Discrete-time quantum walk search on the cycle graph with weighted self-loop

Abstract The evolution operator of the lackadaisical quantum walk on a weighted cycle graph with self-loop weight $$w&gt;0$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>w</mml:mi> <mml:mo>&gt;</mml:mo> <mml:mn>0</mml:mn> </mml:mrow> </mml:math> is examined. With Grover oracle, the effect of different values of $$w$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>w</mml:mi> </mml:math> on the success probability of the search under various hyperparameter combinations is analyzed. The success probability function of the first few steps is provided algebraically, which in turn highlights the role of $$w$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>w</mml:mi> </mml:math> in governing the evolutionary behavior of the quantum walk search. These studies subsequently allow the numerical results to be obtained for various hyperparameter combinations, showing that the highest success probability for the weighted cycle graph with $$N$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>N</mml:mi> </mml:math> vertices is achieved using a flip-flop shift operator, a weighted coin superposition initial state, and $$w=\frac{1.26}{N}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>w</mml:mi> <mml:mo>=</mml:mo> <mml:mfrac> <mml:mrow> <mml:mn>1.26</mml:mn> </mml:mrow> <mml:mi>N</mml:mi> </mml:mfrac> </mml:mrow> </mml:math> . A comparison is also made with other known oracle, demonstrating that the proposed configuration provides a better trade-off between success probability and runtime. An extension of the study to the SKW scheme is also included, and it demonstrates that the scheme provides more variability and potential for quantum walk search.

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Publication Details

Journal
Quantum Information Processing
Published
2025-10-03
DOI
https://doi.org/10.1007/s11128-025-04945-w
Primary Topic
Quantum Computing Algorithms and Architecture
Type
article
Field-Weighted Citation Impact
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article

Discrete-time quantum walk search on the cycle graph with weighted self-loop

Ian K. T. Tan, Kai Lin Ong, Yong Qing Tiong
Quantum Information Processing
Quantum Computing Algorithms and Architecture
article

Discrete-time quantum walk search on the cycle graph with weighted self-loop

Ian K. T. Tan, Kai Lin Ong, Yong Qing Tiong
article en

Abstract

Abstract The evolution operator of the lackadaisical quantum walk on a weighted cycle graph with self-loop weight $$w&gt;0$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>w</mml:mi> <mml:mo>&gt;</mml:mo> <mml:mn>0</mml:mn> </mml:mrow> </mml:math> is examined. With Grover oracle, the effect of different values of $$w$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>w</mml:mi> </mml:math> on the success probability of the search under various hyperparameter combinations is analyzed. The success probability function of the first few steps is provided algebraically, which in turn highlights the role of $$w$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>w</mml:mi> </mml:math> in governing the evolutionary behavior of the quantum walk search. These studies subsequently allow the numerical results to be obtained for various hyperparameter combinations, showing that the highest success probability for the weighted cycle graph with $$N$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>N</mml:mi> </mml:math> vertices is achieved using a flip-flop shift operator, a weighted coin superposition initial state, and $$w=\frac{1.26}{N}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>w</mml:mi> <mml:mo>=</mml:mo> <mml:mfrac> <mml:mrow> <mml:mn>1.26</mml:mn> </mml:mrow> <mml:mi>N</mml:mi> </mml:mfrac> </mml:mrow> </mml:math> . A comparison is also made with other known oracle, demonstrating that the proposed configuration provides a better trade-off between success probability and runtime. An extension of the study to the SKW scheme is also included, and it demonstrates that the scheme provides more variability and potential for quantum walk search.

Quantum Information ProcessingVol. 24(10)
Heriot-Watt University Malaysia (MY)
Openalex Percentile: Top 86%
Quantum Computing Algorithms and Architecture
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Discrete-time quantum walk search on the cycle graph with weighted self-loop — Ian K. T. Tan, Kai Lin Ong, et al. · Quantum Information Processing (2025) | TGRS Research Map | TGRS