scholarly journals Non-equilibrium response and slow equilibration in hard disk systems

2021 ◽  
Vol 249 ◽  
pp. 14004
Author(s):  
Daigo Mugita ◽  
Masaharu Isobe
Keyword(s):  
Large Scale ◽  
Initial Conditions ◽  
Local Density ◽  
Orientational Order ◽  
Hard Disk ◽  
Equilibrium Response ◽  
Equilibration Process ◽  
Liquid States ◽  
Large Scale Simulations ◽  
Non Equilibrium

The relaxation from a non-equilibrium state to the equilibrium depends on the methodologies and initial conditions. To investigate the microscopic mechanisms of equilibration systematically, we focus on the non-equilibrium response during the equilibration process induced by a disturbance of the homogeneous expansion of the simple hard disk systems. Large scale simulations by event-driven molecular dynamics revealed that an anomalous slow equilibration toward the liquid states emerges when starting from the co-existence phase. The origin of the slow decay mechanism is investigated using the probability distribution of local density and orientational order parameter.Their inhomogeneities seem to cause the anomalous slow equilibration.

scholarly journals The Early Growth of the First Black Holes

2016 ◽  
Vol 33 ◽  
Author(s):  
Jarrett L. Johnson ◽  
Francesco Haardt
Keyword(s):  
Black Holes ◽  
Large Scale ◽  
Initial Conditions ◽  
Big Bang ◽  
Massive Black Holes ◽  
The Past ◽  
Stages Of Growth ◽  
The Big Bang ◽  
Large Scale Simulations ◽  
Cosmic History

AbstractWith detections of quasars powered by increasingly massive black holes at increasingly early times in cosmic history over the past decade, there has been correspondingly rapid progress made on the theory of early black hole formation and growth. Here, we review the emerging picture of how the first massive black holes formed from the primordial gas and then grew to supermassive scales. We discuss the initial conditions for the formation of the progenitors of these seed black holes, the factors dictating the initial masses with which they form, and their initial stages of growth via accretion, which may occur at super-Eddington rates. Finally, we briefly discuss how these results connect to large-scale simulations of the growth of supermassive black holes in the first billion years after the Big Bang.

An HPC Framework for Large Scale Simulations and Visualizations of Oil Spill Trajectories

2013 ◽  
Author(s):  
Jian Tao ◽  
Werner Benger ◽  
Kelin Hu ◽  
Edwin Mathews ◽  
Marcel Ritter ◽  
...  
Keyword(s):  
Oil Spill ◽  
Large Scale ◽  
Large Scale Simulations

scholarly journals Measuring sleep regularity: Theoretical properties and practical usage of existing metrics

SLEEP ◽  
2021 ◽  
Author(s):  
Dorothee Fischer ◽  
Elizabeth B Klerman ◽  
Andrew J K Phillips
Keyword(s):  
Large Scale ◽  
Research Question ◽  
Group Differences ◽  
Regularity Index ◽  
Wake Patterns ◽  
Health Related ◽  
Phase Deviation ◽  
Unbiased Estimates ◽  
Large Scale Simulations ◽  
Larger Sample

Abstract Study Objectives Sleep regularity predicts many health-related outcomes. Currently, however, there is no systematic approach to measuring sleep regularity. Traditionally, metrics have assessed deviations in sleep patterns from an individual’s average. Traditional metrics include intra-individual standard deviation (StDev), Interdaily Stability (IS), and Social Jet Lag (SJL). Two metrics were recently proposed that instead measure variability between consecutive days: Composite Phase Deviation (CPD) and Sleep Regularity Index (SRI). Using large-scale simulations, we investigated the theoretical properties of these five metrics. Methods Multiple sleep-wake patterns were systematically simulated, including variability in daily sleep timing and/or duration. Average estimates and 95% confidence intervals were calculated for six scenarios that affect measurement of sleep regularity: ‘scrambling’ the order of days; daily vs. weekly variation; naps; awakenings; ‘all-nighters’; and length of study. Results SJL measured weekly but not daily changes. Scrambling did not affect StDev or IS, but did affect CPD and SRI; these metrics, therefore, measure sleep regularity on multi-day and day-to-day timescales, respectively. StDev and CPD did not capture sleep fragmentation. IS and SRI behaved similarly in response to naps and awakenings but differed markedly for all-nighters. StDev and IS required over a week of sleep-wake data for unbiased estimates, whereas CPD and SRI required larger sample sizes to detect group differences. Conclusions Deciding which sleep regularity metric is most appropriate for a given study depends on a combination of the type of data gathered, the study length and sample size, and which aspects of sleep regularity are most pertinent to the research question.

scholarly journals Accelerating In-Transit Co-Processing for Scientific Simulations Using Region-Based Data-Driven Analysis

