C3.8U · FORMULA WORKBENCH

PN.2 formula workbench

Lower bounds for selected separations. Each formula links to its assumptions and a verified proof page.

Main R/D boundℛ_Rℛ_D≈ 0.375

Parameters

Unit labels

Convert inputs to consistent units first. Labels do not perform unit conversion. [c] = [S]/[R].

Calculation updated. Results are conditional mathematical bounds.

Lower bounds

BoundValue ≈Unit
ℛ_S11
ℛ_R0.51
ℛ_D0.751
ℛ_Sℛ_D0.751
ℛ_Rℛ_D0.3751
ℛ_Sℛ_D (c)0.3751

The numerical condition Δ_S ≥ c‖K‖ holds. This does not prove separation throughout Ω.

Factor (1 − τ)²
Factor (1 − τ)²1000.51τ

Export includes inputs, exact fractions, units, formula references and evidence statuses.

Entering numbers does not validate a physical model. e_X is the maximum error of a fixed estimate; ℛ_X is the maximum expected metric loss. At τ = 0 the coefficients agree, but the definitions remain different.

Formulas and assumptions

K-DEF · Definitions

Associator

K(x,y,z)=(xy)zx(yz)=rLrR K(x,y,z)=(x\odot y)\odot z-x\odot(y\odot z)=r_L-r_R

Objects and domain are specified in a normed algebra; this is a definition, not an experimental result.

SOURCE_ANCHORED · Section 2; 3.1 · PDF page 2

TeX

GAPS · Definitions

Branch separations

ΔS=|S(rL)S(rR)|,ΔD=|𝔇(bL)𝔇(bR)|,ΔR=K \Delta_S=|S(r_L)-S(r_R)|,\quad\Delta_D=|\mathfrak D(b_L)-\mathfrak D(b_R)|,\quad\Delta_R=\|K\|

Objects and domain are specified in a normed algebra; this is a definition, not an experimental result.

SOURCE_ANCHORED · Section 3.4 · PDF page 3

TeX

DET-ERROR · Definitions

Deterministic error

eX=maxb{L,R}dX(x̂,xb) e_X=\max_{b\in\{L,R\}}d_X(\widehat x,x_b)

Theorem package: A1–A4, one estimator for hidden branches. A positive bound requires nonzero separations.

SOURCE_ANCHORED · Section 3.3 · PDF page 3

TeX

C-SEP · Definitions

c-separation condition

ΔS(u)cK(u),c>0,uΩ \Delta_S(u)\ge c\|K(u)\|,\qquad c>0,\quad u\in\Omega

Additionally c > 0 and Δ_S(u) ≥ c‖K(u)‖. A numerical row does not prove separation over all of Ω.

SOURCE_ANCHORED · Section 3.5 · PDF page 3

TeX

PN2-S · Deterministic

PN.2-S · scalar form

eSeDΔSΔD4 e_Se_D\ge\frac{\Delta_S\Delta_D}{4}

Theorem package: A1–A4, one estimator for hidden branches. A positive bound requires nonzero separations.

SOURCE_ANCHORED · Section 7; 8 · PDF page 4

TeX

PN2-R · Deterministic

PN.2-R · full state

eReDKΔD4 e_Re_D\ge\frac{\|K\|\Delta_D}{4}

Theorem package: A1–A4, one estimator for hidden branches. A positive bound requires nonzero separations.

SOURCE_ANCHORED · Section 7; 8 · PDF page 4

TeX

PN2-K · Deterministic

PN.2-K · c-separation

eSeDcKΔD4 e_Se_D\ge\frac{c\|K\|\Delta_D}{4}

Additionally c > 0 and Δ_S(u) ≥ c‖K(u)‖. A numerical row does not prove separation over all of Ω.

SOURCE_ANCHORED · Section 7; 8 · PDF page 5

TeX

TV · Statistical

Data distinguishability

τ=TV(PL,PR)=12|pq|dμ,μ=PL+PR \tau=\operatorname{TV}(P_L,P_R)=\frac12\int|p-q|\,d\mu,\quad\mu=P_L+P_R

Two probability laws on one measurable space; τ uses the entire accessible observation.

SOURCE_ANCHORED · Section 3 · PDF page 2

TeX

OVERLAP · Statistical

Overlap of laws

ν(𝒴)=min(p,q)dμ=1τ \nu(\mathcal Y)=\int\min(p,q)\,d\mu=1-\tau

Two probability laws on one measurable space; τ uses the entire accessible observation.

