arXiv subjects

Xiaodong Ren

Publications and source records attributed to Xiaodong Ren.

6 recordsLinked to original sources

arXiv2026

Physical Optics Analysis of Polarization Effects in SO LAT Reflectors

We present a physical-optics analysis of the polarization response of the reflective optical of the Simons Observatory Large Aperture Telescope (SO LAT). Far-field co-polar and cross-polar beam patterns are simulated for representative feedhorn positions, and the corresponding polarization-angle offsets are evaluated. The results show that the crossed-Dragone reflector system has good polarization performance. Off-axis feed positions introduce small, position-dependent offsets in the far-field polarization orientation, with a maximum value of 0.23 degrees, due to optical asymmetry. The relative polarization-angle offset under feedhorn polarization rotation, however, remains consistent with zero. No significant frequency dependence is found over the frequencies considered. These results provide a practical reference for polarization-angle calibration and for assessing reflector-induced polarization systematics in the SO LAT.

astro-ph.IM↗

arXiv2026

Polarization rotation through differential transmission in refractive CMB telescopes identified using a hybrid physical optics method

We identify a polarization rotation systematic in the far field beams of refractive cosmic microwave background (CMB) telescopes caused by differential transmission in anti-reflection (AR) coatings of optical elements. This systematic was identified following the development of a hybrid physical optics method that incorporates full-wave electromagnetic simulations of AR coatings to model the full polarization response of refractive systems. Applying this method to a two-lens CMB telescope with non-ideal AR coating, we show that polarization-dependent transmission can produce a rotation of the far-field polarization angle that varies across the focal plane with a typical amplitude of 0.05-0.5 degrees. If ignored in analysis, this effect can produce temperature to polarization leakage and Stokes Q/U mixing.

astro-ph.IM↗

arXiv2025

Opening the Black Box: An Explainable, Few-shot AI4E Framework Informed by Physics and Expert Knowledge for Materials Engineering

The industrial adoption of Artificial Intelligence for Engineering (AI4E) faces two fundamental bottlenecks: scarce high-quality data and the lack of interpretability in black-box models-particularly critical in safety-sensitive sectors like aerospace. We present an explainable, few-shot AI4E framework that is systematically informed by physics and expert knowledge throughout its architecture. Starting from only 32 experimental samples in an aerial K439B superalloy castings repair welding case, we first augment physically plausible synthetic data through a three-stage protocol: differentiated noise injection calibrated to process variabilities, enforcement of hard physical constraints, and preservation of inter-parameter relationships. We then employ a nested optimization strategy for constitutive model discovery, where symbolic regression explores equation structures while differential evolution optimizes parameters, followed by intensive parameter refinement using hybrid global-local optimization. The resulting interpretable constitutive equation achieves 88% accuracy in predicting hot-cracking tendency. This equation not only provides quantitative predictions but also delivers explicit physical insight, revealing how thermal, geometric, and metallurgical mechanisms couple to drive cracking-thereby advancing engineers' cognitive understanding of the process. Furthermore, the constitutive equation serves as a multi-functional tool for process optimization and high-fidelity virtual data generation, enabling accuracy improvements in other data-driven models. Our approach provides a general blueprint for developing trustworthy AI systems that embed engineering domain knowledge directly into their architecture, enabling reliable adoption in high-stakes industrial applications where data is limited but physical understanding is available.

cs.LG↗

arXiv2021

Holographic surface measurement system for the Fred Young Submillimeter Telescope

We describe a system being developed for measuring the shapes of the mirrors of the Fred Young Submillimeter Telescope (FYST), now under construction for the CCAT Observatory. "Holographic" antenna-measuring techniques are an efficient and accurate way of measuring the surfaces of large millimeter-wave telescopes and they have the advantage of measuring the wave-front errors of the whole system under operational conditions, e.g. at night on an exposed site. Applying this to FYST, however, presents significant challenges because of the high accuracy needed, the fact that the telescope consists of two large off-axis mirrors, and a requirement that measurements can be made without personnel present. We use a high-frequency (~300GHz) source which is relatively close to the telescope aperture (<1/100th of the Fresnel distance) to minimize atmospheric effects. The main receiver is in the receiver cabin and can be moved under remote control to different positions, so that the wave-front errors in different parts of the focal plane can be measured. A second receiver placed on the yoke provides a phase reference. The signals are combined in a digital cross-correlation spectrometer. Scanning the telescope provides a map of the complex beam pattern. The surface errors are found by inference, i.e. we make models of the reflectors with errors and calculate the patterns expected, and then iterate to find the best match to the data. To do this we have developed a fast and accurate method for calculating the patterns using the Kirchhoff-Fresnel formulation. This paper presents details of the design and outlines the results from simulations of the measurement and inference process. These indicate that a measurement accuracy of ~3 microns rms is achievable.

astro-ph.IM↗

arXiv2021

Enhancing hierarchical surrogate-assisted evolutionary algorithm for high-dimensional expensive optimization via random projection

By remarkably reducing real fitness evaluations, surrogate-assisted evolutionary algorithms (SAEAs), especially hierarchical SAEAs, have been shown to be effective in solving computationally expensive optimization problems. The success of hierarchical SAEAs mainly profits from the potential benefit of their global surrogate models known as "blessing of uncertainty" and the high accuracy of local models. However, their performance leaves room for improvement on highdimensional problems since now it is still challenging to build accurate enough local models due to the huge solution space. Directing against this issue, this study proposes a new hierarchical SAEA by training local surrogate models with the help of the random projection technique. Instead of executing training in the original high-dimensional solution space, the new algorithm first randomly projects training samples onto a set of low-dimensional subspaces, then trains a surrogate model in each subspace, and finally achieves evaluations of candidate solutions by averaging the resulting models. Experimental results on six benchmark functions of 100 and 200 dimensions demonstrate that random projection can significantly improve the accuracy of local surrogate models and the new proposed hierarchical SAEA possesses an obvious edge over state-of-the-art SAEAs

cs.NE↗

arXiv2016

An Alternative Analysis of Discontinuous Galerkin Method for Hyperbolic Conservation Law

The development and application of the Discontinuous Galerkin (DG) method have attracted great attention in computational fluid dynamics (CFD) com- munity in the past decades. The underlying reason for such an intensive investigation is due to favorable properties of the DG method, such as higher order, compactness, and easy parallelization. However, for the compressible flow simulations, the DG method is also associated with unfavorable prop- erties, such as the frequent instabilities in non-smooth regions. Due to the finite element formulation, except the update of the cell averaged conserva- tive flow variable, it becomes rather difficulty to fully understand the physical mechanism in the DG method for the updates of other degrees of freedom in- side each element. In this short note, based on the linear advection equation we are going to analyze the DG method in an alternative way. The results obtained may be useful for the CFD community for its further development of the DG methods.

math.NA↗