Pub Date : 2024-09-05DOI: 10.1038/s42254-024-00753-w
Zoe Budrikis
A model of voters, based on the Ising model, gives an explanation for why elections are often so close.
基于伊辛模型的选民模型解释了为什么选举往往如此接近。
{"title":"Ising-like model predicts close elections","authors":"Zoe Budrikis","doi":"10.1038/s42254-024-00753-w","DOIUrl":"10.1038/s42254-024-00753-w","url":null,"abstract":"A model of voters, based on the Ising model, gives an explanation for why elections are often so close.","PeriodicalId":19024,"journal":{"name":"Nature Reviews Physics","volume":"6 9","pages":"531-531"},"PeriodicalIF":44.8,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142137906","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A fully connected Ising machine using standard technology","authors":"Zoe Budrikis","doi":"10.1038/s42254-024-00757-6","DOIUrl":"10.1038/s42254-024-00757-6","url":null,"abstract":"A paper in Nature Electronics reports a proof-of-concept Ising machine with all-to-all connectivity.","PeriodicalId":19024,"journal":{"name":"Nature Reviews Physics","volume":"6 9","pages":"533-533"},"PeriodicalIF":44.8,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142137882","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-05DOI: 10.1038/s42254-024-00755-8
Zoe Budrikis
An article in Nature Communications uses an Ising-like model to determine the interactions between monomers in a component of the cyanobacterial circadian clock.
{"title":"Measuring interactions in a circadian clock","authors":"Zoe Budrikis","doi":"10.1038/s42254-024-00755-8","DOIUrl":"10.1038/s42254-024-00755-8","url":null,"abstract":"An article in Nature Communications uses an Ising-like model to determine the interactions between monomers in a component of the cyanobacterial circadian clock.","PeriodicalId":19024,"journal":{"name":"Nature Reviews Physics","volume":"6 9","pages":"532-532"},"PeriodicalIF":44.8,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142137873","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-27DOI: 10.1038/s42254-024-00749-6
Yanting Cheng, Hui Zhai
Rydberg atom arrays have emerged as a novel platform exhibiting rich quantum many-body physics and offering promise for universal quantum computation. The Rydberg blockade effect plays an essential role in establishing many-body correlations in this system. Over the past 2 or 3 years, Rydberg arrays have been used to realize exotic ground states such as spin liquids, quantum many-body scar states violating quantum thermalization, and a confinement–deconfinement transition through quantum dynamics. In this Perspective, we use lattice gauge theory as a universal theoretical framework to describe the Rydberg blockade effect and the recent exciting developments in this system from equilibrium phases to quantum dynamics. Analysing Rydberg atom arrays through this theoretical framework can reveal their connection with other strongly correlated systems, such as the Fermi–Hubbard model and the lattice gauge model, which can inspire the discovery of new phenomena in this platform. The Rydberg atomic array is an emerging quantum many-body physics platform, exhibiting rich physical phenomena, such as quantum spin liquids and quantum scar states. This Perspective analyses the latest progress in this system through a unified theoretical framework — lattice gauge theory — providing new insights for quantum simulation.