SOURCE_ANCHORED · Section 3 · PDF page 3

TeX

STAT-RISK · Statistical

Worst expected risk

X=maxb{L,R}𝔼bdX(X̂,xb) \mathcal R_X=\max_{b\in\{L,R\}}\mathbb E_b\,d_X(\widehat X,x_b)

C3.8T audit: A1–A6, common complete-data laws and one decision kernel; finite risks.

SOURCE_ANCHORED · Section 2 · PDF page 2

TeX

STAT-S · Statistical

Risk S

SΔS2(1τ) \mathcal R_S\ge\frac{\Delta_S}{2}(1-\tau)

C3.8T audit: A1–A6, common complete-data laws and one decision kernel; finite risks.

SOURCE_ANCHORED · Section 4; 5 · PDF page 3

TeX

STAT-D · Statistical

Risk D

DΔD2(1τ) \mathcal R_D\ge\frac{\Delta_D}{2}(1-\tau)

C3.8T audit: A1–A6, common complete-data laws and one decision kernel; finite risks.

SOURCE_ANCHORED · Section 4; 5 · PDF page 3

TeX

STAT-R · Statistical

Risk R

RK2(1τ) \mathcal R_R\ge\frac{\|K\|}{2}(1-\tau)

C3.8T audit: A1–A6, common complete-data laws and one decision kernel; finite risks.

SOURCE_ANCHORED · Section 4; 5 · PDF page 3

TeX

STAT-SD · Statistical

Product of S/D risks

SDΔSΔD4(1τ)2 \mathcal R_S\mathcal R_D\ge\frac{\Delta_S\Delta_D}{4}(1-\tau)^2

C3.8T audit: A1–A6, common complete-data laws and one decision kernel; finite risks.

SOURCE_ANCHORED · Section 5 · PDF page 4

TeX

STAT-RD · Statistical

Product of R/D risks

RDKΔD4(1τ)2 \mathcal R_R\mathcal R_D\ge\frac{\|K\|\Delta_D}{4}(1-\tau)^2

C3.8T audit: A1–A6, common complete-data laws and one decision kernel; finite risks.

SOURCE_ANCHORED · Section 5 · PDF page 4

TeX

STAT-cSD · Statistical

Risks with c-separation

SDcKΔD4(1τ)2 \mathcal R_S\mathcal R_D\ge\frac{c\|K\|\Delta_D}{4}(1-\tau)^2

Additionally c > 0 and Δ_S(u) ≥ c‖K(u)‖. A numerical row does not prove separation over all of Ω.

SOURCE_ANCHORED · Section 5 · PDF page 4

TeX

Assumptions and scope

Deterministic model: normed algebra, two defined bracket outcomes, hidden branch index, one estimate and Δ_D > 0. The c-form additionally requires proven c-separation.

Statistical model: the entire accessible observation Y, laws P_L/P_R, measurable metric loss, one branch-independent decision kernel and finite risks; K = r_L − r_R. The c-form requires separation.

The canonical statistical patch has not been applied. Physical validation has not been performed. truth_layer_promotion=0 · EXT_RUN=NOT_RUN · NO_LOSS_FREEZE=BLOCKED.

Where is it proved?

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Records: 51 / 51

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Non-associative packet algebra R⋆RRSTAR-RSOURCE_ANCHORED
Document
PN.2 theorem v1.0 — source excerpt
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v1.0; original title date 11 July 2026; excerpt prepared 6 September 2026
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2; 3
Page
2
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K = r_L-r_R
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OPEN_PROOF_OBLIGATIONS
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5f686dd1f563d7cdb73f67f74ce674064a5f184c0a596df6af8a924f41a6dfc6

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PN.2PN2SOURCE_ANCHORED
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PN.2 theorem v1.0 — source excerpt
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7; 8
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4
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PN.2-S / PN.2-R / PN.2-K
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MATH_PLUS_OPEN_PHYSICS
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5f686dd1f563d7cdb73f67f74ce674064a5f184c0a596df6af8a924f41a6dfc6

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2
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1
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EXPLICIT_ASSUMPTIONS
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PN2-STAT-OVERLAPPN2-STAT-OVERLAPSOURCE_ANCHORED
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Statistical PN.2 audit C3.8T v1.0 RU
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3
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3
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(4)
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PROVED_UNDER_A1_A6
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9b1bcebaaa874bda300e09d98df318c414a8449204768f227810df1e9762ab9a

