Welcome to the Research Space of Lasky Design.
For the past 25 years, my professional journey as an industrial designer and engineering-backed creator has been driven by a singular obsession: uncovering the hidden mathematical rules and structural patterns underlying design—from the golden ratio to Euler’s number—and exploring how they manifest in physical reality. What began as a lifelong personal passion has evolved into an independent exploration of discrete topological networks and recursive spacetime systems.
All fundamental hypotheses, intuitive leaps, and core axiomatic concepts presented in the articles below originate entirely from my own creative intuition, structural background, and 25 years of design philosophy. For the formal academic drafting, technical execution, and textual synthesis of these ideas, I actively utilize modern collaborative AI tools, including Google Gemini and ChatGPT.
Research Publications & Theoretical Framework
1. Emergent Spacetime from Entropy-Driven Phase Transitions: A Structural Mechanics Approach to Gravity and the Time Arrow
Description: Explores recursive time at small scales, laying down the fundamental concept of informational state transitions.
2. Emergence of Newtonian Gravity in a Topologically Expanding Entropic Space-Network
Description: Mathematically and geometrically proves how Newtonian gravity naturally emerges from expanding network topologies rather than traditional physical forces.
3. The Entropic-Resistance Paradigm: Unifying Spacetime, Gravity, and Quantum Mechanics through Topological Network Constraints (2026)
Description: The foundational masterwork establishing the complete theoretical architecture unifying spacetime, gravity, black holes, and quantum mechanics.
4. Not a Theory of Everything, But a Working Sandbox: Spacetime as a Digital Twin for AI Systems (2026)
Description: A clarifying methodological summary emphasizing that this framework is not presented as literal physical reality, but as a rigorous mathematical "sandbox" and digital twin—providing a perfect simulated environment for next-generation AI and robotics development.
5. Emergent Superconductivity as a Topological Tension-Release in Recursive Space-Time Networks
Description: Investigates emergent superconductivity as topological stress-mitigation and tension-release mechanisms across recursive spacetime lattices.
6. 1/f Noise as a Macroscopic Signature of Recursive Time in Topological Space-Networks (2026)
Description: Analyzes pink (1/f) noise as the macroscopic observational fingerprint of recursive time ticking within topological spatial networks.
7. Sonoluminescence as a Topological Singularity: Photon Emission from Rapid Volume Deficits
Description: Provides a topological singularity model to explain photon emission (the characteristic blue light) driven by rapid macroscopic volume deficits.
8. From Minimal Axioms to Emergent Physics: A Top-Down Derivation of Spacetime Phenomena via the Entropic-Resistance Paradigm
Description: Inverts conventional bottom-up physics by introducing a minimal axiomatic core, deriving macroscopic spacetime phenomena strictly from top-down constraints.
9. Operator-Based Forward Sensitivity of Transient Interfacial Fluxes Under Localized Relaxation Contrasts (2026)
Description: Formalizes the operator-based forward-sensitivity framework for analyzing transient fluxes under localized network anomalies.
10. Causal Inference in Recursive Spacetime Networks: A White-Box Physics Engine for Next-Generation Artificial Intelligence
Description: Develops a transparent white-box physics and inference engine designed for advanced artificial intelligence architectures.
11. The Axiomatic Core of Recursive Spacetime Networks: A Manifesto on the Informational Dynamics of Physical Reality
Description: A foundational manifesto outlining the core informational axioms governing discrete reality dynamics.
12. Topological Reactors and Emergent 1/f Noise in Minimal Spacetime Networks
Description: Explores computational topological reactors and the emergence of characteristic noise signatures within minimal network constraints.
13. Topological Flux Screening and Causal-AI Discovery of Persistent Superconducting Channels in Miassite (Rh17S15) and Novel Intermetallic Lattices
Description: Applies high-throughput Materials Project screening and Causal-AI forward-sensitivity analysis to validate miassite and predict novel intermetallic candidate lattices like Rb4SbRhCl12.