Limits to measurement in experiments governed by algorithms
E. J. Beggs, J. F. Costa, J. V. Tucker

TL;DR
This paper explores how algorithms controlling physical experiments influence measurement limits, proposing a theoretical framework that links computation and physical measurement constraints, revealing a new uncertainty principle.
Contribution
It introduces a formal model of physical experiments as oracles for Turing machines, analyzing the computational limits and measurement constraints imposed by algorithmic control.
Findings
Algorithms impose fundamental limits on measurement accuracy.
A new uncertainty principle for physical measurements is proposed.
Experimental procedures can be modeled as computational oracles.
Abstract
We pose the following question: If a physical experiment were to be completely controlled by an algorithm, what effect would the algorithm have on the physical measurements made possible by the experiment? In a programme to study the nature of computation possible by physical systems, and by algorithms coupled with physical systems, we have begun to analyse (i) the algorithmic nature of experimental procedures, and (ii) the idea of using a physical experiment as an oracle to Turing Machines. To answer the question, we will extend our theory of experimental oracles in order to use Turing machines to model the experimental procedures that govern the conduct of physical experiments. First, we specify an experiment that measures mass via collisions in Newtonian Dynamics; we examine its properties in preparation for its use as an oracle. We start to classify the computational power of…
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Taxonomy
TopicsComputability, Logic, AI Algorithms · Machine Learning and Algorithms · Neural Networks and Applications
