Full Distribution Function Research Articles

J-PLUS: Bayesian object classification with a strum of BANNJOS

Context. With its 12 optical filters, the Javalambre-Photometric Local Universe Survey (J-PLUS) provides an unprecedented multicolor view of the local Universe. The third data release (DR3) covers 3192 deg2 and contains 47.4 million objects. However, the classification algorithms currently implemented in the J-PLUS pipeline are deterministic and based solely on the morphology of the sources. Aims. Our goal is to classify the sources identified in the J-PLUS DR3 images as stars, quasi-stellar objects (QSOs), or galaxies. For this task, we present BANNJOS, a machine learning pipeline that utilizes Bayesian neural networks to provide the full probability distribution function (PDF) of the classification. Methods. BANNJOS has been trained on photometric, astrometric, and morphological data from J-PLUS DR3, Gaia DR3, and CatWISE2020, using over 1.2 million objects with spectroscopic classification from SDSS DR18, LAMOST DR9, the DESI Early Data Release, and Gaia DR3. Results were validated on a test set of about 1.4 × 105 objects and cross-checked against theoretical model predictions. Results. BANNJOS outperforms all previous classifiers in terms of accuracy, precision, and completeness across the entire magnitude range. It delivers over 95% accuracy for objects brighter than r = 21.5 mag and ~ 90% accuracy for those up to r = 22 mag, where J-PLUS completeness is ≲ 25%. BANNJOS is also the first object classifier to provide the full PDF of the classification, enabling precise object selection for high purity or completeness, and for identifying objects with complex features, such as active galactic nuclei with resolved host galaxies. Conclusions. BANNJOS effectively classified J-PLUS sources into around 20 million galaxies, one million QSOs, and 26 million stars, with full PDFs for each, which allow for later refinement of the sample. The upcoming J-PAS survey, with its 56 color bands, will further enhance BANNJOS’s ability to detail the nature of each source.

Far-from-equilibrium attractors with full relativistic Boltzmann approach in boost-invariant and non-boost-invariant systems

We study the universal behavior associated with a Relativistic Boltzmann Transport (RBT) approach with the full collision integral in 0+1D conformal systems. We show that all momentum moments of the distribution function exhibit universal behavior. Furthermore, the RBT approach allows to calculate the full distribution function, showing that an attractor behavior is present in both the longitudinal and transverse momentum dependence. We compare our results to the far-from-equilibrium attractors determined with other approaches, such as kinetic theory in Relaxation Time Approximation (RTA) and relativistic hydrodynamic theories, both in their viscous (DNMR) an anisotropic (aHydro) formulations, finding a very similar evolution, but an even faster thermalization in RBT for higher order moments. For the first time, we extended this analysis also to study the attractor behavior under a temperature-dependent viscosity η/s(T)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\eta /s(T)$$\\end{document}, accounting also for the rapid increase toward the hadronic phase. We find that a partial breaking of the scaling behavior with respect to τ/τeq\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ au /\ au _{eq}$$\\end{document} emerges only at T≈Tc\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$T \\approx T_c$$\\end{document} generating a transient deviation from attractors; interestingly this in realistic finite systems may occur around the freeze-out dynamics. Finally, we investigate for the first time results beyond the boost-invariant picture, finding that also in such a case the system evolves toward the universal attractor. In particular, we present the forward and pull-back attractors at different space-time rapidities including rapidity regions where initially the distribution function is even vanishing.

Thermalization of long range Ising model in different dynamical regimes: A full counting statistics approach

We study the thermalization of the transverse field Ising chain with a power law decaying interaction \sim 1/r^{\alpha}∼1/rα following a global quantum quench of the transverse field in two different dynamical regimes. The thermalization behavior is quantified by comparing the full probability distribution function (PDF) of the evolving states with the corresponding thermal state given by the canonical Gibbs ensemble (CGE). To this end, we used the matrix product state (MPS)-based Time Dependent Variational Principle (TDVP) algorithm to simulate both real time evolution following a global quantum quench and the finite temperature density operator. We observe that thermalization is strongly suppressed in the region with strong confinement for all interaction strengths \alphaα, whereas thermalization occurs in the region with weak confinement.

