Research publications on Spectral Brand Theory (SBT), a computational framework for modeling brand perception as an observer-mediated, multi-dimensional process.
| Paper | Words | Refs | Zenodo DOI | Status |
|---|---|---|---|---|
| Spectral Brand Theory: A Computational Framework for Multi-Dimensional Brand Perception | ~15,000 | 81 | 10.5281/zenodo.18945912 | Preprint |
| The Atom-Cloud-Fact Epistemological Pipeline | ~4,100 | 19 | 10.5281/zenodo.18944770 | Preprint |
Eight companion papers establishing formal mathematical foundations for SBT, plus two extensions:
| Key | Paper | Zenodo DOI | Status |
|---|---|---|---|
| R8 | 10.5281/zenodo.19145099 | Superseded | |
| R14 | Research as Repository: Infrastructure for Transparent, Attributed, and Machine-Readable Scholarly Communication | 10.5281/zenodo.19294864 | Under review |
| Key | Paper | Zenodo DOI | Status |
|---|---|---|---|
| R13 | Paper as Specification: A Machine-Readable Standard for Scientific Claims | 10.5281/zenodo.19210037 | Under review |
| Key | Paper | Zenodo DOI | Status |
|---|---|---|---|
| 2026l | The Rendering Problem: From Genetic Expression to Brand Perception | 10.5281/zenodo.19064427 | Preprint |
| 2026w | Canon as Repository: A Specification-Driven Architecture for Transmedia Intellectual Property | 10.5281/zenodo.19355800 | Preprint (v1.1.0) |
Key results: formal metric (R1), metamerism inevitability (R2), fuzzy cohort boundaries (R3), positioning capacity bounds (R4), specification impossibility (R5), non-ergodic dynamics (R6), demand-driven resource allocation (R7), dimensional taxonomy justification (R11), coherence-resilience derivation (R12).
R7 formalizes spectral resource allocation — optimal dimensional investment given measured cohort weights, alignment gap between founder and cohort profiles.
Introduces the full SBT framework: eight perceptual dimensions, observer spectral profiles, cloud formation and conviction collapse, and the seven-metric coherence scorecard. Validated across five brands (Hermès, IKEA, Patagonia, Tesla, Erewhon). Reports nine candidate mechanisms: structural absence (dark signals), five-type coherence taxonomy, asymmetric conviction resilience, brand power/health independence, D/A ratio optimum, temporal compounding, mediated cloud formation, evidence-free conviction stability, and cross-weight barrier penetration.
Keywords: brand perception, computational branding, observer heterogeneity, brand coherence, structural absence, AI-native framework
Describes the domain-agnostic epistemological architecture underlying SBT. Originally developed for probabilistic financial fact extraction, the atom-cloud-fact pipeline provides the formal machinery for observation-to-knowledge progression. Documents the architecture, its seven principles, and the domain transfer from financial document processing to brand perception modeling.
Keywords: epistemology, probabilistic knowledge, atom-cloud-fact, domain transfer, computational framework
Proposes the Rendering Problem as a unifying structural pattern across biological and social systems: a specification (DNA, organizational schema, brand signal) is never directly perceived — it is rendered through an implementation layer, and perception is always of the rendering, not the specification. Documents three instantiations (genetic expression, organizational execution, brand perception), formalizes the structural specification gap at each transition, and argues that the gap is irreducible in principle. Connects SBT, OST, and the body-as-metadata thesis under a single formal architecture.
