Gravity Simulations Research Articles

Efficiency of Optimized Approaches for Gravity Operator Modeling

Numerical tesseroid and radial-type approaches are presented and compared in terms of their efficiency for deriving the regional geoid height, vertical gravity, and gradiometric anomalies from sea floor topography grids. The vertical gradient function is particularly suitable for representing shorter wavelengths of gravity, typically less than 10 km. These two modeling methods were applied to the Great Meteor guyot in the Atlantic Ocean using its bathymetry. To optimize the computation of high-resolution gravity anomalies, the Armadillo, GSL, and OpenMP libraries were used to provide an environment for fast vector implementation, numerical integration for tesseroid calculation, and parallelization for loop iterations, resulting in a computation speed increase. The tesseroid and radial methods remain equivalent up to a resolution of about 1 min, with the radial method being faster when dealing with a large number of model points for the geoid. Aside from optimization enabling high-resolution gravity simulations, these fast modeling data can be used as the main operators in gravimetric inversion or to reduce the terrain effects in gravity observations, revealing gravity and sedimentary layers.

Multiphysics framework for cost-effective, long-term monitoring of carbon storage in a carbonate reservoir

We evaluate an effective and cost-efficient multiphysics approach for long-term monitoring of carbon storage in carbonate reservoirs. A key focus of our study is to advocate for a cost-effective, long-term monitoring strategy for carbon storage projects through the integration of surface and borehole multiphysics measurements. By leveraging technologies related to electromagnetic (EM) and gravity methods, we present a framework that addresses the monitoring of the dynamic behavior of injected CO2 over an extended period. The modeling setup integrates realistic static reservoir models with simulated dynamic saturation models to provide results as close as possible to real experimental conditions. Results demonstrate the high sensitivity of EM fields to changes in reservoir CO2 saturation, especially when surface-to-reservoir acquisition configurations are adopted. Additionally, gravity simulations, employing three-axis vector surface gravity measurements and borehole vector gravity, effectively capture density variations over time. Our proposed framework highlights the sequential use of seismic imaging for preinjection site characterization and the transition to EM and gravity surveys for continuous monitoring during and after the injection phases. The multiphysics simulation results performed on realistic carbon storage conditions contribute to the evolving landscape of effective geophysical CO2 monitoring technology for reliable long-term reservoir management.

Impact of salt diapir geometry and caprock composition on gravity survey results

With respect to difficulties seismic and magnetotellurics may have in accurate definition of exact salt diapir geometry, we performed various gravity simulations and calculations to investigate such exploration targets. Our motivation included the fact that not much has been done on caprock impact on the gravity signal. A very significant favorable condition is the high contrast of rock density between salt and basin sedimentary formations, especially carbonates. However, this can be more complicate if caprock formation is present. Therefore we defined approximate bulk density of typical caprock formation based on its usual composition, resulting in density values 2.45–2.70 g/cm3.We modelled by forward and inverse procedures the gravity signal Gz of salt diapirs with caprock of variable thickness to demonstrate to which extent the salt diapir negative gravity anomaly may be reduced by the impact of caprock formation. In the tested cases the gravity anomaly was reduced by more than 30% depending on respective caprock composition and thickness. Significant contribution to the delineation of salt diapirs themselves, as well as diapirs hidden under caprock, came from the application of horizontal gravity gradients Gzx. We showed the difference of Gzx spikes indicating the edges of density contacts according to the type of gravity survey – land or airborne. It was also proved by calculating the gravity effect of laboratory analogue models of salt deformation and extrusion.We demonstrated that gravity is still a valuable and relatively cheap tool for in-detail investigations of the salt structures within exploration projects.

