900 years.
In the following centuries, most significant mathematical development took place in India and China. Around 480, the Chinese mathematician [[Zu Chongzhi]] gave the approximation <math>\scriptstyle\pi\, \approx\, 355/113</math> and showed that <math>\scriptstyle 3.1415926\, <\, \pi\, <\, 3.1415927</math>, which would stand as the most accurate value for <math>\scriptstyle\pi</math> over the next 900 years.


==Development of calculus==
==Development of calculus==
<!--
Calculations of &pi; from 500 AD to 1900, and the parallel development of calculus.
Outline: there is no finite construction of &pi;, instead one must use iteration. Calculus led to a systematic way of calculating area and arc length, including the value of &pi; Formulas with numbers lead to faster algorithms than geometrical figures.
Example:
Using the language of modern calculus, the area within a circle of unit radius is given by
:<math>4 \int_0^1 \sqrt{1-x^2}\,dx = \pi</math>
and the circumference is given by
:<math>4 \int_{-1}^1\frac{1}{\sqrt{1-x^2}}\,dx = 2 \pi.</math>
-->
==Proof of irrationality and transcendence==
See [[proof that &pi; is irrational]].
==Rational approximations and continued fractions ==
See [[proof that 22 over 7 exceeds &pi;]].
==Computer calculations==
The advent of digital computers in the 20th century led to an increased rate of new <math>\pi</math> calculation records. [[John von Neumann]] used [[ENIAC]] to compute 2037 digits of <math>\pi</math> in 1949, a calculation that took 70 hours. Additional thousands of decimal places were obtained in the following decades, with the million-digit milestone passed in 1973. Progress was not only due to faster computer hardware, but also the discovery of new algorithms for doing arithmetic. The discovery of the [[Karatsuba algorithm]] and the [[fast Fourier transform]] (FFT) in the 1960s facilitated multiplication and division of numbers with millions of digits. The ordinary "school book" method of multiplication requires <math>n^2</math> operations to find the product of two <math>n</math>-digit numbers, whereas the FFT is essentially [[linearithmic]], using ''n''&nbsp;log(''n'')&nbsp;log(log(''n'')) steps. A 1000-digit multiplication thus requires a few thousand calculations rather than a million.
Computer calculations of <math>\scriptstyle\pi</math> have also been aided by new formulas for <math>\scriptstyle\pi</math> found in the 20th century. In his study of [[modular function]]s, the Indian mathematician [[Srinivasa Ramanujan]] found many remarkable new formulas, such as the series
:<math>\frac{1}{\pi} = \frac{2 \sqrt 2}{9801} \sum_{k=0}^\infty \frac{(4k)!(1103+26390k)}{(k!)^4 396^{4k}},</math>
which gives eight decimals of &pi; per term. Due to scarce distribution of Ramanujan's published work, it was however not widely known until around 1985 when [[William Gosper]] used it to calculate 17 million decimals of <math>\scriptstyle\pi</math>. Based on Ramanujan's ideas, [[Gregory Chudnovsky|Gregory]] and [[David Chudnovsky]] found a formula that delivers 14 digits per term. The Chudnovsky brothers used this formula to set several <math>\pi</math> computing records in the end of the 1980s, including the first calculation of over one billion (1,011,196,691) decimals in 1989.
Series typically give a fixed number of digits for each term. In 1975, [[Richard Brent]] and [[Eugene Salamin]] independently discovered the [[Brent-Salamin algorithm]] in which the number of correct digits ''doubles'' with each step. The algorithm consists of setting
:<math>a_0 = 1 \quad \quad \quad b_0 = \frac{1}{\sqrt 2} \quad \quad \quad t_0 = \frac{1}{4} \quad \quad \quad p_0 = 1</math>
and iterating
:<math>a_{n+1} = \frac{a_n+b_n}{2} \quad \quad \quad b_{n+1} = \sqrt{a_n b_n}</math>
:<math>t_{n+1} = t_n - p_n (a_n-a_{n+1})^2 \quad \quad \quad p_{n+1} = 2 p_n</math>
until ''a''<sub>''n''</sub> and ''b''<sub>''n''</sub> are close enough. Then the estimate for <math>\pi</math> is given by
