The persistence of the global climate system is critical for assuring the sustainability of the natural ecosystem. However, persistence at a network level has been rarely discussed. Here we develop a framework to analyze the time persistence of the yearly networks of climate and carbon flux, based on cross-correlations between sites, using daily data from China, the contiguous United States, and the Europe land region. Our framework for determining the persistence is based on analyzing the similarity between the network structures in different years. Our results reveal that the similarity of climate and carbon flux networks in different years are within the range of 0.57 ± 0.07, implying that the climate and carbon flux in the Earth’s climate system are generally persistent and in a steady state. We find a very small decay in similarity when the gap between years increases. Moreover, we find that the persistence of climate variables and carbon flux in the three regions decreases when considering only long range links. Analyzing the persistence and evolution of the climate and carbon flux networks, enhance our understanding of the spatial and temporal evolution of the global climate system. The persistence of the global climate system is essential for the sustainability of natural ecosystems. This work develops a framework, generate climate and carbon flux networks and finds that the similarity of the networks in different years is 0.57 ± 0.07, implying that the system is generally stable and that the similarity decay is very small when the year gap increases.
{"title":"Time persistence of climate and carbon flux networks","authors":"Ting Qing, Fan Wang, Qiuyue Li, Gaogao Dong, Lixin Tian, Shlomo Havlin","doi":"10.1038/s42005-024-01862-9","DOIUrl":"10.1038/s42005-024-01862-9","url":null,"abstract":"The persistence of the global climate system is critical for assuring the sustainability of the natural ecosystem. However, persistence at a network level has been rarely discussed. Here we develop a framework to analyze the time persistence of the yearly networks of climate and carbon flux, based on cross-correlations between sites, using daily data from China, the contiguous United States, and the Europe land region. Our framework for determining the persistence is based on analyzing the similarity between the network structures in different years. Our results reveal that the similarity of climate and carbon flux networks in different years are within the range of 0.57 ± 0.07, implying that the climate and carbon flux in the Earth’s climate system are generally persistent and in a steady state. We find a very small decay in similarity when the gap between years increases. Moreover, we find that the persistence of climate variables and carbon flux in the three regions decreases when considering only long range links. Analyzing the persistence and evolution of the climate and carbon flux networks, enhance our understanding of the spatial and temporal evolution of the global climate system. The persistence of the global climate system is essential for the sustainability of natural ecosystems. This work develops a framework, generate climate and carbon flux networks and finds that the similarity of the networks in different years is 0.57 ± 0.07, implying that the system is generally stable and that the similarity decay is very small when the year gap increases.","PeriodicalId":10540,"journal":{"name":"Communications Physics","volume":" ","pages":"1-10"},"PeriodicalIF":5.4,"publicationDate":"2024-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s42005-024-01862-9.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142665216","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 : 2024-11-15DOI: 10.1038/s42005-024-01848-7
Tianyu Li, Yi Peng, Yucheng Wang, Haiping Hu
Hyperbolic lattices, formed by tessellating the hyperbolic plane with regular polygons, exhibit a diverse range of exotic physical phenomena beyond conventional Euclidean lattices. Here, we investigate the impact of disorder on hyperbolic lattices and reveal that the Anderson localization occurs at strong disorder strength, accompanied by the presence of mobility edges. Taking the hyperbolic {p, q} = {3, 8} and {p, q} = {4, 8} lattices as examples, we employ finite-size scaling of both spectral statistics and the inverse participation ratio to pinpoint the transition point and critical exponents. Our findings indicate that the transition points tend to increase with larger values of {p, q} or curvature. In the limiting case of {∞, q}, we further determine its Anderson transition using the cavity method, drawing parallels with the random regular graph. Our work lays the cornerstone for a comprehensive understanding of Anderson transition and mobility edges on hyperbolic lattices. Anderson localization is a paradigmatic topic of condensed matter physics used to explain the insulating behavior of materials. This paper investigates the effect of disorder in hyperbolic lattices and finds that Anderson localization occurs at strong disorder strength, accompanied by the presence of mobility edges.
