Temperature-density Relation Research Articles

Deep learning the intergalactic medium using lyman-alpha forest at 4 ≤ z ≤ 5

Abstract Unveiling the thermal history of the intergalactic medium (IGM) at 4 ≤ z ≤ 5 holds the potential to reveal early onset He ii reionization or lingering thermal fluctuations from H i reionization. We set out to reconstruct the IGM gas properties along simulated Lyman-alpha forest data on pixel-by-pixel basis, employing deep neural networks. Our approach leverages the Sherwood-Relics simulation suite, consisting of diverse thermal histories, to generate mock spectra. Our convolutional and residual networks with likelihood metric predicts the Lyα optical depth-weighted density or temperature for each pixel in the Lyα forest skewer. We find that our network can successfully reproduce IGM conditions with high fidelity across range of instrumental signal-to-noise. These predictions are subsequently translated into the temperature-density plane, facilitating the derivation of reliable constraints on thermal parameters. This allows us to estimate temperature at mean cosmic density, T0 , with one sigma confidence, $\delta {\rm T_{\rm 0}}\,$≲ 1000K, using only one 20h−1cMpc sightline (Δz ≃ 0.04) with a typical reionization history. Existing studies utilize redshift pathlength comparable to Δz ≃ 4 for similar constraints. We can also provide more stringent constraints on the slope (1σ confidence interval, δγ ≲ 0.1) of the IGM temperature-density relation as compared to other traditional approaches. We test the reconstruction on a single high signal-to-noise observed spectrum (20h−1cMpc segment), and recover thermal parameters consistent with current measurements. This machine learning approach has the potential to provide accurate yet robust measurements of IGM thermal history at the redshifts in question.

LYαNNA: A deep learning field-level inference machine for the Lyman-α forest

The inference of astrophysical and cosmological properties from the Lyman-α forest conventionally relies on summary statistics of the transmission field that carry useful but limited information. We present a deep learning framework for inference from the Lyman-α forest at the field level. This framework consists of a 1D residual convolutional neural network (ResNet) that extracts spectral features and performs regression on thermal parameters of the intergalactic medium that characterize the power-law temperature-density relation. We trained this supervised machinery using a large set of mock absorption spectra from NYX hydrodynamic simulations at z = 2.2 with a range of thermal parameter combinations (labels). We employed Bayesian optimization to find an optimal set of hyperparameters for our network, and then employed a committee of 20 neural networks for increased statistical robustness of the network inference. In addition to the parameter point predictions, our machine also provides a self-consistent estimate of their covariance matrix with which we constructed a pipeline for inferring the posterior distribution of the parameters. We compared the results of our framework with the traditional summary based approach, namely the power spectrum and the probability density function (PDF) of transmission, in terms of the area of the 68% credibility regions as our figure of merit (FoM). In our study of the information content of perfect (noise- and systematics-free) Lyα forest spectral datasets, we find a significant tightening of the posterior constraints – factors of 10.92 and 3.30 in FoM over the power spectrum only and jointly with PDF, respectively – which is the consequence of recovering the relevant parts of information that are not carried by the classical summary statistics.

HYACINTH: HYdrogen And Carbon chemistry in the INTerstellar medium in Hydro simulations

