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At least 109 records · Page 6

Interplay of quantum information, thermodynamics, and gravity in the early Universe

Our interdisciplinary proposal brought together a unique team of researchers to tackle foundational questions on the quantum origins of the Universe and out-of-equilibrium quantum systems in general. The specific goals of our proposal were as follows. First, to develop a self-consistent quantum mechanical framework for the early Universe using an open system approach, with focus on non-Markovian vs. Markovian evolution of system modes and signatures in late-time observables. Second, to explore the use of quantum resource theory and thermodynamics techniques to understand the initial conditions of the Universe. Third, to in vestigate open quantum system dynamics in strongly-coupled qubit and oscillator systems, with focus on non-Markovian evolution, entanglement dynamics, and quantum backaction, including experimental real izations and implications for gravity. And fourth, to establish thermodynamics for chaotic quantum systems, with emphasis on dynamics of information scrambling and implications for black hole solutions in AdS/CFT and quantum gravity.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Newton versus the machine: solving the chaotic three-body problem using deep neural networks

ABSTRACT Since its formulation by Sir Isaac Newton, the problem of solving the equations of motion for three bodies under their own gravitational force has remained practically unsolved. Currently, the solution for a given initialization can only be found by performing laborious iterative calculations that have unpredictable and potentially infinite computational cost, due to the system’s chaotic nature. We show that an ensemble of converged solutions for the planar chaotic three-body problem obtained using an arbitrarily precise numerical integrator can be used to train a deep artificial neural network (ANN) that, over a bounded time interval, provides accurate solutions at a fixed computational cost and up to 100 million times faster than the numerical integrator. In addition, we demonstrate the importance of training an ANN using converged solutions from an arbitrary precise integrator, relative to solutions computed by a conventional fixed precision integrator, which can introduce errors in the training data, due to numerical round-off and time discretization, that are learned by the ANN. Our results provide evidence that, for computationally challenging regions of phase space, a trained ANN can replace existing numerical solvers, enabling fast and scalable simulations of many-body systems to shed light on outstanding phenomena such as the formation of black hole binary systems or the origin of the core collapse in dense star clusters.

Breen, Philip G.↗

Reservoir Computing as a Tool for Climate Predictability Studies

Reduced-order dynamical models play a central role in developing our understanding of predictability of climate irrespective of whether we are dealing with the actual climate system or surrogate climate models. In this context, the linear inverse modeling (LIM) approach, by capturing a few essential interactions between dynamical components of the full system, has proven valuable in providing insights into predictability of the full system. We demonstrate that reservoir computing (RC), a form of learning suitable for systems with chaotic dynamics, provides an alternative nonlinear approach that improves on the predictive skill of the LIM approach. We do this in the example setting of predicting sea surface temperature in the North Atlantic in the preindustrial control simulation of a popular earth system model, the Community Earth System Model so that we can compare the performance of the new RC-based approach with the traditional LIM approach both when learning data are plentiful and when such data are more limited. The improved predictive skill of the RC approach over a wide range of conditions—larger number of retained EOF coefficients, extending well into the limited data regime, etc.—suggests that this machine-learning technique may have a use in climate predictability studies. While the possibility of developing a climate emulator—the ability to continue the evolution of the system on the attractor long after failing to be able to track the reference trajectory—is demonstrated in the Lorenz-63 system, it is suggested that further development of the RC approach may permit such uses of the new approach in more realistic predictability studies.

54 ENVIRONMENTAL SCIENCES↗

Probable Disastrous Consequences of Collision Between Unknown Small (100 m) Asteroids with Known (Approximately 1 km) Near Earth Orbiting (NEO) Asteroids

The long-term stability of the Solar System is not well understood. Ironically its stability is taken for granted even though our knowledge of all the constituents [comets, asteroids. (The Asteroid Belt between Mars and Jupiter, Trojan Asteroids, Kuiper belt, Ort Cloud), planetoids, planets, moons, etc], and its long-term dynamics cannot be easily computed. At best one might say that the solar system is chaotic, but much of the time it seems to exists near a quasi-stationary state. An asteroid that passes near the Earth regularly returns with clock-like precision. Taking into account every known detail of its path through the solar system, its orbit is calculated forward thousands of years with no untoward calamity on the horizon. And then one day, this passive visitor slams into the Earth during a sunny afternoon picnic! Can this happen? Unfortunately, this is a real possibility in the ordinary history of the solar system. In fact our knowledge of the solar system in the small is sketchy, as will be pointed out. Events, which lie outside our awareness, can precipitate disasters that we may perceive when it's too late to launch effective counter measures. In this work, one such scenario is described and the direct consequences for the Earth are calculated.