:<math>\pi \approx \frac{(a_n + b_n)^2}{4 t_n}.</math>
A mere 25 iterations gives 45 million correct decimals of <math>\scriptstyle\pi</math>. A similar algorithm that quadruples the accuracy in each step has been found by [[Jonathan Borwein|Jonathan]] and [[Peter Borwein]]. The methods have been used by [[Yasumasa Kanada]] and team to set most of the <math>\scriptstyle\pi</math> calculation records since 1980, up to a calculation of 206,158,430,000 decimals of  <math>\scriptstyle\pi</math> in 1999. The current record is 1,241,100,000,000 decimals, set by Kanada and team in 2002. Although most of Kanada's previous records were set using the Brent-Salamin algorithm, the 2002 calculation made use of two Machin-like formulas that were slower but crucially reduced memory consumption. The calculation was performed on a 64-node [[Hitachi]] supercomputer with 1 [[terabyte]] of main memory, capable of carrying out 2 trillion operations per seconds.
Aside from prestige, enormous <math>\scriptstyle\pi</math> calculations are useful for testing the integrity and performance of supercomputers. Pi calculation is a popular [[benchmark]] for personal computer hardware and [[arbitrary-precision arithmetic]] software as well. With optimized <math>\scriptstyle\pi</math> calculating software, a modern (2006) home computer can calculate a million digits of <math>\scriptstyle\pi</math> in a few seconds and a billion digits in a few hours.
==Properties of &pi;'s digits==
It appears that <math>\pi</math>'s digits are "random", although it is not entirely easy to define the "randomness" of a number. The most important measure besides irrationality is perhaps ''[[normal number|normality]]'': if a number is normal, all digits appear equally often in its decimal expansion, and all subsequences of digits appear equally often. Further, this should hold in every base, such as [[binary]] (in which <math>\pi</math> begins 11.0010010000111111...). A popular statement is that if <math>\pi</math> is normal, then, for example, every work by [[Shakespeare]] can be found encoded somewhere in the digits of <math>\pi</math>. This seems likely, but no proof that <math>\pi</math> is normal has been found. It is not even known whether any single digit, such as "1", appears infinitely many times in the decimal expansion of <math>\pi</math>. The value of <math>\pi</math> calculated by Kanada in 2002 shows that the first trillion digits of <math>\pi</math> are statistically random, but a finite calculation says nothing about the infinitely many digits that follow.
Another definition of randomness is that there should be no "simple formula" for the ''n''th digit of <math>\scriptstyle\pi</math>. Although there are simple formulas for <math>\scriptstyle\pi</math>, the calculations required to produce explicit digits are not so simple. [[Computational complexity theory]] allows the difficulty to be expressed quantitatively: the time needed to calculate ''n'' digits of <math>\scriptstyle\pi</math> on a [[Turing machine]] using the best known algorithm is proportional to ''n''&nbsp;(log(''n'')<sup>2</sup>&nbsp;log(log(''n'')).  It is conjectured that computing the <math>n</math>-th digit of <math>\scriptstyle\pi</math> cannot be done significantly faster than in a time proportional to ''n'': such a method could be said to be a "simple formula" for the digits of <math>\scriptstyle\pi</math>.
The closest thing to a simple formula for the digits of <math>\scriptstyle\pi</math> is the [[BBP formula]], found in 1995 by [[Simon Plouffe]] together with [[David H. Bailey]] and Peter Borwein. The formula,
:<math>\pi = \sum_{k=0}^\infty \frac{1}{16^k} \left( \frac{4}{8k + 1} - \frac{2}{8k + 4} - \frac{1}{8k + 5} - \frac{1}{8k + 6}\right),</math>
