Related papers: Generic framework for anisotropic flow analyses wi…
Data-driven methods have demonstrated strong predictive capabilities in fluid mechanics, yet most current applications still focus on simplified configurations, often characterised by statistical stationarity or limited temporal…
We present the first measurements of long-range angular correlations and the transverse momentum dependence of elliptic flow $v_2$ in high-multiplicity $p$$+$Au collisions at $\sqrt{s_{_{NN}}}=200$ GeV. A comparison of these results with…
Suspensions of anisotropic particles are commonly encountered in a wide spectrum of applications, including industrial and architectural coatings, targeted drug delivery and manufacturing of fiber-reinforced composites. A grand challenge in…
Granular flows are ubiquitous in nature and industrial applications, yet a complete continuum theory remains a long-standing challenge. The leading empirical approach, {\mu}(I) rheology, lacks microscopic foundations and becomes multivalued…
Estimating per-pixel motion between video frames, known as optical flow, is a long-standing problem in video understanding and analysis. Most contemporary optical flow techniques largely focus on addressing the cross-image matching with…
We present a global optimization approach to optical flow estimation. The approach optimizes a classical optical flow objective over the full space of mappings between discrete grids. No descriptor matching is used. The highly regular…
A series of novel filters for probabilistic inference that propose an alternative way of performing Bayesian updates, called particle flow filters, have been attracting recent interest. These filters provide approximate solutions to…
We review topics related to the first moment of azimuthal anisotropy ($v_1$), commonly known as directed flow, focusing on both charged particles and identified particles from heavy-ion collisions. Beam energies from the highest available,…
There is strong evidence for the formation of small droplets of quark-gluon plasma in $p/d/^{3}$He+Au collisions at the Relativistic Heavy Ion Collider (RHIC) and in $p$+$p$/Pb collisions at the Large Hadron Collider. In particular, the…
State-of-the-art scene flow algorithms pursue the conflicting targets of accuracy, run time, and robustness. With the successful concept of pixel-wise matching and sparse-to-dense interpolation, we push the limits of scene flow estimation.…
In this paper, we present a general framework for efficiently computing diverse solutions to combinatorial optimization problems. Given a problem instance, the goal is to find $k$ solutions that maximize a specified diversity measure; the…
We present a computational framework for efficient learning, sampling, and distribution of general Bayesian posterior distributions. The framework leverages a machine learning approach for the construction of normalizing flows for the…
We formulate a generalisation of the blast-wave model which is suitable for the description of higher order azimuthal anisotropies of the hadron production. The model includes anisotropy in the density profile as well as an anisotropy in…
We show that backward-forward elliptic anisotropy correlation provides an experimentally accessible observable which distinguishes between collective and non-collective contributions to the observed elliptic anisotropy $v_2$ in relativistic…
We discuss signatures of thermalisation in heavy ion collisions based on elliptic flow. We then propose a new method to analyse elliptic flow, based on multiparticle azimuthal correlations. This method allows one to test quantitatively the…
Higher Fourier harmonics of anisotropic flow ($v_4$ and beyond) get large contributions induced by elliptic and triangular flow through nonlinear response. We present a general framework of nonlinear hydrodynamic response which encompasses…
A general framework for dealing with both linear regression and clustering problems is described. It includes Gaussian clusterwise linear regression analysis with random covariates and cluster analysis via Gaussian mixture models with…
An experimental analysis of small-scales anisotropic turbulent fluctuations has been performed in two different flows. We analyzed anisotropic properties of an homogeneous shear flows and of a turbulent boundary layer by means of two…
Detecting a stochastic gravitational wave background, particularly radiation from individually unresolvable super-massive black hole binary systems, is one of the primary targets for Pulsar Timing Arrays. Increasingly more stringent upper…
We propose Riemannian Flow Matching (RFM), a simple yet powerful framework for training continuous normalizing flows on manifolds. Existing methods for generative modeling on manifolds either require expensive simulation, are inherently…