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At least 181 records · Page 10

Impact of dynamics, entanglement and Markovian noise on the fidelity of few-qubit digital quantum simulation

Quantum algorithms have been proposed to accelerate the simulation of the chaotic dynamical systems that are ubiquitous in the physics of plasmas. Quantum computers without error correction might even use noise to their advantage to calculate the Lyapunov exponent by measuring the Loschmidt echo fidelity decay rate. For the first time, digital Hamiltonian simulations of the quantum sawtooth map, performed on the IBM-Q quantum hardware platform, show that the fidelity decay rate of a digital quantum simulation increases during the transition from dynamical localization to chaotic diffusion in the map. The observed error per CNOT gate increases by $1.5{\times }$ as the dynamics varies from localized to diffusive, while only changing the phases of virtual RZ gates and keeping the overall gate count constant. A gate-based Lindblad noise model that captures the effective change in relaxation and dephasing errors during gate operation qualitatively explains the effect of dynamics on fidelity as being due to the localization and entanglement of the states created. Specifically, highly delocalized states that are entangled with random phases show an increased sensitivity to dephasing and, on average, a similar sensitivity to relaxation as localized states. In contrast, delocalized unentangled states show an increased sensitivity to dephasing but a lower sensitivity to relaxation. This gate-based Lindblad model is shown to be a useful benchmarking tool by estimating the effective Lindblad coherence times during CNOT gates and finding a consistent $2\unicode{x2013}3{\times }$ shorter $T_2$ time than reported for idle qubits. Thus, the interplay of the dynamics of a simulation with the noise processes that are active can strongly influence the overall fidelity decay rate.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Rotordynamics on the PC: Further Capabilities of ARDS

Rotordynamics codes for personal computers are now becoming available. One of the most capable codes is Analysis of RotorDynamic Systems (ARDS) which uses the component mode synthesis method to analyze a system of up to 5 rotating shafts. ARDS was originally written for a mainframe computer but has been successfully ported to a PC; its basic capabilities for steady-state and transient analysis were reported in an earlier paper. Additional functions have now been added to the PC version of ARDS. These functions include: 1) Estimation of the peak response following blade loss without resorting to a full transient analysis; 2) Calculation of response sensitivity to input parameters; 3) Formulation of optimum rotor and damper designs to place critical speeds in desirable ranges or minimize bearing loads; 4) Production of Poincard plots so the presence of chaotic motion can be ascertained. ARDS produces printed and plotted output. The executable code uses the full array sizes of the mainframe version and fits on a high density floppy disc. Examples of all program capabilities are presented and discussed.

Fleming, David P.↗

Chaos, percolation and the coronavirus spread: a two-step model

We discuss a two-step model for the rise and decay of a new coronavirus (Severe Acute Respiratory Syndrome-CoV-2) first reported in December 2019, COVID-19. The first stage is well described by the same equation for turbulent flows, population growth and chaotic maps: a small number of infected, d 0 , grows exponentially to a saturation value, d ∞ . The typical growth time (aggressive spreading of the virus) is given by τ = 1/λ where λ is the Lyapunov exponent. After a time t crit determined by social distancing and/or other measures, the spread decreases exponentially analogous to nuclear decays and non-chaotic maps. Some countries, like China, S. Korea and Italy, are in this second stage while others including the USA are near the end of the growth stage. The model predicted 15,000 (±2250) casualties for the Lombardy region (Italy) at the end of the spreading around May 10, 2020. Without the quarantine, the casualties would have been more than 50,000, one hundred days after the start of the pandemic. Here, the data from the 50 US states are of very poor quality because of an extremely late and confused response to the pandemic, resulting unfortunately in a large number of casualties, more than 70,000 on May 6, 2020, and more than 170,000 on August 21, 2020. S. Korea, notwithstanding the high population density (511/km 2 ) and the closeness to China, responded best to the pandemic with 255 deceased as of May 6, 2020, and 301 on August 21, 2020.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Comparisons of the hydraulics of water flows in Martian outflow channels with flows of similar scale on earth

The hydraulics of channelized water flows on Mars and the resulting sediment transport rates are calculated, and similar computations are performed for such terrestrial analogs as the Mississippi River and the catastrophic Lake Missoula floods that formed the Channeled Scabland in eastern Washington State. The morphologies of deep-sea channels formed by catastrophic turbidity currents are compared with the Martian channels, many similarities are pointed out, and the hydraulics of the various flows are compared. The results indicate that the velocities, discharges, bottom shear stresses, and sediment-transport capacity of water flows along the Martian channels would be comparable to those of the oceanic turbidity currents and the Lake Missoula floods. It is suggested that the submarine canyons from which turbidity currents originate are the terrestrial counterparts to the chaotic-terrain areas or craters that serve as sources for many of the Martian channels.

