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Overcoming the disconnect between energy system and climate modelling

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arXiv 2022年

作者： Craig, Michael T. Wohland, Jan Stoop, Laurens P. Kies, Alexander Pickering, Bryn Bloomfield, Hannah C. Browell, Jethro De Felice, Matteo Dent, Chris J. Deroubaix, Adrien Frischmuth, Felix Gonzalez, Paula L.M. Grochowicz, Aleksander Gruber, Katharina Härtel, Philipp Kittel, Martin Kotzur, Leander Labuhn, Inga Lundquist, Julie K. Pflugradt, Noah van der Wiel, Karin Zeyringer, Marianne Brayshaw, David J. School for Environment and Sustainability University of Michigan United States Institute for Environmental Decisions ETH Zurich Switzerland Helmholtz-Zentrum Hereon Germany Information and Computing Science Copernicus Institute of Sustainable Development Utrecht University Netherlands TenneT TSO B.V. Arnhem Netherlands Royal Netherlands Meteorological Institute Netherlands Frankfurt Institute for Advanced Studies Germany Department of Electrical and Computer Engineering Aarhus University Denmark ETH Zürich Switzerland School of Geographical Sciences University of Bristol United Kingdom Department of Meteorology University of Reading United Kingdom University of Glasgow United Kingdom European Commission Joint Research Centre Netherlands School of Mathematics University of Edinburg United Kingdom The Alan Turing Institute United Kingdom Max Planck Institute Germany Fraunhofer Institute for Energy Economics and Energy System Technology Germany Department of Mathematics University of Oslo Norway University of Natural Resources and Life Sciences Austria German Institute for Economic Research Germany Institute of Energy and Climate Research Techno-economic Systems Analysis Germany University of Bremen Institute of Geography Germany Dept. of Atmospheric and Oceanic Science University of Colorado Boulder United States National Renewable Energy Laboratory United States Renewable and Sustainable Energy Institute United States Forschungszentrum Jülich Germany Department of Technology Systems University of Oslo Norway

Energy system models underpin decisions by energy system planners and operators. Energy system modelling faces a transformation: accounting for changing meteorological conditions imposed by climate change. To enable that transformation, a community of practice in energy-climate modelling has started to form that aims to better integrate energy system models with weather and climate models. Here, we evaluate the disconnects between the energy system and climate modelling communities, then lay out a research agenda to bridge those disconnects. In the near-term, we propose interdisciplinary activities for expediting uptake of future climate data in energy system modelling. In the long-term, we propose a transdisciplinary approach to enable development of (1) energy-system-tailored climate datasets for historical and future meteorological conditions and (2) energy system models that can effectively leverage those datasets. This agenda increases the odds of meeting ambitious climate mitigation goals by systematically capturing and mitigating climate risk in energy sector decision making. © 2022, CC BY-NC-ND.

关键词： Decision making

DE/RM-MEDA: A new hybrid multi-objective generator

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arXiv 2019年

作者： Rmalano, Abel Saâ J. Guanjun, D.U. Tong, Guoxiang Xiong, Naixue Shanghai Key Laboratory of Modern Optical System School of Optical-Electrical and Computer Engineering University of Shanghai for Science and Technology Shanghai200093 China College of Intelligence and Computing Tianjin University Tianjin300350 China Department of Mathematics and Computer Science Northeastern State University TahlequahOK74464 United States

Under the condition of Karush-Kuhn-Tucker, the Pareto Set (PS) in the decision area of an m-objective optimization problem is a piecewise continuous (m-1)-D manifold. For illustrate the degree of convergence of the population, we employed the ratio of the sum of the first (m-1) largest eigenvalue of the population's covariance matrix of the sum of all eigenvalue. Based on this property, this paper proposes a new algorithm, called DE/RMMEDA, which mix differential evolutionary (DE) and the estimation of distribution algorithm (EDA) to generate and adaptively adjusts the number of new solutions by the ratio. The proposed algorithm is experimented on nine tec09 problems. The comparison results between DE/RM-MEDA and the others algorithms, called NSGA-II-DE and RM-MEDA, show that the proposed algorithm perform better in terms of convergence and diversity metric. Copyright © 2019, The Authors. All rights reserved.

关键词： Multiobjective optimization

Generating ultradense pair beams using 400 GeV/c protons

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Physical Review Research 2021年第2期3卷 023103-023103页

