Cloud Particles Research Articles

Evaluation of methods and metrics for identifying scattering regime of dielectric particulate medium

The norm for analyzing radiative transfer in randomly dispersed particulate medium is to use the independent scattering assumption, where the radiative characteristics of the system are derived from the superposition of the individual particles' radiative characteristics. This assumption is valid when the particles are sparsely distributed. There are established regime maps that are used to identify if the independent scattering assumption is valid. However, these maps which are based on experimental data have been recently questioned and updates are proposed by studies relying on direct solution of Maxwell's equations, in which scattering coefficients, cross-sections and/or efficiencies of particle ensembles are considered to identify presence of dependent scattering effects. Notably, both directionality of the scattering phenomenon and the presence of coherent scattering occurring on the free-space - particle cloud boundary are overlooked while identifying transition between independent and dependent scattering regimes. This study provides a critical overview of recent numerical approaches and shows that a regime map cannot be drawn relying solely on scattering cross section estimated by electromagnetic field solvers. The dependent scattering effects for dielectric particulate medium can be well represented using static structure factor including the directionality of scattering. Transport scattering coefficient that accounts for both magnitude and directionality of the scattering can be used to represent the radiative behavior adequately. Therefore, it can be used as the single intrinsic characteristic for identifying the transition between dependent and independent scattering, rather than the scattering coefficient and the asymmetry parameter alone.

Contribution of expanded marine sulfur chemistry to the seasonal variability of dimethyl sulfide oxidation products and size-resolved sulfate aerosol

Abstract. Marine emissions of dimethyl sulfide (DMS) and the subsequent formation of its oxidation products methanesulfonic acid (MSA) and sulfuric acid (H2SO4) are well-known natural precursors of atmospheric aerosols, contributing to particle mass and cloud formation over ocean and coastal regions. Despite a long-recognized and well-studied role in the marine troposphere, DMS oxidation chemistry remains a work in progress within many current air quality and climate models, with recent advances exploring heterogeneous chemistry and uncovering previously unknown intermediate species. With the identification of additional DMS oxidation pathways and intermediate species that influence the eventual fate of DMS, it is important to understand the impact of these pathways on the overall sulfate aerosol budget and aerosol size distribution. In this work, we update and evaluate the DMS oxidation mechanism of the chemical transport model GEOS-Chem by implementing expanded DMS oxidation pathways in the model. These updates include gas- and aqueous-phase reactions, the formation of the intermediates dimethyl sulfoxide (DMSO) and methanesulfinic acid (MSIA), and cloud loss and aerosol uptake of the recently quantified intermediate hydroperoxymethyl thioformate (HPMTF). We find that this updated mechanism collectively decreases the global mean surface-layer gas-phase sulfur dioxide (SO2) mixing ratio by 40 % and enhances the sulfate aerosol (SO42-) mixing ratio by 17 %. We further perform sensitivity analyses exploring the contribution of cloud loss and aerosol uptake of HPMTF to the overall sulfur budget. Comparing modeled concentrations to available observations, we find improved biases relative to previous studies. To quantify the impacts of these chemistry updates on global particle size distributions and the mass concentration, we use the TwO-Moment Aerosol Sectional (TOMAS) aerosol microphysics module coupled to GEOS-Chem and find that changes in particle formation and growth affect the size distribution of aerosol. With this new DMS-oxidation scheme, the global annual mean surface-layer number concentration of particles with diameters smaller than 80 nm decreases by 16.8 %, with cloud loss processes related to HPMTF being mostly responsible for this reduction. However, the global annual mean number of particles larger than 80 nm (corresponding to particles capable of acting as cloud condensation nuclei, CCN) increases by 3.8 %, suggesting that the new scheme promotes seasonal particle growth to these sizes.

Investigation of turbulent flow induced by particle sedimentation using RIM-PIV

The spatiotemporal structure of the flow field during particle–cloud sedimentation has not been sufficiently investigated. In this study, experiments on the sedimentation process of particle clouds in water are conducted using hydrogel particles with a refractive index similar to that of water as the settling particles. The flow field during the sedimentation process of particle clouds in water is measured using particle image velocimetry (PIV). Although the measurement conditions in this study are restricted to one condition owing to the limitations of the measurable area by our PIV system and the available hydrogel particles, the measurement target is novel because it has not been measured so far. The spatiotemporal structure of the turbulent flows is investigated by analyzing the turbulent flows induced by the sedimentation particles using the PIV system. Furthermore, the turbulent structure of the vortex formed by particle sedimentation is examined.

