A Pathwise Ergodic Theorem for Quantum Trajectories

If the time evolution of an open quantum system approaches equilibrium in the time mean, then on any single trajectory of any of its unravelings the time averaged state approaches the same equilibrium state with probability 1. In the case of multiple equilibrium states the quantum trajectory converges in the mean to a random choice from these states.Comment: 8 page

Homogeneous Open Quantum Random Walks on a lattice

We study Open Quantum Random Walks for which the underlying graph is a lattice, and the generators of the walk are translation-invariant. We consider the quantum trajectory associated with the OQRW, which is described by a position process and a state process. We obtain a central limit theorem and a large deviation principle for the position process, and an ergodic result for the state process. We study in detail the case of homogeneous OQRWs on a lattice, with internal space $h={\mathbb C}^2$

Characterization and Vector Competence Studies of Chikungunya Virus Lacking Repetitive Motifs in the 3′ Untranslated Region of the Genome

Using reverse genetics, we analyzed a chikungunya virus (CHIKV) isolate of the Indian Ocean lineage lacking direct repeat (DR) elements in the 3′ untranslated region, namely DR1a and DR2a. While this deletion mutant CHIKV-∆DR exhibited growth characteristics comparable to the wild-type virus in Baby Hamster Kidney cells, replication of the mutant was reduced in Aedes albopictus C6/36 and Ae. aegypti Aag2 cells. Using oral and intrathoracic infection of mosquitoes, viral infectivity, dissemination, and transmission of CHIKV-∆DR could be shown for the well-known CHIKV vectors Ae. aegypti and Ae. albopictus. Oral infection of Ae. vexans and Culex pipiens mosquitoes with mutant or wild-type CHIKV showed very limited infectivity. Dissemination, transmission, and transmission efficiencies as determined via viral RNA in the saliva were slightly higher in Ae. vexans for the wild-type virus than for CHIKV-∆DR. However, both Ae. vexans and Cx. pipiens allowed efficient viral replication after intrathoracic injection confirming that the midgut barrier is an important determinant for the compromised infectivity after oral infection. Transmission efficiencies were neither significantly different between Ae. vexans and Cx. pipiens nor between wild-type and CHIKV-∆DR. With a combined transmission efficiency of 6%, both Ae. vexans and Cx. pipiens might serve as potential vectors in temperate regions

Evidence for a Pathophysiological Role of Keratinocyte-Derived Type III Interferon (IFNλ) in Cutaneous Lupus Erythematosus

Type I IFNs (IFNα/β) have been shown to have a central role in the pathophysiology of lupus erythematosus (LE). The recently discovered type III IFNs (IFNλ1/IL29, IFNλ2/IL28a, IFNλ3/IL28b) share several functional similarities with type I IFNs, particularly in antiviral immunity. As IFNλs act primarily on epithelial cells, we investigated whether type III IFNs might also have a role in the pathogenesis of cutaneous LE (CLE). Our investigations demonstrate that IFNλ and the IFNλ receptor were strongly expressed in the epidermis of CLE skin lesions and related autoimmune diseases (lichen planus and dermatomyositis). Significantly enhanced IFNλ1 could be measured in the serum of CLE patients with active skin lesions. Functional analyses revealed that human keratinocytes are able to produce high levels of IFNλ1 but only low amounts of IFNα/β/γ in response to immunostimulatory nuclear acids, suggesting that IFNλ is a major IFN produced by these cells. Exposure of human keratinocytes to IFNλ1 induced the expression of several proinflammatory cytokines, including CXCL9 (CXC-motiv ligand 9), which drive the recruitment of immune cells and are associated with the formation of CLE skin lesions. Our results provide evidence for a role of type III IFNs in not only antiviral immunity but also autoimmune diseases of the skin

Noise models for superoperators in the chord representation

We study many-qubit generalizations of quantum noise channels that can be written as an incoherent sum of translations in phase space. Physical description in terms of the spectral properties of the superoperator and the action in phase space are provided. A very natural description of decoherence leading to a preferred basis is achieved with diffusion along a phase space line. The numerical advantages of using the chord representation are illustrated in the case of coarse-graining noise.Comment: 8 pages, 5 .ps figures (RevTeX4). Submitted to Phys. Rev. A. minor changes made, according to referee suggestion

Unital Quantum Channels - Convex Structure and Revivals of Birkhoff's Theorem

The set of doubly-stochastic quantum channels and its subset of mixtures of unitaries are investigated. We provide a detailed analysis of their structure together with computable criteria for the separation of the two sets. When applied to O(d)-covariant channels this leads to a complete characterization and reveals a remarkable feature: instances of channels which are not in the convex hull of unitaries can return to it when either taking finitely many copies of them or supplementing with a completely depolarizing channel. In these scenarios this implies that a channel whose noise initially resists any environment-assisted attempt of correction can become perfectly correctable.Comment: 31 page

PathGAN: visual scanpath prediction with generative adversarial networks

“This is a post-peer-review, pre-copyedit version of an article published in: Computer Vision – ECCV 2018 Workshops. The final authenticated version is available online at: http://dx.doi.org/10.1007/978-3-030-11021-5_25”.We introduce PathGAN, a deep neural network for visual scanpath prediction trained on adversarial examples. A visual scanpath is defined as the sequence of fixation points over an image defined by a human observer with its gaze. PathGAN is composed of two parts, the generator and the discriminator. Both parts extract features from images using off-the-shelf networks, and train recurrent layers to generate or discriminate scanpaths accordingly. In scanpath prediction, the stochastic nature of the data makes it very difficult to generate realistic predictions using supervised learning strategies, but we adopt adversarial training as a suitable alternative. Our experiments prove how PathGAN improves the state of the art of visual scanpath prediction on the iSUN and Salient360! datasets.Peer ReviewedPostprint (author's final draft

The Free Quon Gas Suffers Gibbs' Paradox

We consider the Statistical Mechanics of systems of particles satisfying the $q$-commutation relations recently proposed by Greenberg and others. We show that although the commutation relations approach Bose (resp.\ Fermi) relations for $q\to1$ (resp.\ $q\to-1$), the partition functions of free gases are independent of $q$ in the range $-1<q<1$. The partition functions exhibit Gibbs' Paradox in the same way as a classical gas without a correction factor $1/N!$ for the statistical weight of the $N$-particle phase space, i.e.\ the Statistical Mechanics does not describe a material for which entropy, free energy, and particle number are extensive thermodynamical quantities.Comment: number-of-pages, LaTeX with REVTE

Saliency Benchmarking Made Easy: Separating Models, Maps and Metrics

Dozens of new models on fixation prediction are published every year and compared on open benchmarks such as MIT300 and LSUN. However, progress in the field can be difficult to judge because models are compared using a variety of inconsistent metrics. Here we show that no single saliency map can perform well under all metrics. Instead, we propose a principled approach to solve the benchmarking problem by separating the notions of saliency models, maps and metrics. Inspired by Bayesian decision theory, we define a saliency model to be a probabilistic model of fixation density prediction and a saliency map to be a metric-specific prediction derived from the model density which maximizes the expected performance on that metric given the model density. We derive these optimal saliency maps for the most commonly used saliency metrics (AUC, sAUC, NSS, CC, SIM, KL-Div) and show that they can be computed analytically or approximated with high precision. We show that this leads to consistent rankings in all metrics and avoids the penalties of using one saliency map for all metrics. Our method allows researchers to have their model compete on many different metrics with state-of-the-art in those metrics: "good" models will perform well in all metrics.Comment: published at ECCV 201