# Algorithmic measurement procedures

## TL;DR

This paper formalizes measurement procedures as Turing machines, highlighting their effectiveness and limitations inspired by the halting problem, which restricts procedures from verifying measurements in all cases.

## Contribution

It introduces a formal computational framework for measurement procedures and identifies fundamental limitations based on halting problem insights.

## Key findings

- Measurements can be modeled as Turing machines.
- Verification procedures cannot work universally due to halting problem constraints.
- Formal limitations are established for measurement verification processes.

## Abstract

Measurements are shown to be processes designed to return figures: they are effective. This effectivity allows for a formalization as Turing machines, which can be described employing computation theory. Inspired in the halting problem we draw some limitations for measurement procedures: procedures that verify if a quantity is measured cannot work in every case.