For time-domain astronomy, it is crucial to frequently image celestial objects at specific depths within a predetermined cadence. To fulfill these scientific demands, scientists globally have started or planned the development of non-interferometric telescope arrays in recent years. Due to the numerous parameters involved in configuring these arrays, there is a need for an automated optimization framework that selects parameter sets to satisfy scientific needs while minimizing costs. In this paper, we introduce such a framework, which integrates optical design software, an exposure time calculator, and an optimization algorithm, to balance the observation capabilities and the cost of optical telescope arrays. Neural networks are utilized to speed up results retrieval of the system with different configurations. We use the SiTian project as a case study to demonstrate the framework’s effectiveness, showing that this approach can aid scientists in selecting optimal parameter sets. The code for this framework is published in the China Virtual Observatory PaperData Repository, enabling users to optimize parameters for various non-interferometric telescope array projects.
{"title":"An optimization framework for wide-field small aperture telescope arrays used in sky surveys","authors":"Wennan Xiang, Peng Jia, Zhengyang Li, Jifeng Liu, Zhenyu Ying, Zeyu Bai","doi":"10.1007/s10686-025-10004-0","DOIUrl":"10.1007/s10686-025-10004-0","url":null,"abstract":"<div><p>For time-domain astronomy, it is crucial to frequently image celestial objects at specific depths within a predetermined cadence. To fulfill these scientific demands, scientists globally have started or planned the development of non-interferometric telescope arrays in recent years. Due to the numerous parameters involved in configuring these arrays, there is a need for an automated optimization framework that selects parameter sets to satisfy scientific needs while minimizing costs. In this paper, we introduce such a framework, which integrates optical design software, an exposure time calculator, and an optimization algorithm, to balance the observation capabilities and the cost of optical telescope arrays. Neural networks are utilized to speed up results retrieval of the system with different configurations. We use the SiTian project as a case study to demonstrate the framework’s effectiveness, showing that this approach can aid scientists in selecting optimal parameter sets. The code for this framework is published in the China Virtual Observatory PaperData Repository, enabling users to optimize parameters for various non-interferometric telescope array projects.</p></div>","PeriodicalId":551,"journal":{"name":"Experimental Astronomy","volume":"59 3","pages":""},"PeriodicalIF":2.7,"publicationDate":"2025-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143913918","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Gamma-ray bursts (GRBs) are among the most energetic phenomena in the universe, and their observation has significantly advanced with the development of space-based gamma-ray telescopes. The Gamma-Ray Integrated Detectors (GRID) mission has initiated a nanosatellite constellation capable of all-sky GRB monitoring, deploying 12 detector payloads in low Earth orbit and collecting its first batch of scientific data. For GRB analysis, dedicated detector response matrices (DRMs) were individually constructed for each detector using Monte Carlo simulations and ground calibration. To further validate detector performance under real operational conditions, cross-calibration with existing space missions offers a robust validation. Herein, cross-calibration between the GRID detectors and the Fermi’s Gamma-ray Burst Monitor (GBM) was performed through joint spectral analysis. The excellent agreement between the instruments validates the accuracy of GRID’s DRMs and the reliability of its scientific data. For nanosatellite constellations like GRID, cross-calibration through orbital observations involving multiple distributed detector payloads is a crucial tool for ensuring uniformity and verifying overall performance of such systems.
{"title":"Cross-calibration of GRID via correlative spectral analysis of GRBs","authors":"Zirui Yang, Chenyu Wang, Hanwen Lin, Xiaofan Pan, Qize Liu, Xutao Zheng, Huaizhong Gao, Longhao Li, Qidong Wang, Jianping Cheng, Zhi Zeng, Ming Zeng, Hua Feng, Binbin Zhang, Zhonghai Wang, Rong Zhou, Yuanyuan Liu, Lin Lin, Jiayong Zhong, Jianyong Jiang, Wentao Han, Yang Tian, Benda Xu","doi":"10.1007/s10686-025-10002-2","DOIUrl":"10.1007/s10686-025-10002-2","url":null,"abstract":"<div><p>Gamma-ray bursts (GRBs) are among the most energetic phenomena in the universe, and their observation has significantly advanced with the development of space-based gamma-ray telescopes. The Gamma-Ray Integrated Detectors (GRID) mission has initiated a nanosatellite constellation capable of all-sky GRB monitoring, deploying 12 detector payloads in low Earth orbit and collecting its first batch of scientific data. For GRB analysis, dedicated detector response matrices (DRMs) were individually constructed for each detector using Monte Carlo simulations and ground calibration. To further validate detector performance under real operational conditions, cross-calibration with existing space missions offers a robust validation. Herein, cross-calibration between the GRID detectors and the Fermi’s Gamma-ray Burst Monitor (GBM) was performed through joint spectral analysis. The excellent agreement between the instruments validates the accuracy of GRID’s DRMs and the reliability of its scientific data. For nanosatellite constellations like GRID, cross-calibration through orbital observations involving multiple distributed detector payloads is a crucial tool for ensuring uniformity and verifying overall performance of such systems.</p></div>","PeriodicalId":551,"journal":{"name":"Experimental Astronomy","volume":"59 3","pages":""},"PeriodicalIF":2.7,"publicationDate":"2025-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10686-025-10002-2.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143908731","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-05-06DOI: 10.1007/s10686-025-10000-4
Enric Palle, Katia Biazzo, Emeline Bolmont, Paul Mollière, Katja Poppenhaeger, Jayne Birkby, Matteo Brogi, Gael Chauvin, Andrea Chiavassa, Jens Hoeijmakers, Emmanuel Lellouch, Christophe Lovis, Roberto Maiolino, Lisa Nortmann, Hannu Parviainen, Lorenzo Pino, Martin Turbet, Jesse Weder, Simon Albrecht, Simone Antoniucci, Susana C. Barros, Andre Beaudoin, Bjorn Benneke, Isabelle Boisse, Aldo S. Bonomo, Francesco Borsa, Alexis Brandeker, Wolfgang Brandner, Lars A. Buchhave, Anne-Laure Cheffot, Robin Deborde, Florian Debras, Rene Doyon, Paolo Di Marcantonio, Paolo Giacobbe, Jonay I. González Hernández, Ravit Helled, Laura Kreidberg, Pedro Machado, Jesus Maldonado, Alessandro Marconi, B. L. Canto Martins, Adriano Miceli, Christoph Mordasini, Mamadou N’Diaye, Andrzej Niedzielski, Brunella Nisini, Livia Origlia, Celine Peroux, Alexander G. M. Pietrow, Enrico Pinna, Emily Rauscher, Sabine Reffert, Cristina Rodríguez-López, Philippe Rousselot, Nicoletta Sanna, Nuno C. Santos, Adrien Simonnin, Alejandro Suárez Mascareño, Alessio Zanutta, Maria Rosa Zapatero-Osorio, Mathias Zechmeister
In the past decade the study of exoplanet atmospheres at high-spectral resolution, via transmission/emission spectroscopy and cross-correlation techniques for atomic/molecular mapping, has become a powerful and consolidated methodology. The current limitation is the signal-to-noise ratio that one can obtain during a planetary transit, which is in turn ultimately limited by telescope size. This limitation will be overcome by ANDES, an optical and near-infrared high-resolution spectrograph for the Extremely Large Telescope, which is currently in Phase B development. ANDES will be a powerful transformational instrument for exoplanet science. It will enable the study of giant planet atmospheres, allowing not only an exquisite determination of atmospheric composition, but also the study of isotopic compositions, dynamics and weather patterns, mapping the planetary atmospheres and probing atmospheric formation and evolution models. The unprecedented angular resolution of ANDES, will also allow us to explore the initial conditions in which planets form in proto-planetary disks. The main science case of ANDES, however, is the study of small, rocky exoplanet atmospheres, including the potential for biomarker detections, and the ability to reach this science case is driving its instrumental design. Here we discuss our simulations and the observing strategies to achieve this specific science goal. Since ANDES will be operational at the same time as NASA’s JWST and ESA’s ARIEL missions, it will provide enormous synergies in the characterization of planetary atmospheres at high and low spectral resolution. Moreover, ANDES will be able to probe for the first time the atmospheres of several giant and small planets in reflected light. In particular, we show how ANDES will be able to unlock the reflected light atmospheric signal of a golden sample of nearby non-transiting habitable zone earth-sized planets within a few tenths of nights, a scientific objective that no other currently approved astronomical facility will be able to reach.
