How statement and proof provenance work
The first chip identifies the source of the statement or construction; the second identifies the source of its local proof or verification.
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- AI-generated: a genuinely novel statement formulated by AI, with no source for the claim itself.
These labels describe origin, not correctness: citations and verification chips remain separate evidence.
Deterministic source classes and optimal recovery
1 · Prerequisites
- Absolute and Conditional Convergence; Rearrangement; Products
- Algebraic Closure, Embeddings, and Separability
- Algebraic Extensions, Extension Degree, and Finite Fields
- Binary Operations, Monoids, Groups and Subgroups
- Bounded Linear Operators and Quotient Spaces
- Compact linear inverse maps and the Picard criterion
- Compact Operators and Riesz Schauder Theory
- Compact Self Adjoint Hilbert Schmidt and Trace Class Operators
- Compactness
- Compactness in Metric Spaces
- Completeness, Completion, and Uniform Continuity
- Complex Norms and Realification
- Complex Subspace Realification
- Complexification, Realification and Real Structures
- Composition Series, the Jordan–Hölder Theorem and Solvable Groups
- Congruences, the Integers Modulo n and the Chinese Remainder Theorem
- 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
- Convergence: Nets and Filters
- Cosets, Index and Lagrange's Theorem
- Countability and Uncountability
- Cyclic Groups and Direct Products
- Determinants of Matrices over a Commutative Ring
- Diagonalisation and the Minimal Polynomial
- Divisibility, Euclidean Domains, Principal Ideal Domains and Unique Factorisation
- Divisibility, Greatest Common Divisors and Bézout's Identity
- Dual Spaces Adjoint Operators and Annihilators
- Dual Spaces, Bilinear and Quadratic Forms, and Sylvester's Law of Inertia
- Eigenvalues, Eigenvectors and the Characteristic Polynomial
- Filters and Ultrafilters
- Finite Counting, Factorials and Binomial Coefficients
- Finite Dimensional Normed Spaces and Riesz Lemma
- Foundations of the Real Numbers for Analysis
- Group Actions, Orbits, Stabilisers and Cayley's Theorem
- Group Homomorphisms and the Isomorphism Theorems
- Hilbert Space Geometry and Riesz Representation
- Ideals, Quotient Rings and the Isomorphism Theorems for Rings
- Inner Product Spaces, Gram-Schmidt, Projections and Adjoints
- Inverse maps, identifiability, and stability
- 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
- Normal Subgroups and Quotient Groups
- Normed and Banach Spaces
- Norming and Separation under Hahn–Banach
- Numerical Inverse Problems and Regularization Error
- Order, Zorn's Lemma, and the Axiom of Choice
- Orthonormal Bases, Parseval and Fourier Series
- Polynomial Rings, the Division Algorithm and Roots
- Power Series and Real-Analytic Functions
- Primes, Euclid's Lemma and the Fundamental Theorem of Arithmetic
- 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
- Simple Field Extensions and the Construction of the Complex Numbers
- Spectral regularization and parameter choice
- Splitting Fields
- Subspaces, Products, and Quotients
- Suprema and Infima
- Sylow's Theorems, p-Groups and Nilpotent Groups
- Symmetric Groups, Cycle Decomposition and the Sign Homomorphism
- The Analytic Hahn Banach Theorem
- 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 Exponential Function
- The Fundamental Theorem of Algebra
- The Fundamental Theorem of Finite Abelian Groups
- The Galois Correspondence
- The Logarithm and General Powers
- The Riemann Integral: Definition and Integrability
- The Spectral Theorem, Positive Operators and Singular Value Decomposition
- The ZFC Axioms and the Basic Set Constructions
- Topological Spaces and Continuity
- Topology of ℝ
- Triangularisation, Generalised Eigenspaces and Jordan Canonical Form
- Vector Spaces, Linear Subspaces, Span and Direct Sums
2 · Logical flowchart
3 · Definitions, theorems and proofs
Spectral-index source balls for compact operators
Definition
Assume Countable Choice. Let and be real or complex Hilbert spaces over the same scalar field and let be compact. Write , , and , and let be zero together with the positive eigenvalues of . An admissible spectral index is a bounded function with . Define by the compact spectral multiplier of with scalar function . For define . For , defines the power source ball . If and , define the logarithmic spectral-index candidate by and for positive ; when it is bounded, it defines .
