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The Real Gamma and Beta Functions: Examples and Counterexamples
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
- 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
- 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 Real Gamma and Beta Functions
- 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
3 · Logical flowchart
4 · Definitions, theorems and proofs
None yet.
5 · Examples, counterexamples and false statements
Special values of the real Gamma and Beta functions
Example
The real Gamma and Beta functions have the values
Facts & Assumptions
Given: The displayed positive arguments.
For every , , and (The real Gamma functional equation ).
For , (The real Beta--Gamma identity).
Verification
Repeated use of [F1] gives , , and .
Fact [F2] and [F1] give and .
Substituting the integer values into [F3] gives and .
The unit-ball volumes through dimension eight from the Gamma formula
Example
For dimensions through , the unit-ball volumes are
Facts & Assumptions
Given: Positive integer dimensions .
For every , (The closed form for the volume of the unit -ball).
For every , (The real Gamma functional equation ).
Verification
Substitute into [F1] and use [F2] and [F3]. This gives .
The same substitution with [F2] and [F3] for gives .
Steps 1.1 and 1.2 establish every value in the displayed list.
A positive convex function need not be log-convex
Example
The identity function on is positive and convex, but it is not log-convex.
Facts & Assumptions
Given: The identity function on the positive real axis.
A positive function is log-convex when its logarithm is convex (Log-convex positive functions).
The natural logarithm is strictly increasing on (Order, continuity, range, and the product, quotient, and reciprocal laws for the natural logarithm).
Verification
For and , , so is affine and hence convex.
The midpoint of and is . By [F2], , so violates the midpoint convexity inequality and [F1] shows that is not log-convex.
Thus this positive function is convex but not log-convex.
A positive non-log-convex solution of the Gamma functional equation
Example
Put , let , and define for . The function is positive, satisfies and , differs from Gamma, and is not log-convex.
Facts & Assumptions
Given: The constants and the function in the Example.
For every , , and (The real Gamma functional equation ).
Sine has period (The zero sets of sine and cosine and the least positive common period 2 pi).
A positive function is log-convex when its logarithm is convex (Log-convex positive functions).
Verification
By [F2], . Together with [F1], this gives and ; positivity is immediate.
At , the sine terms are respectively . Hence the midpoint value of exceeds the average of its endpoint values exactly when , which holds because . By [F3], is not log-convex.
Since , . Thus is a different positive normalized solution of the recurrence.
FALSE: normalization and the functional equation determine the real Gamma function
Statement
False claim: Gamma is the only positive function satisfying and .
Facts & Assumptions
Given: The periodic perturbation of Gamma from the preceding example.
The function is positive, satisfies and , differs from Gamma, and is not log-convex (A positive non-log-convex solution of the Gamma functional equation).
Gamma is the unique positive log-convex function with the normalization and recurrence (Bohr--Mollerup characterisation of the real Gamma function).
Refutation
By [F1], the function is positive, normalized, recurrent, and differs from Gamma.
Fact [F2] identifies the missing hypothesis: log-convexity excludes this and restores uniqueness.
Therefore normalization and the functional equation alone do not determine Gamma.
FALSE: Euler's real Gamma integral converges at the nonpositive integers
Statement
False claim: the Euler integral converges when is a nonpositive integer and thereby defines a real Gamma value there.
Facts & Assumptions
Given: A nonpositive integer .
The Euler integral converges if and only if (Euler's Gamma integral converges exactly for positive real parameters).
Refutation
Since , the reverse direction of [F1] says that the Euler integral diverges, already at its endpoint .
The real Gamma function defined by Euler's integral therefore has no value at this ; a different continuation would not be convergence of this integral.
As the argument applies to every nonpositive integer, the claim is false.
FALSE: unit-ball volume increases with dimension
Statement
False claim: the volume of the unit ball increases with the positive integer dimension .
Facts & Assumptions
Given: The sequence of positive-dimensional unit-ball volumes.
Among positive integer dimensions, the unit-ball volume is uniquely maximal at (The unit-ball volume is maximal in dimension five).
Refutation
Fact [F1] gives the explicit strict decrease , contradicting monotone increase.
Independently, [F2] says the positive volumes tend to zero, which is incompatible with an increasing positive sequence.
Either step refutes the universal monotonicity claim.
Sources
- University of Toronto MAT237Y1, The Gamma Function and the Beta Function, §§1.2, 1.4, 2.2
- University of Toronto MAT237Y1, The Gamma Function and the Beta Function, §2.4
- Sheldon Axler, Measure, Integration & Real Analysis, §5C
- University of Toronto MAT237Y1, The Gamma Function and the Beta Function, §1.5
- K. Chandrasekharan, Lectures on the Riemann Zeta-Function, Lecture 7 §4
- K. Chandrasekharan, Lectures on the Riemann Zeta-Function, Lecture 6 §1(i)
- Sheldon Axler, Measure, Integration & Real Analysis, §5C, Exercise 12