General Dynamics Research Articles

Internal Noise Interference to Warnings of Tipping Points in Generic Multidimensional Dynamical Systems

Internal Noise Interference to Warnings of Tipping Points in Generic Multidimensional Dynamical Systems

Displacement residuals reveal landslide regime shifts

AbstractDespite significant progress in the development of advanced technologies for detecting and monitoring unstable slopes, accurately predicting catastrophic landslides remains a challenge. To tackle this challenge, our research integrates advanced prediction models and granular systems theory to provide insights into regime shifts within slow-moving deep-seated landslide dynamics. Our approach is designed to discern exceptional departures from historical landslide dynamics. The approach leverages the “group dynamics,” crucial for identifying precursory failure indicators, according to the generic dynamics of the precursory failure regime in granular systems. We select three different monitored slow-moving landslides as test cases. We employ an error correction cointegration vector autoregression model together with an exogenous regressor to encode historical spatiotemporal landslide dynamics and predict displacement at multiple locations by considering the historical landslide motion and relationship with external triggers. Displacement residuals are obtained by computing the difference between predicted and measured displacement for a given historical calibration time window. Threshold values for the displacement residuals are determined by analyzing the historical distribution of these residuals. Lastly, persistence in time of the threshold exceedance and the number of monitoring points that exceed the threshold at the same time are considered to encode the group dynamics. This approach offers several advantages, including the effective identification of critical regime shifts, adaptability, and transferability, and it introduces regime shift information into local landslide early warning systems. This approach can enhance confidence in the resultant alert, particularly when integrated with conventional alert systems, thereby improving the reliability of landslide warning systems.

Semiflows Strongly Focusing Monotone with Respect to High-Rank Cones: I. Generic Dynamics

Semiflows Strongly Focusing Monotone with Respect to High-Rank Cones: I. Generic Dynamics

The potential impact of the new ‘Right to Repair’ rules on electrical and electronic equipment waste: A case study of the UK

Every year an estimated two million tonnes of waste electrical and electronic equipment (WEEE) are discarded by householders and companies in the United Kingdom (UK). While the UK has left the European Union (EU), its waste-related policies still mirror those of the EU, including the WEEE-related policies. Motivated by the recent introduction the so-called ‘Right to Repair’ policy for electrical and electronic equipment (EEE) across the EU and UK, this paper aims to demonstrate that, depending on the commitment and behavioural changes by the consumers and the government, the future of the WEEE management of the UK will vary. To this end, focusing on landfilled WEEE reduction we develop a generic system dynamics model and apply it to eleven WEEE categories. They depict the flow of EEE and WEEE representing the interaction among the stakeholders (e.g., consumers and producers of EEE) and relevant government regulations of the UK. Our four scenario analyses find that longer use of EEE and better WEEE collection seem to be effective in reducing landfilled WEEE, while more reuse and more recycling and recovery have negligible impacts, despite excluding the additional generation of landfilled WEEE as a result of recycling and recovery. Comparing with the business-as-usual scenario, one year longer EEE use and 10% more of WEEE collection could at maximum reduce landfilled WEEE by 14.05% of monitoring and control instruments and 93.93% of display equipment respectively. Backcasting scenario analyses reveal that significant efforts are required to reduce the targeted amounts.

External Stefan and Internal Marangoni Thermo-Fluid Dynamics for Evaporating Capillary Bridges.

We probe the evaporation mechanisms of wettability-moderated, confined capillary bridges and bulges. For the first time, we explore the internal Marangoni hydrodynamics and external Stefan advection dynamics in the surrounding gaseous domain due to evaporative effects. A transient simulation approach based on the level set (LS) method and the Arbitrary Lagrangian-Eulerian (ALE) framework was adopted to computationally model the capillary bridge profiles and evaporation phenomenon with generic contact line dynamics (both CCR and CCA modes). The governing equations corresponding to the transport processes in both the liquid and gaseous domains are simulated in a fully coupled manner with appropriate boundary conditions to precisely trace the liquid-vapor interface and the three-phase contact point during evaporation. The effect of the bridge confinement phenomenon, i.e., the extent of confined ambient surrounding the liquid-vapor interface between the solid surfaces, is explored. Also, the role of wetting state and contact line dynamics during CCR and CCA modes of evaporation were probed, and good agreement with experimental observations was noted. Results show that the evaporation rate is primarily dictated by the confinement phenomenon, and wettability effects play a marginal role. A higher confinement curtails the evaporation rate due to an increased local vapor concentration around the liquid bridges. However, the wetting state substantially affects the internal Marangoni effect dynamics and the Stefan advection dynamics due to its explicit influence on the nonuniform evaporative flux along the liquid-vapor interface. Between superhydrophobic confinements, the contact lines are confined in the wedge-shaped region, thereby locally augmenting the vapor concentration. As a result, the large evaporative flux near the bulge region develops a higher temperature gradient, thereby inducing upscaled thermal Marangoni flow compared to hydrophilic confinements. These findings may have significant implications for the efficient designing and development of thermofluidic systems involving thermal transport, mixing, and deposition of dissolved particles in liquid bridges.