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PN2-STAT-T1PN2-STAT-T1SOURCE_ANCHORED
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Statistical PN.2 audit C3.8T v1.0 RU
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4
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3
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(T1)
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PROVED_UNDER_A1_A6
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PN2-STAT-T2-SPN2-STAT-T2-SSOURCE_ANCHORED
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Statistical PN.2 audit C3.8T v1.0 RU
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5
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4
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PROVED_UNDER_A1_A6
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PN2-STAT-T2-RPN2-STAT-T2-RSOURCE_ANCHORED
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5
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4
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PROVED_UNDER_A1_A6
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PN2-STAT-T2-cPN2-STAT-T2-cSOURCE_ANCHORED
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4
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PROVED_UNDER_A1_A6_AND_C_SEPARATION
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PN2-STAT-TAU0PN2-STAT-TAU0SOURCE_ANCHORED
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6
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4
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PROVED_UNDER_A1_A6
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9b1bcebaaa874bda300e09d98df318c414a8449204768f227810df1e9762ab9a

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PN2-STAT-TAU1PN2-STAT-TAU1SOURCE_ANCHORED
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Statistical PN.2 audit C3.8T v1.0 RU
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6
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4
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PROVED_UNDER_A1_A6
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PN2-STAT-SHARPNESS-D1PN2-STAT-SHARPNESS-D1SOURCE_ANCHORED
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4
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PN2-STAT-ASYMMETRIC-D3PN2-STAT-ASYMMETRIC-D3SOURCE_ANCHORED
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7
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5
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MINIMAX_RISK_1_OVER_3
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9b1bcebaaa874bda300e09d98df318c414a8449204768f227810df1e9762ab9a

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PN2-STAT-UNIFORM-C1PN2-STAT-UNIFORM-C1SOURCE_ANCHORED
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8
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5
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PROVED_UNDER_A1_A6
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PN2-STAT-NORMAL-C2PN2-STAT-NORMAL-C2SOURCE_ANCHORED
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PN2-STAT-COUNTEREXAMPLESPN2-STAT-COUNTEREXAMPLESSOURCE_ANCHORED
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6
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CE1_TO_CE7_REFUTE_STRONGER_FORMS
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PN2-STAT-ATTRIBUTIONPN2-STAT-ATTRIBUTIONSOURCE_ANCHORED
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10
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6
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9b1bcebaaa874bda300e09d98df318c414a8449204768f227810df1e9762ab9a

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PN2-STAT-CANON-PROPOSALPN2-STAT-CANON-PROPOSALSOURCE_ANCHORED
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13
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8
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AUTHOR_DECISION_PENDING
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9b1bcebaaa874bda300e09d98df318c414a8449204768f227810df1e9762ab9a

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ARBD-HIERARCHYARBD-HIERARCHYSOURCE_ANCHORED
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inputs/AUTHOR_REPER_DB_SPEC.md
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ARBD Build 28 / KANT R017
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1. Entity hierarchy
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ABSTAIN
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a1ed863cfe2e66248b3d65d6381c0eedb0faf9454a018a8302d7fc9aecd8e880

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ARBD-ACPARBD-ACPSOURCE_ANCHORED
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inputs/FORMAL_MODEL.md
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ARBD Build 28 / KANT R017
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Core_A / ACP
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SHA-256
9149bd0802b74ab67feee2508c6e466cc903771a2d410e098c50900aa6007700

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run/ARBD_MODEL.json
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QA_REPORT.json
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ea582b6e845b6e12a5c1f7bf585de2b9cab28b95fd19d9b427c6b11fe7a7d506

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KLT_ADAPTER_CONTRACT.md
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Граница интеграции
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80f5875353f8e89fe0a4e66f42a737ec4f88b9067b9566f433366cc1d5f53c72

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run/ARBD_MODEL.json
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7d06af7fe13dbfd979d386db230aaf60874f0a5c933e34e7c66e10d7b1432979

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run/ARBD_MODEL.json
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7d06af7fe13dbfd979d386db230aaf60874f0a5c933e34e7c66e10d7b1432979

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run/ARBD_MODEL.json
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7d06af7fe13dbfd979d386db230aaf60874f0a5c933e34e7c66e10d7b1432979

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SHA-256
7d06af7fe13dbfd979d386db230aaf60874f0a5c933e34e7c66e10d7b1432979

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AssociatorFORMULA-K-DEFSOURCE_ANCHORED
Document
PN.2 theorem v1.0 — source excerpt
Edition
PN.2 v1.0 / source excerpt v1.0
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2; 3.1
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2
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K
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PO-1, PO-3
Certificate
Not assigned
Evidence status
DEFINITION
SHA-256
5f686dd1f563d7cdb73f67f74ce674064a5f184c0a596df6af8a924f41a6dfc6

Objects and domain are specified in a normed algebra; this is a definition, not an experimental result.

