A major challenge in high-precision light-pulse atom interferometric experiments such as tests of the weak equivalence principle is uncontrollable dependency phase on initial velocity and position atoms presence inhomogeneous gravitational fields. To overcome this limitation, mitigation strategies have been proposed, however, valid only for harmonic potentials or small branch separations more g...

The Conjugate Gradient Squared (CGS) is an iterative method for solving nonsymmetric linear systems of equations. However, during the iteration large residual norms may appear, which may lead to inaccurate approximate solutions or may even deteriorate the convergence rate. Instead of squaring the Bi-CG polynomial as in CGS, we propose to consider products of two nearby Bi-CG polynomials which l...

The reparameterization gradient has become a widely used method to obtain Monte Carlo gradients to optimize the variational objective. However, this technique does not easily apply to commonly used distributions such as beta or gamma without further approximations, and most practical applications of the reparameterization gradient fit Gaussian distributions. In this paper, we introduce the gene...

The Conjugate Gradient Squared (CGS) is a well-known and widely used iterative method for solving non-symmetric linear systems of equations. In practice the method converges fast, often twice as fast as the Bi-Conjugate Gradient (Bi-CG) method. However, during the iteration large residual norms may appear, which may lead to inaccurate approximate solutions or may even deteriorate the convergenc...

We study the properties of the generalized stochastic gradient (GSG) learning in forward-looking models. GSG algorithms are a natural and convenient way to model learning when agents allow for parameter drift or robustness to parameter uncertainty in their beliefs. The conditions for convergence of GSG learning to a rational expectations equilibrium are distinct from but related to the well-kno...

This article derives characterizations and computational algorithms for continuous general gradient descent trajectories in high-dimensional parameter spaces for statistical model selection, prediction, and classification. Examples include proportional gradient shrinkage as an extension of LASSO and LARS, threshold gradient descent with right-continuous variable selectors, threshold ridge regre...

We study the contact between nonlinearly elastic bodies by variational methods. After the formulation of the mechanical problem we provide existence results based on polyconvexity and on quasiconvexity. Then we derive the Euler-Lagrange equation as a necessary condition for minimizers. Here Clarke’s generalized gradients are the essential tool to treat the nonsmooth obstacle condition.

A strain of EScherichia coli was constructed containing a plasmid from the Clarke-Carbon collection that showed high levels of melibiose transport activity. Membranes from the plasmid-containing strain were extracted with octyl-beta-D-glucopyranoside and melibiose transport was reconstituted in liposomes. The proteoliposomes exhibited counterflow activity, as well as membrane potential and sodi...