Komar, P. D.↗

Scalable Asynchronous Domain Decomposition Solvers

We discuss how parallel implementations of linear iterative solvers generally alternate between phases of data exchange and phases of local computation. Increasingly large problem sizes and more heterogeneous compute architectures make load balancing and the design of low latency network interconnects that are able to satisfy the communication requirements of linear solvers very challenging tasks. In particular, global communication patterns such as inner products become increasingly limiting at scale. We explore the use of asynchronous communication based on one-sided Message Passing Interface primitives in the context of domain decomposition solvers. In particular, a scalable asynchronous two-level Schwarz method is presented. We discuss practical issues encountered in the development of a scalable solver and show experimental results obtained on a state-of-the-art supercomputer system that illustrate the benefits of asynchronous solvers in load balanced as well as load imbalanced scenarios. Using the novel method, we can observe speedups of up to four times over its classical synchronous equivalent.

97 MATHEMATICS AND COMPUTING↗

Active Fluids Form System-Spanning Filamentary Networks

Recent experimental realizations of liquid-liquid phase separation of active liquid crystals have offered an insight into the interaction between phase separation, ubiquitous in soft matter and biology, and chaotic active flows. Here, in this Letter, we use continuum theory to examine phase separation of an active liquid crystal and a passive fluid and report two new results. First, we provide an analytical derivation of the activity-induced suppression of the phase boundary of the coexistence region—a result first reported in simulations and experiments. We show that the shift in the critical point is a result of the balance between self-stirring active flows and phase-separating diffusive fluxes. Second, we show that this same balance is responsible for dramatically changing the morphology of the phase separated state, resulting in the emergence of a new mixed active phase consisting of a dynamical filamentous active network that invades the entire system area, trapping droplets of passive material. This structure exists even for very low volume fractions of active material. Our work provides an important step towards the goal of understanding how to use activity as a new handle for sculpting interfaces.

active nematics↗

Advanced data assimilation in strongly nonlinear dynamical systems

Advanced data assimilation methods are applied to simple but highly nonlinear problems. The dynamical systems studied here are the stochastically forced double well and the Lorenz model. In both systems, linear approximation of the dynamics about the critical points near which regime transitions occur is not always sufficient to track their occurrence or nonoccurrence. Straightforward application of the extended Kalman filter yields mixed results. The ability of the extended Kalman filter to track transitions of the double-well system from one stable critical point to the other depends on the frequency and accuracy of the observations relative to the mean-square amplitude of the stochastic forcing. The ability of the filter to track the chaotic trajectories of the Lorenz model is limited to short times, as is the ability of strong-constraint variational methods. Examples are given to illustrate the difficulties involved, and qualitative explanations for these difficulties are provided. Three generalizations of the extended Kalman filter are described. The first is based on inspection of the innovation sequence, that is, the successive differences between observations and forecasts; it works very well for the double-well problem. The second, an extension to fourth-order moments, yields excellent results for the Lorenz model but will be unwieldy when applied to models with high-dimensional state spaces. A third, more practical method--based on an empirical statistical model derived from a Monte Carlo simulation--is formulated, and shown to work very well. Weak-constraint methods can be made to perform satisfactorily in the context of these simple models, but such methods do not seem to generalize easily to practical models of the atmosphere and ocean. In particular, it is shown that the equations derived in the weak variational formulation are difficult to solve conveniently for large systems.

Miller, Robert N.↗

Chaos in the Solar System

The physical basis of chaos in the solar system is now better understood: In all cases investigated so far, chaotic orbits result from overlapping resonances. Perhaps the clearest examples are found in the asteroid belt. Overlapping resonances account for its kirkwood gaps and were used to predict and find evidence for very narrow gaps in the outer belt. Further afield, about one new "short-peroid" comet is discovered each year. They are believed to come from the "Kuiper Belt" (at 40 AU or more) via chaotic orbits produced by mean-motion and secular resonances with Neptune. Finally, the planetary system itself is not immune from chaos. In the inner solar system, overlapping secular resonances have been identified as the possible source of chaos. For example, Mercury in 1012 years, may suffer a close encounter with Venus or plunge into the Sun. In the outer solar system, three-body resonances have been identified as a source of chaos, but on an even longer time scale of 109 times the age of the solar system. On the human time scale, the planets do follow their orbits in a stately procession, and we can predict their trajectories for hundreds of thousands of years. That is because the mavericks, with shorter instability times, have long since been ejected. The solar system is not stable; it is just old!

