A mathematical constant is a key number whose value is fixed by an unambiguous definition, often referred to by a special symbol (e.g., an alphabet letter), or by mathematicians' names to facilitate using it across multiple mathematical problems.^{ [1]} Constants arise in many areas of mathematics, with constants such as e and π occurring in such diverse contexts as geometry, number theory, statistics, and calculus.
Some constants arise naturally by a fundamental principle or intrinsic property, such as the ratio between the circumference and diameter of a circle (π). Other constants are notable more for historical reasons than for their mathematical properties. The more popular constants have been studied throughout the ages and computed to many decimal places.
All named mathematical constants are definable numbers, and usually are also computable numbers ( Chaitin's constant being a significant exception).
These are constants which one is likely to encounter during precollege education in many countries.
The constant π (pi) has a natural definition in Euclidean geometry as the ratio between the circumference and diameter of a circle. It may be found in many other places in mathematics: for example, the Gaussian integral, the complex roots of unity, and Cauchy distributions in probability. However, its ubiquity is not limited to pure mathematics. It appears in many formulas in physics, and several physical constants are most naturally defined with π or its reciprocal factored out. For example, the ground state wave function of the hydrogen atom is
where is the Bohr radius.
π is an irrational number and a transcendental number.
The numeric value of π is approximately 3.1415926536 (sequence A000796 in the OEIS). Memorizing increasingly precise digits of π is a world record pursuit.
The imaginary unit or unit imaginary number, denoted as i, is a mathematical concept which extends the real number system to the complex number system The imaginary unit's core property is that i^{2} = −1. The term " imaginary" was coined because there is no ( real) number having a negative square.
There are in fact two complex square roots of −1, namely i and −i, just as there are two complex square roots of every other real number (except zero, which has one double square root).
In contexts where the symbol i is ambiguous or problematic, j or the Greek iota (ι) is sometimes used. This is in particular the case in electrical engineering and control systems engineering, where the imaginary unit is often denoted by j, because i is commonly used to denote electric current.
Euler's number e, also known as the exponential growth constant, appears in many areas of mathematics, and one possible definition of it is the value of the following expression:
The constant e is intrinsically related to the exponential function .
The Swiss mathematician Jacob Bernoulli discovered that e arises in compound interest: If an account starts at $1, and yields interest at annual rate R, then as the number of compounding periods per year tends to infinity (a situation known as continuous compounding), the amount of money at the end of the year will approach e^{R} dollars.
The constant e also has applications to probability theory, where it arises in a way not obviously related to exponential growth. As an example, suppose that a slot machine with a one in n probability of winning is played n times, then for large n (e.g., one million), the probability that nothing will be won will tend to 1/e as n tends to infinity.
Another application of e, discovered in part by Jacob Bernoulli along with French mathematician Pierre Raymond de Montmort, is in the problem of derangements, also known as the hat check problem.^{ [2]} Here, n guests are invited to a party, and at the door each guest checks his hat with the butler, who then places them into labelled boxes. The butler does not know the name of the guests, and hence must put them into boxes selected at random. The problem of de Montmort is: what is the probability that none of the hats gets put into the right box. The answer is
which, as n tends to infinity, approaches 1/e.
e is an irrational number.
The numeric value of e is approximately 2.7182818284 (sequence A001113 in the OEIS).
The square root of 2, often known as root 2, radical 2, or Pythagoras' constant, and written as √2, is the positive algebraic number that, when multiplied by itself, gives the number 2. It is more precisely called the principal square root of 2, to distinguish it from the negative number with the same property.
