Quick Navigation
Topics
Quantum Machine Learning
Analyzing Quantum Circuit Depth Reduction with Ancilla Qubits in MCX Gates
arXiv
Authors: Ahmad Bennakhi, Paul Franzon, Gregory T. Byrd
Year
2024
Paper ID
64664
Status
Preprint
Abstract Read
~2 min
Abstract Words
80
Citations
N/A
Abstract
This paper aims to give readers a high-level overview of the different MCX depth reduction techniques that utilize ancilla qubits. We also exhibit a brief analysis of how they would perform under different quantum topological settings. The techniques examined are recursion and v-chain, as they are the most commonly used techniques in the most popular quantum computing libraries, Qiskit. The target audience of this paper is people who do not have intricate mathematical or physics knowledge related to quantum computing.
Why This Paper Matters
- This paper contributes to the Quantum Machine Learning research area in the Quantum Articles archive.
- It adds a 2024 reference point for readers tracking recent quantum research.
- This paper aims to give readers a high-level overview of the different MCX depth reduction techniques that utilize ancilla qubits.
Paper Tools
Become a member to use research tools
Sign in to open papers, visit source links, share, cite, compare, copy DOI links, request category corrections, and build your reading list.
Show Paper arXiv Publisher Share
Cite This Paper
Copy URL
Compare
Copy DOI Add to Reading List
Category Correction Request
Category Correction Request
Help us improve classification quality by proposing a better category. Every request is reviewed by an admin.
Sign in to submit a category correction request for this paper.
Log In to SubmitReferences & Citation Signals
Community Reactions
Quick sentiment from readers on this paper.
Score:
0
Likes: 0
Dislikes: 0
Sign in to react to this paper.
Discussion & Reviews (Moderated)
Average Rating: 0.0 / 5 (0 ratings)
No written reviews yet.