Quick Navigation
Topics
Quantum Simulation
Optimal exact quantum algorithm for the promised element distinctness problem
arXiv
Authors: Guanzhong Li, Lvzhou Li
Year
2022
Paper ID
57507
Status
Preprint
Abstract Read
~2 min
Abstract Words
180
Citations
N/A
Abstract
The element distinctness problem is to determine whether a string x=\(x1,ldots,xN\) of N elements contains two elements of the same value (a.k.a colliding pair), for which Ambainis proposed an optimal quantum algorithm. The idea behind Ambainis' algorithm is to first reduce the problem to the promised version in which x is promised to contain at most one colliding pair, and then design an algorithm mathcal{A} requiring O\(N2/3\) queries based on quantum walk search for the promise problem. However, mathcal{A} is probabilistic and may fail to give the right answer. We thus, in this work, design an exact quantum algorithm for the promise problem which never errs and requires O\(N2/3\) queries. This algorithm is proved optimal. Technically, we modify the quantum walk search operator on quasi-Johnson graph to have arbitrary phases, and then use Jordan's lemma as the analyzing tool to reduce the quantum walk search operator to the generalized Grover's operator. This allows us to utilize the recently proposed fixed-axis-rotation (FXR) method for exact quantum search, and hence achieve 100% success.
Why This Paper Matters
- This paper contributes to the Quantum Simulation research area in the Quantum Articles archive.
- It adds a 2022 reference point for readers tracking recent quantum research.
- The element distinctness problem is to determine whether a string x=(x1,ldots,xN) of N elements contains two elements of the same value (a.k.a colliding pair), for which...
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.