Analysis of 83mKr prompt scintillation signals in the PIXeY detector

Prompt scintillation signals from 83mKr calibration sources are a useful metric to calibrate the spatial variation of light collection efficiency and electric field magnitude of a two phase liquid-gas xenon time projection chamber. Because 83mKr decays in two steps, there are two prompt scintillation pulses for each calibration event, denoted S1a and S1b. We study the ratio of S1b to S1a signal sizes in the Particle Identification in Xenon at Yale (PIXeY) experiment and its dependence on the time separation between the two signals (Δ t), notably its increase at low Δ t. In PIXeY data, the Δ t dependence of S1b/S1a is observed to exhibit two exponential components: one with a time constant of 0.05 ± 0.02 μ s, which can be attributed to processing effects and pulse overlap and one with a time constant of 10.2 ± 2.2 μs that increases in amplitude with electric drift field, the origin of which is not yet understood

Peeking inside the Black Box: Interpreting Deep-learning Models for Exoplanet Atmospheric Retrievals

Deep-learning algorithms are growing in popularity in the field of exoplanetary science due to their ability to model highly nonlinear relations and solve interesting problems in a data-driven manner. Several works have attempted to perform fast retrievals of atmospheric parameters with the use of machine-learning algorithms like deep neural networks (DNNs). Yet, despite their high predictive power, DNNs are also infamous for being "black boxes." It is their apparent lack of explainability that makes the astrophysics community reluctant to adopt them. What are their predictions based on? How confident should we be in them? When are they wrong, and how wrong can they be? In this work, we present a number of general evaluation methodologies that can be applied to any trained model and answer questions like these. In particular, we train three different popular DNN architectures to retrieve atmospheric parameters from exoplanet spectra and show that all three achieve good predictive performance. We then present an extensive analysis of the predictions of DNNs, which can inform us–among other things–of the credibility limits for atmospheric parameters for a given instrument and model. Finally, we perform a perturbation-based sensitivity analysis to identify to which features of the spectrum the outcome of the retrieval is most sensitive. We conclude that, for different molecules, the wavelength ranges to which the DNNs predictions are most sensitive do indeed coincide with their characteristic absorption regions. The methodologies presented in this work help to improve the evaluation of DNNs and to grant interpretability to their predictions

Peeking inside the Black Box: Interpreting Deep-learning Models for Exoplanet Atmospheric Retrievals

Deep-learning algorithms are growing in popularity in the field of exoplanetary science due to their ability to model highly nonlinear relations and solve interesting problems in a data-driven manner. Several works have attempted to perform fast retrievals of atmospheric parameters with the use of machine-learning algorithms like deep neural networks (DNNs). Yet, despite their high predictive power, DNNs are also infamous for being "black boxes." It is their apparent lack of explainability that makes the astrophysics community reluctant to adopt them. What are their predictions based on? How confident should we be in them? When are they wrong, and how wrong can they be? In this work, we present a number of general evaluation methodologies that can be applied to any trained model and answer questions like these. In particular, we train three different popular DNN architectures to retrieve atmospheric parameters from exoplanet spectra and show that all three achieve good predictive performance. We then present an extensive analysis of the predictions of DNNs, which can inform us–among other things–of the credibility limits for atmospheric parameters for a given instrument and model. Finally, we perform a perturbation-based sensitivity analysis to identify to which features of the spectrum the outcome of the retrieval is most sensitive. We conclude that, for different molecules, the wavelength ranges to which the DNNs predictions are most sensitive do indeed coincide with their characteristic absorption regions. The methodologies presented in this work help to improve the evaluation of DNNs and to grant interpretability to their predictions

On the Strength of the Carbon Nanotube-Based Space Elevator Cable: From Nano- to Mega-Mechanics

In this paper different deterministic and statistical models, based on new quantized theories proposed by the author, are presented to estimate the strength of a real, thus defective, space elevator cable. The cable, of ~100 megameters in length, is composed by carbon nanotubes, ~100 nanometers long: thus, its design involves from the nano- to the mega-mechanics. The predicted strengths are extensively compared with the experiments and the atomistic simulations on carbon nanotubes available in the literature. All these approaches unequivocally suggest that the megacable strength will be reduced by a factor at least of ~70% with respect to the theoretical nanotube strength, today (erroneously) assumed in the cable design. The reason is the unavoidable presence of defects in a so huge cable. Preliminary in silicon tensile experiments confirm the same finding. The deduced strength reduction is sufficient to pose in doubt the effective realization of the space elevator, that if built as today designed will surely break (according to the s opinion). The mechanics of the cable is also revised and possibly damage sources discussed

Fast detector of the ellipticity of infrared and terahertz radiation based on HgTe quantum well structures

