IndisputableMonolith.Cryptography.BalancedJSubsetSum
This module defines the Balanced J Subset Sum problem and supporting objects for the Recognition Science cryptography domain. It introduces rungValue as exp(k log phi) for phi-rung representation, BJSSInstance, BJSSWitness, weightSum, residueSum, rungCost, totalJCost, and jCostBound. Researchers developing RS-based cryptographic protocols would cite these objects. The module consists solely of definitions with no proofs.
claimrungValue(k) := exp(k log phi); BJSSInstance is a record specifying weights and residues; BJSSWitness is a subset selector; weightSum and residueSum compute the respective totals; rungCost and totalJCost measure J-costs; jCostBound asserts an upper limit on total J-cost.
background
The module imports Constants, whose doc states the fundamental RS time quantum (RS-native) τ₀ = 1 tick, and the Cost module. It introduces phi-rung values represented by exp(k log phi) to avoid integer-power API details. The local theoretical setting is the cryptography domain, supplying subset-sum structures balanced under J-cost from the Cost module.
proof idea
This is a definition module, no proofs.
why it matters in Recognition Science
This module supplies the core definitions for Balanced J Subset Sum that feed into subsequent cryptography results in the Recognition Science framework. It prepares the ground for theorems that apply J-cost bounds and phi-ladder structures to cryptographic constructions.
scope and limits
- Does not prove computational hardness of BJSS instances.
- Does not supply algorithms or solvers for the subset sum problem.
- Does not connect definitions to concrete cryptographic primitives.
- Does not address security reductions or attack models.
depends on (2)
declarations in this module (19)
-
def
rungValue -
theorem
rungValue_pos -
theorem
rungValue_zero -
structure
BJSSInstance -
structure
BJSSWitness -
def
weightSum -
def
residueSum -
def
rungCost -
def
totalJCost -
def
weightTarget -
def
residueNeutral -
def
jCostBound -
def
isSolution -
theorem
rungCost_nonneg -
theorem
totalJCost_nonneg -
def
solutionDecidable -
def
fromSubsetSum -
theorem
fromSubsetSum_totalJCost_zero -
theorem
fromSubsetSum_isSolution