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Classical coherence matrices and measurement scope
1 · Prerequisites
- Absolute and Conditional Convergence; Rearrangement; Products
- Analyticity of Holomorphic Functions; Liouville and Morera
- Angular-spectrum optics and controlled paraxial limits
- Approximation and Compactness in C(K)
- Arc Length and Rectifiable Curves
- Areas of Elementary Plane Figures
- Banach-Space Differential Calculus and Banach Manifolds
- Binary Operations, Monoids, Groups and Subgroups
- Bounded Linear Operators and Quotient Spaces
- Bounded Variation and the Riemann–Stieltjes Integral
- Causal kernels, gauge and point fields after wave existence
- Character Groups and Elementary LCA Duals
- Cm Math Central
- Cm Math Evidence
- Compactness
- Compactness in Metric Spaces
- Completeness, Completion, and Uniform Continuity
- Complex Coordinate and Path Transport
- Complex Differentiability and the Cauchy–Riemann Equations
- Complex Lp Spaces and Test-Function Conventions
- Complex Norms and Realification
- Complex Power Series and Analytic Functions
- Complexification, Realification and Real Structures
- Connectedness
- Constant Rank, Submersions, Immersions and Regular Level Sets
- 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
- Contour Integration
- Cosets, Index and Lagrange's Theorem
- Countability and Uncountability
- Countability Axioms and Cardinal Functions
- Darboux, L'Hôpital, and Taylor's Theorem
- Density Separability and Convolution in Lᵖ
- Determinants of Matrices over a Commutative Ring
- Distributions Test Functions and Differentiation
- Divisibility, Euclidean Domains, Principal Ideal Domains and Unique Factorisation
- Divisibility, Greatest Common Divisors and Bézout's Identity
- Dual Spaces, Bilinear and Quadratic Forms, and Sylvester's Law of Inertia
- Em Elementary Mathematical Prerequisites
- Em Expanded Analysis Prerequisites
- Energy momentum angular balance
- Equivalent Forms of Completeness
- Euclidean Surface Measure, Divergence, and Green Identities
- Exterior Powers, Orientation and Hodge Duality
- Filters and Ultrafilters
- Finite Counting, Factorials and Binomial Coefficients
- Finite Dimensional Normed Spaces and Riesz Lemma
- Finite Probability and the Probabilistic Method
- Finite Probability Spaces and Random Variables
- Foundations of the Real Numbers for Analysis
- Fourier Transform Convolution and Approximate Identities
- Free Modules, Exact Sequences, Projective and Injective Modules
- Fubini and Change of Variables
- Function Space Topologies and the Exponential Law
- Fundamental Solutions Newtonian Potentials and Green Functions
- Fundamental Trigonometric Identities
- Further Trigonometric Identities and Inverse Functions
- Gaussian Elimination, Elementary Matrices and Reduced Row Echelon Form
- Goursat's Theorem and Cauchy's Theorem in a Convex Domain
- Group Actions, Orbits, Stabilisers and Cayley's Theorem
- Group Homomorphisms and the Isomorphism Theorems
- Harmonic Functions and Mean Values in Rn
- Hausdorff via the Diagonal
- Hereditary and Productive Behaviour of the Separation Axioms
- Hilbert Space Geometry and Riesz Representation
- Ideals, Quotient Rings and the Isomorphism Theorems for Rings
- Improper and Parameter-Dependent Multiple Integrals
- Improper Integrals
- Inner Product Spaces, Gram-Schmidt, Projections and Adjoints
- Lebesgue Measure on Euclidean Space
- Limits of Real Functions
- limsup, liminf, and Subsequential Limits
- Line Integrals and the Gradient Theorem
- Linear Algebra Methods in Combinatorics
- Linear Independence, Bases and Dimension
- Linear Transformations, Rank-Nullity and Quotient Spaces
- Lorentz Transformations
- Manifolds with Boundary Collars and Orientations
- Material response and stationary interfaces
- Matrices, the Matrix of a Linear Map, and Change of Basis
- Maximum Principles Harnack and Liouville in Rn
- Measurable Functions and Simple Approximation
- Measures and Their Basic Properties
- Metric Spaces
- Minkowski Theory and Number Field Class Groups
- Mixed Partials, Taylor Formulae, and Extrema
- Modes of Convergence Egorov and Lusin
- Modules, Submodules, Quotient Modules and the Isomorphism Theorems
- Monotone Functions, Discontinuities, and Continuity Sets
- Monotone Sequences, Bolzano-Weierstrass, and Cauchy Completeness
- Normal Subgroups and Quotient Groups