Determining the time before or after a galaxy merger event

Aims. This work aims to reproduce the time before or after a merger event of merging galaxies from the IllustrisTNG cosmological simulation using machine learning. Methods. Images of merging galaxies were created in the u, g, r, and i bands from IllustrisTNG. The merger times were determined using the time difference between the last simulation snapshot where the merging galaxies were tracked as two galaxies and the first snapshot where the merging galaxies were tracked as a single galaxy. This time was then further refined using simple gravity simulations. These data were then used to train a residual network (ResNet50), a Swin Transformer (Swin), a convolutional neural network (CNN), and an autoencoder (using a single latent neuron) to reproduce the merger time. The full latent space of the autoencoder was also studied to see if it reproduces the merger time better than the other methods. This was done by reducing the latent space dimensions using Isomap, linear discriminant analysis (LDA), neighbourhood components analysis, sparse random projection, truncated singular value decomposition, and uniform manifold approximation and projection. Results. The CNN is the best of all the neural networks. The performance of the autoencoder was close to the CNN, with Swin close behind the autoencoder. ResNet50 performed the worst. The LDA dimensionality reduction performed the best of the six methods used. The exploration of the full latent space produced worse results than the single latent neuron of the autoencoder. For the test data set, we found a median error of 190 Myr, comparable to the time separation between snapshots in IllustrisTNG. Galaxies more than ≈625 Myr before a merger have poorly recovered merger times, as well as galaxies more than ≈125 Myr after a merger event.

Revisiting the Cosmic String Origin of GW190521.

For the first time we analyze gravitational-wave strain data using waveforms constructed from strong gravity simulations of cosmic string loops collapsing to Schwarzschild black holes; a previously unconsidered source. Since the expected signal is dominated by a black-hole ringdown, it can mimic the observed gravitational waves from high-mass binary black hole mergers. To illustrate this, we consider GW190521, a short duration gravitational-wave event observed in the third LIGO-Virgo-KAGRA observing run. We show that describing this event as a collapsing cosmic string loop is favored over previous cosmic string analyses by an approximate log Bayes factor of 22. The binary black hole hypothesis is still preferred, mostly because the cosmic string remnant is nonspinning. It remains an open question whether a spinning remnant could form from loops with angular momentum, but if possible, it would likely bring into contention the binary black hole preference. Finally, we suggest that searches for ringdown-only waveforms would be a viable approach for identifying collapsing cosmic string events and estimating their event rate. This Letter opens up an important new direction for the cosmic-string and gravitational-wave communities.

Bayesian deep learning for cosmic volumes with modified gravity

Context. The new generation of galaxy surveys will provide unprecedented data that will allow us to test gravity deviations at cosmological scales at a much higher precision than could be achieved previously. A robust cosmological analysis of the large-scale structure demands exploiting the nonlinear information encoded in the cosmic web. Machine-learning techniques provide these tools, but no a priori assessment of the uncertainties. Aims. We extract cosmological parameters from modified gravity (MG) simulations through deep neural networks that include uncertainty estimations. Methods. We implemented Bayesian neural networks (BNNs) with an enriched approximate posterior distribution considering two cases: the first case with a single Bayesian last layer (BLL), and the other case with Bayesian layers at all levels (FullB). We trained both BNNs with real-space density fields and power spectra from a suite of 2000 dark matter-only particle-mesh N-body simulations including MG models relying on MG-PICOLA, covering 256 h−1 Mpc side cubical volumes with 1283 particles. Results. BNNs excel in accurately predicting parameters for Ωm and σ8 and their respective correlation with the MG parameter. Furthermore, we find that BNNs yield well-calibrated uncertainty estimates that overcome the over- and under-estimation issues in traditional neural networks. The MG parameter leads to a significant degeneracy, and σ8 might be one possible explanation of the poor MG predictions. Ignoring MG, we obtain a deviation of the relative errors in Ωm and σ8 by 30% at least. Moreover, we report consistent results from the density field and power spectrum analysis and comparable results between BLL and FullB experiments. This halved the computing time. This work contributes to preparing the path for extracting cosmological parameters from complete small cosmic volumes towards the highly nonlinear regime.