Aims. We present a new sub-grid model, HYACINTH – HYdrogen And Carbon chemistry in the INTerstellar medium in Hydro simulations – for computing the non-equilibrium abundances of H2 and its carbon-based tracers, namely CO, C, and C+, in cosmological simulations of galaxy formation. Methods. The model accounts for the unresolved density structure in simulations using a variable probability distribution function of sub-grid densities and a temperature-density relation. Included is a simplified chemical network that has been tailored for hydrogen and carbon chemistry within molecular clouds and easily integrated into large-scale simulations with minimal computational overhead. As an example, we applied HYACINTH to a simulated galaxy at redshift z ~ 2.5 in post-processing and compared the resulting abundances with observations. Results. The chemical predictions from HYACINTH are in reasonable agreement with high-resolution molecular-cloud simulations at different metallicities. By post-processing a galaxy simulation with HYACINTH, we reproduced the H I − H2 transition as a function of the hydrogen column density NH for both Milky-Way-like and Large-Magellanic-Cloud-like conditions. We also matched the NCO versus NH2 relation inferred from absorption measurements towards Milky-Way molecular clouds, although most of our post-processed regions occupy the same region as (optically) dark molecular clouds in the NCO – NH2 plane. Column density maps reveal that CO is concentrated in the peaks of the H2 distribution, while atomic carbon more broadly traces the bulk of H2 in our post-processed galaxy. Based on both the column density maps and the surface density profiles oŕ the different gas species in the post-processed galaxy, we find that C+ maintains a substantially high surŕace density out to ~10 kpc as opposed to other components that exhibit a higher central concentration. This is similar to the extended [C II] emission ŕound in some recent observations at high redshifts.

ELUCID. VIII. Simulating the Coma Galaxy Cluster to Calibrate Model and Understand Feedback

We conducted an investigation of the Coma cluster of galaxies by running a series of constrained hydrodynamic simulations with GIZMO-SIMBA and GADGET-3 based on initial conditions reconstructed from the SDSS survey volume in the ELUCID project. We compared simulation predictions and observations for galaxies, intracluster medium (ICM) and intergalactic medium (IGM) in and around the Coma cluster to constrain galaxy formation physics. Our results demonstrate that this type of constrained investigation allows us to probe in more detail the implemented physical processes, because the comparison between simulations and observations is free of cosmic variance and hence can be conducted in a “one-to-one” manner. We found that an increase in the earlier star formation rate and the supernova feedback of the original GIZMO-SIMBA model is needed to match observational data on stellar, interstellar medium, and ICM metallicity. The simulations without active galactic nucleus (AGN) feedback can well reproduce the observational ICM electron density, temperature, and entropy profiles, ICM substructures, and the IGM temperature–density relation, while the ones with AGN feedback usually fail. However, one requires something like AGN feedback to reproduce a sufficiently large population of quiescent galaxies, particularly in low-density regions. The constrained simulations of the Coma cluster thus provide a test bed to understand processes that drive galaxy formation and evolution.

A modified lognormal approximation of the Lyman-α forest: comparison with full hydrodynamic simulations at 2 ≤ z ≤ 2.7

Observations of the Lyman-α forest in distant quasar spectra with upcoming surveys are expected to provide significantly larger and higher-quality datasets. To interpret these datasets, it is imperative to develop efficient simulations. One such approach is based on the assumption that baryonic densities in the intergalactic medium (IGM) follow a lognormal distribution. We extend our earlier work to assess the robustness of the lognormal model of the Lyman-α forest in recovering the parameters characterizing IGM state, namely, the mean-density IGM temperature (T 0), the slope of the temperature-density relation (γ), and the hydrogen photoionization rate (Γ12), by comparing with high-resolution Sherwood SPH simulations across the redshift range 2 ≤ z ≤ 2.7. These parameters are estimated through a Markov Chain Monte Carlo (MCMC) technique, using the mean and power spectrum of the transmitted flux. We find that the usual lognormal distribution of IGM densities cannot recover the parameters of the SPH simulations. This limitation arises from the fact that the SPH baryonic density distribution cannot be described by a simple lognormal form. To address this, we extend the model by scaling the linear density contrast by a parameter ν. While the resulting baryonic density is still lognormal, the additional parameter gives us extra freedom in setting the variance of density fluctuations. With this extension, values of T 0 and γ implied in the SPH simulations are recovered at ∼ 1 - σ (≲ 10%) of the median (best-fit) values for most redshifts bins. However, this extended lognormal model cannot recover Γ12 reliably, with the best-fit value discrepant by ≳ 3 - σ for z > 2.2. Despite this limitation in the recovery of Γ12, whose origins we explain, we argue that the model remains useful for constraining cosmological parameters.