{"title":"Anderson transition and mobility edges on hyperbolic lattices with randomly connected boundaries","authors":"Tianyu Li, Yi Peng, Yucheng Wang, Haiping Hu","doi":"10.1038/s42005-024-01848-7","DOIUrl":"10.1038/s42005-024-01848-7","url":null,"abstract":"Hyperbolic lattices, formed by tessellating the hyperbolic plane with regular polygons, exhibit a diverse range of exotic physical phenomena beyond conventional Euclidean lattices. Here, we investigate the impact of disorder on hyperbolic lattices and reveal that the Anderson localization occurs at strong disorder strength, accompanied by the presence of mobility edges. Taking the hyperbolic {p, q} = {3, 8} and {p, q} = {4, 8} lattices as examples, we employ finite-size scaling of both spectral statistics and the inverse participation ratio to pinpoint the transition point and critical exponents. Our findings indicate that the transition points tend to increase with larger values of {p, q} or curvature. In the limiting case of {∞, q}, we further determine its Anderson transition using the cavity method, drawing parallels with the random regular graph. Our work lays the cornerstone for a comprehensive understanding of Anderson transition and mobility edges on hyperbolic lattices. Anderson localization is a paradigmatic topic of condensed matter physics used to explain the insulating behavior of materials. This paper investigates the effect of disorder in hyperbolic lattices and finds that Anderson localization occurs at strong disorder strength, accompanied by the presence of mobility edges.","PeriodicalId":10540,"journal":{"name":"Communications Physics","volume":" ","pages":"1-8"},"PeriodicalIF":5.4,"publicationDate":"2024-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s42005-024-01848-7.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142665219","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 : 2024-11-15DOI: 10.1038/s42005-024-01849-6
Daisuke Yoshida, Tomoyuki Horikiri
Quantum repeaters are pivotal in the physical layer of the quantum internet, and quantum repeaters capable of efficient entanglement distribution are necessary for its development. Quantum repeater schemes based on single-photon interference are promising because of their potential efficiency. However, schemes involving first-order interference with photon sources at distant nodes require stringent phase stability of the components, which pose challenges for long-distance implementation. In this paper, we present a quantum repeater scheme that leverages single-photon interference and reduces the difficulty of achieving phase stabilization. Additionally, under specific conditions, our scheme achieves a higher entanglement distribution rate between end nodes compared with the existing schemes. Thus, the proposed approach could lead to improved rates with technologies that are currently unavailable but possible in the future and will ultimately facilitate the development of multimode quantum repeaters. Single-photon interference based quantum repeater schemes are promising due to their potential efficiency. Here, the authors offer a theoretical quantum repeater scheme with reduced complexity of phase stabilization and scope for higher entanglement rates between the end nodes.
{"title":"Multiplexed quantum repeaters based on single-photon interference with mild stabilization","authors":"Daisuke Yoshida, Tomoyuki Horikiri","doi":"10.1038/s42005-024-01849-6","DOIUrl":"10.1038/s42005-024-01849-6","url":null,"abstract":"Quantum repeaters are pivotal in the physical layer of the quantum internet, and quantum repeaters capable of efficient entanglement distribution are necessary for its development. Quantum repeater schemes based on single-photon interference are promising because of their potential efficiency. However, schemes involving first-order interference with photon sources at distant nodes require stringent phase stability of the components, which pose challenges for long-distance implementation. In this paper, we present a quantum repeater scheme that leverages single-photon interference and reduces the difficulty of achieving phase stabilization. Additionally, under specific conditions, our scheme achieves a higher entanglement distribution rate between end nodes compared with the existing schemes. Thus, the proposed approach could lead to improved rates with technologies that are currently unavailable but possible in the future and will ultimately facilitate the development of multimode quantum repeaters. Single-photon interference based quantum repeater schemes are promising due to their potential efficiency. Here, the authors offer a theoretical quantum repeater scheme with reduced complexity of phase stabilization and scope for higher entanglement rates between the end nodes.","PeriodicalId":10540,"journal":{"name":"Communications Physics","volume":" ","pages":"1-9"},"PeriodicalIF":5.4,"publicationDate":"2024-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s42005-024-01849-6.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142665210","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 : 2024-11-14DOI: 10.1038/s42005-024-01859-4
Ana Palacios, Rodrigo Martínez-Peña, Miguel C. Soriano, Gian Luca Giorgi, Roberta Zambrini
Quantum Reservoir Computing (QRC) offers potential advantages over classical reservoir computing, including inherent processing of quantum inputs and a vast Hilbert space for state exploration. Yet, the relation between the performance of reservoirs based on complex and many-body quantum systems and non-classical state features is not established. Through an extensive analysis of QRC based on a transverse-field Ising model we show how different quantum effects, such as quantum coherence and correlations, contribute to improving the performance in temporal tasks, as measured by the Information Processing Capacity. Additionally, we critically assess the impact of finite measurement resources and noise on the reservoir’s dynamics in different regimes, quantifying the limited ability to exploit quantum effects for increasing damping and noise strengths. Our results reveal a monotonic relationship between reservoir performance and coherence, along with the importance of quantum effects in the ergodic regime. Quantum Reservoir Computing leverages the quantum properties of physical systems for solving temporal tasks. This study shows the importance of quantum effects, such as coherence and superposition, in the reservoir’s performance for different dynamical regimes, while considering the impact of finite measurements and noisy environments.
