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Infinite-dimensional Gaussian random-walk reverse flow is singular
Statement refuted
Assume the Axiom of Choice and fix . Let with its complete coordinate basis positively indexed as , where has its nonzero coordinate at . Write for coefficients in this basis throughout. Take mutually independent standard normal variables and set These series converge almost surely in and define independent centered Borel Gaussian random elements with the same law . Define the Gaussian random-walk proposal , its probability kernel its forward flow , and its transpose . Then and are mutually singular: a Borel set satisfies For the same reference law and scale, the pCN proposal flow is symmetric.
Statement references
Facts & Assumptions
Given: AC, , and the Gaussian sequence and Hilbert-space notation of the Statement.
AC implies both Dependent Choice and Countable Choice. The Axiom of Choice AC implies DC implies countable choice
Under Countable Choice and Dependent Choice, a countable independent sequence with the standard normal law exists. The Axiom of Countable Choice () The axiom of dependent choice: a relation in which every element is related to something admits an -indexed chain Countably many independent copies of a prescribed law exist
After the explicit reindexing for , the coordinate vectors form a complete orthonormal basis of , and the norm squared is the sum of coordinate squares. Coordinate vectors form the Hilbert basis of real ell-two
For independent standard normal coordinates and weights , the series converges almost surely in and defines a centered Borel Gaussian random element. Its coordinates are . Weighted Hilbert Gaussian series and prior regularity Coordinate vectors form the Hilbert basis of real ell-two
Disjoint subfamilies of an independent family generate independent sigma-algebras, and measurable functions of independent random elements remain independent. Independent random elements Disjoint groups of an independent sigma-algebra family remain independent Measurable coordinatewise functions preserve independence
A variable has mean zero, second moment one, and fourth moment three. Location-scale normal laws have their stated mean and variance A normal variable has finite fourth moment
Expectations of integrable products of independent variables factor. Expectations factor over finite products of independent random variables
IID square-integrable real variables satisfy the strong law of large numbers. Identical distribution and IID families Iid finite variance strong law
For a probability measure and a probability kernel, the associated joint flow is a probability measure with the iterated-integral identity. Measure kernel and probability kernel A prior and model kernel define a joint law
Integrating a Borel function against a random-element law equals its expectation; independent random elements have product joint law. Law or distribution of a random element Change of variables for expectation Independent random elements have product joint law
The Borel sigma-algebra of a topological space is generated by its open sets; Borel measurable functions are closed under finite arithmetic operations. The Borel sigma-algebra of a topological space Arithmetic and lattice operations preserve measurability whenever they are defined
The finite-support vectors with rational coordinates form a countable dense subset of : for each the rational vectors supported in the first coordinates are countable by the rational countability and finite product facts, their union is countable by Countable Choice, and density follows from finite truncation convergence and rational approximation of each finite coordinate list. The positive rational-radius norm balls are open in the induced metric topology and give a countable base: given with open, choose with , then in the dense set with and a positive rational with ; the triangle inequality gives . Thus is second-countable, the Borel sigma-algebra on is the product sigma-algebra, and integration of a nonnegative product-measurable function against a probability kernel gives a measurable function of its source point. The Axiom of Choice AC implies DC implies countable choice The Axiom of Countable Choice () Coordinate vectors form the Hilbert basis of real ell-two is countably infinite A product of two at most countable sets is at most countable Every subset of an at most countable set is at most countable Countable unions of at most countable sets, assuming The rationals embed densely in the reals Separability: the existence of an at most countable dense subset Second countability: an at most countable basis for the topology A norm on a real vector space, the induced metric, and the dictionary with the metric axioms Open ball, closed ball and sphere in a metric space The metric topology: a set is open when every one of its points has a ball around it inside the set; closed means open complement Arbitrary unions and finite intersections of open sets are open, open balls are open and closed balls are closed Borel sigma-algebra of a product of second-countable spaces Measurability of integration against a kernel A continuous map has Borel preimages of Borel sets
For the same Gaussian reference law and , the pCN proposal pair law is symmetric. The pCN Gaussian reference pair law is symmetric
Under Countable Choice, Borel probability laws on a separable Hilbert space with the same finite coordinate laws in a complete orthonormal basis are equal. The Axiom of Countable Choice () AC implies DC implies countable choice Borel laws on a separable Hilbert space are determined by basis coordinates
Proof
Given: The hypotheses and notation in the Statement.