{"title":"Ground-breaking exoplanet science with the ANDES spectrograph at the ELT","authors":"Enric Palle, Katia Biazzo, Emeline Bolmont, Paul Mollière, Katja Poppenhaeger, Jayne Birkby, Matteo Brogi, Gael Chauvin, Andrea Chiavassa, Jens Hoeijmakers, Emmanuel Lellouch, Christophe Lovis, Roberto Maiolino, Lisa Nortmann, Hannu Parviainen, Lorenzo Pino, Martin Turbet, Jesse Weder, Simon Albrecht, Simone Antoniucci, Susana C. Barros, Andre Beaudoin, Bjorn Benneke, Isabelle Boisse, Aldo S. Bonomo, Francesco Borsa, Alexis Brandeker, Wolfgang Brandner, Lars A. Buchhave, Anne-Laure Cheffot, Robin Deborde, Florian Debras, Rene Doyon, Paolo Di Marcantonio, Paolo Giacobbe, Jonay I. González Hernández, Ravit Helled, Laura Kreidberg, Pedro Machado, Jesus Maldonado, Alessandro Marconi, B. L. Canto Martins, Adriano Miceli, Christoph Mordasini, Mamadou N’Diaye, Andrzej Niedzielski, Brunella Nisini, Livia Origlia, Celine Peroux, Alexander G. M. Pietrow, Enrico Pinna, Emily Rauscher, Sabine Reffert, Cristina Rodríguez-López, Philippe Rousselot, Nicoletta Sanna, Nuno C. Santos, Adrien Simonnin, Alejandro Suárez Mascareño, Alessio Zanutta, Maria Rosa Zapatero-Osorio, Mathias Zechmeister","doi":"10.1007/s10686-025-10000-4","DOIUrl":"10.1007/s10686-025-10000-4","url":null,"abstract":"<div><p>In the past decade the study of exoplanet atmospheres at high-spectral resolution, via transmission/emission spectroscopy and cross-correlation techniques for atomic/molecular mapping, has become a powerful and consolidated methodology. The current limitation is the signal-to-noise ratio that one can obtain during a planetary transit, which is in turn ultimately limited by telescope size. This limitation will be overcome by ANDES, an optical and near-infrared high-resolution spectrograph for the Extremely Large Telescope, which is currently in Phase B development. ANDES will be a powerful transformational instrument for exoplanet science. It will enable the study of giant planet atmospheres, allowing not only an exquisite determination of atmospheric composition, but also the study of isotopic compositions, dynamics and weather patterns, mapping the planetary atmospheres and probing atmospheric formation and evolution models. The unprecedented angular resolution of ANDES, will also allow us to explore the initial conditions in which planets form in proto-planetary disks. The main science case of ANDES, however, is the study of small, rocky exoplanet atmospheres, including the potential for biomarker detections, and the ability to reach this science case is driving its instrumental design. Here we discuss our simulations and the observing strategies to achieve this specific science goal. Since ANDES will be operational at the same time as NASA’s JWST and ESA’s ARIEL missions, it will provide enormous synergies in the characterization of planetary atmospheres at high and low spectral resolution. Moreover, ANDES will be able to probe for the first time the atmospheres of several giant and small planets in reflected light. In particular, we show how ANDES will be able to unlock the reflected light atmospheric signal of a golden sample of nearby non-transiting habitable zone earth-sized planets within a few tenths of nights, a scientific objective that no other currently approved astronomical facility will be able to reach.</p></div>","PeriodicalId":551,"journal":{"name":"Experimental Astronomy","volume":"59 3","pages":""},"PeriodicalIF":2.7,"publicationDate":"2025-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10686-025-10000-4.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143908666","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-05-06DOI: 10.1007/s10686-025-09999-3
Andrea Bocchieri, Lorenzo V. Mugnai, Enzo Pascale, Andreas Papageorgiou, Angèle Syty, Angelos Tsiaras, Paul Eccleston, Giorgio Savini, Giovanna Tinetti, Renaud Broquet, Patrick Chapman, Gianfranco Sechi
The European Space Agency’s Ariel mission, scheduled for launch in 2029, aims to conduct the first large-scale survey of atmospheric spectra of transiting exoplanets. Ariel achieves the high photometric stability on transit timescales required to detect the spectroscopic signatures of chemical elements with a payload design optimized for transit photometry that either eliminates known systematics or allows for their removal during data processing without significantly degrading or biasing the detection. Jitter in the spacecraft’s line of sight is a source of disturbance when measuring the spectra of exoplanet atmospheres. We describe an improved algorithm for de-jittering Ariel observations simulated in the time domain. We opt for an approach based on the spatial information on the Point Spread Function (PSF) distortion from jitter to detrend the optical signals. The jitter model is based on representative simulations from Airbus Defence and Space, the prime contractor for the Ariel service module. We investigate the precision and biases of the retrieved atmospheric spectra from the jitter-detrended observations. At long wavelengths, the photometric stability of the Ariel spectrometer is already dominated by photon noise. Our algorithm effectively de-jitters both photometric and spectroscopic data, ensuring that the performance remains photon noise-limited across the entire Ariel spectrum, fully compliant with mission requirements. This work contributes to the development of the data reduction pipeline for Ariel, aligning with its scientific goals, and may also benefit other astronomical telescopes and instrumentation.
{"title":"De-jittering Ariel: An optimized algorithm","authors":"Andrea Bocchieri, Lorenzo V. Mugnai, Enzo Pascale, Andreas Papageorgiou, Angèle Syty, Angelos Tsiaras, Paul Eccleston, Giorgio Savini, Giovanna Tinetti, Renaud Broquet, Patrick Chapman, Gianfranco Sechi","doi":"10.1007/s10686-025-09999-3","DOIUrl":"10.1007/s10686-025-09999-3","url":null,"abstract":"<div><p>The European Space Agency’s <i>Ariel</i> mission, scheduled for launch in 2029, aims to conduct the first large-scale survey of atmospheric spectra of transiting exoplanets. <i>Ariel</i> achieves the high photometric stability on transit timescales required to detect the spectroscopic signatures of chemical elements with a payload design optimized for transit photometry that either eliminates known systematics or allows for their removal during data processing without significantly degrading or biasing the detection. Jitter in the spacecraft’s line of sight is a source of disturbance when measuring the spectra of exoplanet atmospheres. We describe an improved algorithm for de-jittering <i>Ariel</i> observations simulated in the time domain. We opt for an approach based on the spatial information on the Point Spread Function (PSF) distortion from jitter to detrend the optical signals. The jitter model is based on representative simulations from Airbus Defence and Space, the prime contractor for the <i>Ariel</i> service module. We investigate the precision and biases of the retrieved atmospheric spectra from the jitter-detrended observations. At long wavelengths, the photometric stability of the <i>Ariel</i> spectrometer is already dominated by photon noise. Our algorithm effectively de-jitters both photometric and spectroscopic data, ensuring that the performance remains photon noise-limited across the entire <i>Ariel</i> spectrum, fully compliant with mission requirements. This work contributes to the development of the data reduction pipeline for <i>Ariel</i>, aligning with its scientific goals, and may also benefit other astronomical telescopes and instrumentation.</p></div>","PeriodicalId":551,"journal":{"name":"Experimental Astronomy","volume":"59 3","pages":""},"PeriodicalIF":2.7,"publicationDate":"2025-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10686-025-09999-3.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143908665","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-04-22DOI: 10.1007/s10686-025-09994-8
A. Colin, O. Muñoz, F. J. García-Izquierdo, E. Frattin, J. Martikainen, Z. Gray, J. L. Ramos, J. Jiménez, A. Tobaruela, J. M. Gómez-López, I. Bustamante, J. C. Gómez, F. Moreno, A. Marzo
We present a design of an acoustic levitator composed of 35 ultrasonic transducers operating at 40 kHz configured to form a spherical cavity. The acoustic radiation force measured experimentally in the center of the cavity is ({{varvec{F}}}_{rad}approx 9.6 mN), enough for levitating spheres as well as irregular particles of different materials of up to ~ 50 mg. Levitation tests have been performed with particles of different geometries and compositions, including liquid droplets and minerals relevant in studies of atmospheric aerosol and cosmic dust. This device has been deployed in the center of a polar nephelometer set-up to conduct studies of light scattering by irregular solid particles and liquid droplets. Test experiments have been carried out using a 1.5 mm diameter NBK- 7 glass sphere, for which three elements of the scattering matrix have been measured as functions of the scattering angle using a 647 nm diode laser. Mie theory calculations of the scattering matrix elements at this wavelength agree well with the measurements, demonstrating the functionality of the whole device.
{"title":"An acoustic levitator design for suspending cosmic dust analogues and aerosol particles in light scattering experiments","authors":"A. Colin, O. Muñoz, F. J. García-Izquierdo, E. Frattin, J. Martikainen, Z. Gray, J. L. Ramos, J. Jiménez, A. Tobaruela, J. M. Gómez-López, I. Bustamante, J. C. Gómez, F. Moreno, A. Marzo","doi":"10.1007/s10686-025-09994-8","DOIUrl":"10.1007/s10686-025-09994-8","url":null,"abstract":"<div><p>We present a design of an acoustic levitator composed of 35 ultrasonic transducers operating at 40 <i>kHz</i> configured to form a spherical cavity. The acoustic radiation force measured experimentally in the center of the cavity is <span>({{varvec{F}}}_{rad}approx 9.6 mN)</span>, enough for levitating spheres as well as irregular particles of different materials of up to ~ 50 <i>mg</i>. Levitation tests have been performed with particles of different geometries and compositions, including liquid droplets and minerals relevant in studies of atmospheric aerosol and cosmic dust. This device has been deployed in the center of a polar nephelometer set-up to conduct studies of light scattering by irregular solid particles and liquid droplets. Test experiments have been carried out using a 1.5 <i>mm</i> diameter NBK- 7 glass sphere, for which three elements of the scattering matrix have been measured as functions of the scattering angle using a 647 <i>nm</i> diode laser. Mie theory calculations of the scattering matrix elements at this wavelength agree well with the measurements, demonstrating the functionality of the whole device.</p></div>","PeriodicalId":551,"journal":{"name":"Experimental Astronomy","volume":"59 3","pages":""},"PeriodicalIF":2.7,"publicationDate":"2025-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10686-025-09994-8.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143856494","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-04-22DOI: 10.1007/s10686-025-09998-4
Hao Chang, Ming Zeng, Di Wang, Hua Feng, Yang Tian, Ge Ma, Xiaofan Pan, Chen Li, Zhongming Wang, Xin Zhuo, Xutao Zheng, Yulan Li
High-performance pixelated CZT detectors that achieve 3D position sensitivity are promising candidates for use in Compton imaging telescopes. We proposed to use pixelated CZT detectors in the MeV Astrophysical Spectroscopic Surveyor (MASS), which is a large area Compton telescope. Nevertheless, the presence of high-energy protons in space can lead to radiation damage in pixelated CZT detectors, causing their performance to degrade gradually. Using non-ionizing energy loss (NIEL), this study develops a method that quantitatively evaluates the radiation damage of detectors in space. To verify the method, this study irradiated two (2times 2times 1text { cm}^3) pixelated CZT detectors with 100 MeV protons at fluences ranging from (3times 10^7text { p}^+/text {cm}^2) to ( 3times 10^9text { p}^+/text {cm}^2) under two bias sets. When the proton fluence reaches (3 times 10^9 text { p}^+/text {cm}^2), the energy resolution of the detectors significantly deteriorates to (3.8%) at 511 keV (FWHM/E), even after post-correction. Finally, this study provides engineering considerations for their application in space.