{"title":"Emergent U(1) lattice gauge theory in Rydberg atom arrays","authors":"Yanting Cheng, Hui Zhai","doi":"10.1038/s42254-024-00749-6","DOIUrl":"10.1038/s42254-024-00749-6","url":null,"abstract":"Rydberg atom arrays have emerged as a novel platform exhibiting rich quantum many-body physics and offering promise for universal quantum computation. The Rydberg blockade effect plays an essential role in establishing many-body correlations in this system. Over the past 2 or 3 years, Rydberg arrays have been used to realize exotic ground states such as spin liquids, quantum many-body scar states violating quantum thermalization, and a confinement–deconfinement transition through quantum dynamics. In this Perspective, we use lattice gauge theory as a universal theoretical framework to describe the Rydberg blockade effect and the recent exciting developments in this system from equilibrium phases to quantum dynamics. Analysing Rydberg atom arrays through this theoretical framework can reveal their connection with other strongly correlated systems, such as the Fermi–Hubbard model and the lattice gauge model, which can inspire the discovery of new phenomena in this platform. The Rydberg atomic array is an emerging quantum many-body physics platform, exhibiting rich physical phenomena, such as quantum spin liquids and quantum scar states. This Perspective analyses the latest progress in this system through a unified theoretical framework — lattice gauge theory — providing new insights for quantum simulation.","PeriodicalId":19024,"journal":{"name":"Nature Reviews Physics","volume":"6 9","pages":"566-576"},"PeriodicalIF":44.8,"publicationDate":"2024-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142137907","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-23DOI: 10.1038/s42254-024-00750-z
Jack Dongarra, David Keyes
High-performance computational physics has been instrumental in advancing scientific research by regularly providing breakthroughs in speed, accuracy and modelling fidelity. This Perspective highlights the contributions of physicists to the development of high-performance computing infrastructure, algorithms and applications from the early days of computing to the exascale era. We recall the pioneering work of Fermi and von Neumann, who set directions and laid foundations for computational science and examine the ongoing impact of physicists in overcoming current challenges in high-performance computing, such as energy consumption and data storage. As we celebrate milestones such as exascale computing and generative artificial intelligence, it is inspiring to recognize the enduring influence of physicists in driving technological innovations and ensuring the future progress of computational science. This Perspective examines the pivotal role physicists have in the development and advancement of high-performance computing from its inception to the exascale era, highlighting key contributions and future challenges.
{"title":"The co-evolution of computational physics and high-performance computing","authors":"Jack Dongarra, David Keyes","doi":"10.1038/s42254-024-00750-z","DOIUrl":"10.1038/s42254-024-00750-z","url":null,"abstract":"High-performance computational physics has been instrumental in advancing scientific research by regularly providing breakthroughs in speed, accuracy and modelling fidelity. This Perspective highlights the contributions of physicists to the development of high-performance computing infrastructure, algorithms and applications from the early days of computing to the exascale era. We recall the pioneering work of Fermi and von Neumann, who set directions and laid foundations for computational science and examine the ongoing impact of physicists in overcoming current challenges in high-performance computing, such as energy consumption and data storage. As we celebrate milestones such as exascale computing and generative artificial intelligence, it is inspiring to recognize the enduring influence of physicists in driving technological innovations and ensuring the future progress of computational science. This Perspective examines the pivotal role physicists have in the development and advancement of high-performance computing from its inception to the exascale era, highlighting key contributions and future challenges.","PeriodicalId":19024,"journal":{"name":"Nature Reviews Physics","volume":"6 10","pages":"621-627"},"PeriodicalIF":44.8,"publicationDate":"2024-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142204169","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-22DOI: 10.1038/s42254-024-00747-8
May Chiao
In 2021, physicist and writer, Carlo Rovelli, helped launch an open letter to the world’s politicians calling for a small proportion of military funding to address climate change, poverty and pandemics — the Global Peace Dividend. He discusses the pressing need for global cooperation on common interests.
{"title":"The difficult but necessary role of political engagement for scientists","authors":"May Chiao","doi":"10.1038/s42254-024-00747-8","DOIUrl":"10.1038/s42254-024-00747-8","url":null,"abstract":"In 2021, physicist and writer, Carlo Rovelli, helped launch an open letter to the world’s politicians calling for a small proportion of military funding to address climate change, poverty and pandemics — the Global Peace Dividend. He discusses the pressing need for global cooperation on common interests.","PeriodicalId":19024,"journal":{"name":"Nature Reviews Physics","volume":"6 9","pages":"528-529"},"PeriodicalIF":44.8,"publicationDate":"2024-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142137902","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-20DOI: 10.1038/s42254-024-00746-9
Heather Lewtas
With more public and private funding in fusion, the expectations in terms of spillover benefits are increasing, but these can only happen through enhanced cross-sector collaboration.
