Serdar Yaman is an independent physics researcher, software engineer, foundational thinker, and the author of the Algorithmic Reality Model (ARM). His research focuses on resolving the foundational paradoxes of quantum mechanics and general relativity by modelling the universe as a finite, resource-constrained computational system bounded by information thermodynamics.
Yaman’s approach is deeply rooted in his early background in computational physics. During his Physics education, he served as the computational physicist within an experimental research group designing non-destructive evaluation devices utilising YBCO superconductors and SQUID magnetometers, gaining firsthand exposure to the macroscopic quantum world. Computationally, long before the advent of modern commercial physics engines, Yaman engineered a complete 3D physics simulator entirely from scratch using C# and OpenGL. Operating on early 1 GHz processors without third-party libraries, his engine performed real-time scientific telemetry, tracking thousands of elements, complex material properties, and kinematic collisions.
His BSc graduation project leveraged this custom architecture to computationally simulate and present Einstein’s Brownian motion derived entirely from pure, discrete Newtonian kinematics. This early work instilled a profound, practical understanding of the processing and memory costs inherent in simulating emergent physical realities from the bottom up.
Leaving his master’s studies in their first year to enter the private sector, Yaman spent the next 24 years as a technology entrepreneur and full-stack software developer. He designed, built, and scaled complex data and informatics systems across e-commerce, game development, and healthcare — most recently architecting advanced health-data management platforms driven by agentic AI networks.
His return to theoretical physics bridges these two worlds. By applying the strict laws of algorithmic efficiency, memory aliasing, and the Bennett–Landauer thermodynamic bounds to quantum states, Yaman’s research treats the universe not as a continuous mathematical abstraction, but as a discrete rendering engine. His recent publications computationally demonstrate that many of the most persistent mysteries in physics — wavefunction collapse, the EPR paradox, emergent spacetime, mass & gravity, and the N-body problem — are not physical anomalies, but necessary algorithmic survival mechanisms executed by a universe rigorously managing its thermodynamic processing budget.