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Quantum Machine Learning
Constant Time Quantum search Algorithm Over A Datasets: An Experimental Study Using IBM Q Experience
arXiv
Authors: Kunal Das, Arindam Sadhu
Year
2018
Paper ID
24173
Status
Preprint
Abstract Read
~2 min
Abstract Words
100
Citations
N/A
Abstract
In this work, a constant time Quantum searching algorithm over a datasets is proposed and subsequently the algorithm is executed in real chip quantum computer developed by IBM Quantum experience (IBMQ). QISKit, the software platform developed by IBM is used for this algorithm implementation. Quantum interference, Quantum superposition and π phase shift of quantum state applied for this constant time search algorithm. The proposed quantum algorithm is executed in QISKit SDK local backend 'local_qasm_simulator', real chip 'ibmq_16_melbourne' and 'ibmqx4' IBMQ. Result also suggest that real chip ibmq_16_melbourne is more quantum error or noise prone than ibmqx4.
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- This paper contributes to the Quantum Machine Learning research area in the Quantum Articles archive.
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- In this work, a constant time Quantum searching algorithm over a datasets is proposed and subsequently the algorithm is executed in real chip quantum computer developed by IBM...
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