Parity-time (PT) symmetry has enabled the demonstration of fascinating wave phenomena in non-Hermitian systems characterized by precisely balanced gain and loss. Until now, the exploration and observation of PT symmetry in scattering settings have largely been limited to propagating waves. Here, we demonstrate a versatile coupled-resonator acoustic waveguide (CRAW) system that enables the observation of PT-symmetric scattering responses for evanescent waves within a bandgap. By examining the generalized scattering matrix in the evanescent wave regime, we observe hallmark PT-symmetric phenomena—including phase transitions at an exceptional point, anisotropic transmission resonances, and laser-absorber modes—in systems that do not require balanced distributions of gain and loss. Owing to the peculiar energy transfer features of evanescent waves, our results not only demonstrate a distinct pathway for observing PT symmetry, but also enable strategies for exotic energy tunneling mechanisms, paving fresh directions for wave engineering grounded in non-Hermitian physics. Non-Hermitian physics and parity-time (PT) symmetry are of broad interest in classical wave systems. This work demonstrates evanescent wave manipulation and scattering control based on PT symmetry in a versatile coupled-resonator acoustic waveguide (CRAW) system, which not only extends the framework of non-Hermitian physics but also offers strategies for near-field manipulation and control.
{"title":"Observation of parity-time symmetry for evanescent waves","authors":"Zhaoxian Chen, Huan He, Huanan Li, Meijie Li, Jun-long Kou, Yan-qing Lu, Jingjun Xu, Andrea Alù","doi":"10.1038/s42005-024-01816-1","DOIUrl":"10.1038/s42005-024-01816-1","url":null,"abstract":"Parity-time (PT) symmetry has enabled the demonstration of fascinating wave phenomena in non-Hermitian systems characterized by precisely balanced gain and loss. Until now, the exploration and observation of PT symmetry in scattering settings have largely been limited to propagating waves. Here, we demonstrate a versatile coupled-resonator acoustic waveguide (CRAW) system that enables the observation of PT-symmetric scattering responses for evanescent waves within a bandgap. By examining the generalized scattering matrix in the evanescent wave regime, we observe hallmark PT-symmetric phenomena—including phase transitions at an exceptional point, anisotropic transmission resonances, and laser-absorber modes—in systems that do not require balanced distributions of gain and loss. Owing to the peculiar energy transfer features of evanescent waves, our results not only demonstrate a distinct pathway for observing PT symmetry, but also enable strategies for exotic energy tunneling mechanisms, paving fresh directions for wave engineering grounded in non-Hermitian physics. Non-Hermitian physics and parity-time (PT) symmetry are of broad interest in classical wave systems. This work demonstrates evanescent wave manipulation and scattering control based on PT symmetry in a versatile coupled-resonator acoustic waveguide (CRAW) system, which not only extends the framework of non-Hermitian physics but also offers strategies for near-field manipulation and control.","PeriodicalId":10540,"journal":{"name":"Communications Physics","volume":" ","pages":"1-8"},"PeriodicalIF":5.4,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s42005-024-01816-1.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142443620","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 : 2024-10-15DOI: 10.1038/s42005-024-01832-1
Xiao Xue, Shuo Wang, Hua-Dong Yao, Lars Davidson, Peter V. Coveney
Data-driven approaches offer novel opportunities for improving the performance of turbulent flow simulations, which are critical to wide-ranging applications from wind farms and aerodynamic designs to weather and climate forecasting. However, current methods for these simulations often require large amounts of data and computational resources. While data-driven methods have been extensively applied to the continuum Navier-Stokes equations, limited work has been done to integrate these methods with the highly scalable lattice Boltzmann method. Here, we present a physics-informed neural network framework for improving lattice Boltzmann-based simulations of near-wall turbulent flow. Using a small amount of data and integrating physical constraints, our model accurately predicts flow behaviour at a wide range of friction Reynolds numbers up to 1.0 × 106. In contradistinction with other models that use direct numerical simulation datasets, this approach reduces data requirements by three orders of magnitude and allows for sparse grid configurations. Our work broadens the scope of lattice Boltzmann applications, enabling efficient large-scale simulations of turbulent flow in diverse contexts. The authors provide a data-driven near-wall modelling framework for the lattice Boltzmann method using IDDES data. Their model can predict flows with friction Reynolds numbers up to 1,000,000 and effectively handle sparse near-wall grids.
