Increasing Coupling Strength Research Articles

Plasmon-Exciton Strong Coupling in Colloidal Au Nanocubes with Layered Molecular J-Aggregates.

Strong coupling between light and matter forms hybrid states, such as exciton-polaritons, which are crucial for advancements in quantum science and technology. Plasmonic metal nanoparticles, with their ultrasmall mode volumes, are effective for generating these states, but the coupling strength is often limited by surface saturation of excitonic materials. Additionally, cubic nanoparticles, which can generate strong local fields, have not been systematically explored. This study investigates strong coupling in Au nanocubes (AuNCs) coupled with J-aggregates, observing spectral splitting in both extinction and scattering spectra. Our findings suggest that smaller AuNCs, with higher-quality resonances and reduced mode volumes, achieve stronger coupling. Furthermore, a layer-by-layer (LBL) coating of J-aggregates on AuNCs results in a ∼21% increase in coupling strength. Simulations reveal the mechanism behind the enhanced coupling and confirm that the layering method effectively increases coupling, surpassing the limitations of the finite surface area of nanoparticles.

Synchronization and chimeras in asymmetrically coupled memristive Tabu learning neuron network

The coupling between neuronal oscillators plays an intriguing role in understanding the dynamics of the biological neurons present in realistic situations. Importantly, when the coupling between these neurons assumes an asymmetric nature, it can lead to profound changes in their overall behavior. In order to explore the impact of asymmetrical coupling on neuron models subjected to magnetic flux induction, we employ a coupled Tabu learning neuron model. Specifically, we illustrate the interplay between flux coupling and asymmetric electrical synapses concerning the control parameters of the proposed system using phase portraits, time series, bifurcation analysis, and Lyapunov spectrum. In particular, we show the dynamics by taking into account asymmetric interactions between neurons, from a simple network of two coupled systems to a network of nodes. Primarily, we demonstrate that two coupled systems exhibit synchronization for a fixed magnitude of control parameter with increasing coupling strength. Furthermore, we discuss the collective dynamics for the distinct network connectivity including regular, small-world and random. For all network connections, an increase in coupling strength facilitates a transition from desynchronization to synchronization via chimera state. We believe that attaining synchronization in Tabu learning neuron can act as a pivotal factor for neuron activity, contributing to the realization of such behavior in the context of numerous cognitive processes.

Influences of short-term and long-term plasticity of memristive synapse on firing activity of neuronal network

Abstract Synaptic plasticity can greatly affect the firing behavior of neural networks, and it specifically refers to changes in the strength, morphology, and function of synaptic connections. In this paper, a novel memristor model, which can be configured as a volatile and nonvolatile memristor by adjusting its internal parameter, is proposed to mimic the short-term and long-term synaptic plasticity. Then, a bi-neuron network model, with the proposed memristor serving as a coupling synapse and the external electromagnetic radiation being emulated by the flux-controlled memristors, is established to elucidate the effects of short-term and long-term synaptic plasticity on firing activity of the neuron network. The resultant 7D neuron network has no equilibrium point and its hidden dynamical behavior is revealed by phase diagram, time series, bifurcation diagram, Lyapunov exponent spectrum and two-dimensional dynamic map. Our results show the short-term and long-term plasticity can induce different bifurcation scenarios when the coupling strength increases. In addition, memristor synaptic plasticity has a great influence on the distribution of firing patterns in the parameter space. More interestingly, when exploring the synchronous firing behavior of two neurons, the two neurons can gradually achieve phase synchronization as the coupling strength increases along the opposite directions under two different memory attributes. Finally, a microcontroller-based hardware system is implemented to verify the numerical simulation results.

