检索结果-内蒙古大学图书馆

arXiv 2020年

作者： Pourpanah, Farhad Wang, Ran Lim, Chee Peng Wang, Xi-Zhao Yazdani, Danial College of Mathematics and Statistics Guangdong Key Lab. of Intelligent Information Processing Shenzhen University China Department of Electrical and Computer Engineering University of Windsor Canada College of Mathematics and Statistics Shenzhen Key Lab. of Advanced Machine Learning and Applications Guangdong Key Lab. of Intelligent Information Processing Shenzhen University China Institute for Intelligent Systems Research and Innovation Deakin University Australia College of Computer Science and Software Engineering Guangdong Key Lab. of Intelligent Information Processing Shenzhen University China School of Computer Science and Engineering Southern University of Science and Technology China

The Artificial Fish Swarm Algorithm (AFSA) is inspired by the ecological behaviors of fish schooling in nature, viz., the preying, swarming and following behaviors. Owing to a number of salient properties, which include flexibility, fast convergence, and insensitivity to the initial parameter settings, the family of AFSA has emerged as an effective Swarm Intelligence (SI) methodology that has been widely applied to solve real-world optimization problems. Since its introduction in 2002, many improved and hybrid AFSA models have been developed to tackle continuous, binary, and combinatorial optimization problems. This paper aims to present a concise review of the continuous AFSA, encompassing the original ASFA, its improvements and hybrid models, as well as their associated applications. We focus on articles published in high-quality journals since 2013. Our review provides insights into AFSA parameters modifications, procedure and sub-functions. The main reasons for these enhancements and the comparison results with other hybrid methods are discussed. In addition, hybrid, multi-objective and dynamic AFSA models that have been proposed to solve continuous optimization problems are elucidated. We also analyse possible AFSA enhancements and highlight future research directions for advancing AFSA-based models. Copyright © 2020, The Authors. All rights reserved.

关键词： Multiobjective optimization

来源：评论

学校读者我要写书评

暂无评论

A closed-loop all-electronic pixel-wise adaptive imaging system for high dynamic range video

arXiv

引用

arXiv 2019年

作者： Zhang, Jie [Jack] Newman, Jonathan P. Wang, Xiao Thakur, Chetan Singh Rattray, John Etienne-Cummings, Ralph Wilson, Matthew A. Picower Institute for Learning and Memory Department of Brain and Cognitive Sciences Massachusetts Institute of Technology CambridgeMA United States Department of Electrical and Computer Engineering Johns Hopkins University BaltimoreMD United States Department of Computer Science Boston University BostonMA United States Department of Electronic Systems Engineering Indian Institute of Science Bangalore India

We demonstrated a CMOS imaging system that adapts each pixels exposure and sampling rate to capture high dynamic range (HDR) videos. The system consist of a custom designed image sensor with pixel-wise exposure configurability and a real-time pixel exposure controller. These parts operate in a closed-loop to sample, detect and optimize each pixels exposure and sampling rate to minimize local regions underexposure, overexposure and motion blurring. Exposure control is implemented using all-integrated electronics without external optical modulation. This reduces overall system size and power consumption. The image sensor is implemented using a standard 130nm CMOS process while the exposure controller is implemented on a computer. We performed experiments under complex lighting and motion condition to test performance of the system, and demonstrate the benefit of pixel-wise adaptive imaging on the performance of computer vision tasks such as segmentation, motion estimation and object recognition. Copyright © 2019, The Authors. All rights reserved.

关键词： Pixels

来源：评论

学校读者我要写书评

暂无评论

The virtual lover： variable and easily guided 3D fish animations as an innovative tool inmate-choice experiments with sailfin mollies-I,Design and implementation

引用

Current Zoology 2017年第1期63卷 55-64页

作者： Klaus MuLLER Jevgen SMIELIK Jan-Marco HOTWOHL Stefanie GIERSZEWSKI Klaudia WITTE Klaus-Dieter KUHNERT Department of Electrical Engineering & Computer Science Institute of Real-Time Learning Systems University of Siegen HSIderlinstraBe 3 Siegen 57076 Germany Research Group of Ecology and Behavioral Biology Institute of Biology University of Siegen Adolf-Reichwein-Stral~e 2 Siegen 57068 Germany