{"title":"Physics informed data-driven near-wall modelling for lattice Boltzmann simulation of high Reynolds number turbulent flows","authors":"Xiao Xue, Shuo Wang, Hua-Dong Yao, Lars Davidson, Peter V. Coveney","doi":"10.1038/s42005-024-01832-1","DOIUrl":"10.1038/s42005-024-01832-1","url":null,"abstract":"Data-driven approaches offer novel opportunities for improving the performance of turbulent flow simulations, which are critical to wide-ranging applications from wind farms and aerodynamic designs to weather and climate forecasting. However, current methods for these simulations often require large amounts of data and computational resources. While data-driven methods have been extensively applied to the continuum Navier-Stokes equations, limited work has been done to integrate these methods with the highly scalable lattice Boltzmann method. Here, we present a physics-informed neural network framework for improving lattice Boltzmann-based simulations of near-wall turbulent flow. Using a small amount of data and integrating physical constraints, our model accurately predicts flow behaviour at a wide range of friction Reynolds numbers up to 1.0 × 106. In contradistinction with other models that use direct numerical simulation datasets, this approach reduces data requirements by three orders of magnitude and allows for sparse grid configurations. Our work broadens the scope of lattice Boltzmann applications, enabling efficient large-scale simulations of turbulent flow in diverse contexts. The authors provide a data-driven near-wall modelling framework for the lattice Boltzmann method using IDDES data. Their model can predict flows with friction Reynolds numbers up to 1,000,000 and effectively handle sparse near-wall grids.","PeriodicalId":10540,"journal":{"name":"Communications Physics","volume":" ","pages":"1-8"},"PeriodicalIF":5.4,"publicationDate":"2024-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s42005-024-01832-1.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142443634","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}
Spin-orbitronics, exploiting electron spin and/or orbital angular momentum, offers a powerful route to energy-efficient spintronic applications. Recent research on orbital currents in light metals broadens the scope of spin-orbit torque (SOT). However, distinguishing and manipulating orbital torque in heavy metal/ferromagnet (HM/FM) remains a challenge, limiting the promising synergy of spin and orbital currents. Here, we design a HM/FM/FMSOC heterostructure and experimentally separate orbital torque contribution from spin torque by utilizing the distinct diffusion length of spin and orbital currents. Furthermore, we achieve the synergy of spin and orbital torques by controlling their relative strength, and obtain a 110% improvement in torque efficiency compared to the representative Pt/Co bilayer. Our findings not only contribute to a deeper understanding of SOT mechanisms and orbital current transport in HM/FM multilayers, but also highlight the promising prospect of orbital and spin torque synergy for optimizing the efficiency of next-generation spintronic devices. Eliminating the interference of spin current to distinguish and manipulate orbital torque in heavy metal/ferromagnet (HM/FM) heterojunction remains a challenge. Here, the authors design a HM/FM/FMSOC multilayer to separate orbital torque contribution and harness the synergy of spin and orbital currents for enhanced spin-orbit torque.