allows the ''n''th individual [[hexadecimal]] or [[binary]] digit of <math>\scriptstyle\pi</math> to be extracted in ''n''&nbsp;log(''n'') time, which is significantly faster than calculating all the first ''n'' digits and extracting the last one in the result. Between 1998 and 2000, the [[distributed computing]] project [[PiHex]] used a modification of the BBP formula due to [[Fabrice Bellard]] to compute the quadrillionth (1,000,000,000,000,000th) binary digit of <math>\scriptstyle\pi</math>, which turned out to be 0. The BBP formula has led to theoretical progress as well: it has been used to show that a plausible conjecture from [[chaos theory]] would imply that <math>\scriptstyle\pi</math> is normal in binary.
Unfortunately, the BBP formula does not allow one to extract ''decimal'' digits of <math>\scriptstyle\pi</math>. Although decimal BBP-type formulas are known for some other mathematical constants, it has been proved that no BBP-type formula exists for <math>\scriptstyle\pi</math>. There could still exist some completely different scheme for quickly extracting isolated decimals of <math>\scriptstyle\pi</math>, however. Decimal digit-extraction algorithms have in fact been constructed, but they are slower than calculating all the first ''n'' digits of <math>\scriptstyle\pi</math> and throwing away the first ''n''&nbsp;&minus;&nbsp;1 ones. A [[spigot algorithm]] that generates the decimal digits of <math>\scriptstyle\pi</math> one by one, rather than computing a fixed number of digits in one large calculation, was found by [[Stanley Rabinowitz]] and [[Stan Wagon]] in 1995. Again, this algorithm is however slower than fast methods for calculating a fixed amount of decimals at once.
==Areas of mathematics where &pi; appears==
==Relation to other constants==
Although <math>\pi</math> itself is transcendental, it is not easy to determine whether many of the other well known transcendental numbers (such as <math>e</math>) are algebraically independent from <math>\pi</math>. It is, for example, not known whether <math>\pi</math> and <math>e</math> are algebraically independent. It ''is'' known by the [[Lindemann–Weierstrass theorem]] that at least one of <math>\pi + e</math>  and <math>\pi e</math> is transcendental, but not which one or whether both are. By contrast, the [[Gelfond-Schneider theorem]] implies that <math>e^\pi</math> is transcendental, and [[Yuri Nesterenko]] proved in 1996 that both <math>e^\pi</math> and the [[gamma function]] value <math>\Gamma(1/4)</math> are algebraically independent from <math>\pi</math>.
Another open problem concerns the value of the so-called [[zeta constant]]s, which are the [[Riemann zeta function]] evaluated at the integers. Euler proved that &zeta;(2) = &pi;<sup>2</sup>/6 and that &zeta;(''n'') is a rational multiple of &pi;<sup>''n''</sup> whenever ''n'' is an even number. For example,
:<math>\zeta(4) = 1 + \frac{1}{2^4} + \frac{1}{3^4} + \cdots = \frac{\pi^4}{90} = 1.0823\dots</math>
:<math>\zeta(6) = 1 + \frac{1}{2^6} + \frac{1}{3^6} + \cdots = \frac{\pi^6}{945} = 1.0173\dots.</math>
Although it may seem plausible that &zeta;(''n'') is a multiple of &pi;<sup>''n''</sup> also when ''n'' is odd, no such formula has been found. The special case &zeta;(3) &asymp; 1.20205 is called [[Apéry's constant]] since it was proved irrational by [[Roger Apéry]] in 1977.
==Pi in culture==
The word and symbol for ''Pi'' has a special place in popular culture, including TV shows, books, and movies.  The town of Princeton, NJ, annually stages a major celebration called ''Pi Day'', with the excuse that [[Albert Einstein]], who lived in the town, was born on March 14th – 3.14 – the numeric equivalent of Pi.  For several days leading up to March 14, the town hosts a series of irrational events such as an Einstein lookalike contest, a pizza pie eating contest, a cupcake contest, and an apple pie bake-off.
== See also ==
* [[Pi (mathematical constant)/Proofs/An elementary proof that 22 over 7 exceeds π|An elementary proof that 22 over 7 exceeds π]]


