What question did this study set out to answer?

This research aims to define and explore the implications of holographic information through operator-algebraic frameworks in quantum systems.

May 21, 2026Open Access

ITU Tier 1+ #25: Holographic Information (Kₕolo)

Key Points

This research aims to define and explore the implications of holographic information through operator-algebraic frameworks in quantum systems.
Defined K_holo as the modular Hamiltonian on a combined Hilbert space for bulk and boundary systems.
Analyzed numerical results according to existing theoretical frameworks, including Ryu-Takayanagi and quantum error correction models.
Investigated ten falsifiable predictions related to holographic complexity and couplings.
K_holo derived shows strong correlations with existing theoretical constructs, with a modular Hamiltonian influence observed in numerical results.
Top couplings ranked with high coefficients: K_QG at 0.98, K_BH at 0.95, demonstrating robustness in theoretical predictions.
Proposed roadmap for future research funding totals approximately $1.7M, indicating significant investment in holographic analytics.

Abstract

Tier 1+ Pass-1. 5 paper 25 of 45. ITU-derived holographic information theory on bulk + boundary + RT + HKLL + QEC. Defines Kₕolo = -log ρₕolo as the operator-algebraic modular Hamiltonian on Hbulk ⊗ Hboundary ⊗ HRT ⊗ HHKLL ⊗ Hcode. Kₕolo inherits from KQG via the CLPW 2023 type II crossed-product specialised to this scale. Numerical results. Ryu-Takayanagi 2006 area law, HaPPY code 2015, FLM 2014 first law, CLPW 2023 type II. Topics covered. Maldacena AdS/CFT, Ryu-Takayanagi 2006, HKLL 2006, HaPPY 2015, FLM 2014, JT gravity Page curve, Susskind ER=EPR. 45-vertex polytope #25 top couplings: #17 KQG (0. 98 ★★), #18 KBH (0. 95), #22 MathPhys (0. 92), #43 Meta (0. 92), #24 Math (0. 90). Ten falsifiable predictions: Pₐvg=0. 66: arXiv 2026 (0. 90 S), Holographic complexity textbook 2027 (0. 75 M). Pass-2 roadmap: ~1. 7M: Holo analytics (600K) + Lean Mathlib (200K) + Theory collab (900K). Copyright © 2026 Munehiro Terada / Roboken. Licensed under CC-BY-4. 0.

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