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At least 289 records · Page 16

Potential Predictability of the Monsoon Subclimate Systems

While El Nino/Southern Oscillation (ENSO) phenomenon can be predicted with some success using coupled oceanic-atmospheric models, the skill of predicting the tropical monsoons is low regardless of the methods applied. The low skill of monsoon prediction may be either because the monsoons are not defined appropriately or because they are not influenced significantly by boundary forcing. The latter characterizes the importance of internal dynamics in monsoon variability and leads to many eminent chaotic features of the monsoons. In this study, we analyze results from nine AMIP-type ensemble experiments with the NASA/GEOS-2 general circulation model to assess the potential predictability of the tropical climate system. We will focus on the variability and predictability of tropical monsoon rainfall on seasonal-to-interannual time scales. It is known that the tropical climate is more predictable than its extratropical counterpart. However, predictability is different from one climate subsystem to another within the tropics. It is important to understand the differences among these subsystems in order to increase our skill of seasonal-to-interannual prediction. We assess potential predictability by comparing the magnitude of internal and forced variances as defined by Harzallah and Sadourny (1995). The internal variance measures the spread among the various ensemble members. The forced part of rainfall variance is determined by the magnitude of the ensemble mean rainfall anomaly and by the degree of consistency of the results from the various experiments.

Yang, Song↗

Enhanced quantum state transfer by circumventing quantum chaotic behavior

The ability to realize high-fidelity quantum communication is one of the many facets required to build generic quantum computing devices. In addition to quantum processing, sensing, and storage, transferring the resulting quantum states demands a careful design that finds no parallel in classical communication. Existing experimental demonstrations of quantum information transfer in solid-state quantum systems are largely confined to small chains with few qubits, often relying upon non-generic schemes. Here, by using a superconducting quantum circuit featuring thirty-six tunable qubits, accompanied by general optimization procedures deeply rooted in overcoming quantum chaotic behavior, we demonstrate a scalable protocol for transferring few-particle quantum states in a two-dimensional quantum network. These include single-qubit excitation, two-qubit entangled states, and two excitations for which many-body effects are present. Our approach, combined with the quantum circuit’s versatility, paves the way to short-distance quantum communication for connecting distributed quantum processors or registers, even if hampered by inherent imperfections in actual quantum devices.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Ring Around the Black Hole

Regardless of size, black holes easily acquire accretion disks. Supermassive black holes can feast on the bountiful interstellar gas in galactic nuclei. Small black holes formed from collapsing stars often belong to binary systems in which a bulging companion star can spill some of its gas into the black hole s reach. In the chaotic mess of the accretion disk, atoms collide with one another. Swirling plasma reaches speeds upward of 10% that of light and glows brightly in many wavebands, particularly in X-rays. Gas gets blown back by a wind of radiation from the inner disk. New material enters the disks from different directions.

Wanjek, Christopher↗

Application of non-linear dynamics to the characterization of cardiac electrical instability

Beat-to-beat alternation in the morphology of the ECG has been previously observed in hearts susceptible to fibrillation. In addition, fibrillation has been characterized by some as a chaotic state. Period doubling phenomena, such as alternation, and the onset of chaos have been connected by non-linear dynamical systems theory. In this paper, we describe the use of a technique from nonlinear dynamics theory, the construction of a first return nap, to assess the susceptibility to fibrillation threshhold in canine experiments.

NASA Discipline Cardiopulmonary↗

Chaos: Understanding and Controlling Laser Instability

In order to characterize the behavior of tunable diode lasers (TDL), the first step in the project involved the redesign of the TDL system here at the University of Tennessee Molecular Systems Laboratory (UTMSL). Having made these changes it was next necessary to optimize the new optical system. This involved the fine adjustments to the optical components, particularly in the monochromator, to minimize the aberrations of coma and astigmatism and to assure that the energy from the beam is focused properly on the detector element. The next step involved the taking of preliminary data. We were then ready for the analysis of the preliminary data. This required the development of computer programs that use mathematical techniques to look for signatures of chaos. Commercial programs were also employed. We discovered some indication of high dimensional chaos, but were hampered by the low sample rate of 200 KSPS (kilosamples/sec) and even more by our sample size of 1024 (1K) data points. These limitations were expected and we added a high speed data acquisition board. We incorporated into the system a computer with a 40 MSPS (million samples/sec) data acquisition board. This board can also capture 64K of data points so that were then able to perform the more accurate tests for chaos. The results were dramatic and compelling, we had demonstrated that the lead salt diode laser had a chaotic frequency output. Having identified the chaotic character in our TDL data, we proceeded to stage two as outlined in our original proposal. This required the use of an Occasional Proportional Feedback (OPF) controller to facilitate the control and stabilization of the TDL system output. The controller was designed and fabricated at GSFC and debugged in our laboratories. After some trial and error efforts, we achieved chaos control of the frequency emissions of the laser. The two publications appended to this introduction detail the entire project and its results.