Existence of compact anisotropic stars with Karmarkar–Tolman spacetime

The goal of this study is to investigate various anisotropic spherical distribution of cosmic bodies in f ( R ) gravity, where R is the Ricci scalar. Utilizing three separate mathematical gravity models, Karmarkar and Tolman ansatz is taken to explore the nature of certain compact objects. Graphs are used to evaluate the behavior of structural parameters. Then the energy constraints analyzed to explore the applicability of our calculated results for compact stars. We also address the distribution bahavior of matter variables, the equation of state parameter, the measurement of anisotropic parameter, and the Tolman-Oppenheimer-Volkoff equation. The evaluation of our graphs may provide support for accurate and feasible f ( R ) gravity simulations at both the theoretical and mathematical levels. • The goal of this study is to investigate various anisotropic spherical distribution of cosmic bodies in f ( R ) gravity, where R is the Ricci scalar. • Utilizing three separate mathematical gravity models, Karmarkar and Tolman ansatz is taken to explore the nature of certain compact objects. • Graphs are used to evaluate the behavior of structural parameters, and energy constraints are used to explore the applicability of our calculated results for compact stars. • The evaluation of our graphs may provide support for accurate and feasible f ( R ) gravity simulations at both the theoretical and mathematical levels.

The effect of three body positions on colour preference: An exploration of microgravity and lunar gravity simulations

Understanding the colour preference in microgravity environments will enable better design of future spacecraft and extra-terrestrial environments. In this study, a space station's crew cabin was simulated and evaluated in 33 different colours by 55 participants using a standard body position change methodology in controlled conditions. Three body positions were tested, and included normal sitting position (SP), to reflect terrestrial conditions; −15° head-down (HD) bed rest, to simulate a microgravity state; and 9.6° head-up tilt (HU) bed rest, to simulate a lunar gravity state. VR devices were worn by participants to ensure an immersive environment in which to evaluate the different coloured environments across the three different body positions. The results show that in all colour environments, there was no significant difference in the colour preference between SP and HU, but there was a significant change in the colour preference in HD compared to SP and HU. In the three positions, the participants appeared to prefer lighter colours rather than darker ones, warmer colours in ST and HU, and cool colours in HD. In this short-term simulation study, no evidence of gender differences in colour preference by body position was found, but in each body position, men and women had different preference levels for basic hue and chroma brightness.

Distinguishing between ΛCDM and f(R) gravity models using halo ellipticity correlations in simulations

ABSTRACT There is a growing interest in utilizing intrinsic alignment (IA) of galaxy shapes as a geometric and dynamical probe of cosmology. In this paper, we present the first measurements of IA in a modified gravity model using the gravitational shear-intrinsic ellipticity correlation (GI) and intrinsic ellipticity-ellipticity correlation (II) functions of dark-matter haloes from f(R) gravity simulations. By comparing them with the same statistics measured in Lambda cold dark matter (ΛCDM) simulations, we find that the IA statistics in different gravity models show distinguishable features, with a trend similar to the case of conventional galaxy clustering statistics. Thus, the GI and II correlations are found to be useful in distinguishing between the ΛCDM and f(R) gravity models. More quantitatively, IA statistics enhance detectability of the imprint of f(R) gravity on large-scale structures by $\sim 40{{\ \rm per\ cent}}$ when combined with the conventional halo clustering in redshift space. We also find that the correlation between the axial ratio and orientation of haloes becomes stronger in f(R) gravity than that in ΛCDM. Our results demonstrate the usefulness of IA statistics as a probe of gravity beyond a consistency test of ΛCDM and general relativity.