自旋轨道电子学利用电子自旋和/或轨道角动量，为高能效自旋电子学应用提供了一条强大的途径。最近对轻金属中轨道电流的研究拓宽了自旋轨道力矩（SOT）的范围。然而，在重金属/铁磁体（HM/FM）中区分和操纵轨道力矩仍然是一个挑战，限制了自旋和轨道电流的协同作用。在这里，我们设计了一种 HM/FM/FMSOC 异质结构，并利用自旋电流和轨道电流不同的扩散长度，通过实验将轨道转矩贡献从自旋转矩中分离出来。此外，我们还通过控制自旋扭矩和轨道扭矩的相对强度来实现它们的协同作用，与具有代表性的铂/钴双层结构相比，扭矩效率提高了 110%。我们的发现不仅有助于加深对 HM/FM 多层中的 SOT 机制和轨道电流传输的理解，还凸显了轨道扭矩和自旋扭矩协同作用在优化下一代自旋电子器件效率方面的广阔前景。消除自旋电流的干扰以区分和操纵重金属/铁磁体（HM/FM）异质结中的轨道力矩仍然是一项挑战。在此，作者设计了一种 HM/FM/FMSOC 多层，以分离轨道力矩的贡献，并利用自旋和轨道电流的协同作用来增强自旋轨道力矩。
{"title":"Harnessing synergy of spin and orbital currents in heavy metal/ferromagnet multilayers","authors":"Yumin Yang, Zhicheng Xie, Zhiyuan Zhao, Na Lei, Jianhua Zhao, Dahai Wei","doi":"10.1038/s42005-024-01829-w","DOIUrl":"10.1038/s42005-024-01829-w","url":null,"abstract":"Spin-orbitronics, exploiting electron spin and/or orbital angular momentum, offers a powerful route to energy-efficient spintronic applications. Recent research on orbital currents in light metals broadens the scope of spin-orbit torque (SOT). However, distinguishing and manipulating orbital torque in heavy metal/ferromagnet (HM/FM) remains a challenge, limiting the promising synergy of spin and orbital currents. Here, we design a HM/FM/FMSOC heterostructure and experimentally separate orbital torque contribution from spin torque by utilizing the distinct diffusion length of spin and orbital currents. Furthermore, we achieve the synergy of spin and orbital torques by controlling their relative strength, and obtain a 110% improvement in torque efficiency compared to the representative Pt/Co bilayer. Our findings not only contribute to a deeper understanding of SOT mechanisms and orbital current transport in HM/FM multilayers, but also highlight the promising prospect of orbital and spin torque synergy for optimizing the efficiency of next-generation spintronic devices. Eliminating the interference of spin current to distinguish and manipulate orbital torque in heavy metal/ferromagnet (HM/FM) heterojunction remains a challenge. Here, the authors design a HM/FM/FMSOC multilayer to separate orbital torque contribution and harness the synergy of spin and orbital currents for enhanced spin-orbit torque.","PeriodicalId":10540,"journal":{"name":"Communications Physics","volume":" ","pages":"1-8"},"PeriodicalIF":5.4,"publicationDate":"2024-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s42005-024-01829-w.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142443633","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 : 2024-10-14DOI: 10.1038/s42005-024-01831-2
Tytti Kärki, Into Pääkkönen, Nikos Kyriakopoulos, Jaakko V. I. Timonen
Sessile drops are ubiquitous and important in technological applications. While dynamics of liquid drops have been studied under confinement, the possibility of creating sessile drops with reduced dimensionality has not been explored. Here, we demonstrate a quasi-two-dimensional (Q2D) analogy for axisymmetric sessile three-dimensional (3D) drops. The Q2D drops are created by confining liquids between parallel vertical walls, forming low aspect ratio capillary bridges deformed by gravity. Stationary Q2D drops adopt projected shapes analogous to 3D sessile drops, ranging from circular drops to puddles. When moving, the Q2D drops exhibit capillary and fluid mechanical behaviours conceptually analogous to 3D drops, including impacts and sliding. The Q2D drops also exhibit more complex phenomena such as levitation, various instabilities and pattern formation when subjected to external electric, magnetic and flow fields. The 3D-Q2D analogy suggests that the diverse and often complicated phenomena observed in 3D drops can be studied in the simplified Q2D geometry. Additionally, the Q2D confinement analogy allows exploring phenomena arising from the reduced dimensionality and the altered boundary conditions. Axisymmetric sessile liquid drops are everywhere around us and important in numerous technological applications. Here the authors experimentally prepare quasi-two-dimensional sessile drops and show that they display many similar features as the traditional axisymmetric sessile drops, including analogous equilibrium shape, dynamics, and instabilities.
