Pub Date : 2024-04-08DOI: 10.1038/s42254-024-00709-0
Sergei Gukov, James Halverson, Fabian Ruehle
Despite their successes, machine learning techniques are often stochastic, error-prone and blackbox. How could they then be used in fields such as theoretical physics and pure mathematics for which error-free results and deep understanding are a must? In this Perspective, we discuss techniques for obtaining zero-error results with machine learning, with a focus on theoretical physics and pure mathematics. Non-rigorous methods can enable rigorous results via conjecture generation or verification by reinforcement learning. We survey applications of these techniques-for-rigor ranging from string theory to the smooth 4D Poincaré conjecture in low-dimensional topology. We also discuss connections between machine learning theory and mathematics or theoretical physics such as a new approach to field theory motivated by neural network theory, and a theory of Riemannian metric flows induced by neural network gradient descent, which encompasses Perelman’s formulation of the Ricci flow that was used to solve the 3D Poincaré conjecture. Machine learning techniques may appear ill-suited for application in fields that prioritize rigor and deep understanding; however, they have recently found unexpected uses in theoretical physics and pure mathematics. In this Perspective, Gukov, Halverson and Ruehle have discussed rigorous applications of machine learning to theoretical physics and pure mathematics.
{"title":"Rigor with machine learning from field theory to the Poincaré conjecture","authors":"Sergei Gukov, James Halverson, Fabian Ruehle","doi":"10.1038/s42254-024-00709-0","DOIUrl":"10.1038/s42254-024-00709-0","url":null,"abstract":"Despite their successes, machine learning techniques are often stochastic, error-prone and blackbox. How could they then be used in fields such as theoretical physics and pure mathematics for which error-free results and deep understanding are a must? In this Perspective, we discuss techniques for obtaining zero-error results with machine learning, with a focus on theoretical physics and pure mathematics. Non-rigorous methods can enable rigorous results via conjecture generation or verification by reinforcement learning. We survey applications of these techniques-for-rigor ranging from string theory to the smooth 4D Poincaré conjecture in low-dimensional topology. We also discuss connections between machine learning theory and mathematics or theoretical physics such as a new approach to field theory motivated by neural network theory, and a theory of Riemannian metric flows induced by neural network gradient descent, which encompasses Perelman’s formulation of the Ricci flow that was used to solve the 3D Poincaré conjecture. Machine learning techniques may appear ill-suited for application in fields that prioritize rigor and deep understanding; however, they have recently found unexpected uses in theoretical physics and pure mathematics. In this Perspective, Gukov, Halverson and Ruehle have discussed rigorous applications of machine learning to theoretical physics and pure mathematics.","PeriodicalId":19024,"journal":{"name":"Nature Reviews Physics","volume":"6 5","pages":"310-319"},"PeriodicalIF":38.5,"publicationDate":"2024-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140582150","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 : 2024-04-08DOI: 10.1038/s42254-024-00712-5
Kamyar Azizzadenesheli, Nikola Kovachki, Zongyi Li, Miguel Liu-Schiaffini, Jean Kossaifi, Anima Anandkumar
Scientific discovery and engineering design are currently limited by the time and cost of physical experiments. Numerical simulations are an alternative approach but are usually intractable for complex real-world problems. Artificial intelligence promises a solution through fast data-driven surrogate models. In particular, neural operators present a principled framework for learning mappings between functions defined on continuous domains, such as spatiotemporal processes and partial differential equations. Neural operators can extrapolate and predict solutions at new locations unseen during training. They can be integrated with physics and other domain constraints enforced at finer resolutions to obtain high-fidelity solutions and good generalization. Neural operators are differentiable, so they can directly optimize parameters for inverse design and other inverse problems. Neural operators can therefore augment, or even replace, existing numerical simulators in many applications, such as computational fluid dynamics, weather forecasting and material modelling, providing speedups of four to five orders of magnitude. Neural operators learn mappings between functions on continuous domains, such as spatiotemporal processes and partial differential equations, offering a fast, data-driven surrogate model solution for otherwise intractable numerical simulations of complex real-world problems.
