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SOLIT in the mean-zero 2D satellite-gradiometry model

Example

Assume Countable Choice.

For a relative satellite radius R>1, identify the mean-zero real Fourier coefficients of a function on the unit circle with X=ℓ2(N>0;R2), where the two coordinates at frequency n are its normalized cosine and sine coefficients, and give this space the canonical inner product ⟨(an,bn),(cn,dn)⟩=∑n≥1(ancn+bndn). Interleaving with scalar coordinates z2n−1=an and z2n=bn identifies it isometrically with real ℓ2(N>0), so X is a real Hilbert space. In these coordinates define the 2D satellite-gradiometry operator by

(TR(an,bn))n≥1=(tnan,tnbn)n≥1,tn=n(n+1)R−n−2.

This is the Fourier-coordinate map for recovering the mean-zero gravitational potential from the radial second derivative measured at relative satellite radius R. Take the truth to be the Fourier coefficient sequence of f†(x)=π/2−∣x∣ on [−π,π]. Its constant coefficient is zero, so the omitted zero-frequency component is not part of this mean-zero model. The per-frequency eigenvalue of TR∗TR is μn=n2(n+1)2R−2n−4, each with multiplicity two. For the inverse sequence model, order the cosine–sine modes by nonincreasing multiplier tn, breaking ties by frequency and then placing cosine before sine; write the resulting ordered singular values as (sj) and their squares as λj=sj2. Such an ordering exists because tn→0 and only finitely many modes exceed any positive threshold. Use the Tikhonov filter qα(λ)=(λ+α)−1 and its continuous geometric-variance candidate grid in the SOLIT rule with known σ>0.

Facts & Assumptions

Given: The real cosine–sine Fourier coefficient model on the circle, R>1, the multiplier sequence tn, and the truth f†(x)=π/2−∣x∣.

[A1]

The Axiom of Countable Choice (ACω): Countable Choice is assumed for the upstream Fourier and compact singular-system coordinates.

[F1]

The trigonometric system is complete in L2 of the torus: The complex characters form a complete orthonormal basis of L2 on the circle; their real and imaginary parts give the real cosine–sine coefficient basis.

[F2]

Ordered spectral filters, source indices, and variance grids: A candidate grid has geometric variance growth when its consecutive variance ratios lie in a fixed interval [θ1,θ2] with 1<θ1≤θ2<∞.

[F3]

Gaussian sequence inverse model: The positive-noise sequence experiment has observations Yj=θj+σsj−1ξj in singular coordinates.

[F4]

SOLIT parameter choice on a geometric-variance grid: SOLIT accepts a candidate only after its estimator differences from all finer candidates pass the two-index variance and Gaussian-quantile threshold.

[F5]

Risk decomposition and monotone bias for ordered spectral filters: For each candidate, the regularized estimator is a measurable square-integrable Hilbert-valued random element.

[F6]

Ordered spectral filters, source indices, and variance grids: An ordered filter is nonnegative, satisfies 0≤αqα(t)≤Cq′ and 0≤tqα(t)≤1, and increases pointwise as α decreases.

[F7]

The real square-summable sequence space is complete: Real ℓ2(N) with its canonical inner product is complete. The shift z↦(zk+1)k≥0 is an isometric bijection from ℓ2(N>0) to that space.

Verification

1.1givenA1F1F7algebra

Interleaving (an,bn)n≥1 as (a1,b1,a2,b2,…) is a linear isometry onto real ℓ2(N>0), so [F7] gives the stated real Hilbert structure. In angular coordinates with normalized Haar measure dx/(2π), write the characters as en(x)=einx and use Cn=(en+e−n)/2=2cos⁡(nx) and Sn=(en−e−n)/(i2)=2sin⁡(nx) for n≥1. Their orthonormality follows from character orthonormality in [F1]. They are complete in mean-zero real L2: a real mean-zero function orthogonal to all Cn,Sn is orthogonal to every character, hence is zero by [F1]. Thus their coefficient map identifies this function space isometrically with X. The bounded truth belongs to L2, and its integral over [−π,π] is π2−π2=0, so its constant Fourier coefficient vanishes and its normalized real Fourier coefficient sequence lies in X.

1.2givenalgebra

For every n≥1, tn>0 and tn→0 exponentially since R>1. The ratio of consecutive squared multipliers is ((n+1)/n)2((n+2)/(n+1))2R−2, which tends to R−2<1; choose ρ strictly between R−2 and 1, then the ratio is at most ρ for all sufficiently large n. Thus ∑n≥12tn2<∞. The operator is injective because all its diagonal multipliers are positive. Its truncation to frequencies n≤N is finite rank and the operator-norm error is sup⁡n>Ntn→0, so TR is compact and Hilbert–Schmidt.

1.3givenF1algebra

The frequency multipliers satisfy tn+1/tn=(n+2)/(nR), which can exceed 1 for small n; thus the frequency order is not always the singular-value order. The multiset of modes has a nonincreasing enumeration: at every stage a remaining maximum exists because tn→0 and only finitely many modes lie above any fixed positive threshold, and the fixed tie rule selects one uniquely. Every mode is eventually listed because only finitely many modes have multiplier at least its positive multiplier. The operator is diagonal on the orthonormal cosine–sine basis, so the frequency eigenvalue is μn=tn2=n2(n+1)2R−2n−4 twice at each frequency, and the enumerated singular system has these values in nonincreasing order. Since (n+1)2≍n2, μn≍n4e−2nlog⁡R, an exponential spectrum with exponent ϑ=1.

1.4givenF2F6step 1.2algebra

For every λ≥0, qα(λ)=(λ+α)−1 is nonnegative, αqα(λ)≤1, and λqα(λ)≤1. If α~<α, then λ+α~<λ+α, so qα(λ)≤qα~(λ). Thus it is an ordered filter with Cq′=1 by [F6]. Its trace variance is

V(α):=2∑n≥1μn(μn+α)2,α>0.

On every compact interval [a,b]⊂(0,∞), each summand is continuous and is bounded above by 2μn/a2. Since ∑n2μn<∞ by step 1.2, the series converges uniformly there, so V is continuous. Each summand strictly decreases as α increases, hence so does V. Also V(α)≤2α−2∑nμn→0 as α→∞. For every fixed n, V(α)≥2μn/(μn+α)2→2/μn as α↓0; because μn→0, these lower bounds imply V(α)→∞. Fix any c>0 and θ>1. Continuity, strict decrease, and these endpoint limits give a unique αm>0 with V(αm)=cθm for every m∈N0. Thus αm decreases to zero and the variances vm=σ2V(αm) have the constant consecutive ratio θ. The resulting infinite grid meets [F2], and the SOLIT rule truncates it at its finite mmax⁡.

2.1givenF1F2F3F4F5F6step 1.2step 1.4∎

The truth lies in L2 because it is bounded, and its Fourier coefficients are coordinates in the model by [F1]. The positive diagonal multipliers give the injective compact Hilbert–Schmidt operator verified in step 1.2; the Tikhonov filter satisfies [F6] and its candidates satisfy [F2], and the positive-noise experiment and finite selector are [F3]–[F4]. The well-definedness and moment properties of its estimators follow from [F5]. This example asserts no rate for the resulting estimator.

Finite checks

At frequencies n=1,2, t1=2R−3, t2=6R−4, μ1=4R−6, and μ2=36R−8. The first two Tikhonov variance terms are 2μ1(μ1+α)−2 and 2μ2(μ2+α)−2; both are finite, positive, and continuous for α>0.

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