Geometrically the square root of 2 is the length of a diagonal across a square with sides of one unit of length; this follows from the Pythagorean theorem. It was probably the first number known to be irrational. Its numerical value truncated to 65 decimal places is:
Alternatively, the quick approximation 99/70 (≈ 1.41429) for the square root of two was frequently used before the common use of electronic calculators and computers. Despite having a denominator of only 70, it differs from the correct value by less than 1/10,000 (approx. 7.2 × 10^{ −5}).
The numeric value of √3 is approximately 1.7320508075 (sequence A002194 in the OEIS).
These are constants which are encountered frequently in higher mathematics.
Iterations of continuous maps serve as the simplest examples of models for dynamical systems.^{ [3]} Named after mathematical physicist Mitchell Feigenbaum, the two Feigenbaum constants appear in such iterative processes: they are mathematical invariants of logistic maps with quadratic maximum points^{ [4]} and their bifurcation diagrams. Specifically, the constant α is the ratio between the width of a tine and the width of one of its two subtines, and the constant δ is the limiting ratio of each bifurcation interval to the next between every perioddoubling bifurcation.
The logistic map is a polynomial mapping, often cited as an archetypal example of how chaotic behaviour can arise from very simple nonlinear dynamical equations. The map was popularized in a seminal 1976 paper by the Australian biologist Robert May,^{ [5]} in part as a discretetime demographic model analogous to the logistic equation first created by Pierre François Verhulst. The difference equation is intended to capture the two effects of reproduction and starvation.
The numeric value of α is approximately 2.5029. The numeric value of δ is approximately 4.6692.
Apery's constant is the sum of the series
Despite being a special value of the Riemann zeta function, Apéry's constant arises naturally in a number of physical problems, including in the second and thirdorder terms of the electron's gyromagnetic ratio, computed using quantum electrodynamics.^{ [6]}
The number φ, also called the golden ratio, turns up frequently in geometry, particularly in figures with pentagonal symmetry. Indeed, the length of a regular pentagon's diagonal is φ times its side. The vertices of a regular icosahedron are those of three mutually orthogonal golden rectangles. Also, it appears in the Fibonacci sequence, related to growth by recursion.^{ [7]} Kepler proved that it is the limit of the ratio of consecutive Fibonacci numbers.^{ [8]} The golden ratio has the slowest convergence of any irrational number.^{ [9]} It is, for that reason, one of the worst cases of Lagrange's approximation theorem and it is an extremal case of the Hurwitz inequality for Diophantine approximations. This may be why angles close to the golden ratio often show up in phyllotaxis (the growth of plants).^{ [10]} It is approximately equal to 1.6180339887498948482, or, more precisely 2⋅sin(54°) =
The Euler–Mascheroni constant is defined as the following limit:
The Euler–Mascheroni constant appears in Mertens' third theorem and has relations to the gamma function, the zeta function and many different integrals and series.
It is yet unknown whether is rational or not.
The numeric value of is approximately 0.57721.
Conway's constant is the invariant growth rate of all derived strings similar to the lookandsay sequence (except for one trivial one).^{ [11]}
It is given by the unique positive real root of a polynomial of degree 71 with integer coefficients.^{ [11]}
The value of λ is approximately 1.30357.
If a real number r is written as a simple continued fraction:
where a_{k} are natural numbers for all k, then, as the Russian mathematician Aleksandr Khinchin proved in 1934, the limit as n tends to infinity of the geometric mean: (a_{1}a_{2}...a_{n})^{1/n} exists and is a constant, Khinchin's constant, except for a set of measure 0.^{ [12]}
The numeric value of K is approximately 2.6854520010.
The Glaisher–Kinkelin constant is defined as the limit:
It appears in some expressions of the derivative of the Riemann zeta function. It has a numerical value of approximately 1.2824271291.
Some constants, such as the square root of 2, Liouville's constant and Champernowne constant:
are not important mathematical invariants but retain interest being simple representatives of special sets of numbers, the irrational numbers,^{ [14]} the transcendental numbers^{ [15]} and the normal numbers (in base 10)^{ [16]} respectively. The discovery of the irrational numbers is usually attributed to the Pythagorean Hippasus of Metapontum who proved, most likely geometrically, the irrationality of the square root of 2. As for Liouville's constant, named after French mathematician Joseph Liouville, it was the first number to be proven transcendental.^{ [17]}