{"title":"Role of coherence in many-body Quantum Reservoir Computing","authors":"Ana Palacios, Rodrigo Martínez-Peña, Miguel C. Soriano, Gian Luca Giorgi, Roberta Zambrini","doi":"10.1038/s42005-024-01859-4","DOIUrl":"10.1038/s42005-024-01859-4","url":null,"abstract":"Quantum Reservoir Computing (QRC) offers potential advantages over classical reservoir computing, including inherent processing of quantum inputs and a vast Hilbert space for state exploration. Yet, the relation between the performance of reservoirs based on complex and many-body quantum systems and non-classical state features is not established. Through an extensive analysis of QRC based on a transverse-field Ising model we show how different quantum effects, such as quantum coherence and correlations, contribute to improving the performance in temporal tasks, as measured by the Information Processing Capacity. Additionally, we critically assess the impact of finite measurement resources and noise on the reservoir’s dynamics in different regimes, quantifying the limited ability to exploit quantum effects for increasing damping and noise strengths. Our results reveal a monotonic relationship between reservoir performance and coherence, along with the importance of quantum effects in the ergodic regime. Quantum Reservoir Computing leverages the quantum properties of physical systems for solving temporal tasks. This study shows the importance of quantum effects, such as coherence and superposition, in the reservoir’s performance for different dynamical regimes, while considering the impact of finite measurements and noisy environments.","PeriodicalId":10540,"journal":{"name":"Communications Physics","volume":" ","pages":"1-9"},"PeriodicalIF":5.4,"publicationDate":"2024-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s42005-024-01859-4.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142665221","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 : 2024-11-14DOI: 10.1038/s42005-024-01858-5
Lukas Mühlnickel, Jonnel A. Jaurigue, Lina C. Jaurigue, Kathy Lüdge
Reservoir computing with photonic systems promises fast and energy efficient computations. Vertical emitting semiconductor lasers with two spin-polarized charge-carrier populations (spin-VCSEL), are good candidates for high-speed reservoir computing. With our work, we highlight the role of the internal dynamic coupling on the prediction performance. We present numerical evidence for the critical impact of different data injection schemes and internal timescales. A central finding is that the internal dynamics of all dynamical degrees of freedom can only be utilized if an appropriate perturbation via the input is chosen as data injection scheme. If the data is encoded via an optical phase difference, the internal spin-polarized carrier dynamics is not addressed but instead a faster data injection rate is possible. We find strong correlations of the prediction performance with the system response time and the underlying delay-induced bifurcation structure, which allows to transfer the results to other physical reservoir computing systems. The authors numerically investigate the reservoir computing performance of vertical emitting two-mode semiconductor lasers and show the crucial impact of dynamic coupling, injection schemes and system timescales. A central finding is that high dimensional internal dynamics can only be utilized if an appropriate perturbation via the input is chosen.