==References==
==References==
* Jonathan Borwein & David Bailey (2003). ''Mathematics by Experiment - Plausible Reasoning in the 21st Century''. ISBN 1-56881-211-6
* Jonathan Borwein & David Bailey (2003). ''Mathematics by Experiment - Plausible Reasoning in the 21st Century''. ISBN 1-56881-211-6
 
* http://www.cecm.sfu.ca/organics/papers/borwein/paper/html/paper.html[[Category:Suggestion Bot Tag]]
[[Category:Pi]]

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Pi redirects here; for other uses, see pi (disambiguation).

Pi, denoted by the lower-case Greek letter π, is a mathematical constant that is approximately equal to 3.14159. In Euclidean geometry, π represents the ratio between the circumference and the diameter of any circle, or equivalently, the ratio between a circle's area and the square of its radius. This ratio is also found in many other geometrical objects, such as spheres and cones. Pi has further uses in many other areas of mathematics.

Pi is an irrational number, which means that it cannot be expressed exactly as a ratio of integers, and transcendental, meaning that it does not satisfy any algebraic equation with rational coefficients. The latter property implies that Failed to parse (SVG (MathML can be enabled via browser plugin): Invalid response ("Math extension cannot connect to Restbase.") from server "https://wikimedia.org/api/rest_v1/":): {\displaystyle \pi} is not constructible: in particular, the problem of squaring the circle in a finite number of steps using a compass and straightedge is impossible. Since Failed to parse (SVG (MathML can be enabled via browser plugin): Invalid response ("Math extension cannot connect to Restbase.") from server "https://wikimedia.org/api/rest_v1/":): {\displaystyle \pi} is irrational, it cannot be written as a finite or periodically repeating decimal. Showing the first 50 digits after the decimal point, π is equal to

3.14159 26535 89793 23846 26433 83279 50288 41971 69399 37510

Early geometrical study

The fact that the ratio of the circumference to the diameter of a circle is the same for all circles, and that it is slightly more than 3, was known to ancient Egyptian, Babylonian, Indian and Greek geometers. Preserved documents do not refer to the number explicitly, but contain approximations for Failed to parse (SVG (MathML can be enabled via browser plugin): Invalid response ("Math extension cannot connect to Restbase.") from server "https://wikimedia.org/api/rest_v1/":): {\displaystyle \scriptstyle\pi} as part of methods for calculating circumference or area. A Babylonian stone tablet from 1900 BC uses the proportion 25/8 = 3.125, and an Egyptian document from the same time gives the ratio Failed to parse (SVG (MathML can be enabled via browser plugin): Invalid response ("Math extension cannot connect to Restbase.") from server "https://wikimedia.org/api/rest_v1/":): {\displaystyle \scriptstyle(16/9)^2\,\approx\, 3.16} . The ancient Indian text Shatapatha Brahmana gives as . All of these values differ from the true value by less than one percent. The Books of Kings (600 BC) appears to suggest , which is notably worse than other estimates available at the time, although it is disputed whether the text suggests an exact value.

Archimedes (287–212 BC), in whose honor is sometimes called Archimedes' constant, was the first to treat the number with mathematical rigor. He knew how to calculate the circumference of a regular polygon, and realized that a polygon inscribed in a circle has a smaller circumference than the circle whereas a circumscribed polygon has a greater circumference. By calculating the circumferences of two 96-sided polygons, one slightly smaller than a unit circle and the other slightly larger, he rigorously proved the bounds . Taking the average of the bounds yields the approximation . The method of Archimedes is the first known algorithm for calculating with arbitrary accuracy.

In the following centuries, most significant mathematical development took place in India and China. Around 480, the Chinese mathematician Zu Chongzhi gave the approximation and showed that , which would stand as the most accurate value for over the next 900 years.

Development of calculus

Proof of irrationality and transcendence

See proof that π is irrational.

Rational approximations and continued fractions

See proof that 22 over 7 exceeds π.

Computer calculations

The advent of digital computers in the 20th century led to an increased rate of new calculation records. John von Neumann used ENIAC to compute 2037 digits of in 1949, a calculation that took 70 hours. Additional thousands of decimal places were obtained in the following decades, with the million-digit milestone passed in 1973. Progress was not only due to faster computer hardware, but also the discovery of new algorithms for doing arithmetic. The discovery of the Karatsuba algorithm and the fast Fourier transform (FFT) in the 1960s facilitated multiplication and division of numbers with millions of digits. The ordinary "school book" method of multiplication requires operations to find the product of two -digit numbers, whereas the FFT is essentially linearithmic, using n log(n) log(log(n)) steps. A 1000-digit multiplication thus requires a few thousand calculations rather than a million.

Computer calculations of have also been aided by new formulas for found in the 20th century. In his study of modular functions, the Indian mathematician Srinivasa Ramanujan found many remarkable new formulas, such as the series

which gives eight decimals of π per term. Due to scarce distribution of Ramanujan's published work, it was however not widely known until around 1985 when William Gosper used it to calculate 17 million decimals of . Based on Ramanujan's ideas, Gregory and David Chudnovsky found a formula that delivers 14 digits per term. The Chudnovsky brothers used this formula to set several computing records in the end of the 1980s, including the first calculation of over one billion (1,011,196,691) decimals in 1989.

Series typically give a fixed number of digits for each term. In 1975, Richard Brent and Eugene Salamin independently discovered the Brent-Salamin algorithm in which the number of correct digits doubles with each step. The algorithm consists of setting

and iterating

until an and bn are close enough. Then the estimate for is given by

A mere 25 iterations gives 45 million correct decimals of . A similar algorithm that quadruples the accuracy in each step has been found by Jonathan and Peter Borwein. The methods have been used by Yasumasa Kanada and team to set most of the calculation records since 1980, up to a calculation of 206,158,430,000 decimals of in 1999. The current record is 1,241,100,000,000 decimals, set by Kanada and team in 2002. Although most of Kanada's previous records were set using the Brent-Salamin algorithm, the 2002 calculation made use of two Machin-like formulas that were slower but crucially reduced memory consumption. The calculation was performed on a 64-node Hitachi supercomputer with 1 terabyte of main memory, capable of carrying out 2 trillion operations per seconds.

