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Free, publiclyaccessible full text available September 1, 2024

Teleporting, or jumping, is a common method of moving through virtual environments. It provides a simple user interface, but deprives users of selfmotion cues that are important to acquiring spatial knowledge. This paper examines one parameter of the teleportation interface, the teleportation or jump distance, and how that may affect spatial knowledge acquisition. We report the results of an experiment that examined the effects of two different, but fixed teleportation distances on how users could acquire knowledge of landmarks and routes. The results suggest that the teleport distance does not matter, hence teleportation as an interface is robust. However, use of teleportation resulted in significantly increased simulator sickness, a surprising result.more » « lessFree, publiclyaccessible full text available September 1, 2024

Free, publiclyaccessible full text available May 27, 2024

Plasmabased acceleration has emerged as a promising candidate as an accelerator technology for a future linear collider or a nextgeneration light source. We consider the plasma wakefield accelerator (PWFA) concept where a plasma wave wake is excited by a particle beam and a trailing beam surfs on the wake. For a linear collider, the energy transfer efficiency from the drive beam to the wake and from the wake to the trailing beam must be large, while the emittance and energy spread of the trailing bunch must be preserved. One way to simultaneously achieve this when accelerating electrons is to use longitudinally shaped bunches and nonlinear wakes. In the linear regime, there is an analytical formalism to obtain the optimal shapes. In the nonlinear regime, however, the optimal shape of the driver to maximize the energy transfer efficiency cannot be precisely obtained because currently no theory describes the wake structure and excitation process for all degrees of nonlinearity. In addition, the ion channel radius is not well defined at the front of the wake where the plasma electrons are not fully blown out by the drive beam. We present results using a novel optimization method to effectively determine a current profile for the drive and trailing beam in PWFA that provides low energy spread, low emittance, and high acceleration efficiency. We parameterize the longitudinal beam current profile as a piecewiselinear function and define optimization objectives. For the trailing beam, the algorithm converges quickly to a nearly inverse trapezoidal trailing beam current profile similar to that predicted by the ultrarelativistic limit of the nonlinear wakefield theory. For the drive beam, the beam profile found by the optimization in the nonlinear regime that maximizes the transformer ratio also resembles that predicted by linear theory. The current profiles found from the optimization method provide higher transformer ratios compared with the linear ramp predicted by the relativistic limit of the nonlinear theory.more » « lessFree, publiclyaccessible full text available May 1, 2024

The modes of Pacific decadalscale variability (PDV), traditionally defined as statistical patterns of variance, reflect to first order the ocean's integration (i.e., reddening) of atmospheric forcing that arises from both a shift and a change in strength of the climatological (timemean) atmospheric circulation. While these patterns concisely describe PDV, they do not distinguish among the key dynamical processes driving the evolution of PDV anomalies, including atmospheric and ocean teleconnections and coupled feedbacks with similar spatial structures that operate on different timescales. In this review, we synthesize past analysis using an empirical dynamical model constructed from monthly ocean surface anomalies drawn from several reanalysis products, showing that the PDV modes of variance result from two fundamental lowfrequency dynamical eigenmodes: the North Pacific–central Pacific (NPCP) and Kuroshio–Oyashio Extension (KOE) modes. Both eigenmodes highlight how twoway tropical–extratropical teleconnection dynamics are the primary mechanisms energizing and synchronizing the basinscale footprint of PDV. While the NPCP mode captures interannual to decadalscale variability, the KOE mode is linked to the basinscale expression of PDV on decadal to multidecadal timescales, including contributions from the South Pacific.more » « less

The problem of continuous inverse optimal control (over finite time horizon) is to learn the unknown cost function over the sequence of continuous control variables from expert demonstrations. In this article, we study this fundamental problem in the framework of energybased model, where the observed expert trajectories are assumed to be random samples from a probability density function defined as the exponential of the negative cost function up to a normalizing constant. The parameters of the cost function are learned by maximum likelihood via an “analysis by synthesis” scheme, which iterates (1) synthesis step: sample the synthesized trajectories from the current probability density using the Langevin dynamics via backpropagation through time, and (2) analysis step: update the model parameters based on the statistical difference between the synthesized trajectories and the observed trajectories. Given the fact that an efficient optimization algorithm is usually available for an optimal control problem, we also consider a convenient approximation of the above learning method, where we replace the sampling in the synthesis step by optimization. Moreover, to make the sampling or optimization more efficient, we propose to train the energybased model simultaneously with a topdown trajectory generator via cooperative learning, where the trajectory generator is used to fast initialize the synthesis step of the energybased model. We demonstrate the proposed methods on autonomous driving tasks, and show that they can learn suitable cost functions for optimal control.more » « less