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Kentaro Nagamine - One of the best experts on this subject based on the ideXlab platform.
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Connecting the Dots: Tracking Galaxy Evolution Using Constant Cumulative Number Density at 3
The Astrophysical Journal, 2016Co-Authors: Jason Jaacks, Steven L. Finkelstein, Kentaro NagamineAbstract:Using the cosmological smoothed particle hydrodynamical code GADGET-3 we make a realistic assessment of the technique of using constant Cumulative Number density as a tracer of galaxy evolution at high redshift. We find that over a redshift range of $3\leq z \leq7$ one can on average track the growth of the stellar mass of a population of galaxies selected from the same Cumulative Number density bin to within $\sim 0.20$ dex. Over the stellar mass range we probe ($10^{10.39}\leq M_s/M_\odot \leq 10^{10.75}$ at $z =$ 3 and $10^{8.48}\leq M_s/M_\odot \leq 10^{9.55}$ at $z =$ 7) one can reduce this bias by selecting galaxies based on an evolving Cumulative Number density. We find the Cumulative Number density evolution exhibits a trend towards higher values which can be quantified by simple linear formulations going as $-0.10\Delta z$ for descendants and $0.12\Delta z$ for progenitors. Utilizing such an evolving Cumulative Number density increases the accuracy of descendant/progenitor tracking by a factor of $\sim2$. This result is in excellent agreement, within $0.10$ dex, with abundance matching results over the same redshift range. However, we find that our more realistic cosmological hydrodynamic simulations produce a much larger scatter in descendant/progenitor stellar masses than previous studies, particularly when tracking progenitors. This large scatter makes the application of either the constant Cumulative Number density or evolving Cumulative Number density technique limited to average stellar masses of populations only, as the diverse mass assembly histories caused by stochastic physical processes such as gas accretion, mergers, and star formation of individual galaxies will lead to a larger scatter in other physical properties such as metallicity and star-formation rate.
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connecting the dots tracking galaxy evolution using constant Cumulative Number density at 3 z 7
The Astrophysical Journal, 2016Co-Authors: Jason Jaacks, Steven L. Finkelstein, Kentaro NagamineAbstract:Using the cosmological smoothed particle hydrodynamical code GADGET-3 we make a realistic assessment of the technique of using constant Cumulative Number density as a tracer of galaxy evolution at high redshift. We find that over a redshift range of $3\leq z \leq7$ one can on average track the growth of the stellar mass of a population of galaxies selected from the same Cumulative Number density bin to within $\sim 0.20$ dex. Over the stellar mass range we probe ($10^{10.39}\leq M_s/M_\odot \leq 10^{10.75}$ at $z =$ 3 and $10^{8.48}\leq M_s/M_\odot \leq 10^{9.55}$ at $z =$ 7) one can reduce this bias by selecting galaxies based on an evolving Cumulative Number density. We find the Cumulative Number density evolution exhibits a trend towards higher values which can be quantified by simple linear formulations going as $-0.10\Delta z$ for descendants and $0.12\Delta z$ for progenitors. Utilizing such an evolving Cumulative Number density increases the accuracy of descendant/progenitor tracking by a factor of $\sim2$. This result is in excellent agreement, within $0.10$ dex, with abundance matching results over the same redshift range. However, we find that our more realistic cosmological hydrodynamic simulations produce a much larger scatter in descendant/progenitor stellar masses than previous studies, particularly when tracking progenitors. This large scatter makes the application of either the constant Cumulative Number density or evolving Cumulative Number density technique limited to average stellar masses of populations only, as the diverse mass assembly histories caused by stochastic physical processes such as gas accretion, mergers, and star formation of individual galaxies will lead to a larger scatter in other physical properties such as metallicity and star-formation rate.