{"title":"Quasi-two-dimensional pseudo-sessile drops","authors":"Tytti Kärki, Into Pääkkönen, Nikos Kyriakopoulos, Jaakko V. I. Timonen","doi":"10.1038/s42005-024-01831-2","DOIUrl":"10.1038/s42005-024-01831-2","url":null,"abstract":"Sessile drops are ubiquitous and important in technological applications. While dynamics of liquid drops have been studied under confinement, the possibility of creating sessile drops with reduced dimensionality has not been explored. Here, we demonstrate a quasi-two-dimensional (Q2D) analogy for axisymmetric sessile three-dimensional (3D) drops. The Q2D drops are created by confining liquids between parallel vertical walls, forming low aspect ratio capillary bridges deformed by gravity. Stationary Q2D drops adopt projected shapes analogous to 3D sessile drops, ranging from circular drops to puddles. When moving, the Q2D drops exhibit capillary and fluid mechanical behaviours conceptually analogous to 3D drops, including impacts and sliding. The Q2D drops also exhibit more complex phenomena such as levitation, various instabilities and pattern formation when subjected to external electric, magnetic and flow fields. The 3D-Q2D analogy suggests that the diverse and often complicated phenomena observed in 3D drops can be studied in the simplified Q2D geometry. Additionally, the Q2D confinement analogy allows exploring phenomena arising from the reduced dimensionality and the altered boundary conditions. Axisymmetric sessile liquid drops are everywhere around us and important in numerous technological applications. Here the authors experimentally prepare quasi-two-dimensional sessile drops and show that they display many similar features as the traditional axisymmetric sessile drops, including analogous equilibrium shape, dynamics, and instabilities.","PeriodicalId":10540,"journal":{"name":"Communications Physics","volume":" ","pages":"1-9"},"PeriodicalIF":5.4,"publicationDate":"2024-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s42005-024-01831-2.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142443610","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 : 2024-10-14DOI: 10.1038/s42005-024-01811-6
Vasilis Belis, Kinga Anna Woźniak, Ema Puljak, Panagiotis Barkoutsos, Günther Dissertori, Michele Grossi, Maurizio Pierini, Florentin Reiter, Ivano Tavernelli, Sofia Vallecorsa
The ongoing quest to discover new phenomena at the LHC necessitates the continuous development of algorithms and technologies. Established approaches like machine learning, along with emerging technologies such as quantum computing show promise in the enhancement of experimental capabilities. In this work, we propose a strategy for anomaly detection tasks at the LHC based on unsupervised quantum machine learning, and demonstrate its effectiveness in identifying new phenomena. The designed quantum models-an unsupervised kernel machine and two clustering algorithms-are trained to detect new-physics events using a latent representation of LHC data, generated by an autoencoder designed to accommodate current quantum hardware limitations on problem size. For kernel-based anomaly detection, we implement an instance of the model on a quantum computer, and we identify a regime where it significantly outperforms its classical counterparts. We show that the observed performance enhancement is related to the quantum resources utilised by the model. The ongoing quest in particle physics to discover fundamentally new phenomena necessitates the continuous development of algorithms and technologies. The authors propose a methodology based on quantum machine learning that can identify new phenomena in proton collision experiments, showing that it can outperform its classical counterparts when sufficient quantum computing resources are utilized.
