Large Separation Of Time Scales Research Articles

A two-timescale model of plankton–oxygen dynamics predicts formation of oxygen minimum zones and global anoxia

Decline of the dissolved oxygen in the ocean is a growing concern, as it may eventually lead to global anoxia, an elevated mortality of marine fauna and even a mass extinction. Deoxygenation of the ocean often results in the formation of oxygen minimum zones (OMZ): large domains where the abundance of oxygen is much lower than that in the surrounding ocean environment. Factors and processes resulting in the OMZ formation remain controversial. We consider a conceptual model of coupled plankton–oxygen dynamics that, apart from the plankton growth and the oxygen production by phytoplankton, also accounts for the difference in the timescales for phyto- and zooplankton (making it a “slow-fast system”) and for the implicit effect of upper trophic levels resulting in density dependent (nonlinear) zooplankton mortality. The model is investigated using a combination of analytical techniques and numerical simulations. The slow-fast system is decomposed into its slow and fast subsystems. The critical manifold of the slow-fast system and its stability is then studied by analyzing the bifurcation structure of the fast subsystem. We obtain the canard cycles of the slow-fast system for a range of parameter values. However, the system does not allow for persistent relaxation oscillations; instead, the blowup of the canard cycle results in plankton extinction and oxygen depletion. For the spatially explicit model, the earlier works in this direction did not take into account the density dependent mortality rate of the zooplankton, and thus could exhibit Turing pattern. However, the inclusion of the density dependent mortality into the system can lead to stationary Turing patterns. The dynamics of the system is then studied near the Turing bifurcation threshold. We further consider the effect of the self-movement of the zooplankton along with the turbulent mixing. We show that an initial non-uniform perturbation can lead to the formation of an OMZ, which then grows in size and spreads over space. For a sufficiently large timescale separation, the spread of the OMZ can result in global anoxia.

Energetic cost of feedback control

Successful feedback control of small systems allows for the rectification of thermal fluctuations, converting them into useful energy; however, control itself requires work. This paper emphasizes the fact that the controller is a physical entity interacting with the feedback-controlled system. For a specifically designed class of controllers, reciprocal interactions become nonreciprocal due to large timescale separation, which considerably simplifies the situation. We introduce a minimally dissipative controller model, illustrating the findings using a simple example. We find that the work required to run the controller must at least compensate for the decrease in entropy due to the control operation.

Sensitivity Conditioning: Beyond Singular Perturbation for Control Design on Multiple Time Scales

A classical approach to design controllers for interconnected systems, is to assume that the different subsystems operate at different time scales, then design simpler controllers within each time scale, and finally, certify stability of the interconnected system via singular perturbation analysis. In this work, we propose an alternative approach that also allows to design the controllers of the individual subsystems separately. However, instead of requiring a sufficiently large time-scale separation, our approach consists of adding a feed-forward term to modify the dynamics of faster systems in order to anticipate the dynamics of slower ones. We present several examples in bilevel optimization and cascade control design, where our approach improves the performance of currently available methods.

Variable Dynamic Mode Decomposition for Estimating Time Eigenvalues in Nuclear Systems

We present a new approach to calculating time eigenvalues of the neutron transport operator (also known as eigenvalues) by extending the dynamic mode decomposition (DMD) to allow for nonuniform time steps. The new method, called variable dynamic mode decomposition (VDMD), is shown to be accurate when computing eigenvalues for systems that were infeasible with DMD due to a large separation in timescales (such as those that occur in delayed supercritical systems). The eigenvalues of an infinite medium neutron transport problem with delayed neutrons, and consequently having multiple, very different relevant timescales, are computed. Furthermore, VDMD is shown to be of similar accuracy to the original DMD approach when computing eigenvalues in other systems where the previously studied DMD approach can be used.

Effective Drag in Rotating, Poorly Conducting Plasma Turbulence

Despite the increasing sophistication of numerical models of hot Jupiter atmospheres, the large timescale separation required in simulating the wide range in electrical conductivity between the dayside and nightside has made it difficult to run fully consistent magnetohydrodynamic (MHD) models. This has led to many studies that resort to drag parameterizations of MHD. In this study, we revisit the question of the Lorentz force as an effective drag by running a series of direct numerical simulations of a weakly rotating, poorly conducting flow in the presence of a misaligned, strong background magnetic field. We find that the drag parameterization fails once the timescale associated with the Lorentz force becomes shorter than the dynamical timescale in the system, beyond which the effective drag coefficient remains roughly constant, despite orders-of-magnitude variation in the Lorentz (magnetic) timescale. We offer an improvement to the drag parameterization by considering the relevant asymptotic limit of low conductivity and strong background magnetic field, known as the quasi-static MHD approximation of the Lorentz force. This approximation removes the fast timescale associated with magnetic diffusion, but retains a more complex version of the Lorentz force, which could be utilized in future numerical models of hot Jupiter atmospheric circulation.