{"title":"Neural operators for accelerating scientific simulations and design","authors":"Kamyar Azizzadenesheli, Nikola Kovachki, Zongyi Li, Miguel Liu-Schiaffini, Jean Kossaifi, Anima Anandkumar","doi":"10.1038/s42254-024-00712-5","DOIUrl":"10.1038/s42254-024-00712-5","url":null,"abstract":"Scientific discovery and engineering design are currently limited by the time and cost of physical experiments. Numerical simulations are an alternative approach but are usually intractable for complex real-world problems. Artificial intelligence promises a solution through fast data-driven surrogate models. In particular, neural operators present a principled framework for learning mappings between functions defined on continuous domains, such as spatiotemporal processes and partial differential equations. Neural operators can extrapolate and predict solutions at new locations unseen during training. They can be integrated with physics and other domain constraints enforced at finer resolutions to obtain high-fidelity solutions and good generalization. Neural operators are differentiable, so they can directly optimize parameters for inverse design and other inverse problems. Neural operators can therefore augment, or even replace, existing numerical simulators in many applications, such as computational fluid dynamics, weather forecasting and material modelling, providing speedups of four to five orders of magnitude. Neural operators learn mappings between functions on continuous domains, such as spatiotemporal processes and partial differential equations, offering a fast, data-driven surrogate model solution for otherwise intractable numerical simulations of complex real-world problems.","PeriodicalId":19024,"journal":{"name":"Nature Reviews Physics","volume":"6 5","pages":"320-328"},"PeriodicalIF":38.5,"publicationDate":"2024-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140582497","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 : 2024-04-01DOI: 10.1038/s42254-024-00717-0
Many everyday English words have a double meaning, being used as physics jargon. This month, we share some of our favourite stories of how physics terms came to be.
{"title":"Physics words with surprising origins","authors":"","doi":"10.1038/s42254-024-00717-0","DOIUrl":"10.1038/s42254-024-00717-0","url":null,"abstract":"Many everyday English words have a double meaning, being used as physics jargon. This month, we share some of our favourite stories of how physics terms came to be.","PeriodicalId":19024,"journal":{"name":"Nature Reviews Physics","volume":"6 4","pages":"209-209"},"PeriodicalIF":38.5,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s42254-024-00717-0.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140538048","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-03-22DOI: 10.1038/s42254-024-00699-z
Amin Morteza Najarian, Maral Vafaie, Bin Chen, F. Pelayo García de Arquer, Edward H. Sargent
Fast-response optical sensing across the electromagnetic spectrum is an enabler of quantum systems, 3D machine vision and augmented reality, yet existing technologies are not optimized for infrared sensing. Trade-offs among characteristics such as speed, efficiency, noise, spectral detection range and cost motivate the research community to develop nanostructured sensing materials that provide operation from visible to infrared wavelengths with seamless integration. As efforts are made to advance the combined gain and bandwidth of devices, a clear understanding of physical mechanisms underlying the dynamics of charge carriers, with a particular focus on speed-limiting processes, is of high priority. In this Review, we provide an account of the photophysical attributes of active materials and their impact on optical sensor performance, focusing on the interplay between temporal and peak response to pulsed light of varying durations. We identify performance-limiting processes and directions for future progress in developing materials and device architectures that realize high-speed photodetection. Developing photodetectors that work across the electromagnetic spectrum remains a challenge, and there are many trade-offs to be considered, including speed, efficiency, noise, spectral detection range and cost. This Review discusses the photophysical attributes of the active materials that define the interrelated aspects of response amplitude and temporal dynamics in photodetectors.
