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2025-04-11 更新

Combining high-contrast imaging with high-resolution spectroscopy: Actual on-sky MIRI/MRS results compared to expectations

Authors:S. Martos, A. Bidot, A. Carlotti, D. Mouillet

CONTEXT: Combining high-contrast imaging with high-resolution spectroscopy offers a powerful way to detect and characterize exoplanets around nearby stars, despite challenges linked to their faintness. Instruments like VLT/SPHERE are state of the art in high-contrast imaging, but their spectral resolution (R=50) limits them to basic characterization of close companions. These systems can detect planets down to 5-10 Mjup at 10 AU from their stars. Detection limits are mainly constrained by speckle noise, which dominates over photon and detector noise at short separations, even with advanced differential imaging. Space-based high-contrast imaging is also limited by image stability. Speckle noise can, however, be mitigated through molecular mapping, a technique that leverages high-resolution spectroscopic data. AIMS: We aim to predict detection limits in spectro-imaging after molecular mapping, analyzing how photon and detector noise propagate and comparing predictions with real data to assess performance losses from instrumental effects. We also propose mitigation strategies and validate our model using observations. METHODS: We analyzed JWST/MIRI/MRS data with FastCurves, an numerical tool, and compared results to outputs from the MIRI simulator. We also applied principal component analysis (PCA) to identify and isolate systematic effects, with and without molecular mapping. RESULTS: We studied various systematic effects and their impacts on signal and noise. PCA helped highlight and reduce straylight, fringes, and aliasing. We further compared observed and modeled companion spectra. CONCLUSIONS: FastCurves was improved to account for systematics and validated with real data. In high-flux regimes, systematics impose contrast limits even with molecular mapping. Our approach could benefit other instruments and inform the planning of future facilities like ELT/ANDES and ELT/PCS.

背景：尽管存在与亮度不足相关的挑战，但将高对比度成像技术与高分辨率光谱技术相结合，为检测邻近恒星周围的类太阳系行星并提供其特性描述提供了一种强大方法。像VLT/SPHERE这样的仪器在高对比度成像方面属于顶尖技术，但其光谱分辨率（R=50）仅限于近距离伴侣的基本特征描述。这些系统可以检测到距离其恒星AU 10以下的Mjup质量等级（大约是木星质量的十分之一）。检测极限主要受到斑点噪声的制约，即使在先进的差分成像下，它也在近距离内占主导地位，超越了光子探测器和噪声探测器。空间基高对比度成像也受限于图像稳定性。然而，通过分子映射技术可以减轻斑点噪声的影响，这是一种利用高分辨率光谱数据的技术。目标：我们的目标是预测分子映射后的光谱成像中的检测极限，分析光子探测器噪声的传播情况，并将预测与实际数据比较以评估仪器性能损失情况。我们还提出了缓解策略，并使用观测结果验证了我们的模型。方法：我们使用FastCurves这一数值工具分析了JWST/MIRI/MRS数据，并将结果与MIRI模拟器的输出进行了比较。我们还应用了主成分分析（PCA）来识别和隔离系统效应（是否采用分子映射）。结果：我们研究了各种系统效应及其对信号和噪声的影响。PCA有助于突出并减少杂散光、条纹和混频效应。我们进一步比较了观测到的和模拟的伴星光谱。结论：FastCurves已经改进以考虑系统因素并通过实际数据进行了验证。在高流量状态下，即使有分子映射存在，系统因素也设置了对比度限制。我们的方法可能会对其他仪器有益并为未来设施（如ELT/ANDES和ELT/PCS）的规划提供信息。

论文及项目相关链接

PDF Accepted for publication in Astronomy & Astrophysics, Section 13 (Astronomical instrumentation), reference: aa53382-24 23 pages, 34 figures

Summary
基于高对比成像与高通量光谱技术的结合，在探测邻近恒星周围的外星问题时表现出强大的能力，但也面临着挑战。研究中提到了针对一些关键技术如何改善的情况和初步结果，特别是在消减颗粒噪声、减轻系统性效应和提高预测准确度方面的新见解和方法。该研究有助于推动未来天文观测设施的发展。

