5,784 research outputs found
Regularized Optimal Transport and the Rot Mover's Distance
This paper presents a unified framework for smooth convex regularization of
discrete optimal transport problems. In this context, the regularized optimal
transport turns out to be equivalent to a matrix nearness problem with respect
to Bregman divergences. Our framework thus naturally generalizes a previously
proposed regularization based on the Boltzmann-Shannon entropy related to the
Kullback-Leibler divergence, and solved with the Sinkhorn-Knopp algorithm. We
call the regularized optimal transport distance the rot mover's distance in
reference to the classical earth mover's distance. We develop two generic
schemes that we respectively call the alternate scaling algorithm and the
non-negative alternate scaling algorithm, to compute efficiently the
regularized optimal plans depending on whether the domain of the regularizer
lies within the non-negative orthant or not. These schemes are based on
Dykstra's algorithm with alternate Bregman projections, and further exploit the
Newton-Raphson method when applied to separable divergences. We enhance the
separable case with a sparse extension to deal with high data dimensions. We
also instantiate our proposed framework and discuss the inherent specificities
for well-known regularizers and statistical divergences in the machine learning
and information geometry communities. Finally, we demonstrate the merits of our
methods with experiments using synthetic data to illustrate the effect of
different regularizers and penalties on the solutions, as well as real-world
data for a pattern recognition application to audio scene classification
Design Automation and Design Space Exploration for Quantum Computers
A major hurdle to the deployment of quantum linear systems algorithms and
recent quantum simulation algorithms lies in the difficulty to find inexpensive
reversible circuits for arithmetic using existing hand coded methods. Motivated
by recent advances in reversible logic synthesis, we synthesize arithmetic
circuits using classical design automation flows and tools. The combination of
classical and reversible logic synthesis enables the automatic design of large
components in reversible logic starting from well-known hardware description
languages such as Verilog. As a prototype example for our approach we
automatically generate high quality networks for the reciprocal , which is
necessary for quantum linear systems algorithms.Comment: 6 pages, 1 figure, in 2017 Design, Automation & Test in Europe
Conference & Exhibition, DATE 2017, Lausanne, Switzerland, March 27-31, 201
Newton-Raphson Consensus for Distributed Convex Optimization
We address the problem of distributed uncon- strained convex optimization
under separability assumptions, i.e., the framework where each agent of a
network is endowed with a local private multidimensional convex cost, is
subject to communication constraints, and wants to collaborate to compute the
minimizer of the sum of the local costs. We propose a design methodology that
combines average consensus algorithms and separation of time-scales ideas. This
strategy is proved, under suitable hypotheses, to be globally convergent to the
true minimizer. Intuitively, the procedure lets the agents distributedly
compute and sequentially update an approximated Newton- Raphson direction by
means of suitable average consensus ratios. We show with numerical simulations
that the speed of convergence of this strategy is comparable with alternative
optimization strategies such as the Alternating Direction Method of
Multipliers. Finally, we propose some alternative strategies which trade-off
communication and computational requirements with convergence speed.Comment: 18 pages, preprint with proof
One-log call iterative solution of the Colebrook equation for flow friction based on Pade polynomials
The 80 year-old empirical Colebrook function zeta, widely used as an informal standard for hydraulic resistance, relates implicitly the unknown flow friction factor lambda, with the known Reynolds number Re and the known relative roughness of a pipe inner surface epsilon* ; lambda = zeta(Re, epsilon* ,lambda). It is based on logarithmic law in the form that captures the unknown flow friction factor l in a way that it cannot be extracted analytically. As an alternative to the explicit approximations or to the iterative procedures that require at least a few evaluations of computationally expensive logarithmic function or non-integer powers, this paper offers an accurate and computationally cheap iterative algorithm based on Pade polynomials with only one log-call in total for the whole procedure (expensive log-calls are substituted with Pade polynomials in each iteration with the exception of the first). The proposed modification is computationally less demanding compared with the standard approaches of engineering practice, but does not influence the accuracy or the number of iterations required to reach the final balanced solution.Web of Science117art. no. 182
A Sufficient Condition for Power Flow Insolvability with Applications to Voltage Stability Margins
For the nonlinear power flow problem specified with standard PQ, PV, and
slack bus equality constraints, we present a sufficient condition under which
the specified set of nonlinear algebraic equations has no solution. This
sufficient condition is constructed in a framework of an associated feasible,
convex optimization problem. The objective employed in this optimization
problem yields a measure of distance (in a parameter set) to the power flow
solution boundary. In practical terms, this distance is closely related to
quantities that previous authors have proposed as voltage stability margins. A
typical margin is expressed in terms of the parameters of system loading
(injected powers); here we additionally introduce a new margin in terms of the
parameters of regulated bus voltages.Comment: 12 pages, 7 figure
Implementing Quantum Gates by Optimal Control with Doubly Exponential Convergence
We introduce a novel algorithm for the task of coherently controlling a
quantum mechanical system to implement any chosen unitary dynamics. It performs
faster than existing state of the art methods by one to three orders of
magnitude (depending on which one we compare to), particularly for quantum
information processing purposes. This substantially enhances the ability to
both study the control capabilities of physical systems within their coherence
times, and constrain solutions for control tasks to lie within experimentally
feasible regions. Natural extensions of the algorithm are also discussed.Comment: 4+2 figures; to appear in PR
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