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arXiv 2019年

作者： Bick, Christian Goodfellow, Marc Laing, Carlo R. Martens, Erik Andreas Centre for Systems Dynamics and Control University of Exeter Exeter United Kingdom Department of Mathematics College of Engineering Mathematics and Physical Sciences University of Exeter Exeter United Kingdom Epsrc Centre for Predictive Modelling in Healthcare University of Exeter Exeter United Kingdom Mathematical Institute University of Oxford Oxford United Kingdom Living Systems Institute University of Exeter Exeter United Kingdom School of Natural and Computational Sciences Massey University Auckland New Zealand Department of Applied Mathematics and Computer Science Technical University of Denmark 2800 Kgs Lyngby Denmark Department of Biomedical Science University of Copenhagen Copenhagen N2200 Denmark

Many biological and neural systems can be seen as networks of interacting periodic processes. Importantly, the function of these networks depends on the collective dynamics: Synchrony of oscillations is probably amongst the most prominent examples of collective behavior and has been associated both with function and dysfunction. Understanding how network structure and interactions, as well as the microscopic properties of individual units, shape the emergent collective dynamics is critical to find factors that lead to malfunction. However, many biological systems such as the brain consist of a large number of dynamical units. Hence, their analysis has either primarily relied on simplified heuristic models on a coarse scale, or the analysis comes at a huge computational cost. Here we review recently introduced approaches-commonly known as the Ott-Antonsen and Watanabe-Strogatz reductions-That allow to simplify the analysis by bridging small and large scales: To obtain reduced model equations, a subpopulation in an oscillator network is replaced by a single variable that describes its collective state exactly. The resulting equations are next-generation models: Rather than being heuristic, they capture microscopic properties of the underlying system. At the same time, they are sufficiently simple to analyze without great computational effort. In the last decade, these reduction methods have become instrumental to understand how network structure and interaction shapes the collective dynamics and the emergence of synchrony. We review this progress based on concrete examples and outline possible limitations. Finally, we discuss how linking the reduced models with experimental data can guide the way towards the development of new treatment approaches, for example, for neural disease. Copyright © 2019, The Authors. All rights reserved.

关键词： Dynamics

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Traffic flow optimization with QoS constrained network admission control

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IFAC-PapersOnLine 2017年第1期50卷 5275-5280页

作者： Csikós A. Farhadi H. Kulcsár B. Charalambous T. Wymeersch H. Institute for Computer Science and Control Hungarian Academy of Sciences Budapest Hungary Department of Signals and Systems Chalmers University of Technology Gothenburg Sweden John A. Paulson School of Engineering and Applied Sciences Harvard University Cambridge MA United States Department of Electrical Engineering and Automation School of Electrical Engineering Aalto University Espoo Finland

The paper proposes a control design method in order to gate input flow to a protected urban vehicular network such that travel time Quality of Service (QoS) constraints are preserved within the network. In view of the network to be protected (also called the region), two types of queues are distinguished: external and internal. While external queues represent vehicles waiting to enter the protected network, an internal queue can be used to describe the network's aggregated behaviour. By controlling the number of vehicles entering the internal queue, the travel time within the network subject to the vehicular conservation law and the Network Fundamental Diagram (NFD) can be subsequently controlled. The admission controller can thus be interpreted as a mechanism which transforms the unknown arrival process governing the number of vehicles entering the network to a regulated process, such that prescribed QoS requirements on travel time in the network and upper bound on the external queue are satisfied. The admission control problem is formulated as a constrained convex optimization problem and a Model Predictive control (MPC) problem. A case study demonstrates the benefits of the admission control mechanisms proposed. © 2017

关键词： admission network fundamental diagram perimeter control Quality of Service Traffic control traffic flow travel time

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Opportunities and challenges for monitoring terrestrial biodiversity in the robotics age

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Nature Ecology and Evolution 2025年 1-12页