{"title":"Research on the proton-induced radiation damage of pixelated CdZnTe detectors for space applications","authors":"Hao Chang, Ming Zeng, Di Wang, Hua Feng, Yang Tian, Ge Ma, Xiaofan Pan, Chen Li, Zhongming Wang, Xin Zhuo, Xutao Zheng, Yulan Li","doi":"10.1007/s10686-025-09998-4","DOIUrl":"10.1007/s10686-025-09998-4","url":null,"abstract":"<div><p>High-performance pixelated CZT detectors that achieve 3D position sensitivity are promising candidates for use in Compton imaging telescopes. We proposed to use pixelated CZT detectors in the MeV Astrophysical Spectroscopic Surveyor (MASS), which is a large area Compton telescope. Nevertheless, the presence of high-energy protons in space can lead to radiation damage in pixelated CZT detectors, causing their performance to degrade gradually. Using non-ionizing energy loss (NIEL), this study develops a method that quantitatively evaluates the radiation damage of detectors in space. To verify the method, this study irradiated two <span>(2times 2times 1text { cm}^3)</span> pixelated CZT detectors with 100 MeV protons at fluences ranging from <span>(3times 10^7text { p}^+/text {cm}^2)</span> to <span>( 3times 10^9text { p}^+/text {cm}^2)</span> under two bias sets. When the proton fluence reaches <span>(3 times 10^9 text { p}^+/text {cm}^2)</span>, the energy resolution of the detectors significantly deteriorates to <span>(3.8%)</span> at 511 keV (FWHM/E), even after post-correction. Finally, this study provides engineering considerations for their application in space.</p></div>","PeriodicalId":551,"journal":{"name":"Experimental Astronomy","volume":"59 3","pages":""},"PeriodicalIF":2.7,"publicationDate":"2025-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143856493","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-04-21DOI: 10.1007/s10686-025-09985-9
Heike Rauer, Conny Aerts, Juan Cabrera, Magali Deleuil, Anders Erikson, Laurent Gizon, Mariejo Goupil, Ana Heras, Thomas Walloschek, Jose Lorenzo-Alvarez, Filippo Marliani, César Martin-Garcia, J. Miguel Mas-Hesse, Laurence O’Rourke, Hugh Osborn, Isabella Pagano, Giampaolo Piotto, Don Pollacco, Roberto Ragazzoni, Gavin Ramsay, Stéphane Udry, Thierry Appourchaux, Willy Benz, Alexis Brandeker, Manuel Güdel, Eduardo Janot-Pacheco, Petr Kabath, Hans Kjeldsen, Michiel Min, Nuno Santos, Alan Smith, Juan-Carlos Suarez, Stephanie C. Werner, Alessio Aboudan, Manuel Abreu, Lorena Acuña, Moritz Adams, Vardan Adibekyan, Laura Affer, François Agneray, Craig Agnor, Victor Aguirre Børsen-Koch, Saad Ahmed, Suzanne Aigrain, Ashraf Al-Bahlawan, Ma de los Angeles Alcacera Gil, Eleonora Alei, Silvia Alencar, Richard Alexander, Julia Alfonso-Garzón, Yann Alibert, Carlos Allende Prieto, Leonardo Almeida, Roi Alonso Sobrino, Giuseppe Altavilla, Christian Althaus, Luis Alonso Alvarez Trujillo, Anish Amarsi, Matthias Ammler-von Eiff, Eduardo Amôres, Laerte Andrade, Alexandros Antoniadis-Karnavas, Carlos António, Beatriz Aparicio del Moral, Matteo Appolloni, Claudio Arena, David Armstrong, Jose Aroca Aliaga, Martin Asplund, Jeroen Audenaert, Natalia Auricchio, Pedro Avelino, Ann Baeke, Kevin Baillié, Ana Balado, Pau Ballber Balagueró, Andrea Balestra, Warrick Ball, Herve Ballans, Jerome Ballot, Caroline Barban, Gaële Barbary, Mauro Barbieri, Sebastià Barceló Forteza, Adrian Barker, Paul Barklem, Sydney Barnes, David Barrado Navascues, Oscar Barragan, Clément Baruteau, Sarbani Basu, Frederic Baudin, Philipp Baumeister, Daniel Bayliss, Michael Bazot, Paul G. Beck, Kevin Belkacem, Earl Bellinger, Serena Benatti, Othman Benomar, Diane Bérard, Maria Bergemann, Maria Bergomi, Pierre Bernardo, Katia Biazzo, Andrea Bignamini, Lionel Bigot, Nicolas Billot, Martin Binet, David Biondi, Federico Biondi, Aaron C. Birch, Bertram Bitsch, Paz Victoria Bluhm Ceballos, Attila Bódi, Zsófia Bognár, Isabelle Boisse, Emeline Bolmont, Alfio Bonanno, Mariangela Bonavita, Andrea Bonfanti, Xavier Bonfils, Rosaria Bonito, Aldo Stefano Bonomo, Anko Börner, Sudeshna Boro Saikia, Elisa Borreguero Martín, Francesco Borsa, Luca Borsato, Diego Bossini, Francois Bouchy, Gwenaël Boué, Rodrigo Boufleur, Patrick Boumier, Vincent Bourrier, Dominic M. Bowman, Enrico Bozzo, Louisa Bradley, John Bray, Alessandro Bressan, Sylvain Breton, Daniele Brienza, Ana Brito, Matteo Brogi, Beverly Brown, David J. A. Brown, Allan Sacha Brun, Giovanni Bruno, Michael Bruns, Lars A. Buchhave, Lisa Bugnet, Gaël Buldgen, Patrick Burgess, Andrea Busatta, Giorgia Busso, Derek Buzasi, José A. Caballero, Alexandre Cabral, Juan-Francisco Cabrero Gomez, Flavia Calderone, Robert Cameron, Andrew Cameron, Tiago Campante, Néstor Campos Gestal, Bruno Leonardo Canto Martins, Christophe Cara, Ludmila Carone, Josep Manel Carrasco, Luca Casagrande, Sarah L. Casewell, Santi Cassisi, Marco Castellani, Matthieu Castro, Claude Catala, Irene Catalán Fernández, Márcio Catelan, Heather Cegla, Chiara Cerruti, Virginie Cessa, Merieme Chadid, William Chaplin, Stephane Charpinet, Cristina Chiappini, Simone Chiarucci, Andrea Chiavassa, Simonetta Chinellato, Giovanni Chirulli, Jørgen Christensen-Dalsgaard, Ross Church, Antonio Claret, Cathie Clarke, Riccardo Claudi, Lionel Clermont, Hugo Coelho, Joao Coelho, Fabrizio Cogato, Josep Colomé, Mathieu Condamin, Fernando Conde García, Simon Conseil, Thierry Corbard, Alexandre C. M. Correia, Enrico Corsaro, Rosario Cosentino, Jean Costes, Andrea Cottinelli, Giovanni Covone, Orlagh L. Creevey, Aurelien Crida, Szilard Csizmadia, Margarida Cunha, Patrick Curry, Jefferson da Costa, Francys da Silva, Shweta Dalal, Mario Damasso, Cilia Damiani, Francesco Damiani, Maria Liduina das Chagas, Melvyn Davies, Guy Davies, Ben Davies, Gary Davison, Leandro de Almeida, Francesca de Angeli, Susana Cristina Cabral de Barros, Izan de CastroLeão, Daniel Brito de Freitas, Marcia Cristina de Freitas, Domitilla De Martino, José Renan de Medeiros, Luiz Alberto de Paula, Álvaro de Pedraza Gómez, Jelle de Plaa, Joris De Ridder, Morgan Deal, Leen Decin, Hans Deeg, Scilla Degl’Innocenti, Sebastien Deheuvels, Carlos del Burgo, Fabio Del Sordo, Elisa Delgado-Mena, Olivier Demangeon, Tilmann Denk, Aliz Derekas, Jean-Michel Desert, Silvano Desidera, Marc Dexet, Marcella Di Criscienzo, Anna Maria Di Giorgio, Maria Pia Di Mauro, Federico Jose Diaz Rial, José-Javier Díaz-García, Marco Dima, Giacomo Dinuzzi, Odysseas Dionatos, Elisa Distefano, Jose-Dias do Nascimento Jr., Albert Domingo, Valentina D’Orazi, Caroline Dorn, Lauren Doyle, Elena Duarte, Florent Ducellier, Luc Dumaye, Xavier Dumusque, Marc-Antoine Dupret, Patrick Eggenberger, David Ehrenreich, Philipp Eigmüller, Johannes Eising, Marcelo Emilio, Kjell Eriksson, Marco Ermocida, Riano Isidoro Escate Giribaldi, Yoshi Eschen, Lucía Espinosa Yáñez, Inês Estrela, Dafydd Wyn Evans, Damian Fabbian, Michele Fabrizio, João Pedro Faria, Maria Farina, Jacopo Farinato, Dax Feliz, Sofia Feltzing, Thomas Fenouillet, Miguel Fernández, Lorenza Ferrari, Sylvio Ferraz-Mello, Fabio Fialho, Agnes Fienga, Pedro Figueira, Laura Fiori, Ettore Flaccomio, Mauro Focardi, Steve Foley, Jean Fontignie, Dominic Ford, Karin Fornazier, Thierry Forveille, Luca Fossati, Rodrigo de Marca Franca, Lucas Franco da Silva, Antonio Frasca, Malcolm Fridlund, Marco Furlan, Sarah-Maria Gabler, Marco Gaido, Andrew Gallagher, Paloma I. Gallego Sempere, Emanuele Galli, Rafael A. García, Antonio García Hernández, Antonio Garcia Munoz, Hugo García-Vázquez, Rafael Garrido Haba, Patrick Gaulme, Nicolas Gauthier, Charlotte Gehan, Matthew Gent, Iskra Georgieva, Mauro Ghigo, Edoardo Giana, Samuel Gill, Leo Girardi, Silvia Giuliatti Winter, Giovanni Giusi, João Gomes da Silva, Luis Jorge Gómez Zazo, Juan