Branch separationsFORMULA-GAPSSOURCE_ANCHORED
Document
PN.2 theorem v1.0 — source excerpt
Edition
PN.2 v1.0 / source excerpt v1.0
Section
3.4
Page
3
Formula / pointer
Delta_S / Delta_D / Delta_R
PO obligations
PO-4
Certificate
Not assigned
Evidence status
DEFINITION
SHA-256
5f686dd1f563d7cdb73f67f74ce674064a5f184c0a596df6af8a924f41a6dfc6

Objects and domain are specified in a normed algebra; this is a definition, not an experimental result.

Deterministic errorFORMULA-DET-ERRORSOURCE_ANCHORED
Document
PN.2 theorem v1.0 — source excerpt
Edition
PN.2 v1.0 / source excerpt v1.0
Section
3.3
Page
3
Formula / pointer
e_S / e_D / e_R
PO obligations
PO-6
Certificate
Not assigned
Evidence status
NOTATIONAL_UNIFICATION_OF_SOURCE_DEFINITIONS
SHA-256
5f686dd1f563d7cdb73f67f74ce674064a5f184c0a596df6af8a924f41a6dfc6

Theorem package: A1–A4, one estimator for hidden branches. A positive bound requires nonzero separations.

c-separation conditionFORMULA-C-SEPSOURCE_ANCHORED
Document
PN.2 theorem v1.0 — source excerpt
Edition
PN.2 v1.0 / source excerpt v1.0
Section
3.5
Page
3
Formula / pointer
c-separation
PO obligations
PO-5
Certificate
Not assigned
Evidence status
ASSUMPTION
SHA-256
5f686dd1f563d7cdb73f67f74ce674064a5f184c0a596df6af8a924f41a6dfc6

Additionally c > 0 and Δ_S(u) ≥ c‖K(u)‖. A numerical row does not prove separation over all of Ω.

PN.2-S · scalar formFORMULA-PN2-SSOURCE_ANCHORED
Document
PN.2 theorem v1.0 — source excerpt
Edition
PN.2 v1.0 / source excerpt v1.0
Section
7; 8
Page
4
Formula / pointer
PN.2-S
PO obligations
PO-5, PO-6
Certificate
Not assigned
Evidence status
PROVED_IN_STATED_ABSTRACT_MODEL
SHA-256
5f686dd1f563d7cdb73f67f74ce674064a5f184c0a596df6af8a924f41a6dfc6

Theorem package: A1–A4, one estimator for hidden branches. A positive bound requires nonzero separations.

PN.2-R · full stateFORMULA-PN2-RSOURCE_ANCHORED
Document
PN.2 theorem v1.0 — source excerpt
Edition
PN.2 v1.0 / source excerpt v1.0
Section
7; 8
Page
4
Formula / pointer
PN.2-R
PO obligations
PO-3, PO-6
Certificate
Not assigned
Evidence status
PROVED_IN_STATED_ABSTRACT_MODEL
SHA-256
5f686dd1f563d7cdb73f67f74ce674064a5f184c0a596df6af8a924f41a6dfc6

Theorem package: A1–A4, one estimator for hidden branches. A positive bound requires nonzero separations.

PN.2-K · c-separationFORMULA-PN2-KSOURCE_ANCHORED
Document
PN.2 theorem v1.0 — source excerpt
Edition
PN.2 v1.0 / source excerpt v1.0
Section
7; 8
Page
5
Formula / pointer
PN.2-K
PO obligations
PO-5, PO-6
Certificate
Not assigned
Evidence status
PROVED_CONDITIONALLY_IN_MODEL
SHA-256
5f686dd1f563d7cdb73f67f74ce674064a5f184c0a596df6af8a924f41a6dfc6

Additionally c > 0 and Δ_S(u) ≥ c‖K(u)‖. A numerical row does not prove separation over all of Ω.

Data distinguishabilityFORMULA-TVSOURCE_ANCHORED
Document
Statistical PN.2 audit C3.8T v1.0 RU
Edition
C3.8T v1.0 / 2026-09-06
Section
3
Page
2
Formula / pointer
(3)
PO obligations
PO-6
Certificate
Not assigned
Evidence status
DEFINITION
SHA-256
9b1bcebaaa874bda300e09d98df318c414a8449204768f227810df1e9762ab9a

Two probability laws on one measurable space; τ uses the entire accessible observation.

