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Ion and Electron Acoustic Bursts during Anti-Parallel Reconnection Driven by Lasers
Magnetic reconnection converts magnetic energy into thermal and kinetic energy in plasma. Among the numerous candidate mechanisms, ion acoustic instabilities driven by the relative drift between ions and electrons (or equivalently, electric current) have been suggested to play a critical role in dissipating magnetic energy in collisionless plasmas. However, their existence and effectiveness during reconnection have not been well understood due to ion Landau damping and difficulties in resolving the Debye length scale in the laboratory. We report a sudden onset of ion acoustic bursts measured by collective Thomson scattering in the exhaust of anti-parallel magnetically driven reconnection using high-power lasers. The ion acoustic bursts are followed by electron acoustic bursts with electron heating and bulk acceleration. We reproduce these observations with one- and two-dimensional particle-in-cell simulations in which an electron outflow jet drives ion acoustic instabilities, forming double layers. These layers induce electron two-stream instabilities that generate electron acoustic bursts and energize electrons. Our results demonstrate the importance of ion and electron acoustic dynamics during reconnection when ion Landau damping is ineffective, a condition applicable to a range of astrophysical plasmas including near-Earth space, stellar flares and black hole accretion engines.
GENFIRE: A generalized Fourier iterative reconstruction algorithm for high-resolution 3D imaging
Tomography has made a radical impact on diverse fields ranging from the study of 3D atomic arrangements in matter to the study of human health in medicine. Despite its very diverse applications, the core of tomography remains the same, that is, a mathematical method must be implemented to reconstruct the 3D structure of an object from a number of 2D projections. Here, we present the mathematical implementation of a tomographic algorithm, termed GENeralized Fourier Iterative REconstruction (GENFIRE), for high-resolution 3D reconstruction from a limited number of 2D projections. GENFIRE first assembles a 3D Fourier grid with oversampling and then iterates between real and reciprocal space to search for a global solution that is concurrently consistent with the measured data and general physical constraints. The algorithm requires minimal human intervention and also incorporates angular refinement to reduce the tilt angle error. We demonstrate that GENFIRE can produce superior results relative to several other popular tomographic reconstruction techniques through numerical simulations and by experimentally reconstructing the 3D structure of a porous material and a frozen-hydrated marine cyanobacterium. As a result, equipped with a graphical user interface, GENFIRE is freely available from our website and is expected to find broad applications across different disciplines.
Development of an interpretive simulation tool for the proton radiography technique
Proton radiography is a useful diagnostic of high energy density (HED) plasmas under active theoretical and experimental development. In this paper, we describe a new simulation tool that interacts realistic laser-driven point-like proton sources with three dimensional electromagnetic fields of arbitrary strength and structure and synthesizes the associated high resolution proton radiograph. The present tool’s numerical approach captures all relevant physics effects, including effects related to the formation of caustics. Electromagnetic fields can be imported from particle-in-cell or hydrodynamic codes in a streamlined fashion, and a library of electromagnetic field “primitives” is also provided. This latter capability allows users to add a primitive, modify the field strength, rotate a primitive, and so on, while quickly generating a high resolution radiograph at each step. In this way, our tool enables the user to deconstruct features in a radiograph and interpret them in connection to specific underlying electromagnetic field elements. We show an example application of the tool in connection to experimental observations of the Weibel instability in counterstreaming plasmas, using ∼10{sup 8} particles generated from a realistic laser-driven point-like proton source, imaging fields which cover volumes of ∼10 mm{sup 3}. Insights derived from this application show that the tool can support understanding of HED plasmas.
Thermal interfaces in dynamic compression experiments
Temperature is a difficult thermodynamic variable to measure in dynamic compression experiments. Optical pyrometry is a general-purpose technique for measuring temperature from a radiant surface, but that surface is often the interface between distinct materials with temperatures that vary spatially along the loading direction. This leads to a fundamental problem: how does the measured interface temperature relate to this temperature profile along the compression axis? Numerical analysis of loading history and thermal diffusion at these interfaces shows that seemingly subtle changes in experiment geometry can lead to very different temperature profiles. We compare these results to laboratory temperature measurements of shock-compressed tin.