Animal behavior researchers often face problems regarding standardization and reproducibility oftheir experiments. This has led to the partial substitution of live animals with artificial virtual stim-uli. In addition to standardization and reproducibility, virtual stimuli open new options for re-searchers since they are easily changeable in morphology and appearance, and their behavior canbe defined. In this article, a novel toolchain to conduct behavior experiments with fish is presentedby a case study in sailfin mollies Poecilia latipinna. As the toolchain holds many different and novelfeatures, it offers new possibilities for studies in behavioral animal research and promotes thestandardization of experiments. The presented method includes options to design, animate, andpresent virtual stimuli to live fish. The designing tool offers an easy and user-friendly way to definesize, coloration, and morphology of stimuli and moreover it is able to configure virtual stimuli ran-domly without any user influence. Furthermore, the toolchain brings a novel method to animatestimuli in a semiautomatic way with the help of a game controller. These created swimming pathscan be applied to different stimuli in real time. A presentation tool combines models and swim-ming paths regarding formerly defined playlists, and presents the stimuli onto 2 *** with live sailfin mollies validated the usage of the created virtual 3D fish models inmate-choice experiments.

关键词： computer animation, fish behavior, mate-choice experiment, research tool, virtual fish model.

来源：评论

学校读者我要写书评

暂无评论

Adaptive leader-follower formation control and obstacle avoidance via deep reinforcement learning

arXiv

引用

arXiv 2019年

作者： Zhou, Yanlin Lu, Fan Pu, George Ma, Xiyao Sun, Runhan Chen, Hsi-Yuan Li, Xiaolin Wu, Dapeng National Science Foundation Center for Big Learning Large-scale Intelligent Systems Laboratory Department of Electrical and Computer Engineering University of Florida GainesvilleFL United States Department of Mechanical and Aerospace Engineering University of Florida GainesvilleFL United States Amazon Robotics North Reading AI Institute Tongdun Technology

We propose a deep reinforcement learning (DRL) methodology for the tracking, obstacle avoidance, and formation control of nonholonomic robots. By separating vision-based control into a perception module and a controller module, we can train a DRL agent without sophisticated physics or 3D modeling. In addition, the modular framework averts daunting retrains of an image-to-action end-to-end neural network, and provides flexibility in transferring the controller to different robots. First, we train a convolutional neural network (CNN) to accurately localize in an indoor setting with dynamic foreground/background. Then, we design a new DRL algorithm named Momentum Policy Gradient (MPG) for continuous control tasks and prove its convergence. We also show that MPG is robust at tracking varying leader movements and can naturally be extended to problems of formation control. Leveraging reward shaping, features such as collision and obstacle avoidance can be easily integrated into a DRL controller. Copyright © 2019, The Authors. All rights reserved.

关键词： Deep learning

来源：评论

学校读者我要写书评

暂无评论

The virtual lover： variable and easily guided 3D fish animations as an innovative tool inmate-choice experiments with sailfinmollies-II. Validation

引用

Current Zoology 2017年第1期63卷 65-74页

作者： Stefanie GIERSZEWSKI Klaus MuLLER levgen SMIELIK Jan-Marco HUTWOHL Klaus-Dieter KUHNERT Klaudia WITTE Research Group of Ecology and Behavioral Biology Institute of Biology University of Siegen Adolf-Reichwein- StraBe 2 Siegen 57068 Germany Institute of Real-Time Learning Systems Department of ElectricalEngineering & Computer Science University of Siegen HSIderlinstraBe 3 Siegen 57076 Germany

The use of computer animation in behavioral research is a state-of-the-art method for designing andpresenting animated animals to live test animals. The major advantages of computer animations are：（1） the creation of animated animal stimuli with high variability of morphology and even behavior; （2）animated stimuli provide highly standardized, controlled and repeatable testing procedures; and （3）they allow a reduction in the number of live test animals regarding the 3Rs principle. But the use of ani-mated animals should be attended by a thorough validation for each test species to verify that behaviormeasured with live animals toward virtual animals can also be expected with natural stimuli. Here wepresent results on the validation of a custom-made simulation for animated 3D sailfin mollies Poecilialatipinna and show that responses of live test females were as strong to an animated fish as to a videoor a live male fish. Movement of an animated stimulus was important but female response was stron-ger toward a swimming 3D fish stimulus than to a ＂swimming＂ box. Moreover, male test fish wereable to discriminate between animated male and female stimuli; hence, rendering the animated 3D fisha useful tool in mate-choice experiments with sailfin mollies.

