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- W2018657834 abstract "Singular Value Decomposition (SVD) is one of the most useful techniques for analyzing data in linear algebra. SVD decomposes a rectangular real or complex matrix into two orthogonal matrices and one diagonal matrix. The proposed Quantum-SVD algorithm interpolates the non-uniform angles in the Fourier domain. The error of the Quantum-SVD approach is some orders lower than the error given by ordinary Quantum Fourier Transformation. Our Quantum-SVD algorithm is a fundamentally novel approach for the computation of the Quantum Fourier Transformation (QFT) of non-uniform states. The presented Quantum-SVD algorithm is based on the singular value decomposition mechanism, and the computation of Quantum Fourier Transformation of non-uniform angles of a quantum system. The Quantum-SVD approach provides advantages in terms of computational structure, being based on QFT and multiplications." @default.
- W2018657834 created "2016-06-24" @default.
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- W2018657834 date "2010-10-01" @default.
- W2018657834 modified "2023-09-27" @default.
- W2018657834 title "QUANTUM SINGULAR VALUE DECOMPOSITION BASED APPROXIMATION ALGORITHM" @default.
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- W2018657834 doi "https://doi.org/10.1142/s0218126610006797" @default.
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