Effective Visualization of Temporal Ensembles.

An ensemble is a collection of related datasets, called members, built from a series of runs of a simulation or an experiment. Ensembles are large, temporal, multidimensional, and multivariate, making them difficult to analyze. Another important challenge is visualizing ensembles that vary both in space and time. Initial visualization techniques displayed ensembles with a small number of members, or presented an overview of an entire ensemble, but without potentially important details. Recently, researchers have suggested combining these two directions, allowing users to choose subsets of members to visualization. This manual selection process places the burden on the user to identify which members to explore. We first introduce a static ensemble visualization system that automatically helps users locate interesting subsets of members to visualize. We next extend the system to support analysis and visualization of temporal ensembles. We employ 3D shape comparison, cluster tree visualization, and glyph based visualization to represent different levels of detail within an ensemble. This strategy is used to provide two approaches for temporal ensemble analysis: (1) segment based ensemble analysis, to capture important shape transition time-steps, clusters groups of similar members, and identify common shape changes over time across multiple members; and (2) time-step based ensemble analysis, which assumes ensemble members are aligned in time by combining similar shapes at common time-steps. Both approaches enable users to interactively visualize and analyze a temporal ensemble from different perspectives at different levels of detail. We demonstrate our techniques on an ensemble studying matter transition from hadronic gas to quark-gluon plasma during gold-on-gold particle collisions.

Center domains and their phenomenological consequences.

We argue that the domain structure of deconfined QCD matter, which can be inferred from the properties of the Polyakov loop, can simultaneously explain the two most prominent experimentally verified features of the quark-gluon plasma, namely its large opacity as well as its near ideal fluid properties.

Increasing the perceptual salience of relationships in parallel coordinate plots.

We present three extensions to parallel coordinates that increase the perceptual salience of relationships between axes in multivariate data sets: (1) luminance modulation maintains the ability to preattentively detect patterns in the presence of overplotting, (2) adding a one-vs.-all variable display highlights relationships between one variable and all others, and (3) adding a scatter plot within the parallel-coordinates display preattentively highlights clusters and spatial layouts without strongly interfering with the parallel-coordinates display. These techniques can be combined with one another and with existing extensions to parallel coordinates, and two of them generalize beyond cases with known-important axes. We applied these techniques to two real-world data sets (relativistic heavy-ion collision hydrodynamics and weather observations with statistical principal component analysis) as well as the popular car data set. We present relationships discovered in the data sets using these methods.

Exploring Ensemble Visualization.

An ensemble is a collection of related datasets. Each dataset, or member, of an ensemble is normally large, multidimensional, and spatio-temporal. Ensembles are used extensively by scientists and mathematicians, for example, by executing a simulation repeatedly with slightly different input parameters and saving the results in an ensemble to see how parameter choices affect the simulation. To draw inferences from an ensemble, scientists need to compare data both within and between ensemble members. We propose two techniques to support ensemble exploration and comparison: a pairwise sequential animation method that visualizes locally neighboring members simultaneously, and a screen door tinting method that visualizes subsets of members using screen space subdivision. We demonstrate the capabilities of both techniques, first using synthetic data, then with simulation data of heavy ion collisions in high-energy physics. Results show that both techniques are capable of supporting meaningful comparisons of ensemble data.

Comparative Visualization of Ensembles Using Ensemble Surface Slicing.

By definition, an ensemble is a set of surfaces or volumes derived from a series of simulations or experiments. Sometimes the series is run with different initial conditions for one parameter to determine parameter sensitivity. The understanding and identification of visual similarities and differences among the shapes of members of an ensemble is an acute and growing challenge for researchers across the physical sciences. More specifically, the task of gaining spatial understanding and identifying similarities and differences between multiple complex geometric data sets simultaneously has proved challenging. This paper proposes a comparison and visualization technique to support the visual study of parameter sensitivity. We present a novel single-image view and sampling technique which we call Ensemble Surface Slicing (ESS). ESS produces a single image that is useful for determining differences and similarities between surfaces simultaneously from several data sets. We demonstrate the usefulness of ESS on two real-world data sets from our collaborators.