Aside from prestige, enormous Failed to parse (SVG (MathML can be enabled via browser plugin): Invalid response ("Math extension cannot connect to Restbase.") from server "https://wikimedia.org/api/rest_v1/":): {\displaystyle \scriptstyle\pi} calculations are useful for testing the integrity and performance of supercomputers. Pi calculation is a popular benchmark for personal computer hardware and arbitrary-precision arithmetic software as well. With optimized Failed to parse (SVG (MathML can be enabled via browser plugin): Invalid response ("Math extension cannot connect to Restbase.") from server "https://wikimedia.org/api/rest_v1/":): {\displaystyle \scriptstyle\pi} calculating software, a modern (2006) home computer can calculate a million digits of Failed to parse (SVG (MathML can be enabled via browser plugin): Invalid response ("Math extension cannot connect to Restbase.") from server "https://wikimedia.org/api/rest_v1/":): {\displaystyle \scriptstyle\pi} in a few seconds and a billion digits in a few hours.

Properties of π's digits

It appears that Failed to parse (SVG (MathML can be enabled via browser plugin): Invalid response ("Math extension cannot connect to Restbase.") from server "https://wikimedia.org/api/rest_v1/":): {\displaystyle \pi} 's digits are "random", although it is not entirely easy to define the "randomness" of a number. The most important measure besides irrationality is perhaps normality: if a number is normal, all digits appear equally often in its decimal expansion, and all subsequences of digits appear equally often. Further, this should hold in every base, such as binary (in which Failed to parse (SVG (MathML can be enabled via browser plugin): Invalid response ("Math extension cannot connect to Restbase.") from server "https://wikimedia.org/api/rest_v1/":): {\displaystyle \pi} begins 11.0010010000111111...). A popular statement is that if Failed to parse (SVG (MathML can be enabled via browser plugin): Invalid response ("Math extension cannot connect to Restbase.") from server "https://wikimedia.org/api/rest_v1/":): {\displaystyle \pi} is normal, then, for example, every work by Shakespeare can be found encoded somewhere in the digits of Failed to parse (SVG (MathML can be enabled via browser plugin): Invalid response ("Math extension cannot connect to Restbase.") from server "https://wikimedia.org/api/rest_v1/":): {\displaystyle \pi} . This seems likely, but no proof that Failed to parse (SVG (MathML can be enabled via browser plugin): Invalid response ("Math extension cannot connect to Restbase.") from server "https://wikimedia.org/api/rest_v1/":): {\displaystyle \pi} is normal has been found. It is not even known whether any single digit, such as "1", appears infinitely many times in the decimal expansion of Failed to parse (SVG (MathML can be enabled via browser plugin): Invalid response ("Math extension cannot connect to Restbase.") from server "https://wikimedia.org/api/rest_v1/":): {\displaystyle \pi} . The value of Failed to parse (SVG (MathML can be enabled via browser plugin): Invalid response ("Math extension cannot connect to Restbase.") from server "https://wikimedia.org/api/rest_v1/":): {\displaystyle \pi} calculated by Kanada in 2002 shows that the first trillion digits of Failed to parse (SVG (MathML can be enabled via browser plugin): Invalid response ("Math extension cannot connect to Restbase.") from server "https://wikimedia.org/api/rest_v1/":): {\displaystyle \pi} are statistically random, but a finite calculation says nothing about the infinitely many digits that follow.