We report a fast, room temperature detection scheme for the polarization ellipticity of laser radiation, with a bandwidth that stretches from the infrared to the terahertz range. The device consists of two elements, one in front of the other, that detect the polarization ellipticity and the azimuthal angle of the ellipse. The elements respectively utilise the circular photogalvanic effect in a narrow gap semiconductor and the linear photogalvanic effect in a bulk piezoelectric semiconductor. For the former we characterized both a HgTe quantum well and bulk Te, and for the latter, bulk GaAs. In contrast with optical methods our device is an easy to handle all-electric approach, which we demonstrated by applying a large number of different lasers from low power, continuous wave systems to high power, pulsed sources.Comment: 7 pages, 5 figure

Mesoscopic Effects in the Quantum Hall Regime

We report results of a study of (integer) quantum Hall transitions in a single or multiple Landau levels for non-interacting electrons in disordered two-dimensional systems, obtained by projecting a tight-binding Hamiltonian to corresponding magnetic subbands. In finite-size systems, we find that mesoscopic effects often dominate, leading to apparent non-universal scaling behaviour in higher Landau levels. This is because localization length, which grows exponentially with Landau level index, exceeds the system sizes amenable to numerical study at present. When band mixing between multiple Landau levels is present, mesoscopic effects cause a crossover from a sequence of quantum Hall transitions for weak disorder to classical behaviour for strong disorder. This behaviour may be of relevance to experimentally observed transitions between quantum Hall states and the insulating phase at low magnetic fields.Comment: 13 pages, 6 figures, Proceedings of the International Meeting on Mesoscopic and Disordered Systems, Bangalore December 2000, to appear in Pramana, February 200

Systems analysis of bioenergetics and growth of the extreme halophile Halobacterium salinarum

Halobacterium salinarum is a bioenergetically flexible, halophilic microorganism that can generate energy by respiration, photosynthesis, and the fermentation of arginine. In a previous study, using a genome-scale metabolic model, we have shown that the archaeon unexpectedly degrades essential amino acids under aerobic conditions, a behavior that can lead to the termination of growth earlier than necessary. Here, we further integratively investigate energy generation, nutrient utilization, and biomass production using an extended methodology that accounts for dynamically changing transport patterns, including those that arise from interactions among the supplied metabolites. Moreover, we widen the scope of our analysis to include phototrophic conditions to explore the interplay between different bioenergetic modes. Surprisingly, we found that cells also degrade essential amino acids even during phototropy, when energy should already be abundant. We also found that under both conditions considerable amounts of nutrients that were taken up were neither incorporated into the biomass nor used as respiratory substrates, implying the considerable production and accumulation of several metabolites in the medium. Some of these are likely the products of forms of overflow metabolism. In addition, our results also show that arginine fermentation, contrary to what is typically assumed, occurs simultaneously with respiration and photosynthesis and can contribute energy in levels that are comparable to the primary bioenergetic modes, if not more. These findings portray a picture that the organism takes an approach toward growth that favors the here and now, even at the cost of longer-term concerns. We believe that the seemingly "greedy" behavior exhibited actually consists of adaptations by the organism to its natural environments, where nutrients are not only irregularly available but may altogether be absent for extended periods that may span several years. Such a setting probably predisposed the cells to grow as much as possible when the conditions become favorable

Neutrino Parameters, Abelian Flavor Symmetries, and Charged Lepton Flavor Violation

Neutrino masses and mixings have important implications for models of fermion masses, and, most directly, for the charged lepton sector. We consider supersymmetric Abelian flavor models, where neutrino mass parameters are related to those of charged leptons and sleptons. We show that processes such as \tau to \mu\gamma, \mu to e\gamma and \mu-e conversion provide interesting probes. In particular, some existing models are excluded by current bounds, while many others predict rates within reach of proposed near future experiments. We also construct models in which the predicted rates for charged lepton flavor violation are below even the proposed experimental sensitivities, but argue that such models necessarily involve loss of predictive power.Comment: 27 pages, refs added, published versio

Counterion adsorption on flexible polyelectrolytes: comparison of theories

Counterion adsorption on a flexible polyelectrolyte chain in a spherical cavity is considered by taking a "permuted" charge distribution on the chain so that the "adsorbed" counterions are allowed to move along the backbone. We compute the degree of ionization by using self-consistent field theory (SCFT) and compare with the previously developed variational theory. Analysis of various contributions to the free energy in both theories reveals that the equilibrium degree of ionization is attained mainly as an interplay of the adsorption energy of counterions on the backbone, the translational entropy of the small ions, and their correlated density fluctuations. Degree of ionization computed from SCFT is significantly lower than that from the variational formalism. The difference is entirely due to the density fluctuations of the small ions in the system, which are accounted for in the variational procedure. When these fluctuations are deliberately suppressed in the truncated variational procedure, there emerges a remarkable quantitative agreement in the various contributing factors to the equilibrium degree of ionization, in spite of the fundamental differences in the approximations and computational procedures used in these two schemes. Nevertheless, since the significant effects from density fluctuations of small ions are not captured by the SCFT, and due to the close agreement between SCFT and the other contributing factors in the more transparent variational procedure, the latter is a better computational tool for obtaining the degree of ionization