{"title":"Photophysical properties of materials for high-speed photodetection","authors":"Amin Morteza Najarian, Maral Vafaie, Bin Chen, F. Pelayo García de Arquer, Edward H. Sargent","doi":"10.1038/s42254-024-00699-z","DOIUrl":"10.1038/s42254-024-00699-z","url":null,"abstract":"Fast-response optical sensing across the electromagnetic spectrum is an enabler of quantum systems, 3D machine vision and augmented reality, yet existing technologies are not optimized for infrared sensing. Trade-offs among characteristics such as speed, efficiency, noise, spectral detection range and cost motivate the research community to develop nanostructured sensing materials that provide operation from visible to infrared wavelengths with seamless integration. As efforts are made to advance the combined gain and bandwidth of devices, a clear understanding of physical mechanisms underlying the dynamics of charge carriers, with a particular focus on speed-limiting processes, is of high priority. In this Review, we provide an account of the photophysical attributes of active materials and their impact on optical sensor performance, focusing on the interplay between temporal and peak response to pulsed light of varying durations. We identify performance-limiting processes and directions for future progress in developing materials and device architectures that realize high-speed photodetection. Developing photodetectors that work across the electromagnetic spectrum remains a challenge, and there are many trade-offs to be considered, including speed, efficiency, noise, spectral detection range and cost. This Review discusses the photophysical attributes of the active materials that define the interrelated aspects of response amplitude and temporal dynamics in photodetectors.","PeriodicalId":19024,"journal":{"name":"Nature Reviews Physics","volume":"6 4","pages":"219-230"},"PeriodicalIF":38.5,"publicationDate":"2024-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140198219","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 : 2024-03-19DOI: 10.1038/s42254-024-00707-2
Andrew Massey, Jamie Stewart, Chynna Smith, Cameron Parvini, Moira McCormick, Kun Do, Alexander X. Cartagena-Rivera
The mechanical properties of cells and tissues help determine their architecture, composition and function. Alterations to these properties are associated with many diseases, including cancer. Tensional, compressive, adhesive, elastic and viscous properties of individual cells and multicellular tissues are mostly regulated by reorganization of the actomyosin and microtubule cytoskeletons and extracellular glycocalyx, which in turn drive many pathophysiological processes, including cancer progression. This Review provides an in-depth collection of quantitative data on diverse mechanical properties of living human cancer cells and tissues. Additionally, the implications of mechanical property changes for cancer development are discussed. An increased knowledge of the mechanical properties of the tumour microenvironment, as collected using biomechanical approaches capable of multi-timescale and multiparametric analyses, will provide a better understanding of the complex mechanical determinants of cancer organization and progression. This information can lead to a further understanding of resistance mechanisms to chemotherapies and immunotherapies and the metastatic cascade. This Review summarizes differences in several mechanical properties that play a role in human cancer development, at the cell and tissue levels. Comprehensive cell and tissue quantitative mechanical properties are provided based on cancer types and organs of origin.
{"title":"Mechanical properties of human tumour tissues and their implications for cancer development","authors":"Andrew Massey, Jamie Stewart, Chynna Smith, Cameron Parvini, Moira McCormick, Kun Do, Alexander X. Cartagena-Rivera","doi":"10.1038/s42254-024-00707-2","DOIUrl":"10.1038/s42254-024-00707-2","url":null,"abstract":"The mechanical properties of cells and tissues help determine their architecture, composition and function. Alterations to these properties are associated with many diseases, including cancer. Tensional, compressive, adhesive, elastic and viscous properties of individual cells and multicellular tissues are mostly regulated by reorganization of the actomyosin and microtubule cytoskeletons and extracellular glycocalyx, which in turn drive many pathophysiological processes, including cancer progression. This Review provides an in-depth collection of quantitative data on diverse mechanical properties of living human cancer cells and tissues. Additionally, the implications of mechanical property changes for cancer development are discussed. An increased knowledge of the mechanical properties of the tumour microenvironment, as collected using biomechanical approaches capable of multi-timescale and multiparametric analyses, will provide a better understanding of the complex mechanical determinants of cancer organization and progression. This information can lead to a further understanding of resistance mechanisms to chemotherapies and immunotherapies and the metastatic cascade. This Review summarizes differences in several mechanical properties that play a role in human cancer development, at the cell and tissue levels. Comprehensive cell and tissue quantitative mechanical properties are provided based on cancer types and organs of origin.","PeriodicalId":19024,"journal":{"name":"Nature Reviews Physics","volume":"6 4","pages":"269-282"},"PeriodicalIF":38.5,"publicationDate":"2024-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140172383","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 : 2024-03-19DOI: 10.1038/s42254-024-00703-6
Andreas Crivellin, Bruce Mellado
The standard model (SM) of particle physics is the mathematical description of the fundamental constituents and interactions of matter. Its last missing particle, the Higgs boson, was observed in 2012. However, there are several phenomena that the SM cannot account for (such as dark-matter particles, or non-vanishing neutrino masses), neither does it describe gravity. There must be more to discover, to extend the SM into a full description of nature. Here we review the hints of new physics, called anomalies, that are seen for various interactions as discrepancies between standard-model predictions and experimental measurements. We consider both direct high-energy searches for new particles at the Large Hadron Collider at CERN and indirect low-energy precision experiments. These anomalies span an energy scale of more than four orders of magnitude: from the mass of the proton, to the electroweak scale (approximately the mass of the Higgs boson), to the teraelectronvolt scale, which is the highest scale directly accessible at the Large Hadron Collider. We discuss the experimental and theoretical status of various anomalies and summarize possible explanations in terms of new particles and new interactions as well as discovery prospects. We suggest, in particular, that new additional Higgs bosons and so-called leptoquarks are promising candidates for extending the standard model. The standard model of particle physics describes the fundamental constituents of matter and their interactions. We review the status of experimental hints for new physics, which, if confirmed, would require the extension of the standard model with new particles and new interactions.