- Normed and Banach Spaces
- Norming and Separation under Hahn–Banach
- Order, Zorn's Lemma, and the Axiom of Choice
- Orthonormal Bases, Parseval and Fourier Series
- Outer Measure and the Caratheodory Extension Theorem
- Partial Differential Equations and Characteristics
- Partitions of Unity and Paracompactness
- pi: the Equivalent Characterizations
- Pointwise Extended-Real Function Products
- Poisson Problems and Interior Harmonic Estimates
- Poisson Summation Sampling and Lattice Duality
- Polynomial Rings, the Division Algorithm and Roots
- Potentials and gauge
- Power Series and Real-Analytic Functions
- Primitives and postulates
- Probability Spaces Random Variables and Expectation
- Product Measures and the Fubini Tonelli Theorems
- Projective Algebraic Sets Projective Morphisms and Cones
- Properties of the Integral and the Working FTC
- Radon Measures and the Riesz Markov Kakutani Theorem
- Rank Theorems and Embedded Submanifolds
- Rees Modules Artin Rees and Hilbert Samuel Theory
- Regular Surfaces and Surface Integrals
- Relations, Functions, and Quotients
- Rings, Subrings, Integral Domains and Fields
- Rⁿ as a Normed Space; Vector-Valued Functions
- Roots, Rational Powers, and Classical Inequalities
- Schwartz Space and the Plancherel Theorem
- Separation Axioms: the Hierarchy
- Sequences and Limits
- Sequences and Series of Functions; Uniform Convergence
- Series: Convergence and the Nonnegative Tests
- Sigma Algebras and Borel Sets
- Signed and Complex Measures Hahn and Jordan
- Simple Field Extensions and the Construction of the Complex Numbers
- Sine, Cosine, and the Definition of Pi
- Smooth Approximation and Sobolev Extension
- Smooth Manifolds and Smooth Maps
- Smooth Partitions of Unity and Exhaustions
- Smooth Vector Bundles and Sections
- Spacetime Primitives
- Stone–Weierstrass in General
- Subspaces, Products, and Quotients
- Suprema and Infima
- Symmetric Groups, Cycle Decomposition and the Sign Homomorphism
- Tangent Cotangent and the Differential
- Tensor Fields Exterior Algebra and Differential Forms
- Tensor Products of Modules
- The Ascoli–Arzelà Theorem
- The Cantor Set, Baire Category, and Measure Zero in ℝ
- The Complex Exponential and Euler's Formula
- The Derivative and the Mean Value Theorems
- The Determinant of a Linear Operator, Cofactors and Cramer's Rule
- The Divergence Theorem and Classical Stokes
- The Exponential Function
- The Fundamental Group of the Circle
- The Fundamental Theorems of Calculus
- The Identity Theorem, the Maximum Principle and the Open Mapping Theorem
- The Inverse and Implicit Function Theorems
- The Inverse Function Theorem Completed
- The Lebesgue and Riemann Integrals Compared
- The Lebesgue Integral and the Convergence Theorems
- The Logarithm and General Powers
- The Lᵖ Spaces Holder Minkowski and Riesz Fischer
- The Maximal Function and Lebesgue Differentiation
- 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
- Transverse fields, helicity and angular momentum
- Triangularisation, Generalised Eigenspaces and Jordan Canonical Form
- Uniform Spaces: the Three Definitions
- Vacuum waves and polarization
- Vector PEC scattering, dipole limits and controlled scalar diffraction
- Vector Spaces, Linear Subspaces, Span and Direct Sums
- Volumes of Elementary Solids and Solids of Revolution
- Wave Equation Representation Formulas
- Weak Derivatives and Sobolev Spaces
- Whitney Embedding Tubular Neighbourhoods and Approximation
- Worldlines And Clocks
2 · Summary
3 · Logical flowchart
4 · Definitions, postulates, theorems and proofs
Classical two-component coherency matrix
An ideal classical ensemble of two complex transverse electric-field components at a specified plane in a fixed positively oriented SI laboratory chart, using the exp(-i omega t) convention and the cone specified in the Definition. Gamma is an uncentered second-moment matrix of the two-component projection; it is not a quantum density operator or a full three-dimensional coherence matrix. The paraxial suppliers bound longitudinal amplitude for individual exact plane modes but do not supply an aggregate ensemble or detector-error bound. No measurement, absolute radiometric calibration, sampling law, or empirical claim is made. A time average is not identified with the ensemble expectation without separately stated stationarity and ergodicity assumptions.
