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The Real Gamma and Beta Functions
1 · Prerequisites
- Absolute and Conditional Convergence; Rearrangement; Products
- Binary Operations, Monoids, Groups and Subgroups
- Compactness in Metric Spaces
- Completeness, Completion, and Uniform Continuity
- Construction of the Natural Numbers
- Construction of the Real Numbers via Cauchy Sequences
- Construction of the Real Numbers via Dedekind Cuts
- Continuity, IVT, EVT, and Uniform Continuity
- Convexity
- Countability and Uncountability
- Determinants of Matrices over a Commutative Ring
- Equivalent Forms of Completeness
- Filters and Ultrafilters
- Finite Counting, Factorials and Binomial Coefficients
- Finite Probability and the Probabilistic Method
- Foundations of the Real Numbers for Analysis
- Fubini and Change of Variables
- Fundamental Trigonometric Identities
- Gaussian Elimination, Elementary Matrices and Reduced Row Echelon Form
- Group Actions, Orbits, Stabilisers and Cayley's Theorem
- Improper and Parameter-Dependent Multiple Integrals
- Improper Integrals
- Limits of Real Functions
- limsup, liminf, and Subsequential Limits
- Linear Independence, Bases and Dimension
- Linear Transformations, Rank-Nullity and Quotient Spaces
- Matrices, the Matrix of a Linear Map, and Change of Basis
- Metric Spaces
- Monotone Functions, Discontinuities, and Continuity Sets
- Monotone Sequences, Bolzano-Weierstrass, and Cauchy Completeness
- Order, Zorn's Lemma, and the Axiom of Choice
- pi: the Equivalent Characterizations
- Polynomial Rings, the Division Algorithm and Roots
- Power Series and Real-Analytic Functions
- Properties of the Integral and the Working FTC
- Relations, Functions, and Quotients
- Rings, Subrings, Integral Domains and Fields
- Rⁿ as a Normed Space; Vector-Valued Functions
- Roots, Rational Powers, and Classical Inequalities
- Sequences and Limits
- Sequences and Series of Functions; Uniform Convergence
- Series: Convergence and the Nonnegative Tests
- Sine, Cosine, and the Definition of Pi
- Subspaces, Products, and Quotients
- Suprema and Infima
- Symmetric Groups, Cycle Decomposition and the Sign Homomorphism
- The Derivative and the Mean Value Theorems
- The Exponential Function
- The Inverse and Implicit Function Theorems
- The Logarithm and General Powers
- The Riemann Integral in Rᵐ and Jordan Content
- The Riemann Integral: Definition and Integrability
- The Topology of Euclidean Space
- The Total Derivative in ℝᵐ → ℝⁿ
- The ZFC Axioms and the Basic Set Constructions
- Topological Spaces and Continuity
- Topology of ℝ
- Vector Spaces, Linear Subspaces, Span and Direct Sums
- Volumes of Elementary Solids and Solids of Revolution
2 · Summary
Improper integration supplies convergence, comparison, exhaustion, and dominated parameter differentiation, while logarithms and real powers control endpoint singularities and parameter derivatives. One-variable convexity supplies secant-slope inequalities, and the Gaussian integral and Wallis product give independent real routes to the constant . The ball-volume recursion provides the geometric input for the dimension formula.
Euler's Gamma and Beta integrals are first shown to converge on their exact positive domains. The Gamma recurrence gives factorial values, dominated differentiation gives smoothness, and strict log-convexity yields Gautschi's inequality and, through a factorial squeeze, Bohr--Mollerup uniqueness. A first-quadrant change of variables proves the Beta--Gamma identity. Gaussian and Wallis arguments separately evaluate , Wallis fixes the constant in Stirling's formula, and the Beta identity closes the unit-ball volume formula, its radius scaling, limiting behavior, and maximizing dimension.
3 · Logical flowchart
4 · Definitions, theorems and proofs
Log-convex positive functions
Definition
A positive function is log-convex when is convex on .
Equivalently, for and with ,
It is strictly log-convex when this inequality is strict for and . Positivity ensures that every logarithm and every real power in these formulas is defined.
The real Gamma function by Euler's integral
Definition
For , define .
The integral is improper at both and . Its convergence for every , and its failure for , are proved in Euler's Gamma integral converges exactly for positive real parameters ↗, which justifies the definition on exactly the displayed domain. The integrand is positive, so throughout .
