995 research outputs found
Generalized Finite Algorithms for Constructing Hermitian Matrices with Prescribed Diagonal and Spectrum
In this paper, we present new algorithms that can replace the diagonal entries of a Hermitian matrix by any set of diagonal entries that majorize the original set without altering the eigenvalues of the matrix. They perform this feat by applying a sequence of (N-1) or fewer plane rotations, where N is the dimension of the matrix. Both the Bendel-Mickey and the Chan-Li algorithms are special cases of the proposed procedures. Using the fact that a positive semidefinite matrix can always be factored as \mtx{X^\adj X}, we also provide more efficient versions of the algorithms that can directly construct factors with specified singular values and column norms. We conclude with some open problems related to the construction of Hermitian matrices with joint diagonal and spectral properties
Finite-step algorithms for constructing optimal CDMA signature sequences
A description of optimal sequences for direct-spread code-division multiple access (DS-CDMA) is a byproduct of recent characterizations of the sum capacity. This paper restates the sequence design problem as an inverse singular value problem and shows that the problem can be solved with finite-step algorithms from matrix theory. It proposes a new one-sided algorithm that is numerically stable and faster than previous methods
Designing structured tight frames via an alternating projection method
Tight frames, also known as general Welch-bound- equality sequences, generalize orthonormal systems. Numerous applications - including communications, coding, and sparse approximation- require finite-dimensional tight frames that possess additional structural properties. This paper proposes an alternating projection method that is versatile enough to solve a huge class of inverse eigenvalue problems (IEPs), which includes the frame design problem. To apply this method, one needs only to solve a matrix nearness problem that arises naturally from the design specifications. Therefore, it is the fast and easy to develop versions of the algorithm that target new design problems. Alternating projection will often succeed even if algebraic constructions are unavailable. To demonstrate that alternating projection is an effective tool for frame design, the paper studies some important structural properties in detail. First, it addresses the most basic design problem: constructing tight frames with prescribed vector norms. Then, it discusses equiangular tight frames, which are natural dictionaries for sparse approximation. Finally, it examines tight frames whose individual vectors have low peak-to-average-power ratio (PAR), which is a valuable property for code-division multiple-access (CDMA) applications. Numerical experiments show that the proposed algorithm succeeds in each of these three cases. The appendices investigate the convergence properties of the algorithm
Diagonal unitary entangling gates and contradiagonal quantum states
Nonlocal properties of an ensemble of diagonal random unitary matrices of
order are investigated. The average Schmidt strength of such a bipartite
diagonal quantum gate is shown to scale as , in contrast to the behavior characteristic to random unitary gates. Entangling power of a
diagonal gate is related to the von Neumann entropy of an auxiliary quantum
state , where the square matrix is obtained by
reshaping the vector of diagonal elements of of length into a square
matrix of order . This fact provides a motivation to study the ensemble of
non-hermitian unimodular matrices , with all entries of the same modulus and
random phases and the ensemble of quantum states , such that all their
diagonal entries are equal to . Such a state is contradiagonal with
respect to the computational basis, in sense that among all unitary equivalent
states it maximizes the entropy copied to the environment due to the coarse
graining process. The first four moments of the squared singular values of the
unimodular ensemble are derived, based on which we conjecture a connection to a
recently studied combinatorial object called the "Borel triangle". This allows
us to find exactly the mean von Neumann entropy for random phase density
matrices and the average entanglement for the corresponding ensemble of
bipartite pure states.Comment: 14 pages, 6 figure
Preconditioned Locally Harmonic Residual Method for Computing Interior Eigenpairs of Certain Classes of Hermitian Matrices
We propose a Preconditioned Locally Harmonic Residual (PLHR) method for
computing several interior eigenpairs of a generalized Hermitian eigenvalue
problem, without traditional spectral transformations, matrix factorizations,
or inversions. PLHR is based on a short-term recurrence, easily extended to a
block form, computing eigenpairs simultaneously. PLHR can take advantage of
Hermitian positive definite preconditioning, e.g., based on an approximate
inverse of an absolute value of a shifted matrix, introduced in [SISC, 35
(2013), pp. A696-A718]. Our numerical experiments demonstrate that PLHR is
efficient and robust for certain classes of large-scale interior eigenvalue
problems, involving Laplacian and Hamiltonian operators, especially if memory
requirements are tight
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