Approximation of the Filter Equation for Multiple Timescale, Correlated, Nonlinear Systems

This paper considers the approximation of the continuous time filtering equation for the case of a multiple timescale (slow-intermediate, and fast scales) that may have correlation between the slow-intermediate process and the observation process. The signal process is considered fully coupled, taking values in $\mathbb{R^{m}} \times \mathbb{R^{n}}$ and without periodicity assumptions on coefficients. It is proved that in the weak topology, the solution of the filtering equation converges in probability to a solution of a lower dimensional averaged filtering equation in the limit of large timescale separation. The method of proof uses the perturbed test function approach (method of corrector) to handle the intermediate timescale in showing tightness and characterization of limits. The correctors are solutions of Poisson equations.

Rapid Exchange of Stably Bound Protein and DNA Cargo on a DNA Origami Receptor.

Biomolecular complexes can form stable assemblies yet can also rapidly exchange their subunits to adapt to environmental changes. Simultaneously allowing for both stability and rapid exchange expands the functional capacity of biomolecular machines and enables continuous function while navigating a complex molecular world. Inspired by biology, we design and synthesize a DNA origami receptor that exploits multivalent interactions to form stable complexes that are also capable of rapid subunit exchange. The system utilizes a mechanism first outlined in the context of the DNA replisome, known as multisite competitive exchange, and achieves a large separation of time scales between spontaneous subunit dissociation, which requires days, and rapid subunit exchange, which occurs in minutes. In addition, we use the DNA origami receptor to demonstrate stable interactions with rapid exchange of both DNA and protein subunits, thus highlighting the applicability of our approach to arbitrary molecular cargo, an important distinction with canonical toehold exchange between single-stranded DNA. We expect this study to benefit future studies that use DNA origami structures to exploit multivalent interactions for the design and synthesis of a wide range of possible kinetic behaviors.

Primordial neutrino asymmetry evolution with full mean-field effects and collisions

Neutrino oscillations and mean-field effects considerably enrich the phenomenology of neutrino evolution in the early Universe. Taking into account these effects, most notably the neutrino self-interaction mean-field contribution, we revisit the problem of the evolution of primordial neutrino asymmetries including for the first time the complete expression for collisions, which describe scattering and annihilations with electrons/positrons and reactions among (anti)neutrinos. We show that a generalisation of the adiabatic transfer of averaged oscillations (ATAO) scheme, a numerical method previously developed without neutrino degeneracy and based on the large separation of time scales in this problem, is sufficient to reach the same accuracy as the full quantum kinetic equation integration, but is notably faster. This approximation highlights the physics of synchronous oscillations at play in the evolution of neutrino chemical potentials, especially in the particular case with only two-neutrino mixing. In particular, it allows to understand what controls the beginning and the amplitude of oscillations, but also why there is a subsequent regime of collective oscillations with larger frequencies. We also find that it is very important to use the full collision term instead of relying on damping-like approximations, in order not to overestimate how collisions reduce these synchronous oscillations. Finally we study qualitatively how mixing parameters affect the final neutrino configuration, and in particular we show that the CP-violating Dirac phase cannot substantially affect the final N eff nor the final electronic (anti)-neutrino spectrum, and thus should not affect cosmological observables.

Semi-implicit Hybrid Discrete $$\left( \text {H}^T_N\right) $$ Approximation of Thermal Radiative Transfer