{"title":"Anomalies in particle physics and their implications for physics beyond the standard model","authors":"Andreas Crivellin, Bruce Mellado","doi":"10.1038/s42254-024-00703-6","DOIUrl":"10.1038/s42254-024-00703-6","url":null,"abstract":"The standard model (SM) of particle physics is the mathematical description of the fundamental constituents and interactions of matter. Its last missing particle, the Higgs boson, was observed in 2012. However, there are several phenomena that the SM cannot account for (such as dark-matter particles, or non-vanishing neutrino masses), neither does it describe gravity. There must be more to discover, to extend the SM into a full description of nature. Here we review the hints of new physics, called anomalies, that are seen for various interactions as discrepancies between standard-model predictions and experimental measurements. We consider both direct high-energy searches for new particles at the Large Hadron Collider at CERN and indirect low-energy precision experiments. These anomalies span an energy scale of more than four orders of magnitude: from the mass of the proton, to the electroweak scale (approximately the mass of the Higgs boson), to the teraelectronvolt scale, which is the highest scale directly accessible at the Large Hadron Collider. We discuss the experimental and theoretical status of various anomalies and summarize possible explanations in terms of new particles and new interactions as well as discovery prospects. We suggest, in particular, that new additional Higgs bosons and so-called leptoquarks are promising candidates for extending the standard model. The standard model of particle physics describes the fundamental constituents of matter and their interactions. We review the status of experimental hints for new physics, which, if confirmed, would require the extension of the standard model with new particles and new interactions.","PeriodicalId":19024,"journal":{"name":"Nature Reviews Physics","volume":"6 5","pages":"294-309"},"PeriodicalIF":38.5,"publicationDate":"2024-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140197856","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}
Because of analogies between the 2D Maxwell equations and water wave equations, methods for manipulating electromagnetic waves based on photonic crystals and metamaterials can be extended to manipulate water waves. Doing so provides new opportunities to investigate the interaction of water waves with structures. In this Review, we introduce the research progress of controlling water waves with water wave crystals and metamaterials and summarize the basic theory and calculation methods for water waves. The working principles and design methods for water wave crystals and metamaterials are described, and their properties and applications are presented. We also discuss the current challenges in this field and future directions. Similar to acoustic and electromagnetic waves, water waves are classical waves that can be controlled by artificial structures such as water wave crystals and metamaterials. This Review surveys the development of water wave manipulation using artificial structures and describes its potential applications.
