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Shadow Theory

Section 4 9 October 2026

The original law, fine archive and retained information

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4 The original law, fine archive and retained information

Let NN contain every held nuisance coordinate and genuinely retained external context. Its reference measure may be disintegrated against the actual law of external context; write the complete probability reference during these modules as λ=du dv κ(dN)\lambda=du\,dv\,\kappa(dN). Both ThT_h and the ideal baker act on (u,v)(u,v) and fix NN. They preserve λ\lambda. An original density f(u,v,N)f(u,v,N) may correlate all these variables. A cap f≤Cf\leq C means one cap on this complete law, not a newly assigned conditional cap after a selected digit or a fresh reference draw at the next cycle.

Lemma 4.1 (Repeated baker and exact archive ordering)

For M=2nM=2^n, outside the dyadic boundary set,

Bn(u,v)=(r,b)=({Mu},v+rev⁡n(⌊Mu⌋)M), B^n(u,v)= \left(r,b\right)= \left(\{Mu\}, \frac{v+\operatorname{rev}_n(\lfloor Mu\rfloor)}{M}\right), (4.1)

where rev⁡n\operatorname{rev}_n reverses all nn binary digits, including leading zeros. If sj=⌊2uj−1⌋s_j=\lfloor2u_{j-1}\rfloor is the actual entrance declaration for an exact baker step, then

bn=v0+∑j=1n2j−1sj2n. b_n=\frac{v_0+\sum_{j=1}^n2^{j-1}s_j}{2^n}.

The final fine archive retains all these declarations and the original analog v0v_0. Together (r,b)(r,b) determine the original pair.

Proof

The recursions are uj=2uj−1−sju_j=2u_{j-1}-s_j and vj=(vj−1+sj)/2v_j=(v_{j-1}+s_j)/2. Induction gives un={2nu0}u_n=\{2^nu_0\} and the displayed expression for vnv_n. The integer ⌊2nu0⌋\lfloor2^nu_0\rfloor has binary expansion ∑j2n−jsj\sum_j2^{n-j}s_j, while the integer in the archive has expansion ∑j2j−1sj\sum_j2^{j-1}s_j. This proves the reversal. To invert, put k=⌊Mb⌋k=\lfloor Mb\rfloor:

v0=Mb−k,u0=r+rev⁡n(k)M. v_0=Mb-k,\qquad u_0=\frac{r+\operatorname{rev}_n(k)}{M}.

For example, u0=3/10,v0=2/5,n=2u_0=3/10,v_0=2/5,n=2 gives (r,b)=(1/5,3/5)(r,b)=(1/5,3/5). Omitting reversal would give b=7/20b=7/20, an incorrect archive. Each inverse branch has determinant one; the ideal map is a measure-preserving bijection modulo its null seams.

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Lemma 4.2 (Fine-archive conditional freshness)

Let μ=fλ\mu=f\lambda be a nonnegative finite measure, with writer-direction variation

Vu=∫Var⁡u∈(0,1)f(u,v,N) dv κ(dN)<∞. V_u=\int\operatorname{Var}_{u\in(0,1)} f(u,v,N)\,dv\,\kappa(dN)<\infty.

Let νn\nu_n be the actual (b,N)(b,N) marginal of B#nμB^n_\#\mu. Then

TV⁡(B#nμ, dr νn)≤Vu4 2n. \operatorname{TV}(B^n_\#\mu,\,dr\,\nu_n) \leq \frac{V_u}{4\,2^n}. (4.2)

Here TV is half the variation norm for equal-mass measures, and the full fine archive is retained. For probability laws this is an averaged conditional readiness bound with respect to the actual (b,N)(b,N) marginal, not a uniform bound after arbitrarily rare archive postselection.

Proof

On an interval I=[a,b]I=[a,b] of length ℓ\ell, its average fIf_I obeys

∫I∣f−fI∣≤1ℓ∫I ⁣∫I∣f(s)−f(t)∣ ds dt≤1ℓ∫I2(y−a)(b−y) d∣Df∣(y)≤ℓ2Var⁡If.\begin{aligned}\int_I|f-f_I| &\leq\frac1\ell\int_I\!\int_I|f(s)-f(t)|\,ds\,dt\\ &\leq\frac1\ell\int_I 2(y-a)(b-y)\,d|Df|(y) \leq\frac\ell2\operatorname{Var}_I f . \end{aligned}

This proof includes BV jumps, by the one-dimensional variation measure. Apply it to the MM writer cells at fixed (v,N)(v,N) and let PMfP_Mf be their cell averages. Then ∥f−PMf∥1≤Vu/(2M)\|f-P_Mf\|_1\leq V_u/(2M).