Strong coupling yields abrupt synchronization transitions in coupled oscillators

Coupled oscillator networks often display transitions between qualitatively different phase-locked solutions—such as synchrony and rotating wave solutions—following perturbation or parameter variation. In the limit of weak coupling, these transitions can be understood in terms of commonly studied phase approximations. As the coupling strength increases, however, predicting the location and criticality of transition, whether continuous or discontinuous, from the phase dynamics may depend on the order of the phase approximation—or a phase description of the network dynamics that neglects amplitudes may become impossible altogether. Here we analyze synchronization transitions and their criticality systematically for varying coupling strength in theory and experiments with coupled electrochemical oscillators. First, we analyze bifurcations analysis of synchrony and splay states in an abstract phase model and discuss conditions under which synchronization transitions with different criticalities are possible. In particular, we show that such conditions can be understood by considering the relative contributions of higher harmonics to the phase dynamics. Second, we illustrate that transitions with different criticality indeed occur in experimental systems. Third, we highlight that the amplitude dynamics observed in the experiments can be captured in a numerical bifurcation analysis of delay-coupled oscillators. Our results showcase that reduced order phase models may miss important features that one would expect in the dynamics of the full system. Published by the American Physical Society 2024

A prediction of high temperature magnetic coupling in transition metal phthalocyanines.

In spintronics, a perennial goal has been the generation of organic spin-bearing semiconductor materials with magnetic ordering stable at room temperature. To this end, the class of transition metal phthalocyanines has shown much promise in fulfilling this ambition. In particular, alpha-phase cobalt (II) phthalocyanine (α-CoPc) exhibits strong antiferromagnetic exchange interactions producing a long range order up to ∼100K. However, the underlying mechanism by which this magnetic interaction proceeds is not well understood. In this report, a simple mechanism has been proposed based on the Hubbard Hamiltonian, which elucidates the exchange coupling in α-CoPc. The mechanism provides stipulations for increasing the magnetic coupling, and this directs to a proposal that substitution of the central cobalt ion for rhodium will lead to a significant increase in coupling strength. The strength of this exchange interaction has been evaluated using broken symmetry hybrid exchange density functional theory and indicates that the novel rhodium (II) phthalocyanine system is indeed predicted to exhibit significantly stronger magnetic ordering. This study, therefore, identifies the coupling mechanism in α-CoPc as primarily attributable to kinetic exchange, explains its previously reported strong coupling relative to its first-row transition metal counterparts, and suggests that rhodium (II) phthalocyanine is likely to exhibit stable magnetic ordering at room temperature.

Simulating Cavity-Modified Electron Transfer Dynamics on NISQ Computers.

We present an algorithm based on the quantum-mechanically exact tensor-train thermo-field dynamics (TT-TFD) method for simulating cavity-modified electron transfer dynamics on noisy intermediate-scale quantum (NISQ) computers. The utility and accuracy of the proposed methodology is demonstrated on a model for the photoinduced intramolecular electron transfer reaction within the carotenoid-porphyrin-C60 molecular triad in tetrahydrofuran (THF) solution. The electron transfer rate is found to increase significantly with increasing coupling strength between the molecular system and the cavity. The rate process is also seen to shift from overdamped monotonic decay to under-damped oscillatory dynamics. The electron transfer rate is seen to be highly sensitive to the cavity frequency, with the emergence of a resonance cavity frequency for which the effect of coupling to the cavity is maximal. Finally, an implementation of the algorithm on the IBM Osaka quantum computer is used to demonstrate how TT-TFD-based electron transfer dynamics can be simulated accurately on NISQ computers.

Analysis of the dynamical behavior of discrete memristor-coupled scale-free neural networks

The synchronization of neural networks is crucial for neural information processing and represents a key feature of various functional brain diseases. Memristors are ideal electronic components for mimicking biological synapses, among which discrete memristors have the advantage of fast computing speed and are often used in memristor-based neural networks. For these reasons, this paper proposes a novel discrete memristor-coupled Scale-Free neural network (DMSNN). Phase diagrams and time series of membrane potential are employed to analyze the firing pattern coexistence of individual neurons in the network. Furthermore, Spatiotemporal patterns, heat maps of the Spearman correlation coefficient matrix and the values of neuron membrane potential at a particular time point are adopted to declare the spatio-temporal dynamics of the complex neural network, encompassing asynchronization, chimeric state, synchronization and synchronization transition. The study also identifies the phenomenon of topology-induced coexistence and elucidates the underlying reasons for the emergence of chimeric states in the DMSNN as the coupling strength increases. Finally, a hardware implementation platform is constructed using a highly integrated SSD202 processor to validate the accuracy of the DMSNN. The results are consistent with the numerical simulations.