Definition
Fix a named, positively oriented SI laboratory chart with coordinates and angular frequency . Adopt the SI constants and coordinate units of the laboratory convention: is in m s, is in m, and electric-field components are in V m. Let be a specified reference plane, where and is a specified nonempty region. Let be the positively oriented orthonormal coordinate basis of the chart. The ordered transverse basis of is and its normal is .
For the paraxial context, adopt , , and . The angular-spectrum variable is measured in cycles per metre, is in m, and the forward propagating cone is with . Here . The matrix below is defined pointwise for the two-component projection; it does not assert that an arbitrary random superposition is an exact Maxwell field or that the individual-mode longitudinal bound extends to an ensemble without additional hypotheses.
Let be a specified probability space. Identify with by real and imaginary coordinates and equip it with the Euclidean Borel -algebra; measurable maps to are understood with respect to this -algebra. At each fixed , let be measurable. Let be the first and second continuous coordinate projections, and define the coordinate random variables and . Thus for . The map is defined by the four real coordinate maps of ; these maps are continuous, so is measurable as their composition with . No joint measurability in is assumed or used. Define Since , assume is square-integrable, equivalently . For , and , define the associated transverse real-field model by , where is applied componentwise. Expectation is taken over this declared classical ensemble and is applied componentwise to complex integrable variables. Regard vectors in as columns. For a column define ; for a matrix define , where is obtained by conjugating each entry. Put and . Define Thus is the uncentered second-moment matrix of the two selected components; no zero-mean assumption is made. At each fixed , suppressing the argument in these coordinate names, define the Stokes coordinates When , define the degree of polarization by The minus sign in is fixed by the stated phasor convention and the ordered basis . In this two-component model, call the ensemble at unpolarized when and , where is the identity matrix; this label concerns second moments and does not say that any realization is a quantum state. For the transverse electric-field interpretation, the have units (V m); is a mean-square field coordinate, not an absolutely calibrated irradiance.
The same algebraic construction applies to any ordered pair of square-integrable classical complex amplitudes of a common physical unit; the second moments then have the square of that unit. When the pair labels transverse electric components, the have the polarization interpretation just defined. When it labels two beam channels, the same matrix entries are channel correlations; they are not polarization components.
Definition references
Polarization of a transverse plane wave: linear, circular and elliptical traces, and handedness
Framework-local SI units, the vacuum constants and the exact/measured status of their values
Paraxial phase and longitudinal-field bounds
Mean vector and covariance matrix of a square-integrable random vector
Real and imaginary parts, complex conjugation, and modulus
Linearity, monotonicity, and the modulus bound for expectation
Facts & Assumptions
Given: A fixed detector plane and transverse basis, , a probability space , and for each chosen a measurable for which the associated real coordinate vector in the Definition is square-integrable. Use SI units and the phasor convention.
Mean vector and covariance matrix of a square-integrable random vector: a probability space has total measure one; a measurable real random vector with finite second moment has integrable coordinates and finite second moments. We use this probability and integrability interface, not its centered covariance matrix.
Real and imaginary parts, complex conjugation, and modulus and Linearity, monotonicity, and the modulus bound for expectation: complex conjugation, real and imaginary parts, and modulus are componentwise operations; expectation of an integrable complex variable is the pair of its real expectations and is linear.
The probability law is an adopted ensemble model. Replacing its expectation by a long-time average requires additional stationarity and ergodicity hypotheses; no sampled or measured average is asserted here.
Proof
Fix and write for , with and the four real coordinate maps of . The real and imaginary parts of are and ; these are continuous polynomial functions of , hence measurable. The diagonal products are integrable by the given finite second moment, and pointwise. Hence every entry is a finite complex expectation under [F1]–[F2], so is well-defined.
Componentwise conjugation and linearity of the real integrals give ; the diagonal entries satisfy by monotonicity of expectation. Therefore .
Remarks
The matrix is uncentered: unless the ensemble mean vanishes, it is not the centered covariance matrix. The individual-mode longitudinal bound from Paraxial phase and longitudinal-field bounds does not give an aggregate bound for a random superposition, so none is claimed. A detector model, calibration, noise law, finite-sample uncertainty, or equality between time and ensemble averages must be supplied separately.
Stokes cone and deterministic Jones transformations
Conditional algebra for the classical two-component coherency matrix defined in this library. For transverse electric components its four real coordinates are the stated Stokes parameters; for other classical two-channel amplitudes the same cone is an algebraic second-moment constraint, not a polarization interpretation. No quantum-state identification, apparatus model, empirical observation, or finite-sample claim is made.
