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Updated: May 13, 2026

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Published on: September 8, 2023

Quantum iterative deepening with an application to the halting problem.

Luís Tarrataca¹, Andreas Wichert

¹Department of Informatics, INESC-ID/Instituto Superior Técnico, Lisbon, Portugal. luis.tarrataca@ist.utl.pt

|March 23, 2013

Summary

This summary is machine-generated.

This study introduces a novel quantum computation approach using production systems and Grover

Related Experiment Videos

Last Updated: May 13, 2026

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Published on: September 8, 2023

Area of Science:

Quantum Computing
Theoretical Computer Science
Computational Complexity

Background:

Classical computation relies on halting schemes to check computational states, which are problematic for quantum systems due to superposition.
Measuring quantum halt qubits can collapse states, interfering with computations, especially for undecidable problems like the Entscheidungsproblem.
Universal computational models like Turing machines may need to run indefinitely, posing challenges for traditional halting mechanisms.

Purpose of the Study:

To propose an alternative quantum computation model that overcomes interference issues with halt state detection.
To enable non-terminating computations within a quantum framework.
To achieve inherent speedups in parallelizable computations.

Main Methods:

Integration of production system theory with Grover's amplitude amplification scheme for quantum computation.
Development of a method for detecting halt states without disrupting quantum superposition or computation.
Application of the proposed strategy to simulate classical Turing machines.

Main Results:

A quantum computation framework allowing non-interfering detection of halt states.
Capability for handling non-terminating computations, addressing undecidable problems.
Demonstration of inherent speedups in parallelizable quantum computations.

Conclusions:

The proposed quantum computation model effectively addresses limitations of classical halting schemes.
This approach offers a viable method for simulating classical Turing machines quantum mechanically.
The framework provides a foundation for more robust and efficient quantum computation, particularly for complex problems.