{"title":"Quantum anomaly detection in the latent space of proton collision events at the LHC","authors":"Vasilis Belis, Kinga Anna Woźniak, Ema Puljak, Panagiotis Barkoutsos, Günther Dissertori, Michele Grossi, Maurizio Pierini, Florentin Reiter, Ivano Tavernelli, Sofia Vallecorsa","doi":"10.1038/s42005-024-01811-6","DOIUrl":"10.1038/s42005-024-01811-6","url":null,"abstract":"The ongoing quest to discover new phenomena at the LHC necessitates the continuous development of algorithms and technologies. Established approaches like machine learning, along with emerging technologies such as quantum computing show promise in the enhancement of experimental capabilities. In this work, we propose a strategy for anomaly detection tasks at the LHC based on unsupervised quantum machine learning, and demonstrate its effectiveness in identifying new phenomena. The designed quantum models-an unsupervised kernel machine and two clustering algorithms-are trained to detect new-physics events using a latent representation of LHC data, generated by an autoencoder designed to accommodate current quantum hardware limitations on problem size. For kernel-based anomaly detection, we implement an instance of the model on a quantum computer, and we identify a regime where it significantly outperforms its classical counterparts. We show that the observed performance enhancement is related to the quantum resources utilised by the model. The ongoing quest in particle physics to discover fundamentally new phenomena necessitates the continuous development of algorithms and technologies. The authors propose a methodology based on quantum machine learning that can identify new phenomena in proton collision experiments, showing that it can outperform its classical counterparts when sufficient quantum computing resources are utilized.","PeriodicalId":10540,"journal":{"name":"Communications Physics","volume":" ","pages":"1-11"},"PeriodicalIF":5.4,"publicationDate":"2024-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s42005-024-01811-6.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142443629","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 : 2024-10-14DOI: 10.1038/s42005-024-01830-3
Helcio Felippe, Federico Battiston, Alec Kirkley
A wide range of tasks in network analysis, such as clustering network populations or identifying anomalies in temporal graph streams, require a measure of the similarity between two graphs. To provide a meaningful data summary for downstream scientific analyses, the graph similarity measures used for these tasks must be principled, interpretable, and capable of distinguishing meaningful overlapping network structure from statistical noise at different scales of interest. Here we derive a family of graph mutual information measures that satisfy these criteria and are constructed using only fundamental information theoretic principles. Our measures capture the information shared among networks according to different encodings of their structural information, with our mesoscale mutual information measure allowing for network comparison under any specified network coarse-graining. We test our measures in a range of applications on real and synthetic network data, finding that they effectively highlight intuitive aspects of network similarity across scales in a variety of systems. Graph similarity measures are essential for downstream tasks including clustering, embedding, and regression with populations of networks. Here the authors derive a family of graph mutual information measures that allow for a principled, interpretable, and efficient comparison of networks at multiple scales.
{"title":"Network mutual information measures for graph similarity","authors":"Helcio Felippe, Federico Battiston, Alec Kirkley","doi":"10.1038/s42005-024-01830-3","DOIUrl":"10.1038/s42005-024-01830-3","url":null,"abstract":"A wide range of tasks in network analysis, such as clustering network populations or identifying anomalies in temporal graph streams, require a measure of the similarity between two graphs. To provide a meaningful data summary for downstream scientific analyses, the graph similarity measures used for these tasks must be principled, interpretable, and capable of distinguishing meaningful overlapping network structure from statistical noise at different scales of interest. Here we derive a family of graph mutual information measures that satisfy these criteria and are constructed using only fundamental information theoretic principles. Our measures capture the information shared among networks according to different encodings of their structural information, with our mesoscale mutual information measure allowing for network comparison under any specified