Quantum Catalytic Space
Harry Buhrman, Marten Folkertsma, Ian Mertz, Florian Speelman, Sergii Strelchuk, Sathyawageeswar Subramanian, Quinten Tupker

TL;DR
This paper introduces quantum catalytic computing, exploring its capabilities and showing that quantum catalytic logspace can be efficiently computed, simulated, and can simulate complex circuit classes, highlighting its computational power.
Contribution
The paper formally defines quantum catalytic computing, demonstrates its polynomial-time computability, and shows its ability to simulate complex quantum and classical circuit classes.
Findings
Quantum catalytic logspace can be computed in polynomial time.
Quantum catalytic logspace can simulate log-depth threshold circuits.
Both quantum and classical catalytic logspace can be simulated in the one-clean qubit model.
Abstract
Space complexity is a key field of study in theoretical computer science. In the quantum setting there are clear motivations to understand the power of space-restricted computation, as qubits are an especially precious and limited resource. Recently, a new branch of space-bounded complexity called catalytic computing has shown that reusing space is a very powerful computational resource, especially for subroutines that incur little to no space overhead. While quantum catalysis in an information theoretic context, and the power of ``dirty'' qubits for quantum computation, has been studied over the years, these models are generally not suitable for use in quantum space-bounded algorithms, as they either rely on specific catalytic states or destroy the memory being borrowed. We define the notion of catalytic computing in the quantum setting and show a number of initial results about…
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