{"title":"Controlling water waves with artificial structures","authors":"Shan Zhu, Xinyu Zhao, Linkang Han, Jian Zi, Xinhua Hu, Huanyang Chen","doi":"10.1038/s42254-024-00701-8","DOIUrl":"10.1038/s42254-024-00701-8","url":null,"abstract":"Because of analogies between the 2D Maxwell equations and water wave equations, methods for manipulating electromagnetic waves based on photonic crystals and metamaterials can be extended to manipulate water waves. Doing so provides new opportunities to investigate the interaction of water waves with structures. In this Review, we introduce the research progress of controlling water waves with water wave crystals and metamaterials and summarize the basic theory and calculation methods for water waves. The working principles and design methods for water wave crystals and metamaterials are described, and their properties and applications are presented. We also discuss the current challenges in this field and future directions. Similar to acoustic and electromagnetic waves, water waves are classical waves that can be controlled by artificial structures such as water wave crystals and metamaterials. This Review surveys the development of water wave manipulation using artificial structures and describes its potential applications.","PeriodicalId":19024,"journal":{"name":"Nature Reviews Physics","volume":"6 4","pages":"231-245"},"PeriodicalIF":38.5,"publicationDate":"2024-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140172667","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 : 2024-03-13DOI: 10.1038/s42254-024-00705-4
Kimberli Bell, Taylor M. Cannon, Amira M. Eltony, Chhavi Goenka, Abigail L. Gregg, Nathaniel Hai, Danielle J. Harper, Helen Keshishian, Nichaluk Leartprapun, Haley L. Marks, David O. Otuya, Linhui Yu
Science and society are inextricably entangled, but the discussion of social issues in optics and photonics is, at best, treated as peripheral to the field. A group of researchers, technicians, administrative staff, and clinical liaisons share how they came together to start a conversation recognizing these oft-disregarded issues.
{"title":"Starting a conversation about social issues in optics and photonics","authors":"Kimberli Bell, Taylor M. Cannon, Amira M. Eltony, Chhavi Goenka, Abigail L. Gregg, Nathaniel Hai, Danielle J. Harper, Helen Keshishian, Nichaluk Leartprapun, Haley L. Marks, David O. Otuya, Linhui Yu","doi":"10.1038/s42254-024-00705-4","DOIUrl":"10.1038/s42254-024-00705-4","url":null,"abstract":"Science and society are inextricably entangled, but the discussion of social issues in optics and photonics is, at best, treated as peripheral to the field. A group of researchers, technicians, administrative staff, and clinical liaisons share how they came together to start a conversation recognizing these oft-disregarded issues.","PeriodicalId":19024,"journal":{"name":"Nature Reviews Physics","volume":"6 5","pages":"286-288"},"PeriodicalIF":38.5,"publicationDate":"2024-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140155520","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 : 2024-03-11DOI: 10.1038/s42254-024-00711-6
Chiara Caprini
In 2023, pulsar timing arrays announced what could become the first ever discovery of a stochastic gravitational wave background: the random superposition of gravitational waves permeating the cosmos — a vestige of cosmic processes in the Universe. Upcoming datasets are expected to confirm the discovery and provide insight into the origin of this signal. In 2023, pulsar timing arrays announced what could become the first ever discovery of a stochastic gravitational wave background: the random superposition of gravitational waves permeating the cosmos — a vestige of cosmic processes in the Universe.
{"title":"Strong evidence for the discovery of a gravitational wave background","authors":"Chiara Caprini","doi":"10.1038/s42254-024-00711-6","DOIUrl":"10.1038/s42254-024-00711-6","url":null,"abstract":"In 2023, pulsar timing arrays announced what could become the first ever discovery of a stochastic gravitational wave background: the random superposition of gravitational waves permeating the cosmos — a vestige of cosmic processes in the Universe. Upcoming datasets are expected to confirm the discovery and provide insight into the origin of this signal. In 2023, pulsar timing arrays announced what could become the first ever discovery of a stochastic gravitational wave background: the random superposition of gravitational waves permeating the cosmos — a vestige of cosmic processes in the Universe.","PeriodicalId":19024,"journal":{"name":"Nature Reviews Physics","volume":"6 5","pages":"291-293"},"PeriodicalIF":38.5,"publicationDate":"2024-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140099499","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":"Olfactory cues and memories in animal navigation","authors":"Thierry Emonet, Massimo Vergassola","doi":"10.1038/s42254-024-00710-7","DOIUrl":"10.1038/s42254-024-00710-7","url":null,"abstract":"Thierry Emonet and Massimo Vergassola discuss what research shows about how animals perform the feat of navigating by smell.","PeriodicalId":19024,"journal":{"name":"Nature Reviews Physics","volume":"6 4","pages":"215-216"},"PeriodicalIF":38.5,"publicationDate":"2024-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140099497","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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