作者： Pringle, Stephen Dallimer, Martin Goddard, Mark A. Le Goff, Léni K. Hart, Emma Langdale, Simon J. Fisher, Jessica C. Abad, Sara-Adela Ancrenaz, Marc Angeoletto, Fabio Auat Cheein, Fernando Austen, Gail E. Bailey, Joseph J. Baldock, Katherine C. R. Banin, Lindsay F. Banks-Leite, Cristina Barau, Aliyu S. Bashyal, Reshu Bates, Adam J. Bicknell, Jake E. Bielby, Jon Bosilj, Petra Bush, Emma R. Butler, Simon J. Carpenter, Dan Clements, Christopher F. Cully, Antoine Davies, Kendi F. Deere, Nicolas J. Dodd, Michael Drinkwater, Rosie Driscoll, Don A. Dutilleux, Guillaume Dyrmann, Mads Edwards, David P. Farhadinia, Mohammad S. Faruk, Aisyah Field, Richard Fletcher, Robert J. Foster, Chris W. Fox, Richard Francksen, Richard M. Franco, Aldina M. A. Gainsbury, Alison M. Gardner, Charlie J. Giorgi, Ioanna Griffiths, Richard A. Hamaza, Salua Hanheide, Marc Hayward, Matt W. Hedblom, Marcus Helgason, Thorunn Heon, Sui P. Hughes, Kevin A. Hunt, Edmund R. Ingram, Daniel J. Jackson-Mills, George Jowett, Kelly Keitt, Timothy H. Kloepper, Laura N. Kramer-Schadt, Stephanie Labisko, Jim Labrosse, Frédéric Lawson, Jenna Lecomte, Nicolas de Lima, Ricardo F. Littlewood, Nick A. Marshall, Harry H. Masala, Giovanni L. Maskell, Lindsay C. Matechou, Eleni Mazzolai, Barbara McConnell, Alistair Melbourne, Brett A. Miriyev, Aslan Nana, Eric Djomo Ossola, Alessandro Papworth, Sarah Parr, Catherine L. Payo-Payo, Ana Perry, Gad Pettorelli, Nathalie Pillay, Rajeev Potts, Simon G. Prendergast-Miller, Miranda T. Qie, Lan Rolley-Parnell, Persie Rossiter, Stephen J. Rowcliffe, Marcus Rumble, Heather Sadler, Jon P. Sandom, Christopher J. Sanyal, Asiem Schrodt, Franziska Sethi, Sarab S. Shabrani, Adi Siddall, Robert Smith, Simón C. Snep, Robbert P. H. Soulsbury, Carl D. Stanley, Margaret C. Stephens, Philip A. Stephenson, P.J. Struebig, Matthew J. Studley, Matthew Svátek, Martin Tang, Gilbert Taylor, Nicholas K. Umbers, Kate D. L. Ward, Robert J. White, Patrick J. C. Whittingham, Mark J. Wich, Serge Williams, Christopher D. Yakubu, Ibrahim B. Yoh, Natalie Durrell Institute of Conservation and Ecology (DICE) School of Natural Sciences University of Kent Canterbury United Kingdom Centre for Environmental Policy Imperial College London London United Kingdom Department of Geography and Environmental Sciences Northumbria University Newcastle upon Tyne United Kingdom School of Computing Engineering and the Built Environment Edinburgh Napier University Edinburgh United Kingdom Synthotech Ltd Milner Court Hornbeam Square Harrogate United Kingdom Mechanical Engineering Department University College London London United Kingdom HUTAN SWD Kota Kinabalu Malaysia Programa de Pós-Graduação em Gestão e Tecnologia Ambiental da Universidade Federal de Rondonópolis Rondonópolis Brazil Department of Engineering Harper Adams University Newport United Kingdom Applied Ecology Research Group School of Life Sciences Anglia Ruskin University Cambridge United Kingdom Centre for Ecology and Hydrology Penicuik United Kingdom Department of Life Sciences Imperial College London Silwood Park Campus Ascot United Kingdom Department of Urban and Regional Planning Faculty of Earth and Environmental Sciences Bayero University Kano Nigeria Greenhood Nepal Kathmandu Nepal Animal Rural & Environmental Sciences Nottingham Trent University Nottinghamshire United Kingdom School of Biological and Environmental Sciences Liverpool John Moores University Liverpool United Kingdom Lincoln Centre for Autonomous Systems University of Lincoln Lincoln United Kingdom Royal Botanic Garden Edinburgh Edinburgh United Kingdom School of Biological Sciences University of East Anglia Norwich Research Park Norwich United Kingdom Digital Ecology Limited Bristol United Kingdom School of Biological Sciences University of Bristol Bristol United Kingdom Department of Computing Imperial College London London United Kingdom Department of Ecology and Evolutionary Biology University of Colorado Boulder CO United States Faculty of Science Technology Engineering