关键词： computer animation, fish behavior, mate-choice experiment, validation, virtual fish model.

来源：评论

学校读者我要写书评

暂无评论

Biomedical image analysis competitions: The state of current participation practice

arXiv

引用

arXiv 2022年

作者： Eisenmann, Matthias Reinke, Annika Weru, Vivienn Tizabi, Minu Dietlinde Isensee, Fabian Adler, Tim J. Godau, Patrick Cheplygina, Veronika Kozubek, Michal Maier-Hein, Klaus Jäger, Paul F. Kopp-Schneider, Annette Maier-Hein, Lena Ali, Sharib Gupta, Anubha Kybic, Jan Noble, Alison de Solórzano, Carlos Ortiz Pachade, Samiksha Petitjean, Caroline Sage, Daniel Wei, Donglai Wilden, Elizabeth Alapatt, Deepak Andrearczyk, Vincent Baid, Ujjwal Bakas, Spyridon Balu, Niranjan Bano, Sophia Bawa, Vivek Singh Bernal, Jorge Bodenstedt, Sebastian Casella, Alessandro Choi, Jinwook Commowick, Olivier Daum, Marie Depeursinge, Adrien Dorent, Reuben Egger, Jan Eichhorn, Hannah Engelhardt, Sandy Ganz, Melanie Girard, Gabriel Hansen, Lasse Heinrich, Mattias Heller, Nicholas Hering, Alessa Huaulmé, Arnaud Kim, Hyunjeong Li, Hongwei Bran Landman, Bennett Li, Jianning Ma, Jun Martel, Anne Martín-Isla, Carlos Menze, Bjoern Nwoye, Chinedu Innocent Oreiller, Valentin Padoy, Nicolas Pati, Sarthak Payette, Kelly Sudre, Carole van Wijnen, Kimberlin Vardazaryan, Armine Vercauteren, Tom Wagner, Martin Wang, Chuanbo Yap, Moi Hoon Yu, Zeyun Yuan, Chun Zenk, Maximilian Zia, Aneeq Zimmerer, David Bao, Rina Choi, Chanyeol Cohen, Andrew Dzyubachyk, Oleh Galdran, Adrian Gan, Tianyuan Guo, Tianqi Gupta, Pradyumna Haithami, Mahmood Ho, Edward Jang, Ikbeom Li, Zhili Luo, Zhengbo Lux, Filip Makrogiannis, Sokratis Müller, Dominik Oh, Young-Tack Pang, Subeen Pape, Constantin Polat, Gorkem Reed, Charlotte Rosalie Ryu, Kanghyun Scherr, Tim Thambawita, Vajira Wang, Haoyu Wang, Xinliang Xu, Kele Yeh, Hung Yeo, Doyeob Yuan, Yixuan Zeng, Yan Zhao, Xin Abbing, Julian Adam, Jannes Adluru, Nagesh Agethen, Niklas Ahmed, Salman Al Khalil, Yasmina Alenyà, Mireia Alhoniemi, Esa An, Chengyang Arega, Tewodros Weldebirhan Avisdris, Netanell Aydogan, Dogu Baran Bai, Yingbin Calisto, Maria Baldeon Basaran, Berke Doga Beetz, Marcel Bian, Hao Blansit, Kevin Bloch, Louise Bohnsack, Robert Bosticardo, Sara Breen, Jack Brudfors, Mikael Brüngel, Raphael Cabezas, Mariano Cacciola, Alb Heidelberg Division of Intelligent Medical Systems Germany Heidelberg HI Helmholtz Imaging Germany Faculty of Mathematics and Computer Science Heidelberg University Heidelberg Germany Heidelberg Division of Biostatistics Germany Heidelberg Division of Medical Image Computing Germany Heidelberg HI Applied Vision Lab Germany IT University of Copenhagen Copenhagen Denmark Centre for Biomedical Image Analysis Masaryk University Brno Czech Republic Heidelberg Interactive Machine Learning Group Germany Faculty of Mathematics and Computer Science and Medical Faculty Heidelberg University Heidelberg Germany NCT Heidelberg DKFZ University Hospital Heidelberg Germany School of Computing University of Leeds Leeds United Kingdom SBILab Department of ECE IIIT-Delhi India Faculty of Electrical Engineering Czech Technical University Prague Czech Republic Institute of Biomedical Engineering University of Oxford United Kingdom Center for Applied Medical Research Pamplona Spain Shri Guru Gobind Singhji Institute of Engineering and Technology Maharashtra Nanded India Université de Rouen Normandie France Lausanne Switzerland School of Engineering and Applied Science Harvard University United States ICube University of Strasbourg CNRS France Institute of Informatics School of Management HES-SO Valais-Wallis University of Applied Sciences and Arts Western Switzerland Techno-Pôle 3 Sierre3960 Switzerland Department of Nuclear Medicine and Molecular Imaging Lausanne University Hospital Rue du Bugnon 46 LausanneCH-1011 Switzerland University of Pennsylvania PhiladelphiaPA United States Department of Radiology University of Washington United States Wellcome EPSRC Centre for Interventional and Surgical Sciences University College London London United Kingdom Visual Artificial Intelligence Lab Oxford Brookes University Oxford United Kingdom Universitat Autònoma de Barcelona & Computer Vision Center Spain Dresden Fetscherstraße 74 PF 64 Dresden01307 Germany