By [A1] and [F1], take a countable independent sequence with law and put , . Each subsequence is again IID standard normal. The odd and even coordinate sigma-algebras are independent by [F4]. Apply [F3] with , , and to each subsequence. Since , both series converge almost surely in and define centered Borel Gaussian random elements. Their finite coordinate laws agree: by [F3], each finite coordinate vector is obtained by multiplying independent standard normals by the same coefficients , so each vector has the same product normal law by [F5] and [F9]. AC implies Countable Choice by [A1], so [F13] identifies their Borel laws. Each limit is measurable with respect to its own coordinate sigma-algebra: its partial sums are block-measurable, the event that they are Cauchy is a countable combination of measurable norm inequalities, and the limit, set to zero on the null complement, is therefore block-measurable. In detail, for a proper open with closed complement , on the convergence event the preimage of is the condition ; the distance function is 1-Lipschitz, and the zero value assigned off that event is included exactly when . This is a measurable condition on the block. The odd and even coordinate sigma-algebras are independent by [F4], hence and are independent. Denote their common law by .
For , set Each coordinate map is continuous since by [F2]; finite arithmetic operations make Borel by [F10]. Explicitly, so is Borel by [F10]. The limit criterion follows because for every one can choose with .
For each , is the pushforward of under the continuous map , hence is a probability measure. By [F11], is second-countable and the product Borel sigma-algebra is . For Borel , addition and scalar multiplication make continuous, so is product-measurable. Integrating it against the constant kernel is measurable by [F11], so is a probability kernel. Its joint flow exists by [F8]. By the product joint law [F9] and the proposal pushforward, is the law of .
For each , define The pairs are independent by grouping the independent coordinates, and have the same product standard-normal law by [F9]. Applying the same polynomial map to each pair therefore makes IID by [F4] and [F9]. By [F5]–[F6], , , and They are square-integrable: using , where independence gives and [F5] gives . By [F7],
Under the forward flow , the pair has the law of from step 2.1, and . Step 2.2 therefore gives . Under the transpose , the pair has the law of , and . Since , , hence .
Thus and its complement are disjoint Borel sets with and . This is mutual singularity of the two probability measures, and in particular neither is absolutely continuous with respect to the other. By [F12], the pCN reference proposal flow at this same scale equals its transpose.
Depends on
- Countably many independent copies of a prescribed law exist
- Iid finite variance strong law
- The Axiom of Choice
- The Borel sigma-algebra of a topological space
- The Axiom of Countable Choice ($\mathrm{AC}_\omega$)
- The axiom of dependent choice: a relation in which every element is related to something admits an $\mathbb{N}$-indexed chain
- Identical distribution and IID families
- Independent random elements
- Law or distribution of a random element
- Measure kernel and probability kernel
- Open ball, closed ball and sphere in a metric space
- The metric topology: a set is open when every one of its points has a ball around it inside the set; closed means open complement
- A norm on a real vector space, the induced metric, and the dictionary with the metric axioms
- Separability: the existence of an at most countable dense subset
- Second countability: an at most countable basis for the topology
- Standard normal and normal laws
- Coordinate vectors form the Hilbert basis of real ell-two
- Weighted Hilbert Gaussian series and prior regularity
- The pCN Gaussian reference pair law is symmetric
- Borel laws on a separable Hilbert space are determined by basis coordinates
- Measurable coordinatewise functions preserve independence
- Location-scale normal laws have their stated mean and variance
- The rationals embed densely in the reals
- Every subset of an at most countable set is at most countable
- A normal variable has finite fourth moment
- A prior and model kernel define a joint law
- Arithmetic and lattice operations preserve measurability whenever they are defined
- Change of variables for expectation
- Countable unions of at most countable sets, assuming $\mathrm{AC}_\omega$
- AC implies DC implies countable choice
- A continuous map has Borel preimages of Borel sets
- Disjoint groups of an independent sigma-algebra family remain independent
- Independent random elements have product joint law
- Measurability of integration against a kernel
- Arbitrary unions and finite intersections of open sets are open, open balls are open and closed balls are closed
- Expectations factor over finite products of independent random variables
- Borel sigma-algebra of a product of second-countable spaces
- A product of two at most countable sets is at most countable
- $\mathbb{Q}$ is countably infinite
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Sources
- S. L. Cotter, G. O. Roberts, A. M. Stuart, and D. White, MCMC Methods for Functions: Modifying Old Algorithms to Make Them Faster, Statistical Science 28(3) (2013) (standard reference, not scraped)
- Yury Korolev and Jonas Latz, Inverse Problems: Lecture Notes, Michaelmas Term 2020 (University of Cambridge, 18 May 2021) (standard reference, not scraped)