Bayesian analysis of an anisotropic universe model: systematics and polarization

We revisit the anisotropic universe model previously developed by Ackerman, Carroll and Wise (ACW), and generalize both the theoretical and computational framework to include polarization and various forms of systematic effects. We apply our new tools to simulated WMAP data in order to understand the potential impact of asymmetric beams, noise mis-estimation and potential Zodiacal light emission. We find that neither has any significant impact on the results. We next show that the previously reported ACW signal is also present in the 1-year WMAP temperature sky map presented by Liu & Li, where data cuts are more aggressive. Finally, we reanalyze the 5-year WMAP data taking into account a previously neglected (-i)^{l-l'}-term in the signal covariance matrix. We still find a strong detection of a preferred direction in the temperature map. Including multipoles up to l=400, the anisotropy amplitude for the W-band is found to be g = 0.29 +- 0.031, nonzero at 9 sigma. However, the corresponding preferred direction is also shifted very close to the ecliptic poles at (l,b)= (96,30), in agreement with the analysis of Hanson & Lewis, indicating that the signal is aligned along the plane of the solar system. This strongly suggests that the signal is not of cosmological origin, but most likely is a product of an unknown systematic effect. Determining the nature of the systematic effect is of vital importance, as it might affect other cosmological conclusions from the WMAP experiment. Finally, we provide a forecast for the Planck experiment including polarization.Comment: 9 pages, 8 figure

Cosmological Parameters from CMB Maps without Likelihood Approximation

We propose an efficient Bayesian MCMC algorithm for estimating cosmological parameters from CMB data without use of likelihood approximations. It builds on a previously developed Gibbs sampling framework that allows for exploration of the joint CMB sky signal and power spectrum posterior, P(s,Cl|d), and addresses a long-standing problem of efficient parameter estimation simultaneously in high and low signal-to-noise regimes. To achieve this, our new algorithm introduces a joint Markov Chain move in which both the signal map and power spectrum are synchronously modified, by rescaling the map according to the proposed power spectrum before evaluating the Metropolis-Hastings accept probability. Such a move was already introduced by Jewell et al. (2009), who used it to explore low signal-to-noise posteriors. However, they also found that the same algorithm is inefficient in the high signal-to-noise regime, since a brute-force rescaling operation does not account for phase information. This problem is mitigated in the new algorithm by subtracting the Wiener filter mean field from the proposed map prior to rescaling, leaving high signal-to-noise information invariant in the joint step, and effectively only rescaling the low signal-to-noise component. To explore the full posterior, the new joint move is then interleaved with a standard conditional Gibbs sky map move. We apply our new algorithm to simplified simulations for which we can evaluate the exact posterior to study both its accuracy and performance, and find good agreement with the exact posterior; marginal means agree to less than 0.006 sigma, and standard deviations to better than 3%. The Markov Chain correlation length is of the same order of magnitude as those obtained by other standard samplers in the field.Comment: 9 pages, 3 figures, Published in Ap

Lorentz Violation in Goldstone Gravity

We consider a theory of gravity in which a symmetric two-index tensor in Minkowski spacetime acquires a vacuum expectation value (vev) via a potential, thereby breaking Lorentz invariance spontaneously. When the vev breaks all the generators of the Lorentz group, six Goldstone modes emerge, two linear combinations of which have properties that are identical to those of the graviton in general relativity. Integrating out massive modes yields an infinite number of Lorentz-violating radiative-correction terms in the low-energy effective Lagrangian. We examine a representative subset of these terms and show that they modify the dispersion relation of the two propagating graviton modes such that their phase velocity is direction-dependent. If the phase velocity of the Goldstone gravitons is subluminal, cosmic rays can emit gravi-Cherenkov radiation, and the detection of high-energy cosmic rays can be used to constrain these radiative correction terms. Test particles in the vicinity of the Goldstone gravitons undergo longitudinal oscillations in addition to the usual transverse oscillations as predicted by general relativity. Finally, we discuss the possibility of having vevs that do not break all six generators and examine in detail one such theory.Comment: 14 page

Demonstration of magnetic field tomography with starlight polarization towards a diffuse sightline of the ISM