Keywords: rendering problem, specification gap, brand perception, genetic expression, organizational schema, cross-framework synthesis
@article{zharnikov2026sbt,
title={Spectral Brand Theory: A Computational Framework for
Multi-Dimensional Brand Perception},
author={Zharnikov, Dmitry},
year={2026},
url={https://doi.org/10.5281/zenodo.18945912},
doi={10.5281/zenodo.18945912}
}
@article{zharnikov2026acf,
title={The Atom-Cloud-Fact Epistemological Pipeline: From Financial
Document Processing to Brand Perception Modeling},
author={Zharnikov, Dmitry},
year={2026},
url={https://doi.org/10.5281/zenodo.18944770},
doi={10.5281/zenodo.18944770}
}
@article{zharnikov2026r0,
title={Geometric approaches to brand perception: A critical survey
and research agenda},
author={Zharnikov, Dmitry},
year={2026},
url={https://doi.org/10.5281/zenodo.18945217},
doi={10.5281/zenodo.18945217}
}
@article{zharnikov2026r1,
title={Brand space geometry: A formal metric for multi-dimensional
brand perception},
author={Zharnikov, Dmitry},
year={2026},
url={https://doi.org/10.5281/zenodo.18945295},
doi={10.5281/zenodo.18945295}
}
@article{zharnikov2026r2,
title={Spectral metamerism in brand perception: Projection bounds
from high-dimensional geometry},
author={Zharnikov, Dmitry},
year={2026},
url={https://doi.org/10.5281/zenodo.18945352},
doi={10.5281/zenodo.18945352}
}
@article{zharnikov2026r3,
title={Cohort boundaries in high-dimensional perception space:
A concentration of measure analysis},
author={Zharnikov, Dmitry},
year={2026},
url={https://doi.org/10.5281/zenodo.18945477},
doi={10.5281/zenodo.18945477}
}
@article{zharnikov2026r4,
title={How many brands can a market hold? Sphere packing bounds
for multi-dimensional positioning},
author={Zharnikov, Dmitry},
year={2026},
url={https://doi.org/10.5281/zenodo.18945522},
doi={10.5281/zenodo.18945522}
}
@article{zharnikov2026r5,
title={Specification impossibility in organizational design:
A high-dimensional geometric analysis},
author={Zharnikov, Dmitry},
year={2026},
url={https://doi.org/10.5281/zenodo.18945591},
doi={10.5281/zenodo.18945591}
}
@article{zharnikov2026r6,
title={Non-ergodic brand perception: Diffusion dynamics on
multi-dimensional perceptual manifolds},
author={Zharnikov, Dmitry},
year={2026},
url={https://doi.org/10.5281/zenodo.18945659},
doi={10.5281/zenodo.18945659}
}
@article{zharnikov2026r7,
title={Spectral resource allocation: Demand-driven investment in
multi-dimensional brand space},
author={Zharnikov, Dmitry},
year={2026},
url={https://doi.org/10.5281/zenodo.19009268},
doi={10.5281/zenodo.19009268}
}
@article{zharnikov2026rendering,
title={The Rendering Problem: From Genetic Expression to Brand Perception},
author={Zharnikov, Dmitry},
year={2026},
url={https://doi.org/10.5281/zenodo.19064427},
doi={10.5281/zenodo.19064427}
}
@article{zharnikov2026r11,
title={Why Eight? Completeness and Necessity of the SBT Dimensional
Taxonomy},
author={Zharnikov, Dmitry},
year={2026},
url={https://doi.org/10.5281/zenodo.19207599},
doi={10.5281/zenodo.19207599}
}
@article{zharnikov2026r12,
title={Coherence type as crisis predictor: A formal derivation from
non-ergodic dynamics},
author={Zharnikov, Dmitry},
year={2026},
url={https://doi.org/10.5281/zenodo.19208107},
doi={10.5281/zenodo.19208107}
}
@article{zharnikov2026r13,
title={Paper as Specification: A Machine-Readable Standard for
Scientific Claims},
author={Zharnikov, Dmitry},
year={2026},
url={https://doi.org/10.5281/zenodo.19210037},
doi={10.5281/zenodo.19210037}
}Machine-readable citations: SBT CITATION.cff | ACF CITATION.cff | R0 CITATION.cff | R1 CITATION.cff | R2 CITATION.cff | R3 CITATION.cff | R4 CITATION.cff | R5 CITATION.cff | R6 CITATION.cff | R7 CITATION.cff | Rendering Problem CITATION.cff | R11 CITATION.cff | R12 CITATION.cff | R13 CITATION.cff
R13 (Paper as Specification), R14 (Research as Repository), and The Rendering Problem (2026l) are cross-cutting methodology pieces that apply equally to Spectral Brand Theory and Organizational Schema Theory. They live here for historical reasons (originated in sbt-papers before the orgschema-papers split) but are conceptually shared between the two frameworks. The sibling repository orgschema-papers cross-references them as part of the broader specification-first research program.