With biodiversity loss escalating globally, a step change is needed in our capacity to accurately monitor species populations across ecosystems. Robotic and autonomous systems (RAS) offer technological solutions that may substantially advance terrestrial biodiversity monitoring, but this potential is yet to be considered systematically. We used a modified Delphi technique to synthesize knowledge from 98 biodiversity experts and 31 RAS experts, who identified the major methodological barriers that currently hinder monitoring, and explored the opportunities and challenges that RAS offer in overcoming these barriers. Biodiversity experts identified four barrier categories: site access, species and individual identification, data handling and storage, and power and network availability. Robotics experts highlighted technologies that could overcome these barriers and identified the developments needed to facilitate RAS-based autonomous biodiversity monitoring. Some existing RAS could be optimized relatively easily to survey species but would require development to be suitable for monitoring of more ‘difficult’ taxa and robust enough to work under uncontrolled conditions within ecosystems. Other nascent technologies (for instance, new sensors and biodegradable robots) need accelerated research. Overall, it was felt that RAS could lead to major progress in monitoring of terrestrial biodiversity by supplementing rather than supplanting existing methods. Transdisciplinarity needs to be fostered between biodiversity and RAS experts so that future ideas and technologies can be codeveloped effectively. © The Author(s) 2025.

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Equilibrium solutions of multi-period mean-variance portfolio selection

arXiv

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arXiv 2018年

作者： Ni, Yuan-Hua Li, Xun Zhang, Ji-Feng Krstic, Miroslav College of Computer and Control Engineering Nankai University Tianjin300350 China Department of Applied Mathematics Hong Kong Polytechnic University Kowloon Hong Kong Key Laboratory of Systems and Control Institute of Systems Science Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China School of Mathematical Sciences University of Chinese Academy of Sciences Beijing100049 China Department of Mechanical and Aerospace Engineering University of California San Diego United States

This is a companion paper of [Mixed equilibrium solution of time-inconsistent stochastic LQ problem, arXiv:1802.03032], where general theory has been established to characterize the open-loop equilibrium control, feedback equilibrium strategy and mixed equilibrium solution for a time-inconsistent stochastic linear-quadratic problem. This note is, on the one hand to test the developed theory of that paper, and on the other hand to push the solvability of multi-period mean-variance portfolio selection. A nondegenerate assumption has been removed in this note, which is popular in existing literature about multi-period mean-variance portfolio selection;and neat conditions have been obtained to characterize the existence of equilibrium solutions. Copyright © 2018, The Authors. All rights reserved.

关键词： Stochastic systems

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Publisher Correction: Gaze, visual, myoelectric, and inertial data of grasps for intelligent prosthetics

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Scientific data 2020年第1期7卷 62页

作者： Matteo Cognolato Arjan Gijsberts Valentina Gregori Gianluca Saetta Katia Giacomino Anne-Gabrielle Mittaz Hager Andrea Gigli Diego Faccio Cesare Tiengo Franco Bassetto Barbara Caputo Peter Brugger Manfredo Atzori Henning Müller Information Systems Institute University of Applied Sciences Western Switzerland (HES-SO Valais) Sierre Switzerland. matteo.cognolato@hevs.ch. Rehabilitation Engineering Laboratory Department of Health Sciences and Technology ETH Zurich Zurich Switzerland. matteo.cognolato@hevs.ch. Istituto Italiano di Tecnologia Genoa Italy. Department of Computer Control and Management Engineering University of Rome La Sapienza Rome Italy. Department of Neurology University Hospital of Zurich Zurich Switzerland. Department of Physical Therapy University of Applied Sciences Western Switzerland (HES-SO Valais) Leukerbad Switzerland. Clinic of Plastic Surgery Padova University Hospital Padova Italy. Politecnico di Torino Turin Italy. Rehabilitation Center Valens Valens Switzerland. Information Systems Institute University of Applied Sciences Western Switzerland (HES-SO Valais) Sierre Switzerland. manfredo.atzori@hevs.ch. Information Systems Institute University of Applied Sciences Western Switzerland (HES-SO Valais) Sierre Switzerland. henning.mueller@hevs.ch. University of Geneva Geneva Switzerland. henning.mueller@hevs.ch.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

