Carnegie Mellon University

About: Carnegie Mellon University is a education organization based out in Pittsburgh, Pennsylvania, United States. It is known for research contribution in the topics: Computer science & Robot. The organization has 36317 authors who have published 104359 publications receiving 5975734 citations. The organization is also known as: CMU & Carnegie Mellon.

Optical generation of excitonic valley coherence in monolayer WSe2

Abstract: As a consequence of degeneracies arising from crystal symmetries, it is possible for electron states at band-edges ('valleys') to have additional spin-like quantum numbers. An important question is whether coherent manipulation can be performed on such valley pseudospins, analogous to that implemented using true spin, in the quest for quantum technologies. Here, we show that valley coherence can be generated and detected. Because excitons in a single valley emit circularly polarized photons, linear polarization can only be generated through recombination of an exciton in a coherent superposition of the two valley states. Using monolayer semiconductor WSe2 devices, we first establish the circularly polarized optical selection rules for addressing individual valley excitons and trions. We then demonstrate coherence between valley excitons through the observation of linearly polarized luminescence, whose orientation coincides with that of the linearly polarized excitation, for any given polarization angle. In contrast, the corresponding photoluminescence from trions is not observed to be linearly polarized, consistent with the expectation that the emitted photon polarization is entangled with valley pseudospin. The ability to address coherence, in addition to valley polarization, is a step forward towards achieving quantum manipulation of the valley index necessary for coherent valleytronics.

Sonar-based real-world mapping and navigation

Abstract: A sonar-based mapping and navigation system developed for an autonomous mobile robot operating in unknown and unstructured environments is described. The system uses sonar range data to build a multileveled description of the robot's surroundings. Sonar readings are interpreted using probability profiles to determine empty and occupied areas. Range measurements from multiple points of view are integrated into a sensor-level sonar map, using a robust method that combines the sensor information in such a way as to cope with uncertainties and errors in the data. The resulting two-dimensional maps are used for path planning and navigation. From these sonar maps, multiple representations are developed for various kinds of problem-solving activities. Several dimensions of representation are defined: the abstraction axis, the geographical axis, and the resolution axis. The sonar mapping procedures have been implemented as part of an autonomous mobile robot navigation system called Dolphin. The major modules of this system are described and related to the various mapping representations used. Results from actual runs are presented, and further research is mentioned. The system is also situated within the wider context of developing an advanced software architecture for autonomous mobile robots.

FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence

Abstract: Semi-supervised learning (SSL) provides an effective means of leveraging unlabeled data to improve a model's performance. In this paper, we demonstrate the power of a simple combination of two common SSL methods: consistency regularization and pseudo-labeling. Our algorithm, FixMatch, first generates pseudo-labels using the model's predictions on weakly-augmented unlabeled images. For a given image, the pseudo-label is only retained if the model produces a high-confidence prediction. The model is then trained to predict the pseudo-label when fed a strongly-augmented version of the same image. Despite its simplicity, we show that FixMatch achieves state-of-the-art performance across a variety of standard semi-supervised learning benchmarks, including 94.93% accuracy on CIFAR-10 with 250 labels and 88.61% accuracy with 40 -- just 4 labels per class. Since FixMatch bears many similarities to existing SSL methods that achieve worse performance, we carry out an extensive ablation study to tease apart the experimental factors that are most important to FixMatch's success. We make our code available at this https URL.

Environmental transformations of silver nanoparticles: impact on stability and toxicity.

Abstract: Silver nanoparticles (Ag-NPs) readily transform in the environment, which modifies their properties and alters their transport, fate, and toxicity. It is essential to consider such transformations when assessing the potential environmental impact of Ag-NPs. This review discusses the major transformation processes of Ag-NPs in various aqueous environments, particularly transformations of the metallic Ag cores caused by reactions with (in)organic ligands, and the effects of such transformations on physical and chemical stability and toxicity. Thermodynamic arguments are used to predict what forms of oxidized silver will predominate in various environmental scenarios. Silver binds strongly to sulfur (both organic and inorganic) in natural systems (fresh and sea waters) as well as in wastewater treatment plants, where most Ag-NPs are expected to be concentrated and then released. Sulfidation of Ag-NPs results in a significant decrease in their toxicity due to the lower solubility of silver sulfide, potentiall...