Influence of planetary rotation on metal-silicate mixing and equilibration in a magma ocean

At a late stage of its accretion, the Earth experienced high-energy planetary impacts. Following each collision, the metal core of the impactor sank into molten silicate magma oceans. The efficiency of chemical equilibration between these silicates and the metal core controlled the composition of the Earth interior and left a signature on geochemical and isotopic data. These data constrain the timing, pressure and temperature of Earth formation, but their interpretation strongly depends on the efficiency of metal-silicate mixing and equilibration. We investigate the role of planetary rotation on the dynamics of the sinking metal and on its chemical equilibration using laboratory experiments of particle clouds settling in a rotating fluid. Our clouds initially sink as spherical turbulent thermals, but after a critical depth, rotation becomes important and they transition to a vortical columnar flow aligned with the rotation axis. Applied to Earth formation, our results predict that rotation strongly affects the fall of metal in the magma ocean for impactors smaller than 459 km in radius on a proto-Earth that rotates twice faster than today. On a proto-Earth spinning 5 times faster than today, rotation is important for any impactor smaller than the Earth itself. In contrast with a thermal that grows in all directions, the vortical column grows vertically but keeps a constant horizontal extent. The slower dilution in vortical columns reduces chemical equilibration compared to previous estimates that neglect planetary rotation. We find that rotation significantly affects the degree of equilibration for highly siderophile elements with partition coefficients larger than 103. In this case, for a planet spinning twice faster than today, the degree of equilibration decreases by up to a factor 2 compared to previous estimates that neglect the effect of rotation. Finally, the ultimate fate of iron drops is to be detrained from the vortical column as an iron rain, reconciling the traditional iron rain scenario with the model of turbulent thermal.

Astrobiological Potential of Venus Atmosphere Chemical Anomalies and Other Unexplained Cloud Properties.

Long-standing unexplained Venus atmosphere observations and chemical anomalies point to unknown chemistry but also leave room for the possibility of life. The unexplained observations include several gases out of thermodynamic equilibrium (e.g., tens of ppm O2, the possible presence of PH3 and NH3, SO2 and H2O vertical abundance profiles), an unknown composition of large, lower cloud particles, and the "unknown absorber(s)." Here we first review relevant properties of the venusian atmosphere and then describe the atmospheric chemical anomalies and how they motivate future astrobiology missions to Venus.

Settling dynamics and thresholds for breakup and separation of bi-disperse particle clouds

Settling dynamics and thresholds for breakup and separation of bi-disperse particle clouds

Significantly Accelerated Photosensitized Formation of Atmospheric Sulfate at the Air-Water Interface of Microdroplets.

The multiphase oxidation of sulfur dioxide (SO2) to form sulfate is a complex and important process in the atmosphere. While the conventional photosensitized reaction mainly explored in the bulk medium is reported to be one of the drivers to trigger atmospheric sulfate production, how this scheme functionalizes at the air-water interface (AWI) of aerosol remains an open question. Herein, employing an advanced size-controllable microdroplet-printing device, surface-enhanced Raman scattering (SERS) analysis, nanosecond transient adsorption spectrometer, and molecular level theoretical calculations, we revealed the previously overlooked interfacial role in photosensitized oxidation of SO2 in humic-like substance (HULIS) aerosol, where a 3-4 orders of magnitude increase in sulfate formation rate was speculated in cloud and aerosol relevant-sized particles relative to the conventional bulk-phase medium. The rapid formation of a battery of reactive oxygen species (ROS) comes from the accelerated electron transfer process at the AWI, where the excited triplet state of HULIS (3HULIS*) of the incomplete solvent cage can readily capture electrons from HSO3- in a way that is more efficient than that in the bulk medium fully blocked by water molecules. This phenomenon could be explained by the significantly reduced desolvation energy barrier required for reagents residing in the AWI region with an open solvent shell.

