Quantum Cloning, Bell's Inequality and Teleportation

We analyze a possibility of using the two qubit output state from Buzek-Hillery quantum copying machine (not necessarily universal quantum cloning machine) as a teleportation channel. We show that there is a range of values of the machine parameter $\xi$ for which the two qubit output state is entangled and violates Bell-CHSH inequality and for a different range it remains entangled but does not violate Bell-CHSH inequality. Further we observe that for certain values of the machine parameter the two-qubit mixed state can be used as a teleportation channel. The use of the output state from the Buzek-Hillery cloning machine as a teleportation channel provides an additional appeal to the cloning machine and motivation of our present work.Comment: 7 pages and no figures, Accepted in Journal of Physics

Designing an experience sampling method for smartphone based emotion detection

Smartphones provide the capability to perform in-situ sampling of human behavior using Experience Sampling Method (ESM). Designing an ESM schedule involves probing the user repeatedly at suitable moments to collect self-reports. Timely probe generation to collect high fidelity user responses while keeping probing rate low is challenging. In mobile-based ESM, timeliness of the probe is also impacted by user's availability to respond to self-report request. Thus,

An HST/COS legacy survey of high-velocity ultraviolet absorption in the Milky Way's circumgalactic medium and the Local Group

To characterize the absorption properties of this circumgalactic medium (CGM) and its relation to the LG we present the so-far largest survey of metal absorption in Galactic high-velocity clouds (HVCs) using archival ultraviolet (UV) spectra of extragalactic background sources. The UV data are obtained with the Cosmic Origins Spectrograph (COS) onboard the Hubble Space Telescope (HST) and are supplemented by 21 cm radio observations of neutral hydrogen. Along 270 sightlines we measure metal absorption in the lines of SiII, SiIII, CII, and CIV and associated HI 21 cm emission in HVCs in the velocity range |v_LSR|=100-500 km s^-1. With this unprecedented large HVC sample we were able to improve the statistics on HVC covering fractions, ionization conditions, small-scale structure, CGM mass, and inflow rate. For the first time, we determine robustly the angular two point correlation function of the high-velocity absorbers, systematically analyze antipodal sightlines on the celestial sphere, and compare the absorption characteristics with that of Damped Lyman alpha absorbers (DLAs) and constrained cosmological simulations of the LG. Our study demonstrates that the Milky Way CGM contains sufficient gaseous material to maintain the Galactic star-formation rate at its current level. We show that the CGM is composed of discrete gaseous structures that exhibit a large-scale kinematics together with small-scale variations in physical conditions. The Magellanic Stream clearly dominates both the cross section and mass flow of high-velocity gas in the Milky Way's CGM. The possible presence of high-velocity LG gas underlines the important role of the local cosmological environment in the large-scale gas-circulation processes in and around the Milky Way (abridged).Comment: 37 pages, 25 figures, 8 tables, accepted for publication in A&

Photon & Axion Oscillation In a Magnetized Medium: A Covariant Treatment

Pseudoscalar particles, with almost zero mass and very weak coupling to the visible matter, arise in many extensions of the standard model of particle physics. Their mixing with photons in the presence of an external magnetic field leads to many interesting astrophysical and cosmological consequences. This mixing depends on the medium properties, the momentum of the photon and the background magnetic field. Here we give a general treatment of pseudoscalar-photon oscillations in a background magnetic field, taking the Faraday term into account. We give predictions valid in all regimes, under the assumption that the frequency of the wave is much higher than the plasma frequency of the medium. At sufficiently high frequencies, the Faraday effect is negligible and we reproduce the standard pseudoscalar-photon mixing phenomenon. However at low frequencies, where Faraday effect is important, the mixing formulae are considerably modified. We explicitly compute the contribution due to the longitudinal mode of the photon and show that it is negligible.Comment: 16 pages, no figure

Impact of experience sampling methods on tap pattern based emotion recognition

Smartphone based emotion recognition uses predictive modeling to recognize user's mental states. In predictive modeling, determining ground truth plays a crucial role in labeling and training the model. Experience Sampling Method (ESM) is widely used in behavioral science to gather user responses about mental states. Smartphones equipped with sensors provide new avenues to design Experience Sampling Methods. Sensors provide multiple contexts that can be used to trigger collection of user responses. However, subsampling of sensor data can bias the inference drawn from trigger based ESM. We investigate whether continuous sensor data simplify the design of ESM. We use the typing pattern of users on smartphone as the context that can trigger response collection. We compare the context based and time based ESM designs to determine the impact of ESM strategies on emotion modeling. The results indicate how different ESM designs compare against each other