On the final archive strip k=⌊Mb⌋k=\lfloor Mb\rfloor, the output density is f((r+rev⁡nk)/M,Mb−k,N)f((r+\operatorname{rev}_n k)/M,Mb-k,N). Integrating in rr is exactly averaging ff over the corresponding original writer cell. Consequently B#n((PMf)λ)=dr νnB^n_\#((P_Mf)\lambda)=dr\,\nu_n. Measure preservation and the half-variation convention give (4.2). Bit reversal only permutes the writer cells and does not remove or average the final archive.

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Theorem 4.3 (Exact-outside-collar original-law transfer)

Suppose the original complete probability density obeys 0≤f≤C0\leq f\leq C. After nn compact baker modules,

TV⁡(Thn#μ,B#nμ)≤nCβh,TV⁡(Thn#μ, dr ν~n)≤Vu4 2n+2nCβh,\begin{align}\operatorname{TV}(T_h^n{}_\#\mu,B^n_\#\mu) &\leq nC\beta_h,\tag{4.3}\\ \operatorname{TV}(T_h^n{}_\#\mu,\, dr\,\widetilde\nu_n) &\leq \frac{V_u}{4\,2^n}+2nC\beta_h, \tag{4.4}\end{align}

where ν~n\widetilde\nu_n is its own actual final archive/nuisance marginal. The probability that any step fails exact baker agreement is at most nCβhnC\beta_h. On its complement the final fine archive stores the actual entrance declarations in Lemma 4.1.

If finite writer BV is proved only for one original box submeasure μB\mu_B with outside mass τ\tau, the freshness estimate instead is

TV⁡(Thn#μ, dr ν~n)≤τ+Vu(μB)4 2n+2nCβh. \operatorname{TV}(T_h^n{}_\#\mu,\, dr\,\widetilde\nu_n) \leq\tau+\frac{V_u(\mu_B)}{4\,2^n} +2nC\beta_h . (4.5)

The original outside mass is charged once.

Proof

Every prefix preserves the complete reference; its pushforward density remains at most CC. Couple the physical and ideal iterations by the same original point. Until their first entry outside Lh∪RhL_h\cup R_h the states and the next complete maps agree exactly. A union bound using the ideal reference-preserving prefixes charges at most nCβhnC\beta_h for the first failure. Their endpoint coupling proves (4.3). The same good event identifies each actual pre-stage declaration with the ideal one and proves the digit assertion.

Insert the ideal law and its actual nuisance marginal between the two laws in (4.4). Lemma 4.2 gives the middle fee. The endpoint fee is nCβhnC\beta_h, and marginalizing that comparison and tensoring with drdr costs another at most nCβhnC\beta_h. This is why the own-marginal freshness bound contains a factor two.

For (4.5), apply the same argument to μB\mu_B and its own nuisance submarginal. The outside-box output and drdr times its actual nuisance marginal have equal mass τ\tau, so their TV is at most τ\tau. Adding these two subprobability comparisons proves the result without recutting the law at a later time.

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After the last module the stationary-stock hold fixes the archive point. This is a single fine analog archive, not yet nn separately held macroscopic records or a physical high-resolution decoder. The separate reader, receiver and reset construction below addresses that additional task. During reuse the archive is deliberately overwritten; its invertible final encoding retains the past digits even though its sign need not retain an earlier sign.

4.1 Where the information goes

Proposition 4.4 (Complete relative entropy is retained)

Let FF be any finite composition of the exact compact modules, or any ideal baker iterate, acting on the full retained reference space. For an original μ=fλ\mu=f\lambda,

TV⁡(F#μ,λ)=TV⁡(μ,λ),DKL(F#μ∥λ)=DKL(μ∥λ), \operatorname{TV}(F_\#\mu,\lambda) =\operatorname{TV}(\mu,\lambda),\qquad D_{\rm KL}(F_\#\mu\|\lambda) =D_{\rm KL}(\mu\|\lambda), (4.6)

with the second equality also in the extended sense. These invariants are compatible with (4.4), which compares the writer with its ready reference conditional on the actual final archive.

Proof

The maps are invertible and reference preserving (modulo null seams for the ideal baker). Their pushforward density is f∘F−1f\circ F^{-1}. Changing variables proves equality of the integrals of ∣f−1∣/2|f-1|/2 and flog⁡ff\log f; the negative part of flog⁡ff\log f is bounded on a probability reference, so the extended integral is well defined. The conditional-freshness target is drdr times the actual nuisance marginal, not the original full reference λ\lambda. There is therefore no contradiction.

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When a density is written as f(r,b,N)f(r,b,N), with g(b,N)=∫f(r,b,N) drg(b,N)=\int f(r,b,N)\,dr, the usual exact decomposition is

DKL(f∥1)=DKL(g∥1)+∫flog⁡ ⁣(fg) dr db dκ. D_{\rm KL}(f\|1) =D_{\rm KL}(g\|1) +\int f\log\!\left(\frac{f}{g}\right)\,dr\,db\,d\kappa .