Linear statistics for Coulomb gases: higher order cumulants

We consider N classical particles interacting via the Coulomb potential in spatial dimension d and in the presence of an external trap, at equilibrium at inverse temperature β. In the large N limit, the particles are confined within a droplet of finite size. We study smooth linear statistics, i.e. the fluctuations of sums of the form LN=∑i=1Nf(xi) , where x i ’s are the positions of the particles and where f(xi) is a sufficiently regular function. There exists at present standard results for the first and second moments of LN in the large N limit, as well as associated Central Limit Theorems in general dimension and for a wide class of confining potentials. Here we obtain explicit expressions for the higher order cumulants of LN at large N, when the function f(x)=f(|x|) and the confining potential are both rotationnally invariant. A remarkable feature of our results is that these higher cumulants depend only on the value of f′(|x|) and its higher order derivatives evaluated exactly at the boundary of the droplet, which in this case is a d-dimensional sphere. In the particular two-dimensional case d = 2 at the special value β = 2, a connection to the Ginibre ensemble allows us to derive these results in an alternative way using the tools of determinantal point processes. Finally we also obtain the large deviation form of the full probability distribution function of LN .

Exploring the non-Gaussianity of the cosmic infrared background and its weak gravitational lensing

ABSTRACT Gravitational lensing deflects the paths of photons, altering the statistics of cosmic backgrounds and distorting their information content. We take the cosmic infrared background (CIB), which provides plentiful information about galaxy formation and evolution, as an example to probe the effect of lensing on non-Gaussian statistics. Using the Websky simulations, we first quantify the non-Gaussianity of the CIB, revealing additional detail on top of its well-measured power spectrum. To achieve this, we use needlet-like multipole-band filters to calculate the variance and higher-point correlations. Using our simulations, we show the two-, three- and four-point spectra, and compare our calculated power spectra and bispectra to Planck values. We then lens the CIB, shell-by-shell with corresponding convergence maps, to capture the broad redshift extent of both the CIB and its lensing convergence. The lensing of the CIB changes the three- and four-point functions by a few tens of per cent at large scales, unlike with the power spectrum, which changes by less than two per cent. We expand our analyses to encompass the full intensity probability distribution functions (PDFs) involving all n-point correlations as a function of scale. In particular, we use the relative entropy between lensed and unlensed PDFs to create a spectrum of templates that can allow estimation of lensing. The underlying CIB model is missing the important role of star bursting, which we test by adding a stochastic lognormal term to the intensity distributions. The novel aspects of our filtering and lensing pipeline should prove useful for any radiant background, including line intensity maps.

Challenges in molecular dynamics simulations of heat exchange statistics.

We study heat exchange in temperature-biased metal-molecule-metal molecular junctions by employing the molecular dynamics simulator LAMMPS. Generating the nonequilibrium steady state with Langevin thermostats at the boundaries of the junction, we show that the average heat current across a gold-alkanedithiol-gold nanojunction behaves physically, with the thermal conductance value matching the literature. In contrast, the full probability distribution function for heat exchange, as generated by the simulator, violates the fundamental fluctuation symmetry for entropy production. We trace this failure back to the implementation of the thermostats and the expression used to calculate the heat exchange. To rectify this issue and produce the correct statistics, we introduce single-atom thermostats as an alternative to conventional many-atom thermostats. Once averaging heat exchange over the hot and cold thermostats, this approach successfully generates the correct probability distribution function, which we use to study the behavior of both the average heat current and its noise. We further examine the thermodynamic uncertainty relation in the molecular junction and show that it holds, albeit demonstrating nontrivial trends. Our study points to the need to carefully implement nonequilibrium molecular dynamics solvers in atomistic simulation software tools for future investigations of noise phenomena in thermal transport.

Non-trace full-F gyro-fluid interchange impurity advection

A full-F isothermal gyro-fluid model and code (which is based on the full distribution function F compared to only small fluctuations) is extended to handle self-consistent coupling of multiple quasi-neutral ion species via the polarisation equation in the long wavelength approximation. The numerical model is used to determine two-dimensional interchange driven ‘blob’ transport in a plasma with intrinsic impurity content for a range of impurity parameters. With the same model, the self-consistent advective interaction of a main plasma species blob with a non-trace impurity cloud is studied. For homogeneous impurity distributions an increased effective mass reduces blob transport, whereas it is found that localised impurity clouds can lead either to acceleration or slowing down of blob propagation depending on the alignment of the impurity density gradient during the acceleration phase of the main ion species blob.

