Pub Date : 2024-09-09DOI: 10.1103/physrevresearch.6.033268
Van Dong Pham, Yi Pan, Steven C. Erwin, Felix von Oppen, Kiyoshi Kanisawa, Stefan Fölsch
Atom manipulation by scanning tunneling microscopy was used to construct quantum dots on the InAs(111)A surface. Each dot comprised six ionized indium adatoms. The positively charged adatoms create a confining potential acting on surface-state electrons, leading to the emergence of a bound state associated with the dot. By lining up the dots into -dot chains with alternating tunnel coupling between them, quantum-dot molecules were constructed that revealed electronic boundary states as predicted by the Su-Schrieffer-Heeger (SSH) model of one-dimensional topological phases. Dot chains with odd were constructed such that they host a single end or domain-wall state, allowing one to probe the localization of the boundary state on a given sublattice by scanning tunneling spectroscopy. We found probability density also on the forbidden sublattice together with an asymmetric energy spectrum of the chain-confined states. This deviation from the SSH model arises because the dots are charged and create a variation in on-site potential along the chain—which does not remove the boundary states but shifts their energy away from the midgap position. Our results demonstrate that topological boundary states can be created in quantum-dot arrays engineered with atomic-scale precision.
利用扫描隧道显微镜进行原子操作，在 InAs(111)A 表面构建量子点。每个点由六个电离铟原子组成。带正电荷的原子会对表面态电子产生约束电势，导致出现与点相关的束缚态。通过将这些点排成 N 个点链，并在它们之间交替进行隧道耦合，我们构建出了量子点分子，它揭示了一维拓扑相的苏-施里弗-希格（SSH）模型所预测的电子边界态。我们构建了奇数 N 的点链，使它们能够承载单一的端态或域壁态，从而可以通过扫描隧道光谱探测边界态在给定子晶格上的定位。我们发现禁用子晶格上也存在概率密度，同时链约束态的能谱也不对称。这种与 SSH 模型的偏差是由于点带电，并沿链产生了现场电势的变化--这并没有消除边界态，而是使它们的能量偏离了中隙位置。我们的研究结果表明，拓扑边界态可以在原子级精度的量子点阵列中产生。
{"title":"Topological boundary states in engineered quantum-dot molecules on the InAs(111)A surface: Odd numbers of quantum dots","authors":"Van Dong Pham, Yi Pan, Steven C. Erwin, Felix von Oppen, Kiyoshi Kanisawa, Stefan Fölsch","doi":"10.1103/physrevresearch.6.033268","DOIUrl":"https://doi.org/10.1103/physrevresearch.6.033268","url":null,"abstract":"Atom manipulation by scanning tunneling microscopy was used to construct quantum dots on the InAs(111)A surface. Each dot comprised six ionized indium adatoms. The positively charged adatoms create a confining potential acting on surface-state electrons, leading to the emergence of a bound state associated with the dot. By lining up the dots into <math xmlns=\"http://www.w3.org/1998/Math/MathML\"><mrow><mi>N</mi></mrow></math>-dot chains with alternating tunnel coupling between them, quantum-dot molecules were constructed that revealed electronic boundary states as predicted by the Su-Schrieffer-Heeger (SSH) model of one-dimensional topological phases. Dot chains with odd <math xmlns=\"http://www.w3.org/1998/Math/MathML\"><mrow><mi>N</mi></mrow></math> were constructed such that they host a single end or domain-wall state, allowing one to probe the localization of the boundary state on a given sublattice by scanning tunneling spectroscopy. We found probability density also on the forbidden sublattice together with an asymmetric energy spectrum of the chain-confined states. This deviation from the SSH model arises because the dots are charged and create a variation in on-site potential along the chain—which does not remove the boundary states but shifts their energy away from the midgap position. Our results demonstrate that topological boundary states can be created in quantum-dot arrays engineered with atomic-scale precision.","PeriodicalId":20546,"journal":{"name":"Physical Review Research","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142211137","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-09DOI: 10.1103/physrevresearch.6.033265
Louisiane Devaud, Bernhard Rauer, Simon Mauras, Stefan Rotter, Sylvain Gigan
Speckle patterns are inherent features of coherent light propagation through complex media. As a result of interference, they are sensitive to multiple experimental parameters such as the configuration of disorder or the propagating wavelength. Recent developments in wavefront shaping have made it possible to control speckle pattern statistics and correlations, for example using the concept of the transmission matrix. In this article, we address the problem of correlating scattered fields across multiple degrees of freedom. We highlight the common points between the specific techniques already demonstrated, and we propose a general framework based on the singular value decomposition of a linear combination of multiple transmission matrices. Following analytical predictions, we experimentally illustrate the technique on spectral and temporal correlations, and we show that both the amplitude and the phase of the field correlations can be tuned. Our work opens up new perspectives in speckle correlation manipulation, with potential applications in coherent control.
