7,444 research outputs found
A randomized Kaczmarz algorithm with exponential convergence
The Kaczmarz method for solving linear systems of equations is an iterative
algorithm that has found many applications ranging from computer tomography to
digital signal processing. Despite the popularity of this method, useful
theoretical estimates for its rate of convergence are still scarce. We
introduce a randomized version of the Kaczmarz method for consistent,
overdetermined linear systems and we prove that it converges with expected
exponential rate. Furthermore, this is the first solver whose rate does not
depend on the number of equations in the system. The solver does not even need
to know the whole system, but only a small random part of it. It thus
outperforms all previously known methods on general extremely overdetermined
systems. Even for moderately overdetermined systems, numerical simulations as
well as theoretical analysis reveal that our algorithm can converge faster than
the celebrated conjugate gradient algorithm. Furthermore, our theory and
numerical simulations confirm a prediction of Feichtinger et al. in the context
of reconstructing bandlimited functions from nonuniform sampling
Variational Matrix Product Ansatz for Nonuniform Dynamics in the Thermodynamic Limit
We describe how to implement the time-dependent variational principle for
matrix product states in the thermodynamic limit for nonuniform lattice
systems. This is achieved by confining the nonuniformity to a (dynamically
growable) finite region with fixed boundary conditions. The suppression of
unphysical quasiparticle reflections from the boundary of the nonuniform region
is also discussed. Using this algorithm we study the dynamics of localized
excitations in infinite systems, which we illustrate in the case of the spin-1
anti-ferromagnetic Heisenberg model and the model.Comment: 8 pages, 5 figures, tensor network diagrams. Code available at
http://amilsted.github.io/evoMPS
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