Wave Function Collapse as Information Processing Rate Minimization: A Derivation from QED First Principles

YOUNG HO GOH

Zirui Zhang, Shannon Cheng, Kevin Xiao +2 more

YOUNG HO GOH

Decoherence theory predicts when wave function collapse occurs but does not explain why it proceeds only from superposition to definite state. We derive this directional asymmetry from information processing load minimization. The information processing load of a superposition state after n environmental interactions is C_wave(n) = D·d^n — the dimension of the joint system-environment Hilbert space — where D is the system dimension and d is the environmental coupling dimension. The load of a definite state is C_particle = K_HUP, where K_HUP = σ_x/l_p is derived without free parameters from the uncertainty principle established in Paper 2: the Planck length l_p = √(ℏG/c³) sets the minimum position precision, requiring σ_p,min = ℏ/(2l_p), and K_HUP is the ratio of this momentum cost to the wave packet's natural momentum spread. For an electron with σ_x = 1 Å, K_HUP = 6.19 × 10²⁴; for a dust particle (σ_x = 0.1 μm), K_HUP = 6.19 × 10²⁷. Since C_wave grows exponentially with n while C_particle is constant, collapse occurs at the crossover n* = log(K_HUP/D)/log(d), after which the definite state has lower load. The load increase rate per interaction α = log(d) is identified with the Zurek decoherence parameter (Δx/λ_dB)², establishing that decoherence theory and load minimization are two descriptions of the same physical process. Quantum eraser reversibility is explained as external reduction of n_eff below n*. The framework contains no free parameters: K_HUP is determined by σ_x and l_p, and α by the de Broglie wavelength ratio.

Jincheng Zhang

Wave function collapse is a cornerstone of quantum mechanics, representing the irreversible process by which a quantum system's state is determined. This paper introduces Adaptive Wave Function Collapse (AWC), a dynamic algorithm designed to optimize information extraction and minimize measurement errors during this collapse process. The core of AWC lies in a novel "wave function feedback" loop that continuously adjusts the collapse probability, guided by a "collapse rate" parameter. This dynamic adjustment ensures a more efficient and stable collapse, addressing limitations inherent in traditional collapse methods. The paper details the algorithm's implementation, explores its performance characteristics, and provides a conceptual analysis of its potential impact on quantum information processing.

Jonathan A. Jones

Ali Caner Yücel

The mechanism underlying wave function collapse remains one of the most persistent open questions in the foundations of quantum mechanics. Standard interpretations often treat the collapse as either an inexplicable axiom (Copenhagen) or an illusion (Many-Worlds). This paper proposes a third alternative based on the Principle of Informational Parsimony in a finite-capacity universe. We posit that the wave function represents a system in an informationally compressed state, maintained to optimize the computational resources of spacetime. Within this framework, “collapse” is reinterpreted as a Data Rendering Event: a thermodynamic transition where the system decompresses the state vector into a localized coordinate in response to an interaction request (observation). Using Landauer’s Principle, we derive the minimum thermodynamic cost of this rendering process. We further argue that the Heisenberg Uncertainty Principle arises naturally as a resolution limit inherent to the transition between compressed (momentum-space) and rendered (position-space) data formats. Finally, we propose that the discrete granularity of this rendering process implies a detectable quantization noise at the Planck scale.