Absorption to fluctuating bunching states in nonunitary boson dynamics

We show that noisy nonunitary dynamics of bosons drives arbitrary initial states into a novel , where all bosons occupy one time-dependent mode. We propose a concept of the noisy spectral gap, a generalization of the spectral gap in noiseless systems, and demonstrate that the exponentially fast absorption to the fluctuating bunching state takes place asymptotically. The fluctuating bunching state is unique to noisy nonunitary dynamics, with no counterpart in any unitary dynamics and nonunitary dynamics described by a time-independent generator. We also argue that the times of relaxation to the fluctuating bunching state obey a universal power law as functions of the noise parameter in generic noisy nonunitary dynamics. Published by the American Physical Society 2024

Transients of Marangoni and Stefan advection dynamics during generic sessile droplet evaporation

We probe the transient evolution of Marangoni thermo-hydrodynamics in the liquid domain and the Stefan advection in the gaseous domain during evaporation of sessile droplets with generic contact line dynamics [both constant contact radius (CCR) and constant contact angle (CCA) modes]. A transient arbitrary Lagrangian–Eulerian framework was considered to computationally model the evaporation phenomenon over the droplet lifetime. The governing equations corresponding to the transport processes in both liquid and gaseous domains are simulated in a fully coupled manner, while precisely tracing the liquid–vapor interface and three phase contact line. The effects of the wetting state and contact line dynamics during CCR and CCA modes were explored, and good agreement with experimental observations is noted. The results show that the non-uniformity in an internal temperature field due to evaporation leads to formation of multi-vortex Marangoni patterns in the flow field at initial periods. At the quasi-stable state, the temperature variation becomes monotonic, thereby resulting in a single recirculation vortex in both liquid and gaseous domains. For the CCR mode, the strength of these advection fields is solely governed by a critical contact angle of ∼32°, which is determined to correspond to the critical Marangoni number. Beyond this critical point, viscous action becomes significant, and the fluid motion mitigates progressively with the formation of twin vortices at final stages due to localized heat advection near the contact line. For the CCA mode, the strength of initial vortices augments with progressing time due to amplified evaporative fluxes at smaller contact radius. The internal thermofluidic patterns and evaporative modes in turn modulate the external Stefan flow fields and neighborhood temperature fields. These findings may hold strong implications for efficient functioning of practical droplet based processes involving transport, mixing, and deposition of dissolved particles.

Benchmarking Quantum Simulators Using Ergodic Quantum Dynamics.

We propose and analyze a sample-efficient protocol to estimate the fidelity between an experimentally prepared state and an ideal target state, applicable to a wide class of analog quantum simulators without advanced spatiotemporal control. Our protocol relies on universal fluctuations emerging from generic Hamiltonian dynamics, which we discover in the present work. It does not require fine-tuned control over state preparation, quantum evolution, or readout capability, while achieving near optimal sample complexity: a percent-level precision is obtained with ∼10^{3} measurements, independent of system size. Furthermore, the accuracy of our fidelity estimation improves exponentially with increasing system size. We numerically demonstrate our protocol in a variety of quantum simulator platforms, including quantum gas microscopes, trapped ions, and Rydberg atom arrays. We discuss applications of our method for tasks such as multiparameter estimation of quantum states and processes.

Periodic temporal environmental variations induce coexistence in resource competition models.

Natural ecosystems, in particular on the microbial scale, are inhabited by a large number of species. The population size of each species is affected by interactions of individuals with each other and by spatial and temporal changes in environmental conditions, such as resource abundance. Here, we use a generic population dynamics model to study how, and under what conditions, a periodic temporal environmental variation can alter an ecosystem's composition and biodiversity. We demonstrate that using timescale separation allows one to qualitatively predict the long-term population dynamics of interacting species in varying environments. We show that the notion of Tilman's R* rule, a well-known principle that applies for constant environments, can be extended to periodically varying environments if the timescale of environmental changes (e.g., seasonal variations) is much faster than the timescale of population growth (doubling time in bacteria). When these timescales are similar, our analysis shows that a varying environment deters the system from reaching a steady state, and stable coexistence between multiple species becomes possible. Our results posit that biodiversity can in part be attributed to natural environmental variations.