Manuel Gomez-Lopez, Jonay Isai González Hernández, Kevin Gonzalez Murillo, Alejandro Gonzalo Melchor, Nicolas Gorius, Pierre-Vincent Gouel, Duncan Goulty, Valentina Granata, John Lee Grenfell, Denis Grießbach, Emmanuel Grolleau, Salomé Grouffal, Sascha Grziwa, Mario Giuseppe Guarcello, Loïc Gueguen, Eike Wolf Guenther, Terrasa Guilhem, Lucas Guillerot, Tristan Guillot, Pierre Guiot, Pascal Guterman, Antonio Gutiérrez, Fernando Gutiérrez-Canales, Janis Hagelberg, Jonas Haldemann, Cassandra Hall, Rasmus Handberg, Ian Harrison, Diana L. Harrison, Johann Hasiba, Carole A. Haswell, Petra Hatalova, Artie Hatzes, Raphaelle Haywood, Guillaume Hébrard, Frank Heckes, Ulrike Heiter, Saskia Hekker, René Heller, Christiane Helling, Krzysztof Helminiak, Simon Hemsley, Kevin Heng, Konstantin Herbst , Aline Hermans, JJ Hermes, Nadia Hidalgo Torres, Natalie Hinkel, David Hobbs, Simon Hodgkin, Karl Hofmann, Saeed Hojjatpanah, Günter Houdek, Daniel Huber, Joseph Huesler, Alain Hui-Bon-Hoa, Rik Huygen, Duc-Dat Huynh, Nicolas Iro, Jonathan Irwin, Mike Irwin, André Izidoro, Sophie Jacquinod, Nicholas Emborg Jannsen, Markus Janson, Harald Jeszenszky, Chen Jiang, Antonio José Jimenez Mancebo, Paula Jofre, Anders Johansen, Cole Johnston, Geraint Jones, Thomas Kallinger, Szilárd Kálmán, Thomas Kanitz, Marie Karjalainen, Raine Karjalainen, Christoffer Karoff, Steven Kawaler, Daisuke Kawata, Arnoud Keereman, David Keiderling, Tom Kennedy, Matthew Kenworthy, Franz Kerschbaum, Mark Kidger, Flavien Kiefer, Christian Kintziger, Kristina Kislyakova, László Kiss, Peter Klagyivik, Hubert Klahr, Jonas Klevas, Oleg Kochukhov, Ulrich Köhler, Ulrich Kolb, Alexander Koncz, Judith Korth, Nadiia Kostogryz, Gábor Kovács, József Kovács, Oleg Kozhura, Natalie Krivova, Arūnas Kuĉinskas, Ilyas Kuhlemann, Friedrich Kupka, Wouter Laauwen, Alvaro Labiano, Nadege Lagarde, Philippe Laget, Gunter Laky, Kristine Wai Fun Lam, Michiel Lambrechts, Helmut Lammer, Antonino Francesco Lanza, Alessandro Lanzafame, Mariel Lares Martiz, Jacques Laskar, Henrik Latter, Tony Lavanant, Alastair Lawrenson, Cecilia Lazzoni, Agnes Lebre, Yveline Lebreton, Alain Lecavelier des Etangs, Katherine Lee, Zoe Leinhardt, Adrien Leleu, Monika Lendl, Giuseppe Leto, Yves Levillain, Anne-Sophie Libert, Tim Lichtenberg, Roxanne Ligi, Francois Lignieres, Jorge Lillo-Box, Jeffrey Linsky, John Scige Liu, Dominik Loidolt, Yuying Longval, Ilídio Lopes, Andrea Lorenzani, Hans-Guenter Ludwig, Mikkel Lund, Mia Sloth Lundkvist, Xavier Luri, Carla Maceroni, Sean Madden, Nikku Madhusudhan, Antonio Maggio, Christian Magliano, Demetrio Magrin, Laurent Mahy, Olaf Maibaum, LeeRoy Malac-Allain, Jean-Christophe Malapert, Luca Malavolta, Jesus Maldonado, Elena Mamonova, Louis Manchon, Andres Manjón, Andrew Mann, Giacomo Mantovan, Luca Marafatto, Marcella Marconi, Rosemary Mardling, Paola Marigo, Silvia Marinoni, Rico Marques, Joao Pedro Marques, Paola Maria Marrese, Douglas Marshall, Silvia Martínez Perales, David Mary, Francesco Marzari, Eduard Masana, Andrina Mascher, Stéphane Mathis, Savita Mathur, Iris Martín Vodopivec, Ana Carolina Mattiuci Figueiredo, Pierre F. L. Maxted, Tsevi Mazeh, Stephane Mazevet, Francesco Mazzei, James McCormac, Paul McMillan, Lucas Menou, Thibault Merle, Farzana Meru, Dino Mesa, Sergio Messina, Szabolcs Mészáros, Nadége Meunier, Jean-Charles Meunier, Giuseppina Micela, Harald Michaelis, Eric Michel, Mathias Michielsen, Tatiana Michtchenko, Andrea Miglio, Yamila Miguel, David Milligan, Giovanni Mirouh, Morgan Mitchell, Nuno Moedas, Francesca Molendini, László Molnár, Joey Mombarg, Josefina Montalban, Marco Montalto, Mário J. P. F. G. Monteiro, Francisco Montoro Sánchez, Juan Carlos Morales, Maria Morales-Calderon, Alessandro Morbidelli, Christoph Mordasini, Chrystel Moreau, Thierry Morel, Giuseppe Morello, Julien Morin, Annelies Mortier, Benoît Mosser, Denis Mourard, Olivier Mousis, Claire Moutou, Nami Mowlavi, Andrés Moya, Prisca Muehlmann, Philip Muirhead, Matteo Munari, Ilaria Musella, Alexander James Mustill, Nicolas Nardetto, Domenico Nardiello, Norio Narita, Valerio Nascimbeni, Anna Nash, Coralie Neiner, Richard P. Nelson, Nadine Nettelmann, Gianalfredo Nicolini, Martin Nielsen, Sami-Matias Niemi, Lena Noack, Arlette Noels-Grotsch, Anthony Noll, Azib Norazman, Andrew J. Norton, Benard Nsamba, Aviv Ofir, Gordon Ogilvie, Terese Olander, Christian Olivetto, Göran Olofsson, Joel Ong, Sergio Ortolani, Mahmoudreza Oshagh, Harald Ottacher, Roland Ottensamer, Rhita-Maria Ouazzani, Sijme-Jan Paardekooper, Emanuele Pace, Miriam Pajas, Ana Palacios, Gaelle Palandri, Enric Palle, Carsten Paproth, Vanderlei Parro, Hannu Parviainen, Javier Pascual Granado, Vera Maria Passegger, Carmen Pastor-Morales, Martin Pätzold, May Gade Pedersen, David Pena Hidalgo, Francesco Pepe, Filipe Pereira, Carina M. Persson, Martin Pertenais, Gisbert Peter, Antoine C. Petit, Pascal Petit, Stefania Pezzuto, Gabriele Pichierri, Adriano Pietrinferni, Fernando Pinheiro, Marc Pinsonneault, Emese Plachy, Philippe Plasson, Bertrand Plez, Katja Poppenhaeger, Ennio Poretti, Elisa Portaluri, Jordi Portell, Gustavo Frederico Porto de Mello, Julien Poyatos, Francisco J. Pozuelos, Pier Giorgio Prada Moroni, Dumitru Pricopi, Loredana Prisinzano, Matthias Quade, Andreas Quirrenbach, Julio Arturo Rabanal Reina, Maria Cristina Rabello Soares, Gabriella Raimondo, Monica Rainer, Jose Ramón Rodón, Alejandro Ramón-Ballesta, Gonzalo Ramos Zapata, Stefanie Rätz, Christoph Rauterberg, Bob Redman, Ronald Redmer, Daniel Reese, Sara Regibo, Ansgar Reiners, Timo Reinhold, Christian Renie, Ignasi Ribas, Sergio Ribeiro, Thiago Pereira Ricciardi, Ken Rice, Olivier Richard, Marco Riello, Michel Rieutord, Vincenzo Ripepi, Guy Rixon, Steve Rockstein, José Ramón Rodón Ortiz, María Teresa Rodrigo Rodríguez, Alberto Rodríguez Amor, Luisa Fernanda Rodríguez Díaz, Juan Pablo Rodriguez Garcia, Julio Rodriguez-Gomez, Yannick Roehlly, Fernando Roig, Bárbara Rojas-Ayala, Tobias Rolf, Jakob Lysgaard Rørsted, Hugo Rosado, Giovanni Rosotti, Olivier Roth, Markus Roth, Alex Rousseau, Ian Roxburgh, Fabrice Roy, Pierre Royer, Kirk Ruane, Sergio Rufini Mastropasqua, Claudia Ruiz de Galarreta, Andrea Russi, Steven Saar, Melaine Saillenfest, Maurizio Salaris, Sebastien Salmon, Ippocratis Saltas, Réza Samadi, Aunia Samadi, Dominic Samra, Tiago Sanches da Silva, Miguel Andrés Sánchez Carrasco, Alexandre Santerne, Amaia Santiago Pé, Francesco Santoli, Ängela R. G. Santos, Rosario Sanz Mesa, Luis Manuel Sarro, Gaetano Scandariato, Martin Schäfer, Edward Schlafly, François-Xavier Schmider, Jean Schneider, Jesper Schou, Hannah Schunker, Gabriel Jörg Schwarzkopf, Aldo Serenelli, Dries Seynaeve, Yutong Shan, Alexander Shapiro, Russel Shipman, Daniela Sicilia, Maria Angeles Sierra sanmartin, Axelle Sigot, Kyle Silliman, Roberto Silvotti, Attila E. Simon, Ricardo Simoyama Napoli, Marek Skarka, Barry Smalley, Rodolfo Smiljanic, Samuel Smit, Alexis Smith, Leigh Smith, Ignas Snellen, Ádám Sódor, Frank Sohl, Sami K. Solanki, Francesca Sortino, Sérgio Sousa, John Southworth, Diogo Souto, Alessandro Sozzetti, Dimitris Stamatellos, Keivan Stassun, Manfred Steller, Dennis Stello, Beate Stelzer, Ulrike Stiebeler, Amalie Stokholm, Trude Storelvmo, Klaus Strassmeier, Paul Anthony Strøm, Antoine Strugarek, Sophia Sulis, Michal Švanda, László Szabados, Róbert Szabó, Gyula M. Szabó, Ewa Szuszkiewicz, Geert Jan Talens, Daniele Teti, Tom Theisen, Frédéric Thévenin, Anne Thoul, Didier Tiphene, Ruth Titz-Weider, Andrew Tkachenko, Daniel Tomecki, Jorge Tonfat, Nicola Tosi, Regner Trampedach, Gregor Traven, Amaury Triaud, Reidar Trønnes, Maria Tsantaki, Matthias Tschentscher, Arnaud Turin, Adam