We introduce a method to constrain general cosmological models using Baryon Acoustic Oscillation (BAO) distance measurements from galaxy samples covering different redshift ranges, and apply this ...method to analyse samples drawn from the SDSS and 2dFGRS. BAO are detected in the clustering of the combined 2dFGRS and SDSS main galaxy samples, and measure the distance--redshift relation at z=0.2. BAO in the clustering of the SDSS luminous red galaxies measure the distance--redshift relation at z=0.35. The observed scale of the BAO calculated from these samples and from the combined sample are jointly analysed using estimates of the correlated errors, to constrain the form of the distance measure D_V(z)=(1+z)^2D_A^2cz/H(z)^(1/3). Here D_A is the angular diameter distance, and H(z) is the Hubble parameter. This gives r_s/D_V(0.2)=0.1980+/-0.0058 and r_s/D_V(0.35)=0.1094+/-0.0033 (1sigma errors), with correlation coefficient of 0.39, where r_s is the comoving sound horizon scale at recombination. Matching the BAO to have the same measured scale at all redshifts then gives D_V(0.35)/D_V(0.2)=1.812+/-0.060. The recovered ratio is roughly consistent with that predicted by the higher redshift SNLS supernovae data for Lambda cosmologies, but does require slightly stronger cosmological acceleration at low redshift. If we force the cosmological model to be flat with constant w, then we find Om_m=0.249+/-0.018 and w=-1.004+/-0.089 after combining with the SNLS data, and including the WMAP measurement of the apparent acoustic horizon angle in the CMB.
The spectroscopic Sloan Digital Sky Survey (SDSS) Data Release 7 (DR7) galaxy sample represents the final set of galaxies observed using the original SDSS target selection criteria. We analyse the ...clustering of galaxies within this sample, including both the Luminous Red Galaxy (LRG) and Main samples, and also include the 2-degree Field Galaxy Redshift Survey (2dFGRS) data. Baryon Acoustic Oscillations are observed in power spectra measured for different slices in redshift; this allows us to constrain the distance--redshift relation at multiple epochs. We achieve a distance measure at redshift z=0.275, of r_s(z_d)/D_V(0.275)=0.1390+/-0.0037 (2.7% accuracy), where r_s(z_d) is the comoving sound horizon at the baryon drag epoch, D_V(z)=(1+z)^2D_A^2cz/H(z)^(1/3), D_A(z) is the angular diameter distance and H(z) is the Hubble parameter. We find an almost independent constraint on the ratio of distances D_V(0.35)/D_V(0.2)=1.736+/-0.065, which is consistent at the 1.1sigma level with the best fit Lambda-CDM model obtained when combining our z=0.275 distance constraint with the WMAP 5-year data. The offset is similar to that found in previous analyses of the SDSS DR5 sample, but the discrepancy is now of lower significance, a change caused by a revised error analysis and a change in the methodology adopted, as well as the addition of more data. Using WMAP5 constraints on Omega_bh^2 and Omega_ch^2, and combining our BAO distance measurements with those from the Union Supernova sample, places a tight constraint on Omega_m=0.286+/-0.018 and H_0 = 68.2+/-2.2km/s/Mpc that is robust to allowing curvature and non-Lambda dark energy. This result is independent of the behaviour of dark energy at redshifts greater than those probed by the BAO and supernova measurements. (abridged)
We present the power spectrum of the reconstructed halo density field derived from a sample of Luminous Red Galaxies (LRGs) from the Sloan Digital Sky Survey Seventh Data Release (DR7). The halo ...power spectrum has a direct connection to the underlying dark matter power for k <= 0.2 h/Mpc, well into the quasi-linear regime. This enables us to use a factor of ~8 more modes in the cosmological analysis than an analysis with kmax = 0.1 h/Mpc, as was adopted in the SDSS team analysis of the DR4 LRG sample (Tegmark et al. 2006). The observed halo power spectrum for 0.02 < k < 0.2 h/Mpc is well-fit by our model: chi^2 = 39.6 for 40 degrees of freedom for the best fit LCDM model. We find \Omega_m h^2 * (n_s/0.96)^0.13 = 0.141^{+0.009}_{-0.012} for a power law primordial power spectrum with spectral index n_s and \Omega_b h^2 = 0.02265 fixed, consistent with CMB measurements. The halo power spectrum also constrains the ratio of the comoving sound horizon at the baryon-drag epoch to an effective distance to z=0.35: r_s/D_V(0.35) = 0.1097^{+0.0039}_{-0.0042}. Combining the halo power spectrum measurement with the WMAP 5 year results, for the flat LCDM model we find \Omega_m = 0.289 +/- 0.019 and H_0 = 69.4 +/- 1.6 km/s/Mpc. Allowing for massive neutrinos in LCDM, we find \sum m_{\nu} < 0.62 eV at the 95% confidence level. If we instead consider the effective number of relativistic species Neff as a free parameter, we find Neff = 4.8^{+1.8}_{-1.7}. Combining also with the Kowalski et al. (2008) supernova sample, we find \Omega_{tot} = 1.011 +/- 0.009 and w = -0.99 +/- 0.11 for an open cosmology with constant dark energy equation of state w.