Enhancing the excitation gap of a quantum-dot-based Kitaev chain

Connecting double quantum dots via a semiconductor-superconductor hybrid segment offers a platform for creating a two-site Kitaev chain that hosts Majorana zero modes at a finely tuned sweet spot. However, the effective couplings mediated by Andreev bound states in the hybrid are generally weak in the tunneling regime. As a consequence, the excitation gap is limited in size, presenting a formidable challenge for using this platform to demonstrate non-Abelian statistics and realize topological quantum computing. Here we systematically study the effects of increasing the dot-hybrid coupling. In particular, the proximity effect transforms the dot orbitals into Yu-Shiba-Rusinov states, and as the coupling strength increases, the excitation gap is significantly enhanced and sensitivity to local perturbation is reduced. We also discuss how the strong-coupling regime shows in experimentally accessible quantities, such as conductance, and provide a protocol for tuning a double-dot system into a sweet spot with a large excitation gap.

Gibbs measures for hardcore-solid-on-solid models on Cayley trees

We investigate the finite-state p-solid-on-solid (p-SOS) model for p=∞ on Cayley trees of order k⩾2 and establish a system of functional equations where each solution corresponds to a (splitting) Gibbs measure of the model. Our main result is that, for three states, k=2,3 and increasing coupling strength, the number of translation-invariant Gibbs measures behaves as 1→3→5→6→7 . This phase diagram is qualitatively similar to the one observed for three-state p-SOS models with p > 0 and, in the case of k = 2, we demonstrate that, on the level of the functional equations, the transition p→∞ is continuous.

Emergent order in adaptively rewired networks.

We explore adaptive link change strategies that can lead a system to network configurations that yield ordered dynamical states. We propose two adaptive strategies based on feedback from the global synchronization error. In the first strategy, the connectivity matrix changes if the instantaneous synchronization error is larger than a prescribed threshold. In the second strategy, the probability of a link changing at any instant of time is proportional to the magnitude of the instantaneous synchronization error. We demonstrate that both these strategies are capable of guiding networks to chaos suppression within a prescribed tolerance, in two prototypical systems of coupled chaotic maps. So, the adaptation works effectively as an efficient search in the vast space of connectivities for a configuration that serves to yield a targeted pattern. The mean synchronization error shows the presence of a sharply defined transition to very low values after a critical coupling strength, in all cases. For the first strategy, the total time during which a network undergoes link adaptation also exhibits a distinct transition to a small value under increasing coupling strength. Analogously, for the second strategy, the mean fraction of links that change in the network over time, after transience, drops to nearly zero, after a critical coupling strength, implying that the network reaches a static link configuration that yields the desired dynamics. These ideas can then potentially help us to devise control methods for extended interactive systems, as well as suggest natural mechanisms capable of regularizing complex networks.

Higher-Order Network Interactions Through Phase Reduction for Oscillators with Phase-Dependent Amplitude

Coupled oscillator networks provide mathematical models for interacting periodic processes. If the coupling is weak, phase reduction—the reduction of the dynamics onto an invariant torus—captures the emergence of collective dynamical phenomena, such as synchronization. While a first-order approximation of the dynamics on the torus may be appropriate in some situations, higher-order phase reductions become necessary, for example, when the coupling strength increases. However, these are generally hard to compute and thus they have only been derived in special cases: This includes globally coupled Stuart–Landau oscillators, where the limit cycle of the uncoupled nonlinear oscillator is circular as the amplitude is independent of the phase. We go beyond this restriction and derive second-order phase reductions for coupled oscillators for arbitrary networks of coupled nonlinear oscillators with phase-dependent amplitude, a scenario more reminiscent of real-world oscillations. We analyze how the deformation of the limit cycle affects the stability of important dynamical states, such as full synchrony and splay states. By identifying higher-order phase interaction terms with hyperedges of a hypergraph, we obtain natural classes of coupled phase oscillator dynamics on hypergraphs that adequately capture the dynamics of coupled limit cycle oscillators.

Real-Time Simulation of Ultrafast Electronic Dynamics of Nanoscale Systems Involving an Organic Molecule and a Nanoparticle Dimer.