Tvaruzka, Bernd Ulmer, Solène Ulmer-Moll, Ceren Ulusoy, Gabriele Umbriaco, Diana Valencia, Marica Valentini, Adriana Valio, Ángel Luis Valverde Guijarro, Vincent Van Eylen, Valerie Van Grootel, Tim A. van Kempen, Timothy Van Reeth, Iris Van Zelst, Bart Vandenbussche, Konstantinos Vasiliou, Valeriy Vasilyev, David Vaz de Mascarenhas, Allona Vazan, Marina Vela Nunez, Eduardo Nunes Velloso, Rita Ventura, Paolo Ventura, Julia Venturini, Isabel Vera Trallero, Dimitri Veras, Eva Verdugo, Kuldeep Verma, Didier Vibert, Tobias Vicanek Martinez, Krisztián Vida, Arthur Vigan, Antonio Villacorta, Eva Villaver, Marcos Villaverde Aparicio, Valentina Viotto, Eduard Vorobyov, Sergey Vorontsov, Frank W. Wagner, Nicholas Walton, Dave Walton, Haiyang Wang, Rens Waters, Christopher Watson, Sven Wedemeyer, Angharad Weeks, Jörg Weingrill, Annita Weiss, Belinda Wendler, Richard West, Karsten Westerdorff, Pierre-Amaury Westphal, Peter Wheatley, Tim White, Amadou Whittaker, Kai Wickhusen, Thomas Wilson, James Windsor, Othon Winter, Mark Lykke Winther, Alistair Winton, Ulrike Witteck, Veronika Witzke, Peter Woitke, David Wolter, Günther Wuchterl, Mark Wyatt, Dan Yang, Jie Yu, Ricardo Zanmar Sanchez, María Rosa Zapatero Osorio, Mathias Zechmeister, Yixiao Zhou, Claas Ziemke, Konstanze Zwintz, Torsten Böhm, Léo Michel Dansac
PLATO (PLAnetary Transits and Oscillations of stars) is ESA’s M3 mission designed to detect and characterise extrasolar planets and perform asteroseismic monitoring of a large number of stars. PLATO will detect small planets (down to <2R(_textrm{Earth})) around bright stars (<11 mag), including terrestrial planets in the habitable zone of solar-like stars. With the complement of radial velocity observations from the ground, planets will be characterised for their radius, mass, and age with high accuracy (5%, 10%, 10% for an Earth-Sun combination respectively). PLATO will provide us with a large-scale catalogue of well-characterised small planets up to intermediate orbital periods, relevant for a meaningful comparison to planet formation theories and to better understand planet evolution. It will make possible comparative exoplanetology to place our Solar System planets in a broader context. In parallel, PLATO will study (host) stars using asteroseismology, allowing us to determine the stellar properties with high accuracy, substantially enhancing our knowledge of stellar structure and evolution. The payload instrument consists of 26 cameras with 12cm aperture each. For at least four years, the mission will perform high-precision photometric measurements. Here we review the science objectives, present PLATO‘s target samples and fields, provide an overview of expected core science performance as well as a description of the instrument and the mission profile towards the end of the serial production of the flight cameras. PLATO is scheduled for a launch date end 2026. This overview therefore provides a summary of the mission to the community in preparation of the upcoming operational phases.
PLATO（行星凌日和恒星振荡）是欧空局的M3任务，旨在探测和表征系外行星，并对大量恒星进行星震监测。PLATO将探测明亮恒星（11等）周围的小行星（低至＆lt；2R (_textrm{Earth})），包括类太阳恒星可居住区内的类地行星。在地面径向速度观测的补充下，行星的半径、质量和年龄将得到高精度的表征(5)%, 10%, 10% for an Earth-Sun combination respectively). PLATO will provide us with a large-scale catalogue of well-characterised small planets up to intermediate orbital periods, relevant for a meaningful comparison to planet formation theories and to better understand planet evolution. It will make possible comparative exoplanetology to place our Solar System planets in a broader context. In parallel, PLATO will study (host) stars using asteroseismology, allowing us to determine the stellar properties with high accuracy, substantially enhancing our knowledge of stellar structure and evolution. The payload instrument consists of 26 cameras with 12cm aperture each. For at least four years, the mission will perform high-precision photometric measurements. Here we review the science objectives, present PLATO‘s target samples and fields, provide an overview of expected core science performance as well as a description of the instrument and the mission profile towards the end of the serial production of the flight cameras. PLATO is scheduled for a launch date end 2026. This overview therefore provides a summary of the mission to the community in preparation of the upcoming operational phases.
{"title":"The PLATO mission","authors":"Heike Rauer, Conny Aerts, Juan Cabrera, Magali Deleuil, Anders Erikson, Laurent Gizon, Mariejo Goupil, Ana Heras, Thomas Walloschek, Jose Lorenzo-Alvarez, Filippo Marliani, César Martin-Garcia, J. Miguel Mas-Hesse, Laurence O’Rourke, Hugh Osborn, Isabella Pagano, Giampaolo Piotto, Don Pollacco, Roberto Ragazzoni, Gavin Ramsay, Stéphane Udry, Thierry Appourchaux, Willy Benz, Alexis Brandeker, Manuel Güdel, Eduardo Janot-Pacheco, Petr Kabath, Hans Kjeldsen, Michiel Min, Nuno Santos, Alan Smith, Juan-Carlos Suarez, Stephanie C. Werner, Alessio Aboudan, Manuel Abreu, Lorena Acuña, Moritz Adams, Vardan Adibekyan, Laura Affer, François Agneray, Craig Agnor, Victor Aguirre Børsen-Koch, Saad Ahmed, Suzanne Aigrain, Ashraf Al-Bahlawan, Ma de los Angeles Alcacera Gil, Eleonora Alei, Silvia Alencar, Richard Alexander, Julia Alfonso-Garzón, Yann Alibert, Carlos Allende Prieto, Leonardo Almeida, Roi Alonso Sobrino, Giuseppe Altavilla, Christian Althaus, Luis Alonso Alvarez Trujillo, Anish Amarsi, Matthias Ammler-von Eiff, Eduardo Amôres, Laerte Andrade, Alexandros Antoniadis-Karnavas, Carlos António, Beatriz Aparicio del Moral, Matteo Appolloni, Claudio Arena, David Armstrong, Jose Aroca Aliaga, Martin Asplund, Jeroen Audenaert, Natalia Auricchio, Pedro Avelino, Ann Baeke, Kevin Baillié, Ana Balado, Pau Ballber Balagueró, Andrea Balestra, Warrick Ball, Herve Ballans, Jerome Ballot, Caroline Barban, Gaële Barbary, Mauro Barbieri, Sebastià Barceló Forteza, Adrian Barker, Paul Barklem, Sydney Barnes, David Barrado Navascues, Oscar Barragan, Clément Baruteau, Sarbani Basu, Frederic Baudin, Philipp Baumeister, Daniel Bayliss, Michael Bazot, Paul G. Beck, Kevin Belkacem, Earl Bellinger, Serena Benatti, Othman Benomar, Diane Bérard, Maria Bergemann, Maria Bergomi, Pierre Bernardo, Katia Biazzo, Andrea Bignamini, Lionel Bigot, Nicolas Billot, Martin Binet, David Biondi, Federico Biondi, Aaron C. Birch, Bertram Bitsch, Paz Victoria Bluhm Ceballos, Attila Bódi, Zsófia Bognár, Isabelle Boisse, Emeline Bolmont, Alfio Bonanno, Mariangela Bonavita, Andrea Bonfanti, Xavier Bonfils, Rosaria Bonito, Aldo Stefano Bonomo, Anko Börner, Sudeshna Boro Saikia, Elisa Borreguero Martín, Francesco Borsa, Luca Borsato, Diego Bossini, Francois Bouchy, Gwenaël Boué, Rodrigo Boufleur, Patrick Boumier, Vincent Bourrier, Dominic M. Bowman, Enrico Bozzo, Louisa Bradley, John Bray, Alessandro Bressan, Sylvain Breton, Daniele Brienza, Ana Brito, Matteo Brogi, Beverly Brown, David J. A. Brown, Allan Sacha Brun, Giovanni Bruno, Michael Bruns, Lars A. Buchhave, Lisa Bugnet, Gaël Buldgen, Patrick Burgess, Andrea Busatta, Giorgia Busso, Derek Buzasi, José A. Caballero, Alexandre Cabral, Juan-Francisco Cabrero Gomez, Flavia Calderone, Robert Cameron, Andrew Cameron, Tiago Campante, Néstor Campos Gestal, Bruno Leonardo Canto Martins, Christophe Cara, Ludmila Carone, Josep Manel Carrasco, Luca Casagrande, Sarah L. Casewell, Santi Cassisi, Marco Castellani, Matthieu Castro, Claude Catala, Irene Catalán Fernández, Márcio Catelan, Heather Cegla, Chiara Cerruti, Virginie Cessa, Merieme Chadid, William Chaplin, Stephane Charpinet, Cristina Chiappini, Simone Chiarucci, Andrea Chiavassa, Simonetta Chinellato, Giovanni