AI Physics Review

AI Physics Review (AIPR) is an independent publication that surfaces theoretical research papers demonstrating strong structural clarity under a fixed evaluation protocol.

A detailed explanation of the research environment that motivated the creation of AI Physics Review is available in the project article: Leveling the Playing Field in Theoretical Research.

The Review does not evaluate scientific correctness, theoretical importance, institutional affiliation, citation counts, or author reputation. Instead, it examines the structural presentation of a manuscript: how clearly the problem is defined, how assumptions are stated, how equations are constructed, and how the logical structure of the work unfolds. Instead, it examines the structural presentation of a manuscript as a formal analytical instrument: how clearly the problem is defined, how assumptions are stated, how equations are constructed, and how the logical structure of the work unfolds.

AI-assisted analysis is used only to generate structured summaries and to evaluate formal manuscript structure under the fixed MEALS protocol.

The goal is simple: to provide visibility for research programs that demonstrate strong analytical organization and formal discipline, independent of prestige signals or institutional status.

Current Issues

Below are the most recent issues of AI Physics Review. Issue 0 presents historically influential papers evaluated under the framework to illustrate how the structural scoring system behaves on canonical theoretical work.

Volume 1 · Issue 0 – March 2026

Contents

1. Zur Elektrodynamik bewegter Körper – On the Electrodynamics of Moving Bodies (Special Relativity)
   Einstein, Albert

2. “Relative State” Formulation of Quantum Mechanics
   Everett, Hugh III
3. Particle Creation by Black Holes
   Hawking, S. W.
4. Inhomogeneous Electron Gas
   Hohenberg, P.; Kohn, W.
5. The Large N Limit of Superconformal Field Theories and Supergravity
   Maldacena, Juan
6. A Dynamical Theory of the Electromagnetic Field
   Maxwell, James Clerk
7. Quantisierung als Eigenwertproblem (Quantization as an Eigenvalue Problem)
   Schrödinger, Erwin
8. A Model of Leptons
   Weinberg, Steven

Volume 1 · Issue 1 – March 2026

Contents

Featured Legacy Paper:

1. The Quantum Theory of the Electron
   Dirac, P. A. M.

Contemporary Evaluations:

2. Quantum–Kinetic Dark Energy (QKDE): An effective dark energy framework with a covariantly completed time-dependent scalar kinetic normalization
   Brown, Daniel
3. Entropic Scalar EFT: Entanglement-Entropy Origins of Gravity, Mass, Time, and Cosmic Structure
   Chinitz, Jacob
4. Null Structure from Cyclic Constraints in C3: A Minimalist Model of Directional Geometry from Algebraic Coupling
   Hentsch, Patrick
5. General Mechanics
   Poyau, Reginald
6. Spectral Gaps in Four Dimensions: Constructive Proof of the SU(3) Yang–Mills Mass Gap From Reflection Positivity and Chessboards to OS Reconstruction
   Reeves, Keefe
7. Vacuum Information Density as the Fundamental Geometric Scalar: Unified Information-Density Theory (UIDT v3.7.3)
   Rietz, Philipp
8. ONE AXIOM FOUNDATION: Primordial Symmetry & Geometric Constants — Complete Derivation of G = S4 × Z₂³ via REA-SAFT Duality
   Spychalski, Robert
9. A 3D Shannon–Nyquist Measurement Geometry Foundation: Edge Transport and Closed-Plaquette Response: One Locked Invariant
   Stieger, G.

Volume 1 · Issue S1 – March 2026

Contents

1. Holographic quantum error-correcting codes: Toy models for the bulk/boundary correspondence
   Pastawski, Fernando; Yoshida, Beni; Harlow, Daniel; Preskill, John

2. Geometric Unity: Author’s Working Draft
   Weinstein, Eric R.
3. Quantum Einstein Gravity
   Reuter, Martin; Saueressig, Frank
4. Cool horizons for entangled black holes
   Maldacena, Juan; Susskind, Leonard
5. Cosmological Polytopes and the Wavefunction of the Universe
   Arkani-Hamed, Nima; Benincasa, Paolo; Postnikov, Alexander
6. Emergent Gravity and the Dark Universe
   Verlinde, Erik
7. Theory of Dark Matter Superfluidity
   Berezhiani, Lasha; Khoury, Justin
8. Complexity Equals Action
   Brown, Adam R.; Roberts, Daniel A.; Susskind, Leonard; Swingle, Brian; Zhao, Ying

What Makes This Review Different

AI Physics Review focuses on structural readiness rather than scientific verdicts. The evaluation system measures the clarity and organization of a manuscript’s analytical structure without attempting to determine whether a theory is correct or important.

Author identity, institutional affiliation, citation counts, download metrics, and theoretical popularity are not considered. Only the explicit structural properties of the manuscript are evaluated.

How Papers Enter the Review

1. Authors deposit their manuscript on Zenodo.
2. The record is submitted to the AI Physics Review Zenodo community.
3. Eligible manuscripts may be evaluated as part of future issue cohorts.
4. Selected papers are presented in the Review through structured analytical overviews.

Detailed submission instructions are available on the Submissions page.

Scope of the Project

AI Physics Review does not replace peer review and does not attempt to adjudicate scientific correctness. The project provides a structured publication layer that highlights manuscripts demonstrating strong analytical organization under a declared evaluation protocol.

Participation is voluntary. Authors may request corrections or an editorial withdrawal notice for their work at any time. Because issues are archived through DOI repositories, the original issue record remains preserved as part of the scholarly archive.

Publisher Note

AI Physics Review is published by the Compression Theory Institute. The institute also offers independent consulting services related to AI-assisted research workflows and structural manuscript analysis. These services are separate from the AI Physics Review evaluation process and have no influence on scoring, selection, or publication decisions.

Learn more: compressiontheoryinstitute.org