Fast generation of mock galaxy catalogues in modified gravity models with COLA

We investigate the viability of producing galaxy mock catalogues with COmoving Lagrangian Acceleration (COLA) simulations in Modified Gravity (MG) models employing the Halo Occupation Distribution (HOD) formalism. In this work, we focus on two theories of MG: f(R) gravity with the chameleon mechanism, and a braneworld model (nDGP) that incorporates the Vainshtein mechanism. We use a suite of full N-body simulations in MG as a benchmark to test the accuracy of COLA simulations. At the level of Dark Matter (DM), we show that COLA accurately reproduces the matter power spectrum up to k ∼ 1 h Mpc-1, while it is less accurate in reproducing the velocity field. To produce halo catalogues, we find that the rockstar halo-finder does not perform well with COLA simulations. On the other hand, using a simple Friends-of-Friends (FoF) finder and an empirical mass conversion from FoF to spherical over-density masses, we are able to produce halo catalogues in COLA that are in good agreement with those in N-body simulations. To consider the effects of the MG fifth force on the halo profile, we derive simple fitting formulae for the concentration-mass and the velocity dispersion-mass relations that we calibrate using rockstar halo catalogues in N-body simulations. We then use these results to extend the HOD formalism to modified gravity simulations in COLA. We use an HOD model with five parameters that we tune to obtain galaxy catalogues in redshift space. We find that despite the great freedom of the HOD model, MG leaves characteristic imprints in the redshift space power spectrum multipoles and these features are well captured by the COLA galaxy catalogues.

CO2 storage monitoring using 3-axis borehole gravity

Carbon capture and storage underground (CCS) is now regarded as a vital and significant means to achieve 3 of the 4 IPCC pathways necessary to limit global warming to 1.5degC. Our internal analysis indicates the number of wells required to facilitate the levels of CO2 capture to meet these objectives are numerous over the next 30 years. An understanding of containment is essential for CO2 storage, but few options exist to monitor a CO2 plume growth 100's of metres away from a well. Gravity is a direct measurement of density, through substitution of water by CO2. The gravity measurement detects changes in mass in the subsurface, such that time-lapse wireline-based surveys may be taken to build up a picture of fluid movements at 100’s of meters from the wellbore. By measuring gravity in all three-axis it is possible to determine directional information about the spatial movement of fluid, even when acquired from just a single borehole. We present emerging 3-axis borehole gravity technology that enables the recording of gravitational acceleration at very high sensitivity (targeted at ≈ 5 µGal) using an innovation in resonant Microelectromechanical system (MEMS) vibrating beam technology with the aim of making small, cheap, but highly stable and highly sensitive field and borehole-deployable relative gravimeters. The vibrating beam gravimeter consists of a suspended mass connected to a vibrating beam, such that the inertial force experienced by the mass in gravitational field is communicated as an axial load on the beam. The technology is currently undergoing field trials as part of the CCP* and we show the results of a feasibility study aimed at monitoring CO2 in a deep storage reservoir in Canada which shows the gravity variation likely to be seen due to density changes during a period of CO2 injection. The displacement and substitution of the aquifer water at the storage site over time is referred to as a 4D gravity survey. The cost effectiveness of a 4D wireline gravity survey compared to 4D seismic survey is highly attractive in smaller carbon storage programs. Where the project size or complexity allow both to be run, the complementary nature of the measurements has been noted by several operators. Survey feasibility modelling and a workflow are presented that together provide important information for planning and acquiring a successful gravity survey, as well as the best time interval (given the planned injection rate), and which well location is most suitable to use. The workflow for conducting borehole gravity simulations from time-lapse reservoir models starts with a 3D model of reservoir porosity, saturation and fluid constituent density, which is used to generate a time-lapse density model from the provided set of reservoir simulation data. Vector gravity anomaly responses (gz, gx, and gy) along the wellbore in a variety of well locations are then predicted through forward modelling. The density changes due to fluid substitution are measured by the vertical, gz, gravity anomaly with respect to the reference gravity field. The fluid front progress through the field is assessed through the horizontal gravity anomalies (gx, and gy). Modelling shows plume growth is detectable even over a period of 1 year (Figure 1) and with MEMS technology lifetime monitoring is possible. We conclude that this emerging technology has the potential to provide a solution for long term monitoring of CO2 plume growth within the likely numerous wells that may be needed to fill the CO2 storage requirements resulting from the IPCC pathway scenarios to 1.5degC.