Chirulli, Jørgen Christensen-Dalsgaard, Ross Church, Antonio Claret, Cathie Clarke, Riccardo Claudi, Lionel Clermont, Hugo Coelho, Joao Coelho, Fabrizio Cogato, Josep Colomé, Mathieu Condamin, Fernando Conde García, Simon Conseil, Thierry Corbard, Alexandre C. M. Correia, Enrico Corsaro, Rosario Cosentino, Jean Costes, Andrea Cottinelli, Giovanni Covone, Orlagh L. Creevey, Aurelien Crida, Szilard Csizmadia, Margarida Cunha, Patrick Curry, Jefferson da Costa, Francys da Silva, Shweta Dalal, Mario Damasso, Cilia Damiani, Francesco Damiani, Maria Liduina das Chagas, Melvyn Davies, Guy Davies, Ben Davies, Gary Davison, Leandro de Almeida, Francesca de Angeli, Susana Cristina Cabral de Barros, Izan de CastroLeão, Daniel Brito de Freitas, Marcia Cristina de Freitas, Domitilla De Martino, José Renan de Medeiros, Luiz Alberto de Paula, Álvaro de Pedraza Gómez, Jelle de Plaa, Joris De Ridder, Morgan Deal, Leen Decin, Hans Deeg, Scilla Degl’Innocenti, Sebastien Deheuvels, Carlos del Burgo, Fabio Del Sordo, Elisa Delgado-Mena, Olivier Demangeon, Tilmann Denk, Aliz Derekas, Jean-Michel Desert, Silvano Desidera, Marc Dexet, Marcella Di Criscienzo, Anna Maria Di Giorgio, Maria Pia Di Mauro, Federico Jose Diaz Rial, José-Javier Díaz-García, Marco Dima, Giacomo Dinuzzi, Odysseas Dionatos, Elisa Distefano, Jose-Dias do Nascimento Jr., Albert Domingo, Valentina D’Orazi, Caroline Dorn, Lauren Doyle, Elena Duarte, Florent Ducellier, Luc Dumaye, Xavier Dumusque, Marc-Antoine Dupret, Patrick Eggenberger, David Ehrenreich, Philipp Eigmüller, Johannes Eising, Marcelo Emilio, Kjell Eriksson, Marco Ermocida, Riano Isidoro Escate Giribaldi, Yoshi Eschen, Lucía Espinosa Yáñez, Inês Estrela, Dafydd Wyn Evans, Damian Fabbian, Michele Fabrizio, João Pedro Faria, Maria Farina, Jacopo Farinato, Dax Feliz, Sofia Feltzing, Thomas Fenouillet, Miguel Fernández, Lorenza Ferrari, Sylvio Ferraz-Mello, Fabio Fialho, Agnes Fienga, Pedro Figueira, Laura Fiori, Ettore Flaccomio, Mauro Focardi, Steve Foley, Jean Fontignie, Dominic Ford, Karin Fornazier, Thierry Forveille, Luca Fossati, Rodrigo de Marca Franca, Lucas Franco da Silva, Antonio Frasca, Malcolm Fridlund, Marco Furlan, Sarah-Maria Gabler, Marco Gaido, Andrew Gallagher, Paloma I. Gallego Sempere, Emanuele Galli, Rafael A. García, Antonio García Hernández, Antonio Garcia Munoz, Hugo García-Vázquez, Rafael Garrido Haba, Patrick Gaulme, Nicolas Gauthier, Charlotte Gehan, Matthew Gent, Iskra Georgieva, Mauro Ghigo, Edoardo Giana, Samuel Gill, Leo Girardi, Silvia Giuliatti Winter, Giovanni Giusi, João Gomes da Silva, Luis Jorge Gómez Zazo, Juan Manuel Gomez-Lopez, Jonay Isai González Hernández, Kevin Gonzalez Murillo, Alejandro Gonzalo Melchor, Nicolas Gorius, Pierre-Vincent Gouel, Duncan Goulty, Valentina Granata, John Lee Grenfell, Denis Grießbach, Emmanuel Grolleau, Salomé Grouffal, Sascha Grziwa, Mario Giuseppe Guarcello, Loïc Gueguen, Eike Wolf Guenther, Terrasa Guilhem, Lucas Guillerot, Tristan Guillot, Pierre Guiot, Pascal Guterman, Antonio Gutiérrez, Fernando Gutiérrez-Canales, Janis Hagelberg, Jonas Haldemann, Cassandra Hall, Rasmus Handberg, Ian Harrison, Diana L. Harrison, Johann Hasiba, Carole A. Haswell, Petra Hatalova, Artie Hatzes, Raphaelle Haywood, Guillaume Hébrard, Frank Heckes, Ulrike Heiter, Saskia Hekker, René Heller, Christiane Helling, Krzysztof Helminiak, Simon Hemsley, Kevin Heng, Konstantin Herbst , Aline Hermans, JJ Hermes, Nadia Hidalgo Torres, Natalie Hinkel, David Hobbs, Simon Hodgkin, Karl Hofmann, Saeed Hojjatpanah, Günter Houdek, Daniel Huber, Joseph Huesler, Alain Hui-Bon-Hoa, Rik Huygen, Duc-Dat Huynh, Nicolas Iro, Jonathan Irwin, Mike Irwin, André Izidoro, Sophie Jacquinod, Nicholas Emborg Jannsen, Markus Janson, Harald Jeszenszky, Chen Jiang, Antonio José Jimenez Mancebo, Paula Jofre, Anders Johansen, Cole Johnston, Geraint Jones, Thomas Kallinger, Szilárd Kálmán, Thomas Kanitz, Marie Karjalainen, Raine Karjalainen, Christoffer Karoff, Steven Kawaler, Daisuke Kawata, Arnoud Keereman, David Keiderling, Tom Kennedy, Matthew Kenworthy, Franz Kerschbaum, Mark Kidger, Flavien Kiefer, Christian Kintziger, Kristina Kislyakova, László Kiss, Peter Klagyivik, Hubert Klahr, Jonas Klevas, Oleg Kochukhov, Ulrich Köhler, Ulrich Kolb, Alexander Koncz, Judith Korth, Nadiia Kostogryz, Gábor Kovács, József Kovács, Oleg Kozhura, Natalie Krivova, Arūnas Kuĉinskas, Ilyas Kuhlemann, Friedrich Kupka, Wouter Laauwen, Alvaro Labiano, Nadege Lagarde, Philippe Laget, Gunter Laky, Kristine Wai Fun Lam, Michiel Lambrechts, Helmut Lammer, Antonino Francesco Lanza, Alessandro Lanzafame, Mariel Lares Martiz, Jacques Laskar, Henrik Latter, Tony Lavanant, Alastair Lawrenson, Cecilia Lazzoni, Agnes Lebre, Yveline Lebreton, Alain Lecavelier des Etangs, Katherine Lee, Zoe Leinhardt, Adrien Leleu, Monika Lendl, Giuseppe Leto, Yves Levillain, Anne-Sophie Libert, Tim Lichtenberg, Roxanne Ligi, Francois Lignieres, Jorge Lillo-Box, Jeffrey Linsky, John Scige Liu, Dominik Loidolt, Yuying Longval, Ilídio Lopes, Andrea Lorenzani, Hans-Guenter Ludwig, Mikkel Lund, Mia Sloth Lundkvist, Xavier Luri, Carla Maceroni, Sean Madden, Nikku Madhusudhan, Antonio Maggio, Christian Magliano, Demetrio Magrin, Laurent Mahy, Olaf Maibaum, LeeRoy Malac-Allain, Jean-Christophe Malapert, Luca Malavolta, Jesus Maldonado, Elena Mamonova, Louis Manchon, Andres Manjón, Andrew Mann, Giacomo Mantovan, Luca Marafatto, Marcella Marconi, Rosemary Mardling, Paola Marigo, Silvia Marinoni, Rico Marques, Joao Pedro Marques, Paola Maria Marrese, Douglas Marshall, Silvia Martínez Perales, David Mary, Francesco Marzari, Eduard Masana, Andrina Mascher, Stéphane Mathis, Savita Mathur, Iris Martín Vodopivec, Ana Carolina Mattiuci Figueiredo, Pierre F. L. Maxted, Tsevi Mazeh, Stephane Mazevet, Francesco Mazzei, James McCormac, Paul McMillan, Lucas Menou, Thibault Merle, Farzana Meru, Dino Mesa, Sergio Messina, Szabolcs Mészáros, Nadége Meunier, Jean-Charles Meunier, Giuseppina Micela, Harald Michaelis, Eric Michel, Mathias Michielsen, Tatiana Michtchenko, Andrea Miglio, Yamila Miguel, David Milligan, Giovanni Mirouh, Morgan Mitchell, Nuno Moedas, Francesca Molendini, László Molnár, Joey Mombarg, Josefina Montalban, Marco Montalto, Mário J. P. F. G. Monteiro, Francisco Montoro Sánchez, Juan Carlos Morales, Maria Morales-Calderon, Alessandro Morbidelli, Christoph Mordasini, Chrystel Moreau, Thierry Morel, Giuseppe Morello, Julien Morin, Annelies Mortier, Benoît Mosser, Denis Mourard, Olivier Mousis, Claire Moutou, Nami Mowlavi, Andrés Moya, Prisca Muehlmann, Philip Muirhead, Matteo Munari, Ilaria Musella, Alexander James Mustill, Nicolas Nardetto, Domenico Nardiello, Norio Narita, Valerio Nascimbeni, Anna Nash, Coralie Neiner, Richard P. Nelson, Nadine Nettelmann, Gianalfredo Nicolini, Martin Nielsen, Sami-Matias Niemi, Lena Noack, Arlette Noels-Grotsch, Anthony Noll, Azib Norazman, Andrew J. Norton, Benard Nsamba, Aviv Ofir, Gordon Ogilvie, Terese Olander, Christian Olivetto, Göran Olofsson, Joel Ong, Sergio Ortolani, Mahmoudreza Oshagh, Harald Ottacher, Roland Ottensamer, Rhita-Maria Ouazzani, Sijme-Jan Paardekooper, Emanuele Pace, Miriam Pajas, Ana Palacios, Gaelle Palandri, Enric Palle, Carsten Paproth, Vanderlei Parro, Hannu Parviainen, Javier Pascual Granado, Vera Maria Passegger, Carmen Pastor-Morales, Martin Pätzold, May Gade Pedersen, David Pena Hidalgo, Francesco Pepe, Filipe Pereira, Carina M. Persson, Martin Pertenais, Gisbert Peter, Antoine C. Petit, Pascal Petit, Stefania Pezzuto, Gabriele Pichierri, Adriano Pietrinferni, Fernando Pinheiro, Marc Pinsonneault, Emese Plachy, Philippe Plasson, Bertrand Plez, Katja Poppenhaeger, Ennio Poretti, Elisa