Search arXiv⌕ Search
Home/Archive/arXiv

arXiv · 2607.13533

Scientific-Intention Driven Embodied Intelligent Solar Telescope: Conceptual Design

Lin Jiaben·Tong Liyue·Wang Hui·Shao Mingfu·Yang Chen
View original source ↗Read source document ↗Export metadata ↓

Abstract

Artificial Intelligence (AI) is profoundly transforming the paradigms of scientific research. Cutting-edge technologies such as Large Language Models (LLMs) and embodied intelligence are continuously pushing the boundaries of scientific instrumentation. Against this backdrop, this paper proposes a novel conceptual system: the Scientific-Intention Driven Embodied Intelligent Solar Telescope (SIDEST). The system is designed with three core layers to achieve three types of intelligent scientific research closed loops. First, the Scientific Intent Research and Demonstration Layer parses the research objectives and intents of scientists (e.g., solar physicists) through natural language interaction, achieving a closed loop for the generation and optimization of executable observation plans aligned with scientific intent via in-depth research. Subsequently, the Observation Realization Layer schedules embodied intelligent solar telescopes to implement a closed loop for the execution of scientific observation plans. Finally, the Evaluation and Evolution Layer coordinates intelligent agents for data processing and scientific analysis to analyze observation data, generate research reports, and iteratively optimize observation strategies and model methods based on results, thereby realizing a self-evolving closed loop for the entire system. During the research process, we constructed a minimal prototype system based on a precision temperature control device for solar telescope birefringent filters to validate the core principles of SIDEST. This prototype successfully implemented all key steps of intention-driven automated research, demonstrating the feasibility of the technical pathways for the three types of intelligent research closed loops. SIDEST redefines telescopes through cutting-edge AI methods.

Explore related subjects

astro-ph.IMastro-ph.SR

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Lin Jiaben, Tong Liyue, Wang Hui, Shao Mingfu, Yang Chen. 2026-07-15. Scientific-Intention Driven Embodied Intelligent Solar Telescope: Conceptual Design. https://doi.org/10.3788/lop252270

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

arXiv2026

Scale-Vector Alignment: A Scale-Aware Framework for Spatially Resolved Morphological Similarity in Astronomical Images

Astronomical maps made with different tracers are not expected to have identical morphology. Excitation, optical depth, chemistry, radiation, and ISM phase alter the response of a tracer, and the resulting differences can depend on both position and spatial scale. We propose scale-vector alignment, a scale-aware method based on Constrained Diffusion Decomposition (CDD). CDD decomposes an image into localized scale components; at each position, their amplitudes define a scale vector that describes how the measured intensity is distributed over spatial scale. We define the pixel-wise similarity $\Spix(x,y)$ as the normalized alignment of two local scale vectors. The normalization removes the overall amplitude, so $\Spix$ compares relative scale composition rather than absolute flux. We also define the scale-wise similarity $\Sscale(l)$ by comparing the two CDD component maps at each spatial scale. Spatial shifts are used to construct an empirical shifted reference distribution for $\Spix$. In Orion~A, the tracer with the highest similarity to the dust-derived column-density map changes from $^{12}$CO to $^{13}$CO to C$^{18}$O toward higher column density. In NGC~6334I(N), the line--continuum similarity decreases locally around the brightest compact structures, where radiative-transfer effects can alter the observed line morphology. In NGC~3627, CO is most similar to 21~$μ$m emission, and $\Sscale$ reaches its maximum at an intermediate sub-kpc scale. The method measures where two tracers have similar multiscale structure and at which scales their spatial distributions agree. The implementation is publicly available at https://github.com/meng-ke/Scale-Vector-Alignment.

astro-ph.IM↗
arXiv2026

Fast and accurate astronomical source deblending with Density-Peak Clustering

Source deblending is a fundamental challenge for current and forthcoming astronomical surveys, where increasing source density and image depth lead to a growing number of overlapping detections. Accurate deblending is essential for reliable measurements of source morphology and photometry, as well as for cosmological analyses. We present a redesign of the Advanced Density Peak (ADP) clustering algorithm, tailored to the identification and separation of blended astronomical sources within detection regions. We develop a validation framework combining realistic image simulations, automatically generated ground-truth segmentation, and label-invariant metrics. ADP is assessed against ASTErIsM, an established density-based astronomical deblender, using pairwise simulations, synthetic multi-source images, and Euclid Q1 public data. In pairwise simulations, the methods show comparable performance across a broad range of source separations and flux ratios, with photometric differences typically below 1% and reaching 5-7% in the most challenging cases, without systematic bias. In multi-source simulations, ADP recovers approximately 8% more ground-truth sources, while the positions of sources identified by both methods agree at the sub-pixel level. On Euclid Q1 public data, the methods show strong agreement in segmentation area, ellipticity, position angle, and photometry, with the largest differences for the smallest and faintest sources. ADP also provides a substantial computational advantage: end-to-end benchmarks on 19200 x 19200 pixel Euclid images require approximately 16-200 s, corresponding to speedups of 12-156x relative to ASTErIsM, with median and mean improvements of 36x and 54x, respectively. These results show that ADP provides scientifically competitive deblending at substantially lower computational cost, making it a promising approach for large-scale astronomical imaging surveys.

astro-ph.IM↗
arXiv2026

IceCube Upgrade status and perspectives

The IceCube Neutrino Observatory instruments one cubic kilometer of deep-glacial ice between 1450 m and 2450 m below the surface at the geographic South Pole to detect neutrinos via Cherenkov radiation of relativistic charged particles produced in their interactions. This detector is responsible for a number of key observations in neutrino astrophysics, which include the discovery of a high-energy astrophysical neutrino flux and, more recently, the galactic plane. During the austral summer of 2025/26, five new strings equipped with new photosensor designs were deployed as a dense infill in the middle of the existing detector. The science goals of this detector are twofold: Firstly, given the higher photocathode density, an improved atmospheric neutrino event selection and reconstruction at a few GeV can be achieved for enhanced capabilities to study neutrino oscillations. Secondly, novel calibration devices will improve the knowledge of the optical properties of the glacial ice and the detector response. These new calibration results will be applied to archival IceCube data, improving angular and spatial resolution of all detected astrophysical neutrino events. The IceCube Upgrade also serves as a first step towards the next-generation neutrino telescope at the South Pole, called IceCube-Gen2.

astro-ph.IM↗