scholarly journals Accurate Determination of the Lagrangian Bias for the Dark Matter Halos

1999 ◽  
Vol 515 (2) ◽  
pp. L45-L48 ◽  
Author(s):  
Y. P. Jing
Keyword(s):  
Dark Matter ◽  
Accurate Determination ◽  
Dark Matter Halos

scholarly journals Precision Determination of the Mass Function of Dark Matter Halos

2006 ◽  
Vol 646 (2) ◽  
pp. 881-885 ◽  
Author(s):  
Michael S. Warren ◽  
Kevork Abazajian ◽  
Daniel E. Holz ◽  
Luis Teodoro
Keyword(s):  
Dark Matter ◽  
Mass Function ◽  
Dark Matter Halos ◽  
Precision Determination

scholarly journals The emergence of the red sequence at z~2 seen through galaxy clustering in the UKIDSS UDS

2012 ◽  
Vol 8 (S295) ◽  
pp. 105-108
Author(s):  
William G. Hartley ◽  
Omar Almaini ◽  
Alice Mortlock ◽  
Chris Conselice ◽  
Keyword(s):  
Dark Matter ◽  
Cross Correlation ◽  
Near Infrared ◽  
Correlation Technique ◽  
Dark Matter Halos ◽  
Star Forming ◽  
Deep Survey ◽  
Cross Correlation Technique ◽  
Infrared Survey

AbstractWe use the UKIDSS Ultra-Deep Survey, the deepest degree-scale near-infrared survey to date, to investigate the clustering of star-forming and passive galaxies to z ~ 3.5. Our new measurements include the first determination of the clustering for passive galaxies at z > 2, which we achieve using a cross-correlation technique. We find that passive galaxies are the most strongly clustered, typically hosted by massive dark matter halos with Mhalo > 1013 M⊙ irrespective of redshift or stellar mass. Our findings are consistent with models in which a critical halo mass determines the transition from star-forming to passive galaxies.

scholarly journals Testing dark matter halos using rotation curves and lensing: A warning on the determination of the halo mass

2010 ◽  
Vol 82 (2) ◽  
Author(s):  
Darío Núñez ◽  
Alma X. González-Morales ◽  
Jorge L. Cervantes-Cota ◽  
Tonatiuh Matos
Keyword(s):  
Dark Matter ◽  
Dark Matter Halos ◽  
Rotation Curves

scholarly journals Constancy of the cluster gas mass fraction in the R h = ct Universe

2016 ◽  
Vol 472 (2186) ◽  
pp. 20150765 ◽  
Author(s):  
F. Melia
Keyword(s):  
Dark Matter ◽  
Cold Dark Matter ◽  
Accurate Determination ◽  
Information Criterion ◽  
Angular Distance ◽  
Link Type ◽  
Mass Fractions ◽  
Parameter Values ◽  
Baryonic Mass

The ratio of baryonic to dark matter densities is assumed to have remained constant throughout the formation of structure. With this, simulations show that the fraction f gas ( z ) of baryonic mass to total mass in galaxy clusters should be nearly constant with redshift z . However, the measurement of these quantities depends on the angular distance to the source, which evolves with z according to the assumed background cosmology. An accurate determination of f gas ( z ) for a large sample of hot ( kT e >5 keV), dynamically relaxed clusters could therefore be used as a probe of the cosmological expansion up to z <2. The fraction f gas ( z ) would remain constant only when the correct cosmology is used to fit the data. In this paper, we compare the predicted gas mass fractions for both Λ cold dark matter ( Λ CDM) and the R h = ct Universe and test them against the three largest cluster samples (LaRoque et al. 2006 Astrophys. J. 652, 917–936 ( doi:10.1086/508139 ); Allen et al. 2008 Mon. Not. R. Astron. Soc. 383, 879–896 ( doi:10.1111/j.1365-2966.2007.12610.x ); Ettori et al. 2009 Astron. Astrophys. 501, 61–73 ( doi:10.1051/0004-6361/200810878 )). We show that R h = ct is consistent with a constant f gas in the redshift range z ≲ 2 , as was previously shown for the reference Λ CDM model (with parameter values H 0 =70 km s −1  Mpc −1 , Ω m =0.3 and w Λ =−1). Unlike Λ CDM, however, the R h = ct Universe has no free parameters to optimize in fitting the data. Model selection tools, such as the Akaike information criterion and the Bayes information criterion (BIC), therefore tend to favour R h = ct over Λ CDM. For example, the BIC favours R h = ct with a likelihood of approximately 95% versus approximately 5% for Λ CDM.

Measuring Dark Matter Halos by Modeling Interacting Galaxies

2004 ◽  
Vol 220 ◽  
pp. 461-462 ◽  
Author(s):  
Christian Theis
Keyword(s):  
Genetic Algorithm ◽  
Dark Matter ◽  
Parameter Space ◽  
Matter Content ◽  
Interacting Galaxies ◽  
Dark Matter Halo ◽  
Dark Matter Halos ◽  
Characteristic Parameters ◽  
Galactic Dark Matter

The richness of tidal features seen in interacting galaxies allows for the determination of their characteristic parameters, provided one can deal with the extended parameter space. Genetic algorithm based methods – like our code minga – have proven to be such a tool. Here I discuss the implementation of dark matter halo descriptions in the restricted N-body simulations of minga. I show that the final morphology of a galaxy encounter strongly depends on the halo properties. Thus, modeling tidal features of interacting galaxies might allow also for conclusions on the galactic dark matter content.