Euler's Gamma integral converges exactly for positive real parameters
Statement
Let be real. The Euler integral converges if and only if .
Facts & Assumptions
Given: A real parameter , with the integral split at .
For every natural and real , as (The exponential dominates every fixed nonnegative integer power at ).
If eventually at a singular end and the improper integral of converges there, then the integral of converges; the same assertion holds separately at infinity and at either finite singular endpoint (Comparison tests for improper integrals).
The natural logarithm is strictly increasing and maps onto (Order, continuity, range, and the product, quotient, and reciprocal laws for the natural logarithm).
For real , is differentiable on with derivative (Continuity and derivatives of positive-base real powers).
Proof
Suppose . On , , and [F5] with the fundamental theorem gives . Thus [F2] gives convergence at zero.
If , then on , while . At this is exactly the logarithmic threshold, and [F3] and [F4] show diverges; the same lower comparison proves divergence for .
For arbitrary real , choose a natural . For , , and [F1] with makes eventually. Since the latter has a convergent improper integral, [F2] gives convergence at infinity.
Steps 1.1 and 1.3 prove convergence for , while step 1.2 proves divergence for every . Hence the two improper ends converge simultaneously exactly on the positive real axis.
Euler's real Beta integral
Definition
For , define .
The integral is improper at both endpoints. The exact convergence theorem Euler's Beta integral converges exactly for two positive parameters ↗ proves that it exists precisely for the displayed positive parameters and therefore discharges the definition's existence obligation.
Euler's Beta integral converges exactly for two positive parameters
Statement
Let be real. The Beta integral converges if and only if and .
Here the Beta integral means .
Facts & Assumptions
Given: Real parameters , with the integral split at .
If eventually at a finite singular endpoint and the improper integral of converges there, then the integral of converges (Comparison tests for improper integrals).
The natural logarithm is strictly increasing and maps onto (Order, continuity, range, and the product, quotient, and reciprocal laws for the natural logarithm).
For real , is differentiable on with derivative (Continuity and derivatives of positive-base real powers).
Proof
On , the continuous positive factor is bounded above and below by positive constants. Thus [F1] reduces convergence at zero to that of , whose primitive from [F4] converges exactly for ; at , [F2] and [F3] give logarithmic divergence, and for the integrand dominates the same threshold.
The substitution changes the end into . There is bounded above and below by positive constants, so [F4] and the same comparison give convergence exactly for , with logarithmic divergence at .
Both endpoint integrals converge exactly when and . If either parameter is nonpositive, the corresponding endpoint diverges by step 1.1 or step 1.2.
The real Gamma functional equation
Statement
For every , , and .
Facts & Assumptions
Given: A real parameter and truncation parameters .
If differentiable on a compact interval have integrable derivatives, then (If are differentiable on with integrable, then ).
The Euler integral converges if and only if its real parameter is positive (Euler's Gamma integral converges exactly for positive real parameters).
Proof
Apply [F1] on with and : .
Since , as . At infinity choose a natural ; then by exponential domination.
Letting the two truncations approach their improper ends in step 1.1 and using [F2] gives .
At , .
for every natural number
Statement
For every natural number , .
Facts & Assumptions
Given: Factorial recursion and from The factorial and the falling factorial , defined by recursion in .
For every , , and (The real Gamma functional equation ).
Proof
At , [F1] gives .
Assume . Then [F1] gives .
The induction principle therefore proves for every .
The real Gamma function is smooth and its derivatives are logarithmic moments
Statement
The real Gamma function is smooth on . For every natural and every , .
Facts & Assumptions
Given: A compact parameter interval and a natural derivative order .
If an integrand and its parameter derivative are continuous, one slice is absolutely improperly integrable, and on each compact parameter interval the derivative has a nonnegative improperly integrable uniform bound, then the integral is continuously differentiable and its derivative is the integral of the parameter derivative (Differentiation under an improper multiple integral under an integrable derivative bound).
For every natural and real , as (The exponential dominates every fixed nonnegative integer power at ).
If a property holds at and passes from to , then it holds for every natural (The principle of mathematical induction).
The Euler integral converges for every positive real parameter (Euler's Gamma integral converges exactly for positive real parameters).