Blass, William E.↗

Fuzzy spheres in stringy matrix models: quantifying chaos in a mixed phase space

We consider a truncation of the BMN matrix model to a configuration of two fuzzy spheres, described by two coupled non-linear oscillators dependent on the mass parameter μ. The classical phase diagram of the system generically (μ ≠ 0) contains three equilibrium points: two centers and a center-saddle; as μ → 0 the system exhibits a pitchfork bifurcation. We demonstrate that the system is exactly integrable in quadratures for μ = 0, while for very large values of μ, it approaches another integrable point characterized by two harmonic oscillators. The classical phase space is mixed, containing both integrable islands and chaotic regions, as evidenced by the classical Lyapunov spectrum. At the quantum level, we explore indicators of early and late time chaos. The eigenvalue spacing is best described by a Brody distribution, which interpolates between Poisson and Wigner distributions; it dovetails, at the quantum level, the classical results and reemphasizes the notion that the quantum system is mixed. We also study the spectral form factor and the quantum Lyapunov exponent, as defined by out-of-time-ordered correlators. These two indicators of quantum chaos exhibit weak correlations with the Brody distribution. We speculate that the behavior of the system as μ → 0 dominates the spectral form factor and the quantum Lyapunov exponent, making these indicators of quantum chaos less effective in the context of a mixed phase space.

AdS-CFT correspondence↗

Rigorous justification for the space–split sensitivity algorithm to compute linear response in Anosov systems

Ruelle gave a formula for linear response of transitive Anosov diffeomorphisms. Recently, practically computable realizations of Ruelle's formula have emerged that potentially enable sensitivity analysis of certain high-dimensional chaotic numerical simulations encountered in the applied sciences. In this paper, we provide full mathematical justification for the convergence of one such efficient computation, the space–split sensitivity, or S3, algorithm. In S3, Ruelle's formula is computed as a sum of two terms obtained by decomposing the perturbation vector field into a coboundary and a remainder that is parallel to the unstable direction. Such a decomposition results in a splitting of Ruelle's formula that is amenable to efficient computation. Here, we prove the existence of the S3 decomposition and the convergence of the computations of both resulting components of Ruelle's formula.

97 MATHEMATICS AND COMPUTING↗

Open-system spin transport and operator weight dissipation in spin chains

Here, we use nonequilibrium steady states to study the effect of dissipation-assisted operator evolution (DAOE) on the scaling behavior of transport in one-dimensional spin chains. We consider three models in the XXZ family: the XXZ model with staggered anisotropy, which is chaotic; XXZ model with no external field and tunable interaction, which is Bethe-ansatz integrable and (in the zero interaction limit) free-fermion integrable; and the disordered XY model, which is free-fermion integrable and Anderson localized. We find evidence that DAOE's effect on transport is controlled by its effect on the system's conserved quantities. To the extent that DAOE preserves those symmetries, it preserves the scaling of the system's transport properties; to the extent it breaks those conserved quantities, it pushes the system towards diffusive scaling of transport.

1-dimensional spin chains↗

Mars dust storms - Interannual variability and chaos

The hypothesis is that the global climate system, consisting of atmospheric dust interacting with the circulation, produces its own interannual variability when forced at the annual frequency. The model has two time-dependent variables representing the amount of atmospheric dust in the northern and southern hemispheres, respectively. Absorption of sunlight by the dust drives a cross-equatorial Hadley cell that brings more dust into the heated hemisphere. The circulation decays when the dust storm covers the globe. Interannual variability manifests itself either as a periodic solution in which the period is a multiple of the Martian year, or as an aperiodic (chaotic) solution that never repeats. Both kinds of solution are found in the model, lending support to the idea that interannual variability is an intrinsic property of the global climate system. The next step is to develop a hierarchy of dust-circulation models capable of being integrated for many years.

