A concentrator for static magnetic field

We propose a compact passive device as a super-concentrator to create an extremely high uniform static magnetic field over 50T in a large two-dimensional free space from a weak background magnetic field. Such an amazing thing becomes possible for the first time, thanks to space-folded transformation and metamaterials for static magnetic fields. Finite element method (FEM) is utilized to verify the performance of the proposed device

Transforming magnets

Based on the form-invariant of Maxwell's equations under coordinate transformations, we extend the theory of transformation optics to transformation magneto-statics, which can design magnets through coordinate transformations. Some novel DC magnetic field illusions created by magnets (e.g. shirking magnets, cancelling magnets and overlapping magnets) are designed and verified by numerical simulations. Our research will open a new door to designing magnets and controlling DC magnetic fields

A potential approach to solutions for set games

Concerning the solution theory for set games, the paper introduces a new solution by allocating, to any player, the items (taken from an universe) that are attainable for the player, but can not be blocked (by any coalition not containing the player). The resulting value turns out to be an utmost important concept for set games to characterize the family of set game solutions that possess a so-called potential representation (similar to the potential approaches applied in both physics and cooperative game theory). An axiomatization of the new value, called Driessen--Sun value, is given by three properties, namely one type of an efficiency property, the substitution property and one type of a monotonocity property

Observing collapse in two colliding dipolar Bose-Einstein condensates

We study the collision of two Bose-Einstein condensates with pure dipolar interaction. A stationary pure dipolar condensate is known to be stable when the atom number is below a critical value. However, collapse can occur during the collision between two condensates due to local density fluctuations even if the total atom number is only a fraction of the critical value. Using full three-dimensional numerical simulations, we observe the collapse induced by local density fluctuations. For the purpose of future experiments, we present the time dependence of the density distribution, energy per particle and the maximal density of the condensate. We also discuss the collapse time as a function of the relative phase between the two condensates.Comment: 6 pages, 7 figure

Evaluating methods for controlling depth perception in stereoscopic cinematography.

Existing stereoscopic imaging algorithms can create static stereoscopic images with perceived depth control function to ensure a compelling 3D viewing experience without visual discomfort. However, current algorithms do not normally support standard Cinematic Storytelling techniques. These techniques, such as object movement, camera motion, and zooming, can result in dynamic scene depth change within and between a series of frames (shots) in stereoscopic cinematography. In this study, we empirically evaluate the following three types of stereoscopic imaging approaches that aim to address this problem. (1) Real-Eye Configuration: set camera separation equal to the nominal human eye interpupillary distance. The perceived depth on the display is identical to the scene depth without any distortion. (2) Mapping Algorithm: map the scene depth to a predefined range on the display to avoid excessive perceived depth. A new method that dynamically adjusts the depth mapping from scene space to display space is presented in addition to an existing fixed depth mapping method. (3) Depth of Field Simulation: apply Depth of Field (DOF) blur effect to stereoscopic images. Only objects that are inside the DOF are viewed in full sharpness. Objects that are far away from the focus plane are blurred. We performed a human-based trial using the ITU-R BT.500-11 Recommendation to compare the depth quality of stereoscopic video sequences generated by the above-mentioned imaging methods. Our results indicate that viewers' practical 3D viewing volumes are different for individual stereoscopic displays and viewers can cope with much larger perceived depth range in viewing stereoscopic cinematography in comparison to static stereoscopic images. Our new dynamic depth mapping method does have an advantage over the fixed depth mapping method in controlling stereo depth perception. The DOF blur effect does not provide the expected improvement for perceived depth quality control in 3D cinematography. We anticipate the results will be of particular interest to 3D filmmaking and real time computer games

Dynamics of a two-species Bose-Einstein condensate in a double well

We study the dynamics of a two-species Bose-Einstein condensate in a double well. Such a system is characterized by the intraspecies and interspecies s-wave scattering as well as the Josephson tunneling between the two wells and the population transfer between the two species. We investigate the dynamics for some interesting regimes and present numerical results to support our conclusions. In the case of vanishing intraspecies scattering lengths and a weak interspecies scattering length, we find collapses and revivals in the population dynamics. A possible experimental implementation of our proposal is briefly discussed.Comment: 7 pages, 5 figure

Millimeter Wave MIMO Channel Estimation Based on Adaptive Compressed Sensing

Multiple-input multiple-output (MIMO) systems are well suited for millimeter-wave (mmWave) wireless communications where large antenna arrays can be integrated in small form factors due to tiny wavelengths, thereby providing high array gains while supporting spatial multiplexing, beamforming, or antenna diversity. It has been shown that mmWave channels exhibit sparsity due to the limited number of dominant propagation paths, thus compressed sensing techniques can be leveraged to conduct channel estimation at mmWave frequencies. This paper presents a novel approach of constructing beamforming dictionary matrices for sparse channel estimation using the continuous basis pursuit (CBP) concept, and proposes two novel low-complexity algorithms to exploit channel sparsity for adaptively estimating multipath channel parameters in mmWave channels. We verify the performance of the proposed CBP-based beamforming dictionary and the two algorithms using a simulator built upon a three-dimensional mmWave statistical spatial channel model, NYUSIM, that is based on real-world propagation measurements. Simulation results show that the CBP-based dictionary offers substantially higher estimation accuracy and greater spectral efficiency than the grid-based counterpart introduced by previous researchers, and the algorithms proposed here render better performance but require less computational effort compared with existing algorithms.Comment: 7 pages, 5 figures, in 2017 IEEE International Conference on Communications Workshop (ICCW), Paris, May 201

A uniform approach to semi-marginalistic values for set games

Concerning the solution theory for set games, the paper focuses on a family of solutions, each of which allocates to any player some type of marginalistic contribution with respect to any coalition containing the player. Here the marginalistic contribution may be interpreted as an individual one, or a coalitionally one. For any value of the relevant family, an axiomatization is given by three properties, namely one type of an efficiency property, the substitution property and one type of a monotonocity property. We present two proof techniques, each of which is based on the decomposition of any arbitrary set game into a union of either simple set games or elementary set games, the solutions of which are much easier to determine. A simple respectively elementary set game is associated with an arbitrary, but fixed item of the universe respectively coalition

Multi-view Regularized Gaussian Processes

Gaussian processes (GPs) have been proven to be powerful tools in various areas of machine learning. However, there are very few applications of GPs in the scenario of multi-view learning. In this paper, we present a new GP model for multi-view learning. Unlike existing methods, it combines multiple views by regularizing marginal likelihood with the consistency among the posterior distributions of latent functions from different views. Moreover, we give a general point selection scheme for multi-view learning and improve the proposed model by this criterion. Experimental results on multiple real world data sets have verified the effectiveness of the proposed model and witnessed the performance improvement through employing this novel point selection scheme