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Estimates, trends, and drivers of the global burden of type 2 diabetes attributable to PM_2·5 air pollution, 1990–2019: an analysis of data from the Global Burden of Disease Study 2019

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The Lancet Planetary Health 2022年第7期6卷 e586-e600页

作者： Burkart, Katrin Causey, Kate Cohen, Aaron J Wozniak, Sarah S Salvi, Devashri Digvijay Abbafati, Cristiana Adekanmbi, Victor Adsuar, Jose C Ahmadi, Keivan Alahdab, Fares Al-Aly, Ziyad Alipour, Vahid Alvis-Guzman, Nelson Amegah, Adeladza Kofi Andrei, Catalina Liliana Andrei, Tudorel Ansari, Fereshteh Arabloo, Jalal Aremu, Olatunde Aripov, Timur Babaee, Ebrahim Banach, MacIej Barnett, Anthony Bärnighausen, Till Winfried Bedi, Neeraj Behzadifar, Masoud Béjot, Yannick Bennett, Derrick A Bensenor, Isabela M Bernstein, Robert S Bhattacharyya, Krittika Bijani, Ali Biondi, Antonio Bohlouli, Somayeh Breitner, Susanne Brenner, Hermann Butt, Zahid A Cámera, Luis Alberto Cantu-Brito, Carlos Carvalho, Felix Cerin, Ester Chattu, Vijay Kumar Chauhan, Bal Govind Choi, Jee-Young Jasmine Chu, Dinh-Toi Dai, Xiaochen Dandona, Lalit Dandona, Rakhi Daryani, Ahmad Davletov, Kairat De Courten, Barbora Demeke, Feleke Mekonnen Denova-Gutiérrez, Edgar Dharmaratne, Samath Dhamminda Dhimal, Meghnath Diaz, Daniel Djalalinia, Shirin Duncan, Bruce B El Sayed Zaki, Maysaa Eskandarieh, Sharareh Fareed, Mohammad Farzadfar, Farshad Fattahi, Nazir Fazlzadeh, Mehdi Fernandes, Eduarda Filip, Irina Fischer, Florian Foigt, Nataliya A Freitas, Marisa Ghashghaee, Ahmad Gill, Paramjit Singh Ginawi, Ibrahim Abdelmageed Gopalani, Sameer Vali Guo, Yuming Gupta, Rajat Das Habtewold, Tesfa Dejenie Hamadeh, Randah R Hamidi, Samer Hankey, Graeme J Hasanpoor, Edris Hassen, Hamid Yimam Hay, Simon I Heibati, Behzad Hole, Michael K Hossain, Naznin Househ, Mowafa Irvani, Seyed Sina Naghibi Jaafari, Jalil Jakovljevic, Mihajlo Jha, Ravi Prakash Jonas, Jost B Jozwiak, Jacek Jerzy Kasaeian, Amir Kaydi, Neda Khader, Yousef Saleh Khafaie, Morteza Abdullatif Khan, Ejaz Ahmad Khan, Junaid Khan, Md Nuruzzaman Khatab, Khaled Khater, Amir M Kim, Yun Jin Kimokoti, Ruth W Kisa, Adnan Kivimäki, Mika Knibbs, Luke D Kosen, Soewarta Koul, Parvaiz A Koyanagi, Ai Defo, Barthelemy Kuate Kugbey, Nuworza Lauriola, Paolo Lee, Paul H Leili, Mostafa Lewycka, Sonia Li, Shanshan Lim, Lee-Ling Li Institute for Health Metrics and Evaluation University of Washington Seattle WA United States Department of Health Metrics Sciences School of Medicine University of Washington Seattle WA United States Division of Plastic and Reconstructive Surgery University of Washington Seattle WA United States Research Insights and Innovation Seattle WA United States Health Effects Institute Boston MA United States School of Public Health Boston University Boston MA United States Department of Juridical and Economic Studies La Sapienza University Rome Italy Department of Population Medicine Cardiff University Cardiff United Kingdom Sport Science Department University of Extremadura Badajoz Spain School of Public Health Imperial College London London United Kingdom Department of Primary Care and Public Health Imperial College London London United Kingdom Mayo Evidence-based Practice Center Mayo Clinic Foundation for Medical Education and Research Rochester MN United States John T. Milliken Department of Internal Medicine Washington University in St. Louis St. Louis MO United States Clinical Epidemiology Center US Department of Veterans Affairs (VA) St Louis MO United States Health Management and Economics Research Center Iran University of Medical Sciences Tehran Iran Department of Health Economics Iran University of Medical Sciences Tehran Iran Preventive Medicine and Public Health Research Center Iran University of Medical Sciences Tehran Iran Pars Advanced and Minimally Invasive Medical Manners Research Center Iran University of Medical Sciences Tehran Iran Department of Community and Family Medicine Iran University of Medical Sciences Tehran Iran Research Group in Hospital Management and Health Policies Universidad de la Costa (University of the Coast) Barranquilla Colombia Research Group in Health Economics University of Cartagena Cartagena Colombia Department of Biomedical Science University of Cape Coast Cape Coast Ghana Cardiology Department Ca