The number of international benchmarking competitions is steadily increasing in various fields of machine learning (ML) research and practice. So far, however, little is known about the common practice as well as bottlenecks faced by the community in tackling the research questions posed. To shed light on the status quo of algorithm development in the specific field of biomedical imaging analysis, we designed an international survey that was issued to all participants of challenges conducted in conjunction with the IEEE ISBI 2021 and MICCAI 2021 conferences (80 competitions in total). The survey covered participants' expertise and working environments, their chosen strategies, as well as algorithm characteristics. A median of 72% challenge participants took part in the survey. According to our results, knowledge exchange was the primary incentive (70%) for participation, while the reception of prize money played only a minor role (16%). While a median of 80 working hours was spent on method development, a large portion of participants stated that they did not have enough time for method development (32%). 25% perceived the infrastructure to be a bottleneck. Overall, 94% of all solutions were deep learning-based. Of these, 84% were based on standard architectures. 43% of the respondents reported that the data samples (e.g., images) were too large to be processed at once. This was most commonly addressed by patch-based training (69%), downsampling (37%), and solving 3D analysis tasks as a series of 2D tasks. K-fold cross-validation on the training set was performed by only 37% of the participants and only 50% of the participants performed ensembling based on multiple identical models (61%) or heterogeneous models (39%). 48% of the respondents applied postprocessing steps. © 2022, CC BY.

关键词： Benchmarking

来源：评论

学校读者我要写书评

暂无评论

An In-Depth Look at TOI-3884b: a Super-Neptune Transiting a M4 Dwarf with Persistent Star Spot Crossings