An Analytic Benchmark for Neutron Boltzmann Transport with Downscattering—Part I: Flux and Eigenvalue Solutions
Computing in the energy dimension is one of the greatest challenges confronting present-day deterministic neutron transport solvers. Accurately resolving the neutron flux as neutrons downscatter across resonances in the nuclear cross sections currently requires considerable computing power and suffers from approximation errors. Flux uncertainty resulting from the uncertainty of the resonance structure is the single-largest cause of reactivity uncertainty. Any additional reference solution for the critical neutron downscattering problem with resonance phenomena would be a boon to verification and validation of neutronics codes. This paper establishes a benchmark to verify the accuracy of neutron transport criticality solvers along the energy dimension. For the first time, the analytic solution of the flux amplitude is derived in the particular case of an infinite homogeneous medium with isotropic scattering in the center of mass and an arbitrary number of no-threshold, neutral particle reaction resonances (e.g., radiative capture, fission, and resonance scattering). Furthermore, original analytic expressions are established to quantify the discrepancy between the ψ k (E) and ψ α (E) flux amplitudes, respective solutions of the multiplication factor k, or the exponential time-evolution frequency α eigenproblems. The physical study of these relations led to analysis of their first-order relative difference near the criticality condition α=0. Finally, numerical solutions are provided to a benchmark problem constituted of the first resonance of 239 Pu, the 6.67-eV resonance of 238 U, and a scattering isotope with a flat cross section, allowing for the computational verification of the energy resolution of current neutron transport criticality codes. Through these novel results, this analytic benchmark can serve as a reference to verify the energy resolution and sensitivity analysis of neutron transport criticality calculations.
MODELING ATMOSPHERIC EMISSION FOR CMB GROUND-BASED OBSERVATIONS
Atmosphere is one of the most important noise sources for ground-based cosmic microwave background (CMB) experiments. By increasing optical loading on the detectors, it amplifies their effective noise, while its fluctuations introduce spatial and temporal correlations between detected signals. We present a physically motivated 3D-model of the atmosphere total intensity emission in the millimeter and sub-millimeter wavelengths. We derive a new analytical estimate for the correlation between detectors time-ordered data as a function of the instrument and survey design, as well as several atmospheric parameters such as wind, relative humidity, temperature and turbulence characteristics. Using an original numerical computation, we examine the effect of each physical parameter on the correlations in the time series of a given experiment. We then use a parametric-likelihood approach to validate the modeling and estimate atmosphere parameters from the polarbear-i project first season data set. We derive a new 1.0% upper limit on the linear polarization fraction of atmospheric emission. We also compare our results to previous studies and weather station measurements. The proposed model can be used for realistic simulations of future ground-based CMB observations.
Synergy of coupled kink and tearing modes in fast ion transport
One aspect of the interaction between fast ions and magnetohydrodynamic (MHD) instabilities is the fast ion transport. Coupled kink and tearing MHD instabilities have also been reported to cause fast ion transport. Recently, the 'kick' model has been developed to compute the evolution of the fast ion distribution from neutral beam injection using instabilities as phase-space resonance sources. Overall, the goal of this paper is to utilize the kick model to understand the physics of fast ion transport caused by the coupled kink and tearing modes. Soft x-ray diagnostics are used to identify the mode parameters in the National Spherical Torus Experiment. The comparison of neutron rates measured and computed from time-dependent TRANSP simulation with the kick model shows that the coupling of kink and tearing mode is important in determination of the fast ion transport. The numerical scan of the mode parameters shows that the relative phase of the kink and tearing modes and the overlapping of kink and tearing mode resonances in the phase space can affect the fast ion transport, suggesting that the synergy of the coupled modes may be causing the fast ion transport.
Strongly coupled dark energy with warm dark matter vs. LCDM
Cosmologies including strongly Coupled (SC) Dark Energy (DE) and Warm dark matter (SCDEW) are based on a conformally invariant (CI) attractor solution modifying the early radiative expansion. Then, aside of radiation, a kinetic field Φ and a DM component account for a stationary fraction, ∼ 1 %, of the total energy. Most SCDEW predictions are hardly distinguishable from LCDM, while SCDEW alleviates quite a few LCDM conceptual problems, as well as its difficulties to meet data below the average galaxy scale. The CI expansion begins at the end of inflation, when Φ (future DE) possibly plays a role in reheating, and ends at the Higgs scale. Afterwards, a number of viable options is open, allowing for the transition from the CI expansion to the present Universe. In this paper: (i) We show how the attractor is recovered when the spin degrees of freedom decreases. (ii) We perform a detailed comparison of CMB anisotropy and polarization spectra for SCDEW and LCDM, including tensor components, finding negligible discrepancies. (iii) Linear spectra exhibit a greater parameter dependence at large k 's, but are still consistent with data for suitable parameter choices. (iv) We also compare previous simulation results with fresh data on galaxy concentration. Finally, (v) we outline numerical difficulties at high k . This motivates a second related paper [1], where such problems are treated in a quantitative way.