Kinetic interpretation of the classical Rayleigh-Taylor instability.

Rayleigh-Taylor (RT) instabilities are prevalent in many physical regimes ranging from astrophysical to laboratory plasmas and have primarily been studied using fluid models, the majority of which have been ideal fluid models. This work presents a five-dimensional (two spatial dimensions, three velocity space dimensions) simulation using the continuum-kinetic model to study the effect of the collisional mean free path and transport on the instability growth. The continuum-kinetic model provides noise-free access to the full particle distribution function permitting a detailed investigation of the role of kinetic physics in hydrodynamic phenomena such as the RT instability. For long mean free path, there is no RT instability growth, but as collisionality increases, particles relax towards the Maxwellian velocity distribution, and the kinetic simulations reproduce the fluid simulation results. An important and novel contribution of this work is in the intermediate collisional cases that are not accessible with traditional fluid models and require kinetic modeling. Simulations of intermediate collisional cases show that the RT instability evolution is significantly altered compared to the highly collisional fluidlike cases. Specifically, the growth rate of the intermediate collisionality RT instability is lower than the high collisionality case while also producing a significantly more diffused interface. The higher moments of the distribution function play a more significant role relative to inertial terms for intermediate collisionality during the evolution of the RT instability interface. Particle energy flux is calculated from moments of the distribution and shows that transport is significantly altered in the intermediate collisional case and deviates much more so from the high collisionality limit of the fluid regime.

Localization and Delocalization in Solids from Electron Distribution Functions.

The extent of electron localization and delocalization in molecular and condensed phases has been the subject of intense scrutiny over the years. In Chemistry, where real, instead of momentum space viewpoints are many times closer to intuition, a plethora of localization descriptors exist, including a family of indices invariant under orbital transformations that rely only on an underlying partition of the physical space into meaningful regions. These localization and delocalization indices measure the fluctuation of the electron population contained in such domains, and have been rigorously related to the insulating or conductive character of extended systems. Knowledge of the full electron population probability distribution function is also available in molecules, where it has provided many meaningful results as well as uncovered exotic interaction regimes in excited states. Electron distribution functions (EDFs), which can be seen as real space analogs of Pauling resonance structures, are now reported in periodic systems. In agreement with what is known in finite systems, ionic compounds display narrow EDFs that get wider as covalency sets in. Contrarily to conventional wisdom, most electrons delocalize over their nearest neighbors, even in quasi electron-gas metals like sodium, and it is only in the decay rate of the probability distribution where conductors and insulators can be distinguished.

Prediction Markets for Probabilistic Forecasting of Renewable Energy Sources

This paper demonstrates how a binary prediction market is capable of achieving a probabilistic renewable energy forecast. In prediction markets, participants trade shares associated with the outcome of unknown future events (here, the renewable production, as a random variable), and the instantaneous price of shares represents the probability of the outcome. The focus of this study is to exploit this informational value of the prediction market price in renewable energy forecasting. To this end, in this paper three different methods of renewable probabilistic forecasting have been considered as the trading agents in a binary prediction market, the aggregated probability of the renewable output is elicited from the equilibrium price in this market and finally, the full cumulative distribution function of possible renewable output is extracted through regression analysis. The proposed method is applied to the test cases of three onshore wind farms in Australia. The simulation results suggest that the performance of the proposed method is superior to the individual models and forecasting is improved in terms of reduction in the electricity market imbalance costs.

A Conditional Autoencoder for Galaxy Photometric Parameter Estimation

Astronomical photometric surveys routinely image billions of galaxies, and traditionally infer the parameters of a parametric model for each galaxy. This approach has served us well, but the computational expense of deriving a full posterior probability distribution function is a challenge for increasingly ambitious surveys. In this paper, we use deep learning methods to characterize galaxy images, training a conditional autoencoder on mock data. The autoencoder can reconstruct and denoise galaxy images via a latent space engineered to include semantically meaningful parameters, such as brightness, location, size, and shape. Our model recovers galaxy fluxes and shapes on mock data with a lower variance than the Hyper Suprime-Cam photometry pipeline, and returns reasonable answers even for inputs outside the range of its training data. When applied to data in the training range, the regression errors on all extracted parameters are nearly unbiased with a variance near the Cramr-Rao bound.