Portaluri, Jordi Portell, Gustavo Frederico Porto de Mello, Julien Poyatos, Francisco J. Pozuelos, Pier Giorgio Prada Moroni, Dumitru Pricopi, Loredana Prisinzano, Matthias Quade, Andreas Quirrenbach, Julio Arturo Rabanal Reina, Maria Cristina Rabello Soares, Gabriella Raimondo, Monica Rainer, Jose Ramón Rodón, Alejandro Ramón-Ballesta, Gonzalo Ramos Zapata, Stefanie Rätz, Christoph Rauterberg, Bob Redman, Ronald Redmer, Daniel Reese, Sara Regibo, Ansgar Reiners, Timo Reinhold, Christian Renie, Ignasi Ribas, Sergio Ribeiro, Thiago Pereira Ricciardi, Ken Rice, Olivier Richard, Marco Riello, Michel Rieutord, Vincenzo Ripepi, Guy Rixon, Steve Rockstein, José Ramón Rodón Ortiz, María Teresa Rodrigo Rodríguez, Alberto Rodríguez Amor, Luisa Fernanda Rodríguez Díaz, Juan Pablo Rodriguez Garcia, Julio Rodriguez-Gomez, Yannick Roehlly, Fernando Roig, Bárbara Rojas-Ayala, Tobias Rolf, Jakob Lysgaard Rørsted, Hugo Rosado, Giovanni Rosotti, Olivier Roth, Markus Roth, Alex Rousseau, Ian Roxburgh, Fabrice Roy, Pierre Royer, Kirk Ruane, Sergio Rufini Mastropasqua, Claudia Ruiz de Galarreta, Andrea Russi, Steven Saar, Melaine Saillenfest, Maurizio Salaris, Sebastien Salmon, Ippocratis Saltas, Réza Samadi, Aunia Samadi, Dominic Samra, Tiago Sanches da Silva, Miguel Andrés Sánchez Carrasco, Alexandre Santerne, Amaia Santiago Pé, Francesco Santoli, Ängela R. G. Santos, Rosario Sanz Mesa, Luis Manuel Sarro, Gaetano Scandariato, Martin Schäfer, Edward Schlafly, François-Xavier Schmider, Jean Schneider, Jesper Schou, Hannah Schunker, Gabriel Jörg Schwarzkopf, Aldo Serenelli, Dries Seynaeve, Yutong Shan, Alexander Shapiro, Russel Shipman, Daniela Sicilia, Maria Angeles Sierra sanmartin, Axelle Sigot, Kyle Silliman, Roberto Silvotti, Attila E. Simon, Ricardo Simoyama Napoli, Marek Skarka, Barry Smalley, Rodolfo Smiljanic, Samuel Smit, Alexis Smith, Leigh Smith, Ignas Snellen, Ádám Sódor, Frank Sohl, Sami K. Solanki, Francesca Sortino, Sérgio Sousa, John Southworth, Diogo Souto, Alessandro Sozzetti, Dimitris Stamatellos, Keivan Stassun, Manfred Steller, Dennis Stello, Beate Stelzer, Ulrike Stiebeler, Amalie Stokholm, Trude Storelvmo, Klaus Strassmeier, Paul Anthony Strøm, Antoine Strugarek, Sophia Sulis, Michal Švanda, László Szabados, Róbert Szabó, Gyula M. Szabó, Ewa Szuszkiewicz, Geert Jan Talens, Daniele Teti, Tom Theisen, Frédéric Thévenin, Anne Thoul, Didier Tiphene, Ruth Titz-Weider, Andrew Tkachenko, Daniel Tomecki, Jorge Tonfat, Nicola Tosi, Regner Trampedach, Gregor Traven, Amaury Triaud, Reidar Trønnes, Maria Tsantaki, Matthias Tschentscher, Arnaud Turin, Adam Tvaruzka, Bernd Ulmer, Solène Ulmer-Moll, Ceren Ulusoy, Gabriele Umbriaco, Diana Valencia, Marica Valentini, Adriana Valio, Ángel Luis Valverde Guijarro, Vincent Van Eylen, Valerie Van Grootel, Tim A. van Kempen, Timothy Van Reeth, Iris Van Zelst, Bart Vandenbussche, Konstantinos Vasiliou, Valeriy Vasilyev, David Vaz de Mascarenhas, Allona Vazan, Marina Vela Nunez, Eduardo Nunes Velloso, Rita Ventura, Paolo Ventura, Julia Venturini, Isabel Vera Trallero, Dimitri Veras, Eva Verdugo, Kuldeep Verma, Didier Vibert, Tobias Vicanek Martinez, Krisztián Vida, Arthur Vigan, Antonio Villacorta, Eva Villaver, Marcos Villaverde Aparicio, Valentina Viotto, Eduard Vorobyov, Sergey Vorontsov, Frank W. Wagner, Nicholas Walton, Dave Walton, Haiyang Wang, Rens Waters, Christopher Watson, Sven Wedemeyer, Angharad Weeks, Jörg Weingrill, Annita Weiss, Belinda Wendler, Richard West, Karsten Westerdorff, Pierre-Amaury Westphal, Peter Wheatley, Tim White, Amadou Whittaker, Kai Wickhusen, Thomas Wilson, James Windsor, Othon Winter, Mark Lykke Winther, Alistair Winton, Ulrike Witteck, Veronika Witzke, Peter Woitke, David Wolter, Günther Wuchterl, Mark Wyatt, Dan Yang, Jie Yu, Ricardo Zanmar Sanchez, María Rosa Zapatero Osorio, Mathias Zechmeister, Yixiao Zhou, Claas Ziemke, Konstanze Zwintz, Torsten Böhm, Léo Michel Dansac","doi":"10.1007/s10686-025-09985-9","DOIUrl":"10.1007/s10686-025-09985-9","url":null,"abstract":"<div><p>PLATO (PLAnetary Transits and Oscillations of stars) is ESA’s M3 mission designed to detect and characterise extrasolar planets and perform asteroseismic monitoring of a large number of stars. PLATO will detect small planets (down to <2R<span>(_textrm{Earth})</span>) around bright stars (<11 mag), including terrestrial planets in the habitable zone of solar-like stars. With the complement of radial velocity observations from the ground, planets will be characterised for their radius, mass, and age with high accuracy (5%, 10%, 10% for an Earth-Sun combination respectively). PLATO will provide us with a large-scale catalogue of well-characterised small planets up to intermediate orbital periods, relevant for a meaningful comparison to planet formation theories and to better understand planet evolution. It will make possible comparative exoplanetology to place our Solar System planets in a broader context. In parallel, PLATO will study (host) stars using asteroseismology, allowing us to determine the stellar properties with high accuracy, substantially enhancing our knowledge of stellar structure and evolution. The payload instrument consists of 26 cameras with 12cm aperture each. For at least four years, the mission will perform high-precision photometric measurements. Here we review the science objectives, present PLATO‘s target samples and fields, provide an overview of expected core science performance as well as a description of the instrument and the mission profile towards the end of the serial production of the flight cameras. PLATO is scheduled for a launch date end 2026. This overview therefore provides a summary of the mission to the community in preparation of the upcoming operational phases.</p></div>","PeriodicalId":551,"journal":{"name":"Experimental Astronomy","volume":"59 3","pages":""},"PeriodicalIF":2.7,"publicationDate":"2025-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10686-025-09985-9.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143852579","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-04-10DOI: 10.1007/s10686-025-09996-6
Fangyuan Chen, Liangping Tu, Hao Liu, Jian Zhao
Stellar spectral line indices are key tools for studying stellar physical properties and evolutionary processes, playing a significant role in inferring important stellar attributes such as Teff, [Fe/H], and logg. This paper proposes an automated method for measuring stellar spectral line indices, specifically targeting LAMOST-DR7 A-type stellar spectra. The method involves several key steps: spectral preprocessing, continuum normalization, baseline correction, baseline fitting, spectral line fitting, and line index calculation, all aimed at achieving accurate spectral line index measurements. Traditional methods often encounter significant errors when dealing with complex spectral backgrounds. In contrast, the proposed method incorporates a series of optimizations and has been validated for robustness through Monte Carlo simulations. Our observational results indicate that this method is highly feasible from the comparisons to the line indices officially released by LAMOST and those in the Lick spectral library. Further testing with simulated data further demonstrates the reliability of this approach. This method provides a promising tool for future astronomical observations and stellar evolution studies and holds broad application potential. It not only helps improve the accuracy of research into stellar physical properties but also offers a practical technical approach for analyzing the composition and evolutionary patterns of stellar populations in galaxies.