Background: Experimental and epidemiological studies indicate an association between exposure to particulate matter (PM) air pollution and increased risk of type 2 diabetes. In view of the high and increasing prevalence of diabetes, we aimed to quantify the burden of type 2 diabetes attributable to PM_2·5 originating from ambient and household air pollution. Methods: We systematically compiled all relevant cohort and case-control studies assessing the effect of exposure to household and ambient fine particulate matter (PM_2·5) air pollution on type 2 diabetes incidence and mortality. We derived an exposure–response curve from the extracted relative risk estimates using the MR-BRT (meta-regression—Bayesian, regularised, trimmed) tool. The estimated curve was linked to ambient and household PM_2·5 exposures from the Global Burden of Diseases, Injuries, and Risk Factors Study 2019, and estimates of the attributable burden (population attributable fractions and rates per 100 000 population of deaths and disability-adjusted life-years) for 204 countries from 1990 to 2019 were calculated. We also assessed the role of changes in exposure, population size, age, and type 2 diabetes incidence in the observed trend in PM_2·5-attributable type 2 diabetes burden. All estimates are presented with 95% uncertainty intervals. Findings: In 2019, approximately a fifth of the global burden of type 2 diabetes was attributable to PM_2·5 exposure, with an estimated 3·78 (95% uncertainty interval 2·68–4·83) deaths per 100 000 population and 167 (117–223) disability-adjusted life-years (DALYs) per 100 000 population. Approximately 13·4% (9·49–17·5) of deaths and 13·6% (9·73–17·9) of DALYs due to type 2 diabetes were contributed by ambient PM2·5, and 6·50% (4·22–9·53) of deaths and 5·92% (3·81–8·64) of DALYs by household air pollution. High burdens, in terms of numbers as well as rates, were estimated in Asia, sub-Saharan Africa, and South Am

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Iran in transition (vol 393, pg 1984, 2019)

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LANCET 2019年第10186期393卷 2124-2124页

作者： Danaei, G. Farzadfar, F. Kelishadi, R. [a]Department of Global Health and Population and Department of Epidemiology Harvard T H Chan School of Public Health Boston MA USA Department of Global Health and Population and Department of Epidemiology Harvard T H Chan School of Public Health Boston MA USA [b]Scientific Association for Public Health in Iran Boston MA USA Scientific Association for Public Health in Iran Boston MA USA [c]Non-Communicable Diseases Research Center Endocrinology and Metabolism Population Sciences Institute Tehran University of Medical Sciences Tehran Iran Non-Communicable Diseases Research Center Endocrinology and Metabolism Population Sciences Institute Tehran University of Medical Sciences Tehran Iran [d]Endocrinology and Metabolism Research Center Tehran University of Medical Sciences Tehran Iran Endocrinology and Metabolism Research Center Tehran University of Medical Sciences Tehran Iran [e]Diabetes Research Center Tehran University of Medical Sciences Tehran Iran Diabetes Research Center Tehran University of Medical Sciences Tehran Iran [f]Endocrinology and Metabolism Clinical Sciences Institute Department of Health Management and Economics Tehran University of Medical Sciences Tehran Iran Endocrinology and Metabolism Clinical Sciences Institute Department of Health Management and Economics Tehran University of Medical Sciences Tehran Iran [g]Department of Global Health and Public Policy Tehran University of Medical Sciences Tehran Iran Department of Global Health and Public Policy Tehran University of Medical Sciences Tehran Iran [h]Department of Epidemiology and Biostatistics Tehran University of Medical Sciences Tehran Iran Department of Epidemiology and Biostatistics Tehran University of Medical Sciences Tehran Iran [i]School of Public Health Tehran University of Medical Sciences Tehran Iran School of Public Health Tehran University of Medical Sciences Tehran Iran [j]Faculty of Medicine Tehran University of Medical Sciences Tehran Iran Faculty of Medicine Te