The thermal radiative transfer (TRT) equations form an integro-differential system that describes the propagation and collisional interactions of photons. Computing numerical solutions of the TRT equations accurately and efficiently is challenging for several reasons, the first of which is that TRT is defined on a high-dimensional phase space that includes the independent variables of time, space, and velocity. In order to reduce the dimensionality of the phase space, classical approaches such as the P\(_N\) (spherical harmonics) or the S\(_N\) (discrete ordinates) ansatz are often used in the literature. In this work, we introduce a novel approach: the hybrid discrete (H\(^T_N\)) approximation to the radiative thermal transfer equations. This approach acquires desirable properties of both P\(_N\) and S\(_N\), and indeed reduces to each of these approximations in various limits: H\(^1_N\) \(\equiv \) P\(_N\) and H\(^T_0\) \(\equiv \) S\(_T\). We prove that H\(^T_N\) results in a system of hyperbolic partial differential equations for all \(T\ge 1\) and \(N\ge 0\). Another challenge in solving the TRT system is the inherent stiffness due to the large timescale separation between propagation and collisions, especially in the diffusive (i.e., highly collisional) regime. This stiffness challenge can be partially overcome via implicit time integration, although fully implicit methods may become computationally expensive due to the strong nonlinearity and system size. On the other hand, explicit time-stepping schemes that are not also asymptotic-preserving in the highly collisional limit require resolving the mean-free path between collisions, making such schemes prohibitively expensive. In this work we develop an asymptotic-preserving numerical method that is based on a nodal discontinuous Galerkin discretization in space, coupled with a semi-implicit discretization in time. In particular, we make use of a second order explicit Runge–Kutta scheme for the streaming term and an implicit Euler scheme for the material coupling term. Furthermore, in order to solve the material energy equation implicitly after each predictor and corrector step, we linearize the temperature term using a Taylor expansion; this avoids the need for an iterative procedure, and therefore improves efficiency. In order to reduce unphysical oscillation, we apply a slope limiter after each time step. Finally, we conduct several numerical experiments to verify the accuracy, efficiency, and robustness of the H\(^T_N\) ansatz and the numerical discretizations.

Theory of classical metastability in open quantum systems

We present a general theory of classical metastability in open quantum systems. Metastability is a consequence of a large separation in timescales in the dynamics, leading to the existence of a regime when states of the system appear stationary, before eventual relaxation toward a true stationary state at much larger times. In this work, we focus on the emergence of classical metastability, i.e., when metastable states of an open quantum system with separation of timescales can be approximated as probabilistic mixtures of a finite number of states. We find that a number of classical features follow from this approximation, for the manifold of metastable states, long-time dynamics between them, and symmetries of the dynamics. Namely, those states are approximately disjoint and thus play the role of metastable phases, the relaxation toward the stationary state is approximated by a classical stochastic dynamics between them, and weak symmetries correspond to their permutations. Importantly, the classical dynamics is observed not only on average but also at the level of individual quantum trajectories: We show that time coarse-grained continuous measurement records can be viewed as noisy classical trajectories, while their statistics can be approximated by that of the classical dynamics. Among others, this explains how first-order dynamical phase transitions arise from metastability. Finally, to verify the presence of classical metastability in a given open quantum system, we develop an efficient numerical approach that delivers the set of metastable phases together with the effective classical dynamics. Since the proximity to a first-order dissipative phase transition manifests as metastability, the theory and tools introduced in this work can be used to investigate such transitions---which occur in the large size limit---through the metastable behavior of many-body systems of moderate sizes accessible to numerics.

Stripes on finite domains: Why the zigzag instability is only a partial story.

Stationary periodic patterns are widespread in natural sciences, ranging from nano-scale electrochemical and amphiphilic systems to mesoscale fluid, chemical, and biological media and to macro-scale vegetation and cloud patterns. Their formation is usually due to a primary symmetry breaking of a uniform state to stripes, often followed by secondary instabilities to form zigzag and labyrinthine patterns. These secondary instabilities are well studied under idealized conditions of an infinite domain; however, on finite domains, the situation is more subtle since the unstable modes depend also on boundary conditions. Using two prototypical models, the Swift-Hohenberg equation and the forced complex Ginzburg-Landau equation, we consider finite size domains with no flux boundary conditions transversal to the stripes and reveal a distinct mixed-mode instability that lies in between the classical zigzag and the Eckhaus lines. This explains the stability of stripes in the mildly zigzag unstable regime and, after crossing the mixed-mode line, the evolution of zigzag stripes in the bulk of the domain and the formation of defects near the boundaries. The results are of particular importance for problems with large timescale separation, such as bulk-heterojunction deformations in organic photovoltaic and vegetation in semi-arid regions, where early temporal transients may play an important role.

Phase reduction for FitzHugh-Nagumo neuron with large timescale separation.

Phase reduction approach is a useful tool to reduce the dimension of limit-cycle oscillators. In this paper, it is applied to the FitzHugh-Nagumo neuron model with large timescale separation. To quantitate the response of the oscillator to the external perturbations, the asymptotic behaviors of the phase sensitivity functions for fast and slow variables are obtained. It is shown that in the relaxation limit, apart from the jump points which are the vertices of the cubic nullcline, the phase is insensitive to the perturbations on the fast variable. By using the phase sensitivity functions, two cases, namely, periodic pulse train perturbation and common noise perturbation, are investigated. Theoretical and numerical results suggest better performance for the synchronization behaviors of the perturbations on the slow variable for large timescale separation.