{"title":"Correlating light fields through disordered media across multiple degrees of freedom","authors":"Louisiane Devaud, Bernhard Rauer, Simon Mauras, Stefan Rotter, Sylvain Gigan","doi":"10.1103/physrevresearch.6.033265","DOIUrl":"https://doi.org/10.1103/physrevresearch.6.033265","url":null,"abstract":"Speckle patterns are inherent features of coherent light propagation through complex media. As a result of interference, they are sensitive to multiple experimental parameters such as the configuration of disorder or the propagating wavelength. Recent developments in wavefront shaping have made it possible to control speckle pattern statistics and correlations, for example using the concept of the transmission matrix. In this article, we address the problem of correlating scattered fields across multiple degrees of freedom. We highlight the common points between the specific techniques already demonstrated, and we propose a general framework based on the singular value decomposition of a linear combination of multiple transmission matrices. Following analytical predictions, we experimentally illustrate the technique on spectral and temporal correlations, and we show that both the amplitude and the phase of the field correlations can be tuned. Our work opens up new perspectives in speckle correlation manipulation, with potential applications in coherent control.","PeriodicalId":20546,"journal":{"name":"Physical Review Research","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142211129","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-09DOI: 10.1103/physrevresearch.6.033267
Julia Freund, Alexander Pirker, Wolfgang Dür
We consider multipath generation of Bell states in quantum networks, where a preprepared multipartite entangled two-dimensional cluster state serves as a resource to perform different tasks on demand. We show how to achieve parallel connections between multiple, freely chosen groups of parties by performing appropriate local measurements along a diagonal, staircase-shaped path on a two-dimensional cluster state. Remarkably, our measurement scheme preserves the entanglement structure of the cluster state such that the remaining state is again a two-dimensional cluster state. We demonstrate strategies for generating crossing, turning, and merging of multiple measurement lines along the two-dimensional cluster state. The results apply to local area as well as to long-distance networks.
{"title":"Flexible quantum data bus for quantum networks","authors":"Julia Freund, Alexander Pirker, Wolfgang Dür","doi":"10.1103/physrevresearch.6.033267","DOIUrl":"https://doi.org/10.1103/physrevresearch.6.033267","url":null,"abstract":"We consider multipath generation of Bell states in quantum networks, where a preprepared multipartite entangled two-dimensional cluster state serves as a resource to perform different tasks on demand. We show how to achieve parallel connections between multiple, freely chosen groups of parties by performing appropriate local measurements along a diagonal, staircase-shaped path on a two-dimensional cluster state. Remarkably, our measurement scheme preserves the entanglement structure of the cluster state such that the remaining state is again a two-dimensional cluster state. We demonstrate strategies for generating crossing, turning, and merging of multiple measurement lines along the two-dimensional cluster state. The results apply to local area as well as to long-distance networks.","PeriodicalId":20546,"journal":{"name":"Physical Review Research","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142211138","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In parallel with advances in microscale imaging techniques, the fields of biology and materials science have focused on precisely extracting particle properties based on their diffusion behavior. Although the majority of real-world particles exhibit anisotropy, their behavior has been studied less than that of isotropic particles. In this study, we introduce a method for estimating the diffusion coefficients of individual anisotropic particles using short-trajectory data on the basis of a maximum likelihood framework. Traditional estimation techniques often use mean-squared displacement (MSD) values or other statistical measures that inherently remove angular information. Instead, we treated the angle as a latent variable and used belief propagation to estimate it while maximizing the likelihood using the expectation-maximization algorithm. Compared to conventional methods, this approach facilitates better estimation of shorter trajectories and faster rotations, as confirmed by numerical simulations and experimental data involving bacteria and quantum rods. Additionally, we performed an analytical investigation of the limits of detectability of anisotropy and provided guidelines for the experimental design. In addition to serving as a powerful tool for analyzing complex systems, the proposed method will pave the way for applying maximum likelihood methods to more complex diffusion phenomena.