Lecar, Myron↗

The case for digital twins in metal additive manufacturing

The digital twin (DT) is a relatively new concept that is finding increased acceptance in industry. A DT is generally considered as comprising a physical entity, its virtual replica, and two-way digital data communications in-between. Its primary purpose is to leverage the process intelligence captured within digital models—or usually their faster-solving surrogates—towards generating increased value from the physical entities. The surrogate models are created using machine learning based on data obtained from the field, experiments and digital models, which may be physics-based or statistics-based. Anomaly detection and correction, and diagnostic closed-loop process control are examples of how a process DT can be deployed. In the manufacturing industry, its use can achieve improvements in product quality and process productivity. Metal additive manufacturing (AM) stands to gain tremendously from the use of DTs. This is because the AM process is inherently chaotic, resulting in poor repeatability. However, a DT acting in a supervisory role can inject certainty into the process by actively keeping it within bounds through real-time control commands. Closed-loop feedforward control is achieved by observing the process through sensors that monitor critical parameters and, if there are any deviations from their respective optimal ranges, suitable corrective actions are triggered. The type of corrective action (e.g. a change in laser power or a modification to the scanning speed) and its magnitude are determined by interrogating the surrogate models. Because of their artificial intelligence (AI)-endowed predictive capabilities, which allow them to foresee a future state of the physical twin (e.g. the AM process), DTs proactively take context-sensitive preventative steps, whereas traditional closed-loop feedback control is usually reactive. Apart from assisting a build process in real-time, a DT can help with planning the build of a part by pinpointing the optimum processing window relevant to the desired outcome. Again, the surrogate models are consulted to obtain the required information. In this article, we explain how the application of DTs to the metal AM process can significantly widen its application space by making the process more repeatable (through quality assurance) and cheaper (by getting builds right the first time).

36 MATERIALS SCIENCE↗

Transport, correlations, and chaos in a classical disordered anharmonic chain

Here, we explore transport properties in a disordered nonlinear chain of classical harmonic oscillators, and thereby identify a regime exhibiting behavior analogous to that seen in quantum many-body-localized systems. Through extensive numerical simulations of this system connected at its ends to heat baths at different temperatures, we computed the heat current and the temperature profile in the nonequilibrium steady state as a function of system size $\textit{N}$, disorder strength Δ, and temperature $\textit{T}$. The conductivity $κ_N$, obtained for finite length ($\textit{N}$), saturates to a value $κ_∞$ > 0 in the large $\textit{N}$ limit, for all values of disorder strength Δ and temperature $\textit{T}$ > 0. We show evidence that for any Δ > 0 the conductivity goes to zero faster than any power of $\textit{T}$ in the ($\textit{T}$/Δ) → 0 limit, and find that the form $κ_∞$ ~ $e^{{–B|\text{ln}(CΔ/T)|}^{3}}$ fits our data. This form has earlier been suggested by a theory based on the dynamics of multioscillator chaotic islands. The finite-size effect can be $κ_N < κ_∞$ due to boundary resistance when the bulk conductivity is high (the weak disorder case), or $κ_N > κ_∞$ due to direct bath-to-bath coupling through bulk localized modes when the bulk is weakly conducting (the strong disorder case). We also present results on equilibrium dynamical correlation functions and on the role of chaos on transport properties. Finally, we explore the differences in the growth and propagation of chaos in the weak and strong chaos regimes by studying the classical version of the out-of-time-ordered commutator.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Exact Coherent Structures and Phase Space Geometry of Preturbulent 2D Active Nematic Channel Flow

Confined active nematics exhibit rich dynamical behavior, including spontaneous flows, periodic defect dynamics, and chaotic “active turbulence.” Here, we study these phenomena using the framework of exact coherent structures, which has been successful in characterizing the routes to high Reynolds number turbulence of passive fluids. Exact coherent structures are stationary, periodic, quasiperiodic, or traveling wave solutions of the hydrodynamic equations that, together with their invariant manifolds, serve as an organizing template of the dynamics. We compute the dominant exact coherent structures and connecting orbits in a preturbulent active nematic channel flow, which enables a fully nonlinear but highly reduced-order description in terms of a directed graph. Using this reduced representation, we compute instantaneous perturbations that switch the system between disparate spatiotemporal states occupying distant regions of the infinite-dimensional phase space. Overall, our results lay the groundwork for a systematic means of understanding and controlling active nematic flows in the moderate- to high-activity regime.