Smalley, Larry↗

NASA's Seasonal-to-Interannual Prediction Project: In Partnership With the NCCS

Researchers with NASA's Season-to-Interannual Prediction Project (NSIPP) refer to different types of memory when running models on NCCS computers: the computer memory required for their models and the memory of the atmosphere or the ocean. Because of the atmosphere's chaotic nature, its memory is short. For weather predictions, the initial information taken from atmospheric observations has a limited useful life. Currently, there is no way to take observations, initialize an atmosphere model, integrate ahead in time, and make an accurate weather forecast beyond about 2 weeks. After that, the system becomes chaotic. What conditions could be used to make predictions beyond 2 weeks? If not conditions in the atmosphere, then the memory must be found somewhere else. That place is in the oceans. Although most changes in the atmosphere vary on a short timescale, the weather being a prime example, some important large atmospheric climate variations occur over much longer timescales-month s, years, or decades. NSIPP is interested specifically in those phenomena that occur over timescales of several months to a few years, and the El Nino Southern Oscillation (ENSO) is the most significant of these.

Source record↗

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↗

Matrix ensembles with global symmetries and ’t Hooft anomalies from 2d gauge theory

The Hilbert space of a quantum system with internal global symmetry $\textit{G}$ decomposes into sectors labelled by irreducible representations of $\textit{G}$. If the system is chaotic, the energies in each sector should separately resemble ordinary random matrix theory. We show that such “sector-wise” random matrix ensembles arise as the boundary dual of two- dimensional gravity with a $\textit{G}$ gauge field in the bulk. Within each sector, the eigenvalue density is enhanced by a nontrivial factor of the dimension of the representation, and the ground state energy is determined by the quadratic Casimir. We study the consequences of ’t Hooft anomalies in the matrix ensembles, which are incorporated by adding specific topological terms to the gauge theory action. The effect is to introduce projective representations into the decomposition of the Hilbert space. Finally, we consider ensembles with $\textit{G}$ symmetry and time reversal symmetry, and analyze a simple case of a mixed anomaly between time reversal and an internal $\mathbb{Z}$ 2 symmetry.

2D Gravity↗

Guiding center and gyrokinetic orbit theory for large electric field gradients and strong shear flows

The guiding center and gyrokinetic theory of magnetized particle motion is extended to the regime of large electric field gradients perpendicular to the magnetic field. A gradient in the electric field directly modifies the oscillation frequency and causes the Larmor orbits to deform from circular to elliptical trajectories. In order to retain a good adiabatic invariant, there can only be strong dependence on a single coordinate at lowest order, so that resonances do not generate chaotic motion that destroys the invariant. When the gradient across magnetic flux surfaces is dominant, the guiding center drift velocity becomes anisotropic in response to external forces and additional curvature drifts must be included. The electric polarization density remains gyrotropic, but both the polarization and magnetization are modified by the change in gyrofrequency. The theory can be applied to shear flows that are even stronger than those observed in the edge transport barrier of a high-performance tokamak (H-mode) pedestal, even if the toroidal field is as small as or even smaller than the poloidal field. Yet, the theory retains a mathematical form that is similar to the standard case and can readily be implemented within existing simulation tools.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

How Hall electric fields intrinsically chaotize and heat ions during collisionless magnetic reconnection

The origin of extreme and anomalous ion heating during magnetic reconnection has been a longstanding mystery. It is shown in this paper that, at the core of the process, the stochastic heating mechanism is responsible for this energization. The in-plane Hall electric fields that intrinsically develop during collisionless reconnection not only accelerate ions, but also thermalize them by inducing chaotic motion. The mechanism explains various observed features of ion heating, e.g., its relation to the guide field strength and the ion mass-to-charge ratio.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Subexponential Decay of Local Correlations from Diffusion-Limited Dephasing

Chaotic quantum systems at finite entropy density are expected to act as their own heat baths, rapidly dephasing local quantum superpositions. Here, we argue that in fact this dephasing is generically subexponential in one-dimensional systems with conservation laws: all local correlation functions decay as exp⁡[−𝒪⁡(𝑡 𝛼 )] with 0 ≤ 𝛼 ≤ 2/3, even when the operators are orthogonal to all hydrodynamic modes. The mechanism is diffusion-limited dephasing, in which rare low-entropy regions (“voids”) protect quantum coherences. This intrinsically quantum effect lies beyond standard hydrodynamics and disappears under extrinsic dephasing. In random charge-conserving circuits we find 𝛼 = 1/2, while in generic translation-invariant Floquet systems we bound 𝛼 ≤ 2/3. Our arguments are general, subject principally to the assumption that thermal fluctuations can create regions of zero entropy density. In systems with energy conservation, this assumption is automatically satisfied because of the third law of thermodynamics.

information scrambling↗

Origin and limit of the recovery of damaged information by time reversal

Recently it was found that scrambled information can be partially recovered by a time-reversed evolution, even after being damaged by an intruder. Here we reconsider the origin of the information recovery, and argue that the presence of classical chaos does not preclude it and only leads to a quantitative reduction of the recovery ratio. We also show how decoherence (i.e., entanglement with the intruder) limits the recovery, by proving an upper bound on the recovery ratio in terms of the entangling power of the intruder's action.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Full Counting Statistics of Charge in Chaotic Many-Body Quantum Systems