{"title":"In fusion, collaboration is both a necessity and an opportunity","authors":"Heather Lewtas","doi":"10.1038/s42254-024-00746-9","DOIUrl":"10.1038/s42254-024-00746-9","url":null,"abstract":"With more public and private funding in fusion, the expectations in terms of spillover benefits are increasing, but these can only happen through enhanced cross-sector collaboration.","PeriodicalId":19024,"journal":{"name":"Nature Reviews Physics","volume":"6 9","pages":"526-527"},"PeriodicalIF":44.8,"publicationDate":"2024-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142137898","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Thermal transport is a fundamental mechanism of energy transfer process quite distinct from wave propagation phenomena. It can be manipulated well beyond the possibilities offered by natural materials with a new generation of artificial metamaterials: thermal metamaterials. Topological physics, a focal point in contemporary condensed matter physics, has been intertwined with thermal metamaterials in recent years. Inspired by topological photonics and topological acoustics in wave metamaterials, a new research field emerged recently, which we dub ‘topological thermotics’, which encompasses three primary branches: topological thermal conduction, convection and radiation. For topological thermal conduction, we discuss recent advances in both 1D and higher-dimensional thermal topological phases. For topological thermal convection, we discuss the implementation of thermal exceptional points with their unique properties and non-Hermitian thermal topological states. Finally, we review the most recent demonstration of topological effects in the near-field and far-field radiation. Anticipating future developments, we conclude by discussing potential directions of topological thermotics, including the expansion into other diffusion processes such as particle dynamics and plasma physics, and the integration with machine-learning techniques. This Perspective summarizes the recent progress of topological physics in thermal metamaterials and thus proposes a new research field, ‘topological thermotics’, which is inspired by topological photonics and topological acoustics in wave metamaterials.
{"title":"Topological thermal transport","authors":"Zhoufei Liu, Peng Jin, Min Lei, Chengmeng Wang, Fabio Marchesoni, Jian-Hua Jiang, Jiping Huang","doi":"10.1038/s42254-024-00745-w","DOIUrl":"10.1038/s42254-024-00745-w","url":null,"abstract":"Thermal transport is a fundamental mechanism of energy transfer process quite distinct from wave propagation phenomena. It can be manipulated well beyond the possibilities offered by natural materials with a new generation of artificial metamaterials: thermal metamaterials. Topological physics, a focal point in contemporary condensed matter physics, has been intertwined with thermal metamaterials in recent years. Inspired by topological photonics and topological acoustics in wave metamaterials, a new research field emerged recently, which we dub ‘topological thermotics’, which encompasses three primary branches: topological thermal conduction, convection and radiation. For topological thermal conduction, we discuss recent advances in both 1D and higher-dimensional thermal topological phases. For topological thermal convection, we discuss the implementation of thermal exceptional points with their unique properties and non-Hermitian thermal topological states. Finally, we review the most recent demonstration of topological effects in the near-field and far-field radiation. Anticipating future developments, we conclude by discussing potential directions of topological thermotics, including the expansion into other diffusion processes such as particle dynamics and plasma physics, and the integration with machine-learning techniques. This Perspective summarizes the recent progress of topological physics in thermal metamaterials and thus proposes a new research field, ‘topological thermotics’, which is inspired by topological photonics and topological acoustics in wave metamaterials.","PeriodicalId":19024,"journal":{"name":"Nature Reviews Physics","volume":"6 9","pages":"554-565"},"PeriodicalIF":44.8,"publicationDate":"2024-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142137875","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-08DOI: 10.1038/s42254-024-00743-y
Johannes Buchner, Sotiria Fotopoulou
Large, freely available, well-maintained data sets have made astronomy a popular playground for machine learning (ML) projects. Nevertheless, robust insights gained to both ML and physics could be improved by clarity in problem definition and establishing workflows that critically verify, characterize and calibrate ML models. We provide a collection of guidelines to setting up ML projects that are less time-consuming and resource-intensive and more likely to lead to robust and useful scientific insights. We draw examples and experience from astronomy, but the advice is potentially applicable to other areas of science. This Expert Recommendation provides a guide to setting up machine learning projects that are less time-consuming and more likely to lead to robust and useful scientific insights.