L. Kebbabi - One of the best experts on this subject based on the ideXlab platform.
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Analysis of Cumulative Number and polarity of creeping discharges initiated at solid/liquid interfaces subjected to AC voltage
2009 IEEE Conference on Electrical Insulation and Dielectric Phenomena, 2009Co-Authors: A. Beroual, L. KebbabiAbstract:This paper deals with the influence of voltage and the nature of solid sample on the Cumulative Number of creeping discharge events and their locations on one voltage cycle. It's shown that the total Number of discharges recorded during 500 cycles of voltage increases significantly with the voltage. The threshold voltage Ui of discharges depends on the kind of material; and the average Number of discharges (n moy ) increases with the dielectric constant, e r , of insulator. For instance, n moy is the highest for Bakelite (e r = 4.8) and the lowest for Polycarbonate (e r = 2.9). On the other hand, n moy of negative discharges seems to be slightly higher than that of positive ones whatever the solid sample and the amplitude of voltage.
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analysis of Cumulative Number and polarity of creeping discharges initiated at solid liquid interfaces subjected to ac voltage
Conference on Electrical Insulation and Dielectric Phenomena, 2009Co-Authors: A. Beroual, L. KebbabiAbstract:This paper deals with the influence of voltage and the nature of solid sample on the Cumulative Number of creeping discharge events and their locations on one voltage cycle. It's shown that the total Number of discharges recorded during 500 cycles of voltage increases significantly with the voltage. The threshold voltage Ui of discharges depends on the kind of material; and the average Number of discharges (n moy ) increases with the dielectric constant, e r , of insulator. For instance, n moy is the highest for Bakelite (e r = 4.8) and the lowest for Polycarbonate (e r = 2.9). On the other hand, n moy of negative discharges seems to be slightly higher than that of positive ones whatever the solid sample and the amplitude of voltage.
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Analysis of Cumulative Number and polarity of creeping discharges initiated at solid/liquid interfaces subjected to AC voltage
2009 IEEE Conference on Electrical Insulation and Dielectric Phenomena, 2009Co-Authors: A. Beroual, L. KebbabiAbstract:This paper deals with the influence of voltage and the nature of solid sample on the Cumulative Number of creeping discharge events and their locations on one voltage cycle. It's shown that the total Number of discharges recorded during 500 cycles of voltage increases significantly with the voltage. The threshold voltage Ui of discharges depends on the kind of material; and the average Number of discharges (nmoy) increases with the dielectric constant, ¿r, of insulator. For instance, nmoy is the highest for Bakelite (¿r = 4.8) and the lowest for Polycarbonate (¿r = 2.9). On the other hand, nmoy of negative discharges seems to be slightly higher than that of positive ones whatever the solid sample and the amplitude of voltage.
S. F. Tebbens - One of the best experts on this subject based on the ideXlab platform.
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UPPER-TRUNCATED POWER LAW DISTRIBUTIONS
Fractals, 2001Co-Authors: Stephen M. Burroughs, S. F. TebbensAbstract:Power law Cumulative Number-size distributions are widely used to describe the scaling properties of data sets and to establish scale invariance. We derive the relationships between the scaling exponents of non-Cumulative and Cumulative Number-size distributions for linearly binned and logarithmically binned data. Cumulative Number-size distributions for data sets of many natural phenomena exhibit a "fall-off" from a power law at the largest object sizes. Previous work has often either ignored the fall-off region or described this region with a different function. We demonstrate that when a data set is abruptly truncated at large object size, fall-off from a power law is expected for the Cumulative distribution. Functions to describe this fall-off are derived for both linearly and logarithmically binned data. These functions lead to a generalized function, the upper-truncated power law, that is independent of binning method. Fitting the upper-truncated power law to a Cumulative Number-size distribution determines the parameters of the power law, thus providing the scaling exponent of the data. Unlike previous approaches that employ alternate functions to describe the fall-off region, an upper-truncated power law describes the data set, including the fall-off, with a single function.