arXiv

引用

arXiv 2023年

作者： Libby-Roberts, Jessica E. Schutte, Maria Hebb, Leslie Kanodia, Shubham Cañas, Caleb I. Stefánsson, Guðmundur Lin, Andrea S.J. Mahadevan, Suvrath Parts, Winter Powers, Luke Wisniewski, John Bender, Chad F. Cochran, William D. Diddams, Scott A. Everett, Mark E. Gupta, Arvind F. Halverson, Samuel Kobulnicky, Henry A. Kowalski, Adam F. Larsen, Alexander Monson, Andrew Ninan, Joe P. Parker, Brock A. Ramsey, Lawrence W. Robertson, Paul Schwab, Christian Swaby, Tera N. Terrien, Ryan C. Department of Astronomy & Astrophysics 525 Davey Laboratory The Pennsylvania State University University ParkPA16802 United States Center for Exoplanets and Habitable Worlds 525 Davey Laboratory The Pennsylvania State University University ParkPA16802 United States Homer L. Dodge Department of Physics and Astronomy University of Oklahoma 440 W. Brooks Street NormanOK73019 United States Physics Department Hobart and William Smith Colleges 300 Pulteney Street GenevaNY14456 United States Department of Astronomy Cornell University 245 East Ave IthacaNY14850 United States Earth and Planets Laboratory Carnegie Institution for Science 5241 Broad Branch Road NW WashingtonDC20015 United States NASA Goddard Space Flight Center 8800 Greenbelt Road GreenbeltMD20771 United States Department of Astrophysical Sciences Princeton University 4 Ivy Lane PrincetonNJ08540 United States ETH Zurich Institute for Particle Physics & Astrophysics Switzerland Department of Physics & Astronomy George Mason University 4400 University Drive MS 3F3 FairfaxVA22030 United States Steward Observatory The University of Arizona 933 N. Cherry Avenue TucsonAZ85721 United States McDonald Observatory Department of Astronomy The University of Texas Austin United States Center for Planetary Systems Habitability The University of Texas Austin United States Electrical Computer & Energy Engineering University of Colorado 425 UCB BoulderCO80309 United States Department of Physics University of Colorado 2000 Colorado Avenue BoulderCO80309 United States Time and Frequency Division National Institute of Standards and Technology 325 Broadway BoulderCO80305 United States NSF’s National Optical-Infrared Astronomy Research Laboratory 950 N. Cherry Ave. TucsonAZ85719 United States Jet Propulsion Laboratory California Institute of Technology 4800 Oak Grove Drive PasadenaCA91109 United States Department of Physics & Astronomy University of Wyoming LaramieWY82070 Uni

We perform an in-depth analysis of the recently validated TOI-3884 system, an M4 dwarf star with a transiting super-Neptune. Using high precision light curves obtained with the 3.5 m Apache Point Observatory and radial velocity observations with the Habitable-zone Planet Finder (HPF), we derive a planetary mass of 32.6+7.3−7.4M⨁ and radius of 6.4 ± 0.2 R⨁. We detect a distinct star spot crossing event occurring just after ingress and spanning half the transit for every transit. We determine this spot feature to be wavelength-dependent with the amplitude and duration evolving slightly over time. Best-fit star spot models show that TOI-3884b possesses a misaligned (λ = 75 ± 10◦) orbit which crosses a giant pole-spot. This system presents a rare opportunity for studies into the nature of both a misaligned super-Neptune and spot evolution on an active mid-M dwarf. © 2023, CC BY.

关键词： Orbits

来源：评论

学校读者我要写书评

暂无评论

Forecasting intracranial hypertension using multi-scale waveform metrics

arXiv

引用

arXiv 2019年

作者： Hüser, Matthias Kündig, Adrian Karlen, Walter De Luca, Valeria Jaggi, Martin Biomedical Informatics Group Department of Computer Science ETH Zürich Universitätstrasse 6 Zürich8092 Switzerland Mobile Health Systems Lab Institute of Robotics and Intelligent Systems Department of Health Sciences and Technology ETH Zürich Zürich8008 Switzerland Department of Information Technology and Electrical Engineering ETH Zürich Zürich8092 Switzerland Machine Learning & Optimization Lab EPFL Lausanne1015 Switzerland

Objective: Acute intracranial hypertension is an important risk factor of secondary brain damage after traumatic brain injury. Hypertensive episodes are often diagnosed reactively, leading to late detection and lost time for intervention planning. A pro-active approach that predicts critical events several hours ahead of time could assist in directing attention to patients at risk. Approach: We developed a prediction framework that forecasts onsets of acute intracranial hypertension in the next 8 hours. It jointly uses cerebral auto-regulation indices, spectral energies and morphological pulse metrics to describe the neurological state of the patient. One-minute base windows were compressed by computing signal metrics, and then stored in a multi-scale history, from which physiological features were derived. Main results: Our model predicted events up to 8 hours in advance with alarm recall rates of 90% at a precision of 30.3% in the MIMIC-III waveform database, improving upon two baselines from the literature. We found that features derived from high-frequency waveforms substantially improved the prediction performance over simple statistical summaries of low-frequency time serie1s, and each of the three feature classes contributed to the performance gain. The inclusion of long-term history up to 8 hours was especially important. Significance: Our results highlight the importance of information contained in high-frequency waveforms in the neurological intensive care unit. They could motivate future studies on pre-hypertensive patterns and the design of new alarm algorithms for critical events in the injured brain. Copyright © 2019, The Authors. All rights reserved.