200 A GeV Au + Au collisions serve a nearly perfect quark-gluon liquid.

A new robust method to extract the specific shear viscosity (η/s)(QGP) of a quark-gluon plasma (QGP) at temperatures T(c) < T ≲ 2T(c) from the centrality dependence of the eccentricity-scaled elliptic flow v2/ε measured in ultrarelativistic heavy-ion collisions is presented. Coupling viscous fluid dynamics for the QGP with a microscopic transport model for hadronic freeze-out we find for 200 A GeV Au + Au collisions that v2/ε is a universal function of multiplicity density (1/S)(dN(ch)/dy) that depends only on the viscosity but not on the model used for computing the initial fireball eccentricity ε. Comparing with measurements we find 1<4π(η/s)(QGP) < 2.5 where the uncertainty range is dominated by model uncertainties for the values of ε used to normalize the measured v2.

Shear-viscosity to entropy-density ratio of a relativistic hadron gas.

Ultrarelativistic heavy-ion collisions at the Brookhaven National Laboratory Relativistic Heavy Ion Collider (RHIC) are thought to have produced a state of matter called the quark-gluon plasma, characterized by a very small shear-viscosity to entropy-density ratio eta/s, near the lower bound predicted for that quantity by anti-de Sitter space/conformal field theory methods. As the produced matter expands and cools, it evolves through a phase described by a hadron gas with rapidly increasing eta/s. We calculate eta/s as a function of temperature in this phase both in and out of chemical equilibrium and find that its value poses a challenge for viscous relativistic hydrodynamics, which requires small values of eta/s in order to successfully describe the collective flow observables at the RHIC. We therefore conclude that the origin of the low viscosity matter at the RHIC must be in the partonic phase of the reaction.

Photon interferometry of Au+Au collisions at the BNL Relativistic Heavy-Ion Collider.

We calculate the two-body correlation function of direct photons produced in central Au+Au collisions at the Relativistic Heavy-Ion Collider. Our calculation includes contributions from the early preequilibrium phase in which photons are produced via hard parton scatterings as well as radiation of photons from a thermalized quark-gluon plasma and the subsequent expanding hadron gas. We find that high energy photon interferometry provides a faithful probe of the details of the space-time evolution and of the early reaction stages of the system.

Net baryon density in Au+Au collisions at the relativistic heavy ion collider.

We calculate the net-baryon rapidity distribution in Au+Au collisions at the Relativistic Heavy Ion Collider (RHIC) in the framework of the parton cascade model (PCM). Parton rescattering and fragmentation leads to a substantial increase in the net-baryon density at midrapidity over the density produced by initial primary parton-parton scatterings. The PCM is able to describe the measured net-baryon density at RHIC.

Light from cascading partons in relativistic heavy-ion collisions.

We calculate the production of high energy photons from Compton and annihilation processes as well as fragmentation off quarks in the parton cascade model. The multiple scattering of partons is seen to lead to a substantial production of high energy photons, which rises further when parton multiplication due to final state radiation is included. The photon yield is found to be directly proportional to the number of hard collisions and thus provides valuable information on the preequilibrium reaction dynamics.

Kaon interferometry: a sensitive probe of the QCD equation of state?

We calculate the kaon-interferometry radius parameters for high-energy heavy-ion collisions, assuming a first-order phase transition from a thermalized quark-gluon plasma (QGP) to a gas of hadrons. At high transverse momenta K(T) approximately 1 GeV/c direct emission from the phase boundary becomes important; the emission duration signal, i.e., the R(out)/R(side) ratio, and its sensitivity to T(c) (and thus to the latent heat) are enlarged. The QGP+hadronic rescattering transport model calculations do not yield unusually large radii (R(i) < or = 9 fm). Finite-momentum-resolution effects have a strong impact on the extracted interferometry parameters ( R(i) and lambda), as well as on the ratio R(out)/R(side).