A quantitative approach to inner shell losses

1978 ◽  
Vol 36 (1) ◽  
pp. 526-527 ◽  
Author(s):  
R.D. Leapman ◽  
P. Rez ◽  
D.F. Mayers
Keyword(s):  
Energy Transfer ◽  
Cross Section ◽  
Cross Sections ◽  
Accurate Determination ◽  
Background Intensity ◽  
Core Excitation ◽  
Quantitative Basis ◽  
Cross Section Differential ◽  
Bound Electrons

Microanalysis by EELS has been developing rapidly and though the general form of the spectrum is now understood there is a need to put the technique on a more quantitative basis (1,2). Certain aspects important for microanalysis include: (i) accurate determination of the partial cross sections, σx(α,ΔE) for core excitation when scattering lies inside collection angle a and energy range ΔE above the edge, (ii) behavior of the background intensity due to excitation of less strongly bound electrons, necessary for extrapolation beneath the signal of interest, (iii) departures from the simple hydrogenic K-edge seen in L and M losses, effecting σx and complicating microanalysis. Such problems might be approached empirically but here we describe how computation can elucidate the spectrum shape.The inelastic cross section differential with respect to energy transfer E and momentum transfer q for electrons of energy E0 and velocity v can be written as

Fast calibration of CBED patterns for quantitative analysis

1993 ◽  
Vol 51 ◽  
pp. 674-675
Author(s):  
M.A. Gribelyuk ◽  
M. Rühle
Keyword(s):  
Reciprocal Lattice ◽  
Accurate Determination ◽  
Incident Beam ◽  
Crystal Thickness ◽  
Structure Model ◽  
Beam Direction ◽  
Transmitted Beam ◽  
Reciprocal Vector ◽  
On Line

A new method is suggested for the accurate determination of the incident beam direction K, crystal thickness t and the coordinates of the basic reciprocal lattice vectors V1 and V2 (Fig. 1) of the ZOLZ plans in pixels of the digitized 2-D CBED pattern. For a given structure model and some estimated values Vest and Kest of some point O in the CBED pattern a set of line scans AkBk is chosen so that all the scans are located within CBED disks.The points on line scans AkBk are conjugate to those on A0B0 since they are shifted by the reciprocal vector gk with respect to each other. As many conjugate scans are considered as CBED disks fall into the energy filtered region of the experimental pattern. Electron intensities of the transmitted beam I0 and diffracted beams Igk for all points on conjugate scans are found as a function of crystal thickness t on the basis of the full dynamical calculation.

Computer-Assisted High-Re Solution TEM

1990 ◽  
Vol 48 (1) ◽  
pp. 162-163
Author(s):  
F.A. Ponce ◽  
H. Hikashi
Keyword(s):  
Signal To Noise Ratio ◽  
Accurate Determination ◽  
Computer Software ◽  
Video Camera ◽  
Image Contrast ◽  
Objective Lens ◽  
Computer Assisted ◽  
Optical Parameters ◽  
Astigmatism Correction

The determination of the atomic positions from HRTEM micrographs is only possible if the optical parameters are known to a certain accuracy, and reliable through-focus series are available to match the experimental images with calculated images of possible atomic models. The main limitation in interpreting images at the atomic level is the knowledge of the optical parameters such as beam alignment, astigmatism correction and defocus value. Under ordinary conditions, the uncertainty in these values is sufficiently large to prevent the accurate determination of the atomic positions. Therefore, in order to achieve the resolution power of the microscope (under 0.2nm) it is necessary to take extraordinary measures. The use of on line computers has been proposed [e.g.: 2-5] and used with certain amount of success.We have built a system that can perform operations in the range of one frame stored and analyzed per second. A schematic diagram of the system is shown in figure 1. A JEOL 4000EX microscope equipped with an external computer interface is directly linked to a SUN-3 computer. All electrical parameters in the microscope can be changed via this interface by the use of a set of commands. The image is received from a video camera. A commercial image processor improves the signal-to-noise ratio by recursively averaging with a time constant, usually set at 0.25 sec. The computer software is based on a multi-window system and is entirely mouse-driven. All operations can be performed by clicking the mouse on the appropiate windows and buttons. This capability leads to extreme friendliness, ease of operation, and high operator speeds. Image analysis can be done in various ways. Here, we have measured the image contrast and used it to optimize certain parameters. The system is designed to have instant access to: (a) x- and y- alignment coils, (b) x- and y- astigmatism correction coils, and (c) objective lens current. The algorithm is shown in figure 2. Figure 3 shows an example taken from a thin CdTe crystal. The image contrast is displayed for changing objective lens current (defocus value). The display is calibrated in angstroms. Images are stored on the disk and are accessible by clicking the data points in the graph. Some of the frame-store images are displayed in Fig. 4.

Constraints on the Clumpiness of Dark Matter Halos Through Heating of Disk Galaxies

2003 ◽  
Vol 10 ◽  
pp. 95-95
Author(s):  
E. Ardi ◽  
T. Tsuchiya ◽  
A. Burkert
Keyword(s):  
Dark Matter ◽  
Disk Galaxies ◽  
Dark Matter Halos

Constrained Simulations of Dark Matter Halos

2006 ◽  
Vol 20 ◽  
pp. 15-18
Author(s):  
Y. Hoffman ◽  
E. Romano-Díaz ◽  
A. Faltenbacher ◽  
D. Jones ◽  
C. Heller ◽  
...  
Keyword(s):  
Dark Matter ◽  
Dark Matter Halos
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