Time-resolved laser scanning photothermal microscopy for characterization of thermal properties of semi-insulating GaAs.

The strong coupling effect of thermal and plasma waves disturbs the accurate characterization of thermal properties of semiconductors under super bandgap energy photon excitation. We propose a time-resolved laser scanning photothermal microscopy to decouple the thermo-electronic effect for accurate determination of the thermal diffusivity of a semi-insulating GaAs sample. The distinct advantage of the decoupling principle relies on that the scanning excitation of a laser beam on the sample surface introduces different transient and steady-state characteristics into the thermal and electronic parts of the photothermal response, where the transients between the thermal and electronic parts have a large time-scale separation, and the steady states show an enhanced thermal effect over the electronic effect. Therefore, the plasma wave is simply responsible for a negligible constant background in the thermo-electronic coupling. The theoretical and experimental results confirmed that the time-resolved photothermal signal is insensitive to the electronic transport parameters varying even by several orders of magnitude and can be used to determine the thermal diffusivity from its best fit. Moreover, the scanning excitation nature of this method allows for high-efficiency photothermal imaging of the sample to identify the thermal defects.

Study of micro–macro acceleration schemes for linear slow-fast stochastic differential equations with additive noise

Computational multi-scale methods capitalize on a large time-scale separation to efficiently simulate slow dynamics over long time intervals. For stochastic systems, one often aims at resolving the statistics of the slowest dynamics. This paper looks at the efficiency of a micro-macro acceleration method that couples short bursts of stochastic path simulation with extrapolation of spatial averages forward in time. To have explicit derivations, we elicit an amenable linear test equation containing multiple time scales. We make derivations and perform numerical experiments in the Gaussian setting, where only the evolution of mean and variance matters. The analysis shows that, for this test model, the stability threshold on the extrapolation step is largely independent of the time-scale separation. In consequence, the micro-macro acceleration method increases the admissible time steps far beyond those for which a direct time discretization becomes unstable.

Metadynamics to Enhance Sampling in Biomolecular Simulations.

Molecular dynamics is a powerful simulation method to provide detailed atomic-scale insight into a range of biological processes including protein folding, biochemical reactions, ligand binding, and many others. Over the last several decades, enhanced sampling methods have been developed to address the large separation in time scales between a molecular dynamics simulation (usually microseconds or shorter) and the time scales of biological processes (often orders of magnitude longer). This chapter specifically focuses on the metadynamics family of methods, which achieves enhanced sampling through the introduction of a history-dependent bias potential that is based on one or more slow degrees of freedom, called collective variables. We introduce the method and its recent variants related to biomolecular studies and then discuss frontier areas of the method. A large part of this chapter is devoted to helping new users of the method understand how to choose metadynamics parameters properly and apply the method to their system of interest.

Deformation of a biconcave-discoid capsule in extensional flow and electric field

Natural (red blood cells) and artificial biconcave-discoid-shaped capsules have immense biological (a cellular component of blood) and technological (as drug carrier) relevance, respectively. Their low reduced volume allows significant shape changes under external fields such as extensional flows (encountered at junctions and size-varying capillaries in biological flows) and electric fields (in applications such as electroporation and dielectrophoresis). This work demonstrates biconcave-discoid to capped-cylindrical and prolate-spheroid shape transitions of a capsule in uniaxial extensional flow as well as in DC and AC electric fields. The shape changes of a stress-free biconcave-discoid capsule in external fields are important in determining the momentum and mass transfer between the capsule and the medium fluid as well as dielectrophoresis and electroporation phenomena of a capsule in an electric field. The biconcave-discoid to capped-cylindrical/prolate-spheroid shape transition is demonstrated for both a capsule (with parameters relevant to drug delivery) as well as for a red blood cell (physiological conditions). However, significant differences are observed in this shape transition depending upon the applied external fields. In an extensional flow, the pressure-driven transition shows the equator being squeezed in and the poles being pulled out to deform into a capped cylinder at low capillary number and a prolate spheroid at high capillary number. On the other hand, in the transition driven by electric fields, the shoulders of the capsule seem to play a significant role in the dynamics. The shape transition in the electric fields depends upon the relative magnitude of the electric and the hydrodynamic response times, particularly relevant for the dynamics of red blood cells in physiological conditions. A new method of analysing the shape transition of red blood cells in AC electric fields is suggested, where a large separation of time scales is observed between the hydrodynamic and electric responses.