Definition references
Centered conditional modulus of continuity
Definition
For a compact operator between real or complex Hilbert spaces over the same scalar field, write . For a set with and , define .
Index source elements are minimum-norm solutions
Statement
Assume Countable Choice. Let be compact between real or complex Hilbert spaces over the same scalar field, let be a bounded nonnegative spectral index with , and let for some . Then ; consequently, among all satisfying , is the unique vector of minimum norm.
Statement references
Facts & Assumptions
Given: Countable Choice, compact between real or complex Hilbert spaces, an admissible index function with , and .
The Axiom of Countable Choice (): Countable Choice is assumed by the compact singular-value decomposition supplier.
Singular value decomposition for compact operators: A compact operator has orthonormal right singular vectors spanning , with for each positive singular value , and .
Spectral-index source balls for compact operators and Compact spectral filters, source conditions, and qualification: A bounded spectral index acts by on each right singular vector and by on the kernel.
Hilbert space, Real and complex inner-product spaces and their induced length, and Orthogonality and the orthogonal complement: The Hilbert norm is induced by the inner product; if , then .
Proof
By [F1], write in norm, with and the an orthonormal basis of . The compact spectral multiplier in [F2] gives . This norm-convergent sum is a limit of finite linear combinations of the , so [F1] places in their closed span ; if the positive singular set is empty, the sum and closed span are both zero. Thus .
If , then . By step 1.1, , so [F3] gives , with equality only when , that is, . Thus is the unique minimum-norm solution.
Power source ball
Definition
Assume Countable Choice. Let be compact between real or complex Hilbert spaces over the same scalar field and let . The power source ball is , where is defined by compact spectral calculus. It lies in and consists of minimum-norm representatives of the exact data . In the convention this is the source condition .
Spectral interpolation for power source balls
Statement
Assume Countable Choice. Let be compact between real or complex Hilbert spaces over the same scalar field, let and , and put . Then .
Statement references
Facts & Assumptions
Given: Countable Choice, compact between real or complex Hilbert spaces, , , and .
The Axiom of Countable Choice (): Countable Choice is assumed by the compact singular-value decomposition supplier.
Singular value decomposition for compact operators: The positive singular system has orthonormal right and left singular vectors with and , and the closed span of the is .
Power source ball: The power source multiplier is .
Compact spectral filters, source conditions, and qualification: The compact spectral multiplier acts on an eigenvector by its scalar function, and the power multiplier has value zero at the zero eigenvalue.
The natural logarithm as the inverse of the exponential function, Order, continuity, range, and the product, quotient, and reciprocal laws for the natural logarithm, Real powers for positive bases, with the zero-base positive-exponent convention, The real exponential function and the number by a power series, The exponential is positive and satisfies , Continuity and derivatives of positive-base real powers, The exponent, product, quotient, and iterated-power laws for positive real bases and real exponents, The mean value theorem, as the case of Cauchy's: for continuous on with and differentiable on there is with , and Inverses of positives are positive, and reciprocation reverses order: For and , , , and ; hence the mean value theorem makes strictly increasing. For , exponent laws give , and reciprocation reverses positive inequalities.
Proof
Let index the positive singular values in [F1]. Write in norm, with . By [F2]–[F3], and , with norm-convergent expansions. For each finite , orthonormality gives the squared norms of the partial sums as the sums of squared coefficients; taking limits by continuity of the norm gives and . The same finite-sum identity and give , where , , and .
Put . For a finite , set , , and . If or , then every with is zero because , so . Otherwise, for put and . The scalar inequality holds for : for set . By [F4], . If , strict increase of gives ; by [F4] and inverse order this implies and . If , the inequalities reverse and . The mean value theorem then gives for every , while . If , apply the scalar inequality to to obtain ; if , the same inequality is immediate. Since , summing and using gives .