Orbit tomography of energetic particle distribution functions

Both fast ions and runaway electrons are described by distribution functions, the understanding of which are of critical importance for the success of future fusion devices such as ITER. Typically, energetic particle diagnostics are only sensitive to a limited subsection of the energetic particle phase-space which is often insufficient for model validation. However, previous publications show that multiple measurements of a single spatially localized volume can be used to reconstruct a distribution function of the energetic particle velocity-space by using the diagnostics’ velocity-space weight functions, i.e. velocity-space Tomography. In this work we use the recently formulated orbit weight functions to remove the restriction of spatially localized measurements and present orbit tomography, which is used to reconstruct the 3D phase-space distribution of all energetic particle orbits in the plasma. Through a transformation of the orbit distribution, the full energetic particle distribution function can be determined in the standard {energy, pitch, r, z}-space. We benchmark the technique by reconstructing the fast-ion distribution function of an MHD-quiescent DIII-D discharge using synthetic and experimental FIDA measurements. We also use the method to study the redistribution of fast ions during a sawtooth crash at ASDEX upgrade using FIDA measurements. Finally, a comparison between the orbit tomography and velocity-space tomography is shown.

Statistics of the Effective Massive MIMO Channel in Correlated Rician Fading

Massive multiple-input multiple-output base stations use multiple spatial diversity branches, which are often assumed to be uncorrelated in theoretical work. Correlated branches are seldom considered since they are mathematically less tractable. For correlated Rician fading, only the first- and second-order moments have been explored. To describe propagation environments more accurately, full distribution functions are needed. This manuscript provides distribution functions for the maximum ratio combining effective channel, a quadratic form of a random complex normal channel vector. Its mean vector and covariance matrix are based on a plane wave model incorporating array geometry, antenna element pattern, power angular spectra and power delay profiles. Closed-form approximations of the distribution functions are presented, to allow the fast evaluation of many real-world scenarios. The statistical framework is used to show that low-directivity antenna elements provide better performance in angular constricted Rician fading with off-axis incidence than high-directivity elements. Moreover, two base station array layouts are compared, showing that a half-circle array illuminates a cell more evenly than a uniform linear array. With the full distribution functions available, performance can be compared over the full range of received powers and not only based on the average signal-to-noise ratio.

Ultra-slow-roll inflation with quantum diffusion

We consider the effect of quantum diffusion on the dynamics of the inflaton during a period of ultra-slow-roll inflation. We extend the stochastic-δ\U0001d4a9 formalism to the ultra-slow-roll regime and show how this system can be solved analytically in both the classical-drift and quantum-diffusion dominated limits.By deriving the characteristic function, we are able to construct the full probability distribution function for the primordial density field. In the diffusion-dominated limit, we recover an exponential tail for the probability distribution, as found previously in slow-roll inflation.To complement these analytical techniques, we present numerical results found both by very large numbers of simulations of the Langevin equations, and through a new, more efficient approach based on iterative Volterra integrals.We illustrate these techniques with two examples of potentials that exhibit an ultra-slow-roll phase leading to the possible production of primordial black holes.

Mitigating the Noise-source Coupling Effect in Shear Measurement

Abstract Subpercent level accuracy in shear measurement is required by the Stage-IV weak lensing surveys. One important challenge is suppressing the shear bias on source images of low signal-to-noise ratios (S/N ≲ 10). Previously, it has been demonstrated that the shear estimators defined in the Fourier_Quad (FQ) method can achieve subpercent accuracy at the very faint end (S/N ≲ 5) through ensemble averaging. Later, it was found that we can approach the minimum statistical error (the Cramer–Rao Bound) by symmetrizing the full probability distribution function (PDF) of the FQ shear estimators (the PDF_SYM approach), instead of taking ensemble averages. Recently, with a large amount of mock galaxy images, we were able to identify some small amount of shear biases in the PDF_SYM approach at the faint end. The multiplicative bias goes up to (1–2) × 10−2 at S/N ≲ 10, and the anisotropy of the point-spread function causes an additive bias that can reach a few times 10−4. We find that these biases originate from the noise-source coupling in the galaxy power spectrum. It turns out that this problem can be largely fixed by adding additional terms to the FQ shear estimators. The resulting multiplicative and additive biases can be significantly suppressed to the level of 10−3 and 10−5, respectively. These corrections substantially extend the available S/N range for accurate shear measurement with the PDF_SYM approach.

