arXiv subjects

Evan Widloski

Publications and source records attributed to Evan Widloski.

4 recordsLinked to original sources

arXiv2026

TomoSphero: Fast Differentiable Projector for Planetary and Solar Tomography on Spherical Grids

Computational tomography is a tool for determining the internal structure of objects from a set of projections, typically taken along some regular path. In recent years, methods and GPU-accelerated libraries have emerged that allow for fast reconstruction from projections along more complicated paths. Most of these libraries rely on a Cartesian discretization of the object, which is not appropriate for all scenarios. We present TomoSphero, a differentiable tomographic projector over spherical grids which are often used in planetary and solar tomography. TomoSphero is designed to be used as a building block in reconstruction algorithms and includes common projection types such as cone-beam and parallel-beam, but is flexible enough to accommodate arbitrary projections. TomoSphero is implemented in PyTorch which allows for fast projection computation on GPUs, easy access to modern machine learning optimizers, and automatic differentiation for rapid prototyping of parametric models.

astro-ph.IM↗

arXiv2026

Numerical Model Simulation of the Carruthers GCI Images

The Carruthers Geocorona Observatory, launched in September 2025, is NASA's first mission devoted to investigating the fundamental nature of Earth's exosphere from its distant vantage in halo orbit around the Earth-Sun Lagrange (L1) point. Its primary payload, the GeoCoronal Imager, consists of two coaligned photometric imagers that measure the radiance of ultraviolet emission at 121.6 nm (Lyman-$\alpha$, or Ly-$\alpha$) from exospheric hydrogen atoms simultaneously at wide and narrow fields of view. In order to validate the calibration and hydrogen density retrieval algorithms used in the Carruthers data processing pipeline, we developed a comprehensive numerical simulator to produce realistic images similar to those collected by the actual imagers on orbit. This paper details the algorithms used to simulate the exospheric emissions, background scene components, and instrument measurement model necessary to produce synthetic raw images.

astro-ph.IM↗

arXiv2022

Low SNR Multiframe Registration for Cubesats

We present a registration algorithm which jointly estimates motion and the ground truth image from a set of noisy frames under rigid, constant translation. The algorithm is non-iterative and needs no hyperparameter tuning. It requires a fixed number of FFT, multiplication, and downsampling operations for a given input size, enabling fast implementation on embedded platforms like cubesats where on-board image fusion can greatly save on limited downlink bandwidth. The algorithm is optimal in the maximum likelihood sense for additive white Gaussian noise and non-stationary Gaussian approximations of Poisson noise. Accurate registration is achieved for very low SNR, even when visible features are below the noise floor.

eess.IV↗

arXiv2020

Optimal Measurement Configuration in Computational Diffractive Imaging

Diffractive lenses have recently been applied to the domain of multispectral imaging in the X-ray and UV regimes where they can achieve very high resolution as compared to reflective and refractive optics. Conventionally, spectral components are reconstructed by taking measurements at the focal planes. However, the reconstruction quality can be improved by optimizing the measurement configuration. In this work, we adapt a sequential backward selection algorithm to search for a configuration which minimizes expected reconstruction error. By approximating the forward system as a circular convolution and making assumptions on the source and noise, we greatly reduce the complexity of the algorithm. Numerical results show that the configuration found by the algorithm significantly improves the reconstruction performance compared to a standard configuration.

eess.IV↗