FIRST-PRINCIPLES COMPUTATION

I design and build computational systems for modeling complex physical and biological processes. My work centers on developing new mathematical frameworks and architectural abstractions that improve fidelity, stability, and scale in high dimensional simulation.

I study how structure governs behavior in complex systems. This includes exploring ways to maintain coherence across heterogeneous dynamical regimes, to limit interference propagation in constrained environments, and to address the bottlenecks that appear when small variations compound into large scale effects.

My current work focuses on foundational capabilities that remain in stealth.

THE ARCHITECT

Much of my work comes down to how I structure and reason about complex systems.

I work at the intersection of physics, applied mathematics, and computational design. I focus on building architectures that can sustain coherent transformations across intricate configuration spaces, systems where small perturbations cascade through multiple scales, and where conventional frameworks struggle to maintain a unified way of reasoning between classical, statistical, and algorithmic views of a problem.

My applied work involves designing computational substrates that map fundamental operators to emergent behavior, enabling more reliable inference in domains where structure and dynamics interact in high dimensional ways.

ABOUT

I am the founder of Aliqubit, a deterministic simulation engine built to remove instability and sampling noise from modern solvers.

My path into this work was not academic. I spent years in competitive golf, where rebuilding mechanics under structural injury taught me to think in terms of constraints, force transfer, error accumulation, and stability under pressure. Those ideas stayed with me and eventually shaped how I approach computational modeling.

In 2024 I began formalizing a set of modeling concepts I had been developing informally for several years. I taught myself the numerical methods, solver design, and software architecture needed to test them. The result is LQM, Localized Quantum Models, a deterministic approach that focuses on structure rather than repeated sampling. It is not physics. It is a mathematical perspective influenced by operator style thinking and localized state transitions.

I built the initial engine to prove the core thesis, and the framework has since been refined with external review and real world feedback. Aliqubit now focuses on high confidence simulation and optimization in settings where reproducibility and clarity of assumptions matter as much as speed.

My work is motivated by a simple belief. Computational systems should behave predictably, reveal their underlying structure, and be grounded in clear first principles rather than obscured inside opaque sampling routines.