Emergence of the temperature–density relation in the low-density intergalactic medium

ABSTRACT We examine the evolution of the phase diagram of the low-density intergalactic medium during the Epoch of Reionization in simulation boxes with varying reionization histories from the Cosmic Reionization on Computers project. The probability density function (PDF) of gas temperature at fixed density exhibits two clear modes: a warm and a cold temperature mode, corresponding to the gas inside and outside of ionized bubbles. We find that the transition between the two modes is ‘universal’ in the sense that its timing is accurately parametrized by the value of the volume-weighted neutral fraction for any reionization history. This ‘universality’ is more complex than just a reflection of the fact that ionized gas is warm and neutral gas is cold: it holds for the transition at a fixed value of gas density, and gas at different densities transitions from the cold to the warm mode at different values of the neutral fraction, reflecting a non-trivial relationship between the ionization history and the evolving gas density PDF. Furthermore, the ‘emergence’ of the tight temperature–density relation in the warm mode is also approximately ‘universally’ controlled by the volume-weighted neutral fraction for any reionization history. In particular, the ‘emergence’ of the temperature–density relation (as quantified by the rapid decrease in its width) occurs when the neutral fraction is 10−4 ≲ XH i ≲ 10−3 for any reionization history. Our results indicate that the neutral fraction is a primary quantity controlling the various properties of the temperature–density relation, regardless of reionization history.

Evaluating the elastic behaviour of boron nitride nanotube (BNNT) reinforced phenolic nanocomposites

The present analysis concerns investigation of the elastic behavior of boron nitride nanotube (BNNT)-reinforced phenolic nanocomposite using molecular dynamics (MD) simulations. In the investigation, an armchair BNNT with chiral vectors (10, 10) was used as reinforcement and novolac-type phenolic chains and formaldehyde mixture was used as a matrix. The crosslinking of phenolic chains and formaldehyde mixture was achieved to obtain the three-dimensional crosslinked structure reinforced with BNNT. In addition to the tensile elastic modulus, the glass transition temperature was evaluated for the bulk phenolic resin and the nanocomposite using the density-temperature relationship. Based on the results, it was concluded that 6.8% (volume fraction) of BNNT can enhance the elastic modulus of the composite by ∼15 times. Poisson’s ratio was found to be independent of the mixing ratio. It was also observed that reinforcement with BNNT can enhance the glass transition temperature of the nanocomposite. Continuum-based rule of mixture showed a good correlation with the MD predictions.

The Origin of Anomalous Density Behavior of Silica Glass.

The anomalous density-temperature relationship of vitreous silica with low hydroxyl content is explained by the formation of medium-range ordering structure in the glass transition process. The ordered medium-range structure has the shape of a "nanoflake" and consists of two layers of SiO4 tetrahedra, bonded by O atoms located in the middle of the structure. The nanoflakes interact with their surrounding structures through both covalent chemical bonds and van der Waals bonds. In the formation of the van der Waals bonds, the orientation of SiO4 tetrahedra can change, which results in an increase in distance between the nanoflakes and their surrounding structures. Thus, there is a slight volume enlargement associated with the formation of nanoflakes. Since the nanoflakes' formation starts at a temperature near 1480 °C, and the population of the nanoflakes grows continuously as temperature decreases until about 950 °C, the bulk volume of silica glass increases in the temperature range from about 1480 °C to 950 °C. Therefore, the density anomaly of silica glass can be explained as a byproduct of forming of medium-range ordering structure in the silica glass transition.

Analysis of entropy generation in nonlinear convection flow of unsteady magneto-nanofluid configured by vertical stretching sheet with Ohmic heating