Proof
On , put . Uniformly for , the absolute th parameter derivative becomes after substitution. By [F2] this is eventually bounded by and is integrable.
On , and allow to be bounded by for one natural depending only on . By [F2] this has an integrable exponential majorant.
The case is the defining integral, convergent by [F4] and absolutely convergent because its integrand is nonnegative. If the displayed formula holds at order , its integrand and parameter derivative are continuous; steps 1.1 and 1.2, applied at orders and , give one absolutely integrable slice and an integrable uniform derivative bound. Thus [F1] differentiates once more. By [F3], the formula holds for every natural .
Every lies in a compact interval , so step 2.1 proves the formulas and smoothness throughout the positive axis.
The real Gamma function is strictly log-convex
Statement
The real Gamma function is strictly log-convex on .
Facts & Assumptions
Given: Distinct and a weight .
For , exponential convexity is strict unless its two arguments are equal (The two-point convexity inequality for the exponential function).
A positive function is log-convex when its logarithm is convex (Log-convex positive functions).
Proof
Fix and write . By [F1], the integrand at is at most the corresponding convex combination, with strict inequality except at the single point ; integration makes strictly convex.
Choose . Then .
Apply step 1.1 at with the from step 1.2. After cancelling , one gets , which is strict log-convexity by [F2].
The real Gamma function has one minimum and diverges at both ends of its domain
Statement
As , and . As , both and tend to . Moreover there is a unique at which attains its global minimum; it decreases on and increases on .
Facts & Assumptions
Given: The positive smooth function on and .
For every , , and (The real Gamma functional equation ).
The real Gamma function is strictly log-convex on (The real Gamma function is strictly log-convex).
The real Gamma function is smooth on (The real Gamma function is smooth and its derivatives are logarithmic moments).
For every natural , ( for every natural number ).
For a differentiable on an open interval, is convex if and only if is nondecreasing (A differentiable function on an open interval is convex if and only if its derivative is nondecreasing).
If is continuous on and differentiable on , then for some (The mean value theorem, as the case of Cauchy's: for continuous on with and differentiable on there is with ); a function with positive derivative on an interval is increasing there and one with negative derivative is decreasing (On an interval , for continuous on and differentiable at every interior point: throughout gives nondecreasing, gives increasing, and give the two decreasing forms; conversely a nondecreasing has and a nonincreasing has wherever it is differentiable, and no strict converse is claimed).
Proof
By continuity at and [F1], as . Since , this also gives .
One has , while strict convexity [F2] gives for . Fixing such an and applying [F6] on and on gives with and with .
By [F2] and [F5], is nondecreasing. If for some , then is constant on , so is affine there, contradicting the strict convexity of [F2]; hence is strictly increasing and has at most one zero. By [F3] it is continuous, so the sign change in step 1.2 gives exactly one zero . Strict increase makes negative before and positive after it, so [F6] makes , and hence , decreasing on and increasing on , and is the unique global minimum.
By [F4], . For , the ratios of grow by a factor exceeding , so this sequence tends to infinity. By the eventual increase from step 2.1, if then and . Thus both quantities tend to infinity.
Gautschi's inequality for the real Gamma function
Statement
For and , .
For both inequalities are strict. At the lower inequality is equality, and at both are equalities.
Facts & Assumptions
Given: A real and .
The real Gamma function is strictly log-convex on (The real Gamma function is strictly log-convex).
For every , (The real Gamma functional equation ).
Proof
Log-convexity between and gives , strictly when .
Since , log-convexity gives .
Divide the inequalities in steps 1.1 and 1.2 by positive Gamma values and use [F2]. This gives the displayed bounds and the stated strictness. Direct substitution shows the lower equality at and both equalities at .
Log-convex solutions of the Gamma recurrence obey the Bohr--Mollerup factorial squeeze
Statement
Let be log-convex, with and for every . For and every integer , put
Then
Every positive log-convex with and lies between the Bohr--Mollerup factorial bounds, whose ratio is for .
Facts & Assumptions
Given: Such a function , a real , and an integer .
A positive function is log-convex exactly when its logarithm is convex (Log-convex positive functions).
Factorial is determined by and (The factorial and the falling factorial , defined by recursion in ).
