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Cases, R., Ros, E., & Zuñiga, J. (2011). Measuring radon concentration in air using a diffusion cloud chamber. Am. J. Phys., 79(9), 903–908.
Abstract: Radon concentration in air is a major concern in lung cancer studies. A traditional technique used to measure radon abundance is the charcoal canister method. We propose a novel technique using a diffusion cloud chamber. This technique is simpler and can easily be used for physics demonstrations for high school and university students.
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Conde, D., Castillo, F. L., Escobar, C., García, C., Garcia Navarro, J. E., Sanz, V., et al. (2023). Forecasting Geomagnetic Storm Disturbances and Their Uncertainties Using Deep Learning. Space Weather, 21(11), e2023SW003474–27pp.
Abstract: Severe space weather produced by disturbed conditions on the Sun results in harmful effects both for humans in space and in high-latitude flights, and for technological systems such as spacecraft or communications. Also, geomagnetically induced currents (GICs) flowing on long ground-based conductors, such as power networks, potentially threaten critical infrastructures on Earth. The first step in developing an alarm system against GICs is to forecast them. This is a challenging task given the highly non-linear dependencies of the response of the magnetosphere to these perturbations. In the last few years, modern machine-learning models have shown to be very good at predicting magnetic activity indices. However, such complex models are on the one hand difficult to tune, and on the other hand they are known to bring along potentially large prediction uncertainties which are generally difficult to estimate. In this work we aim at predicting the SYM-H index characterizing geomagnetic storms multiple-hour ahead, using public interplanetary magnetic field (IMF) data from the Sun-Earth L1 Lagrange point and SYM-H data. We implement a type of machine-learning model called long short-term memory (LSTM) network. Our scope is to estimate the prediction uncertainties coming from a deep-learning model in the context of forecasting the SYM-H index. These uncertainties will be essential to set reliable alarm thresholds. The resulting uncertainties turn out to be sizable at the critical stages of the geomagnetic storms. Our methodology includes as well an efficient optimization of important hyper-parameters of the LSTM network and robustness tests.
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Gariazzo, S., Di Valentino, E., Mena, O., & Nunes, R. C. (2022). Late-time interacting cosmologies and the Hubble constant tension. Phys. Rev. D, 106(2), 023530–12pp.
Abstract: In this manuscript we reassess the potential of interacting dark matter-dark energy models in solving the Hubble constant tension. These models have been proposed but also questioned as possible solutions to the H0 problem. Here we examine several interacting scenarios against cosmological observations, focusing on the important role played by the calibration of supernovae data. In order to reassess the ability of interacting dark matter-dark energy scenarios in easing the Hubble constant tension, we systematically confront their theoretical predictions using a prior on the supernovae Ia absolute magnitude MB, which has been argued to be more robust and certainly less controversial than using a prior on the Hubble constant H0. While some data combinations do not show any preference for interacting dark sectors and in some of these scenarios the clustering sigma 8 tension worsens, interacting cosmologies with a dark energy equation of state w < -1 are preferred over the canonical lambda CDM picture even with cosmic microwave background data alone and also provide values of sigma 8 in perfect agreement with those from weak lensing surveys. Future cosmological surveys will test these exotic dark energy cosmologies by accurately measuring the dark energy equation of state and its putative redshift evolution.
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Perez, A., & Romanelli, A. (2013). Spatially Dependent Decoherence and Anomalous Diffussion of Quantum Walks. J. Comput. Theor. Nanosci., 10(7), 1591–1595.
Abstract: We analyze the long time behavior of a discrete time quantum walk subject to decoherence with a strong spatial dependence, acting on one half of the lattice. We show that, except for limiting cases on the decoherence parameter, the quantum walk at late times behaves sub-ballistically, meaning that the characteristic features of the quantum walk are not completely spoiled. Contrarily to expectations, the asymptotic behavior is non Markovian, and depends on the amount of decoherence. This feature can be clearly shown on the long time value of the Generalized Chiral Distribution (GCD).
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Hinarejos, M., Bañuls, M. C., & Perez, A. (2013). A Study of Wigner Functions for Discrete-Time Quantum Walks. J. Comput. Theor. Nanosci., 10(7), 1626–1633.
Abstract: We perform a systematic study of the discrete time Quantum Walk on one dimension using Wigner functions, which are generalized to include the chirality (or coin) degree of freedom. In particular, we analyze the evolution of the negative volume in phase space, as a function of time, for different initial states. This negativity can be used to quantify the degree of departure of the system from a classical state. We also relate this quantity to the entanglement between the coin and walker subspaces.
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