network coarse-graining. We test our measures in a range of applications on real and synthetic network data, finding that they effectively highlight intuitive aspects of network similarity across scales in a variety of systems. Graph similarity measures are essential for downstream tasks including clustering, embedding, and regression with populations of networks. Here the authors derive a family of graph mutual information measures that allow for a principled, interpretable, and efficient comparison of networks at multiple scales.","PeriodicalId":10540,"journal":{"name":"Communications Physics","volume":" ","pages":"1-12"},"PeriodicalIF":5.4,"publicationDate":"2024-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s42005-024-01830-3.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142443623","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 : 2024-10-14DOI: 10.1038/s42005-024-01834-z
Peter Deák, Song Li, Adam Gali
Defect-related spin-to-photon interfaces in silicon promise the realization of quantum repeaters by combining advanced semiconductor and photonics technologies. Recently, controlled creation/erasure of simple carbon interstitial defects have been successfully realised in silicon. This defect has a stable structure near room temperature and coherently emits in the wave-length where the signal loss is minimal in optical fibres used in communication technologies. Our in-depth theoretical characterization confirms the assignment of the observed emission to the neutral charge state of this defect, as arising due to the recombination of a bound exciton. We also identified a metastable triplet state that could be applied as a quantum memory. Based on the analysis of the electronic structure of the defect and its similarities to a known optically detected magnetic resonance centre in silicon, we propose that a carbon interstitial can act as a quantum bit and may realize a spin-to-photon interface in complementary metal-oxide semiconductor-compatible platforms. This work presents a theoretical investigation of the single carbon interstitial (Ci) defect in silicon as a potential candidate for spin-photon interfaces. Computed charge transition levels and optical properties show good agreement with the experimental results and allow assigning the experimentally observed telecom zero-phonon emission (1448 nm) to the neutral Ci defect.
硅中与缺陷相关的自旋光子界面有望通过结合先进的半导体和光子技术实现量子中继器。最近，在硅中成功实现了简单碳间隙缺陷的受控创建/测量。这种缺陷在室温附近具有稳定的结构，并在通信技术中使用的光纤信号损失最小的波长上相干发射。我们深入的理论分析证实，所观察到的发射归因于该缺陷的中性电荷态，是由束缚激子的重组引起的。我们还发现了一种可用作量子存储器的瞬变三重态。基于对该缺陷电子结构的分析及其与硅中已知的光学检测磁共振中心的相似性，我们提出碳间隙可以充当量子位，并可能在互补金属氧化物半导体兼容平台中实现自旋到光子的接口。本研究对硅中的单个碳间隙（Ci）缺陷作为自旋光子接口的潜在候选者进行了理论研究。计算的电荷转移水平和光学特性与实验结果显示出良好的一致性，并允许将实验观测到的电信零光子发射（1448 nm）归因于中性 Ci 缺陷。
{"title":"Quantum bit with telecom wave-length emission from a simple defect in Si","authors":"Peter Deák, Song Li, Adam Gali","doi":"10.1038/s42005-024-01834-z","DOIUrl":"10.1038/s42005-024-01834-z","url":null,"abstract":"Defect-related spin-to-photon interfaces in silicon promise the realization of quantum repeaters by combining advanced semiconductor and photonics technologies. Recently, controlled creation/erasure of simple carbon interstitial defects have been successfully realised in silicon. This defect has a stable structure near room temperature and coherently emits in the wave-length where the signal loss is minimal in optical fibres used in communication technologies. Our in-depth theoretical characterization confirms the assignment of the observed emission to the neutral charge state of this defect, as arising due to the recombination of a bound exciton. We also identified a metastable triplet state that could be applied as a quantum memory. Based on the analysis of the electronic structure of the defect and its similarities to a known optically detected magnetic resonance centre in silicon, we propose that a carbon interstitial can act as a quantum bit and may realize a spin-to-photon interface in complementary metal-oxide semiconductor-compatible platforms. This work presents a theoretical investigation of the single carbon interstitial (Ci) defect in silicon as a potential candidate for spin-photon interfaces. Computed charge transition levels and optical properties show good agreement with the experimental results and allow assigning the experimentally observed telecom zero-phonon emission (1448 nm) to the neutral Ci defect.","PeriodicalId":10540,"journal":{"name":"Communications Physics","volume":" ","pages":"1-6"},"PeriodicalIF":5.4,"publicationDate":"2024-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s42005-024-01834-z.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142443619","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 : 2024-10-13DOI: 10.1038/s42005-024-01817-0