An ALMA survey of the SCUBA-2 Cosmology Legacy Survey UKIDSS/UDS field: halo masses for submillimetre galaxies

ABSTRACT We present an analysis of the spatial clustering of a large sample of high-resolution, interferometically identified, submillimetre galaxies (SMGs). We measure the projected cross-correlation function of ∼350 SMGs in the UKIDSS Ultra Deep-Survey Field across a redshift range of z = 1.5–3 utilizing a method that incorporates the uncertainties in the redshift measurements for both the SMGs and cross-correlated galaxies through sampling their full probability distribution functions. By measuring the absolute linear bias of the SMGs, we derive halo masses of $\log _{10}(M_{\rm halo}[{h^{-1}\, \rm M_{\odot }}])$ ∼ 12.8 with no evidence of evolution in the halo masses with redshift, contrary to some previous work. From considering models of halo mass growth rates, we predict that the SMGs will reside in haloes of mass $\log _{10}(M_{\rm halo}[{h^{-1}\, \rm M_{\odot }}])$ ∼ 13.2 at z = 0, consistent with the expectation that the majority of z = 1.5–3 SMGs will evolve into present-day spheroidal galaxies. Finally, comparing to models of stellar-to-halo mass ratios, we show that SMGs may correspond to systems that are maximally efficient at converting their gas reservoirs into stars. We compare them to a simple model for gas cooling in haloes that suggests that the unique properties of the SMG population, including their high levels of star formation and their redshift distribution, are a result of the SMGs being the most massive galaxies that are still able to accrete cool gas from their surrounding intragalactic medium.

Magnetotail‐Inner Magnetosphere Transport Associated With Fast Flows Based on Combined Global‐Hybrid and CIMI Simulation

AbstractUsing the combined Auburn global hybrid simulation code in 3‐D (ANGIE3D) and the Comprehensive Inner Magnetosphere‐Ionosphere (CIMI) model, we investigate the self‐consistent connection of fast flow injections from the tail plasma sheet and the inner magnetosphere under a southward IMF. In the dynamic run, the hybrid results provide the CIMI model with 3‐D magnetic field and the electric potential at the high latitude ionosphere boundary as well as the full ion phase space distribution function at the CIMI outer boundary at the equator. The simulation shows that magnetotail reconnection, which has a dawn‐dusk size of ∼1–5 RE, recurs with a period of several minutes, resulting in recurring localized fast flow injections. Strong ion temperature anisotropy and non‐Maxwellian distributions are present in the fast flows, and the braking of fast flows due to the dipole‐like field results in further perpendicular heating in the injection sources. Multiple fast flow injections lead to multiple peaks in the particle fluxes in the inner magnetosphere as well as layers of upward and downward field‐aligned currents at the ionosphere, and low energy particles penetrate deeper radially than the high energy particles. The combined ANGIE3D‐CIMI model can be used to calculate the global kinetic physics that contains both Region‐1 and Region‐2 field‐aligned currents.

The AGN–galaxy–halo connection: the distribution of AGN host halo masses to z = 2.5

ABSTRACT It is widely reported, based on clustering measurements of observed active galactic nucleus (AGN) samples, that AGNs reside in similar mass host dark matter haloes across the bulk of cosmic time, with log $\mathcal {M}/\mathcal {M}_{\odot }\sim 12.5\!-\!13.0$ to z ∼ 2.5. We show that this is due in part to the AGN fraction in galaxies rising with increasing stellar mass, combined with AGN observational selection effects that exacerbate this trend. Here, we use AGN specific accretion rate distribution functions determined as a function of stellar mass and redshift for star-forming and quiescent galaxies separately, combined with the latest galaxy–halo connection models, to determine the parent and subhalo mass distribution function of AGNs to various observational limits. We find that while the median (sub)halo mass of AGNs, $\approx 10^{12}\mathcal {M}_{\odot }$, is fairly constant with luminosity, specific accretion rate, and redshift, the full halo mass distribution function is broad, spanning several orders of magnitude. We show that widely used methods to infer a typical dark matter halo mass based on an observed AGN clustering amplitude can result in biased, systematically high host halo masses. While the AGN satellite fraction rises with increasing parent halo mass, we find that the central galaxy is often not an AGN. Our results elucidate the physical causes for the apparent uniformity of AGN host haloes across cosmic time and underscore the importance of accounting for AGN selection biases when interpreting observational AGN clustering results. We further show that AGN clustering is most easily interpreted in terms of the relative bias to galaxy samples, not from absolute bias measurements alone.