As a new kind of heat transfer liquid, nanofluids may be thought of as an efficient medium for increasing energy transmission. The concept of energy enhancement via nanofluids is covered in this study. Copper (Cu), copper oxide (CuO), aluminium oxide (Al2O3), and titanium dioxide (TiO2) are the forms of water-based nanofluids that are considered to examine the impact of entropy generation analysis on the unsteady nanofluid flow and heat transfer across a vertical plate with the influence of viscous dissipation. The nonlinear temperature density relation is implemented to address thermal transport issues. By appropriate similarity conversion, the leading equations are transformed into their dimensionless form. The successive linearisation (SL) technique plus the Chebyshev collocation method is employed to solve the dimensionless equations. Effects of emerging parameters are graphed on the profiles of skin friction, Nusselt number, entropy generation, temperature and velocity while the error plot is demonstrated to assess the method's quick convergence characteristics. The result shows that by adjusting the convection parameter, the skin drag fast declines for Cu-water-based nanofluid. However, the heat transfer rate increases in the absence of a convection parameter. Further, the entropy generation rate is boosted as the Reynolds number and volume fraction parameter.

The Rayleigh–Bénard problem for water with maximum density effects

Linear stability and weakly nonlinear stability analyses are developed for Rayleigh–Bénard convection in water near 3.98 °C subject to isothermal boundary conditions. The density–temperature relationship (equation of state) is approximated by a cubic polynomial, including linear, quadratic, and cubic terms. The continuity equation, the Navier–Stokes momentum equation, the equation of state, and the energy equation constitute the governing system. Linear stability analysis is used to investigate how the maximum density property of water affects the onset of convective instability and the choice of unstable wave number for four different types of boundary conditions. Then, a weakly nonlinear stability study is done using the spectral Fourier method for isothermal tangential stress-free boundary conditions to quantify the heat transport of the system and demonstrate the transition from regular/periodic convection to chaotic convection. A Stuart-Ginzburg–Landau equation is obtained using the multiscale expansion method. Streamlines and isotherms are presented and analyzed. The influence of maximum density has been shown to delay the onset of instability and is, therefore, a stabilizing mechanism for thermal instability. Due to the maximum density, the onset of chaotic convection is also delayed. Among four different boundaries, the impermeable rigid boundaries require the highest Rayleigh number for instability to begin. Increasing boundary temperatures advance the onset of chaotic convection and improve the heat transport situation.

The evaluation of density and diffusion properties in hydrogen/oxygen mixture modelled by Lennard-Jones fluid

This paper examines the satisfaction of the principle of corresponding states (PCS) on thepressure–density–temperature relation and the binary diffusion coefficient of hydrogen/oxygen mixture modelled as binary Lennard–Jones (LJ) fluid especially in a supercritical region. The hydrogen/oxygen mixture properties were computed by molecular dynamics simulation and compared with simulation results for a nitrogen/oxygen mixture as well as while using the Peng–Robinson (PR) equation of state (EOS) for both mixture types and a mono-component LJ-EOS. The Fuller–Schettler–Giddings model with the PR-EOS and Takahashi’s EOS were used for binary diffusion coefficient comparison. The pseudocritical point concept of a fluid mixture was applied for PCS reduction and PCS satisfaction was conducted over a wide temperature range above the pseudocritical pressure with changing hydrogen molar fraction. PCS satisfaction for hydrogen/oxygen mixture properties was confirmed at reduced temperature of 1.5 or above. At reduced temperature of 1.0 or below, the hydrogen/oxygen mixture properties disagree with those of the comparison mixture because phase separation occurs. We conclude that the properties of hydrogen/oxygen mixtures can be estimated using the pseudocritical point concept and the investigated EOSs based on the PCS in the supercritical region at reduced temperature of1.5 or above.

Constraining the Temperature-density Relation of the Inter-galactic Medium from Analytically Modeling Lyα Forest Absorbers

The absorption by neutral hydrogen in the intergalactic medium (IGM) produces the Lyα forest in the spectra of quasars. The Lyα forest absorbers have a broad distribution of neutral hydrogen column density N H I and Doppler b parameter. The narrowest Lyα absorption lines (of lowest b) with neutral hydrogen column density above ∼1013cm−2 are dominated by thermal broadening, which can be used to constrain the thermal state of the IGM. Here we constrain the temperature-density relation of the IGM at 1.6 < z < 3.6 by using N H I and b parameters measured from 24 high-resolution and high-signal-to-noise quasar spectra and by employing an analytic model to model the N H I-dependent low-b cutoff in the b distribution. In each N H I bin, the b cutoff is estimated using two methods, one non-parametric method from computing the cumulative b distribution and a parametric method from fitting the full b distribution. We find that the IGM temperature T 0 at the mean gas density shows a peak of ∼1.5 × 104 K at z ∼ 2.7–2.9. At redshift higher than this, the index γ approximately remains constant, and it starts to increase toward lower redshifts. The evolution in both parameters is in good agreement with constraints from completely different approaches, which signals that He ii reionization completes around z ∼ 3.

