RAS Techniques and Instruments最新文献_第2页

Micrometre-sized ice particles for planetary science experiments – CoPhyLab cryogenic granular sample production and storage 行星科学实验用微米级冰粒。CoPhyLab低温颗粒样品的生产和储存

RAS Techniques and Instruments Pub Date : 2023-11-03 DOI: 10.1093/rasti/rzad049

C Kreuzig, D Bischoff, N S Molinski, J N Brecher, A Kovalev, G Meier, J Oesert, S N Gorb, B Gundlach, J Blum

{"title":"Micrometre-sized ice particles for planetary science experiments – CoPhyLab cryogenic granular sample production and storage","authors":"C Kreuzig, D Bischoff, N S Molinski, J N Brecher, A Kovalev, G Meier, J Oesert, S N Gorb, B Gundlach, J Blum","doi":"10.1093/rasti/rzad049","DOIUrl":"https://doi.org/10.1093/rasti/rzad049","url":null,"abstract":"Abstract In this work, we present a comprehensive investigation into the production, characteristics, handling, and storage of micrometre-sized granular water-ice. The focus of this research is to provide well-characterized analogue samples for laboratory experiments simulating icy bodies found in the Solar System, particularly comets. These experiments are conducted as part of the CoPhyLab (Comet Physics Laboratory) project, an international collaboration aimed at studying cometary processes to gain insights into the underlying physics of cometary activity. Granular water-ice, along with other less abundant but more volatile ices, plays a crucial role in the ejection of gas and dust particles when comets approach the Sun. To facilitate large-scale laboratory experiments, an ice-particle machine was developed, capable of autonomously producing sufficient quantities of granular water-ice. Additionally, a cryogenic desiccator was designed to remove any residual moisture from the ice using liquid nitrogen. The resulting ice particles can be mixed with other materials and stored within the desiccator or a cryogenic transport can, enabling easy shipment to any laboratory, including via air transport. To analyse the ice grains, cryogenic scanning electron microscopy was employed to determine their particle shape and size-frequency distribution. These analyses contribute to a better understanding of the properties of granular water-ice and its behavior under cryogenic conditions, supporting the objectives of the CoPhyLab project.","PeriodicalId":500957,"journal":{"name":"RAS Techniques and Instruments","volume":"33 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135874505","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Lessons learned from the 1st Ariel Machine Learning Challenge: Correcting transiting exoplanet light curves for stellar spots 从第一届Ariel机器学习挑战中吸取的教训:纠正恒星黑子的凌日系外行星光曲线

RAS Techniques and Instruments Pub Date : 2023-11-02 DOI: 10.1093/rasti/rzad050

Nikolaos Nikolaou, Ingo P. Waldmann, Angelos Tsiaras, Mario Morvan, Billy Edwards, Kai Hou Yip, Giovanna Tinetti, Subhajit Sarkar, James M. Dawson, Vadim Borisov, Gjergji Kasneci, Matej Petkovic, Tomaz Stepisnik, Tarek Al-Ubaidi, Rachel Louise Bailey, Michael Granitzer, Sahib Julka, Roman Kern, Patrick Ofner, Stefan Wagner, Lukas Heppe, Mirko Bunse, Katharina Morik

{"title":"Lessons learned from the 1st Ariel Machine Learning Challenge: Correcting transiting exoplanet light curves for stellar spots","authors":"Nikolaos Nikolaou, Ingo P. Waldmann, Angelos Tsiaras, Mario Morvan, Billy Edwards, Kai Hou Yip, Giovanna Tinetti, Subhajit Sarkar, James M. Dawson, Vadim Borisov, Gjergji Kasneci, Matej Petkovic, Tomaz Stepisnik, Tarek Al-Ubaidi, Rachel Louise Bailey, Michael Granitzer, Sahib Julka, Roman Kern, Patrick Ofner, Stefan Wagner, Lukas Heppe, Mirko Bunse, Katharina Morik","doi":"10.1093/rasti/rzad050","DOIUrl":"https://doi.org/10.1093/rasti/rzad050","url":null,"abstract":"Abstract The last decade has witnessed a rapid growth of the field of exoplanet discovery and characterisation. However, several big challenges remain, many of which could be addressed using machine learning methodology. For instance, the most prolific method for detecting exoplanets and inferring several of their characteristics, transit photometry, is very sensitive to the presence of stellar spots. The current practice in the literature is to identify the effects of spots visually and correct for them manually or discard the affected data. This paper explores a first step towards fully automating the efficient and precise derivation of transit depths from transit light curves in the presence of stellar spots. The primary focus of the paper is to present in detail a diverse arsenal of methods for doing so. The methods and results we present were obtained in the context of the 1st Machine Learning Challenge organized for the European Space Agency’s upcoming Ariel mission. We first present the problem, the simulated Ariel-like data and outline the Challenge while identifying best practices for organizing similar challenges in the future. Finally, we present the solutions obtained by the top-5 winning teams, provide their code and discuss their implications. Successful solutions either construct highly non-linear (w.r.t. the raw data) models with minimal preprocessing –deep neural networks and ensemble methods– or amount to obtaining meaningful statistics from the light curves, constructing linear models on which yields comparably good predictive performance.","PeriodicalId":500957,"journal":{"name":"RAS Techniques and Instruments","volume":"19 4","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135874953","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 9

