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It is cumbersome to find the magnitudes of vectors using the parallelogram rule or using the graphical method to perform mathematical operations like addition, subtraction, and multiplication. There are two ways to circumvent this algebraic complexity. One way is to draw the vectors to scale, as in navigation, and read approximate vector lengths and angles (directions) from the graphs. The other way is to use the method of components.
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Complex numbers, represented in Cartesian coordinates, can also be visualized as vectors. These vectors can be expressed in polar form, emphasizing their magnitude and angle. When a complex number is input into a function, the output is another complex number, highlighting the function's zero point from which the vector representation can originate.
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Construction of Binary Quantum Error-Correcting Codes from Orthogonal Array.

Shanqi Pang1, Hanxiao Xu1, Mengqian Chen1

  • 1College of Mathematics and Information Science, Henan Normal University, Xinxiang 453007, China.

Entropy (Basel, Switzerland)
|July 27, 2022
PubMed
Summary
This summary is machine-generated.

New methods using orthogonal arrays construct pure quantum error-correcting codes. These novel quantum error-correcting codes offer advantages over existing binary codes, featuring fewer terms for basis states.

Failed At:

2026-06-19T13:39:40.195843+00:00

Keywords:
k-uniform statesorthogonal arrayorthogonal partitionquantum error-correcting codes

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