Accelerated evolution of convective simulations

High Peclet number, turbulent convection is a classic system with a large timescale separation between flow speeds and the thermal relaxation time. In this paper, we present a method of fast-forwarding through the long thermal relaxation of convective simulations, and we test the validity of this method. This accelerated evolution (AE) method involves measuring the dynamics of convection early in a simulation and using its characteristics to adjust the mean thermodynamic profile within the domain towards its evolved state. We study Rayleigh-B\'enard convection as a test case for AE. Evolved flow properties of AE solutions are measured to be within a few percent of solutions which are reached through standard evolution (SE) over a full thermal timescale. At the highest values of the Rayleigh number at which we compare SE and AE, we find that AE solutions require roughly an order of magnitude fewer computing hours to evolve than SE solutions.

Reduced α-stable dynamics for multiple time scale systems forced with correlated additive and multiplicative Gaussian white noise.

Stochastic averaging problems with Gaussian forcing have been the subject of numerous studies, but far less attention has been paid to problems with infinite-variance stochastic forcing, such as an α-stable noise process. It has been shown that simple linear systems driven by correlated additive and multiplicative (CAM) Gaussian noise, which emerge in the context of reduced atmosphere and ocean dynamics, have infinite variance in certain parameter regimes. In this study, we consider the stochastic averaging of systems where a linear CAM noise process in the infinite variance parameter regime drives a comparatively slow process. We use (semi)-analytical approximations combined with numerical illustrations to compare the averaged process to one that is forced by a white α-stable process, demonstrating consistent properties in the case of large time-scale separation. We identify the conditions required for the fast linear CAM process to have such an influence in driving a slower process and then derive an (effectively) equivalent fast, infinite-variance process for which an existing stochastic averaging approximation is readily applied. The results are illustrated using numerical simulations of a set of example systems.

Feedback loops interlocked at competitive binding sites amplify and facilitate genetic oscillations

Positive and negative feedback loops are often present in regulatory networks for genetic oscillations. Relative time scales and integration of these feedback loops are key to robust oscillations in expression levels. Using examples from the circadian clock and synthetic genetic oscillators, we study positive and negative feedback loops interlocked at competitive binding sites. In the mammalian circadian clock, a key clock gene Bmal1 is regulated by the activator ROR and the repressor REV-ERB. Conversely, Bmal1 activates both of them, forming interlocked feedback loops. Previous experiments indicate that the activator and repressor compete for the same binding sites in the Bmal1 promoter. Transcription patterns predict that ROR peaks later than REV-ERB and, moreover, the peak phase difference between them is small. Using mathematical modeling we reveal an optimal ratio of dissociation constants of an activator and a repressor for the competitive binding sites to enhance the amplitude of Bmal1 oscillations. This optimal ratio arises only when the amplitude of the repressor is larger than that of the activator. Secondly, we reveal that the preference of binding sites for an activator and a repressor depends on their relative time scales. A previous study demonstrated that noncompetitive binding sites are preferable for synthetic genetic oscillators that comprise a fast activator and a slow repressor with a large time scale separation. Here we show that when their time scales are similar, competitive binding sites are more likely to generate oscillation than noncompetitive sites. In contrast, for a slow activator and a fast repressor with a small phase difference as in Bmal1 regulation, noncompetitive binding sites are advantageous for amplifying oscillations. Our results, therefore, predict that additional mechanisms are necessary to compensate the disadvantage of the Bmal1 promoter and further facilitate amplification under the regulation by ROR and REV-ERB.

Spontaneous emission of Schrödinger cats in a waveguide at ultrastrong coupling

Josephson circuits provide a realistic physical setup where the light–matter fine structure constant can become of order one, allowing to reach a regime dominated by non-perturbative effects beyond standard quantum optics. Simple processes, such as spontaneous emission, thus acquire a many-body character, that can be tackled using a new description of the time-dependent state vector in terms of quantum-superposed coherent states. We find that spontaneous atomic decay at ultrastrong coupling leads to the emission of spectrally broad Schrödinger cats rather than of monochromatic single photons. These cats states remain partially entangled with the emitter at intermediate stages of the dynamics, even after emission, due to a large separation in time scales between fast energy relaxation and exponentially slow decoherence. Once decoherence of the qubit is finally established, quantum information is completely transfered to the state of the emitted cat.