Barred spiral galaxies in modified gravity theories

ABSTRACT When bars form within galaxy formation simulations in the standard cosmological context, dynamical friction with dark matter (DM) causes them to rotate rather slowly. However, almost all observed galactic bars are fast in terms of the ratio between corotation radius and bar length. Here, we explicitly display an 8σ tension between the observed distribution of this ratio and that in the EAGLE simulation at redshift 0. We also compare the evolution of Newtonian galactic discs embedded in DM haloes to their evolution in three extended gravity theories: Milgromian Dynamics (MOND), a model of non-local gravity, and a scalar–tensor–vector gravity theory (MOG). Although our models start with the same initial baryonic distribution and rotation curve, the long-term evolution is different. The bar instability happens more violently in MOND compared to the other models. There are some common features between the extended gravity models, in particular the negligible role played by dynamical friction − which plays a key role in the DM model. Partly for this reason, all extended gravity models predict weaker bars and faster bar pattern speeds compared to the DM case. Although the absence of strong bars in our idealized, isolated extended gravity simulations is in tension with observations, they reproduce the strong observational preference for ‘fast’ bar pattern speeds, which we could not do with DM. We confirm previous findings that apparently ‘ultrafast’ bars can be due to bar-spiral arm alignment leading to an overestimated bar length, especially in extended gravity scenarios where the bar is already fast.

Weak lensing light-cones in modified gravity simulations with and without massive neutrinos

We present a novel suite of cosmological N-body simulations called the DUSTGRAIN-pathfinder, implementing simultaneously the effects of an extension to General Relativity in the form of $f(R)$ gravity and of a non-negligible fraction of massive neutrinos. We describe the generation of simulated weak lensing and cluster counts observables within a past light-cone extracted from these simulations. The simulations have been performed by means of a combination of the MG-GADGET code and a particle-based implementation of massive neutrinos, while the light-cones have been generated using the MapSim pipeline allowing us to compute weak lensing maps through a ray-tracing algorithm for different values of the source plane redshift. The mock observables extracted from our simulations will be employed for a series of papers focussed on understanding and possibly breaking the well-known observational degeneracy between $f(R)$ gravity and massive neutrinos, i.e. the fact that some specific combinations of the characteristic parameters for these two phenomena (the $f_{R0}$ scalar amplitude and the total neutrino mass $\Sigma m_{\nu}$) may result indistinguishable from the standard $\mathrm{\Lambda CDM}$ cosmology through several standard observational probes. In particular, in the present work we show how a tomographic approach to weak lensing statistics could allow - especially for the next generation of wide-field surveys - to disentangle some of the models that appear statistically indistinguishable through standard single-redshift weak lensing probe.

Two-dimensional Core-collapse Supernova Explosions Aided by General Relativity with Multidimensional Neutrino Transport

Abstract We present results from simulations of core-collapse supernovae in FLASH using a newly implemented multidimensional neutrino transport scheme and a newly implemented general relativistic (GR) treatment of gravity. We use a two-moment method with an analytic closure (so-called M1 transport) for the neutrino transport. This transport is multienergy, multispecies, velocity dependent, and truly multidimensional, i.e., we do not assume the commonly used “ray-by-ray” approximation. Our GR gravity is implemented in our Newtonian hydrodynamics simulations via an effective relativistic potential that closely reproduces the GR structure of neutron stars and has been shown to match GR simulations of core collapse quite well. In axisymmetry, we simulate core-collapse supernovae with four different progenitor models in both Newtonian and GR gravity. We find that the more compact proto–neutron star structure realized in simulations with GR gravity gives higher neutrino luminosities and higher neutrino energies. These differences in turn give higher neutrino heating rates (upward of ∼20%–30% over the corresponding Newtonian gravity simulations) that increase the efficacy of the neutrino mechanism. Three of the four models successfully explode in the simulations assuming GREP gravity. In our Newtonian gravity simulations, two of the four models explode, but at times much later than observed in our GR gravity simulations. Our results, in both Newtonian and GR gravity, compare well with several other studies in the literature. These results conclusively show that the approximation of Newtonian gravity for simulating the core-collapse supernova central engine is not acceptable. We also simulate four additional models in GR gravity to highlight the growing disparity between parameterized 1D models of core-collapse supernovae and the current generation of 2D models.

