with Asgard BIFROST at VLTI - arXiv. org light from the IO outputs Given that IO combiners can be optimized only for a limited bandwidth, we plan for two IO devices { one for the YJ-band an a separate one for H-band The two devices are mounted on a motorized stage, so that either the YJ-band or H-band device can feed
Contents NONLINEAR WAVE - University of Chicago Abstract This paper explores the properties of nonlinear wave equations The proof for the existence and uniqueness of solutions to the 1+1 dimensional linear wave equation with smooth data is given The D'Alembert formula is then presented in its full generality for the nonlinear equation Important properties like the domain of dependence and propagation of information are discussed and
Transfer Sensitive Inequality Measures - JSTOR aa basis for inequality comparisons, however, its scope is severely limited On its own, it does not allow us to pass judgement when distributions are defined over populations of different sizes, or when they have different means
Accurate Unsupervised Photon Counting from Transition Edge . . . We compare methods for signal classification applied to voltage traces from transition-edge sensors (TES) which are photon-number resolving detectors fundamental for accessing quantum advantages in information processing, communication and metrology We quantify the impact of numerical analysis on the distinction of such signals Furthermore, we explore dimensionality reduction tech-niques to
A HYBRID DATA DRIVEN PHYSICS CONSTRAINED GAUSSIAN UNCERTAINTY . . . ABSTRACT Gaussian process regression (GPR) has been a well-known machine learning method for various applications such as uncertainty quantifications (UQ) However, GPR is inherently a data-driven method, which requires sufficiently large dataset If appropriate physics constraints (e g expressed in partial differential equations) can be incorporated, the amount of data can be greatly reduced