Summary Being the second-largest country in the Middle East, Iran has a long history of civilisation during which several dynasties have been overthrown and established and health-related structures have been reorganised. Iran has had the replacement of traditional practices with modern medical treatments, emergence of multiple pioneer scientists and physicians with great contributions to the advancement of science, environmental and ecological changes in addition to large-scale natural disasters, epidemics of multiple communicable diseases, and the shift towards non-communicable diseases in recent decades. Given the lessons learnt from political instabilities in the past centuries and the approaches undertaken to overcome health challenges at the time, Iran has emerged as it is today. Iran is now a country with a population exceeding 80 million, mainly inhabiting urban regions, and has an increasing burden of non-communicable diseases, including cardiovascular diseases, hypertension, diabetes, malignancies, mental disorders, substance abuse, and road injuries.

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Ergodicity-breaking reveals time optimal economic behavior in humans

arXiv

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arXiv 2019年

作者： Meder, David Rabe, Finn Morville, Tobias Madsen, Kristoffer H. Koudahl, Magnus T. Dolan, Ray J. Siebner, Hartwig R. Hulme, Oliver J. Danish Research Centre for Magnetic Resonance Centre for Functional and Diagnostic Imaging and Research Copenhagen University Hospital Hvidovre Kettegard Allé 30 Hvidovre2650 Denmark Neural Control of Movement Lab ETH Zurich Winterthurerstrasse 190 Building Y36 Zurich8057 Switzerland Department of Applied Mathematics and Computer Science Technical University of Denmark Kongens Lyngby2800 Denmark Department of Electrical Engineering Eindhoven University of Technology Eindhoven6500 MB Netherlands Max Planck UCL Centre for Computational Psychiatry and Ageing Research 10-12 Russell Square LondonWC1B5EH United Kingdom Department of Neurology Copenhagen University Hospital Bispebjerg Bispebjerg Bakke 23 Copenhagen2400 Denmark Institute for Clinical Medicine Faculty of Medical and Health Sciences University of Copenhagen Blegdamsvej 9 Copenhagen2100 Denmark

Ergodicity describes an equivalence between the expectation value and the time average of observables. applied to human behaviour, ergodic theory reveals how individuals should tolerate risk in different environments. To optimise wealth over time, agents should adapt their utility function according to the dynamical setting they face. Linear utility is optimal for additive dynamics, whereas logarithmic utility is optimal for multiplicative dynamics. Whether humans approximate time optimal behavior across different dynamics is unknown. Here we compare the effects of additive versus multiplicative gamble dynamics on risky choice. We show that utility functions are modulated by gamble dynamics in ways not explained by prevailing economic theory. Instead, as predicted by time optimality, risk aversion increases under multiplicative dynamics, distributing close to the values that maximise the time average growth of wealth. We suggest that our findings motivate a need for explicitly grounding theories of decision-making on ergodic considerations. Copyright © 2019, The Authors. All rights reserved.

关键词： Dynamics

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Web Science 2024: Conference Chairs' Welcome Message

Proceedings of the 16th ACM Web Science Conference, WebSci 2...

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Proceedings of the 16th ACM Web Science Conference, WebSci 2024 2024年 III-X页