关键词： Morphology

来源：评论

学校读者我要写书评

暂无评论

TOI-3757 b: A low density gas giant orbiting a solar-metallicity M dwarf

arXiv

引用

arXiv 2022年

作者： Kanodia, Shubham Libby-Roberts, Jessica Cañas, Caleb I. Ninan, Joe P. Mahadevan, Suvrath Stefansson, Gudmundur Lin, Andrea S.J. Jones, Sinclaire Monson, Andrew Parker, Brock A. Kobulnicky, Henry A. Swaby, Tera N. Powers, Luke Beard, Corey Bender, Chad F. Blake, Cullen H. Cochran, William D. Dong, Jiayin Diddams, Scott A. Fredrick, Connor Gupta, Arvind F. Halverson, Samuel Hearty, Fred Logsdon, Sarah E. Metcalf, Andrew J. McElwain, Michael W. Morley, Caroline Rajagopal, Jayadev Ramsey, Lawrence W. Robertson, Paul Roy, Arpita Schwab, Christian Terrien, Ryan C. Wisniewski, John Wright, Jason T. Department of Astronomy & Astrophysics 525 Davey Laboratory The Pennsylvania State University University ParkPA16802 United States Center for Exoplanets and Habitable Worlds 525 Davey Laboratory The Pennsylvania State University University ParkPA16802 United States Department of Astrophysical Sciences Princeton University 4 Ivy Lane PrincetonNJ08540 United States Department of Physics & Astronomy University of Wyoming LaramieWY82070 United States Department of Physics and Astronomy The University of California Irvine IrvineCA92697 United States Steward Observatory The University of Arizona 933 N. Cherry Avenue TucsonAZ85721 United States Department of Physics and Astronomy University of Pennsylvania 209 S 33rd St PhiladelphiaPA19104 United States McDonald Observatory Department of Astronomy The University of Texas Austin United States Center for Planetary Systems Habitability The University of Texas Austin United States Time and Frequency Division National Institute of Standards and Technology 325 Broadway BoulderCO80305 United States Department of Physics University of Colorado 2000 Colorado Avenue BoulderCO80309 United States Electrical Computer & Energy Engineering University of Colorado 425 UCB BoulderCO80309 United States Jet Propulsion Laboratory California Institute of Technology 4800 Oak Grove Drive PasadenaCA91109 United States NSF's National Optical-Infrared Astronomy Research Laboratory 950 N. Cherry Ave. TucsonAZ85719 United States Space Vehicles Directorate Air Force Research Laboratory 3550 Aberdeen Ave. SE Kirtland AFB NM87117 United States Time and Frequency Division National Institute of Technology 325 Broadway BoulderCO80305 United States Department of Physics University of Colorado Boulder 390 UCB BoulderCO80309 United States Exoplanets and Stellar Astrophysics Laboratory NASA Goddard Space Flight Center GreenbeltMD20771 United States Department of Astronomy The University of Texas Austin Uni

We present the discovery of a new Jovian-sized planet, TOI-3757 b, the lowest density transiting planet known to orbit an M dwarf (M0V). This planet was discovered around a solar-metallicity M dwarf, using TESS photometry and confirmed with precise radial velocities from HPF and NEID. With a planetary radius of 12.0−+0.40.5 R⊕ and mass of 85.3+8.8−8.7 M⊕, not only does this object add to the small sample of gas giants (∼ 10) around M dwarfs, but also, its low density (ρ = 0.27+0.05−0.04 g cm−3) provides an opportunity to test theories of planet formation. We present two hypotheses to explain its low density;first, we posit that the low metallicity of its stellar host (∼ 0.3 dex lower than the median metallicity of M dwarfs hosting gas giants) could have played a role in the delayed formation of a solid core massive enough to initiate runaway accretion. Second, using the eccentricity estimate of 0.14 ± 0.06 we determine it is also plausible for tidal heating to at least partially be responsible for inflating the radius of TOI-3757b b. The low density and large scale height of TOI-3757 b makes it an excellent target for transmission spectroscopy studies of atmospheric escape and composition (TSM ∼ 190). We use HPF to perform transmission spectroscopy of TOI-3757 b using the helium 10830 Å line. Doing this, we place an upper limit of 6.9 % (with 90% confidence) on the maximum depth of the absorption from the metastable transition of He at ∼ 10830 Å, which can help constraint the atmospheric mass loss rate in this energy limited regime. © 2022, CC BY.

