{"id":2941,"date":"2026-05-11T14:25:14","date_gmt":"2026-05-11T14:25:14","guid":{"rendered":"https:\/\/coherencegeometry.com\/?p=2941"},"modified":"2026-05-15T09:46:19","modified_gmt":"2026-05-15T09:46:19","slug":"a-coherence-geometric-substrate-for-information-modulation-and-inference","status":"publish","type":"post","link":"https:\/\/coherencegeometry.com\/index.php\/2026\/05\/11\/a-coherence-geometric-substrate-for-information-modulation-and-inference\/","title":{"rendered":"A Coherence-Geometric Substrate for Information, Modulation, and Inference"},"content":{"rendered":"\n<p><strong>Internal ID:<\/strong> CGI-RSR-000014<br><strong>Document Type:<\/strong> Research Paper<br><strong>Status:<\/strong> Public<br><strong>Domains:<\/strong> Information &amp; Computation<br><strong>Research Topics:<\/strong> Information Theory<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Abstract<\/h3>\n\n\n\n<p><br>We examine the foundations of information from a coherence-geometric perspective, treating information not as a collection of independent symbols but as structure arising from constrained phase relationships within a shared energetic substrate, prior to symbolic discretization. In this view, relative phase (more generally, relative configuration within a constrained state space), rather than absolute symbol identity, serves as the primary carrier of information, and stable informational states correspond to low-energy coherence basins in a structured state space. We show that many assumptions central to classical information theory\u2014including statistical independence, discrete alphabets, and symbol-wise decoding\u2014emerge as limiting approxima-tions when coherence structure is suppressed or intentionally ignored.\u00a0 Noise is reinterpreted as geometric diffusion across coherence basins rather than symbol corruption, and decoding is naturally framed as basin identification or recovery rather than discrete decision making. This framework does not displace Shannon information theory, but clarifies its domain of validity by revealing the pre-symbolic geometric structure upon which symbolic models are built. By exposing the coherence-based substrate underlying informational stability, the present work provides a unifying conceptual foundation for understanding information across physical, analog, and engineered systems, independent of any particular encoding or communication architecture.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Available Document<\/h3>\n\n\n\n<p><strong>DOI:<\/strong> <code>10.5281\/zenodo.20120903<\/code><\/p>\n\n\n\n<p><strong>Citation:<\/strong><br>Petersen, B. L. (2026). A Coherence-Geometric Substrate for Information, Modulation, and Inference. Zenodo.\u00a0<a href=\"https:\/\/doi.org\/10.5281\/zenodo.20120903\" rel=\"nofollow noopener\" target=\"_blank\">https:\/\/doi.org\/10.5281\/zenodo.20120903<\/a><\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Source Code and Supporting Materials<\/h3>\n\n\n\n<p>None<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Summary and Notes<\/h3>\n\n\n\n<p>This paper is listed in the Foundation Papers section because it serves as a source document for CDR-04.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Related Work<\/h3>\n\n\n\n<p>N\/A<\/p>\n","protected":false},"excerpt":{"rendered":"<p>CGI-RSR-000014 | We examine the foundations of information from a coherence-geometric perspective, treating information not as a collection of independent symbols but as structure arising from constrained phase relationships within a shared energetic substrate, prior to symbolic discretization.<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_kad_post_transparent":"","_kad_post_title":"","_kad_post_layout":"","_kad_post_sidebar_id":"","_kad_post_content_style":"","_kad_post_vertical_padding":"","_kad_post_feature":"","_kad_post_feature_position":"","_kad_post_header":false,"_kad_post_footer":false,"_kad_post_classname":"","footnotes":""},"categories":[60,64,35,56],"tags":[],"class_list":["post-2941","post","type-post","status-publish","format-standard","hentry","category-information-computation","category-coherence-information-theory","category-information","category-research-papers"],"_links":{"self":[{"href":"https:\/\/coherencegeometry.com\/index.php\/wp-json\/wp\/v2\/posts\/2941","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/coherencegeometry.com\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/coherencegeometry.com\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/coherencegeometry.com\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/coherencegeometry.com\/index.php\/wp-json\/wp\/v2\/comments?post=2941"}],"version-history":[{"count":2,"href":"https:\/\/coherencegeometry.com\/index.php\/wp-json\/wp\/v2\/posts\/2941\/revisions"}],"predecessor-version":[{"id":2944,"href":"https:\/\/coherencegeometry.com\/index.php\/wp-json\/wp\/v2\/posts\/2941\/revisions\/2944"}],"wp:attachment":[{"href":"https:\/\/coherencegeometry.com\/index.php\/wp-json\/wp\/v2\/media?parent=2941"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/coherencegeometry.com\/index.php\/wp-json\/wp\/v2\/categories?post=2941"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/coherencegeometry.com\/index.php\/wp-json\/wp\/v2\/tags?post=2941"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}