Hybrid quantum simulations with qubits and qumodes on trapped-ion platforms
We explore the feasibility of gate-based hybrid quantum computing using both discrete (qubit) and continuous (qumode) variables on trapped-ion platforms. Trapped-ion systems have demonstrated record one- and two-qubit gate fidelities and long qubit coherence times, while qumodes, which can be represented by the collective vibrational modes of the ion chain, have remained relatively unex- plored for their use in computing. Using numerical simulations, we show that high-fidelity hybrid gates and measurement operations can be achieved for existing trapped-ion quantum platforms. As an exemplary application, we consider quantum simulations of the Jaynes-Cummings-Hubbard model, which is given by a one-dimensional chain of interacting spin and boson degrees of free- dom. Using classical simulations, we study its real-time evolution and develop a suitable variational quantum algorithm for ground state preparation. Furthermore, our results motivate further studies of hybrid quantum computing in this context, which may lead to direct applications in condensed matter and fundamental particle and nuclear physics.
Chiral matrix model of the semi-QGP in QCD
Previously, a matrix model of the region near the transition temperature, in the “semi”quark gluon plasma, was developed for the theory of SU(3) gluons without quarks. In this paper we develop a chiral matrix model applicable to QCD by including dynamical quarks with 2+1 flavors. This requires adding a nonet of scalar fields, with both parities, and coupling these to quarks through a Yukawa coupling, y. Treating the scalar fields in mean field approximation, the effective Lagrangian is computed by integrating out quarks to one loop order. As is standard, the potential for the scalar fields is chosen to be symmetric under the flavor symmetry of SU (3) L × SU(3) R × Z (3) A , except for a term linear in the current quark mass, m qk . In addition, at a nonzero temperature T it is necessary to add a new term, ~ m qk T 2 . The parameters of the gluon part of the matrix model are identical to those for the pure glue theory without quarks. The parameters in the chiral matrix model are fixed by the values, at zero temperature, of the pion decay constant and the masses of the pions, kaons, η , and η' . The temperature for the chiral crossover at T$χ$ = 155 MeV is determined by adjusting the Yukawa coupling y . We find reasonable agreement with the results of numerical simulations on the lattice for the pressure and related quantities. In the chiral limit, besides the divergence in the chiral susceptibility there is also a milder divergence in the susceptibility between the Polyakov loop and the chiral order parameter, with critical exponent β $-$ 1 . We compute derivatives with respect to a quark chemical potential to determine the susceptibilities for baryon number, the $χ$ 2n . Especially sensitive tests are provided by $χ$ 4 $-$ $χ$ 2 and by $χ$ 6 , which changes in sign about T$χ$ . In conclusion, the behavior of the susceptibilities in the chiral matrix model strongly suggests that as the temperature increases from T$χ$ , that the transition to deconfinement is significantly quicker than indicated by the measurements of the (renormalized) Polyakov loop on the lattice.
Using kernel-based statistical distance to study the dynamics of charged particle beams in particle-based simulation codes
Measures of discrepancy between probability distributions (statistical distance) are widely used in the fields of artificial intelligence and machine learning. We describe how certain measures of statistical distance can be implemented as numerical diagnostics for simulations involving charged-particle beams. Related measures of statistical dependence are also described. The resulting diagnostics provide sensitive measures of dynamical processes important for beams in nonlinear or high-intensity systems, which are otherwise difficult to characterize. Here, the focus is on kernel-based methods such as maximum mean discrepancy, which have a well-developed mathematical foundation and reasonable computational complexity. Several benchmark problems and examples involving intense beams are discussed. While the focus is on charged-particle beams, these methods may also be applied to other many-body systems such as plasmas or gravitational systems.