Understanding and predicting the behavior of nanomaterials composed of plasmons interacting with quantum emitters at ultrafast timescales is crucial for the better manipulation of light at the nanoscale and advancing technologies like ultrafast communication and computing. Here we perform a simulation of the "real-time" electronic dynamics of a coupled molecule-metal nanoparticle dimer interacting with an ultrashort resonant laser pulse by combining the real-time time-dependent density functional theory (RT-TDDFT) approach with the time-domain frequency-dependent fluctuating charge (TD-ωFQ) model, an atomistic electromagnetic (AEM) model for the dynamic plasmonic response of nanoparticles. It is shown that the induced dipoles evolve from an exponential decay pattern to a beat pattern with an increase in coupling strength, which is altered by changing the molecular orientation relative to the dimer axis. It is further shown that in the strong coupling regime, both the excited molecule and the plasmon relax rapidly due to the molecule-plasmon interaction, and the efficient coherent energy exchange between the interacting molecule and plasmon modes occurs on a femtosecond (fs) timescale. This work provides guidance on manipulating light-matter interaction and studying molecular plasmonics at extremely fast timescales.

Effect of iron layer thickness on the interlayer exchange coupling in Fe/MgO (001) superlattices

We describe the effect of the Fe layer thickness on the antiferromagnetic interlayer exchange coupling in [Fe/MgO]N superlattices. An increase in coupling strength with increasing Fe layer thickness is observed, which highlights the need for including the extension of both layers when discussing the interlayer exchange coupling in superlattices. Published by the American Physical Society 2024

Non-Gaussian feature of the output field from a double qubit-cavity ultrastrong coupling system

We investigate the non-Gaussian feature of radiation in a circuit quantum electrodynamics (QED) system where two qubits are strongly coupled to a single-mode cavity. In the regime of ultrastrong coupling (USC), the rotating-wave approximation is not valid, and the Rabi Hamiltonian contains counter-rotating wave terms, leading to level crossing and avoided crossings in the energy spectrum. We further analyze the intensity-amplitude correlation of the output field in these two novel scenarios. In the USC regime, the creation and annihilation operators in the correlation function are replaced, allowing for the identification of non-Gaussian features in the output field. Our findings reveal that despite the absence of squeezing effects in the output light, significant non-Gaussian characteristics are present. Additionally, we demonstrate that as the driving or coupling strength increases, the non-Gaussian features of the output field become more pronounced. This suggests that USC systems hold broad potential applications in the realms of nonlinear optics and the generation of non-Gaussian states.

Tripartite quantum Rabi model with trapped Rydberg ions

We investigate a tripartite quantum Rabi model (TQRM) wherein a bosonic mode concurrently couples to two spin-1/2 particles through a spin-spin interaction, resulting in a spin-spin-boson coupling—a departure from conventional quantum Rabi models featuring bipartite spin-boson couplings. The symmetries of the TQRM depend on the detuning parameter, representing the energy difference between the spin states. At zero detuning a parity symmetry renders the TQRM reducible to a quantum Rabi model. A subradiant-to-superradiant transition in the ground state is predicted as the tripartite coupling strength increases. For nonzero detuning the total spin emerges as the sole conserved quantity in the TQRM. It is found that superradiance prevails in the ground state as long as the tripartite coupling remains nonzero. We derive the Braak G function of the TQRM analytically, with which the eigenspectra are obtained. The TQRM can be realized in a viable trapped Rydberg ion quantum simulator, where the required tripartite couplings and single-body interactions in the TQRM are naturally present. Our study opens opportunities to explore and create correlations and entanglement in the spin and motional degrees of freedoms with the TQRM. Published by the American Physical Society 2024

Parametric Optothermal Modulation of Carbon Nanooscillator Decorated with Mie Resonant Silicon Particle

AbstractNanomechanical resonators provide a versatile platform for nanoscale mass sensing and force microscopy, as well as for enhancing light‐matter interaction offering unique functionality for optomechanical applications. In this way, discovering new approaches for coupling light with the mechanical degrees of freedom opens the strong desire paths for further developing of nanomechanical technology. Here, the parametric optothermal modulation of hybrid nanomechanical systems consisting of carbon nanowire with a silicon nanoparticle on its top, is reported. The mechanism of the modulation is based on the periodic optical heating of the nanowire and further modulation of the elasticity parameters. Utilizing the silicon nanoparticle provides additional functionality owing to optical absorption enhanced with Mie resonance and the unique feature of optical Raman thermometry enabling optical monitoring of local temperature. It is shown that the parametric mechanism of modulation allows for a significant increase of the optomechanical coupling strength.