In the computer science subfield of algorithmic information theory, Chaitin's constant is the real number representing the probability that a randomly chosen Turing machine will halt, formed from a construction due to Argentine American mathematician and computer scientist Gregory Chaitin. Chaitin's constant, though not being computable, has been proven to be transcendental and normal. Chaitin's constant is not universal, depending heavily on the numerical encoding used for Turing machines; however, its interesting properties are independent of the encoding.
When unspecified, constants indicate classes of similar objects, commonly functions, all equal up to a constant—technically speaking, this may be viewed as 'similarity up to a constant'. Such constants appear frequently when dealing with integrals and differential equations. Though unspecified, they have a specific value, which often is not important.
Indefinite integrals are called indefinite because their solutions are only unique up to a constant. For example, when working over the field of real numbers
where C, the constant of integration, is an arbitrary fixed real number.^{ [18]} In other words, whatever the value of C, differentiating sin x + C with respect to x always yields cos x.
In a similar fashion, constants appear in the solutions to differential equations where not enough initial values or boundary conditions are given. For example, the ordinary differential equation y^{'} = y(x) has solution Ce^{x} where C is an arbitrary constant.
When dealing with partial differential equations, the constants may be functions, constant with respect to some variables (but not necessarily all of them). For example, the PDE
has solutions f(x,y) = C(y), where C(y) is an arbitrary function in the variable y.
It is common to express the numerical value of a constant by giving its decimal representation (or just the first few digits of it). For two reasons this representation may cause problems. First, even though rational numbers all have a finite or everrepeating decimal expansion, irrational numbers don't have such an expression making them impossible to completely describe in this manner. Also, the decimal expansion of a number is not necessarily unique. For example, the two representations 0.999... and 1 are equivalent^{ [19]}^{ [20]} in the sense that they represent the same number.
Calculating digits of the decimal expansion of constants has been a common enterprise for many centuries. For example, German mathematician Ludolph van Ceulen of the 16th century spent a major part of his life calculating the first 35 digits of pi.^{ [21]} Using computers and supercomputers, some of the mathematical constants, including π, e, and the square root of 2, have been computed to more than one hundred billion digits. Fast algorithms have been developed, some of which — as for Apéry's constant — are unexpectedly fast.
Some constants differ so much from the usual kind that a new notation has been invented to represent them reasonably. Graham's number illustrates this as Knuth's uparrow notation is used.^{ [22]}^{ [23]}
It may be of interest to represent them using continued fractions to perform various studies, including statistical analysis. Many mathematical constants have an analytic form, that is they can be constructed using wellknown operations that lend themselves readily to calculation. Not all constants have known analytic forms, though; Grossman's constant^{ [24]} and Foias' constant^{ [25]} are examples.
Symbolizing constants with letters is a frequent means of making the notation more concise. A common convention, instigated by René Descartes in the 17th century and Leonhard Euler in the 18th century, is to use lower case letters from the beginning of the Latin alphabet or the Greek alphabet when dealing with constants in general.
However, for more important constants, the symbols may be more complex and have an extra letter, an asterisk, a number, a lemniscate or use different alphabets such as Hebrew, Cyrillic or Gothic.^{ [23]}
Sometimes, the symbol representing a constant is a whole word. For example, American mathematician Edward Kasner's 9yearold nephew coined the names googol and googolplex.^{ [23]}^{ [26]}
Other names are either related to the meaning of the constant ( universal parabolic constant, twin prime constant, ...) or to a specific person ( Sierpiński's constant, Josephson constant, and so on).
Abbreviations used:
Symbol  Value  Name  Field  N  First described  Number of known decimal digits 

