End-to-end numerical modeling of the Roman Space Telescope coronagraph

The Roman Space Telescope will have the first advanced coronagraph in space, with deformable mirrors for wavefront control, low-order wavefront sensing and maintenance, and a photon-counting detector. It is expected to be able to detect and characterize mature, giant exoplanets in reflected visible light. Over the past decade the performance of the coronagraph in its flight environment has been simulated with increasingly detailed diffraction and structural/thermal finite element modeling. With the instrument now being integrated in preparation for launch within the next few years, the present state of the end-to-end modeling is described, including the measured flight components such as deformable mirrors. The coronagraphic modes are thoroughly described, including characteristics most readily derived from modeling. The methods for diffraction propagation, wavefront control, and structural and thermal finite-element modeling are detailed. The techniques and procedures developed for the instrument will serve as a foundation for future coronagraphic missions such as the Habitable Worlds Observatory.Comment: 113 pages, 85 figures, to be published in SPIE Journal of Astronomical Telescopes, Instruments, and System

Convex decomposition of games and axiomatizations of the core and the D-core

Cooperative TU-game, Core, Undominated imputations, Reasonable outcomes, C71,

Systematic benchmarking of single-cell ATAC-sequencing protocols

Single-cell assay for transposase-accessible chromatin by sequencing (scATAC-seq) has emerged as a powerful tool for dissecting regulatory landscapes and cellular heterogeneity. However, an exploration of systemic biases among scATAC-seq technologies has remained absent. In this study, we benchmark the performance of eight scATAC-seq methods across 47 experiments using human peripheral blood mononuclear cells (PBMCs) as a reference sample and develop PUMATAC, a universal preprocessing pipeline, to handle the various sequencing data formats. Our analyses reveal significant differences in sequencing library complexity and tagmentation specificity, which impact cell-type annotation, genotype demultiplexing, peak calling, differential region accessibility and transcription factor motif enrichment. Our findings underscore the importance of sample extraction, method selection, data processing and total cost of experiments, offering valuable guidance for future research. Finally, our data and analysis pipeline encompasses 169,000 PBMC scATAC-seq profiles and a best practices code repository for scATAC-seq data analysis, which are freely available to extend this benchmarking effort to future protocols