{"title":"Detection of diffusion anisotropy from an individual short particle trajectory","authors":"Kaito Takanami, Daisuke Taniguchi, Masafumi Kuroda, Sawako Enoki, Yasushi Okada, Yoshiyuki Kabashima","doi":"10.1103/physrevresearch.6.033272","DOIUrl":"https://doi.org/10.1103/physrevresearch.6.033272","url":null,"abstract":"In parallel with advances in microscale imaging techniques, the fields of biology and materials science have focused on precisely extracting particle properties based on their diffusion behavior. Although the majority of real-world particles exhibit anisotropy, their behavior has been studied less than that of isotropic particles. In this study, we introduce a method for estimating the diffusion coefficients of individual anisotropic particles using short-trajectory data on the basis of a maximum likelihood framework. Traditional estimation techniques often use mean-squared displacement (MSD) values or other statistical measures that inherently remove angular information. Instead, we treated the angle as a latent variable and used belief propagation to estimate it while maximizing the likelihood using the expectation-maximization algorithm. Compared to conventional methods, this approach facilitates better estimation of shorter trajectories and faster rotations, as confirmed by numerical simulations and experimental data involving bacteria and quantum rods. Additionally, we performed an analytical investigation of the limits of detectability of anisotropy and provided guidelines for the experimental design. In addition to serving as a powerful tool for analyzing complex systems, the proposed method will pave the way for applying maximum likelihood methods to more complex diffusion phenomena.","PeriodicalId":20546,"journal":{"name":"Physical Review Research","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142211132","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-09DOI: 10.1103/physrevresearch.6.033266
P. Giuliani, K. Godbey, V. Kejzlar, W. Nazarewicz
One can improve predictability in the unknown domain by combining forecasts of imperfect complex computational models using a Bayesian statistical machine learning framework. In many cases, however, the models used in the mixing process are similar. In addition to contaminating the model space, the existence of such similar, or even redundant, models during the multimodeling process can result in misinterpretation of results and deterioration of predictive performance. In this paper we describe a method based on the principal component analysis that eliminates model redundancy. We show that by adding model orthogonalization to the proposed Bayesian model combination framework, one can arrive at better prediction accuracy and reach excellent uncertainty quantification performance.