An investigation into the effect of exposing XMM-Newton’s Optical Monitor to the light of Jupiter 对xmm -牛顿光学监测器暴露在木星光线下的影响的研究

RAS Techniques and Instruments Pub Date : 2023-10-20 DOI: 10.1093/rasti/rzad048

S Sullivan, M J Page, A A Breeveld, S Rosen, A Talavera

引用次数: 0

Experimental and analytical methods for thermal infrared spectroscopy of complex dust coatings in a simulated asteroid environment 模拟小行星环境下复杂尘埃涂层热红外光谱的实验与分析方法

RAS Techniques and Instruments Pub Date : 2023-10-16 DOI: 10.1093/rasti/rzad047

C R Tinker, T D Glotch, L B Breitenfeld, A Ryan, L Li

{"title":"Experimental and analytical methods for thermal infrared spectroscopy of complex dust coatings in a simulated asteroid environment","authors":"C R Tinker, T D Glotch, L B Breitenfeld, A Ryan, L Li","doi":"10.1093/rasti/rzad047","DOIUrl":"https://doi.org/10.1093/rasti/rzad047","url":null,"abstract":"Abstract Airless bodies in the Solar System are commonly dominated by complex regolith mixtures consisting of coarse and fine particulates. These materials often manifest as coatings with the potential to modify or obscure the spectral signatures of underlying substrates. This can make accurate spectral analysis of surface materials challenging, especially for thermal infrared (TIR) techniques of which the spectral properties concurrently depend on grain size and albedo. Further complexity is presented when these coatings occur as discontinuous patterns in which some substrate is exposed and some is masked. Discontinuous patterns are distinguished by scale as having macroscopic or microscopic discontinuity, with the former being patches of homogeneous dust covering portions of the substrate and the latter being randomly distributed individual particles on the substrate. Investigations of asteroid (101955) Bennu’s surface by NASA’s Origins, Spectral Interpretation, Resource Identification, and Security-Regolith Explorer (OSIRIS-REx) have revealed contradictions between spectral and thermophysical results that are hypothesized to indicate the presence of thin and/or laterally discontinuous dust coatings. To address this, we constructed an environment chamber that enables the controlled deposition of size-regulated dust particles in coatings with varying continuity and thickness. TIR spectra of coated substrates acquired in a simulated asteroid environment (SAE) are used to investigate the extent to which dust coatings of different thicknesses and arrangements contribute to orbital spectral signatures of airless body surfaces.","PeriodicalId":500957,"journal":{"name":"RAS Techniques and Instruments","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136078622","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Paying attention to astronomical transients: Introducing the time-series transformer for photometric classification 关注天文瞬变:介绍用于光度分类的时间序列变压器