作者： C. D. Arrowsmith N. Shukla N. Charitonidis R. Boni H. Chen T. Davenne A. Dyson D. H. Froula J. T. Gudmundsson B. T. Huffman Y. Kadi B. Reville S. Richardson S. Sarkar J. L. Shaw L. O. Silva P. Simon R. M. G. M. Trines R. Bingham G. Gregori Department of Physics University of Oxford Parks Road Oxford OX1 3PU United Kingdom CINECA High-Performance Computing Department Via Magnanelli 6/3 40033 Casalecchio di Reno - Bologna Italy European Organization for Nuclear Research (CERN) CH-1211 Geneva 23 Switzerland University of Rochester Laboratory for Laser Energetics Rochester New York 14623 USA Lawrence Livermore National Laboratory 7000 East Avenue Livermore California 94550 USA Rutherford Appleton Laboratory Chilton Didcot OX11 0QX United Kingdom Science Institute University of Iceland Dunhaga 3 IS-107 Reykjavik Iceland Department of Space and Plasma Physics School of Electrical Engineering and Computer Science KTH Royal Institute of Technology SE-100 44 Stockholm Sweden Max-Planck-Institut für Kernphysik Saupfercheckweg 1 D-69117 Heidelberg Germany Atomic Weapons Establishment Aldermaston Reading Berkshire RG7 4PR United Kingdom GoLP/Instituto de Plasmas e Fusão Nuclear Instituto Superior Técnico Universidade de Lisboa 1049-001 Lisboa Portugal Department of Physics University of Strathclyde Glasgow G4 0NG United Kingdom

An experimental scheme is presented for generating low-divergence, ultradense, relativistic, electron-positron beams using 400 GeV/c protons available at facilities such as HiRadMat and AWAKE at CERN. Preliminary Monte Carlo and particle-in-cell simulations demonstrate the possibility of generating beams containing 1013–1014 electron-positron pairs at sufficiently high densities to drive collisionless beam-plasma instabilities, which are expected to play an important role in magnetic field generation and the related radiation signatures of relativistic astrophysical phenomena. The pair beams are quasineutral, with size exceeding several skin depths in all dimensions, allowing the examination of the effect of competition between transverse and longitudinal instability modes on the growth of magnetic fields. Furthermore, the presented scheme allows for the possibility of controlling the relative density of hadrons to electron-positron pairs in the beam, making it possible to explore the parameter spaces for different astrophysical environments.

关键词： Beam instabilities Cosmic ray acceleration Cosmic ray composition & spectra Cosmic ray sources Gamma ray astronomy Gamma ray bursts High-energy-density plasmas laboratory studies of space & astrophysical plasmas Optical, UV, & IR astronomy Plasma instabilities Plasma-beam interactions Relativistic multiple-particle dynamics

Biomedical image analysis competitions: The state of current participation practice

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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

Building a quantum engineering undergraduate program

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arXiv 2021年

作者： Asfaw, Abraham Blais, Alexandre Brown, Kenneth R. Candelaria, Jonathan Cantwell, Christopher Carr, Lincoln D. Combes, Joshua Debroy, Dripto M. Donohue, John M. Economou, Sophia E. Edwards, Emily Fox, Michael F.J. Girvin, Steven M. Ho, Alan Hurst, Hilary M. Jacob, Zubin Johnson, Blake R. Johnston-Halperin, Ezekiel Joynt, Robert Kapit, Eliot Klein-Seetharaman, Judith Laforest, Martin Lewandowski, H.J. Lynn, Theresa W. McRae, Corey Rae H. Merzbacher, Celia Michalakis, Spyridon Narang, Prineha Oliver, William D. Palsberg, Jens Pappas, David P. Raymer, Michael G. Reilly, David J. Saffman, Mark Searles, Thomas A. Shapiro, Jeffrey H. Singh, Chandralekha IBM Quantum IBM T. J. Watson Research Center Yorktown HeightsNY United States Institut Quantique Département de Physique Université de Sherbrooke SherbrookeQCJ1K 2R1 Canada Canadian Institute for Advanced Research TorontoONM5G 1M1 Canada The Duke Quantum Center Department of Physics Department of Electrical and Computer Engineering Department of Chemistry Duke University DurhamNC27708 United States SystemX Program Department of Electrical Engineering Stanford University StanfordCA94305 United States Department of Physics and Astronomy University of Southern California Los AngelesCA90089 United States The Quantum Engineering Program Department of Physics Colorado School of Mines GoldenCO80401 United States The Department of Electrical Computer and Energy Engineering University of Colorado Boulder BoulderCO80309 United States The Institute for Quantum Computing University of Waterloo WaterlooONN2L 3G1 Canada The Department of Physics Virginia Tech BlacksburgVA24061 United States The IQUIST University of Illinois Urbana-Champaign UrbanaIL61801 United States JILA National Institute of Standards and Technology The University of Colorado BoulderCO80309 United States Department of Physics University of Colorado Boulder BoulderCO80309 United States The Department of Physics Imperial College London Prince Consort Road LondonSW7 2AZ United Kingdom The Yale Quantum Institute Department of Physics Yale University New HavenCT06520 United States Google Research VeniceCA90291 United States The Department of Physics & Astronomy San José State University San JoséCA95192 United States The School of Electrical and Computer Engineering Purdue University Indiana West Lafayatte47907 United States The Department of Physics The Ohio State University ColumbusOH43210 United States The Department of Physics University of Wisconsin-Madison 1150 University Avenue MadisonWI53706 United States The Quantitative Biosciences and Engineering