Validating estimates of the growth rate of structure with modified gravity simulations

We perform a validation of estimates of the growth rate of structure, described by the parameter combination $f\sigma_8$, in modified gravity cosmologies. We consider an analysis pipeline based on the redshift-space distortion modelling of the clustering wedges statistic of the galaxy correlation function and apply it to mock catalogues of $\Lambda{\rm CDM}$ and the normal branch of DGP cosmologies. We employ a halo occupation distribution approach to construct our mocks, which we ensure resemble the CMASS sample from BOSS in terms of the total galaxy number density and large scale amplitude of the power spectrum monopole. We show that the clustering wedges model successfully recovers the true growth rate difference between DGP and $\Lambda{\rm CDM}$, even for cases with over 40\% enhancement in $f\sigma_8$ compared to $\Lambda{\rm CDM}$. The unbiased performance of the clustering wedges model allows us to use the growth rate values estimated from the BOSS DR12 data to constrain the cross-over scale $r_c$ of DGP gravity to $\left[r_cH_0\right]^{-1} < 0.97$ ($2\sigma$) or $r_c > 3090\ {\rm Mpc}/h$, cutting into the interesting region of parameter space with $r_c \sim H_0^{-1}$ using constraints from the growth of structure alone.

Probing scalar tensor theories for gravity in redshift space

We present measurements of the spatial clustering statistics in redshift space of various scalar field modified gravity simulations. We utilise the two-point and the three-point correlation functions to quantify the spatial distribution of dark matter halos within these simulations and thus discern between the models. We compare $\Lambda$CDM simulations to various modified gravity scenarios and find consistency with previous work in terms of 2-point statistics in real and redshift-space. However using higher order statistics such as the three-point correlation function in redshift space we find significant deviations from $\Lambda$CDM hinting that higher order statistics may prove to be a useful tool in the hunt for deviations from General Relativity.

Effects of artificial gravity on the cardiovascular system: Computational approach

Artificial gravity has been suggested as a multisystem countermeasure against the negative effects of weightlessness. However, many questions regarding the appropriate configuration are still unanswered, including optimal g-level, angular velocity, gravity gradient, and exercise protocol. Mathematical models can provide unique insight into these questions, particularly when experimental data is very expensive or difficult to obtain. In this research effort, a cardiovascular lumped-parameter model is developed to simulate the short-term transient hemodynamic response to artificial gravity exposure combined with ergometer exercise, using a bicycle mounted on a short-radius centrifuge. The model is thoroughly described and preliminary simulations are conducted to show the model capabilities and potential applications. The model consists of 21 compartments (including systemic circulation, pulmonary circulation, and a cardiac model), and it also includes the rapid cardiovascular control systems (arterial baroreflex and cardiopulmonary reflex). In addition, the pressure gradient resulting from short-radius centrifugation is captured in the model using hydrostatic pressure sources located at each compartment. The model also includes the cardiovascular effects resulting from exercise such as the muscle pump effect. An initial set of artificial gravity simulations were implemented using the Massachusetts Institute of Technology (MIT) Compact-Radius Centrifuge (CRC) configuration. Three centripetal acceleration (artificial gravity) levels were chosen: 1g, 1.2g, and 1.4g, referenced to the subject's feet. Each simulation lasted 15.5 minutes and included a baseline period, the spin-up process, the ergometer exercise period (5 minutes of ergometer exercise at 30W with a simulated pedal cadence of 60RPM), and the spin-down process. Results showed that the cardiovascular model is able to predict the cardiovascular dynamics during gravity changes, as well as the expected steady-state cardiovascular behavior during sustained artificial gravity and exercise. Further validation of the model was performed using experimental data from the combined exercise and artificial gravity experiments conducted on the MIT CRC, and these results will be presented separately in future publications. This unique computational framework can be used to simulate a variety of centrifuge configuration and exercise intensities to improve understanding and inform decisions about future implementation of artificial gravity in space.