{"title":"Model orthogonalization and Bayesian forecast mixing via principal component analysis","authors":"P. Giuliani, K. Godbey, V. Kejzlar, W. Nazarewicz","doi":"10.1103/physrevresearch.6.033266","DOIUrl":"https://doi.org/10.1103/physrevresearch.6.033266","url":null,"abstract":"One can improve predictability in the unknown domain by combining forecasts of imperfect complex computational models using a Bayesian statistical machine learning framework. In many cases, however, the models used in the mixing process are similar. In addition to contaminating the model space, the existence of such similar, or even redundant, models during the multimodeling process can result in misinterpretation of results and deterioration of predictive performance. In this paper we describe a method based on the principal component analysis that eliminates model redundancy. We show that by adding model orthogonalization to the proposed Bayesian model combination framework, one can arrive at better prediction accuracy and reach excellent uncertainty quantification performance.","PeriodicalId":20546,"journal":{"name":"Physical Review Research","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142211140","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-09DOI: 10.1103/physrevresearch.6.033271
Michael A. Rampp, Suhail A. Rather, Pieter W. Claeys
Entanglement membrane theory is an effective coarse-grained description of entanglement dynamics and operator growth in chaotic quantum many-body systems. The fundamental quantity characterizing the membrane is the entanglement line tension. However, determining the entanglement line tension for microscopic models is in general exponentially difficult. We compute the entanglement line tension in a recently introduced class of exactly solvable yet chaotic unitary circuits, so-called generalized dual-unitary circuits, obtaining a nontrivial form that gives rise to a hierarchy of velocity scales with . For the lowest level of the hierarchy, circuits, the entanglement line tension can be computed entirely, while for the higher levels the solvability is reduced to certain regions in spacetime. This partial solvability enables us to place bounds on the entanglement velocity. We find that circuits saturate certain bounds on entanglement growth that are also saturated in holographic models. Furthermore, we relate the entanglement line tension to temporal entanglement and correlation functions. We also develop methods of constructing generalized dual-unitary gates, including constructions based on complex Hadamard matrices that exhibit additional solvability properties and constructions that display behavior unique to local dimension greater than or equal to three. Our results shed light on entanglement membrane theory in microscopic Floquet lattice models and enable us to perform nontrivial checks on the validity of its predictions by comparison to exact and numerical calculations. Moreover, they demonstrate that generalized dual-unitary circuits display a more generic form of information dynamics than dual-unitary circuits.
{"title":"Entanglement membrane in exactly solvable lattice models","authors":"Michael A. Rampp, Suhail A. Rather, Pieter W. Claeys","doi":"10.1103/physrevresearch.6.033271","DOIUrl":"https://doi.org/10.1103/physrevresearch.6.033271","url":null,"abstract":"Entanglement membrane theory is an effective coarse-grained description of entanglement dynamics and operator growth in chaotic quantum many-body systems. The fundamental quantity characterizing the membrane is the entanglement line tension. However, determining the entanglement line tension for microscopic models is in general exponentially difficult. We compute the entanglement line tension in a recently introduced class of exactly solvable yet chaotic unitary circuits, so-called generalized dual-unitary circuits, obtaining a nontrivial form that gives rise to a hierarchy of velocity scales with <math xmlns=\"http://www.w3.org/1998/Math/MathML\"><mrow><msub><mi>v</mi><mi>E</mi></msub><mo><</mo><msub><mi>v</mi><mi>B</mi></msub></mrow></math>. For the lowest level of the hierarchy, <math xmlns=\"http://www.w3.org/1998/Math/MathML\"><msub><mover accent=\"true\"><mi mathvariant=\"script\">L</mi><mo>¯</mo></mover><mn>2</mn></msub></math> circuits, the entanglement line tension can be computed entirely, while for the higher levels the solvability is reduced to certain regions in spacetime. This partial solvability enables us to place bounds on the entanglement velocity. We find that <math xmlns=\"http://www.w3.org/1998/Math/MathML\"><msub><mover accent=\"true\"><mi mathvariant=\"script\">L</mi><mo>¯</mo></mover><mn>2</mn></msub></math> circuits saturate certain bounds on entanglement growth that are also saturated in holographic models. Furthermore, we relate the entanglement line tension to temporal entanglement and correlation functions. We also develop methods of constructing generalized dual-unitary gates, including constructions based on complex Hadamard matrices that exhibit additional solvability properties and constructions that display behavior unique to local dimension greater than or equal to three. Our results shed light on entanglement membrane theory in microscopic Floquet lattice models and enable us to perform nontrivial checks on the validity of its predictions by comparison to exact and numerical calculations. Moreover, they demonstrate that generalized dual-unitary circuits display a more generic form of information dynamics than dual-unitary circuits.","PeriodicalId":20546,"journal":{"name":"Physical Review Research","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142211135","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-09DOI: 10.1103/physrevresearch.6.033269
Uroš Barać, Matjaž Perc, Marko Gosak
When individual oscillators age and become inactive, the collective dynamics of coupled oscillators is often affected as well. Depending on the fraction of inactive oscillators or cascading failures that percolate from crucial information exchange points, the critical shift toward macroscopic inactivity in coupled oscillator networks is known as the aging transition. Here, we study this phenomenon in two overlayed square lattices that together constitute a multilayer network, whereby one layer is populated with slow Poincaré oscillators and the other with fast Rulkov neurons. Moreover, in this multimodal setup, the excitability of fast oscillators is influenced by the phase of slow oscillators that are gradually inactivated toward the aging transition in the fast layer. Through extensive numerical simulations, we find that the progressive inactivation of oscillators in the slow layer nontrivially affects the collective oscillatory activity and the aging transitions in the fast layer. Most counterintuitively, we show that it is possible for the intensity of oscillatory activity in the fast layer to progressively increase to up to 100%, even when up to 60% of units in the slow oscillatory layer are inactivated. We explain our results with a numerical analysis of collective behavior in individual layers, and we discuss their implications for biological systems.