Statement
Let be a measurable square-integrable complex two-component vector on a probability space and define , with . Put , , , and ; when , put . Then is positive semidefinite, meaning for every ; its rank is the complex dimension of its image. The Stokes coordinates satisfy Equality in the second relation holds exactly when or has rank one. Consequently when , and it is undefined when . If a fixed deterministic dimensionless complex-linear map (a Jones matrix in this model) sends each realization to , then transforms to .
Statement references
Facts & Assumptions
Given: A measurable square-integrable and its matrix and Stokes coordinates from the Definition.
Classical two-component coherency matrix: , , , , , , and is defined only when .
Linearity, monotonicity, and the modulus bound for expectation: expectation of an integrable complex variable is linear.
is a fixed deterministic linear map, not a random matrix correlated with ; its entries are dimensionless and the output amplitudes use the same component units as the input.
Proof
For , the finite sum has an integrable squared modulus, because it is bounded by . Expanding the finite matrix product therefore gives . Hence is positive semidefinite.
Write , where . If , positivity applied to gives , hence . If and , positivity at gives for every , which fails for sufficiently large ; thus and again .
The definitions give and . Step 2.1 therefore proves . Equality is equivalent to , which for a positive-semidefinite matrix means rank below two; it is rank zero exactly when , and otherwise rank one. When , taking nonnegative square roots gives ; when the quotient is undefined by its Definition.
Since is fixed, for every realization. Taking the componentwise expectation and using [F2]'s linearity gives .
Remarks
This is a conditional identity for an ensemble second-moment model. A deterministic Jones transformation is not a model of a general random, depolarizing, or statistically estimated optical device.
Visibility bound in a specified two-beam model
Conditional result for an ideal scalar two-beam classical phasor model with a common ensemble, finite second moments, a controllable full relative-phase sweep, and mean-square amplitude as the detector-response model. The here is the cross-moment between two beam channels; it is not the transverse-polarization cross-component of one beam. The visibility is the model contrast, not a finite-sample estimate. No detector calibration, noise model, empirical observation, or unconditional claim about measured fringe visibility is made.
Statement
Let be jointly measurable classical phasor amplitudes at one fixed observation point for a single selected scalar field component, on one probability space, each in V m, with . Define and . Adopt the ideal scalar two-beam model with a phase multiplier ranging over the full unit circle . For each , set and . The quantities and are mean-square field coordinates in (V m), not calibrated irradiances. Set and . When , define the model visibility by Then
Statement references
Facts & Assumptions
Given: The common probability space, square-integrable beam amplitudes , a full controllable phase sweep, and the ideal mean-square detector model stated above.
Classical two-component coherency matrix: applying its second-moment construction to gives , , and . Here the coordinates are distinct beam channels, not polarization components.
Stokes cone and deterministic Jones transformations: every such second-moment matrix is positive semidefinite, so its entries obey .
Linearity, monotonicity, and the modulus bound for expectation: expectation of the integrable cross terms is linear and commutes with complex conjugation under the componentwise complex-integral convention.
Real and imaginary parts, complex conjugation, and modulus: write a complex number as , take its conjugate as , and define its modulus by .
The ideal detector output is the ensemble mean of the squared modulus of the coherently summed phasor; no finite-sample or noisy detector response is assumed.
Proof
Expanding the squared modulus in [A1] gives . Taking expectations, using [F1] and [F3], yields .
Put and . Write and . Since , . By [F4], and . Therefore so each lies in . If , set and . Then , so , and direct multiplication gives while . Both endpoints are therefore attained. If , the cross term is identically zero. Hence and .
By [F2], ; since , this gives . Under the given condition, , so substitution of step 2.1 into the visibility definition gives .
Remarks
The displayed is a phase-extremized ensemble-model contrast. A finite set of detector readings need not attain it; estimating visibility from data requires separate sampling, calibration, uncertainty, and detector-response assumptions. This theorem supplies none of those empirical inputs.
5 · Examples, experiments and counterexamples
None yet.
Sources
- José J. Gil, Polarimetric Characterization of Light and Media, §2.1–2.6, author-revised 2020 version of Eur. Phys. J. Appl. Phys. 40 (2007)
- José J. Gil, Polarimetric Characterization of Light and Media, §2.1–2.3, author-revised 2020 version of Eur. Phys. J. Appl. Phys. 40 (2007)
- Optics Lectures, University of Oxford, 2012, sections on coherence and interferometers
- A. Hemmerich, Lectures on Classical Optics, Part III (2023)