We present the large-scale correlation function measured from a spectroscopic sample of 46,748 luminous red galaxies from the Sloan Digital Sky Survey. The survey region covers 0.72 h super(-3) Gpc ...super(3) over 3816 deg super(2) and 0.16 < z < 0.47, making it the best sample yet for the study of large-scale structure. We find a well-detected peak in the correlation function at 100 h super(-1) Mpc separation that is an excellent match to the predicted shape and location of the imprint of the recombination-epoch acoustic oscillations on the low-redshift clustering of matter. This detection demonstrates the linear growth of structure by gravitational instability between z 1000 and the present and confirms a firm prediction of the standard cosmological theory. The acoustic peak provides a standard ruler by which we can measure the ratio of the distances to z = 0.35 and z = 1089 to 4% fractional accuracy and the absolute distance to z = 0.35 to 5% accuracy. From the overall shape of the correlation function, we measure the matter density sub(m)h super(2) to 8% and find agreement with the value from cosmic microwave background (CMB) anisotropies. Independent of the constraints provided by the CMB acoustic scale, we find sub(m) = 0.273 c 0.025 + 0.123 (1 + W sub(0)) + 0.137 sub(K). Including the CMB acoustic scale, we find that the spatial curvature is sub(K) = -0.010 c 0.009 if the dark energy is a cosmological constant. More generally, our results provide a measurement of cosmological distance, and hence an argument for dark energy, based on a geometric method with the same simple physics as the microwave background anisotropies. The standard cosmological model convincingly passes these new and robust tests of its fundamental properties.
Eigenmode analysis is one of the most promising methods of analyzing large data sets in ongoing and near-future galaxy surveys. In such analyses, a fast evaluation of the correlation matrix in ...arbitrary cosmological models is crucial. The observational effects, including peculiar velocity distortions in redshift space, light-cone effects, selection effects, and effects of the complex shape of the survey geometry, should be taken into account in the analysis. In the framework of the linear theory of gravitational instability, we provide the methodology to quickly compute the correlation matrix. Our methods are not restricted to shallow redshift surveys, arbitrarily deep samples can be dealt with as well. Therefore, our methods are useful in constraining the geometry of the universe and the dark energy component, as well as the power spectrum of galaxies, since ongoing and near-future galaxy surveys probe the universe at intermediate to deep redshifts, z ~ 0.2--5. In addition to the detailed methods to compute the correlation matrix in 3-dimensional redshift surveys, methods to calculate the matrix in 2-dimensional projected samples are also provided. Prospects of applying our methods to likelihood estimation of the cosmological parameters are discussed.
Astrophys.J.657:51-55,2007 We measure the cosmological matter density by observing the positions of
baryon acoustic oscillations in the clustering of galaxies in the Sloan Digital
Sky Survey (SDSS). ...We jointly analyse the main galaxies and LRGs in the SDSS
DR5 sample, using over half a million galaxies in total. The oscillations are
detected with 99.74% confidence (3.0sigma assuming Gaussianity) compared to a
smooth power spectrum. When combined with the observed scale of the peaks
within the CMB, we find a best-fit value of Omega_m=0.256+0.029-0.024 (68%
confidence interval), for a flat Lambda cosmology when marginalising over the
Hubble parameter and the baryon density. This value of the matter density is
derived from the locations of the baryon oscillations in the galaxy power
spectrum and in the CMB, and does not include any information from the overall
shape of the power spectra. This is an extremely clean cosmological measurement
as the physics of the baryon acoustic oscillation production is well
understood, and the positions of the oscillations are expected to be
independent of systematics such as galaxy bias.
Autonomous control in high-dimensional, continuous state spaces is a persistent and important challenge in the fields of robotics and artificial intelligence. Because of high risk and complexity, the ...adoption of AI for autonomous combat systems has been a long-standing difficulty. In order to address these issues, DARPA's AlphaDogfight Trials (ADT) program sought to vet the feasibility of and increase trust in AI for autonomously piloting an F-16 in simulated air-to-air combat. Our submission to ADT solves the high-dimensional, continuous control problem using a novel hierarchical deep reinforcement learning approach consisting of a high-level policy selector and a set of separately trained low-level policies specialized for excelling in specific regions of the state space. Both levels of the hierarchy are trained using off-policy, maximum entropy methods with expert knowledge integrated through reward shaping. Our approach outperformed human expert pilots and achieved a second-place rank in the ADT championship event. Impact Statement- Significant performance milestones in reinforcement learning have been achieved in recent years, with autonomous agents demonstrating super-human performance across a wide variety of tasks. Before these algorithms can be extensively deployed in real-world defense applications, a greater level of trust must first be achieved. ADT was an important step towards developing the trust necessary to operationalize these algorithms, by demonstrating their effectiveness on a foundational yet relevant problem in a high-fidelity simulation environment. Developed for the program, our hierarchical reinforcement learning agent was designed alongside of and competed against active fighter pilots, and ultimately defeated a graduate of the United States Air Force's F-16 Weapons Instructor Course in match play.
The human gastrointestinal tract harbors a dense and diverse microbial community, the makeup of which is intimately linked to health. Extrinsic factors such as diet and host immunity are insufficient ...to explain the constituents of this community, implicating direct interactions between co-resident microbes as an important driver of microbiome composition. The genomes of bacteria derived from the gut microbiome are replete with pathways that mediate contact-dependent interbacterial antagonism
1
–
3
. Many members of the Gram-negative order Bacteroidales encode the type VI secretion system (T6SS), which facilitates the delivery of toxic effector proteins into adjacent cells
4
,
5
. Here we report the occurrence of acquired interbacterial defense (AID) gene clusters in Bacteroidales residing within the human gut microbiome. These clusters encode arrays of immunity genes that protect against T6SS-mediated intra- and inter-species bacterial antagonism. Moreover, the clusters reside on mobile elements and we demonstrate that their transfer is sufficient to confer toxin resistance
in vitro
and in gnotobiotic mice. Finally, we identify and validate the protective capacity of a recombinase-associated AID subtype (
r
AID-1) present broadly in Bacteroidales genomes. These
r
AID-1 gene clusters have a structure suggestive of active gene acquisition and include predicted immunity factors of toxins deriving from diverse organisms. Our data suggest that neutralization of contact-dependent interbacterial antagonism via AID systems shapes human gut microbiome ecology.
PDF