免费提供、维护良好的大型数据集已使天文学成为机器学习（ML）项目的热门场所。然而，通过明确问题定义和建立严格验证、描述和校准机器学习模型的工作流程，可以提高机器学习和物理学的强大洞察力。我们提供了一系列指导原则，以建立耗时少、资源密集型的 ML 项目，从而更有可能获得可靠而有用的科学见解。我们借鉴了天文学的实例和经验，但这些建议也可能适用于其他科学领域。本 "专家建议 "为建立机器学习项目提供了指南，这些项目耗时较少，更有可能带来可靠、有用的科学见解。
{"title":"How to set up your first machine learning project in astronomy","authors":"Johannes Buchner, Sotiria Fotopoulou","doi":"10.1038/s42254-024-00743-y","DOIUrl":"10.1038/s42254-024-00743-y","url":null,"abstract":"Large, freely available, well-maintained data sets have made astronomy a popular playground for machine learning (ML) projects. Nevertheless, robust insights gained to both ML and physics could be improved by clarity in problem definition and establishing workflows that critically verify, characterize and calibrate ML models. We provide a collection of guidelines to setting up ML projects that are less time-consuming and resource-intensive and more likely to lead to robust and useful scientific insights. We draw examples and experience from astronomy, but the advice is potentially applicable to other areas of science. This Expert Recommendation provides a guide to setting up machine learning projects that are less time-consuming and more likely to lead to robust and useful scientific insights.","PeriodicalId":19024,"journal":{"name":"Nature Reviews Physics","volume":"6 9","pages":"535-545"},"PeriodicalIF":44.8,"publicationDate":"2024-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141926281","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-05DOI: 10.1038/s42254-024-00740-1
Yang-Hui He (, )
The past five years have seen a dramatic increase in the usage of artificial intelligence (AI) algorithms in pure mathematics and theoretical sciences. This might appear counter-intuitive as mathematical sciences require rigorous definitions, derivations and proofs, in contrast to the experimental sciences, which rely on the modelling of data with error bars. In this Perspective, we categorize the approaches to mathematical and theoretical discovery as ‘top-down’, ‘bottom-up’ and ‘meta-mathematics’. We review the progress over the past few years, comparing and contrasting both the advances and the shortcomings of each approach. We believe that although the theorist is not in danger of being replaced by AI systems in the near future, the combination of human expertise and AI algorithms will become an integral part of theoretical research. Advances in artificial-intelligence-assisted mathematical investigations suggest that human–machine collaboration will be an integral part of future theoretical research.
{"title":"AI-driven research in pure mathematics and theoretical physics","authors":"Yang-Hui He \u0000 (, )","doi":"10.1038/s42254-024-00740-1","DOIUrl":"10.1038/s42254-024-00740-1","url":null,"abstract":"The past five years have seen a dramatic increase in the usage of artificial intelligence (AI) algorithms in pure mathematics and theoretical sciences. This might appear counter-intuitive as mathematical sciences require rigorous definitions, derivations and proofs, in contrast to the experimental sciences, which rely on the modelling of data with error bars. In this Perspective, we categorize the approaches to mathematical and theoretical discovery as ‘top-down’, ‘bottom-up’ and ‘meta-mathematics’. We review the progress over the past few years, comparing and contrasting both the advances and the shortcomings of each approach. We believe that although the theorist is not in danger of being replaced by AI systems in the near future, the combination of human expertise and AI algorithms will become an integral part of theoretical research. Advances in artificial-intelligence-assisted mathematical investigations suggest that human–machine collaboration will be an integral part of future theoretical research.","PeriodicalId":19024,"journal":{"name":"Nature Reviews Physics","volume":"6 9","pages":"546-553"},"PeriodicalIF":44.8,"publicationDate":"2024-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141936385","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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