Ingersoll, Andrew P.↗

Linear growth of circuit complexity from Brownian dynamics

How rapidly can a many-body quantum system generate randomness? Using path integral methods, we demonstrate that Brownian quantum systems have circuit complexity that grows linearly with time. In particular, we study Brownian clusters of N spins or fermions with time-dependent all-to-all interactions, and calculate the Frame Potential to characterize complexity growth in these models. In both cases the problem can be mapped to an effective statistical mechanics problem which we study using path integral methods. Within this framework it is straightforward to show that the kth Frame Potential comes within ϵ of the Haar value after a time of order t ~ kN + k log k + log ϵ –1 . Using a bound on the diamond norm, this implies that such circuits are capable of coming very close to a unitary k-design after a time of order t ~ kN. We also consider the same question for systems with a time-independent Hamiltonian and argue that a small amount of time-dependent randomness is sufficient to generate a k-design in linear time provided the underlying Hamiltonian is quantum chaotic. These models provide explicit examples of linear complexity growth that are analytically tractable and are directly applicable to practical applications calling for unitary k-designs.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Dynamical responses of constrained pipe conveying fluids and its dependence on the modeling of the contact force

Accurately modeling the impact force used in the analysis of loosely constrained cantilevered pipes conveying fluid is imperative. If little information is known of the motion-limiting constraints used in experiments, the analysis of the system may yield inaccurate predictions. Here in this work, multiple forcing representations of the impact force are defined and analyzed for a cantilevered pipe that conveys fluid. Depending on the representation of the impact force, the dynamics of the pipe can vary greatly when only the stiffness of the constraints is known from experiments. Three gap sizes of the constraints are analyzed, and the representation of the impact force used to analyze the system is found to significantly affect the response of the pipe at each gap size. An investigation on the effects of the vibro-impact force representation is performed through using basin of attraction analysis and nonlinear characterization of the system’s response.

42 ENGINEERING↗

The Development of a Generalized Riser Flow Regime Map Based Upon Higher Moment and Chaotic Statistics Using Electrical Capacitance Volume Tomography (ECVT)

Dynamic analyses have been applied to the temporal signals from an Electro Capacitance Volume Tomography instrument located near mid-height on the riser of an industrial-scale cold-flow circulating fluidized bed to characterize gas-solids flow behavior in the riser. Twelve capacitance electrodes surround the cylindrical riser over a height of 1.3 m. The instrument used a neural network deconvolution algorithm to determine the spatially resolved solids fraction recorded at 52 Hz. Experiments were carried out over a range of gas and solids flows in the transport regime using a Geldart Group B bed material, high density polyethylene with mean particle size of 880 μm. The radial solids distribution was found to vary from one-time step to the next between profiles typical of laminar and turbulent flow. The duration of time spent in each of these flow profiles depended upon the operating regime – dilute, core-annular, or fast fluidized bed. The chaotic structure of the temporal data was characterized using the three conventional approaches: the first 4 moments from the distribution of signal in time, system memory parameters from the autocorrelation function and the Hurst exponent, and analysis of the correlationentropy and correlation dimension of the attractor. These signal analysis techniques were used to clearly distinguish differences between different transport operating regimes. Specifically, it was experimentally observed that a riser transitions from core annular flow profile to dilute and dense regimes via increasing the frequency of short term transients to either dilute or dense flow profiles, respectively. A regime map was generated based upon these dynamics using solids flux and gas velocity axes. Fast fluidized, core annular, and dilute each exhibited different degree of dynamic characteristics typical of fluid dominated or particle compromising behavior. It should be noted that the magnitude for the different statistics was in the same range regardless of the regime, it was the radial profile for the statistic that changed and subsequently identified that there was a change in the regime. Finally, a reduced regime map was developed consisting of plotting the gas velocity normalized by the upper transport velocity versus the solids flux normalized by the saturation carrying capacity. The use of this reduced plot allowed the data from widely different conditions to be plotted and compared on the same<p>graph. Note that in many instances, some of the statistics identified the operating point as being in one regime while others indicated that it was in another indicating a transition region between dilute or core annular regimes and between the core annular and fast fluidization regimes. This now provides a tool that can be used to optimize process performance, identify changes in operating states, or replicate process dynamics during process scaling or changing operating parameters. </p>

Breault, Ronald↗

Permafrost features on Earth and Mars: Similarities, differences

Typical permafrost features on Earth are polygonal structures, pingos and soli-/gelifluxion features. In areas around the poles and in mountain ranges the precipitation accumulates to inland ice or ice streams. On Mars the same features were identified: polygonal features cover the larger part of the northern lowlands indicating probably an ice wedge-/sand wedge system or desiccation cracks. These features indicate the extend of large mud accumulations which seem to be related to large outflow events of the chaotic terrains. The shore line of this mud accumulation is indicated by a special set of relief types. In some areas large pingo-like hills were identified. In the vicinity of the largest martian volcano, Olympus Mons, the melting of underlying permafrost and/or ground ice led to the downslope sliding of large parts of the primary shield which formed the aureole around Olympus Mons. Glacier-like features are identified along the escarpment which separates the Southern Uplands from the Northern Lowlands.