Numerical Study on the Precipitation Concentration over the Western Coast of Sumatra Island

Abstract Large amounts of tropical precipitation have been observed as significantly concentrated over the western coast of Sumatra Island. In the present study, we used a cloud-resolving model to perform 14-day numerical simulations and reproduce the distinctive precipitation distributions over western Sumatra Island and adjacent areas. The control experiment, in which the warmer sea surface temperature (SST) near the coast was incorporated and the terminal velocity and effective radius of ice clouds were parameterized to be temperature dependent, adequately reproduced the precipitation concentration as well as the diurnal cycles of precipitation. We then used the column-integrated frozen moist static energy budget equation, which is virtually equivalent to the column-integrated moisture budget equation under the weak temperature gradient assumption, to formulate sensitivity experiments focusing on the effects of coastal SST and upper-level ice clouds. Analysis of the time-averaged fields revealed that the column-integrated moisture and precipitation in the coast were significantly reduced when a cooler coastal SST or larger ice cloud particle size was assumed. Based on the comparison of the sensitivity experiments and in situ observations, we speculate that ice clouds, which are exported from inland convection that is strictly regulated by solar radiation, promote the accumulation of moisture in the coastal region by mitigating radiative cooling. Together with the moisture and heat supplied by the warm ocean surface, they contribute to the large amounts of precipitation here.

The radiative and dynamical impact of clouds in the atmosphere of the hot Jupiter WASP-43 b

Context. Hot Jupiters are tidally locked gaseous exoplanets that exhibit large day-night temperature contrasts. Their cooler nightsides are thought to host clouds, as has been suggested by numerous observations. However, the exact nature of these clouds, their spatial distribution, and their impact on atmospheric dynamics, thermal structure, and spectra is still unclear. Aims. We investigate the atmosphere of WASP-43 b, a short period hot Jupiter recently observed with James Webb Space Telescope (JWST), to understand the radiative and dynamical impact of clouds on the atmospheric circulation and thermal structure. We aim to understand the impact of different kinds of condensates potentially forming in WASP-43 b, with various sizes and atmospheric metallicities. Methods. We used a 3D global climate model (GCM) with a new temperature-dependent cloud model that includes radiative feedbacks coupled with hydrodynamical integrations to study the atmospheric properties of WASP-43 b. We produced observables from our GCM simulations and compared them to spectral phase curves from various observations to derive constraints on the atmospheric properties. Results. We show that clouds have a net warming effect, meaning that the greenhouse effect caused by clouds is stronger than the albedo cooling effect. We show that the radiative effect of clouds has various impacts on the dynamical and thermal structure of WASP-43 b. Depending on the type of condensates and their sizes, the radiative-dynamical feedback will modify the horizontal and vertical temperature gradient and reduce the wind speed. For super-solar metallicity atmospheres, fewer clouds form in the atmosphere, leading to a weaker feedback. Comparisons with spectral phase curves observed with HST, Spitzer, and JWST indicate that WASP-43 b's nightside is cloudy and rule out sub-micron Mg2SiO4 cloud particles as the main opacity source. Distinguishing between cloudy solarand cloudy super-solar-metallicity atmospheres is not straightforward, and further observations of both reflected light and thermal emission are needed.

Instabilities of a circular moderately dense particle cloud impacted by an incident shock

Shock-driven gas-particle flows exist in a wide variety of physical systems, covering the range from dilute to dense regime. There are a lot of fundamental questions remaining to be answered, like the evolutions of flow instability, two-phase interactions, and inter-particle collision effects. In this work, the Eulerian-Lagrangian approach with gas-particle four-way coupling is applied to model two-dimensional shock-driven gas-particle flow under the moderately dense regime. For the gas flow, the formation mechanism of primary and secondary vortexes is discussed. The primary vortex is caused by the roll-up of slip line, while the secondary vortexes are induced by the velocity and density difference between the penetrating flow of particle-laden zone and the outside mainstream. Parametric studies of different Mach numbers, particle diameters and initial volume fractions have been performed to investigate the effects on shock behaviours and slip line instabilities. For the particle phase, a high-volume-fraction compression region forms at the upstream cloud zone, which blocks the penetrating gas, and results in the formation of slip line. The cloud tail is mainly composed of the upstream edge particles. The inter-particle collisions have impact on the particle distributions, and greatly affect the slip line stability at the upstream cloud edge. This work provides valuable insights into the instability mechanism of compressible gas-solid flow and the particle dispersion behaviours. However, it is important to note that our analysis is based on a two-dimensional configuration. In a real three-dimensional context, the generation of vortices is likely to differ, and may affect the particle dynamics to a certain degree.