The Solar Orbiter Solar Wind Analyser (SWA) suite

The Solar Orbiter mission seeks to make connections between the physical processes occurring at the Sun or in the solar corona and the nature of the solar wind created by those processes which is subsequently observed at the spacecraft. The mission also targets physical processes occurring in the solar wind itself during its journey from its source to the spacecraft. To meet the specific mission science goals, Solar Orbiter will be equipped with both remote-sensing and in-situ instruments which will make unprecedented measurements of the solar atmosphere and the inner heliosphere. A crucial set of measurements will be provided by the Solar Wind Analyser (SWA) suite of instruments. This suite consists of an Electron Analyser System (SWA-EAS), a Proton and Alpha particle Sensor (SWA-PAS), and a Heavy Ion Sensor (SWA-HIS) which are jointly served by a central control and data processing unit (SWA-DPU). Together these sensors will measure and categorise the vast majority of thermal and suprathermal ions and electrons in the solar wind and determine the abundances and charge states of the heavy ion populations. The three sensors in the SWA suite are each based on the top hat electrostatic analyser concept, which has been deployed on numerous space plasma missions. The SWA-EAS uses two such heads, each of which have 360° azimuth acceptance angles and ±45° aperture deflection plates. Together these two sensors, which are mounted on the end of the boom, will cover a full sky field-of-view (FoV) (except for blockages by the spacecraft and its appendages) and measure the full 3D velocity distribution function (VDF) of solar wind electrons in the energy range of a few eV to ∼5 keV. The SWA-PAS instrument also uses an electrostatic analyser with a more confined FoV (−24° to +42° × ±22.5° around the expected solar wind arrival direction), which nevertheless is capable of measuring the full 3D VDF of the protons and alpha particles arriving at the instrument in the energy range from 200 eV/q to 20 keV/e. Finally, SWA-HIS measures the composition and 3D VDFs of heavy ions in the bulk solar wind as well as those of the major constituents in the suprathermal energy range and those of pick-up ions. The sensor resolves the full 3D VDFs of the prominent heavy ions at a resolution of 5 min in normal mode and 30 s in burst mode. Additionally, SWA-HIS measures 3D VDFs of alpha particles at a 4 s resolution in burst mode. Measurements are over a FoV of −33° to +66° × ±20° around the expected solar wind arrival direction and at energies up to 80 keV/e. The mass resolution (m/Δm) is > 5. This paper describes how the three SWA scientific sensors, as delivered to the spacecraft, meet or exceed the performance requirements originally set out to achieve the mission’s science goals. We describe the motivation and specific requirements for each of the three sensors within the SWA suite, their expected science results, their main characteristics, and their operation through the central SWA-DPU. We describe the combined data products that we expect to return from the suite and provide to the Solar Orbiter Archive for use in scientific analyses by members of the wider solar and heliospheric communities. These unique data products will help reveal the nature of the solar wind as a function of both heliocentric distance and solar latitude. Indeed, SWA-HIS measurements of solar wind composition will be the first such measurements made in the inner heliosphere. The SWA data are crucial to efforts to link the in situ measurements of the solar wind made at the spacecraft with remote observations of candidate source regions. This is a novel aspect of the mission which will lead to significant advances in our understanding of the mechanisms accelerating and heating the solar wind, driving eruptions and other transient phenomena on the Sun, and controlling the injection, acceleration, and transport of the energetic particles in the heliosphere.

Nonequilibrium Attractor in High-Temperature QCD Plasmas

We establish the existence of a far-from-equilibrium attractor in weakly coupled gauge theory undergoing one-dimensional Bjorken expansion. We demonstrate that the resulting far-from-equilibrium evolution is insensitive to certain features of the initial condition, including both the initial momentum-space anisotropy and initial occupancy. We find that this insensitivity extends beyond the energy-momentum tensor to the detailed form of the one-particle distribution function. Based on our results, we assess different procedures for reconstructing the full one-particle distribution function from the energy-momentum tensor along the attractor and discuss implications for the freeze-out procedure used in the phenomenological analysis of ultrarelativistic nuclear collisions.