36 MATERIALS SCIENCE↗

Sensitivity of Grass Fires Burning in Marginal Conditions to Atmospheric Turbulence

Abstract Atmospheric forcing and interactions between the fire and atmosphere are primary drivers of wildland fire behavior. The atmosphere is known to be a chaotic system that, although deterministic, is very sensitive to small perturbations to initial conditions. We assume that as a result of the tight coupling between fire and atmosphere; wildland fire behavior, in turn, should also be sensitive to perturbations in atmospheric initial conditions. Observations suggest that low intensity prescribed fire, in particular, is susceptible to small perturbations in the wind field, which can significantly alter fire spread. Here, we employ a computational fluid dynamics model of coupled fire‐atmosphere interactions to answer the question: How sensitive is fire behavior to small variations in atmospheric turbulence? We perform ensemble simulations of fires in homogenous grass fuels. The only difference between ensemble members is the state of the turbulent atmosphere provided to the model throughout the simulation. The atmospheric state is a function of the initial conditions applied at the start of the simulation and boundary conditions applied throughout the simulation. We find a wide range of outcomes, with area burned ranging from 2,212 to 11,236 m 2 (>400% change), driven primarily by sensitivity to initial conditions, with nonnegligible contributions from boundary condition variability during the initial 30 s of simulation. Our results highlight the need for ensemble simulations, especially when considering fire behavior in marginal burning conditions.

54 ENVIRONMENTAL SCIENCES↗

Spectroscopic far ultraviolet observations of transition zone instabilities and their possible role in a pre-flare energy build-up

Highly flare-productive newly emerging active regions are characterized by numerous small low-lying loops which frequently show a chaotic pattern. Flare activity in such a region subsides as the chaotic loop structures relax and expand into a bipolar configuration. The transition zone in such an active region is highly unstable, as shown by broadened and shifted nonthermal line profiles of medium-ionized elements like Si III, Si IV, and C IV. These transition-zone instabilities, which occur as isolated events in active regions of low flare productivity, are often observed prior to flares. Transition-zone instabilities can be traced to the footpoints of active loops and seem to be accompanied by heating of the loop. The loops vary in size and show differing degrees of activity, with the brightest and most compact ones seemingly being in a pre-flare state which results in the catastrophic energy release along the loop during a flare.

Brueckner, G. E.↗

The relation between ferroelasticity and superconductivity

The high-temperature superconductivity is explained widely by the layered crystal structure. The one- and two-dimensional subsystems and their interaction are investigated here. It is assumed that the high-T(sub c) superconductivity takes place in the two-dimensional subsystem and the increase of the phase transition temperature from 60 K up to 90 K is the consequence of turning on the influence of one-dimensional chains. The interaction between the two subsystems is transferred along the c axis by the phonons of breathing mode, which causes the hybridization of the electronic bonds between these subsystems. The experimental works indicate that the existence of both the chains Cu(1)-O and their interaction with the superconducting plane of Cu(2)-O modify the temperature of the transition to the superconducting state. It is seen from the neutron scattering data that the rates of the interatomic distance dependencies on temperature are changed around 140 K and 90 K. The 'zig-zag' order in Cu(1)-O chains has been postulated but, on the other hand, the vibrations with a large amplitude only were reported. The bi-stabilized situation of the oxygen ions can be caused by the change of distance between these ions and the Ba ions. It leads to the appearance of a two-well potential. Its parameters depend on temperature and the dynamics of the oxygen ions' movement. They can induce the antipolar order, which can be, however, more or less chaotic. The investigation of the ferroelastic properties of Y-Ba-Cu-O samples lead to the conclusion that they are related to jumps of ions inside the given chain and not to a diffusion between different sites in the ab plane. Researchers deduce thus that the fluctuating oxygen ions from these chains create dipoles in the ab plane. They can be described with the pseudo-spin formalism/ - Pauli matrices/. The system can be described with the Ising model. The pseudo-spins interact with phonons and influence the superconductivity in the second subsystem.