{"title":"The influence of timescales and data injection schemes for reservoir computing using spin-VCSELs","authors":"Lukas Mühlnickel, Jonnel A. Jaurigue, Lina C. Jaurigue, Kathy Lüdge","doi":"10.1038/s42005-024-01858-5","DOIUrl":"10.1038/s42005-024-01858-5","url":null,"abstract":"Reservoir computing with photonic systems promises fast and energy efficient computations. Vertical emitting semiconductor lasers with two spin-polarized charge-carrier populations (spin-VCSEL), are good candidates for high-speed reservoir computing. With our work, we highlight the role of the internal dynamic coupling on the prediction performance. We present numerical evidence for the critical impact of different data injection schemes and internal timescales. A central finding is that the internal dynamics of all dynamical degrees of freedom can only be utilized if an appropriate perturbation via the input is chosen as data injection scheme. If the data is encoded via an optical phase difference, the internal spin-polarized carrier dynamics is not addressed but instead a faster data injection rate is possible. We find strong correlations of the prediction performance with the system response time and the underlying delay-induced bifurcation structure, which allows to transfer the results to other physical reservoir computing systems. The authors numerically investigate the reservoir computing performance of vertical emitting two-mode semiconductor lasers and show the crucial impact of dynamic coupling, injection schemes and system timescales. A central finding is that high dimensional internal dynamics can only be utilized if an appropriate perturbation via the input is chosen.","PeriodicalId":10540,"journal":{"name":"Communications Physics","volume":" ","pages":"1-12"},"PeriodicalIF":5.4,"publicationDate":"2024-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s42005-024-01858-5.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142665214","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 : 2024-11-13DOI: 10.1038/s42005-024-01820-5
Fang Qin, Rui Chen, Ching Hua Lee
The Hall response can be dramatically different from its quantized value in materials with broken inversion symmetry. This stems from the leading Hall contribution beyond the linear order, known as the Berry curvature dipole (BCD). While the BCD is in principle always present, it is typically very small outside of a narrow window close to a topological transition and is thus experimentally elusive without careful tuning of external fields, temperature, or impurities. We transcend this challenge by devising optical driving and quench protocols that enable practical and direct access to large BCD. Varying the amplitude of an incident circularly polarized laser drives a topological transition between normal and Chern insulator phases, and importantly allows the precise unlocking of nonlinear Hall currents comparable to or larger than the linear Hall contributions. This strong BCD engineering is even more versatile with our two-parameter quench protocol, as demonstrated in our experimental proposal. In this work, the authors investigate nonlinear Hall materials under optical driving. They find that nonlinear Hall materials can exhibit a strong light-enhanced nonlinear Hall response when excited by circularly polarized lasers.
{"title":"Light-enhanced nonlinear Hall effect","authors":"Fang Qin, Rui Chen, Ching Hua Lee","doi":"10.1038/s42005-024-01820-5","DOIUrl":"10.1038/s42005-024-01820-5","url":null,"abstract":"The Hall response can be dramatically different from its quantized value in materials with broken inversion symmetry. This stems from the leading Hall contribution beyond the linear order, known as the Berry curvature dipole (BCD). While the BCD is in principle always present, it is typically very small outside of a narrow window close to a topological transition and is thus experimentally elusive without careful tuning of external fields, temperature, or impurities. We transcend this challenge by devising optical driving and quench protocols that enable practical and direct access to large BCD. Varying the amplitude of an incident circularly polarized laser drives a topological transition between normal and Chern insulator phases, and importantly allows the precise unlocking of nonlinear Hall currents comparable to or larger than the linear Hall contributions. This strong BCD engineering is even more versatile with our two-parameter quench protocol, as demonstrated in our experimental proposal. In this work, the authors investigate nonlinear Hall materials under optical driving. They find that nonlinear Hall materials can exhibit a strong light-enhanced nonlinear Hall response when excited by circularly polarized lasers.","PeriodicalId":10540,"journal":{"name":"Communications Physics","volume":" ","pages":"1-14"},"PeriodicalIF":5.4,"publicationDate":"2024-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s42005-024-01820-5.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142665213","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 : 2023-09-09DOI: 10.1038/s42005-023-01359-x
Lukas Weber, Emil Viñas Boström, Martin Claassen, Angel Rubio, Dante M. Kennes
Strong light-matter interactions as realized in an optical cavity provide a tantalizing opportunity to control the properties of condensed matter systems. Inspired by experimental advances in cavity quantum electrodynamics and the fabrication and control of two-dimensional magnets, we investigate the fate of a quantum critical antiferromagnet coupled to an optical cavity field. Using unbiased quantum Monte Carlo simulations, we compute the scaling behavior of the magnetic structure factor and other observables. While the position and universality class are not changed by a single cavity mode, the critical fluctuations themselves obtain a sizable enhancement, scaling with a fractional exponent that defies expectations based on simple perturbation theory. The scaling exponent can be understood using a generic scaling argument, based on which we predict that the effect may be even stronger in other universality classes. Our microscopic model is based on realistic parameters for two-dimensional magnetic quantum materials and the effect may be within the range of experimental detection. The authors employ Quantum Monte Carlo simulations to study the scaling behavior of the magnetic structure factor and other observables in a 2D quantum critical magnet coupled to a single cavity mode. They find that while the quantum critical point remains unchanged, critical fluctuations are significantly enhanced and a fractional scaling exponent deviates from expectations based on perturbation theory.