Exhaust by its first indices when is infinite, and take when it is finite; if is empty, all three sums in step 1.1 are zero. Passing to the limit in step 1.2 gives . Taking nonnegative square roots and substituting proves the claimed inequality.
Deterministic minimax lower bound on power source balls
Statement
Assume Countable Choice. Let be compact between real or complex Hilbert spaces over the same scalar field, , and let be its power source ball. For any deterministic reconstruction map and any , define . Then , and therefore . For any with , define the two-truth modulus . Then .
Statement references
Facts & Assumptions
Given: Countable Choice, compact between real or complex Hilbert spaces over the same scalar field, , the power source ball , a noise level , and a deterministic map .
The Axiom of Countable Choice (): Countable Choice is required by the compact spectral multiplier used to define the power source ball; the indistinguishable-data argument below uses no further choice.
Index source elements are minimum-norm solutions: Every element of lies in .
Hilbert space and The induced length is a norm: The Hilbert norm is induced by the inner product, and its triangle inequality holds.
Proof
The class contains by taking in [F1]. It is symmetric: if with , then with . It is convex: for with and , , while the triangle inequality gives . By [F3], this class is contained in , so [F2] applies.
Let satisfy . The two admissible truths and with noises and both produce the same observed datum . Their reconstruction errors are and , and the triangle inequality yields . Hence the larger error is at least , so taking the supremum over all such gives . Taking the infimum over preserves this lower bound.
If and , then lies in the class by symmetry and convexity from step 1.1 and satisfies ; thus . Conversely, for every in the centered-modulus set, the pair lies in the source ball and has , so the two-truth supremum is at least . Taking suprema proves the claimed factor of two.
Conditional modulus on a power source ball
Statement
Assume Countable Choice. Let be compact between real or complex Hilbert spaces over the same scalar field and . For every , . For every positive singular value with right singular vector , equality holds at , witnessed by . If has infinite rank, these form a null sequence; if has finite positive rank, equality is asserted only at its finitely many positive singular values; if , the source ball and modulus are and .
Statement references
Facts & Assumptions
Given: Countable Choice, compact between real or complex Hilbert spaces over the same scalar field, , the power source ball, its centered modulus, and .
The Axiom of Countable Choice (): Countable Choice is assumed by the compact singular-value decomposition supplier.
Centered conditional modulus of continuity: is the supremum of over with .
Index source elements are minimum-norm solutions: Every element of the power source ball lies in .
Spectral interpolation for power source balls: If , then .
Singular value decomposition for compact operators and Absolute value and singular values of a compact operator: Each positive singular value has a unit right singular vector with and ; an infinite positive singular sequence tends to zero.
Proof
If and belongs to the centered-modulus set, then . By [F3], as well, so and . If , [F3] likewise forces every member of the power source ball to be zero, so the asserted bound holds with no positive singular direction.
Suppose and let be any element of the centered-modulus set. By [F1], choose with and . Applying [F4] and using gives ; taking the supremum over the centered-modulus set proves the bound.
Fix a positive singular value and its unit right singular vector from [F5]. Set and . Then and . Thus is feasible in the centered-modulus supremum at and attains the upper bound from step 1.2. If there are infinitely many positive singular values, compactness gives and hence ; finite positive rank gives only the stated finite list, while was handled in step 1.1.
4 · Examples, counterexamples and false statements
None yet.
Sources
- Christian Clason, Regularization of Inverse Problems, lecture notes — Section 4.2, printed pp. 36–43
- Bernd Hofmann and Peter Mathé, A Note on the Modulus of Continuity for Ill-Posed Problems in Hilbert Space
- Christian Clason, Regularization of Inverse Problems, lecture notes — Chapter 3, compact SVD and minimum-norm solutions
- Christian Clason, Regularization of Inverse Problems, lecture notes — Lemma 3.14 and Section 4.2
- Christian Clason, Regularization of Inverse Problems, lecture notes — Theorem 4.10
- Christian Clason, Regularization of Inverse Problems, lecture notes — Theorems 4.11–4.12