0

= 0  Zero  Gen  R  by c. 500 BC  all 
1

= 1  One, Unity  Gen  R  all  
i

= √–1  Imaginary unit, unit imaginary number  Gen, Ana  A  by c. 1500  all 
π

≈ 3.14159 26535 89793 23846 26433 83279 50288  Pi, Archimedes' constant or Ludolph's number  Gen, Ana  T  by c. 2600 BC  62,831,853,071,796^{ [27]} 
e

≈ 2.71828 18284 59045 23536 02874 71352 66249  e, Napier's constant, or Euler's number  Gen, Ana  T  1618  31,415,926,535,897^{ [27]} 
√2

≈ 1.41421 35623 73095 04880 16887 24209 69807  Pythagoras' constant, square root of 2  Gen  A  by c. 800 BC  10,000,000,000,000^{ [27]} 
√3

≈ 1.73205 08075 68877 29352 74463 41505 87236  Theodorus' constant, square root of 3  Gen  A  by c. 800 BC  2,199,023,255,552^{ [28]} 
√5

≈ 2.23606 79774 99789 69640 91736 68731 27623  Square root of 5  Gen  A  by c. 800 BC  2,199,023,255,552^{ [28]} 
≈ 0.57721 56649 01532 86060 65120 90082 40243  Euler–Mascheroni constant  Gen, NuT  1735  600,000,000,100^{ [28]}  
≈ 1.61803 39887 49894 84820 45868 34365 63811  Golden ratio  Gen  A  by c. 200 BC  10,000,000,000,000^{ [28]}  
^{ [29]}^{ [30]}^{ [31]}^{ [32]}  de Bruijn–Newman constant  NuT, Ana  1950  none  
M_{1}

≈ 0.26149 72128 47642 78375 54268 38608 69585  Meissel–Mertens constant  NuT  1866 1874 
8,010  
≈ 0.28016 94990 23869 13303  Bernstein's constant^{ [33]}  Ana  
≈ 0.30366 30028 98732 65859 74481 21901 55623  Gauss–Kuzmin–Wirsing constant  Com  1974  385  
≈ 0.35323 63718 54995 98454 35165 50432 68201  Hafner–Sarnak–McCurley constant  NuT  1993  
L

≈ 0.5  Landau's constant  Ana  1  
Ω

≈ 0.56714 32904 09783 87299 99686 62210 35554  Omega constant  Ana  T  
,

≈ 0.62432 99885 43550 87099 29363 83100 83724  Golomb–Dickman constant  Com, NuT  1930 1964 

≈ 0.64341 05462  Cahen's constant  T  1891  4000  
C_{2}

≈ 0.66016 18158 46869 57392 78121 10014 55577  Twin prime constant  NuT  5,020  
≈ 0.66274 34193 49181 58097 47420 97109 25290  Laplace limit  1822  
^{*}

≈ 0.70258  Embree–Trefethen constant  NuT  
K

≈ 0.76422 36535 89220 66299 06987 31250 09232  Landau–Ramanujan constant  NuT  30,010  
B_{4}

≈ 0.87058 838  Brun's constant for prime quadruplets  NuT  8  
G

≈ 0.91596 55941 77219 01505 46035 14932 38411  Catalan's constant  Com  1,000,000,001,337^{ [28]}  
B´_{L}

= 1  Legendre's constant  NuT  R  all  
K

≈ 1.13198 824  Viswanath's constant  NuT  8  
≈ 1.20205 69031 59594 28539 97381 61511 44999  Apéry's constant  I  1979  1,200,000,000,100^{ [28]}  
≈ 1.30357 72690 34296 39125 70991 12152 55189  Conway's constant  NuT  A  
≈ 1.30637 78838 63080 69046 86144 92602 60571  Mills' constant  NuT  1947  6850  
≈ 1.32471 79572 44746 02596 09088 54478 09734  Plastic constant  NuT  A  1928  
≈ 1.45136 92348 83381 05028 39684 85892 02744  Ramanujan–Soldner constant  NuT  I  75,500  
≈ 1.45607 49485 82689 67139 95953 51116 54356  Backhouse's constant^{ [34]}  
≈ 1.46707 80794  Porter's constant^{ [35]}  NuT  1975  
≈ 1.53960 07178  Lieb's square ice constant^{ [36]}  Com  A  1967  
E_{B}

≈ 1.60669 51524 15291 76378 33015 23190 92458  Erdős–Borwein constant  NuT  I  
≈ 1.70521 11401 05367 76428 85514 53434 50816  Niven's constant  NuT  1969  
B_{2}

≈ 1.90216 05831 04  Brun's constant for twin primes  NuT  1919  12  
P_{2}

≈ 2.29558 71493 92638 07403 42980 49189 49039  Universal parabolic constant  Gen  T  
≈ 2.50290 78750 95892 82228 39028 73218 21578  Feigenbaum constant  ChT  
K

≈ 2.58498 17595 79253 21706 58935 87383 17116  Sierpiński's constant  
≈ 2.68545 20010 65306 44530 97148 35481 79569  Khinchin's constant  NuT  1934  7350  
F

≈ 2.80777 02420 28519 36522 15011 86557 77293  Fransén–Robinson constant  Ana  
≈ 3.27582 29187 21811 15978 76818 82453 84386  Lévy's constant  NuT  
≈ 3.35988 56662 43177 55317 20113 02918 92717  Reciprocal Fibonacci constant^{ [37]}  I  
≈ 4.66920 16091 02990 67185 32038 20466 20161  Feigenbaum constant  ChT  1975 