作者： Staab, Steffen Aiello, Luca Maria Mejova, Yelena Seneviratne, Oshani Sindermann, Cornelia Hagendorff, Thilo Brandes, Simone Rohlmann, Juliane Spaniol, Marc Kinder-Kurlanda, Katharina Faleńska, Agnieszka Heiberger, Raphael Sun, Jun Kaiser, Sierra De Choudhury, Munmun Weber, Matthew De Francisci Morales, Gianmarco Dunn, Adam Gadiraju, Ujwal Gaito, Sabrina Hooper, Silas Javarone, Marco Alberto Kalimeri, Kyriaki Kwak, Haewoon Maity, Suman Kalyan Mashhadi, Afra Mustafaraj, Eni Purohit, Hemant Rossetti, Giulio Sastry, Nishanth Srinivasa, Srinath Vaz-De-Melo, Pedro Weal, Mark Weber, Ingmar Weninger, Tim Withing, Mark Zubiaga, Arkaitz Ahlers, Dirk Tamime, Reham Al Alam, Sawood Alhoori, Hamed Andriotis, Panagiotis Bär, Dominik Bernstein, Mark Boratto, Ludovico Camargo, Chico Capozzi, Arthur Chelmis, Charalampos Vieira, Carolina Coimbra De Meo, Pasquale Dinh, Ly Dividino, Renata Doerfel, Stephan Farahbakhsh, Reza Ferreira, Carlos H.G. Flores-Saviaga, Claudia Florio, Komal Galdeman, Alessia Guo, Cheng Hakimov, Sherzod Rad, Radin Hamidi Helic, Denis Hohmann, Marilena Horawalavithana, Sameera Horne, Benjamin Ibanez-Gonzalez, Luis Jiang, Julie Jones, Shawn Kamdar, Maulik R. Kao, Hsien-Te Kassa, Yonas Mitike Kastrin, Andrej Kazama, Kazuhiro Kelly, Mat Khanday, Akib Khatua, Aparup Khudabukhsh, Ashiqur Krüger, Frank Kumari, Neha Lai, Mirko Lamba, Hemank Lee, Roy Ka-Wei Lee, Eun Liao, Yiming Lin, Wenqing Magelinski, Thomas Magnani, Matteo Hill, Benjamin Mako Manikonda, Lydia Masud, Sarah Mekouar, Soufiana Møller, Anders Giovanni Muthiah, Sakthi Ni, Congning Nishimura, Joel Nwala, Alexander Pera, Arianna Piao, Guangyuan Piccardi, Tiziano Pierri, Francesco Porcaro, Lorenzo Ramasco, Jose J. Reelfs, Jens Rezapour, Rezvaneh Salminen, Joni Šćepanović, Sanja Shahi, Gautam Kishore Sinha, Priyanka Smaragdakis, Georgios Smirnova, Inna Song, Melodie Yun-Ju Sosnovik, Vera Truong, Bao Tran Tsugawa, Sho Vasarhelyi, Orsolya D'Aurelio, Davide Vega Vekaria, Yash Vilella, Salvatore Viviani, Marco Wang, Yichen Wu, Siqi Yang, Kaicheng Zeng, Yilei Zha University of Stuttgart Germany IT University of Copenhagen Denmark ISI Foundation Italy Rensselaer Polytechnic Institute United States Université de Caen Normandie France University of Klagenfurt Austria University of Washington United States GESIS Germany Georgia Tech United States IIIT Bangalore India Rutgers University United States CENTAI Italy University of Sydney Australia Delft University of Technology Netherlands University of Milan Italy Canada Centro Ricerche Enrico Fermi UCL CBT Italy Indiana University Bloomington United States Northwestern University United States UW United States Wellesley College United States George Mason University United States CNRS France King's College London United Kingdom International Institute of Information Technology Bangalore India UFMG Brazil University of Southampton United Kingdom Saarland University Germany University of Notre Dame United States UPenn United States Queen Mary University of London United Kingdom Norwegian University of Science and Technology Norway Internet Archive United States Northern Illinois University United States University of the West of England United Kingdom LMU Munich Germany Eastgate Systems Inc. United States University of Cagliari Italy University of Exeter United Kingdom University of Turin Italy University at Albany State University of New York United States Max Planck Institute for Demographic Research Germany Vrije Universiteit Amsterdam Netherlands University of South Florida United States Brock University Canada Kiel University of Applied Sciences Germany Institut Mines-Télécom Télécom SudParis France Universidade Federal de Ouro Preto Brazil Northeastern University United States Università di Torino Dipartimento di Informatica Italy Clemson University Google United States TIB - Leibniz Information Centre for Science and Technology Germany Ryerson University Canada Graz University of Technology Austria University of Copenhagen Denmark Pacific Northwest National La