We investigate the full counting statistics of charge transport in U(1)-symmetric random unitary circuits. We consider an initial mixed state prepared with a chemical potential imbalance between the left and right halves of the system and study the fluctuations of the charge transferred across the central bond in typical circuits. Using an effective replica statistical mechanics model and a mapping onto an emergent classical stochastic process valid at large on-site Hilbert space dimension, we show that charge transfer fluctuations approach those of the symmetric exclusion process at long times, with subleading t –1/2 quantum corrections. Here, we discuss our results in the context of fluctuating hydrodynamics and macroscopic fluctuation theory of classical nonequilibrium systems and check our predictions against direct matrix-product state calculations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Computing nuclear response functions with time-dependent coupled-cluster theory

We compute nuclear response functions by solving the time-dependent 𝐴-body Schrödinger equation, recording the time-dependent transition moment and extracting spectral information via Fourier transforms. The solution of the time-dependent many-body problem accounts for correlations on top of the mean field by taking advantage of a time-dependent formulation of coupled-cluster theory. As a validation, we focus on electric dipole transitions in 4 He and 16 O and compare moments of the response function distribution to the results of an equivalent static framework, finding negligible discrepancies. We investigate how proton and neutron densities evolve in time, and we see the traditional picture of soft and giant dipole resonances as collective oscillations of protons and neutrons emerging from our calculations in 16 O and 24 O. Furthermore, this method also allows us to investigate the behavior of the nucleus in the presence of a strong electric field. In that regime, the behavior of the system becomes chaotic. Qualitatively, the spectral information obtained in this limit is in line with previous time-dependent mean-field results.

Ab initio calculations↗

Sea Height Information from Complex SAR Data

Synthetic aperture radar data was used to construct an estimation algorithm for development of information on long waves. The evolution of chaotic dynamic systems was also explored.

Harger, R. O.↗

Discretization chaos - Feedback control and transition to chaos

Problems in the design of feedback controllers for chaotic dynamical systems are considered theoretically, focusing on two cases where chaos arises only when a nonchaotic continuous-time system is discretized into a simpler discrete-time systems (exponential discretization and pseudo-Euler integration applied to Lotka-Volterra competition and prey-predator systems). Numerical simulation results are presented in extensive graphs and discussed in detail. It is concluded that care must be taken in applying standard dynamical-systems methods to control systems that may be discontinuous or nondifferentiable.

Grantham, Walter J.↗

AMPTE/CCE and SCATHA simultaneous observations of magnetic signatures associated with a substorm onset

Magnetic field signatures associated with a substorm onset event are examined by making use of simultaneous observations from the Active Magnetosphere Particle Tracer Explorer (AMPTE)/Charge Composition Explorer (CCE) and Spacecraft Charging AT High Altitude (SCATHA). The observations of the two satellites are discussed in relation to their differences and the relative positions of the satellites. Despite the small separation between the satellites, AMPTE/CCE observed the start of irregular magnetic field fluctuations a few tens of seconds earlier than SCATHA, indicating that the CCE was within, or closer to, the onset region. It was found that the amplitude of the fluctuations was largest in the north-south component. The results indicate that the magnetic field fluctuations were excited locally and the coherence length was less than a multiple of Larmor radius of thermal protons. It is suggested that the tail current disruption is described as a system of chaotic filamentary electric currents which flow in various directions, but preferentially anti-parallel to the cross-tail current, and that ions play an important role in the triggering of the tail current disruption.

Ohtani, S.↗

Computing Halo Orbits In Bicircular Model Using Energy Balancing Method

The orbits around the Lagrange points L1 and L2 of the Sun-Earth-Moon system are chaotic and unstable by nature. In this work, we describe a simple method to control Halo Orbits with a single maneuver at the XZ-plane crossing for each revolution of the orbit in the Bicircular Problem. Examples of up to 500 revolutions of the Halo Orbit are controlled using this method. With optimization and adjustment of the maneuver design, the 𝚫V can be significantly reduced. The simplicity of the method and the infrequency of the maneuvers make this a good candidate for future autonomous control of libration orbits.

Lo, Martin W.↗

Modelling chaotic vibrations using NASTRAN

Due to the unavailability and, later, prohibitive cost of the computational power required, many phenomena in nonlinear dynamic systems have in the past been addressed in terms of linear systems. Linear systems respond to periodic inputs with periodic outputs, and may be characterized in the time domain or in the frequency domain as convenient. Reduction to the frequency domain is frequently desireable to reduce the amount of computation required for solution. Nonlinear systems are only soluble in the time domain, and may exhibit a time history which is extremely sensitive to initial conditions. Such systems are termed chaotic. Dynamic buckling, aeroelasticity, fatigue analysis, control systems and electromechanical actuators are among the areas where chaotic vibrations have been observed. Direct transient analysis over a long time period presents a ready means of simulating the behavior of self-excited or externally excited nonlinear systems for a range of experimental parameters, either to characterize chaotic behavior for development of load spectra, or to define its envelope and preclude its occurrence.

Sheerer, T. J.↗