Pilot Command Implementation in Aircrafts: A New Approach Based on Dynamic Inversion

A new approach based on dynamic inversion is proposed in this paper for implementing pilot commands in an aircrafts. The command inputs from the pilot are assumed to be (i) the normal acceleration and forward velocity commands in the longitudinal mode and (ii) roll rate, height and forward velocity commands in the lateral mode. A major difference here is that the second derivatives of the velocities along body y and z directions are assumed to be zero, as opposed to the first derivatives (which is used in many published literature). The new approach leads to a significant reduction of tuning parameters in the control design process, which is a major advantage. Detailed derivations of the modified approach are presented with respect to the generic aircraft dynamics model available in [16]. Extensive Six-DOF simulation studies show that, besides the above advantage, the new approach leads to two other additional advantages; namely reduced oscillatory response and reduced control magnitude. In a comparison study with an existing method using the Six-DOF model for Boeing 747 (with the numerical data available in [16]), numerical results clearly show the improved performance of this new approach. Furthermore, in lateral mode a technique for obtaining a corresponding roll rate command from the desired bank angle command is also implemented. Comparison results show improved performance of the new approach with this modification as well.

Quantum Computation of Hydrogen Bond Dynamics and Vibrational Spectra.

Calculating observable properties of chemical systems is often classically intractable and widely viewed as a promising application of quantum information processing. Here, we introduce a new framework for solving generic quantum chemical dynamics problems using quantum logic. We experimentally demonstrate a proof-of-principle instance of our method using the QSCOUT ion-trap quantum computer, where we experimentally drive the ion-trap system to emulate the quantum wavepacket dynamics corresponding to the shared-proton within an anharmonic hydrogen bonded system. Following the experimental creation and propagation of the shared-proton wavepacket on the ion-trap, we extract measurement observables such as its time-dependent spatial projection and its characteristic vibrational frequencies to spectroscopic accuracy (3.3 cm-1 wavenumbers, corresponding to >99.9% fidelity). Our approach introduces a new paradigm for studying the chemical dynamics and vibrational spectra of molecules and opens the possibility to describe the behavior of complex molecular processes with unprecedented accuracy.

Dynamics of a modular manipulator with multiple actuation modes for space applications

A manipulator, designed with N double-tripod multi-loop modules, is the subject of this paper. Each module is configured with multiple actuation alternatives, thus offering both multiple operation modes and design possibilities, along with control challenges. In this paper, a dynamics model of the manipulator of interest is implemented via a novel procedure. The key issue lies in finding the relationship between various actuation modes, to establish one generic dynamics model suitable to all actuation modes. The twists of all moving rigid bodies of the manipulator are derived and represented in terms of general expressions, to be used in the subsequent analysis. A three-modular manipulator is employed to illustrate the implementation of the modeling procedure. Simulation results and prototype experiments of the same manipulator are reported, to validate the procedure. The dynamics analysis reported here is intended to support the subsequent actuation-mode optimization and design of the whole system.

Extending a generic and fast coarse-grained molecular dynamics model to examine the mechanical behavior of grafted polymer nanocomposites

Polymer nanocomposites are an important class of materials for engineering applications due to their high versatility and good mechanical properties combined with low density. By directly attaching the polymer chains to the nanofillers, the so-called grafting, a better load transfer between matrix and filler is achieved, and, in addition, a better dispersion of the fillers is obtained. Both result in enhanced mechanical properties. Since experimental investigations on the nanoscale are extremely challenging, complementary numerical studies are needed to unravel the mechanical behavior of polymer nanocomposites. To this end, molecular dynamics is ideally suited since it captures the microstructure, but is also numerically expensive. Therefore, this contribution presents a fast coarse-grained molecular dynamics model for the investigation of the mechanical behavior of grafted polymer nanocomposites. For this purpose, we extend an existing model by grafting bonds, which allows us to compare the effect of untreated and grafted fillers directly. In particular, we investigate the influence of filler content, grafting degree, and filler size on the stiffness and strength of the polymer (grafted) nanocomposites. We conclude that the grafting bonds have little effect on the stiffness, while the strength is significantly improved compared to the untreated fillers, which is in agreement with the literature. The presented molecular dynamics model for polymer grafted nanocomposites provides the basis for further investigations, particularly of the crucial matrix-filler interphase. In addition, this contribution translates molecular dynamics insights into mechanical properties, which bridges the gap to the engineering scale and thus represents a step towards exploiting the full potential of polymer (grafted) nanocomposites.

