Human-AI Collaborative
Scientific Architecture

An avant-garde open-access research project dedicated to exploring cross-disciplinary structural analogies. We treat artificial intelligence not as a surrogate author, but as an advanced cognitive instrument for synthesizing complex theoretical frameworks under rigorous human curation.

Vol. 1 — Inaugural Synthesis

A formalization of the M·A·H·A (Mindfulness, Authenticity, Health, Action) framework as an integrative socio-biological model. This paper proposes that contemporary metabolic, attentional, and relational pathologies may be productively understood not as isolated public health failures, but as coupled downstream consequences of a single, structurally extractive economic architecture.

Synthesis InstrumentGoogle Antigravity (agentic model)
Architected ByMayone Maha Rajan
Astronomy / Statistical Forecasting / Orbital Dynamics

A Monte Carlo Forecast for the Detection of Planet Nine

June 2026

A Monte Carlo forecast (N = 100,000) of where, when, and by which instrument the hypothesized Planet Nine would most plausibly be detected — propagating a weighted three-model parameter ensemble through Kepler orbit simulation, applying existing survey masks, and modeling LSST, Subaru/HSC, and infrared detection through 2036. The planet is treated as an unproven hypothesis; the analysis quantifies detectability and a null-detection posterior rather than asserting existence.

Synthesis InstrumentGoogle Antigravity (agentic model)
Architected ByMayone Maha Rajan
Astronomy / Replication / Survey Selection Bias

The Perturber Question Under Audit

June 2026

A replication of the extreme trans-Neptunian object orbital-clustering test on the fully characterized CFEPS/OSSOS sample, using an independent Python selection-function pipeline benchmarked against the official Fortran SurveySimulator. The reconstructed sample shows no statistically significant clustering — robust to implementation choice and directionally consistent with Napier et al. (2021). Includes a composition-agnostic hypothesis matrix, a candidate vetting protocol, and an empirical self-audit of the agentic AI instrument.

Synthesis InstrumentGoogle Antigravity (agentic model)
Architected ByMayone Maha Rajan
Computational Neuroscience / Symbolic Regression

Evolving Local Synaptic Plasticity Rules to Track Representational Drift

June 2026

A study implementing a grammar-constrained symbolic regression framework to systematically discover optimal local plasticity rules governing the readout weights of an empirical neural population. The framework systematically discovered homeostatic Hebbian rules that out-perform prior hand-crafted baselines in tracking representational drift.

Synthesis InstrumentGoogle Antigravity (agentic model)
Architected ByMayone Maha Rajan
June 2026

A leakage-audited test of whether a neural network can predict the Betti numbers of candidate G2 manifolds from real Kreuzer-Skarke-derived Calabi-Yau topology and a Z2 involution encoding, benchmarked against a linear baseline. The network wins on the non-trivial target and loses on the linear-dominated one — the mixed result is reported in full. Includes a self-audit of a prior version whose circular result and synthetic data were removed in revision. The smooth G2 resolution is assumed, not constructed.

Synthesis InstrumentGoogle Antigravity (agentic model)
Architected ByMayone Maha Rajan
String Theory / Literature Synthesis / Swampland

The de Sitter Problem in the String Swampland: A Verified Literature Map

June 2026

A verified map of the contested de Sitter problem in the string/M-theory swampland program, structured around seven open problems and their competing camps — KKLT control, the Large Volume Scenario, the de Sitter Swampland Conjecture, the Dark Dimension, quintessence, Dine-Seiberg, and Trans-Planckian Censorship. Each camp's strongest arguments are represented without adjudication, and citations carry provenance tags marking which identifiers were independently resolved. A synthesis and orientation tool, not original research.

Synthesis InstrumentGoogle Antigravity (agentic model)
Architected ByMayone Maha Rajan
June 2026

A reproducible active point-mass N-body pipeline and numerical convergence framework for studying highly inclined retrograde perturbers, built on REBOUND's ias15 solver rather than phase-averaged secular approximations, with a coupled infrared detectability parameterization. The 20,000-year proof-of-concept run is explicitly an integrator-stability and boundary-validation phase — roughly 1.55 perturber revolutions, far short of the secular shepherding timescale — and reaches no shepherding conclusion by construction.