Emotion detection from touch interactions during text entry on smartphones

There are different modes of interaction with a software keyboard on a smartphone, such as typing and swyping. Patterns of such touch interactions on a keyboard may reflect emotions of a user. Since users may switch between different touch modalities while using a keyboard, therefore, automatic detection of emotion from touch patterns must consider both modalities in combination to detect the pattern. In this paper, we focus on identifying different features of touch interactions with a smartphone keyboard that lead to a personalized model for inferring user emotion. Since distinguishing typing and swyping activity is important to record the correct features, we designed a technique to correctly identify the modality. The ground truth labels for user emotion are collected directly from the user by periodically collecting self-reports. We jointly model typing and swyping features and correlate them with user provided self-reports to build a personalized machine learning model, which detects four emotion states (happy, sad, stressed, relaxed). We combine these design choices into an Android application TouchSense and evaluate the same in a 3-week in-the-wild study involving 22 participants. Our key evaluation results and post-study participant assessment demonstrate that it is possible to predict these emotion states with an average accuracy (AUCROC) of 73% (std dev. 6%, maximum 87%) combining these two touch interactions only

Smart-phone based spatio-temporal sensing for annotated transit map generation

City transit maps are one of the important resources for public navigation in today's digital world. However, the availability of transit maps for many developing countries is very limited, primarily due to the various socio-economic factors that drive the private operated and partially regulated transport services. Public transports at these cities are marred with many factors such as uncoordinated waiting time at bus stoppages, crowding in the bus, sporadic road conditions etc., which also need to be annotated so that commuters can take informed decision. Interestingly, many of these factors are spatio-temporal in nature. In this paper, we develop CityMap, a system to automatically extract transit routes along with their eccentricities from spatio-temporal crowdsensed data collected via commuters' smart-phones. We apply a learning based methodology coupled with a feature selection mechanism to filter out the necessary information from raw smart-phone sensor data with minimal user engagement and drain of batt

Does emotion influence the use of auto-suggest during smartphone typing?

Typing based interfaces are common across many mobile applications, especially messaging apps. To reduce the difficulty of typing using keyboard applications on smartphones, smartwatches with restricted space, several techniques, such as auto-complete, auto-suggest, are implemented. Although helpful, these techniques do add more cognitive load on the user. Hence beyond the importance to improve the word recommendations, it is useful to understand the pattern of use of auto-suggestions during typing. Among several factors that may influence use of auto-suggest, the role of emotion has been mostly overlooked, often due to the difficulty of unobtrusively inferring emotion. With advances in affective computing, and ability to infer user's emotional states accurately, it is imperative to investigate how auto-suggest can be guided by emotion aware decisions. In this work, we investigate correlations between user emotion and usage of auto-suggest i.e. whether users prefer to use auto-suggest in specific emotion states. We developed an Android keyboard application, which records auto-suggest usage and collects emotion self-reports from users in a 3-week in-the-wild study. Analysis of the dataset reveals relationship between user reported emotion state and use of auto-suggest. We used the data to train personalized models for predicting use of auto-suggest in specific emotion state. The model can predict use of auto-suggest with an average accuracy (AUCROC) of 82% showing the feasibility of emotion-aware auto-suggestion

Magnetic and electron transport properties of the rare-earth cobaltates, La0.7-xLnxCa0.3CoO3 (Ln = Pr, Nd, Gd and Dy) : A case of phase separation

Magnetic and electrical properties of four series of rare earth cobaltates of the formula La0.7-xLnxCa0.3CoO3 with Ln = Pr, Nd, Gd and Dy have been investigated. Compositions close to x = 0.0 contain large ferromagnetic clusters or domains, and show Brillouin-like behaviour of the field-cooled DC magnetization data with fairly high ferromagnetic Tc values, besides low electrical resistivities with near-zero temperature coefficients. The zero-field-cooled data generally show a non-monotonic behaviour with a peak at a temperatures slightly lower than Tc. The near x = 0.0 compositions show a prominent peak corresponding to the Tc in the AC-susceptibility data. The ferromagnetic Tc varies linearly with x or the average radius of the A-site cations, (rA). With increase in x or decrease in (rA), the magnetization value at any given temperature decreases markedly and the AC-susceptibility measurements show a prominent transition arising from small magnetic clusters with some characteristics of a spin-glass. Electrical resistivity increases with increase in x, showed a significant increase around a critical value of x or (rA), at which composition the small clusters also begin to dominate. These properties can be understood in terms of a phase separation scenario wherein large magnetic clusters give way to smaller ones with increase in x, with both types of clusters being present in certain compositions. The changes in magnetic and electrical properties occur parallely since the large ferromagnetic clusters are hole-rich and the small clusters are hole-poor. Variable-range hopping seems to occur at low temperatures in these cobaltates.Comment: 23 pages including figure

Unsupervised annotated city traffic map generation

Public bus services in many cities in countries like India are controlled by private owners, hence, building up a database for all the bus routes is non-trivial. In this paper, we leverage smart-phone based sensing to crowdsource and populate the information repository for bus routes in a city. We have developed an intelligent data logging module for smartphones and a server side processing mechanism to extract roads and bus routes information. From a 3 month long study involving more than 30 volunteers in 3 different cities in India, we found that the developed system, CrowdMap, can annotate bus routes wit