Neuronal Coupling Modes Show Differential Development in the Early Cortical Activity Networks of Human Newborns.

The third trimester is a critical period for the development of functional networks that support the lifelong neurocognitive performance, yet the emergence of neuronal coupling in these networks is poorly understood. Here, we used longitudinal high-density electroencephalographic recordings from preterm infants during the period from 33 to 45 weeks of conceptional age (CA) to characterize early spatiotemporal patterns in the development of local cortical function and the intrinsic coupling modes [ICMs; phase-phase (PPCs), amplitude-amplitude (AACs), and phase-amplitude correlations (PACs)]. Absolute local power showed a robust increase with CA across the full frequency spectrum, while local PACs showed sleep state-specific, biphasic development that peaked a few weeks before normal birth. AACs and distant PACs decreased globally at nearly all frequencies. In contrast, the PPCs showed frequency- and region-selective development, with an increase of coupling strength with CA between frontal, central, and occipital regions at low-delta and alpha frequencies together with a wider-spread decrease at other frequencies. Our findings together present the spectrally and spatially differential development of the distinct ICMs during the neonatal period and provide their developmental templates for future basic and clinical research.

Degenerate subspace localization and local symmetries

Domain specific localization of eigenstates has been a persistent observation for systems with local symmetries. The underlying mechanism for this localization behavior has, however, remained elusive. We provide here an analysis of a local reflection symmetric tight-binding Hamiltonian which attempts at identifying the key features that lead to the localized eigenstates. A weak coupling expansion of closed-form expressions for the eigenvectors demonstrates that the degeneracy of on-site energies occurring at the center of the locally symmetric domains represents the nucleus for eigenstates spreading across the domain. Since the symmetry-related subdomains constituting a locally symmetric domain are isospectral, we encounter pairwise degenerate eigenvalues that split linearly with an increasing coupling strength of the subdomains. The coupling to the (nonsymmetric) environment in an extended setup then leads to the survival of a certain system specific fraction of linearly splitting eigenvalues. The latter go hand in hand with the eigenstate localization on the locally symmetric domain. We provide a brief outlook addressing possible generalizations of local symmetry transformations while maintaining isospectrality. Published by the American Physical Society 2024

Extraordinary Electrical Conductance through Amorphous Nonconducting Polymers under Vibrational Strong Coupling.

Enhancing the electrical conductance through amorphous nondoped polymers is challenging. Here, we show that vibrational strong coupling (VSC) of intrinsically nonconducting and amorphous polymers such as polystyrene, deuterated polystyrene, and poly(benzyl methacrylate) to the vacuum electromagnetic field of the cavity enhances the electrical conductivity by at least 6 orders of magnitude compared to the uncoupled polymers. Remarkably, the observed extraordinary conductance is vibrational mode selective and occurs only under the VSC of the aromatic C-H(D) out-of-plane bending modes of the polymers. The conductance is thermally activated at the onset of strong coupling and becomes temperature-independent as the collective strong coupling strength increases. The electrical characterizations are performed without external light excitation, demonstrating the role of vacuum electromagnetic field-matter strong coupling in enhancing long-range transport even in amorphous nonconducting polymers.

Inferring failure coupling strength in complex networks through generative models

ABSTRACT The failure propagation process has always been a research hotspot in the field of complex system reliability. Most of the research studies focus on the inference of network structure, ignoring one of the most critical parameters for network reliability, failure coupling strength. Here, we develop a generative model describing the failure process to infer the failure coupling strength. Using this model, we generate the node failure sequences under different coupling strength and analyze the spatial properties of failure propagation. We find the failed nodes tend to appear near the previously failed nodes with increasing coupling strength. Based on our generative model, we propose a Bayesian inference method to infer the failure coupling strength from observed system instantaneous failure state data. We find the inferred values are close to the true values for small failure coupling strength. As failure coupling strength increases, error comes from the limits of failure propagation spatial data. We apply this Bayesian inference method to actual biological networks and infer the network failure coupling strength. Our proposed Bayesian inference method helps analyze the hidden failure mechanism from actual scenarios.