{"title":"Aging transitions of multimodal oscillators in multilayer networks","authors":"Uroš Barać, Matjaž Perc, Marko Gosak","doi":"10.1103/physrevresearch.6.033269","DOIUrl":"https://doi.org/10.1103/physrevresearch.6.033269","url":null,"abstract":"When individual oscillators age and become inactive, the collective dynamics of coupled oscillators is often affected as well. Depending on the fraction of inactive oscillators or cascading failures that percolate from crucial information exchange points, the critical shift toward macroscopic inactivity in coupled oscillator networks is known as the aging transition. Here, we study this phenomenon in two overlayed square lattices that together constitute a multilayer network, whereby one layer is populated with slow Poincaré oscillators and the other with fast Rulkov neurons. Moreover, in this multimodal setup, the excitability of fast oscillators is influenced by the phase of slow oscillators that are gradually inactivated toward the aging transition in the fast layer. Through extensive numerical simulations, we find that the progressive inactivation of oscillators in the slow layer nontrivially affects the collective oscillatory activity and the aging transitions in the fast layer. Most counterintuitively, we show that it is possible for the intensity of oscillatory activity in the fast layer to progressively increase to up to 100%, even when up to 60% of units in the slow oscillatory layer are inactivated. We explain our results with a numerical analysis of collective behavior in individual layers, and we discuss their implications for biological systems.","PeriodicalId":20546,"journal":{"name":"Physical Review Research","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142211136","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-06DOI: 10.1103/physrevresearch.6.033261
Martin Roa-Villescas, Xuanzhao Gao, Sander Stuijk, Henk Corporaal, Jin-Guo Liu
Probabilistic inference is a fundamental task in modern machine learning. Recent advances in tensor network (TN) contraction algorithms have enabled the development of better exact inference methods. However, many common inference tasks in probabilistic graphical models (PGMs) still lack corresponding TN-based adaptations. In this paper, we advance the connection between PGMs and TNs by formulating and implementing tensor-based solutions for the following inference tasks: (A) computing the partition function, (B) computing the marginal probability of sets of variables in the model, (C) determining the most likely assignment to a set of variables, (D) the same as (C) but after having marginalized a different set of variables, and (E) generating samples from a learned probability distribution using a generalized method. Our study is motivated by recent technical advances in the fields of quantum circuit simulation, quantum many-body physics, and statistical physics. Through an experimental evaluation, we demonstrate that the integration of these quantum technologies with a series of algorithms introduced in this study significantly improves the performance efficiency of existing methods for solving probabilistic inference tasks.