Lognormal seminumerical simulations of the Lyman α forest: comparison with full hydrodynamic simulations

ABSTRACTObservations of the Lyman α (Ly α) forest in spectra of distant quasars enable us to probe the matter power spectrum at relatively small scales. With several upcoming surveys, it is expected that there will be a many-fold increase in the quantity and quality of data, and hence it is important to develop efficient simulations to forward model these data sets. One such seminumerical method is based on the assumption that the baryonic densities in the intergalactic medium (IGM) follow a lognormal distribution. In this work, we test the robustness of the lognormal model of the Ly α forest in recovering a set of IGM parameters by comparing with high-resolution Sherwood smoothed particle hydrodynamics (SPH) simulations. We study the recovery of the parameters T0 (temperature of the mean-density IGM), γ (slope of the temperature–density relation), and Γ12 (hydrogen photoionization rate) at z ∼ 2.5 using a Markov chain Monte Carlo technique for parameter estimation. Using three flux statistics, the probability distribution, the mean flux, and the power spectrum, values of all three parameters, T0, γ, and Γ12, implied in the SPH simulations are recovered within 1 − σ (∼9, 4, and 1 per cent, respectively) of the median (best-fitting) values. We verify the validity of our results at different baryon smoothing filter, signal-to-noise ratio, box size and resolution, and data seed and confirm that the lognormal model can be used as an efficient tool for modelling the Ly α transmitted flux at z ∼ 2.5.

The Cheng-Minkowycz problem for quadratic convective and radiative heat transfer in a nanofluid saturated porous medium: A revised model

The characteristics of heat transport in a porous medium saturated by a nanoliquid subject to non-linear variations of density-temperature relation and a novel quadratic thermal radiation are studied. For the first time, the well-known Cheng-Minkowycz problem was revisited by nonlinear convection and radiation. The governing equations, based on Darcy's law and Buongiorno's model, are simplified using boundary layer theory, which is further solved by the finite element method. The parameterization of the problem is used to describe the characteristics of the Boussinesq quadratic approximation, Brownian diffusion, quadratic radiation, thermophoretic diffusion, and no-mass flux conditions on the rheological and heat transport features. Our results demonstrate that the rate of heat transport (Nusselt number) is reduced due to thermophoretic diffusion, and the rate of reduction increases with increasing Lewis number values. The Nusselt number is improved due to increasing the values of the Brownian motion parameter at the rate of 0.00616835 and 0.00113362 for the cases of linear thermal radiation and quadratic thermal radiation, respectively. The improvement/reduction rate of the Nusselt number is higher for the case of quadratic thermal convection than for linear thermal convection. Furthermore, the heat transfer rate is achieved for the convection parameter, temperature ratio, and radiation parameter.

Maximum density perspectives on the stability of Brinkman porous convection in a vertical channel