Algorithms ◽  
2021 ◽  
Vol 14 (5) ◽  
pp. 154
Author(s):  
Marcus Walldén ◽  
Masao Okita ◽  
Fumihiko Ino ◽  
Dimitris Drikakis ◽  
Ioannis Kokkinakis
Keyword(s):  
Large Scale ◽  
Data Driven ◽  
Data Sets ◽  
Output Constraints ◽  
Data Driven Approach ◽  
Scientific Simulations ◽  
Multiple Metrics ◽  
In Transit ◽  
Multiple Compression ◽  
Large Scale Simulations

Increasing processing capabilities and input/output constraints of supercomputers have increased the use of co-processing approaches, i.e., visualizing and analyzing data sets of simulations on the fly. We present a method that evaluates the importance of different regions of simulation data and a data-driven approach that uses the proposed method to accelerate in-transit co-processing of large-scale simulations. We use the importance metrics to simultaneously employ multiple compression methods on different data regions to accelerate the in-transit co-processing. Our approach strives to adaptively compress data on the fly and uses load balancing to counteract memory imbalances. We demonstrate the method’s efficiency through a fluid mechanics application, a Richtmyer–Meshkov instability simulation, showing how to accelerate the in-transit co-processing of simulations. The results show that the proposed method expeditiously can identify regions of interest, even when using multiple metrics. Our approach achieved a speedup of 1.29× in a lossless scenario. The data decompression time was sped up by 2× compared to using a single compression method uniformly.

scholarly journals The anisotropy of the power spectrum in periodic cosmological simulations

2021 ◽  
Vol 503 (4) ◽  
pp. 5638-5645
Author(s):  
Gábor Rácz ◽  
István Szapudi ◽  
István Csabai ◽  
László Dobos
Keyword(s):  
Dark Matter ◽  
Power Spectrum ◽  
Large Scale ◽  
Cold Dark Matter ◽  
Initial Conditions ◽  
Power Spectra ◽  
Cosmological Simulations ◽  
Spherical Collapse ◽  
Lower Amplitude ◽  
Hydrodynamical Simulations

ABSTRACT The classical gravitational force on a torus is anisotropic and always lower than Newton’s 1/r2 law. We demonstrate the effects of periodicity in dark matter only N-body simulations of spherical collapse and standard Lambda cold dark matter (ΛCDM) initial conditions. Periodic boundary conditions cause an overall negative and anisotropic bias in cosmological simulations of cosmic structure formation. The lower amplitude of power spectra of small periodic simulations is a consequence of the missing large-scale modes and the equally important smaller periodic forces. The effect is most significant when the largest mildly non-linear scales are comparable to the linear size of the simulation box, as often is the case for high-resolution hydrodynamical simulations. Spherical collapse morphs into a shape similar to an octahedron. The anisotropic growth distorts the large-scale ΛCDM dark matter structures. We introduce the direction-dependent power spectrum invariant under the octahedral group of the simulation volume and show that the results break spherical symmetry.

scholarly journals EDGE: a new approach to suppressing numerical diffusion in adaptive mesh simulations of galaxy formation

2020 ◽  
Vol 501 (2) ◽  
pp. 1755-1765
Author(s):  
Andrew Pontzen ◽  
Martin P Rey ◽  
Corentin Cadiou ◽  
Oscar Agertz ◽  
Romain Teyssier ◽  
...  
Keyword(s):  
Star Formation ◽  
Galaxy Formation ◽  
Adaptive Mesh Refinement ◽  
Large Scale ◽  
Initial Conditions ◽  
Dwarf Galaxy ◽  
High Redshift ◽  
Morphological Structure ◽  
Adaptive Mesh ◽  
Numerical Diffusion

ABSTRACT We introduce a new method to mitigate numerical diffusion in adaptive mesh refinement (AMR) simulations of cosmological galaxy formation, and study its impact on a simulated dwarf galaxy as part of the ‘EDGE’ project. The target galaxy has a maximum circular velocity of $21\, \mathrm{km}\, \mathrm{s}^{-1}$ but evolves in a region that is moving at up to $90\, \mathrm{km}\, \mathrm{s}^{-1}$ relative to the hydrodynamic grid. In the absence of any mitigation, diffusion softens the filaments feeding our galaxy. As a result, gas is unphysically held in the circumgalactic medium around the galaxy for $320\, \mathrm{Myr}$, delaying the onset of star formation until cooling and collapse eventually triggers an initial starburst at z = 9. Using genetic modification, we produce ‘velocity-zeroed’ initial conditions in which the grid-relative streaming is strongly suppressed; by design, the change does not significantly modify the large-scale structure or dark matter accretion history. The resulting simulation recovers a more physical, gradual onset of star formation starting at z = 17. While the final stellar masses are nearly consistent ($4.8 \times 10^6\, \mathrm{M}_{\odot }$ and $4.4\times 10^6\, \mathrm{M}_{\odot }$ for unmodified and velocity-zeroed, respectively), the dynamical and morphological structure of the z = 0 dwarf galaxies are markedly different due to the contrasting histories. Our approach to diffusion suppression is suitable for any AMR zoom cosmological galaxy formation simulations, and is especially recommended for those of small galaxies at high redshift.