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Roadmap on Quantum Thermodynamics

arXiv

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arXiv 2025年

作者： Campbell, Steve D’Amico, Irene Ciampini, Mario A. Anders, Janet Ares, Natalia Artini, Simone Auffèves, Alexia Oftelie, Lindsay Bassman Bettmann, Laetitia P. Bonança, Marcus V.S. Busch, Thomas Campisi, Michele Cavalcante, Moallison F. Correa, Luis A. Cuestas, Eloisa Dag, Ceren B. Dago, Salambô Deffner, Sebastian Del Campo, Adolfo Deutschmann-Olek, Andreas Donadi, Sandro Doucet, Emery Elouard, Cyril Ensslin, Klaus Erker, Paul Fabbri, Nicole Fedele, Federico Fiusa, Guilherme Fogarty, Thomás Folk, Joshua Guarnieri, Giacomo Hegde, Abhaya S. Hernández-Gómez, Santiago Hu, Chang-Kang Iemini, Fernando Karimi, Bayan Kiesel, Nikolai Landi, Gabriel T. Lasek, Aleksander Lemziakov, Sergei Monaco, Gabriele Lo Lutz, Eric Lvov, Dmitrii Maillet, Olivier Mehboudi, Mohammad Mendonça, Taysa M. Miller, Harry J.D. Mitchell, Andrew K. Mitchison, Mark T. Mukherjee, Victor Paternostro, Mauro Pekola, Jukka Perarnau-Llobet, Martí Poschinger, Ulrich Rolandi, Alberto Rosa, Dario Sánchez, Rafael Santos, Alan C. Sarthour, Roberto S. Sela, Eran Solfanelli, Andrea Souza, Alexandre M. Splettstoesser, Janine Tan, Dian Tesser, Ludovico Van Vu, Tan Widera, Artur Halpern, Nicole Yunger Zawadzki, Krissia School of Physics University College Dublin Belfield Dublin 4 Ireland Centre for Quantum Engineering Science and Technology University College Dublin Dublin 4 Ireland School of Physics Engineering and Technology University of York York United Kingdom York Centre for Quantum Technologies University of York York United Kingdom Boltzmanngasse 5 ViennaA-1090 Austria Institute of Physics and Astronomy University of Potsdam Potsdam14476 Germany Department of Physics and Astronomy University of Exeter ExeterEX4 4QL United Kingdom Department of Engineering Science University of Oxford Parks Road OxfordOX1 3PJ United Kingdom Università degli Studi di Palermo Dipartimento di Fisica e Chimica - Emilio Segrè via Archirafi 36 PalermoI-90123 Italy MajuLab CNRS-UCA-SU-NUS-NTU International Joint Research Laboratory France Centre for Quantum Technologies National University of Singapore Singapore117543 Singapore NEST Istituto Nanoscienze-CNR and Scuola Normale Superiore Pisa56127 Italy School of Physics Trinity College Dublin College Green Dublin 2 Ireland Gleb Wataghin Physics Institute The University of Campinas Campinas São Paulo13083-859 Brazil Quantum Systems Unit OIST Graduate University Okinawa Onna904-0495 Japan Department of Physics University of Maryland Baltimore County BaltimoreMD21250 United States Quantum Science Institute University of Maryland Baltimore County BaltimoreMD21250 United States Universidad de La Laguna La Laguna38203 Spain Departamento de Física Universidad de La Laguna La Laguna38203 Spain Jülich54245 Germany Department of Physics Indiana University BloomingtonIN47405 United States Department of Physics Harvard University 17 Oxford Street CambridgeMA02138 United States National Quantum Laboratory College ParkMD20740 United States Department of Physics and Materials Science University of Luxembourg LuxembourgL-1511 Luxembourg Donostia International Physics Center San SebastianE-20018 Spain Au

The last two decades has seen quantum thermodynamics become a well established field of research in its own right. In that time, it has demonstrated a remarkably broad applicability, ranging from providing foundational advances in the understanding of how thermodynamic principles apply at the nano-scale and in the presence of quantum coherence, to providing a guiding framework for the development of efficient quantum devices. Exquisite levels of control have allowed state-of-the-art experimental platforms to explore energetics and thermodynamics at the smallest scales which has in turn helped to drive theoretical advances. This Roadmap provides an overview of the recent developments across many of the field’s sub-disciplines, assessing the key challenges and future prospects, providing a guide for its near term progress. Copyright © 2025, The Authors. All rights reserved.

关键词： Temperature

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