天体物理仪器与方法：2025–2026 年度综述

An annual survey of the astro-ph.IM arXiv category, covering research published from September 2025 – August 2026. Built on a close-reading set of 132 papers and organised into 37 chapters, it maps the year by the field's research sub-directions.

Book framework (share of the year's output):

• Stellar Kinematics and Machine Learning Frameworks (35.2%) — Developing neural network models and statistical frameworks for stellar kinematics, atmospheric corrections, and light curve classification.
• Space Telescope Design and Calibration (16.1%) — Addressing radiation damage, charge transfer inefficiency, and calibration issues in space-based optical and infrared instruments.
• Survey Data Reduction and Processing Pipelines (8.3%) — Implementing data acquisition networks, reduction pipelines, and analysis algorithms for large-scale spectroscopic and photometric surveys.
• Gravitational Wave Detector Technologies (6.6%) — Optimizing detector sensitivity, signal processing, and source modeling for ground-based and space-based gravitational wave observatories.
• Simulation-Based Inference and Modeling (6.4%) — Utilizing simulation-based inference, reinforcement learning, and high-performance N-body codes for astrophysical source detection and parameter estimation.
• High-Energy Cosmic Ray and X-ray Instrumentation (6.1%) — Developing hard X-ray spectrometers, transition edge sensors, and detection methods for cosmic rays and high-energy astrophysical sources.
• Radio Astronomy and Fast Radio Bursts (5.7%) — Advancing radio telescope arrays, fast radio burst characterization, and spectral analysis techniques for radio astronomy observations.
• Deep Learning in Astrophysical Analysis (4.9%) — Applying deep learning and interpretable machine learning techniques for stellar mass estimation, source classification, and physical parameter inference.
• High-Contrast Imaging and Spectroscopy (4.3%) — Enhancing high-resolution imaging, coronagraphy, and precision spectroscopy capabilities for exoplanet and solar system observations.
• Habitable Worlds Observatory and Survey Planning (3.8%) — Designing instrumentation, target selection strategies, and observational frameworks for the Habitable Worlds Observatory and large sky surveys.
• Black Hole Binary Detection and Analysis (2.6%) — Analyzing binary black hole mergers, primordial black hole signatures, and supermassive black hole populations using gravitational wave and electromagnetic data.

Each sub-direction is covered across three chapters — how it framed its questions, the strength of its key findings, and its open debates and frontiers — so the reader gets a traceable picture of what this part of the field actually produced over the year.