For a convex on an interval, writing , one has whenever lie in it (For a convex function and , the three secant slopes satisfy ).
Proof
By [F1] the function is convex, and the recurrence with makes its secant slopes and . For , [F3] at gives and [F3] at gives ; at the middle slope is itself and . Either way , and exponentiation yields .
Iterating the recurrence gives and, by induction from [F2], .
Divide the bounds of step 1.1 by the positive product in step 1.2. Use the upper bound at and the lower bound with replaced by ; both then have the common term , and they become .
Bohr--Mollerup characterisation of the real Gamma function
Statement
Gamma is the unique positive log-convex function with and .
Facts & Assumptions
Given: The real Gamma function and an arbitrary positive log-convex function satisfying the displayed normalization and recurrence.
Every such function lies between common factorial bounds whose ratio is for (Log-convex solutions of the Gamma recurrence obey the Bohr--Mollerup factorial squeeze).
For every , , and (The real Gamma functional equation ).
The real Gamma function is strictly log-convex on (The real Gamma function is strictly log-convex).
Every real lies in a unique half-open unit interval between consecutive integers (Integer part: for every real there is exactly one integer with ).
Proof
Gamma is positive by its Euler integrand, normalized and recurrent by [F2], and log-convex by [F3]. Thus it satisfies the characterizing properties.
Fix . Apply [F1] to and to Gamma. Both lie between and for every , and the ratio of these bounds tends to . The squeeze theorem therefore gives .
By [F4], every positive real is an integer shift of a unique . Iterating the common recurrence from [F2] and the hypothesis on extends the equality of step 2.1 from that strip to .
Step 1.1 proves that Gamma has the properties, and steps 2.1 and 3.1 prove that every function with them equals Gamma. This is the claimed characterization.
Symmetry and the trigonometric form of the real Beta integral
Statement
For , .
Facts & Assumptions
Given: Positive real parameters .
If is a monotone differentiable surjection with locally integrable derivative, the proper change-of-variable hypotheses hold on every compact truncation, and is locally integrable on , then the improper integrals of and converge simultaneously and are equal when convergent (Change of variable in an improper integral).
The Beta integral converges if and only if and (Euler's Beta integral converges exactly for two positive parameters).
Proof
In the convergent integral [F2], the decreasing substitution interchanges and . By [F1], .
On compact interior truncations use , with and . The transformed integrand is .
Let the truncations tend to and . Convergence from [F2] and [F1] yields the full trigonometric integral and completes the displayed equality.
The real Beta--Gamma identity
Statement
For , .
Facts & Assumptions
Given: Positive reals and the nonnegative function on the open first quadrant.
If is locally Riemann integrable and is a compact Jordan exhaustion, then , independently of the exhaustion (Every Jordan exhaustion computes a nonnegative improper multiple integral).
If is injective and with invertible derivative on an open set, is compact Jordan, and is bounded on , then is integrable exactly when is, and their integrals are equal (Change of variables for an injective map on a compact Jordan set).
If are nondegenerate closed rectangles, is integrable on , and every section in one coordinate order is integrable, then the ordinary iterated integral in that order exists and equals the multiple integral (Riemann--Fubini on product rectangles, with lower and upper section integrals and content-zero exceptional sections).
Proof
On compact rectangles inside the first quadrant, [F3] factors the integral as a product of one-variable integrals. Passing through rectangular exhaustion by [F1] gives total improper integral .
On compact rectangles inside use , . The map is injective, its absolute Jacobian is , and [F2] transforms the integrand times Jacobian into .
A fixed nested family of such compact rectangles maps to a cofinal exhaustion of the first quadrant. By [F1] the limit is independent of this exhaustion, and by [F3] the transformed integral factors as .
Gamma is positive on the positive axis, so division of the equality in step 2.1 by gives the claimed identity.
The elementary recurrences for the real Beta function
Statement
For ,
and consequently .
Facts & Assumptions
Given: Positive real parameters .
For , (The real Beta--Gamma identity).
For every , (The real Gamma functional equation ).
Proof
By [F1] and [F2], .
Similarly, .
Adding steps 1.1 and 1.2 and using gives .
from the Gaussian integral
Statement
.
Facts & Assumptions
Given: Euler's Gamma integral at .