{"title":"A novel automated method for measuring spectral line indices of LAMOST-DR7 A-type stars","authors":"Fangyuan Chen, Liangping Tu, Hao Liu, Jian Zhao","doi":"10.1007/s10686-025-09996-6","DOIUrl":"10.1007/s10686-025-09996-6","url":null,"abstract":"<div><p>Stellar spectral line indices are key tools for studying stellar physical properties and evolutionary processes, playing a significant role in inferring important stellar attributes such as Teff, [Fe/H], and logg. This paper proposes an automated method for measuring stellar spectral line indices, specifically targeting LAMOST-DR7 A-type stellar spectra. The method involves several key steps: spectral preprocessing, continuum normalization, baseline correction, baseline fitting, spectral line fitting, and line index calculation, all aimed at achieving accurate spectral line index measurements. Traditional methods often encounter significant errors when dealing with complex spectral backgrounds. In contrast, the proposed method incorporates a series of optimizations and has been validated for robustness through Monte Carlo simulations. Our observational results indicate that this method is highly feasible from the comparisons to the line indices officially released by LAMOST and those in the Lick spectral library. Further testing with simulated data further demonstrates the reliability of this approach. This method provides a promising tool for future astronomical observations and stellar evolution studies and holds broad application potential. It not only helps improve the accuracy of research into stellar physical properties but also offers a practical technical approach for analyzing the composition and evolutionary patterns of stellar populations in galaxies.</p></div>","PeriodicalId":551,"journal":{"name":"Experimental Astronomy","volume":"59 2","pages":""},"PeriodicalIF":2.7,"publicationDate":"2025-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143809341","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-04-08DOI: 10.1007/s10686-025-09995-7
Alexandru Pop, Maria Crăciun
Estimation of the statistical significance of the peaks appearing in the spectra of various astronomical time series is essential for the detection of signals especially when they are contaminated by high levels of observational noise. In the present paper we consider a broader perspective which relies on two main aspects: (i) all the peaks have or may have significance and, therefore, (ii) we propose two complementary approaches to simultaneously supply estimates of the statistical significance of all the peaks of interest through Monte Carlo simulations. They are natural generalisations of the already used methods featured either by specificity in frequency or by specificity in amplitude/power of the peaks occurred in the spectrum. Three recently obtained radial velocity data on stars with orbiting exoplanets were used to illustrate these approaches: two G-type stars observed by the HARPS spectrograph (TOI-733, TOI-763) and an M-type star observed by the CARMENES spectrograph (Wolf 327). Some both interesting and useful features of the two considered statistical significances are also emphasised.
对各种天文时间序列光谱中出现的峰值的统计意义进行估算，对于信号的探测至关重要，尤其是在信号受到高水平观测噪声污染的情况下。在本文中，我们从更广阔的视角进行了思考，这主要依赖于两个方面：(i) 所有峰值都具有或可能具有重要意义，因此，(ii) 我们提出了两种互补的方法，通过蒙特卡罗模拟，同时对所有相关峰值的统计意义进行估算。这两种方法是对已经使用过的方法的自然概括，其特点是对频谱中出现的峰的频率或振幅/功率具有特异性。为了说明这些方法，我们使用了最近获得的三颗有系外行星运行的恒星的径向速度数据：HARPS 摄谱仪观测到的两颗 G 型恒星（TOI-733 和 TOI-763）和 CARMENES 摄谱仪观测到的一颗 M 型恒星（Wolf 327）。还强调了这两种统计意义的一些有趣和有用的特点。
{"title":"Two complementary approaches of the periodicity detection in astronomical time series","authors":"Alexandru Pop, Maria Crăciun","doi":"10.1007/s10686-025-09995-7","DOIUrl":"10.1007/s10686-025-09995-7","url":null,"abstract":"<div><p>Estimation of the statistical significance of the peaks appearing in the spectra of various astronomical time series is essential for the detection of signals especially when they are contaminated by high levels of observational noise. In the present paper we consider a broader perspective which relies on two main aspects: (i) all the peaks have or may have significance and, therefore, (ii) we propose two complementary approaches to simultaneously supply estimates of the statistical significance of all the peaks of interest through Monte Carlo simulations. They are natural generalisations of the already used methods featured either by <i>specificity in frequency</i> or by <i>specificity in amplitude/power</i> of the peaks occurred in the spectrum. Three recently obtained radial velocity data on stars with orbiting exoplanets were used to illustrate these approaches: two G-type stars observed by the HARPS spectrograph (TOI-733, TOI-763) and an M-type star observed by the CARMENES spectrograph (Wolf 327). Some both interesting and useful features of the two considered statistical significances are also emphasised.</p></div>","PeriodicalId":551,"journal":{"name":"Experimental Astronomy","volume":"59 2","pages":""},"PeriodicalIF":2.7,"publicationDate":"2025-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143793217","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-31DOI: 10.1007/s10686-025-09993-9
Y. Meng, J. Huang, D. Chen, K Y. Hu, Y. Zhang, L M. Zhai, Y H. Zou, Y L. Yu, Y Y. Li
In order to improve the energy reconstruction accuracy of gamma-ray events observed by ground-based array experiments, this work propose a new energy estimator based on machine learning (ML) algorithm to determine the energies of gamma ray induced air showers in the energy range between 1 TeV and 10 PeV. We carry out a full Monte Carlo (MC) simulation using the Tibet air shower array and underground muon detector array, located at an altitude of 4,300 m above sea level. The MC simulated gamma-ray data are used to extract characteristic parameters depicting the air shower information, which are then fed into the ML model for training on both high-energy data sets ((E >sim 10) TeV) and low-energy data sets ((E < 10) TeV). In our simulation data tests, we found that the ML method showed significant advantages over traditional energy estimators (S50, (N_e), and (sum rho )), with improved energy resolution for both low and high energy datasets. Compared to the traditional estimator, the energy resolution improves by approximately 30% for the inner array events and 55% for the outer array events at (E < 10) TeV. At around 100 TeV, the energy resolution for large zenith angle events in the outer array improves by approximately 20%. This work also found that while the energy resolution of events falling the inside array can only be slightly improved, however, events outside array and at large zenith shower clear improvements. Moreover, it is particularly noteworthy that the ML method has little difference in the energy resolution of the inner and outer array events. The enhanced energy resolution achieved through the machine learning method for outer array events reduces the limitations imposed by the observation area, resulting in an approximately 30% improvement in statistical events. This method is suitable for ground-based array experiments in gamma-ray astronomy, and provides some technical support for further study of the primary gamma-ray energy reconstruction.
为了提高地面阵列实验观测到的伽马射线事件的能量重建精度，本文提出了一种新的基于机器学习（ML）算法的能量估计器，用于确定1 TeV ～ 10 PeV能量范围内伽马射线诱导的空气簇射的能量。我们利用西藏空气淋点阵列和地下介子探测器阵列，在海拔4300米的高度进行了完整的蒙特卡罗（MC）模拟。MC模拟的伽马射线数据用于提取表征风淋信息的特征参数，然后将其输入ML模型，在高能数据集（(E >sim 10) TeV）和低能数据集（(E < 10) TeV）上进行训练。在我们的模拟数据测试中，我们发现ML方法比传统的能量估计器（S50, (N_e)和(sum rho )）具有显著的优势，并且在低能和高能数据集上都具有更高的能量分辨率。与传统估计器相比，能量分辨率提高了约30％% for the inner array events and 55% for the outer array events at (E < 10) TeV. At around 100 TeV, the energy resolution for large zenith angle events in the outer array improves by approximately 20%. This work also found that while the energy resolution of events falling the inside array can only be slightly improved, however, events outside array and at large zenith shower clear improvements. Moreover, it is particularly noteworthy that the ML method has little difference in the energy resolution of the inner and outer array events. The enhanced energy resolution achieved through the machine learning method for outer array events reduces the limitations imposed by the observation area, resulting in an approximately 30% improvement in statistical events. This method is suitable for ground-based array experiments in gamma-ray astronomy, and provides some technical support for further study of the primary gamma-ray energy reconstruction.
{"title":"Machine learning applications to energy reconstruction of gamma-ray showers for the Tibet AS(gamma ) experiment","authors":"Y. Meng, J. Huang, D. Chen, K Y. Hu, Y. Zhang, L M. Zhai, Y H. Zou, Y L. Yu, Y Y. Li","doi":"10.1007/s10686-025-09993-9","DOIUrl":"10.1007/s10686-025-09993-9","url":null,"abstract":"<div><p>In order to improve the energy reconstruction accuracy of gamma-ray events observed by ground-based array experiments, this work propose a new energy estimator based on machine learning (ML) algorithm to determine the energies of gamma ray induced air showers in the energy range between 1 TeV and 10 PeV. We carry out a full Monte Carlo (MC) simulation using the Tibet air shower array and underground muon detector array, located at an altitude of 4,300 m above sea level. The MC simulated gamma-ray data are used to extract characteristic parameters depicting the air shower information, which are then fed into the ML model for training on both high-energy data sets (<span>(E >sim 10)</span> TeV) and low-energy data sets (<span>(E < 10)</span> TeV). In our simulation data tests, we found that the ML method showed significant advantages over traditional energy estimators (S50, <span>(N_e)</span>, and <span>(sum rho )</span>), with improved energy resolution for both low and high energy datasets. Compared to the traditional estimator, the energy resolution improves by approximately 30% for the inner array events and 55% for the outer array events at <span>(E < 10)</span> TeV. At around 100 TeV, the energy resolution for large zenith angle events in the outer array improves by approximately 20%. This work also found that while the energy resolution of events falling the inside array can only be slightly improved, however, events outside array and at large zenith shower clear improvements. Moreover, it is particularly noteworthy that the ML method has little difference in the energy resolution of the inner and outer array events. The enhanced energy resolution achieved through the machine learning method for outer array events reduces the limitations imposed by the observation area, resulting in an approximately 30% improvement in statistical events. This method is suitable for ground-based array experiments in gamma-ray astronomy, and provides some technical support for further study of the primary gamma-ray energy reconstruction.</p></div>","PeriodicalId":551,"journal":{"name":"Experimental Astronomy","volume":"59 2","pages":""},"PeriodicalIF":2.7,"publicationDate":"2025-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10686-025-09993-9.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143740871","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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