It follows by adding and subtracting log⁡g\log g; zero-marginal fibres have zero ff mass. The identity also holds with value +∞+\infty: the negative parts of glog⁡gg\log g and flog⁡(f/g)f\log(f/g) have integrals at most 1/e1/e each, so conditional integration justifies the sum without subtracting infinite quantities. If conditional freshness were exact, the second term would vanish and the retained nuisance would carry the entire relative-entropy discrepancy. A small TV estimate alone is not asserted to make that conditional KL term small. The exact digit inverse already shows directly that no complete positional information was erased by the map.

4.2 A cap-free fixed-dimensional preparation variant

The same geometric map admits a different, explicitly priced law class. This result concerns preparation of a writer with one reused archive and one untouched future receiver. It is not a cap-free theorem for the later repeated-record bank, whose complete coordinate/law conditions must be checked separately.

Lemma 4.5 (Three-dimensional concentration from BV)

For a nonnegative BV subdensity gg on the unit cube, with mass mm and directional variations V1,V2,V3V_1,V_2,V_3,

∥g∥3/2≤∏i=13(m+Vi)1/3≤m+V1+V2+V33. \|g\|_{3/2}\leq \prod_{i=1}^3(m+V_i)^{1/3} \leq m+\frac{V_1+V_2+V_3}{3}. (4.7)

Consequently a reference event of volume β\beta has actual mass at most the right side times β1/3\beta^{1/3}.

Proof

One-dimensional BV slicing gives g(u)≤Ai(u−i)g(u)\leq A_i(u_{-i}) almost everywhere, where AiA_i is the integral plus variation of its iith slice. Thus g3/2≤(A1A2A3)1/2g^{3/2}\leq(A_1A_2A_3)^{1/2}. Integrate first in u1u_1 and apply Cauchy to A21/2A31/2A_2^{1/2}A_3^{1/2}. Then apply Cauchy in (u2,u3)(u_2,u_3) to the remaining A11/2A_1^{1/2} and the separated product. This gives ∫g3/2≤∏i(∫Ai)1/2=∏i(m+Vi)1/2\int g^{3/2}\leq\prod_i(\int A_i)^{1/2} =\prod_i(m+V_i)^{1/2}. Taking the 2/32/3 power and arithmetic-geometric mean proves (4.7). Hölder with conjugate exponent three proves the event estimate.

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Corollary 4.6 (Cap-free exact-event preparation)

Suppose the original boxed density, conditional on genuine external information XX with its actual law, has an averaged L3/2L^{3/2} bound at most BB, writer variation VuV_u, and outside mass τ\tau. Then

TV⁡(Thn#μ, dr ν~n)≤τ+Vu4 2n+2nBβh1/3. \operatorname{TV}(T_h^n{}_\#\mu,\, dr\,\widetilde\nu_n) \leq\tau+\frac{V_u}{4\,2^n} +2nB\beta_h^{1/3}. (4.8)

In particular the finite sufficient values

τ≤10−5,Vu≤2.6331 1023,B≤1+2.6331 1023,n=100,h=10−108 \tau\leq10^{-5},\quad V_u\leq2.6331\,10^{23}, \quad B\leq1+2.6331\,10^{23},\quad n=100,\quad h=10^{-108}

give a complete retained-archive freshness bound below 1.1 10−51.1\,10^{-5}.

Proof

Every complete ideal prefix preserves the L3/2L^{3/2} norm. Its next exceptional set has the same volume βh\beta_h, so Hölder bounds its boxed mass by the conditional concentration coefficient times βh1/3\beta_h^{1/3}. Average using the actual XX law and sum over nn first-failure events. The boxed map fee is at most nBβh1/3nB\beta_h^{1/3}. The proof of Theorem 4.3, including its own-marginal factor two and one original tail, then gives (4.8). For the displayed row, βh1/3<2 10−36\beta_h^{1/3}<2\,10^{-36} and the map fee is below 5.2663 10−115.2663\,10^{-11}; the dyadic term and tail give the stated loose ceiling.

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The concentration and writer-BV numbers in this corollary are actual-law hypotheses, not supplied by the stationary wave. A physical-score-to-BV conversion with an actual joint cutoff can supply them, but every coordinate and conditioning variable of that conversion must be retained. If further drifting positions are added, the full-dimensional concentration exponent changes unless a stronger sectional estimate is proved. The illustrative row has degree p=4 10108p=4\,10^{108}. Its finite mathematical existence and the first-flow-jet bound do not make its higher control jets or physical spatial scales feasible.