Brain stem – from general view to computational model based on switchboard rules of operation

2019 ◽  
Vol 16 (1) ◽  
Author(s):  
Włodzisław Duch ◽  
Dariusz Mikołajewski
Keyword(s):  
Brain Stem ◽  
Large Scale ◽  
Ionic Channels ◽  
General View ◽  
The Central Nervous System ◽  
Network States ◽  
Large Scale Simulations ◽  
Influence Of Noise ◽  
The Brain ◽  
Sufficient Precision

Abstract Despite great progress in understanding the functions and structures of the central nervous system (CNS) the brain stem remains one of the least understood systems. We know that the brain stem acts as a decision station preparing the organism to act in a specific way, but such functions are rather difficult to model with sufficient precision to replicate experimental data due to the scarcity of data and complexity of large-scale simulations of brain stem structures. The approach proposed in this article retains some ideas of previous models, and provides more precise computational realization that enables qualitative interpretation of the functions played by different network states. Simulations are aimed primarily at the investigation of general switching mechanisms which may be executed in brain stem neural networks, as far as studying how the aforementioned mechanisms depend on basic neural network features: basic ionic channels, accommodation, and the influence of noise.

scholarly journals Relativistic Cosmology with an Introduction to Inflation

Universe ◽  
2021 ◽  
Vol 7 (8) ◽  
pp. 276
Author(s):  
Muhammad Zahid Mughal ◽  
Iftikhar Ahmad ◽  
Juan Luis García Guirao
Keyword(s):  
Standard Model ◽  
Early Universe ◽  
Large Scale ◽  
Initial Conditions ◽  
Big Bang ◽  
Relativistic Cosmology ◽  
The Standard Model ◽  
Big Bang Model ◽  
The Big Bang ◽  
The Universe

In this review article, the study of the development of relativistic cosmology and the introduction of inflation in it as an exponentially expanding early phase of the universe is carried out. We study the properties of the standard cosmological model developed in the framework of relativistic cosmology and the geometric structure of spacetime connected coherently with it. The geometric properties of space and spacetime ingrained into the standard model of cosmology are investigated in addition. The big bang model of the beginning of the universe is based on the standard model which succumbed to failure in explaining the flatness and the large-scale homogeneity of the universe as demonstrated by observational evidence. These cosmological problems were resolved by introducing a brief acceleratedly expanding phase in the very early universe known as inflation. The cosmic inflation by setting the initial conditions of the standard big bang model resolves these problems of the theory. We discuss how the inflationary paradigm solves these problems by proposing the fast expansion period in the early universe. Further inflation and dark energy in fR modified gravity are also reviewed.

scholarly journals Tropical Cyclone Count Forecasting Using a Dynamical Seasonal Prediction System: Sensitivity to Improved Ocean Initialization

2011 ◽  
Vol 24 (12) ◽  
pp. 2963-2982 ◽  
Author(s):  
Andrea Alessandri ◽  
Andrea Borrelli ◽  
Silvio Gualdi ◽  
Enrico Scoccimarro ◽  
Simona Masina
Keyword(s):  
Tropical Cyclone ◽  
Indian Ocean ◽  
Wind Shear ◽  
Large Scale ◽  
Initial Conditions ◽  
North Pacific Ocean ◽  
Convective Available Potential Energy ◽  
Seasonal Prediction ◽  
Boreal Summer ◽  
Prediction System

Abstract This study investigates the predictability of tropical cyclone (TC) seasonal count anomalies using the Centro Euro-Mediterraneo per i Cambiamenti Climatici–Istituto Nazionale di Geofisica e Vulcanologia (CMCC-INGV) Seasonal Prediction System (SPS). To this aim, nine-member ensemble forecasts for the period 1992–2001 for two starting dates per year were performed. The skill in reproducing the observed TC counts has been evaluated after the application of a TC location and tracking detection method to the retrospective forecasts. The SPS displays good skill in predicting the observed TC count anomalies, particularly over the tropical Pacific and Atlantic Oceans. The simulated TC activity exhibits realistic geographical distribution and interannual variability, thus indicating that the model is able to reproduce the major basic mechanisms that link the TCs’ occurrence with the large-scale circulation. TC count anomalies prediction has been found to be sensitive to the subsurface assimilation in the ocean for initialization. Comparing the results with control simulations performed without assimilated initial conditions, the results indicate that the assimilation significantly improves the prediction of the TC count anomalies over the eastern North Pacific Ocean (ENP) and northern Indian Ocean (NI) during boreal summer. During the austral counterpart, significant progresses over the area surrounding Australia (AUS) and in terms of the probabilistic quality of the predictions also over the southern Indian Ocean (SI) were evidenced. The analysis shows that the improvement in the prediction of anomalous TC counts follows the enhancement in forecasting daily anomalies in sea surface temperature due to subsurface ocean initialization. Furthermore, the skill changes appear to be in part related to forecast differences in convective available potential energy (CAPE) over the ENP and the North Atlantic Ocean (ATL), in wind shear over the NI, and in both CAPE and wind shear over the SI.

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