Nanoparticles synthesis in microwave plasmas: peculiarities and comprehensive insight

Low-pressure plasma processes are routinely used to grow, functionalize or etch materials, and thanks to some of its unique attributes, plasma has become a major player for some applications such as microelectronics. Plasma processes are however still at a research level when it comes to the synthesis and functionalization of nanoparticles. Yet plasma processes can offer a particularly suitable solution to produce nanoparticles having very peculiar features since they enable to: (i) reach particle with a variety of chemical compositions, (ii) tune the size and density of the particle cloud by acting on the transport dynamics of neutral or charged particles through a convenient setting of the thermal gradients or the electric field topology in the reactor chamber and (iii) manipulate nanoparticles and deposit them directly onto a substrate, or codeposit them along with a continuous film to produce nanocomposites or (iv) use them as a template to produce 1D materials. In this article, we present an experimental investigation of nanoparticles synthesis and dynamics in low-pressure microwave plasmas by combining time-resolved and in-situ laser extinction and scattering diagnostics, QCL absorption spectroscopy, mass spectrometry, optical emission spectroscopy and SEM along with a particle transport model. We showed for the first time the thermophoresis-driven dynamic of particle cloud in electrodless microwave plasmas. We showed that this effect is linked to particular fluctuations in the plasma composition and results in the formation of a void region in the bulk of the plasma surrounded by a particle cloud in the peripherical post-discharge. We also reveals and analyze the kinetics of precursor dissociation and molecular growth that result in the observed nanoparticle nucleation.

Characterization of ejecta in shock experiments with multiple light scattering

Upon impact, the free surface of a solid metal may eject a cloud of fast and fine particles. Photon Doppler Velocimetry (PDV) is one of the optical diagnostics used to characterize these ejecta. Although the technique provides a direct way to estimate the particle velocities in the single scattering regime, it has been shown that multiple scattering cannot be neglected in real ejecta. Here, we derive a model for PDV measurements starting from the first principles of wave scattering. We establish rigorously the relationship between the specific intensity and the measured signal, as well as the Radiative Transport Equation (RTE) that describes the evolution of the specific intensity upon scattering and absorption in dynamic ejecta, including the effects of inelastic scattering and inhomogeneities in the optical properties. We also establish rigorously the connection between the Monte Carlo scheme used for numerical simulations and the solution to the RTE. Using numerical simulations, we demonstrate the crucial contribution of multiple scattering to PDV spectrograms as well as the effect of statistical inhomogeneities in particle size distribution. These results could substantially impact the analysis of ejecta by PDV.

An effective approach for aerosol dynamics modeling in dusty plasma

In this paper, we demonstrate the application of the Dirac-lognormal bimodal moment approach to investigate aerosol dynamics in dusty plasmas. This approach was evaluated by comparison with the detailed and computationally expensive sectional approach for two dusty plasma systems. The first one is a sputtering Argon DC discharge and the second is a capacitively coupled Ar/C2H2 radio-frequency (CCRF) discharge. The results obtained by the bimodal and the sectional approaches are in good agreement for the sputtering DC discharge where the aerosol dynamics is dominated by nucleation and surface deposition growth processes. This agreement is obtained not only on the averaged characteristics of the particle cloud, but also on the detailed particle size distributions. In the case of the CCRF discharge a satisfactory agreement between the two approaches is obtained on the averaged characteristics and on the core distributions of the particle cloud even if a significant difference is observed at low and intermediate particle size. Nevertheless, the bimodal moment approach is accurate enough for the simulation of the dusty plasmas of interest. Its low-computational cost makes it a very effective method as far as dusty plasma simulation is concerned.

Carrier-Phase DNS of Ignition and Combustion of Iron Particles in a Turbulent Mixing Layer

Three-dimensional carrier-phase direct numerical simulations (CP-DNS) of reacting iron particle dust clouds in a turbulent mixing layer are conducted. The simulation approach considers the Eulerian transport equations for the reacting gas phase and resolves all scales of turbulence, whereas the particle boundary layers are modelled employing the Lagrangian point-particle framework for the dispersed phase. The CP-DNS employs an existing sub-model for iron particle combustion that considers the oxidation of iron to FeO and that accounts for both diffusion- and kinetically-limited combustion. At first, the particle sub-model is validated against experimental results for single iron particle combustion considering various particle diameters and ambient oxygen concentrations. Subsequently, the CP-DNS approach is employed to predict iron particle cloud ignition and combustion in a turbulent mixing layer. The upper stream of the mixing layer is initialised with cold particles in air, while the lower stream consists of hot air flowing in the opposite direction. Simulation results show that turbulent mixing induces heating, ignition and combustion of the iron particles. Significant increases in gas temperature and oxygen consumption occur mainly in regions where clusters of iron particles are formed. Over the course of the oxidation, the particles are subjected to different rate-limiting processes. While initially particle oxidation is kinetically-limited it becomes diffusion-limited for higher particle temperatures and peak particle temperatures are observed near the fully-oxidised particle state. Comparing the present non-volatile iron dust flames to general trends in volatile-containing solid fuel flames, non-vanishing particles at late simulation times and a stronger limiting effect of the local oxygen concentration on particle conversion is found for the present iron dust flames in shear-driven turbulence.

