Simulations of Helical Inflationary Magnetogenesis and Gravitational Waves

Using numerical simulations of helical inflationary magnetogenesis in a low reheating temperature scenario, we show that the magnetic energy spectrum is strongly peaked at a particular wavenumber that depends on the reheating temperature. Gravitational waves (GWs) are produced at frequencies between 3 nHz and 50 mHz for reheating temperatures between 150 MeV and 3 × 105 GeV, respectively. At and below the peak frequency, the stress spectrum is always found to be that of white noise. This implies a linear increase of GW energy per logarithmic wavenumber interval, instead of a cubic one. Both in the helical and nonhelical cases, the GW spectrum is followed by a sharp drop for frequencies above the respective peak frequency. In this magnetogenesis scenario, the presence of a helical term extends the peak of the GW spectrum and therefore also the position of the aforementioned drop toward larger frequencies compared to the case without helicity. This might make a difference in it being detectable with space interferometers. The efficiency of GW production is found to be almost the same as in the nonhelical case, and independent of the reheating temperature, provided the electromagnetic energy at the end of reheating is fixed to be a certain fraction of the radiation energy density. Also, contrary to the case without helicity, the electric energy is now less than the magnetic energy during reheating. The fractional circular polarization is found to be nearly 100% in a certain range below the peak frequency range.

Prediction of Leakage Current and Depletion Voltage in Silicon Detectors Under Extraterrestrial Radiation Conditions

Silicon detection is a mature technology for registering the passage of charged particles. At the same time it continues to evolve toward increasing radiation tolerance as well as precision and adaptability. For these reasons it is likely to remain a critical element of detection of systems associated with extraterrestrial exploration. Silicon sensor leakage current and depletion voltage depend on the integrated fluence received by the sensor and on its thermal history during and after the irradiation process. For minimal assumptions on shielding and hence on the particle energy spectrum, and using published data on Martian ground temperature, we predict the leakage current density and the depletion voltage, as a function of time, of silicon sensors in transit to and deployed continuously on the Mars surface for a duration of up to 28 Earth-years, for several sensor geometries and a worst-case temperature scenario.

Conceptualization of color temperature scenario applied to quality lighting design.

Quality lighting is characterized by four major factors, one of them being the color temperature. When designed for elderly, this quality lighting can allow them to evolve within their environment safely, independently and above all comfort without having to focus on the effects of aging. This article aims to show the benefits of designing color temperature scenarios, made possible for example by dynamic LED lighting, thus contributing to the production of comfortable lighting and thus quality.

Ice sheet contributions to future sea-level rise from structured expert judgment

Despite considerable advances in process understanding, numerical modeling, and the observational record of ice sheet contributions to global mean sea-level rise (SLR) since the Fifth Assessment Report (AR5) of the Intergovernmental Panel on Climate Change, severe limitations remain in the predictive capability of ice sheet models. As a consequence, the potential contributions of ice sheets remain the largest source of uncertainty in projecting future SLR. Here, we report the findings of a structured expert judgement study, using unique techniques for modeling correlations between inter- and intra-ice sheet processes and their tail dependences. We find that since the AR5, expert uncertainty has grown, in particular because of uncertain ice dynamic effects. For a +2 °C temperature scenario consistent with the Paris Agreement, we obtain a median estimate of a 26 cm SLR contribution by 2100, with a 95th percentile value of 81 cm. For a +5 °C temperature scenario more consistent with unchecked emissions growth, the corresponding values are 51 and 178 cm, respectively. Inclusion of thermal expansion and glacier contributions results in a global total SLR estimate that exceeds 2 m at the 95th percentile. Our findings support the use of scenarios of 21st century global total SLR exceeding 2 m for planning purposes. Beyond 2100, uncertainty and projected SLR increase rapidly. The 95th percentile ice sheet contribution by 2200, for the +5 °C scenario, is 7.5 m as a result of instabilities coming into play in both West and East Antarctica. Introducing process correlations and tail dependences increases estimates by roughly 15%.

Residual Entropy and Critical Behavior of Two Interacting Boson Species in a Double Well

Motivated by the importance of entanglement and correlation indicators in the analysis of quantum systems, we study the equilibrium and the residual entropy in a two-species Bose Hubbard dimer when the spatial phase separation of the two species takes place. We consider both the zero and non-zero-temperature regime. We present different kinds of residual entropies (each one associated to a different way of partitioning the system), and we show that they strictly depend on the specific quantum phase characterizing the two species (supermixed, mixed or demixed) even at finite temperature. To provide a deeper physical insight into the zero-temperature scenario, we apply the fully-analytical variational approach based on su(2) coherent states and provide a considerbly good approximation of the entanglement entropy. Finally, we show that the effectiveness of residual entropy as a critical indicator at non-zero temperature is unchanged when considering a restricted combination of energy eigenstates.

Climate change inspector with intentionally biased bootstrapping (CCIIBB ver. 1.0) – methodology development

The outputs from general circulation models (GCMs) provide useful information about the rate and magnitude of future climate change. The temperature variable is more reliable than other variables in GCM outputs. However, hydrological variables (e.g., precipitation) from GCM outputs for future climate change possess an uncertainty that is too high for practical use. Therefore, a method called intentionally biased bootstrapping (IBB), which simulates the increase of the temperature variable by a certain level as ascertained from observed global warming data, is proposed. In addition, precipitation data were resampled by employing a block-wise sampling technique associated with the temperature simulation. In summary, a warming temperature scenario is simulated, along with the corresponding precipitation values whose time indices are the same as those of the simulated warming temperature scenario. The proposed method was validated with annual precipitation data by truncating the recent years of the record. The proposed model was also employed to assess the future changes in seasonal precipitation in South Korea within a global warming scenario as well as in weekly timescales. The results illustrate that the proposed method is a good alternative for assessing the variation of hydrological variables such as precipitation under the warming condition.

Simulating climate warming scenarios with intentionally biased bootstrapping and its implications for precipitation

The outputs from GCMs provide useful information about the rate and magnitude of future climate change. The temperature variable is the most reliable of the GCM outputs. However, hydrological variables (e.g., precipitation) from GCM outputs for future climate change possess an uncertainty that is too high for practical use. Therefore, a method, called intentionally biased bootstrapping (IBB), that simulates the increase of the temperature variable by a certain level as ascertained from observed global warming data is proposed. In addition, precipitation data was resampled by employing a block-wise sampling technique associated with the temperature simulation. In summary, a warming temperature scenario is simulated and the corresponding precipitation values whose time indices are the same as the one of the simulated warming temperature scenario. The proposed method was validated with annual precipitation data by truncating the recent years of the record. The proposed model was also employed to assess the future changes in seasonal precipitation in South Korea within a global warming scenario as well as in weekly time scale. The results illustrate that the proposed method is a good alternative for assessing the variation of hydrological variables such as precipitation under the warming condition.