相关论文: Performance results of HESP physical model

For the astronomical community analyzing ISO-SWS data, a first point to assess when judging and qualifying the observational data concerns the flux calibration accuracy. Since the calibration process is not straightforward and since a wrong…

We study efficient optimization of the Hamiltonians of multi-species spherical spin glasses. Our results characterize the maximum value attained by algorithms that are suitably Lipschitz with respect to the disorder through a variational…

Microscope objectives achieve near diffraction-limited performance only when used under the conditions they are designed for. In non-standard geometries, such as thick cover slips or curved surfaces, severe aberrations arise, inevitably…

Context: Instrumental profile (IP) is the basic property of a spectrograph. Accurate IP characterisation is the prerequisite of accurate wavelength solution. It also facilitates new spectral acquisition methods such as the forward modeling…

Hidden Markov models have successfully been applied as models of discrete time series in many fields. Often, when applied in practice, the parameters of these models have to be estimated. The currently predominating identification methods,…

The ultraslow dynamics of glass-formers has been explained by two views considered as mutually exclusive: one invokes locally hindered mobility, the other rests on the complexity of the configuration space. Here we demonstrate that the…

In fiber-based spectroscopy within telescopes, a prevailing limitation has been the necessity to align the fiber diameter with the telescope's seeing conditions, often characterized by the Full Width at Half Maximum of the point spread…

Precision calibration poses challenges to experiments probing the redshifted 21-cm signal of neutral hydrogen from the Cosmic Dawn and Epoch of Reionization (z~30-6). In both interferometric and global signal experiments, systematic…

Model monitoring is a critical component of the machine learning lifecycle, safeguarding against undetected drops in the model's performance after deployment. Traditionally, performance monitoring has required access to ground truth labels,…

While experiments and simulations have provided a rich picture of the dynamic heterogeneity in glasses at constant temperature or under steady shear, the dynamics of glasses under oscillatory shear remain comparatively less explored. Recent…

We propose a theory based on simple physical arguments that describes a non equilibrium steady-state by a temperature-like parameter (an "effective temperature"). We show how one can predict the effective temperature as a function of the…

We present numerical experiments for geophysics electromagnetic (EM) modeling based upon high-order edge elements and supervised $h+p$ refinement approaches on massively parallel computers. Our high-order $h+p$ refinement strategy is based…

We employ classical statistical methods of multivariate classification for the exploitation of the stellar content of the Hamburg/ESO objective prism survey (HES). In a simulation study we investigate the precision of a three-dimensional…

We describe techniques for photometric calibration of optical spectra obtained with the MMT's fiber-fed spectrograph, Hectospec. The atmospheric dispersion compensation prisms built into the MMT's f/5 wide field corrector effectively…

Computer model calibration is a crucial step in building a reliable computer model. In the face of massive physical observations, a fast estimation for the calibration parameters is urgently needed. To alleviate the computational burden, we…

We describe automatic procedures for the selection of DA white dwarfs in the Hamburg/ESO objective-prism survey (HES). For this purpose, and the selection of other stellar objects (e.g., metal-poor stars and carbon stars), a flexible,…

In this paper optimal designs for regression problems with spherical predictors of arbitrary dimension are considered. Our work is motivated by applications in material sciences, where crystallographic textures such as the missorientation…

Cloud-related parameterizations remain a leading source of uncertainty in climate projections. Although machine learning holds promise for Earth system models (ESMs), many data-driven parameterizations lack interpretability, physical…

Safe operation of machine learning models requires architectures that explicitly delimit their operational ranges. We evaluate the ability of anomaly detection algorithms to provide indicators correlated with degraded model performance. By…

The plastic deformation of amorphous solids is mediated by localized shear transformations involving small groups of particles rearranging irreversibly in an elastic background. We introduce and compare three different computational methods…