Analysis of the Micro-Physical Characteristics of the Sea of Clouds Phenomena in Jiuxian Mountain Based on Multiple Source Observations

The micro-physical characteristics of a typical sea of clouds process in Jiuxian Mountain are investigated by comprehensively analyzing parameters that delineate the micro-physical characteristics of clouds and atmospheric stratification based on data from a cloud radar, wind profiler, meteorological gradient observation in high mountains, and other observations. The results show that water vapor condenses into cloud particles via an entrained and mixing process accompanied by an updraft originating from orographic uplift. During the thickening stage of the sea of clouds, atmospheric motion within the clouds is featured as “downdraft on the top—updraft on the bottom”. The zero vertical velocity area is located closely to the maximum of liquid water content. The thermal inversion layer is formed during the maintenance stage; however, the enhancement of inversion on the cloud top could suppress updraft in areas with a high liquid water content. The values mainly concentrate on the cloud top, and repetitively lifting and falling processes caused by the atmospheric upward and downward motion are in favor of the coalescence growth of cloud particles, which result in the persistence of strong radar echo. At the dissipation stage, warming on the cloud top is greater than that on the cloud bottom due to the short-wave absorption of clouds as the solar radiation enhances. As a result, the inversion layer thickens and elevates, evaporation caused by heating outweighs the condensation caused by cooling, a strong radar echo band descends from the top to the middle part of clouds, a sea of clouds dissipates gradually as cloud particles evaporates, and the particle size and concentration number of cloud particles decrease simultaneously.

Technical note: Bimodal parameterizations of in situ ice cloud particle size distributions

Abstract. The cloud particle size distribution (PSD) is a key parameter for the retrieval of microphysical and optical properties from remote-sensing instruments, which in turn are necessary for determining the radiative effect of clouds. Current representations of PSDs for ice clouds rely on parameterizations that were largely based on aircraft in situ measurements where the distribution of small ice crystals were uncertain. This makes current parameterizations deficient to simulate remote-sensing observations sensitive to small ice, such as from lidar and thermal infrared instruments. In this study we fit the in situ PSDs of ice crystals from the JULIA (JÜLich In situ Aircraft data set) database, which consists of 11 campaigns covering the tropics, midlatitudes and the Arctic, consistently processed and considered more robust in their measurements of small ice. For the fitting, we implement an established approach to PSD parameterizations, which consists of finding an adequate set of parameters for a modified gamma function after normalization of both PSD axes. These parameters are constrained to match in situ measurements when predicting microphysical properties from the PSDs, via a cost function minimization method. We selected the ice water content and the ice crystal number concentration, which are currently key parameters for modern satellite retrievals and model microphysics schemes. We found that a bimodal parameterization yields better results than a monomodal one. The bimodal parameterization has a lower spread for almost all ice crystal sizes over the entire range of analyzed temperatures and fits better the observations, especially for particles between 20 and about 110 µm at temperatures between −60 and −20 ∘C. For this temperature range, the root mean square error for the retrieved Nice is reduced from 0.36 to 0.20. This demonstrates a clear advantage to considering the bimodality of PSDs, e.g., for satellite retrievals.

Aggregation and Charging of Mineral Cloud Particles under High-energy Irradiation

It is known from Earth that ionizing high-energy radiation can lead to ion-induced nucleation of cloud condensation nuclei in the atmosphere. Since the amount of high-energy radiation can vary greatly based on the radiative environment of a host star, understanding the effect of high-energy radiation on cloud particles is critical to understand exoplanet atmospheres. This study aims to explore how high-energy radiation affects the aggregation and charging of mineral cloud particles. We present experiments conducted in an atmosphere chamber on mineral SiO2 particles with diameters of 50 nm. The particles were exposed to gamma radiation in either low-humidity (RH ≈ 20%) or high-humidity (RH > 50%) environments. The aggregation and charging state of the particles were studied with a scanning mobility particle sizer. We find that the single SiO2 particles (N1) cluster to form larger aggregates (N2–N4), and that this aggregation is inhibited by gamma radiation. We find that gamma radiation shifts the charging of the particles to become more negative by increasing the charging state of negatively charged particles. Through an independent t-test, we find that this increase is statistically significant within a 5% significance level for all aggregates in the high-humidity environment and all except the N1 particles in the low-humidity environment. For the positively charged particles, the changes in charging state are not within the 5% significance level. We suggest that the overall effect of gamma radiation could favor the formation of a high number of small particles over a lower number of larger particles.