The stability of parallel buoyant flow is studied in a vertical layer of Brinkman porous medium possessing a density maximum in its interior with quadratic density law. The vertical boundaries are considered to be rigid and maintained at different uniform temperatures. The similarities and differences between the linear and quadratic density-temperature relationships on the base flow, stability features of fluid flow, and the mode of instability are underlined. If the flow is governed by classical Darcy's law, then it is proved analytically that the base flow remains unconditionally stable irrespective of how the density varies with temperature. On the contrary, the change in the density-temperature relationship affects the stability of base flow when the flow is governed by either unsteady Darcy's law or the Brinkman-extended Darcy law and for these cases, the eigenvalue problem is solved numerically. For the unsteady Darcy flow model, instability occurs through the traveling-wave mode in a certain range of Darcy–Prandtl number for the quadratic density law yet the base flow is always stable if the density law is linear. The nature of the density-temperature relationship and the magnitude of governing parameters combine together in influencing the instability of fluid flow in the Brinkman regime. The possibility of otherwise stabilization of the base flow becoming unstable with the change in the density-temperature relationship from linear to quadratic for the same values of governing parameters is identified. These intricacies are discussed in detail by computing the critical stability parameters for different values of the Darcy–Prandtl number and the Darcy number.

Outlook of Density Maximum on the Onset of Forchheimer-Bénard Convection with throughflow

The vertical throughflow effect is investigated on the onset of porous convection by considering a cubic density-temperature relationship and using the Forchheimer-Darcy model. The stability eigenvalue problem is explained numerically using the Galerkin technique. Contrary to the linear density-temperature relationship, the direction of throughflow alters the onset of convection. The throughflow dependent Péclet number is found to stabilize the fluid motion against convection and the upflow is found to be either stabilizing or destabilizing than the downflow depending on the values of thermal condition parameters λ1 and λ2. A destabilizing effect on the onset is observed with increasing λ1 and λ2. The Darcy number Da and the Forchheimer drag co-efficient, cb instability characteristics have been investigated and depicted graphically.

A new approach for the equation of state of pure neutron matter using the quantum second virial coefficient with the Reid-93 soft-core potential

In this work, a new approach is presented for determining the equation of state for pure neutron matter. This is valid in the temperature- and density-regime where the system behaves like a nonideal gas. Further, the calculations involved are confined to the nonrelativistic and low-energy ([Formula: see text] 150 MeV) regime. The approach is based on evaluating the quantum second virial coefficient [Formula: see text] of the system, where the input potential is the Reid-93 soft-core potential for [Formula: see text], together with the one-pion-exchange potential (OPEP) for higher [Formula: see text]. The many-body phase shifts are determined within the framework of a generalized scattering theory, taken here as the Galitskii–Migdal–Feynman formalism. The integral equations involved are solved using a highly-accurate matrix-inversion method. These medium phase shifts are then inserted in the Beth–Uhlenbeck formula to determine [Formula: see text]. Once this coefficient has been calculated, other thermophysical properties of the system can be readily computed according to standard expressions. Specifically, these properties include the equation of state (pressure–temperature–density relations), Helmholtz (free) energy, entropy, mean internal energy, specific heat capacity and chemical potential. Our results are compared, whenever possible, to those of previous calculations. The agreement is, on the whole, fair considering that the available calculations vary considerably among themselves.

Thermistor string corrections in data from very weakly stratified deep-ocean waters

An important parameter for observational studies on dynamical variations of the ocean is temperature (T) which determines density variations together with salinity. While the achievement of high absolute accuracy of T-sensors is a formidable task, even the maintaining of high precision is difficult for any long-term deep-ocean observations. This is because the deep ocean is very weakly stably stratified in density, in which all the dynamics is covered by a range of about 0.001 °C. One requires high-resolution T-sensors with low noise levels and precisely calibrated. However, common Negative Temperature Coefficient (NTC) thermistor T-sensors have electronic drift causing a bias of temperature with time. The drift rate varies with temperature (change) and time (age) between 0.0002 and 0.001 °C wk−1 for T-sensors used here. A string of such T-sensors moored in the open-ocean for more than a month after calibration requires a drift-correction. When moored in the deep-ocean, a secondary correction is necessary even immediately after calibration. Secondary correction uses reference layers that are homogeneous to within 0.00005 °C over 100 m vertically plus an additional polynomial correction to remove remaining bias prior or after the reference date. Secondary correction may also involve pressure information on surface tides and mooring deflection. In this paper, secondary corrections are described for two cases of data. For one case from the West-Mediterranean varying temperature-density relationship and near-homogeneous conditions exist. The other is from hadal-deep instruments on a long mooring line in the Challenger Deep, Mariana Trench, affected by tidal flow. Nearby shipborne CTD-data are always needed to establish the temperature-density relationship and the background vertical temperature slope to which the moored T-sensor data are referenced. The stability of moored T-sensors is compared with that of temperature sensors of CTD.