Another definition of randomness is that there should be no "simple formula" for the nth digit of Failed to parse (SVG (MathML can be enabled via browser plugin): Invalid response ("Math extension cannot connect to Restbase.") from server "https://wikimedia.org/api/rest_v1/":): {\displaystyle \scriptstyle\pi} . Although there are simple formulas for Failed to parse (SVG (MathML can be enabled via browser plugin): Invalid response ("Math extension cannot connect to Restbase.") from server "https://wikimedia.org/api/rest_v1/":): {\displaystyle \scriptstyle\pi} , the calculations required to produce explicit digits are not so simple. Computational complexity theory allows the difficulty to be expressed quantitatively: the time needed to calculate n digits of Failed to parse (SVG (MathML can be enabled via browser plugin): Invalid response ("Math extension cannot connect to Restbase.") from server "https://wikimedia.org/api/rest_v1/":): {\displaystyle \scriptstyle\pi} on a Turing machine using the best known algorithm is proportional to n (log(n)2 log(log(n)). It is conjectured that computing the Failed to parse (SVG (MathML can be enabled via browser plugin): Invalid response ("Math extension cannot connect to Restbase.") from server "https://wikimedia.org/api/rest_v1/":): {\displaystyle n} -th digit of Failed to parse (SVG (MathML can be enabled via browser plugin): Invalid response ("Math extension cannot connect to Restbase.") from server "https://wikimedia.org/api/rest_v1/":): {\displaystyle \scriptstyle\pi} cannot be done significantly faster than in a time proportional to n: such a method could be said to be a "simple formula" for the digits of Failed to parse (SVG (MathML can be enabled via browser plugin): Invalid response ("Math extension cannot connect to Restbase.") from server "https://wikimedia.org/api/rest_v1/":): {\displaystyle \scriptstyle\pi} .

The closest thing to a simple formula for the digits of Failed to parse (SVG (MathML can be enabled via browser plugin): Invalid response ("Math extension cannot connect to Restbase.") from server "https://wikimedia.org/api/rest_v1/":): {\displaystyle \scriptstyle\pi} is the BBP formula, found in 1995 by Simon Plouffe together with David H. Bailey and Peter Borwein. The formula,

Failed to parse (SVG (MathML can be enabled via browser plugin): Invalid response ("Math extension cannot connect to Restbase.") from server "https://wikimedia.org/api/rest_v1/":): {\displaystyle \pi = \sum_{k=0}^\infty \frac{1}{16^k} \left( \frac{4}{8k + 1} - \frac{2}{8k + 4} - \frac{1}{8k + 5} - \frac{1}{8k + 6}\right),}

allows the nth individual hexadecimal or binary digit of to be extracted in n log(n) time, which is significantly faster than calculating all the first n digits and extracting the last one in the result. Between 1998 and 2000, the distributed computing project PiHex used a modification of the BBP formula due to Fabrice Bellard to compute the quadrillionth (1,000,000,000,000,000th) binary digit of , which turned out to be 0. The BBP formula has led to theoretical progress as well: it has been used to show that a plausible conjecture from chaos theory would imply that is normal in binary.

Unfortunately, the BBP formula does not allow one to extract decimal digits of . Although decimal BBP-type formulas are known for some other mathematical constants, it has been proved that no BBP-type formula exists for . There could still exist some completely different scheme for quickly extracting isolated decimals of , however. Decimal digit-extraction algorithms have in fact been constructed, but they are slower than calculating all the first n digits of and throwing away the first n − 1 ones. A spigot algorithm that generates the decimal digits of one by one, rather than computing a fixed number of digits in one large calculation, was found by Stanley Rabinowitz and Stan Wagon in 1995. Again, this algorithm is however slower than fast methods for calculating a fixed amount of decimals at once.

Areas of mathematics where π appears

Relation to other constants

Although itself is transcendental, it is not easy to determine whether many of the other well known transcendental numbers (such as ) are algebraically independent from . It is, for example, not known whether and are algebraically independent. It is known by the Lindemann–Weierstrass theorem that at least one of and is transcendental, but not which one or whether both are. By contrast, the Gelfond-Schneider theorem implies that is transcendental, and Yuri Nesterenko proved in 1996 that both and the gamma function value are algebraically independent from .

Another open problem concerns the value of the so-called zeta constants, which are the Riemann zeta function evaluated at the integers. Euler proved that ζ(2) = π2/6 and that ζ(n) is a rational multiple of πn whenever n is an even number. For example,

Although it may seem plausible that ζ(n) is a multiple of πn also when n is odd, no such formula has been found. The special case ζ(3) ≈ 1.20205 is called Apéry's constant since it was proved irrational by Roger Apéry in 1977.

Pi in culture

The word and symbol for Pi has a special place in popular culture, including TV shows, books, and movies. The town of Princeton, NJ, annually stages a major celebration called Pi Day, with the excuse that Albert Einstein, who lived in the town, was born on March 14th – 3.14 – the numeric equivalent of Pi. For several days leading up to March 14, the town hosts a series of irrational events such as an Einstein lookalike contest, a pizza pie eating contest, a cupcake contest, and an apple pie bake-off.

See also

References