Fully time-dependent cloud formation from a non-equilibrium gas-phase in exoplanetary atmospheres

Context. Recent observations suggest the presence of clouds in exoplanet atmospheres, but they have also shown that certain chemical species in the upper atmosphere might not be in chemical equilibrium. Present and future interpretation of data from, for example, CHEOPS, JWST, PLATO, and Ariel require a combined understanding of the gas-phase and the cloud chemistry. Aims. The goal of this work is to calculate the two main cloud formation processes, nucleation, and bulk growth consistently from a non-equilibrium gas phase. The aim is also to explore the interaction between a kinetic gas-phase and cloud microphysics. Methods. The cloud formation is modelled using the moment method and kinetic nucleation, which are coupled to a gas-phase kinetic rate network. Specifically, the formation of cloud condensation nuclei is derived from cluster rates that include the thermochemical data of (TiO2)N from N = 1 to 15. The surface growth of nine bulk Al, Fe, Mg, O, Si, S, and Ti binding materials considers the respective gas-phase species through condensation and surface reactions as derived from kinetic disequilibrium. The effect of the completeness of rate networks and the time evolution of the cloud particle formation is studied for an example exoplanet, HD 209458 b. Results. A consistent, fully time-dependent cloud formation model in chemical disequilibrium with respect to nucleation, bulk growth, and the gas-phase is presented and first test cases are studied. This model shows that cloud formation in exoplanet atmospheres is a fast process. This confirms previous findings that the formation of cloud particles is a local process. Tests on selected locations within the atmosphere of the gas-giant HD 209458 b show that the cloud particle number density and volume reach constant values within 1 s. The complex kinetic polymer nucleation of TiO2 confirms results from classical nucleation models. The surface reactions of SiO[s] and SiO2[s] can create a catalytic cycle that dissociates H2 to 2 H, resulting in a reduction of the CH4 number densities.

Kinetic Theory for the Low-Density Lorentz Gas

The Lorentz gas is one of the simplest and most widely-studied models for particle transport in matter. It describes a cloud of non-interacting gas particles in an infinitely extended array of identical spherical scatterers. The model was introduced by Lorentz in 1905 who, following the pioneering ideas of Maxwell and Boltzmann, postulated that in the limit of low scatterer density, the macroscopic transport properties of the model should be governed by a linear Boltzmann equation. The linear Boltzmann equation has since proved a useful tool in the description of various phenomena, including semiconductor physics and radiative transfer. A rigorous derivation of the linear Boltzmann equation from the underlying particle dynamics was given, for random scatterer configurations, in three seminal papers by Gallavotti, Spohn and Boldrighini-Bunimovich-Sinai. The objective of the present study is to develop an approach for a large class of deterministic scatterer configurations, including various types of quasicrystals. We prove the convergence of the particle dynamics to transport processes that are in general (depending on the scatterer configuration) not described by the linear Boltzmann equation. This was previously understood only in the case of the periodic Lorentz gas through work of Caglioti-Golse and Marklof-Strömbergsson. Our results extend beyond the classical Lorentz gas with hard sphere scatterers, and in particular hold for general classes of spherically symmetric finite-range potentials. We employ a rescaling technique that randomises the point configuration given by the scatterers’ centers. The limiting transport process is then expressed in terms of a point process that arises as the limit of the randomised point configuration under a certain volume-preserving one-parameter linear group action.

Faster diffusion model with improved quality for particle cloud generation

Building on the success of PC-JeDi we introduce PC-Droid, a substantially improved diffusion model for the generation of jet particle clouds. By leveraging a new diffusion formulation, studying more recent integration solvers, and training on all jet types simultaneously, we are able to achieve state-of-the-art performance for all types of jets across all evaluation metrics. We study the trade-off between generation speed and quality by comparing two attention based architectures, as well as the potential of consistency distillation to reduce the number of diffusion steps. Both the faster architecture and consistency models demonstrate performance surpassing many competing models, with generation time up to two orders of magnitude faster than PC-JeDi and three orders of magnitude faster than . Published by the American Physical Society 2024