{"title":"Cavity-renormalized quantum criticality in a honeycomb bilayer antiferromagnet","authors":"Lukas Weber, Emil Viñas Boström, Martin Claassen, Angel Rubio, Dante M. Kennes","doi":"10.1038/s42005-023-01359-x","DOIUrl":"10.1038/s42005-023-01359-x","url":null,"abstract":"Strong light-matter interactions as realized in an optical cavity provide a tantalizing opportunity to control the properties of condensed matter systems. Inspired by experimental advances in cavity quantum electrodynamics and the fabrication and control of two-dimensional magnets, we investigate the fate of a quantum critical antiferromagnet coupled to an optical cavity field. Using unbiased quantum Monte Carlo simulations, we compute the scaling behavior of the magnetic structure factor and other observables. While the position and universality class are not changed by a single cavity mode, the critical fluctuations themselves obtain a sizable enhancement, scaling with a fractional exponent that defies expectations based on simple perturbation theory. The scaling exponent can be understood using a generic scaling argument, based on which we predict that the effect may be even stronger in other universality classes. Our microscopic model is based on realistic parameters for two-dimensional magnetic quantum materials and the effect may be within the range of experimental detection. The authors employ Quantum Monte Carlo simulations to study the scaling behavior of the magnetic structure factor and other observables in a 2D quantum critical magnet coupled to a single cavity mode. They find that while the quantum critical point remains unchanged, critical fluctuations are significantly enhanced and a fractional scaling exponent deviates from expectations based on perturbation theory.","PeriodicalId":10540,"journal":{"name":"Communications Physics","volume":" ","pages":"1-11"},"PeriodicalIF":5.5,"publicationDate":"2023-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s42005-023-01359-x.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48868217","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 : 2023-09-08DOI: 10.1038/s42005-023-01364-0
Xin-Jie Zhang, Jack Murdoch Moore, Gang Yan, Xiang Li
Sparse neural networks can achieve performance comparable to fully connected networks but need less energy and memory, showing great promise for deploying artificial intelligence in resource-limited devices. While significant progress has been made in recent years in developing approaches to sparsify neural networks, artificial neural networks are notorious as black boxes, and it remains an open question whether well-performing neural networks have common structural features. Here, we analyze the evolution of recurrent neural networks (RNNs) trained by different sparsification strategies and for different tasks, and explore the topological regularities of these sparsified networks. We find that the optimized sparse topologies share a universal pattern of signed motifs, RNNs evolve towards structurally balanced configurations during sparsification, and structural balance can improve the performance of sparse RNNs in a variety of tasks. Such structural balance patterns also emerge in other state-of-the-art models, including neural ordinary differential equation networks and continuous-time RNNs. Taken together, our findings not only reveal universal structural features accompanying optimized network sparsification but also offer an avenue for optimal architecture searching. Deep neural networks have shown remarkable success in application areas across physical sciences and engineering science and finding such networks that can work efficiently with less connections (weight parameters) without sacrificing performance is thus of great interest. In this work the authors show that a large number of such efficient recurrent neural networks display certain connectivity patterns in their structure.
{"title":"Universal structural patterns in sparse recurrent neural networks","authors":"Xin-Jie Zhang, Jack Murdoch Moore, Gang Yan, Xiang Li","doi":"10.1038/s42005-023-01364-0","DOIUrl":"10.1038/s42005-023-01364-0","url":null,"abstract":"Sparse neural networks can achieve performance comparable to fully connected networks but need less energy and memory, showing great promise for deploying artificial intelligence in resource-limited devices. While significant progress has been made in recent years in developing approaches to sparsify neural networks, artificial neural networks are notorious as black boxes, and it remains an open question whether well-performing neural networks have common structural features. Here, we analyze the evolution of recurrent neural networks (RNNs) trained by different sparsification strategies and for different tasks, and explore the topological regularities of these sparsified networks. We find that the optimized sparse topologies share a universal pattern of signed motifs, RNNs evolve towards structurally balanced configurations during sparsification, and structural balance can improve the performance of sparse RNNs in a variety of tasks. Such structural balance patterns also emerge in other state-of-the-art models, including neural ordinary differential equation networks and continuous-time RNNs. Taken together, our findings not only reveal universal structural features accompanying optimized network sparsification but also offer an avenue for optimal architecture searching. Deep neural networks have shown remarkable success in application areas across physical sciences and engineering science and finding such networks that can work efficiently with less connections (weight parameters) without sacrificing performance is thus of great interest. In this work the authors show that a large number of such efficient recurrent neural networks display certain connectivity patterns in their structure.","PeriodicalId":10540,"journal":{"name":"Communications Physics","volume":" ","pages":"1-10"},"PeriodicalIF":5.5,"publicationDate":"2023-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s42005-023-01364-0.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42093798","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 : 2023-09-08DOI: 10.1038/s42005-023-01365-z