If is a monotone differentiable surjection with locally integrable derivative, the proper change-of-variable hypotheses hold on every compact truncation, and is locally integrable on , then the improper integrals of and converge simultaneously and are equal when convergent (Change of variable in an improper integral).
The Gaussian integral is (The Gaussian integral ).
Proof
In , use on proper truncations. By [F1], the improper limit is .
The integrand is even, so splitting [F2] at zero shows .
Combining the two identities gives , with the positive square root selected because Gamma is positive.
Remarks
The independent Wallis-product route is by Wallis's product.
by Wallis's product
Statement
.
Facts & Assumptions
Given: Positive integers tending to infinity.
For and , (Gautschi's inequality for the real Gamma function).
For naturals , ( for ; hence , the quotient is a natural number, and ).
For every , (The real Gamma functional equation ).
Proof
Iterating [F4] gives , with the empty product valid at .
Apply [F1] with and . After inversion, , so this middle sequence tends to .
By step 1.1 and [F3], the middle sequence is . Fact [F2] makes its limit , while step 1.2 makes the same limit .
Positivity of Gamma and uniqueness of limits therefore give .
Remarks
This proof uses Gautschi and Wallis. The Gaussian-integral proof from the Gaussian integral is logically independent of it.
Stirling's factorial asymptotic holds up to a positive constant
Statement
There is a constant such that . Here tends to infinity through the positive integers.
Facts & Assumptions
Given: Positive integers and the logarithm on positive reals.
The positive series converges exactly when (The p-series for a real exponent p converges exactly when p is greater than one).
Proof
Put . After , expand by [F1]. Integration over the symmetric interval cancels the odd powers, and the remaining absolutely convergent even series gives for one constant and all .
By step 1.1 and [F2] with , the series converges absolutely.
Summing the definition of from to telescopes the integrals to . Fact [F3] gives the primitive , and comparison of with shows that converges to a real constant .
Exponentiating step 3.1 and putting gives , which is the stated asymptotic.
Wallis's product determines the Stirling constant as
Statement
The constant in the preceding asymptotic is .
Facts & Assumptions
Given: The positive constant from the preceding lemma.
There is a constant such that (Stirling's factorial asymptotic holds up to a positive constant).
The Wallis consequence is (The central binomial coefficient is asymptotic to 4^n divided by the square root of pi n).
For , , so ( for ; hence , the quotient is a natural number, and ).
Proof
Insert the two asymptotics of [F1] into the quotient [F3]. Cancellation gives .
Comparing the positive leading coefficient in step 1.1 with [F2] gives . Since , .
Stirling's formula for factorials
Statement
as the positive integer tends to infinity.
Equivalently,
Facts & Assumptions
Given: Positive integer tending to infinity.
There is a constant such that (Stirling's factorial asymptotic holds up to a positive constant).
The constant in that asymptotic is (Wallis's product determines the Stirling constant as ).
Proof
Insert [F2] into [F1] and combine .
By the definition of asymptotic equivalence, step 1.1 is exactly the displayed ratio limit. The restriction keeps its denominator positive.
The closed form for the volume of the unit -ball
Statement
For every , . Here is an integer.
Facts & Assumptions
Given: Unit-ball volumes in positive integer dimensions.
One has for , and for , (Closed Euclidean balls are Jordan measurable and their volumes satisfy the slicing recursion).
For , (The real Beta--Gamma identity).
For , (The real Gamma functional equation ).
Proof
In dimension , [F1] gives , while [F3] and [F4] give .
Assume the formula in dimension . In the integral of [F1], symmetry followed by gives . By [F2] and [F3], this equals .
Multiply the expression in step 1.2 by the induction value ; the common Gamma factor cancels, giving . This discharges the induction.
The volume of a radius- closed -ball is
Statement
For and , , where is an integer.
Facts & Assumptions
Given: Positive integer and radius .
One has for , and for and , (Closed Euclidean balls are Jordan measurable and their volumes satisfy the slicing recursion).
For every , (The closed form for the volume of the unit -ball).
Proof
If , the ball is a singleton of content zero, and the right side is zero because .
Suppose . For , . For , substitute in [F1]; the power and differential contribute and , so comparison with [F1] at radius gives .
Insert [F2] into step 1.2 and combine it with the zero-radius case of step 1.1. This gives the displayed formula for every allowed .
