scholarly journals Genetic algorithm‐based optimization of pulse sequences

2021 ◽  
Author(s):  
Vencel Somai ◽  
Felix Kreis ◽  
Adam Gaunt ◽  
Anastasia Tsyben ◽  
Ming Li Chia ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Pulse Sequences

scholarly journals Universal quantum computation and leakage reduction in the 3-Qubit decoherence free subsystem

2011 ◽  
Vol 11 (11&12) ◽  
pp. 1003-1018
Author(s):  
Bryan H. Fong ◽  
Stephen M. Wandzura
Keyword(s):  
Genetic Algorithm ◽  
Angular Momentum ◽  
Closed Form ◽  
Quantum Computation ◽  
Total Angular Momentum ◽  
Pulse Sequences ◽  
Reduction Sequence ◽  
Leakage Reduction ◽  
Universal Quantum

We describe exchange-only universal quantum computation and leakage reduction in the 3-qubit decoherence free subsystem (DFS). We discuss the angular momentum structure of the DFS, the proper forms for the DFS CNOT and leakage reduction operators in the total angular momentum basis, and new exchange-only pulse sequences for the CNOT and leakage reduction operators. Our new DFS CNOT sequence requires 22 pulses in 13 time steps. The DFS leakage reduction sequence, the first explicit leakage reduction sequence of its kind, requires 30 pulses in 20 time steps. Although the search for sequences was performed numerically using a genetic algorithm, the solutions presented here are exact, with closed-form expressions.

Evaluation of pulse sequences used for magnetic resonance sialography

2001 ◽  
Vol 30 (5) ◽  
pp. 276-284 ◽  
Author(s):  
M Sakamoto ◽  
T Sasano ◽  
S Higano ◽  
S Takahashi ◽  
T Nagasaka ◽  
...  
Keyword(s):  
Magnetic Resonance ◽  
Pulse Sequences ◽  
Magnetic Resonance Sialography

The ground state energy of the ±J spin glass from the genetic algorithm

1994 ◽  
Vol 4 (9) ◽  
pp. 1281-1285 ◽  
Author(s):  
P. Sutton ◽  
D. L. Hunter ◽  
N. Jan
Keyword(s):  
Genetic Algorithm ◽  
Spin Glass ◽  
Ground State Energy ◽  
Ground State ◽  
State Energy

A Comparative Study of Ant and Genetic Algorithms in Digital Mammography

2018 ◽  
pp. 194-200
Author(s):  
J. Magelin Mary ◽  
Chitra K. ◽  
Y. Arockia Suganthi
Keyword(s):  
Genetic Algorithm ◽  
Image Processing ◽  
Medical Image ◽  
Medical Image Processing ◽  
Processing Technique ◽  
Input Image ◽  
Image Processing Technique ◽  
Computational Time ◽  
Image Mining ◽  
The Individual

Image processing technique in general, involves the application of signal processing on the input image for isolating the individual color plane of an image. It plays an important role in the image analysis and computer version. This paper compares the efficiency of two approaches in the area of finding breast cancer in medical image processing. The fundamental target is to apply an image mining in the area of medical image handling utilizing grouping guideline created by genetic algorithm. The parameter using extracted border, the border pixels are considered as population strings to genetic algorithm and Ant Colony Optimization, to find out the optimum value from the border pixels. We likewise look at cost of ACO and GA also, endeavors to discover which one gives the better solution to identify an affected area in medical image based on computational time.

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