Haroldo V. Ribeiro, Angel A. Tateishi, Ervin K. Lenzi, Richard L. Magin, Matjaž Perc
Heterogeneous media diffusion is often described using position-dependent diffusion coefficients and estimated indirectly through mean squared displacement in experiments. This approach may overlook other mechanisms and their interaction with position-dependent diffusion, potentially leading to erroneous conclusions. Here, we introduce a hybrid diffusion model that merges a position-dependent diffusion coefficient with the trapping mechanism of the comb model. We derive exact solutions for position distributions and mean squared displacements, validated through simulations of Langevin equations. Our model shows that the trapping mechanism attenuates the impact of media heterogeneity. Superdiffusion occurs when the position-dependent coefficient increases superlinearly, while subdiffusion occurs for sublinear and inverse power-law relations. This nontrivial interplay between heterogeneity and state-independent mechanisms also leads to anomalous yet Brownian, and non-Brownian yet Gaussian regimes. These findings emphasize the need for cautious interpretations of experiments and highlight the limitations of relying solely on mean squared displacements or position distributions for diffusion characterization. Position dependent diffusion coefficients are often estimated indirectly through mean square displacement. The authors propose a diffusion model merging position-dependent coefficients and comb-like trapping mechanisms, revealing that particle trapping mitigates the impact of media heterogeneity and that thus caution is needed in experimental interpretations.
{"title":"Interplay between particle trapping and heterogeneity in anomalous diffusion","authors":"Haroldo V. Ribeiro, Angel A. Tateishi, Ervin K. Lenzi, Richard L. Magin, Matjaž Perc","doi":"10.1038/s42005-023-01365-z","DOIUrl":"10.1038/s42005-023-01365-z","url":null,"abstract":"Heterogeneous media diffusion is often described using position-dependent diffusion coefficients and estimated indirectly through mean squared displacement in experiments. This approach may overlook other mechanisms and their interaction with position-dependent diffusion, potentially leading to erroneous conclusions. Here, we introduce a hybrid diffusion model that merges a position-dependent diffusion coefficient with the trapping mechanism of the comb model. We derive exact solutions for position distributions and mean squared displacements, validated through simulations of Langevin equations. Our model shows that the trapping mechanism attenuates the impact of media heterogeneity. Superdiffusion occurs when the position-dependent coefficient increases superlinearly, while subdiffusion occurs for sublinear and inverse power-law relations. This nontrivial interplay between heterogeneity and state-independent mechanisms also leads to anomalous yet Brownian, and non-Brownian yet Gaussian regimes. These findings emphasize the need for cautious interpretations of experiments and highlight the limitations of relying solely on mean squared displacements or position distributions for diffusion characterization. Position dependent diffusion coefficients are often estimated indirectly through mean square displacement. The authors propose a diffusion model merging position-dependent coefficients and comb-like trapping mechanisms, revealing that particle trapping mitigates the impact of media heterogeneity and that thus caution is needed in experimental interpretations.","PeriodicalId":10540,"journal":{"name":"Communications Physics","volume":" ","pages":"1-11"},"PeriodicalIF":5.5,"publicationDate":"2023-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s42005-023-01365-z.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42499019","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 : 2023-09-08DOI: 10.1038/s42005-023-01346-2
Alexander Osterkorn, Constantin Meyer, Salvatore R. Manmana
Modern time-resolved spectroscopy experiments on quantum materials raise the question, how strong electron-electron interactions, in combination with periodic driving, form unconventional transient states. Here we show using numerically exact methods that in a driven strongly interacting charge-density-wave insulator a band-like resonance in the gap region is formed. We associate this feature to the so-called Villain mode in quantum-magnetic materials, which originates in moving domain walls induced by the interaction. We do not obtain the in-gap band when driving a non-interacting charge density wave model. In contrast, it appears in the interacting system also in equilibrium at intermediate temperatures and in the short-time evolution of the system after a quantum quench to the lowest-order high-frequency effective Floquet Hamiltonian. Our findings connect the phenomenology of a periodically driven strongly correlated system and its quench dynamics to the finite-temperature dynamical response of quantum-magnetic materials and will be insightful for future investigations of strongly correlated materials in pump-probe setups. The interplay of strong electronic interactions and periodic driving leads to new effects in nonequilibrium quantum-many body systems. The authors find an in-gap band, which is due to moving domain walls, similar to the so-called Villain-mode of quantum magnets.
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