Molak, A.↗

The relation between ferroelasticity and superconductivity

The high-temperature superconductivity is explained widely by the layered crystal structure. The one- and two-dimensional subsystems and their interaction are investigated here. It is assumed that the high-T(sub c) superconductivity takes place in the two-dimensional subsystem and the increase of the phase transition temperature from 60 K up to 90 K is the consequence of turning on the influence of one-dimensional chains. The interaction between the two subsystems is transferred along the c axis by the phonons of breathing mode, which causes the hybridization of the electronic bonds between these subsystems. The experimental works indicate that the existence of both the chains Cu(1)-O and their interaction with the superconducting plane of Cu(2)-O modify the temperature of the transition to the superconducting state. It is seen from the neutron scattering data that the rates of the interatomic distance dependencies on temperature are changed around 240 K and 90 K. The 'zig-zag' order in Cu(1)-O chains has been postulated but, on the other hand, the vibrations with a large amplitude only were reported. The bi-stabilized situation of the oxygen ions can be caused by the change of distance between these ions and the Ba ions. It leads to the appearance of a two-well potential. Its parameters depend on temperature and the dynamics of the oxygen ions' movement. They can induce the antipolar order, which can be, however, more or less chaotic. The investigation of the ferroelastic properties of Y-Ba-Cu-O samples lead to the conclusion that they are related to jumps of ions inside the given chain and not to a diffusion between different sites in the ab plane. Researchers deduce, thus, that the fluctuating oxygen ions from these chains create dipoles in the ab plane. They can be described with the pseudo-spin formalism (- Pauli matrices). The system can be described with the Ising model. The pseudo-spins interact with phonons and influence the superconductivity in the second subsystem.

Molak, A.↗

Quantum Energy Teleportation versus Information Teleportation

Quantum energy teleportation (QET) is the phenomenon in which locally inaccessible energy is activated as extractable work through collaborative local operations and classical communication (LOCC) with an entangled partner. It closely resembles the more well-known quantum information teleportation (QIT) where quantum information can be sent through an entangled pair with LOCC. It is tempting to ask how QET is related to QIT. Here we report a first study of this connection. Despite the apparent similarity, we show that these two phenomena are not only distinct but moreover are mutually competitive. We show a perturbative trade-off relation between their performance in a thermal entangled chaotic many-body system, in which both QET and QIT are simultaneously implemented through a traversable wormhole in an emergent spacetime. Motivated by this example, we study a generic setup of two entangled qudits and prove a universal non-perturbative trade-off bound. It shows that for any teleportation protocol, the overall performance of QET and QIT together is constrained by the entanglement resource. We discuss some explanations of our results.

Wang, Jinzhao [Stanford University, CA (United Sta↗

Mean-field entanglement transitions in random tree tensor networks

Entanglement phase transitions in quantum chaotic systems subject to projective measurements and in random tensor networks have emerged as a new class of critical points separating phases with different entanglement scaling. We propose a mean-field theory of such transitions by studying the entanglement properties of random tree tensor networks. As a function of bond dimension, we find a phase transition separating area-law from logarithmic scaling of the entanglement entropy. Using a mapping onto a replica statistical mechanics model defined on a Cayley tree and the cavity method, we analyze the scaling properties of such transitions. Our approach provides a tractable, mean-field-like example of an entanglement transition. Furthermore, we verify our predictions numerically by computing directly the entanglement of random tree tensor network states.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Reconfigurable training and reservoir computing in an artificial spin-vortex ice via spin-wave fingerprinting

Strongly interacting artificial spin systems are moving beyond mimicking naturally occurring materials to emerge as versatile functional platforms, from reconfigurable magnonics to neuromorphic computing. Typically, artificial spin systems comprise nanomagnets with a single magnetization texture: collinear macrospins or chiral vortices. Here, by tuning nanoarray dimensions we have achieved macrospin–vortex bistability and demonstrated a four-state metamaterial spin system, the ‘artificial spin-vortex ice’ (ASVI). ASVI can host Ising-like macrospins with strong ice-like vertex interactions and weakly coupled vortices with low stray dipolar field. Vortices and macrospins exhibit starkly differing spin-wave spectra with analogue mode amplitude control and mode frequency shifts of Δf = 3.8 GHz. The enhanced bitextural microstate space gives rise to emergent physical memory phenomena, with ratchet-like vortex injection and history-dependent non-linear fading memory when driven through global magnetic field cycles. We employed spin-wave microstate fingerprinting for rapid, scalable readout of vortex and macrospin populations, and leveraged this for spin-wave reservoir computation. ASVI performs non-linear mapping transformations of diverse input and target signals in addition to chaotic time-series forecasting.

97 MATHEMATICS AND COMPUTING↗