| Repository | Description |
|---|---|
| orgschema-papers | Organizational Schema Theory research papers (sibling framework — operations side) |
| sbt-framework | AI-native brand analysis toolkit — 7-module prompt kit with YAML templates |
| brand-code | Executable brand identity specification — spectral palette, particle system source, AI-readable prompt |
| paper-spec | Paper Spec v0.1.0 — machine-readable YAML standard for scientific claims, with validator and 24 examples |
| Substack | Applied analysis articles on brand perception |
Dmitry Zharnikov — dmitry@spectralbranding.com
Brand measurement scientist and framework designer. Creator of Spectral Brand Theory, an AI-native approach to modeling how brands form in the observer's mind. Background in financial systems engineering and applied epistemology.
All papers are released under MIT License. Use, cite, and build upon this work freely with attribution.
"Spectral Brand Theory" and "Brand Code" are trademarks of Dmitry Zharnikov. The MIT license applies to the source code and text only and does not grant permission to use the project trademarks. You may cite, reference, and build upon this work freely, but derivative works should not use these names in ways that imply endorsement or official affiliation.
git clone https://github.com/spectralbranding/sbt-papers
cd sbt-papersFor a specific paper, navigate to its slug directory and read its local paper.md (or README.md if shipped) for paper-specific setup, dependencies, and reproduction instructions:
cd r7-spectral-resource-allocation
cat paper.mdPython tooling at the hub level uses uv (Python 3.12+). Install via curl -LsSf https://astral.sh/uv/install.sh | sh.
This is a hub repository: each top-level subdirectory is a self-contained per-paper bundle named by paper slug (e.g., spectral-brand-theory/, r0-literature-survey/, prism-instrument/). Every paper-slug directory ships its own paper.md, CITATION.cff, license files, and (where applicable) reproduce.sh plus output/ artifacts. The hub root provides the index (this README), the hub-level citation metadata (CITATION.cff), shared license declarations, and an iterating reproduction orchestrator.
sbt-papers/
├── CITATION.cff # hub-level citation
├── LICENSE # MIT (code)
├── LICENSE-data # CC BY 4.0 (data / figures / tables)
├── README.md # this file
├── pyproject.toml # hub project anchor
├── reproduce.sh # hub orchestrator: iterates each paper slug
├── output/{figures,tables,logs}/
└── <paper-slug>/ # one directory per paper (see Papers tables above)
├── paper.md
├── CITATION.cff
└── ...
Each paper-slug subdirectory that ships a computational pipeline includes its own reproduce.sh. The hub-level ./reproduce.sh iterates every paper slug, invoking each slug's reproduce.sh if present and executable:
./reproduce.sh # iterate all paper slugs
./reproduce.sh --check-only # verify per-slug dependency blocks only
./reproduce.sh --fast # pass --fast through to per-slug scriptsHub-level run log lands in output/logs/hub_run.log. Per-paper outputs land under <paper-slug>/output/ per the per-paper standard. Pure-theory papers without pipelines are skipped silently.
The hub itself has no Python runtime dependencies — the orchestrator only iterates subdirectories and invokes their scripts. Each paper-slug subdirectory declares its own dependencies in its local pyproject.toml or equivalent. The hub's pyproject.toml exists as a project root anchor; the standard uv (Python 3.12+) toolchain is the only hub-level requirement.
To cite the hub repository itself, see CITATION.cff at the root (GitHub renders a "Cite this repository" button). To cite an individual paper, use that paper's concept DOI from the tables above; full BibTeX entries are also listed in the "How to Cite" section earlier in this README, and each paper slug ships its own CITATION.cff.
Concept DOIs always point to the latest version of a paper. Per-version DOIs (immutable) are recorded in each paper slug's CITATION.cff and in the corresponding Zenodo record.
- Code — MIT License (see
LICENSE). Applies to scripts, configurations, and computational artifacts. - Data, figures, tables, rendered artifacts — Creative Commons Attribution 4.0 International (CC BY 4.0; see
LICENSE-data). - Trademarks — "Spectral Brand Theory" and "Brand Code" are trademarks of Dmitry Zharnikov; see the Trademarks section above.
Per-paper subdirectories inherit the dual-license discipline. Where a paper slug has its own LICENSE / LICENSE-data, those override the hub defaults for that paper only.
Last updated: 2026-05-29