Town Savior or Scourge? Asian Identity in the Western and Generic Reversal in 7 Faces of Dr. Lao (1964)

ABSTRACT The often-racist portrayals of Asians in Hollywood productions of the 1950s and 1960s and earlier decades constitutes one facet of a double-bind within which Asian Americans have historically found themselves. Bearing in mind wider cultural, economic, and political discourses surrounding Asian American communities in the postwar period, it is important to closely consider specific cinematic representations of Asians during this period. This article argues that 7 Faces of Dr. Lao (1964) operates as a strange and conflicted film informed by progressive science fiction literature and many of the sentiments that would come to define revisionist westerns. Charles Beaumont's screenplay adaptation of Charles G. Finney's novel The Circus of Dr. Lao (1935) infuses the film with clever and engaging dialogue and mirrors the concepts of reversal often present in Beaumont's work. Furthermore, Beaumont's screenplay offers insightful takes on racial and generic dynamics in a film that might otherwise be dismissed as an egregious example of harmful yellowface practices. Thus, viewing 7 Faces of Dr. Lao as a prototypical revisionist western draws attention to its engagement with concepts of reversal and critique of stereotypes.

Measuring Arbitrary Physical Properties in Analog Quantum Simulation

A central challenge in analog quantum simulation is to characterize desirable physical properties of quantum states produced in experiments. However, in conventional approaches, the extraction of arbitrary information requires performing measurements in many different bases, which necessitates a high level of control that present-day quantum devices may not have. Here, we propose and analyze a scalable protocol that leverages the ergodic nature of generic quantum dynamics, enabling the efficient extraction of many physical properties. The protocol does not require sophisticated controls and can be generically implemented in analog quantum simulation platforms today. Our protocol involves introducing ancillary degrees of freedom in a predetermined state to a system of interest, quenching the joint system under Hamiltonian dynamics native to the particular experimental platform, and then measuring globally in a single, fixed basis. We show that arbitrary information of the original quantum state is contained within such measurement data, and can be extracted using a classical data-processing procedure. We numerically demonstrate our approach with a number of examples, including the measurements of entanglement entropy, many-body Chern number, and various superconducting orders in systems of neutral atom arrays, bosonic and fermionic particles on optical lattices, respectively, only assuming existing technological capabilities. Our protocol excitingly promises to overcome limited controllability and, thus, enhance the versatility and utility of near-term quantum technologies.

From Dual Unitarity to Generic Quantum Operator Spreading.

Dual-unitary circuits are paradigmatic examples of exactly solvable yet chaotic quantum many-body systems, but solvability naturally goes along with a degree of nongeneric behavior. By investigating the effect of weakly broken dual unitarity on the spreading of local operators, we study whether, and how, small deviations from dual unitarity recover fully generic many-body dynamics. We present a discrete path-integral formula for the out-of-time-order correlator and recover a butterfly velocity smaller than the light-cone velocity, v_{B}<v_{LC}, and a diffusively broadening operator front, two generic features of ergodic quantum spin chains absent in dual-unitary circuit dynamics. The butterfly velocity and diffusion constant are determined by a small set of microscopic quantities, and the operator entanglement of the gates has a crucial role.

Distributed decentralized EKF for very large-scale networks with application to satellite mega-constellations navigation

The design of a decentralized and distributed filtering solution for large-scale networks of interconnected systems is addressed considering (i) generic nonlinear dynamics and (ii) generic coupled nonlinear outputs in a generic, possibly time-varying, topology. The local filters, which follow the structure of the extended Kalman filter, are implemented in each system, which estimates its own state exclusively. To be suitable for the heavily restricted implementation to very large-scale systems, a novel algorithm is proposed, which: (i) does not rely on instantaneous data transmission; (ii) allows local communication exclusively; and (iii) requires computational, memory, and data transmission resources for each system that do not scale with the dimension of the network. The scalability of the proposed algorithm allows for its application to the cooperative localization problem of very large-scale systems. In particular, it is applied herein to the on-board position estimation problem of LEO mega-constellations using GNSS featuring numerical simulations for the Starlink constellation.

