PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
January 23, 20260 citationsOpen Access

The Boundary-Induced Collapse Ontological Theorem (BIC Theorem)

View Full Paper
CBClaudio Bresciano

Key Points

  • The aim is to formalize the Boundary-Induced Collapse Ontological Theorem and its implications for quantum state reduction.
  • Developed a structural derivation of the BIC Theorem.
  • Defined a self-adjoint operator that models the interaction with boundaries.
  • Established a relationship between boundary configurations and quantum state outcomes.
  • Collapse is demonstrated as an objective phenomenon rather than a probabilistic process.
  • The boundary configuration forbids alternative outcomes through spectral selection.
  • Decoherence is confirmed as the mechanism that links quantum measurement to boundary interactions.

Abstract

We formalize the Boundary-Induced Collapse (BIC) Ontological Theorem, providing a structural derivation of quantum state reduction that replaces stochastic postulates with physical necessity. We demonstrate that the interaction between a quantum system and its physical boundary—environment, apparatus, or constraints—induces a self-adjoint operator hatB whose spectral decomposition defines a set of structurally stable modes, or Ontological Deltas (|deltaᵢ). The theorem proves that collapse is not a probabilistic miracle but an objective transition determined by the microscopic configuration of the boundary, which "forbids" alternatives through spectral selection. By establishing that decoherence is the mechanism and BIC is the ontology, we unify quantum measurement with the stability of linear systems. This theorem restores quantum mechanics to the domain of structural physics, asserting that reality does not "choose" outcomes; rather, boundaries enforce them through spectral necessity. Diagram https: //drive. google. com/file/d/1TxZtBJpwCAzkOGBU3sEpLwhV7DoC3tFA/view? usp=driveₗink

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Claudio Bresciano (2026) studied this question.

synapsesocial.com/papers/69730fc4c8125b09b0d1f8ddhttps://doi.org/10.5281/zenodo.18320582
Ask AI
Helpful
Bookmark
Share
View Full Paper