The volume of the unit -ball tends to zero with dimension
Statement
as . The limit is through the positive integers.
Facts & Assumptions
Given: The positive sequence of unit-ball volumes .
For every , (The closed form for the volume of the unit -ball).
For every , (The real Gamma functional equation ).
Proof
From [F1] and [F2], for every .
Choose an integer threshold after which . Along each parity chain, step 1.1 then bounds every later volume by a fixed initial volume times successive powers of , which tend to zero by [F3].
Both the odd-dimensional and even-dimensional subsequences tend to zero, so their interleaving also tends to zero.
The unit-ball volume is maximal in dimension five
Statement
Among positive integer dimensions, the unit-ball volume is uniquely maximal at .
Facts & Assumptions
Given: Unit-ball volumes for positive integers .
For every , (The closed form for the volume of the unit -ball).
For every natural , the Gregory--Leibniz formula writes as its partial sum through plus a signed remainder of magnitude at most (The Gregory-Leibniz series: pi over four equals 1-1/3+1/5-1/7+...).
For every , , and (The real Gamma functional equation ).
Proof
In [F2], the partial sum through is and its remainder is positive, so . The partial sum through is and its remainder is negative, so .
Facts [F1] and [F3] give . Using step 1.1, the odd chain increases through and then decreases, while the even chain increases through and then decreases.
From [F3], by [F4], and . Hence [F1] gives and . The upper bound from step 1.1 gives .
Step 2.1 identifies the unique maximum within each parity chain, and step 2.2 compares the two candidates. Therefore is the unique global maximum.
5 · Examples, counterexamples and false statements
None yet.
Sources
- University of Toronto MAT237Y1, The Gamma Function and the Beta Function, §1.5
- K. Chandrasekharan, Lectures on the Riemann Zeta-Function, Lecture 7 §4
- University of Toronto MAT237Y1, The Gamma Function and the Beta Function, §1
- K. Chandrasekharan, Lectures on the Riemann Zeta-Function, Lecture 6 §1
- K. Chandrasekharan, Lectures on the Riemann Zeta-Function, Lecture 6 §1(i)
- University of Toronto MAT237Y1, The Gamma Function and the Beta Function, §1.1
- University of Toronto MAT237Y1, The Gamma Function and the Beta Function, §2
- University of Toronto MAT237Y1, The Gamma Function and the Beta Function, §2.1
- University of Toronto MAT237Y1, The Gamma Function and the Beta Function, §1.2
- K. Chandrasekharan, Lectures on the Riemann Zeta-Function, Lecture 6 §1(iv)
- University of Toronto MAT237Y1, The Gamma Function and the Beta Function, §1.3(a)
- K. Chandrasekharan, Lectures on the Riemann Zeta-Function, Lecture 6 §1(ii)
- University of Toronto MAT237Y1, The Gamma Function and the Beta Function, §1.3(c,d)
- University of Toronto MAT237Y1, The Gamma Function and the Beta Function, §1.5(c)
- University of Toronto MAT237Y1, The Gamma Function and the Beta Function, §2.2(a)
- University of Toronto MAT237Y1, The Gamma Function and the Beta Function, §2.2(b)
- K. Chandrasekharan, Lectures on the Riemann Zeta-Function, Lecture 6 §1(vi)
- University of Toronto MAT237Y1, The Gamma Function and the Beta Function, §2.2
- University of Toronto MAT237Y1, The Gamma Function and the Beta Function, §1.4
- University of Toronto MAT237Y1, The Gamma Function and the Beta Function, §2.3
- K. Chandrasekharan, Lectures on the Riemann Zeta-Function, Lecture 6 §1(v)
- University of Toronto MAT237Y1, The Gamma Function and the Beta Function, §2.3(g)
- K. Chandrasekharan, Lectures on the Riemann Zeta-Function, Lecture 7 §6
- University of Toronto MAT237Y1, The Gamma Function and the Beta Function, §2.4(d)
- Sheldon Axler, Measure, Integration & Real Analysis, §5C
- University of Toronto MAT237Y1, The Gamma Function and the Beta Function, §2.4(a,e)
- Sheldon Axler, Measure, Integration & Real Analysis, §5C, Exercise 12(a)
- Sheldon Axler, Measure, Integration & Real Analysis, §5C, Exercise 12(b)