Distinguishability transitions in nonunitary boson-sampling dynamics

We discover novel transitions characterized by distinguishability of bosons in non-unitary dynamics with parity-time ($\mathcal{PT}$) symmetry. We show that $\mathcal{PT}$ symmetry breaking, a unique transition in non-Hermitian open systems, enhances regions in which bosons can be regarded as distinguishable. This means that classical computers can sample the boson distributions efficiently in these regions by sampling the distribution of distinguishable particles. In a $\mathcal{PT}$-symmetric phase, we find one dynamical transition upon which the distribution of bosons deviates from that of distinguishable particles, when bosons are initially put at distant sites. If the system enters a $\mathcal{PT}$-broken phase, the threshold time for the transition is suddenly prolonged, since dynamics of each boson is diffusive (ballistic) in the $\mathcal{PT}$-broken ($\mathcal{PT}$-symmetric) phase. Furthermore, the $\mathcal{PT}$-broken phase also exhibits a notable dynamical transition on a longer time scale, at which the bosons again become distinguishable. This transition, and hence the classical easiness of sampling bosons in long times, are true for generic postselected non-unitary quantum dynamics, while it is absent in unitary dynamics of isolated quantum systems. $\mathcal{PT}$ symmetry breaking can also be characterized by the efficiency of a classical algorithm based on the rank of matrices, which can (cannot) efficiently compute the photon distribution in the long-time regime of the $\mathcal{PT}$-broken ($\mathcal{PT}$-symmetric) phase.

Numerical Study on Tandem-Rotor Autorotation in Forward Flight

This work presents a systematic approach to analyzing the aerodynamic characteristics of tandem rotor forward autorotation considering rotor-to-rotor interference. The single-rotor computational model trimmed from a generic helicopter flight dynamics analysis program was used as the baseline model. The effectiveness of the baseline model is demonstrated by a comparison with data from wind tunnel tests performed in this work. The rotor disk angle of attack and driven moment distribution obtained by the modified model indicate the fact that the rotor acceleration is primarily caused by the higher angle of attack region of the disk. This is of great significance in the rotor blade design, in terms of the drag-to-lift ratio characteristics of the airfoil under different angle-of-attack ranges. The influence of wind speed, rotor shaft angle, and collective pitch on the steady-state rotor speed was then studied. The results show a nonlinear nature of the variation of steady rotor speed with collective pitch, which can cause a thrust control reverse problem during flight operations. To reveal the flow field details of rotor-to-rotor interference, the flow field Navier–Stokes equations of tandem rotor autorotation were solved. Computational results of both rotors’ inflow velocities were considered when deriving the empirical model of interference. The refined interference model was compared to the wind tunnel test data of the tandem rotor autorotation and showed good performance. This synthetical methodology, which combines mechanism analysis with CFD-aided refinement and experiment verification, achieves a balance between computational costs and accuracy and thus can be readily applied to engineering practices.

Learning in Transcriptional Network Models: Computational Discovery of Pathway-Level Memory and Effective Interventions.

Trainability, in any substrate, refers to the ability to change future behavior based on past experiences. An understanding of such capacity within biological cells and tissues would enable a particularly powerful set of methods for prediction and control of their behavior through specific patterns of stimuli. This top-down mode of control (as an alternative to bottom-up modification of hardware) has been extensively exploited by computer science and the behavioral sciences; in biology however, it is usually reserved for organism-level behavior in animals with brains, such as training animals towards a desired response. Exciting work in the field of basal cognition has begun to reveal degrees and forms of unconventional memory in non-neural tissues and even in subcellular biochemical dynamics. Here, we characterize biological gene regulatory circuit models and protein pathways and find them capable of several different kinds of memory. We extend prior results on learning in binary transcriptional networks to continuous models and identify specific interventions (regimes of stimulation, as opposed to network rewiring) that abolish undesirable network behavior such as drug pharmacoresistance and drug sensitization. We also explore the stability of created memories by assessing their long-term behavior and find that most memories do not decay over long time periods. Additionally, we find that the memory properties are quite robust to noise; surprisingly, in many cases noise actually increases memory potential. We examine various network properties associated with these behaviors and find that no one network property is indicative of memory. Random networks do not show similar memory behavior as models of biological processes, indicating that generic network dynamics are not solely responsible for trainability. Rational control of dynamic pathway function using stimuli derived from computational models opens the door to empirical studies of proto-cognitive capacities in unconventional embodiments and suggests numerous possible applications in biomedicine, where behavior shaping of pathway responses stand as a potential alternative to gene therapy.