Joscha Mecke, Yongxiang Gao, Gerhard Gompper, Marisol Ripoll
Chiral active fluids show the emergence of a turbulent behaviour characterised by multiple dynamic vortices whose maximum size varies for each experimental system, depending on conditions not yet identified. We propose and develop an approach to model the effect of friction close to a surface in a particle based hydrodynamic simulation method in two dimensions, in which the friction coefficient can be related to the system parameters and to the emergence of a damping length. This length is system dependent, limits the size of the emergent vortices, and influences other relevant system properties such as the actuated velocity, rotational diffusion, or the cutoff of the energy spectra. Comparison of simulation and experimental results of a large ensemble of rotating colloids sedimented on a surface shows a good agreement, which demonstrates the predictive capabilities of the approach, which can be applied to a wider class of quasi-two-dimensional systems with friction. The dynamics of chiral active fluids is characterised by a multitude of interacting dynamic vortices whose maximum size varies for each system. Here we show how the friction induced by the substrate is related to a damping length which is ultimately responsible of limiting the maximum size of the vortices.
{"title":"Chiral active systems near a substrate: Emergent damping length controlled by fluid friction","authors":"Joscha Mecke, Yongxiang Gao, Gerhard Gompper, Marisol Ripoll","doi":"10.1038/s42005-024-01817-0","DOIUrl":"10.1038/s42005-024-01817-0","url":null,"abstract":"Chiral active fluids show the emergence of a turbulent behaviour characterised by multiple dynamic vortices whose maximum size varies for each experimental system, depending on conditions not yet identified. We propose and develop an approach to model the effect of friction close to a surface in a particle based hydrodynamic simulation method in two dimensions, in which the friction coefficient can be related to the system parameters and to the emergence of a damping length. This length is system dependent, limits the size of the emergent vortices, and influences other relevant system properties such as the actuated velocity, rotational diffusion, or the cutoff of the energy spectra. Comparison of simulation and experimental results of a large ensemble of rotating colloids sedimented on a surface shows a good agreement, which demonstrates the predictive capabilities of the approach, which can be applied to a wider class of quasi-two-dimensional systems with friction. The dynamics of chiral active fluids is characterised by a multitude of interacting dynamic vortices whose maximum size varies for each system. Here we show how the friction induced by the substrate is related to a damping length which is ultimately responsible of limiting the maximum size of the vortices.","PeriodicalId":10540,"journal":{"name":"Communications Physics","volume":" ","pages":"1-10"},"PeriodicalIF":5.4,"publicationDate":"2024-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s42005-024-01817-0.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142443639","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 : 2024-10-11DOI: 10.1038/s42005-024-01819-y
Lena Mangold, Camille Roth
Network analysis is often enriched by including an examination of node metadata. In the context of understanding the mesoscale of networks it is often assumed that node groups based on metadata and node groups based on connectivity patterns are intrinsically linked. This assumption is increasingly being challenged, whereby metadata might be entirely unrelated to structure or, similarly, multiple sets of metadata might be relevant to the structure of a network in different ways. We propose the metablox tool to quantify the relationship between a network’s node metadata and its mesoscale structure, measuring the strength of the relationship and the type of structural arrangement exhibited by the metadata. We show on a number of synthetic and empirical networks that our tool distinguishes relevant metadata and allows for this in a comparative setting, demonstrating that it can be used as part of systematic meta analyses for the comparison of networks from different domains. Network data often includes categorical node attributes whose relevance to the network’s structure is often unknown. Here the authors propose the metablox (metadata block structure exploration) tool, to quantify the relationship between categorical node metadata and the block structure of the network, using Stochastic block models and description length.
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