Key Takeaways

• 高对比成像与高分辨率光谱技术结合对于探测和表征邻近恒星周围的外星行星具有强大潜力。
• 仪器如VLT/SPHERE受限于其光谱分辨率，但可通过分子映射技术减轻颗粒噪声的影响。
• 研究旨在预测分子映射后的光谱成像检测极限，并分析了光子与探测器噪声的传播。
• 使用FastCurves数值工具和MIRI模拟器进行分析，并用主成分分析（PCA）识别并隔离系统性效应。
• 研究发现系统性效应在高流量环境下对外星探测有影响，即使采用分子映射技术也是如此。

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GenCAD: Image-Conditioned Computer-Aided Design Generation with Transformer-Based Contrastive Representation and Diffusion Priors

Authors:Md Ferdous Alam, Faez Ahmed

The creation of manufacturable and editable 3D shapes through Computer-Aided Design (CAD) remains a highly manual and time-consuming task, hampered by the complex topology of boundary representations of 3D solids and unintuitive design tools. While most work in the 3D shape generation literature focuses on representations like meshes, voxels, or point clouds, practical engineering applications demand the modifiability and manufacturability of CAD models and the ability for multi-modal conditional CAD model generation. This paper introduces GenCAD, a generative model that employs autoregressive transformers with a contrastive learning framework and latent diffusion models to transform image inputs into parametric CAD command sequences, resulting in editable 3D shape representations. Extensive evaluations demonstrate that GenCAD significantly outperforms existing state-of-the-art methods in terms of the unconditional and conditional generations of CAD models. Additionally, the contrastive learning framework of GenCAD facilitates the retrieval of CAD models using image queries from large CAD databases, which is a critical challenge within the CAD community. Our results provide a significant step forward in highlighting the potential of generative models to expedite the entire design-to-production pipeline and seamlessly integrate different design modalities.

通过计算机辅助设计（CAD）创建可制造和可编辑的3D形状仍然是一项高度手动和耗时的任务，受到3D实体边界表示复杂拓扑和非直观设计工具的限制。虽然大多数关于三维形状生成的研究文献都集中在网格、体素或点云等表示方法上，但实际应用中的工程需求要求CAD模型的可修改性和可制造性，以及多模式条件CAD模型生成的能力。本文介绍了GenCAD，这是一种采用自回归变压器和对比学习框架以及潜在扩散模型的生成模型，能够将图像输入转换为参数化CAD命令序列，从而产生可编辑的3D形状表示。广泛评估表明，GenCAD在无条件和有条件生成CAD模型方面显著优于现有最先进的算法。此外，GenCAD的对比学习框架促进了使用图像查询从大型CAD数据库中检索CAD模型，这是CAD社区面临的一个关键挑战。我们的研究结果突显了生成模型在加快整个设计到生产流程并无缝集成不同设计模式方面的潜力，迈出了重要的一步。

论文及项目相关链接

PDF 24 pages, 13 figures

Summary

本文介绍了GenCAD，一种利用对比学习框架和潜在扩散模型的生成模型，能够将图像输入转换为参数化CAD命令序列，生成可编辑的3D形状表示。它显著提高了CAD模型的无条件与条件生成能力，并能通过图像查询从大型CAD数据库中检索模型，为设计到生产流程的优化和不同设计模式的无缝集成提供了潜力。

Key Takeaways

1. GenCAD是一种采用对比学习框架和潜在扩散模型的生成模型，能转化图像输入为参数化CAD命令序列。
2. GenCAD提高了CAD模型的无条件和有条件生成能力。
3. GenCAD能通过图像查询从大型CAD数据库中检索模型。
4. 该方法解决了传统CAD设计中手动操作复杂、耗时的问题。
5. GenCAD具有模性可修改性和可制造性，适应了实际工程应用的需求。
6. GenCAD为优化整个设计到生产的流程提供了潜力。

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