MO-DE-207A-10: One-Step CT Reconstruction for Metal Artifact Reduction by a Modification of Penalized Weighted Least-Squares (PWLS)
Purpose: Metal objects create severe artifacts in kilo-voltage (kV) CT image reconstructions due to the high attenuation coefficients of high atomic number objects. Most of the techniques devised to reduce this artifact utilize a two-step approach, which do not reliably yield the qualified reconstructed images. Thus, for accuracy and simplicity, this work presents a one-step reconstruction method based on a modified penalized weighted least-squares (PWLS) technique. Methods: Existing techniques for metal artifact reduction mostly adopt a two-step approach, which conduct additional reconstruction with the modified projection data from the initial reconstruction. This procedure does not consistently perform well due to the uncertainties in manipulating the metal-contaminated projection data by thresholding and linear interpolation. This study proposes a one-step reconstruction process using a new PWLS operation with total-variation (TV) minimization, while not manipulating the projection. The PWLS for CT reconstruction has been investigated using a pre-defined weight, based on the variance of the projection datum at each detector bin. It works well when reconstructing CT images from metal-free projection data, which does not appropriately penalize metal-contaminated projection data. The proposed work defines the weight at each projection element under the assumption of a Poisson random variable. This small modification using element-wise penalization has a large impact in reducing metal artifacts. For evaluation, the proposed technique was assessed with two noisy, metal-contaminated digital phantoms, against the existing PWLS with TV minimization and the two-step approach. Result: The proposed PWLS with TV minimization greatly improved the metal artifact reduction, relative to the other techniques, by watching the results. Numerically, the new approach lowered the normalized root-mean-square error about 30 and 60% for the two cases, respectively, compared to the two-step method. Conclusion: A new PWLS operation shows promise for improving metal artifact reduction in CT imaging, as well as simplifying the reconstructing procedure.
Optical Tomograms of Multiple-Photon-Added Gaussian States via the Intermediate State Representation Theory
Optical tomogram of a quantum state can serve as an alternative to its density matrix since it contains all the information on this state. In this paper we use the explicit expression of the intermediate state |q, f, g〉(that is, an eigenvector of the coordinate and momentum operator fQ + gP) and the Radon transform between the Wigner operator Δ(p, q) and the pure-state density operator |q, f, g〉〈q, f, g| to calculate the specific tomograms for multiple-photon-added coherent states (MPACSs), thermal states (MPATSs) and displaced thermal states (MPADTSs). Their analytical tomograms are actually the finite-summation representations related to single-variable Hermite polynomials. Besides, the numerical results indicate that the larger photon-addition number can lead to the multi-peak tomographic distributions for these three states, and the measurable tomograms of MPACSs and MPADTSs exhibit π-periodic features but MPATSs can’t.
Multilevel Sequential Monte Carlo Samplers for Normalizing Constants
This article considers the sequential Monte Carlo (SMC) approximation of ratios of normalizing constants associated to posterior distributions which in principle rely on continuum models. Therefore, the Monte Carlo estimation error and the discrete approximation error must be balanced. A multilevel strategy is utilized to substantially reduce the cost to obtain a given error level in the approximation as compared to standard estimators. Two estimators are considered and relative variance bounds are given. The theoretical results are numerically illustrated for two Bayesian inverse problems arising from elliptic partial differential equations (PDEs). The examples involve the inversion of observations of the solution of (i) a 1-dimensional Poisson equation to infer the diffusion coefficient, and (ii) a 2-dimensional Poisson equation to infer the external forcing.
Constructing Neural Network Based Models for Simulating Dynamical Systems
Dynamical systems see widespread use in natural sciences like physics, biology, and chemistry, as well as engineering disciplines such as circuit analysis, computational fluid dynamics, and control. For simple systems, the differential equations governing the dynamics can be derived by applying fundamental physical laws. However, for more complex systems, this approach becomes exceedingly difficult. Data-driven modeling is an alternative paradigm that seeks to learn an approximation of the dynamics of a system using observations of the true system. In recent years, there has been an increased interest in applying data-driven modeling techniques to solve a wide range of problems in physics and engineering. Here this article provides a survey of the different ways to construct models of dynamical systems using neural networks. In addition to the basic overview, we review the related literature and outline the most significant challenges from numerical simulations that this modeling paradigm must overcome. Based on the reviewed literature and identified challenges, we provide a discussion on promising research areas.
Synergy of Coupled Kink and Tearing Modes in Fast Ion Transport
One aspect of the interaction between fast ions and magnetohydrodynamic (MHD) instabilities is the fast ion transport. Coupled kink and tearing MHD instabilities have also been reported to cause fast ion transport. Recently, the ''kick" model has been developed to compute the evolution of the fast ion distribution from the neutral beam injection using instabilities as phase space resonance sources. The goal of this paper is to utilize the kick model to understand the physics of fast ion transport caused by the coupled kink and tearing modes. Soft X-ray diagnostics are used to identify the mode parameters in NSTX. The comparison of neutron rates measured and computed from time-dependent TRANSP simulation with the kick model shows the coupling of kink and tearing mode is important in determination of the fast ion transport. The numerical scan of the mode parameters shows that the relative phase of the kink and tearing modes and the overlapping of kink and tearing mode resonances in the phase space can affect the fast ion transport, suggesting that the synergy of the coupled modes may be causing the fast ion transpor