Phase Factors in Singular Value Decomposition and Schmidt Decomposition
- URL: http://arxiv.org/abs/2203.12579v1
- Date: Wed, 23 Mar 2022 17:41:18 GMT
- Title: Phase Factors in Singular Value Decomposition and Schmidt Decomposition
- Authors: Chu Ryang Wie
- Abstract summary: In singular value decomposition (SVD) of a complex matrix A, the singular vectors or the eigenvectors of AAdag and AdagA are unique up to complex phase factors.
We summarize here three simple steps to consistently carry out the SVD and the Schmidt decomposition including the phase factors.
- Score: 0.0
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: In singular value decomposition (SVD) of a complex matrix A, the singular
vectors or the eigenvectors of AA{\dag} and A{\dag}A are unique up to complex
phase factors. Thus, the two unitary matrices in SVD are unique up to diagonal
matrices of phase factors, the phase-factor matrices. Also, the product of
these two phase-factor matrices, or the product of phase factors of the
corresponding singular vectors with the same singular value, is unique. In the
Schmidt decomposition, a phase-factor matrix is a phase rotation operator
acting on a subsystem alone. We summarize here three simple steps to
consistently carry out the SVD and the Schmidt decomposition including the
phase factors.
Related papers
- Efficient conversion from fermionic Gaussian states to matrix product states [48.225436651971805]
We propose a highly efficient algorithm that converts fermionic Gaussian states to matrix product states.
It can be formulated for finite-size systems without translation invariance, but becomes particularly appealing when applied to infinite systems.
The potential of our method is demonstrated by numerical calculations in two chiral spin liquids.
arXiv Detail & Related papers (2024-08-02T10:15:26Z) - Matrix decompositions in Quantum Optics: Takagi/Autonne,
Bloch-Messiah/Euler, Iwasawa, and Williamson [0.0]
We present four important matrix decompositions commonly used in quantum optics.
The first two of these decompositions are specialized versions of the singular-value decomposition.
The third factors any symplectic matrix in a unique way in terms of matrices that belong to different subgroups of the symplectic group.
arXiv Detail & Related papers (2024-03-07T15:43:17Z) - Factor Fitting, Rank Allocation, and Partitioning in Multilevel Low Rank
Matrices [43.644985364099036]
We address three problems that arise in fitting a given matrix by an MLR matrix in the Frobenius norm.
The first problem is factor fitting, where we adjust the factors of the MLR matrix.
The second is rank allocation, where we choose the ranks of the blocks in each level, subject to the total rank having a given value.
The final problem is to choose the hierarchical partition of rows and columns, along with the ranks and factors.
arXiv Detail & Related papers (2023-10-30T00:52:17Z) - Mutually-orthogonal unitary and orthogonal matrices [6.9607365816307]
We show that the minimum and maximum numbers of an unextendible maximally entangled bases within a real two-qutrit system are three and four, respectively.
As an application in quantum information theory, we show that the minimum and maximum numbers of an unextendible maximally entangled bases within a real two-qutrit system are three and four, respectively.
arXiv Detail & Related papers (2023-09-20T08:20:57Z) - Householder Projector for Unsupervised Latent Semantics Discovery [58.92485745195358]
Householder Projector helps StyleGANs to discover more disentangled and precise semantic attributes without sacrificing image fidelity.
We integrate our projector into pre-trained StyleGAN2/StyleGAN3 and evaluate the models on several benchmarks.
arXiv Detail & Related papers (2023-07-16T11:43:04Z) - Level compressibility of certain random unitary matrices [0.0]
The value of spectral form factor at the origin, called level compressibility, is an important characteristic of random spectra.
The paper is devoted to analytical calculations of this quantity for different random unitary matrices describing models with intermediate spectral statistics.
arXiv Detail & Related papers (2022-02-22T21:31:24Z) - Quantum correlations, entanglement spectrum and coherence of
two-particle reduced density matrix in the Extended Hubbard Model [62.997667081978825]
We study the ground state properties of the one-dimensional extended Hubbard model at half-filling.
In particular, in the superconducting region, we obtain that the entanglement spectrum signals a transition between a dominant singlet (SS) to triplet (TS) pairing ordering in the system.
arXiv Detail & Related papers (2021-10-29T21:02:24Z) - Identifiability in Exact Two-Layer Sparse Matrix Factorization [0.0]
Sparse matrix factorization is the problem of approximating a matrix Z by a product of L sparse factors X(L) X(L--1).
This paper focuses on identifiability issues that appear in this problem, in view of better understanding under which sparsity constraints the problem is well-posed.
arXiv Detail & Related papers (2021-10-04T07:56:37Z) - Identifiability in Exact Multilayer Sparse Matrix Factorization [0.0]
We prove that any matrix which is the product of L factors whose supports are exactly the so-called butterfly supports, admits a unique sparse factorization into L factors.
This applies in particular to the Hadamard or the discrete Fourier transform matrix of size 2L.
arXiv Detail & Related papers (2021-10-04T07:50:51Z) - Non-PSD Matrix Sketching with Applications to Regression and
Optimization [56.730993511802865]
We present dimensionality reduction methods for non-PSD and square-roots" matrices.
We show how these techniques can be used for multiple downstream tasks.
arXiv Detail & Related papers (2021-06-16T04:07:48Z) - Granular Computing: An Augmented Scheme of Degranulation Through a
Modified Partition Matrix [86.89353217469754]
Information granules forming an abstract and efficient characterization of large volumes of numeric data have been considered as the fundamental constructs of Granular Computing.
Previous studies have shown that there is a relationship between the reconstruction error and the performance of the granulation process.
To enhance the quality of degranulation, in this study, we develop an augmented scheme through modifying the partition matrix.
arXiv Detail & Related papers (2020-04-03T03:20:09Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.