Speeding up N-body simulations of modified gravity: Vainshtein screening models

We introduce and demonstrate the power of a method to speed up current iterative techniques for N-body modified gravity simulations. Our method is based on the observation that the accuracy of the final result is not compromised if the calculation of the fifth force becomes less accurate, but substantially faster, in high-density regions where it is relatively weak due to screening. We focus on the nDGP model which employs Vainshtein screening, and test our method by running AMR simulations in which the fifth force on the finer levels of the mesh (high density) is not obtained iteratively, but instead interpolated from coarser levels. The calculation of the standard gravity component of the force still employs the full AMR structure. We show that the impact this has on the matter power spectrum is below 1% for k < 5h/Mpc at 0z = , and even smaller at higher redshift. The impact on halo properties is also small (≲ 3% for abundance, profiles, mass; and ≲ 0.05% for positions and velocities). The method can boost the performance of modified gravity simulations by more than a factor of 10. This allows them to run on timescales similar to GR simulations and to push them to resolution levels that were previously hard to achieve.

Testing the quasi-static approximation in f(R) gravity simulations

Numerical simulations in modified gravity have commonly been performed under the quasi-static approximation—that is, by neglecting the effect of time derivatives in the equation of motion of the scalar field that governs the fifth force in a given modified gravity theory. To test the validity of this approximation, we analyse the case of f(R) gravity beyond this quasi-static limit, by considering effects, if any, these terms have in the matter and velocity divergence cosmic fields. To this end, we use the adaptive mesh refinement code ECOSMOG to study three variants (|fR|= 10−4[F4], 10−5[F5] and 10−6[F6]) of the Hu-Sawicki f(R) gravity model, each of which refers to a different magnitude for the scalar field that generates the fifth force. We find that for F4 and F5, which show stronger deviations from standard gravity, a low-resolution simulation is enough to conclude that time derivatives make a negligible contribution to the matter distribution. The F6 model shows a larger deviation from the quasi-static approximation, but one that diminishes when re-simulated at higher-resolution. We therefore come to the conclusion that the quasi-static approximation is valid for the most practical applications in f(R) cosmologies.

Simulated microgravity: critical review on the use of random positioning machines for mammalian cell culture.

Random Positioning Machines (RPMs) have been used since many years as a ground-based model to simulate microgravity. In this review we discuss several aspects of the RPM. Recent technological development has expanded the operative range of the RPM substantially. New possibilities of live cell imaging and partial gravity simulations, for example, are of particular interest. For obtaining valuable and reliable results from RPM experiments, the appropriate use of the RPM is of utmost importance. The simulation of microgravity requires that the RPM's rotation is faster than the biological process under study, but not so fast that undesired side effects appear. It remains a legitimate question, however, whether the RPM can accurately and reliably simulate microgravity conditions comparable to real microgravity in space. We attempt to answer this question by mathematically analyzing the forces working on the samples while they are mounted on the operating RPM and by comparing data obtained under real microgravity in space and simulated microgravity on the RPM. In conclusion and after taking the mentioned constraints into consideration, we are convinced that simulated microgravity experiments on the RPM are a valid alternative for conducting examinations on the influence of the force of gravity in a fast and straightforward approach.