The ratchet effect in a two lag setting and the mitigating influence of yardstick competition

In order to increase efficiency in the provision of power distribution networks, the German regulator Bundesnetzagentur plans to implement revenue cap regulation together with yardstick competition. Revenue cap regulation could bear the ratchet effect: cost minimization need not to be optimal for the operator who anticipates that his revenue cap will become adjusted according to his cost performance. The regulator could extract all the rent by lowering an operator's revenue cap to the level of costs he revealed to be possible for him to reach. The ratchet effect could be mitigated by yardstick competition at which the level of revenues that is allowed to one operator is tied to the performance of others that are comparable to him. One will only be allowed to accumulate revenues that recover the least cost level that has been adopted within the group of comparable decision makers. In a setting of two sequential regulatory lags, this paper examines the occurence of the ratchet effect and the mitigating influence that yardstick competition has on it.ratchet effect, yardstick competition, regulation

Disorder and interference: localization phenomena

The specific problem we address in these lectures is the problem of transport and localization in disordered systems, when interference is present, as characteristic for waves, with a focus on realizations with ultracold atoms.Comment: Notes of a lecture delivered at the Les Houches School of Physics on "Ultracold gases and quantum information" 2009 in Singapore. v3: corrected mistakes, improved script for numerics, Chapter 9 in "Les Houches 2009 - Session XCI: Ultracold Gases and Quantum Information" edited by C. Miniatura et al. (Oxford University Press, 2011

The Missing Data Encoder: Cross-Channel Image Completion\\with Hide-And-Seek Adversarial Network

Image completion is the problem of generating whole images from fragments only. It encompasses inpainting (generating a patch given its surrounding), reverse inpainting/extrapolation (generating the periphery given the central patch) as well as colorization (generating one or several channels given other ones). In this paper, we employ a deep network to perform image completion, with adversarial training as well as perceptual and completion losses, and call it the ``missing data encoder'' (MDE). We consider several configurations based on how the seed fragments are chosen. We show that training MDE for ``random extrapolation and colorization'' (MDE-REC), i.e. using random channel-independent fragments, allows a better capture of the image semantics and geometry. MDE training makes use of a novel ``hide-and-seek'' adversarial loss, where the discriminator seeks the original non-masked regions, while the generator tries to hide them. We validate our models both qualitatively and quantitatively on several datasets, showing their interest for image completion, unsupervised representation learning as well as face occlusion handling

The ratchet effect in a two lag setting and the mitigating influence of yardstick competition

In order to increase efficiency in the provision of power distribution networks, the German regulator Bundesnetzagentur plans to implement revenue cap regulation together with yardstick competition. Revenue cap regulation could bear the ratchet effect: cost minimization need not to be optimal for the operator who anticipates that his revenue cap will become adjusted according to his cost performance. The regulator could extract all the rent by lowering an operator’s revenue cap to the level of costs he revealed to be possible for him to reach. The ratchet effect could be mitigated by yardstick competition at which the level of revenues that is allowed to one operator is tied to the performance of others that are comparable to him. One will only be allowed to accumulate revenues that recover the least cost level that has been adopted within the group of comparable decision makers. In a setting of two sequential regulatory lags, this paper examines the occurence of the ratchet effect and the mitigating influence that yardstick competition has on it.ratchet effect, yardstick competition, regulation

Maxmin convolutional neural networks for image classification

Convolutional neural networks (CNN) are widely used in computer vision, especially in image classification. However, the way in which information and invariance properties are encoded through in deep CNN architectures is still an open question. In this paper, we propose to modify the standard convo- lutional block of CNN in order to transfer more information layer after layer while keeping some invariance within the net- work. Our main idea is to exploit both positive and negative high scores obtained in the convolution maps. This behav- ior is obtained by modifying the traditional activation func- tion step before pooling. We are doubling the maps with spe- cific activations functions, called MaxMin strategy, in order to achieve our pipeline. Extensive experiments on two classical datasets, MNIST and CIFAR-10, show that our deep MaxMin convolutional net outperforms standard CNN

Quantum and Classical Superballistic Transport in a Relativistic Kicked-Rotor System

As an unusual type of anomalous diffusion behavior, superballistic transport is not well known but has been experimentally simulated recently. Quantum superballistic transport models to date are mainly based on connected sublattices which are constructed to have different properties. In this work, we show that both quantum and classical superballistic transport in the momentum space can occur in a simple periodically driven Hamiltonian system, namely, a relativistic kicked-rotor system with a nonzero mass term. The nonzero mass term essentially realizes a junction-like scenario: regimes with low or high momentum values have different dispersion relations and hence different transport properties. It is further shown that the quantum and classical superballistic transport should occur under much different choices of the system parameters. The results are of interest to studies of anomalous transport, quantum and classical chaos, and the issue of quantum-classical correspondence.Comment: 10 pages, 8 figure