The rapidly growing quantum information science and engineering (QISE) industry will require both quantum-aware and quantum-proficient engineers at the bachelor's level. We provide a roadmap for building a quantum engineering education program to satisfy this need. For quantum-aware engineers, we describe how to design a first quantum engineering course accessible to all STEM students. For the education and training of quantum-proficient engineers, we detail both a quantum engineering minor accessible to all STEM majors, and a quantum track directly integrated into individual engineering majors. We propose that such programs typically require only three or four newly developed courses that complement existing engineering and science classes available on most larger campuses. We describe a conceptual quantum information science course for implementation at any post-secondary institution, including community colleges and military schools. QISE presents extraordinary opportunities to work towards rectifying issues of inclusivity and equity that continue to be pervasive within engineering. We present a plan to do so and describe how quantum engineering education presents an excellent set of education research opportunities. Finally, we outline a hands-on training plan on quantum hardware, a key component of any quantum engineering program, with a variety of technologies including optics, atoms and ions, cryogenic and solid-state technologies, nanofabrication, and control and readout electronics. Our recommendations provide a flexible framework that can be tailored for academic institutions ranging from teaching and undergraduate-focused two- and four-year colleges to research-intensive universities. © 2021, CC BY.

关键词： engineering education

Leveraging randomized compiling for the QITE algorithm

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arXiv 2021年

作者： Ville, Jean-Loup Morvan, Alexis Hashim, Akel Naik, Ravi K. Lu, Marie Mitchell, Bradley Kreikebaum, John-Mark O’Brien, Kevin P. Wallman, Joel J. Hincks, Ian Emerson, Joseph Smith, Ethan Younis, Ed Iancu, Costin Santiago, David I. Siddiqi, Irfan Quantum Nanoelectronics Laboratory Dept. of Physics University of California at Berkeley BerkeleyCA94720 United States Computational Research Division Lawrence Berkeley National Lab BerkeleyCA94720 United States Materials Sciences Division Lawrence Berkeley National Lab BerkeleyCA94720 United States Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology CambridgeMA02139 United States Inst. for Quantum Computing Dept. of Applied Mathematics University of Waterloo WaterlooONN2L 3G1 Canada Quantum Benchmark Inc. KitchenerONN2H 5G5 Canada

The success of the current generation of Noisy Intermediate-Scale Quantum (NISQ) hardware shows that quantum hardware may be able to tackle complex problems even without error correction. One outstanding issue is that of coherent errors arising from the increased complexity of these devices. These errors can accumulate through a circuit, making their impact on algorithms hard to predict and mitigate. Iterative algorithms like Quantum Imaginary time Evolution are susceptible to these errors. This article presents the combination of both noise tailoring using Randomized Compiling and error mitigation with a purification. We also show that Cycle Benchmarking gives an estimate of the reliability of the purification. We apply this method to the Quantum Imaginary time Evolution of a Transverse Field Ising Model and report an energy estimation and a ground state infidelity both below 1%. Our methodology is general and can be used for other algorithms and platforms. We show how combining noise tailoring and error mitigation will push forward the performance of NISQ devices. © 2021, CC BY.

关键词： Benchmarking

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

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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

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

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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

Photocurrent imaging of multi-memristive charge density wave switching in two-dimensional 1T-TaS2

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arXiv 2020年

作者： Patel, Tarun Okamoto, Junichi Dekker, Tina Yang, Bowen Gao, Jingjing Luo, Xuan Lu, Wenjian Sun, Yuping Tsen, Adam W. Institute for Quantum Computing Department of Physics and Astronomy Department of Electrical and Computer Engineering Department of Chemistry University of Waterloo WaterlooONN2L 3G1 Canada Institute of Physics University of Freiburg FreiburgD-79104 Germany Key Laboratory of Materials Physics Institute of Solid State Physics Chinese Academy of Sciences Hefei230031 China University of Science and Technology of China Hefei230026 China High Magnetic Field Laboratory Chinese Academy of Sciences Hefei230031 China Collaborative Innovation Centre of Advanced Microstructures Nanjing University Nanjing210093 China

Transport studies of atomically thin 1T-TaS2 have demonstrated the presence of intermediate resistance states across the nearly commensurate (NC) to commensurate (C) charge density wave (CDW) transition, which can be further switched electrically. While this presents exciting opportunities for the material in memristor applications, the switching mechanism has remained elusive and could be potentially attributed to the formation of inhomogeneous C and NC domains across the 1T-TaS2 flake. Here, we present simultaneous electrical driving and scanning photocurrent imaging of CDWs in ultrathin 1T-TaS2 using a vertical heterostructure geometry. While micron-sized CDW domains form upon changing temperature, electrically driven transitions result in largely uniform changes, indicating that states of intermediate resistance for the latter likely correspond to true metastable CDW states in between the NC and C phases, which we then explain by a free energy analysis. Additionally, we are able to perform repeatable and bidirectional switching across the multiple CDW states without changing sample temperature, demonstrating that atomically thin 1T-TaS2 can be further used as a robust and reversible multi-memristor material. Copyright © 2020, The Authors. All rights reserved.

关键词： Memristors