{"title":"Probabilistic inference in the era of tensor networks and differential programming","authors":"Martin Roa-Villescas, Xuanzhao Gao, Sander Stuijk, Henk Corporaal, Jin-Guo Liu","doi":"10.1103/physrevresearch.6.033261","DOIUrl":"https://doi.org/10.1103/physrevresearch.6.033261","url":null,"abstract":"Probabilistic inference is a fundamental task in modern machine learning. Recent advances in tensor network (TN) contraction algorithms have enabled the development of better exact inference methods. However, many common inference tasks in probabilistic graphical models (PGMs) still lack corresponding TN-based adaptations. In this paper, we advance the connection between PGMs and TNs by formulating and implementing tensor-based solutions for the following inference tasks: (A) computing the partition function, (B) computing the marginal probability of sets of variables in the model, (C) determining the most likely assignment to a set of variables, (D) the same as (C) but after having marginalized a different set of variables, and (E) generating samples from a learned probability distribution using a generalized method. Our study is motivated by recent technical advances in the fields of quantum circuit simulation, quantum many-body physics, and statistical physics. Through an experimental evaluation, we demonstrate that the integration of these quantum technologies with a series of algorithms introduced in this study significantly improves the performance efficiency of existing methods for solving probabilistic inference tasks.","PeriodicalId":20546,"journal":{"name":"Physical Review Research","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142211163","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-06DOI: 10.1103/physrevresearch.6.033264
Michael Dick, Alexander van Meegen, Moritz Helias
It is frequently hypothesized that cortical networks operate close to a critical point. Advantages of criticality include rich dynamics well suited for computation and critical slowing down, which may offer a mechanism for dynamic memory. However, mean-field approximations, while versatile and popular, inherently neglect the fluctuations responsible for such critical dynamics. Thus, a renormalized theory is necessary. We consider the Sompolinsky-Crisanti-Sommers model which displays a well studied chaotic as well as a magnetic transition. Based on the analog of a quantum effective action, we derive self-consistency equations for the first two renormalized Greens functions. Their self-consistent solution reveals a coupling between the population level activity and single neuron heterogeneity. The quantitative theory explains the population autocorrelation function, the single-unit autocorrelation function with its multiple temporal scales, and cross correlations.
{"title":"Linking network- and neuron-level correlations by renormalized field theory","authors":"Michael Dick, Alexander van Meegen, Moritz Helias","doi":"10.1103/physrevresearch.6.033264","DOIUrl":"https://doi.org/10.1103/physrevresearch.6.033264","url":null,"abstract":"It is frequently hypothesized that cortical networks operate close to a critical point. Advantages of criticality include rich dynamics well suited for computation and critical slowing down, which may offer a mechanism for dynamic memory. However, mean-field approximations, while versatile and popular, inherently neglect the fluctuations responsible for such critical dynamics. Thus, a renormalized theory is necessary. We consider the Sompolinsky-Crisanti-Sommers model which displays a well studied chaotic as well as a magnetic transition. Based on the analog of a quantum effective action, we derive self-consistency equations for the first two renormalized Greens functions. Their self-consistent solution reveals a coupling between the population level activity and single neuron heterogeneity. The quantitative theory explains the population autocorrelation function, the single-unit autocorrelation function with its multiple temporal scales, and cross correlations.","PeriodicalId":20546,"journal":{"name":"Physical Review Research","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142211159","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-06DOI: 10.1103/physrevresearch.6.033255
A. Ghosh, M. M. Bandi, S. Ghosh
In experiments conducted on a weakly confined 2D assembly of deformable cylinders subject ed to rapid in-plane shear loading, we have identified the key obstacle in achieving compaction. This obstacle involves a dynamic transition between mechanical instabilities, progressing from in-plane rearrangement to out-of-plane popping as the density increases. The popping effect reinforces the frictional constraints from the confining wall and restricts particle mobility, impeding the system from attaining greater compaction. We quantify this transition and demonstrate that interparticle friction contributes to smoothing the transition.
{"title":"Popping: A granular transition","authors":"A. Ghosh, M. M. Bandi, S. Ghosh","doi":"10.1103/physrevresearch.6.033255","DOIUrl":"https://doi.org/10.1103/physrevresearch.6.033255","url":null,"abstract":"In experiments conducted on a weakly confined 2D assembly of deformable cylinders subject ed to rapid in-plane shear loading, we have identified the key obstacle in achieving compaction. This obstacle involves a dynamic transition between mechanical instabilities, progressing from in-plane rearrangement to out-of-plane popping as the density increases. The popping effect reinforces the frictional constraints from the confining wall and restricts particle mobility, impeding the system from attaining greater compaction. We quantify this transition and demonstrate that interparticle friction contributes to smoothing the transition.","PeriodicalId":20546,"journal":{"name":"Physical Review Research","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142211167","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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