How the area of solar coronal holes affects the properties of high-speed solar wind streams near Earth: An analytical model

Since the 1970s it has been empirically known that the area of solar coronal holes affects the properties of high-speed solar wind streams (HSSs) at Earth. We derive a simple analytical model for the propagation of HSSs from the Sun to Earth and thereby show how the area of coronal holes and the size of their boundary regions affect the HSS velocity, temperature, and density near Earth. We assume that velocity, temperature, and density profiles form across the HSS cross section close to the Sun and that these spatial profiles translate into corresponding temporal profiles in a given radial direction due to the solar rotation. These temporal distributions drive the stream interface to the preceding slow solar wind plasma and disperse with distance from the Sun. The HSS properties at 1 AU are then given by all HSS plasma parcels launched from the Sun that did not run into the stream interface at Earth distance. We show that the velocity plateau region of HSSs as seen at 1 AU, if apparent, originates from the center region of the HSS close to the Sun, whereas the velocity tail at 1 AU originates from the trailing boundary region. Small HSSs can be described to entirely consist of boundary region plasma, which intrinsically results in smaller peak velocities. The peak velocity of HSSs at Earth further depends on the longitudinal width of the HSS close to the Sun. The shorter the longitudinal width of an HSS close to the Sun, the more of its “fastest” HSS plasma parcels from the HSS core and trailing boundary region have impinged upon the stream interface with the preceding slow solar wind, and the smaller is the peak velocity of the HSS at Earth. As the longitudinal width is statistically correlated to the area of coronal holes, this also explains the well-known empirical relationship between coronal hole areas and HSS peak velocities. Further, the temperature and density of HSS plasma parcels at Earth depend on their radial expansion from the Sun to Earth. The radial expansion is determined by the velocity gradient across the HSS boundary region close to the Sun and gives the velocity-temperature and density-temperature relationships at Earth their specific shape. When considering a large number of HSSs, the assumed correlation between the HSS velocities and temperatures close to the Sun degrades only slightly up to 1 AU, but the correlation between the velocities and densities is strongly disrupted up to 1 AU due to the radial expansion. Finally, we show how the number of particles of the piled-up slow solar wind in the stream interaction region depends on the velocities and densities of the HSS and preceding slow solar wind plasma.

A Hydro-particle-mesh Code for Efficient and Rapid Simulations of the Intracluster Medium

Abstract We introduce the cosmological HYPER code based on an innovative hydro-particle-mesh (HPM) algorithm for efficient and rapid simulations of gas and dark matter. For the HPM algorithm, we update the approach of Gnedin &amp; Hui to expand the scope of its application from the lower-density intergalactic medium (IGM) to the higher-density intracluster medium (ICM). While the original algorithm tracks only one effective particle species, the updated version separately tracks the gas and dark matter particles, as they do not exactly trace each other on small scales. For the approximate hydrodynamics solver, the pressure term in the gas equations of motion is calculated using robust physical models. In particular, we use a dark matter halo model, ICM pressure profile, and IGM temperature–density relation, all of which can be systematically varied for parameter-space studies. We show that the HYPER simulation results are in good agreement with the halo model expectations for the density, temperature, and pressure radial profiles. Simulated galaxy cluster scaling relations for Sunyaev–Zel’dovich (SZ) and X-ray observables are also in good agreement with mean predictions, with scatter comparable to that found in hydrodynamic simulations. HYPER also produces lightcone catalogs of dark matter halos and full-sky tomographic maps of the lensing convergence, SZ effect, and X-ray emission. These simulation products are useful for testing data analysis pipelines, generating training data for machine learning, understanding selection and systematic effects, and for interpreting astrophysical and cosmological constraints.