RAS Techniques and Instruments Pub Date : 2023-10-09 DOI: 10.1093/rasti/rzad046

Tarek Allam, Jason D McEwen

{"title":"Paying attention to astronomical transients: Introducing the time-series transformer for photometric classification","authors":"Tarek Allam, Jason D McEwen","doi":"10.1093/rasti/rzad046","DOIUrl":"https://doi.org/10.1093/rasti/rzad046","url":null,"abstract":"Future surveys such as the Legacy Survey of Space and Time (LSST) of the Vera C. Rubin Observatory will observe an order of magnitude more astrophysical transient events than any previous survey before. With this deluge of photometric data, it will be impossible for all such events to be classified by humans alone. Recent efforts have sought to leverage machine learning methods to tackle the challenge of astronomical transient classification, with ever improving success. Transformers are a recently developed deep learning architecture, first proposed for natural language processing, that have shown a great deal of recent success. In this work we develop a new transformer architecture, which uses multi-head self attention at its core, for general multi-variate time-series data. Furthermore, the proposed time-series transformer architecture supports the inclusion of an arbitrary number of additional features, while also offering interpretability. We apply the time-series transformer to the task of photometric classification, minimising the reliance of expert domain knowledge for feature selection, while achieving results comparable to state-of-the-art photometric classification methods. We achieve a logarithmic-loss of 0.507 on imbalanced data in a representative setting using data from the Photometric LSST Astronomical Time-Series Classification Challenge (PLAsTiCC). Moreover, we achieve a micro-averaged receiver operating characteristic area under curve of 0.98 and micro-averaged precision-recall area under curve of 0.87.","PeriodicalId":500957,"journal":{"name":"RAS Techniques and Instruments","volume":"85 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135045770","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

A reduction procedure and pipeline for the detection of trans-Neptunian objects using occultations 用掩星探测海王星外天体的简化程序和管道

RAS Techniques and Instruments Pub Date : 2023-01-01 DOI: 10.1093/rasti/rzad040

Guy Nir, Eran O Ofek, Barak Zackay

引用次数: 1

Tied-array beam localization of radio transients and pulsars 射电瞬变和脉冲星的束阵定位

RAS Techniques and Instruments Pub Date : 2023-01-01 DOI: 10.1093/rasti/rzad007

M C Bezuidenhout, C J Clark, R P Breton, B W Stappers, E D Barr, M Caleb, W Chen, F Jankowski, M Kramer, K Rajwade, M Surnis

引用次数: 2

A brief review of contrastive learning applied to astrophysics 对比学习在天体物理学中的应用综述

RAS Techniques and Instruments Pub Date : 2023-01-01 DOI: 10.1093/rasti/rzad028

Marc Huertas-Company, Regina Sarmiento, Johan H Knapen

引用次数: 0

Post-processing CHARIS integral field spectrograph data with pyKLIP 用pyKLIP对CHARIS积分场光谱仪数据进行后处理

RAS Techniques and Instruments Pub Date : 2023-01-01 DOI: 10.1093/rasti/rzad039

Minghan Chen, Jason J Wang, Timothy D Brandt, Thayne Currie, Julien Lozi, Jeffrey Chilcote, Maria Vincent

{"title":"Post-processing CHARIS integral field spectrograph data with pyKLIP","authors":"Minghan Chen, Jason J Wang, Timothy D Brandt, Thayne Currie, Julien Lozi, Jeffrey Chilcote, Maria Vincent","doi":"10.1093/rasti/rzad039","DOIUrl":"https://doi.org/10.1093/rasti/rzad039","url":null,"abstract":"Abstract We present the pyKLIP-CHARIS post-processing pipeline, a Python library that reduces high contrast imaging data for the CHARIS integral field spectrograph used with the SCExAO project on the Subaru Telescope. The pipeline is a part of the pyklip package, a Python library dedicated to the reduction of direct imaging data of exoplanets, brown dwarfs, and discs. For PSF subtraction, the pyKLIP-CHARIS post-processing pipeline relies on the core algorithms implemented in pyklip but uses image registration and calibrations that are unique to CHARIS. We describe the pipeline procedures, calibration results, and capabilities in processing imaging data acquired via the angular differential imaging and spectral differential imaging observing techniques. We showcase its performance on extracting spectra of injected synthetic point sources as well as compare the extracted spectra from real data sets on HD 33632 and HR 8799 to results in the literature. The pipeline is a python-based complement to the SCExAO project supported, widely used (and currently IDL-based) CHARIS data post-processing pipeline (CHARIS DPP) and provides an additional approach to reducing CHARIS data and extracting calibrated planet spectra.","PeriodicalId":500957,"journal":{"name":"RAS Techniques and Instruments","volume":"127 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135102199","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A set of codes for numerical convection and geodynamo calculations 一组用于数值对流和地球动力学计算的代码

RAS Techniques and Instruments Pub Date : 2023-01-01 DOI: 10.1093/rasti/rzad043

Steven J Gibbons, Ashley P Willis, Chris Davies, David Gubbins

引用次数: 0