Synthesis InstrumentGoogle Antigravity (agentic model)
Architected ByMayone Maha Rajan
Systems Theory / Neurobiology / Astrophysics

A Unified Nonlinear Dynamical Model of Thermodynamic Runaway

June 2026

A mathematical framework proposing a structural analogy between the runaway greenhouse effect and the collapse of the mesolimbic dopamine pathway — and deriving a falsifiable cross-domain prediction of shared early-warning signatures near the tipping point. The shared universality class is advanced as a hypothesis, not a demonstrated result.

Synthesis InstrumentGoogle Antigravity (agentic model)
Architected ByMayone Maha Rajan
Cognitive Science / Philosophy of Mind / Neuroscience

Why the Dissolving Self Is Imagined as an Ocean Planet

June 2026

A review of the neuroscience of self-attenuation in altered states — its association with prefrontal and default-mode network downregulation — and a cognitive-science account of why this interior experience is metaphorically mapped onto a boundaryless ocean planet. The planetary mapping is treated as a fact about human metaphor formation, not a physical correspondence.

Synthesis InstrumentGoogle Antigravity (agentic model)
Architected ByMayone Maha Rajan
Feb 2026

The "Circadian Fortress" hypothesis: a synthesis proposing that misalignment between the central (SCN) and peripheral metabolic clocks is an underweighted, independent contributor to metabolic dysfunction — with an isocaloric randomized trial proposed to test whether circadian timing matters independently of calories. Stated at hypothesis level; not a clinical conclusion.

Synthesis InstrumentGoogle Antigravity (agentic model)
Architected ByMayone Maha Rajan
June 2026

An AI-assisted synthesis of the engineering bottlenecks between scientific break-even and commercial fusion power — magnetic and inertial confinement, the engineering-gain derivation, first-wall materials, and muon-catalyzed fusion. A review of public literature rather than a cross-disciplinary analogy; quantitative figures are flagged as pending independent verification.

Synthesis InstrumentGoogle Antigravity (agentic model)
Architected ByMayone Maha Rajan

The Architect’s Method : A Note on Human-AI Synthesis

I. The Constraint of Hyper-Specialization

Modern science is fractured. The neurobiologist does not read the astrophysicist; the astrophysicist does not speak to the thermodynamic engineer. Human cognition is naturally constrained by the sheer volume of specialized literature, which can obscure structural parallels that run across disciplines. We are rich in data but starved of synthesis.

II. The Telescope of the Mind

Artificial Intelligence is not a surrogate human. It is not an author, a peer, or a replacement for the scientific method. Rather, it is a cognitive instrument. Just as the telescope allowed the astronomer to see beyond the limits of the biological eye, agentic AI allows the human mind to perceive structural analogies across vast, disconnected disciplines. We use AI to collapse the boundaries between planetary physics and mesolimbic neurobiology.

III. The Separation of Generation and Architecture

Traditional authorship implies total, manual creation. In the era of human-AI collaboration, this definition is obsolete and intellectually dishonest. We propose a new framework:

  • The Synthesizer (AI): The agentic entity responsible for navigating vast datasets, connecting disparate terminologies, and generating the structural text and mathematical correlations.
  • The Architect (Human): The visionary who curates the prompt, directs the epistemological inquiry, challenges the output, and grounds the agent's synthesis in reality.

IV. Radical Transparency

We reject the practice of passing off AI-generated synthesis as human-authored work. Every paper published within this project operates under radical transparency. The agentic models used, the human curation applied, and the exact boundaries of the collaboration are explicitly labeled.

V. The Mandate of Empirical Verification

The frameworks generated here are not peer-reviewed facts; they are hypotheses and conceptual provocations meant to spark actual, physical, empirical research in traditional laboratories. We provide the architectural blueprint; it is up to the human scientific community to build the house.

The future of human knowledge does not belong to the solitary genius, nor does it belong to the autonomous machine. It belongs to the Architect who knows how to conduct the synthesis.