41,101 research outputs found
The Halo Occupation Distribution of SDSS Quasars
We present an estimate of the projected two-point correlation function (2PCF)
of quasars in the Sloan Digital Sky Survey (SDSS) over the full range of one-
and two-halo scales, 0.02-120 Mpc/h. This was achieved by combining data from
SDSS DR7 on large scales and Hennawi et al. (2006; with appropriate statistical
corrections) on small scales. Our combined clustering sample is the largest
spectroscopic quasar clustering sample to date, containing ~48,000 quasars in
the redshift range 0.4<z<2.5 with median redshift 1.4. We interpret these
precise 2PCF measurements within the halo occupation distribution (HOD)
framework and constrain the occupation functions of central and satellite
quasars in dark matter halos. In order to explain the small-scale clustering,
the HOD modeling requires that a small fraction of z~1.4 quasars,
fsat=(7.4+/-1.4) 10^(-4), be satellites in dark matter halos. At z~1.4, the
median masses of the host halos of central and satellite quasars are
constrained to be Mcen=(4.1+0.3/-0.4) 10^12 Msun/h and Msat=(3.6+0.8/-1.0)
10^14 Msun/h, respectively. To investigate the redshift evolution of the
quasar-halo relationship, we also perform HOD modeling of the projected 2PCF
measured by Shen et al. (2007) for SDSS quasars with median redshift 3.2. We
find tentative evidence for an increase in the mass scale of quasar host
halos---the inferred median mass of halos hosting central quasars at z~3.2 is
Mcen=(14.1+5.8/-6.9) 10^12 Msun/h. The cutoff profiles of the mean occupation
functions of central quasars reveal that quasar luminosity is more tightly
correlated with halo mass at higher redshifts. The average quasar duty cycle
around the median host halo mass is inferred to be fq=(7.3+0.6/-1.5) 10^(-4) at
z~1.4 and fq=(8.6+20.4/-7.2) 10^(-2) at z~3.2. We discuss the implications of
our results for quasar evolution and quasar-galaxy co-evolution.Comment: matches the ApJ published versio
Solving the G-problems in less than 500 iterations: Improved efficient constrained optimization by surrogate modeling and adaptive parameter control
Constrained optimization of high-dimensional numerical problems plays an
important role in many scientific and industrial applications. Function
evaluations in many industrial applications are severely limited and no
analytical information about objective function and constraint functions is
available. For such expensive black-box optimization tasks, the constraint
optimization algorithm COBRA was proposed, making use of RBF surrogate modeling
for both the objective and the constraint functions. COBRA has shown remarkable
success in solving reliably complex benchmark problems in less than 500
function evaluations. Unfortunately, COBRA requires careful adjustment of
parameters in order to do so.
In this work we present a new self-adjusting algorithm SACOBRA, which is
based on COBRA and capable to achieve high-quality results with very few
function evaluations and no parameter tuning. It is shown with the help of
performance profiles on a set of benchmark problems (G-problems, MOPTA08) that
SACOBRA consistently outperforms any COBRA algorithm with fixed parameter
setting. We analyze the importance of the several new elements in SACOBRA and
find that each element of SACOBRA plays a role to boost up the overall
optimization performance. We discuss the reasons behind and get in this way a
better understanding of high-quality RBF surrogate modeling
Imaging starspot evolution on Kepler target KIC 5110407 using light curve inversion
The Kepler target KIC 5110407, a K-type star, shows strong quasi-periodic
light curve fluctuations likely arising from the formation and decay of spots
on the stellar surface rotating with a period of 3.4693 days. Using an
established light-curve inversion algorithm, we study the evolution of the
surface features based on Kepler space telescope light curves over a period of
two years (with a gap of .25 years). At virtually all epochs, we detect at
least one large spot group on the surface causing a 1-10% flux modulation in
the Kepler passband. By identifying and tracking spot groups over a range of
inferred latitudes, we measured the surface differential rotation to be much
smaller than that found for the Sun. We also searched for a correlation between
the seventeen stellar flares that occurred during our observations and the
orientation of the dominant surface spot at the time of each flare. No
statistically-significant correlation was found except perhaps for the very
brightest flares, suggesting most flares are associated with regions devoid of
spots or spots too small to be clearly discerned using our reconstruction
technique. While we may see hints of long-term changes in the spot
characteristics and flare statistics within our current dataset, a longer
baseline of observation will be needed to detect the existence of a magnetic
cycle in KIC 5110407.Comment: 32 pages, 15 figures, accepted to Ap
Experimental design trade-offs for gene regulatory network inference: an in silico study of the yeast Saccharomyces cerevisiae cell cycle
Time-series of high throughput gene sequencing data intended for gene
regulatory network (GRN) inference are often short due to the high costs of
sampling cell systems. Moreover, experimentalists lack a set of quantitative
guidelines that prescribe the minimal number of samples required to infer a
reliable GRN model. We study the temporal resolution of data vs quality of GRN
inference in order to ultimately overcome this deficit. The evolution of a
Markovian jump process model for the Ras/cAMP/PKA pathway of proteins and
metabolites in the G1 phase of the Saccharomyces cerevisiae cell cycle is
sampled at a number of different rates. For each time-series we infer a linear
regression model of the GRN using the LASSO method. The inferred network
topology is evaluated in terms of the area under the precision-recall curve
AUPR. By plotting the AUPR against the number of samples, we show that the
trade-off has a, roughly speaking, sigmoid shape. An optimal number of samples
corresponds to values on the ridge of the sigmoid
- …