Joens, H. P.↗

Steady-state dynamic behavior of an auxiliary bearing supported rotor system

This paper investigates the steady-state responses of a rotor system supported by auxiliary bearings in which there is a clearance between the rotor and the inner race of the bearing. A simulation model based upon the rotor of a production jet engine is developed and its steady-state behavior is explored over a wide range of operating conditions for various parametric configurations. Specifically, the influence of rotor imbalance, support stiffness, and damping is studied. It is found that imbalance may change the rotor responses dramatically in terms of frequency contents at certain operating speeds. Subharmonic responses of 2nd order through 10th order are all observed except the 9th order. Chaotic phenomenon is also observed. Jump phenomena (or double-valued responses) of both hard-spring type and soft-spring type are shown to occur at low operating speeds for systems with low auxiliary bearing damping or large clearance even with relatively small imbalance. The effect of friction between the shaft and the inner race of the bearing is also discussed.

Xie, Huajun↗

Cascade Error Projection with Low Bit Weight Quantization for High Order Correlation Data

In this paper, we reinvestigate the solution for chaotic time series prediction problem using neural network approach. The nature of this problem is such that the data sequences are never repeated, but they are rather in chaotic region. However, these data sequences are correlated between past, present, and future data in high order. We use Cascade Error Projection (CEP) learning algorithm to capture the high order correlation between past and present data to predict a future data using limited weight quantization constraints. This will help to predict a future information that will provide us better estimation in time for intelligent control system. In our earlier work, it has been shown that CEP can sufficiently learn 5-8 bit parity problem with 4- or more bits, and color segmentation problem with 7- or more bits of weight quantization. In this paper, we demonstrate that chaotic time series can be learned and generalized well with as low as 4-bit weight quantization using round-off and truncation techniques. The results show that generalization feature will suffer less as more bit weight quantization is available and error surfaces with the round-off technique are more symmetric around zero than error surfaces with the truncation technique. This study suggests that CEP is an implementable learning technique for hardware consideration.

Duong, Tuan A.↗

Terrestrial Planet Growth in Circumbinary Disks

We examine the accu~ulation of terrestrial from circumbinary disks surrounding pairs of stars with masses of either 0.5 solar masses each or 0.8 and 0.2 solar masses and orbital separations of 0.05 AU to 0.4 AU by performing numerical simulations of the late stages of planetary growth. Initial disks contain about 2.6 Earth masses of lunar to Mars-sized bodies orbiting within 2 AU of the center of mass of the system, plus giant planets with masses and orbits analogous to those of Jupiter and Saturn. We also performed simulations using analogous disks orbiting single 1 solar mass stars. The dynamics of planetary growth is quite chaotic because the gravitational perturbations resulting from close approaches greatly amplify differences in orbits. Thus, several simulations of each configuration were run with very slightly different initial conditions to enable us to distinguish systematic effects resulting from differences in the binary orbit (or differences of the initial orbits of the bodies within the disk) from pseudo-random variability in outcomes resulting from chaos. Most runs simulated 200 million years of evolution. At least one terrestrial planet remained at the end of each run; one simulation produced 6 terrestrial planets in a configuration that appears to be quite stable. The systems that formed around stars with binary apastron separations of less than 0.2 AU contained on average slightly more planets than those that formed around single stars, with the outermost planet typically orbiting at a greater distance from the system barycenter. Greater stellar separations tended to result in fewer planets, with the inner planet orbiting farther from the stars. More eccentric binaries have a more pronounced effect for the same apastron distance. The statistical distribution of final systems is not sensitive to moderate differences in the initial eccentricities of the bodies in the disk.

Lissauer, J. J.↗

Krylov complexity in mixed phase space

We investigate the Krylov complexity of thermofield double states in systems with mixed phase space, uncovering a direct correlation with the Brody distribution, which interpolates between Poisson and Wigner statistics. Our analysis spans two-dimensional random matrix models featuring (I) GOE-Poisson and (II) GUE-Poisson transitions and extends to higher-dimensional cases, including a stringy matrix model (GOE-Poisson) and the mass-deformed SYK model (GUE-Poisson). Krylov complexity consistently emerges as a reliable marker of quantum chaos, displaying a characteristic peak in the chaotic regime that gradually diminishes as the Brody parameter approaches zero, signaling a shift toward integrability. These results establish Krylov complexity as a powerful diagnostic of quantum chaos and highlight its interplay with eigenvalue statistics in mixed phase systems.

chaos & nonlinear dynamics↗