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Upper-truncated Power Laws in Natural Systems
Pure and Applied Geophysics, 2001Co-Authors: Stephen M. Burroughs, S. F. TebbensAbstract:— When a Cumulative Number-size distribution of data follows a power law, the data set is often considered fractal since both power laws and fractals are scale invariant. Cumulative Number-size distributions for data sets of many natural phenomena exhibit a “fall-off ” from a power law as the measured object size increases. We demonstrate that this fall-off is expected when a Cumulative data set is truncated at large object size. We provide a generalized equation, herein called the General Fitting Function (GFF), that describes an upper-truncated Cumulative Number-size distribution based on a power law. Fitting the GFF to a Cumulative Number-size distribution yields the coefficient and exponent of the underlying power law and a parameter that characterizes the upper truncation. Possible causes of upper truncation include data sampling limitations (spatial or temporal) and changes in the physics controlling the object sizes. We use the GFF method to analyze four natural systems that have been studied by other approaches: forest fire area in the Australian Capital Territory; fault offsets in the Vernejoul coal field; hydrocarbon volumes in the Frio Strand Plain exploration play; and fault lengths on Venus. We demonstrate that a traditional approach of fitting a power law directly to the Cumulative Number-size distribution estimates too negative an exponent for the power law and overestimates the fractal dimension of the data set. The four systems we consider are well fit by the GFF method, suggesting they have properties characterized by upper-truncated power laws.
Mark Vogelsberger - One of the best experts on this subject based on the ideXlab platform.
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forward and backward galaxy evolution in comoving Cumulative Number density space
Monthly Notices of the Royal Astronomical Society, 2017Co-Authors: Paul Torrey, Sarah Wellons, Philip F Hopkins, Mark VogelsbergerAbstract:Galaxy Cumulative comoving Number density is commonly used to forge progenitor/descendant links between observed galaxy populations at different epochs. However, this method breaks down in the presence of galaxy mergers, or when galaxies experience stochastic growth rates. We present a simple analytic framework to treat the physical processes that drive the evolution and diffusion of galaxies within comoving Number density space. The evolution in mass rank order of a galaxy population with time is influenced by (1) the non-conservative nature of total galaxy Number density driven by galaxies combining in mergers (which we tabulate as a galaxy ‘coagulation’ rate) and (2) galaxy ‘mass rank scatter’ driven by stochasticity in stellar-mass growth rates from in situ star formation and mergers. We quantify the relative contribution of these two effects to the total mass rank order evolution using the Illustris simulation. We show that galaxy coagulation is dominant at lower redshifts and stellar masses, while scattered growth rates dominate the mass rank evolution at higher redshifts and stellar masses. For a galaxy population at 10^(10) M⊙, coagulation has been the dominant effect since z = 2.2, but a galaxy population at 10^(11) M⊙ was dominated by mass rank scatter until z = 0.6. We show that although the forward and backward median Cumulative Number density evolution tracks are asymmetric, the backward median Cumulative Number density evolution can be obtained by convolving the descendant distribution function with progenitor relative abundances. We tabulate fits for the median Cumulative Number density evolution and scatter that can be applied to improve the way galaxy populations are linked in multi-epoch observational data sets.
Peter Behroozi - One of the best experts on this subject based on the ideXlab platform.
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using Cumulative Number densities to compare galaxies across cosmic time
The Astrophysical Journal, 2013Co-Authors: Peter Behroozi, Danilo Marchesini, Risa H Wechsler, Adam Muzzin, Casey Papovich, Mauro StefanonAbstract:Comparing galaxies across redshifts at fixed Cumulative Number density is a popular way to estimate the evolution of specific galaxy populations. This method ignores scatter in mass accretion histories and galaxy-galaxy mergers, which can lead to errors when comparing galaxies over large redshift ranges (Δz > 1). We use abundance matching in the ΛCDM paradigm to estimate the median change in Cumulative Number density with redshift and provide a simple fit (+0.16 dex per unit Δz) for progenitors of z = 0 galaxies. We find that galaxy descendants do not evolve in the same way as galaxy progenitors, largely due to scatter in mass accretion histories. We also provide estimates for the 1σ range of Cumulative Number densities corresponding to galaxy progenitors and descendants. Finally, we discuss some limits on Cumulative Number density comparisons, which arise due to difficulties measuring physical quantities (e.g., stellar mass) consistently across redshifts. A public tool to calculate Cumulative Number density evolution for galaxies, as well as approximate halo masses, is available online.
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Using Cumulative Number Densities to Compare Galaxies Across Cosmic Time
2013Co-Authors: Peter BehrooziAbstract:Abstract Not Provide
