SALT3: An Improved Type Ia Supernova Model for Measuring Cosmic Distances

A spectral-energy distribution (SED) model for Type Ia supernovae (SNe Ia) is a critical tool for measuring precise and accurate distances across a large redshift range and constraining cosmological parameters. We present an improved model framework, SALT3, which has several advantages over current models—including the leading SALT2 model (SALT2.4). While SALT3 has a similar philosophy, it differs from SALT2 by having improved estimation of uncertainties, better separation of color and light-curve stretch, and a publicly available training code. We present the application of our training method on a cross-calibrated compilation of 1083 SNe with 1207 spectra. Our compilation is 2.5× larger than the SALT2 training sample and has greatly reduced calibration uncertainties. The resulting trained SALT3.K21 model has an extended wavelength range 2000–11,000 Å (1800 Å redder) and reduced uncertainties compared to SALT2, enabling accurate use of low-z I and iz photometric bands. Including these previously discarded bands, SALT3.K21 reduces the Hubble scatter of the low-z Foundation and CfA3 samples by 15% and 10%, respectively. To check for potential systematic uncertainties, we compare distances of low (0.01 < z < 0.2) and high (0.4 < z < 0.6) redshift SNe in the training compilation, finding an insignificant 3 ± 14 mmag shift between SALT2.4 and SALT3.K21. While the SALT3.K21 model was trained on optical data, our method can be used to build a model for rest-frame NIR samples from the Roman Space Telescope. Our open-source training code, public training data, model, and documentation are available at https://saltshaker.readthedocs.io/en/latest/, and the model is integrated into the sncosmo and SNANA software packages.

MASS RATIOS OF LONG-PERIOD BINARY STARS RESOLVED IN PRECISION ASTROMETRY CATALOGS OF TWO EPOCHS

Mass ratios of widely separated, long-period, resolved binary stars can be directly estimated from the available data in major space astrometry catalogs, such as the ESA's Hipparcos and Gaia mission results. The method is based on the universal principle of inertial motion of the system's center of mass in the absence of external forces, and is independent of any assumptions about the physical parameters or stellar models. The application is limited by the precision of input astrometric data, the orbital period and distance to the system, and possible presence of other attractors in the vicinity, such as in triple systems. A generalization of this technique to triples is proposed, as well as approaches to estimation of uncertainties. The known long-period binary HIP 473 AB is discussed as an application example, for which a m2/ m1 = 0.996+0.026 −0.026 is obtained.

Critical Buckling Generation of TCA Benchmark by the B1 Theory-Augmented Monte Carlo Calculation and Estimation of Uncertainties

The Korea Atomic Energy Research Institute (KAERI) has developed the DeCART2D 2-dimensional (2D) method of characteristics (MOC) transport code and the MASTER nodal diffusion code and has established its own two-step procedure. For design code licensing, KAERI prepared a critical experiment on the verification and validation (V&V) of the DeCART2D code. DeCART2D is able to perform the MOC calculation only for 2D nuclear fuel systems, such as the fuel assembly. Therefore, critical buckling in the vertical direction is essential for comparison between the results of experiments and DeCART2D. In this study, the B1 theory-augmented Monte Carlo (MC) method was adopted for the generation of critical buckling. To examine critical buckling using the B1 theory-augmented MC method, TCA critical experiment benchmark problems were considered. Based on the TCA benchmark results, it was confirmed that the DeCART2D code with the newly-generated critical buckling predicts the criticality very well. In addition, the critical buckling generated by the B1 theory-augmented MC method was bound to uncertainties. Therefore, utilizing basic equations (e.g., SNU S/U formulation) linking input uncertainties to output uncertainties, a new formulation to estimate the uncertainties of the newly generated critical buckling was derived. This was then used to compute the uncertainties of the critical buckling for a TCA critical experiment, under the assumption that nuclear cross-section data have uncertainties.

Spiking-Free HGO-Based Dynamic Surface Control for Flexible Joint Manipulator with Unmeasurable States

For the flexible joint manipulator control system (FJMCS) with unmeasurable states, a novel partial states feedback control (PSFC) is proposed. Firstly, the unmeasurable states and the uncertainties are observed by a high-gain observer (HGO) simultaneously. Then, a dynamic surface controller is proposed based on the output of the HGO. The newly proposed controller has several advantages over existing methods. First, the proposed controller not only uses the estimate states to avoid using unmeasurable states, but also uses the estimation of uncertainties to enhance the robustness of FJMCS. Second, a novel spike suppression function (SSF) is developed to avoid the estimation spike problem in the existing HGO-based controllers. The closed-loop system stability is proved by the Lyapunov theory. Simulation results demonstrate the effectiveness of the proposed controller.

Analysis of the covariance matrix in FWI through density of covariance maps

Full waveform inversion (FWI) is a tool for the inversion of seismic data. There are several sources of uncertainty in the results provided by FWI. The quantification of such uncertainties has been studied through the resolution matrix (Res), which rests on a quadratic approximation that interprets the Hessian matrix as the posterior covariance matrix. Despite efforts in the use of Res, there is no published analysis of the uncertainties contained in the full correlation matrix, (R). Our approach leads to build the full R matrix, which, at the end of the day, is the final quantity that includes all the information associated with uncertainties.We focused on uncertainties related to variation in the starting models of the FWI, and thus propose a method to study the full R matrix, which is-called the Density of Correlation Map, D. By using the D map, we found that the highest uncertainty zones in the FWI inverted model are near the sources, the model boundaries, and the interfaces. We argue that D can be a complement for the study and estimation of uncertainties in FWI.

Revisiting the Global and Regional Steric Sea-level Trends in the Satellite Era

&lt;p&gt;The steric component of sea-level change comprises variations in the temperature (thermosteric) and salinity (halosteric) of the oceans, which alter the water&amp;#8217;s density, leading to volumetric variations of the water column. Although its importance is unarguable, throughout the literature there is a disagreement on how much the steric component actually contributes to sea-level change.&lt;/p&gt;&lt;p&gt;Here, we investigate two sources of uncertainty to steric trends, both at global and regional scale. First, we look at how the use of different temperature and salinity datasets influences the estimated steric height. For that, we analyzed 15 datasets, combining different techniques (hydrographic profiles, Argo floats and ocean reanalyses). Second, since the estimation of uncertainties for linear and quadratic trends requires the adoption of a noise model, we compared the performance of several different noise models. &amp;#160;&lt;/p&gt;&lt;p&gt;We find that by varying both the dataset and noise-model, the global mean trend and uncertainty from 2005 to 2015 can vary from 0.566 to 2.334 mm/yr and 0.022 to 1.646 mm/yr, respectively. This range becomes even larger at regional scales. At a global scale, the selection of datasets has a larger influence on the trend, while at a regional scale the choice of the noise model dominates the spread in steric sea-level trends. Our results emphasize the need to use an ensemble of datasets to infer steric changes, and to carefully choose a noise model.&lt;/p&gt;