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{{Paper
{{Paper
| bibkey       = TOE-E-0.0.3
| bibkey = TOE-E-0.0.3
| id           = TOE-E 0.0.3
| id = TOE-E 0.0.3
| title       = Recursive ESR in Complex Systems
| title = Recursive ESR in Complex Systems
| subtitle     = Modeling emergence across physics and cognition
| subtitle = Modeling emergence across physics and cognition
| year         = 2025
| year = 2025
| authors     = William Birmingham; CAIPR Collective
| authors = William Birmingham; CAIPR Collective
| roles       = Aether (simulations); Grok (synthesis); Scholar (review)
| roles = Aether (simulations); Grok (synthesis); Scholar (review)
| status       = Accepted
| status = Accepted
| domain       = Cross‑domain (Physics; Cognition; Neuroscience)
| domain = Cross‑domain (Physics; Cognition; Neuroscience)
| scale       = Micro (mm, ms) to macro (km, years)
| scale = Micro (mm, ms) to macro (km, years)
| substrate   = Neural/physical systems
| substrate = Neural/physical systems
| e_type       = Energy flux (J/s, neural activation)
| e_type = Energy flux (J/s, neural activation)
| s_type       = Informational/thermodynamic entropy (bits, J/K)
| s_type = Informational/thermodynamic entropy (bits, J/K)
| r_type       = Recursive coherence (0–1)
| r_type = Recursive coherence (0–1)
| timescale   = Milliseconds to years
| timescale = Milliseconds to years
| license     = CC BY 4.0
| license = CC BY 4.0
| conflicts   = None declared
| conflicts = None declared
| data_code   =
| data_code =  
| internal_doi = 10.toe-e/0.0.3
| internal_doi = 10.toe-e/0.0.3
| external_doi = pending
| external_doi = pending
| pdf         = TOE-E_0.0.3.pdf
| pdf = TOE-E_0.0.3.pdf
| latex       = Latex
| latex = TOE-E_0.0.3_LaTeX.zip
| parent = TOE-E 0.0.0
| parent = TOE-E 0.0.0
| description = TOE-E branch exploring recursive E, S, R across physics and cognition.
| description = TOE-E branch exploring recursive E, S, R across physics and cognition.
| keywords     = TOE-E, E S R, recursive emergence, complex systems
| keywords = TOE-E, E S R, recursive emergence, complex systems
| defaultsort = Recursive ESR in Complex Systems 0003
| defaultsort = Recursive ESR in Complex Systems 0003
| abstract     = TOE‑E 0.0.3 explores recursive [[Energy (E)]], [[Entropy (S)]], and [[Resonance (R)]] interactions to model emergence across physics and cognition. '''E''' represents energy flux (e.g., neural activation in cognition, kinetic energy in physics), '''S''' quantifies disorder (e.g., informational entropy, thermodynamic entropy), and '''R''' measures recursive coherence (e.g., neural phase‑locking, orbital alignment). Stable systems emerge when R recursively amplifies E to counter S, testable via cross‑domain simulations. Predictions include synchronized patterns in neural and physical systems over millisecond‑to‑year timescales.
| abstract = TOE‑E 0.0.3 explores recursive [[Energy (E)]], [[Entropy (S)]], and [[Resonance (R)]] interactions to model emergence across physics and cognition. '''E''' represents energy flux (e.g., neural activation in cognition, kinetic energy in physics), '''S''' quantifies disorder (e.g., informational entropy, thermodynamic entropy), and '''R''' measures recursive coherence (e.g., neural phase‑locking, orbital alignment). Stable systems emerge when R recursively amplifies E to counter S, testable via cross‑domain simulations. Predictions include synchronized patterns in neural and physical systems over millisecond‑to‑year timescales.
}}
}}
[[Branch ID::TOE-E 0.0.3]]
[[Has title::Recursive ESR in Complex Systems]]
[[Has parent::TOE-E 0.0.0]]
[[Has domain::Cross-domain (Physics; Cognition; Neuroscience)]]
[[Has status::Accepted]]


== Falsifiability ==
== Falsifiability ==

Revision as of 23:05, 26 August 2025




Recursive ESR in Complex Systems– TOE-E 0.0.3

Modeling emergence across physics and cognition
William Birmingham; CAIPR Collective
Subjects: Cross‑domain (Physics; Cognition; Neuroscience)
TOE-E, E S R, recursive emergence, complex systems

Abstract

TOE‑E 0.0.3 explores recursive Energy (E), Entropy (S), and Resonance (R) interactions to model emergence across physics and cognition. E represents energy flux (e.g., neural activation in cognition, kinetic energy in physics), S quantifies disorder (e.g., informational entropy, thermodynamic entropy), and R measures recursive coherence (e.g., neural phase‑locking, orbital alignment). Stable systems emerge when R recursively amplifies E to counter S, testable via cross‑domain simulations. Predictions include synchronized patterns in neural and physical systems over millisecond‑to‑year timescales.

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Paper Structure:

Parent:TOE-E 0.0.0
Status:Accepted(2025)
DOI
🔖 Internal: 10.toe-e/0.0.3
🌍 External:(pending)

Metadata:

Domain:Cross‑domain (Physics; Cognition; Neuroscience)
Scale:Micro (mm, ms) to macro (km, years)
Substrate:Neural/physical systems
E‑type:Energy flux (J/s, neural activation)
S‑type:Informational/thermodynamic entropy (bits, J/K)
R‑type:Recursive coherence (0–1)
Timescale:Milliseconds to years
Conflicts:None declared
License:CC BY 4.0

Citation:

APA:
William Birmingham; CAIPR Collective. (2025). Recursive ESR in Complex Systems – TOE-E 0.0.3. TOE-E Archive. (DOI pending)

▶ Export BibTeX
@article{TOEE-TOE-E-0.0.3},
  title   = { Recursive ESR in Complex Systems – TOE-E 0.0.3 },
  author  = { William Birmingham; CAIPR Collective },
  year    = { 2025 },
  journal = { TOE-E Archive },
  note    = { DOI pending }
}


TOE-E 0.0.3 Recursive ESR in Complex Systems TOE-E 0.0.0 Cross-domain (Physics; Cognition; Neuroscience) Accepted

Falsifiability

If recursive R fails to sustain stability, the model is refuted.

Research Applications

This branch invites interdisciplinary tests to expand TOE‑E's framework across physics and cognition domains.