关键词： Orbits

来源：评论

学校读者我要写书评

暂无评论

TOI-5205 b: A Short-period Jovian Planet Transiting a Mid-M Dwarf

arXiv

引用

arXiv 2022年

作者： Kanodia, Shubham Mahadevan, Suvrath Libby-Roberts, Jessica Stefansson, Gudmundur Cañas, Caleb I. Piette, Anjali A.A. Boss, Alan Teske, Johanna Chambers, John Zeimann, Greg Monson, Andrew Robertson, Paul Ninan, Joe P. Lin, Andrea S.J. Bender, Chad F. Cochran, William D. Diddams, Scott A. Gupta, Arvind F. Halverson, Samuel Hawley, Suzanne Kobulnicky, Henry A. Metcalf, Andrew J. Parker, Brock A. Powers, Luke Ramsey, Lawrence W. Roy, Arpita Schwab, Christian Swaby, Tera N. Terrien, Ryan C. Wisniewski, John Earth and Planets Laboratory Carnegie Institution for Science 5241 Broad Branch Road NW WashingtonDC20015 United States Department of Astronomy & Astrophysics 525 Davey Laboratory The Pennsylvania State University University ParkPA16802 United States Center for Exoplanets and Habitable Worlds 525 Davey Laboratory The Pennsylvania State University University ParkPA16802 United States ETH Zurich Institute for Particle Physics & Astrophysics Switzerland Henry Norris Russell Fellow United States Department of Astrophysical Sciences Princeton University 4 Ivy Lane PrincetonNJ08540 United States NASA Goddard Space Flight Center 8800 Greenbelt Road GreenbeltMD20771 United States Hobby Eberly Telescope University of Texas Austin AustinTX78712 United States Steward Observatory The University of Arizona 933 N. Cherry Avenue TucsonAZ85721 United States Department of Physics & Astronomy University of California Irvine IrvineCA92697 United States Department of Astronomy and Astrophysics Tata Institute of Fundamental Research Homi Bhabha Road Colaba Mumbai400005 India McDonald Observatory Department of Astronomy The University of Texas Austin United States Center for Planetary Systems Habitability The University of Texas Austin United States Electrical Computer & Energy Engineering University of Colorado 425 UCB BoulderCO80309 United States Department of Physics University of Colorado 2000 Colorado Avenue BoulderCO80309 United States Time and Frequency Division National Institute of Standards and Technology 325 Broadway BoulderCO80305 United States Jet Propulsion Laboratory 4800 Oak Grove Drive PasadenaCA91109 United States Department of Astronomy University of Washington Box 351580 SeattleWA98195 United States Department of Physics & Astronomy University of Wyoming LaramieWY82070 United States Space Vehicles Directorate Air Force Research Laboratory 3550 Aberdeen Ave. SE AFB KirtlandNM87117 United States Space Telescope Sc

We present the discovery of TOI-5205 b, a transiting Jovian planet orbiting a solar metallicity M4V star, which was discovered using Transiting Exoplanet Survey Satellite photometry and then confirmed using a combination of precise radial velocities, ground-based photometry, spectra, and speckle imaging. TOI-5205 b has one of the highest mass ratios for M dwarf planets with a mass ratio of almost 0.3%, as it orbits a host star that is just 0.392 ± 0.015 M☉. Its planetary radius is 1.03 ± 0.03 RJ, while the mass is 1.08 ± 0.06 MJ. Additionally, the large size of the planet orbiting a small star results in a transit depth of ∼ 7%, making it one of the deepest transits of a confirmed exoplanet orbiting a main-sequence star. The large transit depth makes TOI-5205 b a compelling target to probe its atmospheric properties, as a means of tracing the potential formation pathways. While there have been radial-velocity-only discoveries of giant planets around mid-M dwarfs, this is the first transiting Jupiter with a mass measurement discovered around such a low-mass host star. The high mass of TOI-5205 b stretches conventional theories of planet formation and disk scaling relations that cannot easily recreate the conditions required to form such planets. © 2022, CC BY.

关键词： Photometry

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：