Overlap of lawsFORMULA-OVERLAPSOURCE_ANCHORED
Document
Statistical PN.2 audit C3.8T v1.0 RU
Edition
C3.8T v1.0 / 2026-09-06
Section
3
Page
3
Formula / pointer
(4)
PO obligations
Not assigned
Certificate
Not assigned
Evidence status
PROVED_UNDER_STATED_ASSUMPTIONS
SHA-256
9b1bcebaaa874bda300e09d98df318c414a8449204768f227810df1e9762ab9a

Two probability laws on one measurable space; τ uses the entire accessible observation.

Worst expected riskFORMULA-STAT-RISKSOURCE_ANCHORED
Document
Statistical PN.2 audit C3.8T v1.0 RU
Edition
C3.8T v1.0 / 2026-09-06
Section
2
Page
2
Formula / pointer
(1)
PO obligations
PO-6
Certificate
Not assigned
Evidence status
DEFINITION
SHA-256
9b1bcebaaa874bda300e09d98df318c414a8449204768f227810df1e9762ab9a

C3.8T audit: A1–A6, common complete-data laws and one decision kernel; finite risks.

Risk SFORMULA-STAT-SSOURCE_ANCHORED
Document
Statistical PN.2 audit C3.8T v1.0 RU
Edition
C3.8T v1.0 / 2026-09-06
Section
4; 5
Page
3
Formula / pointer
(8)
PO obligations
Not assigned
Certificate
Not assigned
Evidence status
PROVED_UNDER_A1_A6
SHA-256
9b1bcebaaa874bda300e09d98df318c414a8449204768f227810df1e9762ab9a

C3.8T audit: A1–A6, common complete-data laws and one decision kernel; finite risks.

Risk DFORMULA-STAT-DSOURCE_ANCHORED
Document
Statistical PN.2 audit C3.8T v1.0 RU
Edition
C3.8T v1.0 / 2026-09-06
Section
4; 5
Page
3
Formula / pointer
(8)
PO obligations
Not assigned
Certificate
Not assigned
Evidence status
PROVED_UNDER_A1_A6
SHA-256
9b1bcebaaa874bda300e09d98df318c414a8449204768f227810df1e9762ab9a

C3.8T audit: A1–A6, common complete-data laws and one decision kernel; finite risks.

Risk RFORMULA-STAT-RSOURCE_ANCHORED
Document
Statistical PN.2 audit C3.8T v1.0 RU
Edition
C3.8T v1.0 / 2026-09-06
Section
4; 5
Page
3
Formula / pointer
(8)
PO obligations
Not assigned
Certificate
Not assigned
Evidence status
PROVED_UNDER_A1_A6
SHA-256
9b1bcebaaa874bda300e09d98df318c414a8449204768f227810df1e9762ab9a

C3.8T audit: A1–A6, common complete-data laws and one decision kernel; finite risks.

Product of S/D risksFORMULA-STAT-SDSOURCE_ANCHORED
Document
Statistical PN.2 audit C3.8T v1.0 RU
Edition
C3.8T v1.0 / 2026-09-06
Section
5
Page
4
Formula / pointer
T2-S
PO obligations
Not assigned
Certificate
Not assigned
Evidence status
PROVED_UNDER_A1_A6
SHA-256
9b1bcebaaa874bda300e09d98df318c414a8449204768f227810df1e9762ab9a

C3.8T audit: A1–A6, common complete-data laws and one decision kernel; finite risks.

Product of R/D risksFORMULA-STAT-RDSOURCE_ANCHORED
Document
Statistical PN.2 audit C3.8T v1.0 RU
Edition
C3.8T v1.0 / 2026-09-06
Section
5
Page
4
Formula / pointer
T2-R
PO obligations
Not assigned
Certificate
Not assigned
Evidence status
PROVED_UNDER_A1_A6
SHA-256
9b1bcebaaa874bda300e09d98df318c414a8449204768f227810df1e9762ab9a

C3.8T audit: A1–A6, common complete-data laws and one decision kernel; finite risks.

Risks with c-separationFORMULA-STAT-cSDSOURCE_ANCHORED
Document
Statistical PN.2 audit C3.8T v1.0 RU
Edition
C3.8T v1.0 / 2026-09-06
Section
5
Page
4
Formula / pointer
T2-c
PO obligations
PO-5
Certificate
Not assigned
Evidence status
PROVED_UNDER_A1_A6_AND_C_SEPARATION
SHA-256
9b1bcebaaa874bda300e09d98df318c414a8449204768f227810df1e9762ab9a

Additionally c > 0 and Δ_S(u) ≥ c‖K(u)‖. A numerical row does not prove separation over all of Ω.

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