The availability of large datasets with stellar distance and polarization information will enable a tomographic reconstruction of the (plane-of-the-sky-projected) interstellar magnetic field in the near future. We demonstrate the feasibility of such a decomposition within a small region of the diffuse ISM. We combine measurements of starlight (R-band) linear polarization obtained using the RoboPol polarimeter with stellar distances from the second Gaia data release. The stellar sample is brighter than 17 mag in the R band and reaches out to several kpc from the Sun. HI emission spectra reveal the existence of two distinct clouds along the line of sight. We decompose the line-of-sight-integrated stellar polarizations to obtain the mean polarization properties of the two clouds. The two clouds exhibit significant differences in terms of column density and polarization properties. Their mean plane-of-the-sky magnetic field orientation differs by 60 degrees. We show how our tomographic decomposition can be used to constrain our estimates of the polarizing efficiency of the clouds as well as the frequency dependence of the polarization angle of polarized dust emission. We also demonstrate a new method to constrain cloud distances based on this decomposition. Our results represent a preview of the wealth of information that can be obtained from a tomographic map of the ISM magnetic field.Comment: 25 pages, 14 figures, published in ApJ, data appear in journa

Cross-correlating Carbon Monoxide Line-intensity Maps with Spectroscopic and Photometric Galaxy Surveys

Line-intensity mapping (LIM or IM) is an emerging field of observational work, with strong potential to fit into a larger effort to probe large-scale structure and small-scale astrophysical phenomena using multiple complementary tracers. Taking full advantage of such complementarity means, in part, undertaking line-intensity surveys with galaxy surveys in mind. We consider the potential for detection of a cross-correlation signal between COMAP and blind surveys based on photometric redshifts (as in COSMOS) or based on spectroscopic data (as with the HETDEX survey of Lyman-$\alpha$ emitters). We find that obtaining $\sigma_z/(1+z)\lesssim0.003$ accuracy in redshifts and $\gtrsim10^{-4}$ sources per Mpc$^3$ with spectroscopic redshift determination should enable a CO-galaxy cross spectrum detection significance at least twice that of the CO auto spectrum. Either a future targeted spectroscopic survey or a blind survey like HETDEX may be able to meet both of these requirements.Comment: 19 pages + appendix (31 pages total), 16 figures, 6 tables; accepted for publication in Ap

Foreground Separation and Constraints on Primordial Gravitational Waves with the PICO Space Mission

PICO is a concept for a NASA probe-scale mission aiming to detect or constrain the tensor to scalar ratio $r$, a parameter that quantifies the amplitude of inflationary gravity waves. We carry out map-based component separation on simulations with five foreground models and input $r$ values $r_{in}=0$ and $r_{in} = 0.003$. We forecast $r$ determinations using a Gaussian likelihood assuming either no delensing or a residual lensing factor $A_{\rm lens}$ = 27%. By implementing the first full-sky, post component-separation, map-domain delensing, we show that PICO should be able to achieve $A_{\rm lens}$ = 22% - 24%. For four of the five foreground models we find that PICO would be able to set the constraints r < 1.3 \times 10^{-4} \,\, \mbox{to} \,\, r <2.7 \times 10^{-4}\, (95\%) if $r_{in}=0$, the strongest constraints of any foreseeable instrument. For these models, $r=0.003$ is recovered with confidence levels between $18\sigma$ and $27\sigma$. We find weaker, and in some cases significantly biased, upper limits when removing few low or high frequency bands. The fifth model gives a $3\sigma$ detection when $r_{in}=0$ and a $3\sigma$ bias with $r_{in} = 0.003$. However, by correlating $r$ determinations from many small 2.5% sky areas with the mission's 555 GHz data we identify and mitigate the bias. This analysis underscores the importance of large sky coverage. We show that when only low multipoles $\ell \leq 12$ are used, the non-Gaussian shape of the true likelihood gives uncertainties that are on average 30% larger than a Gaussian approximation.Comment: 34 pages, 13 figures, published in JCA

Joint power spectrum and voxel intensity distribution forecast on the CO luminosity function with COMAP

We develop a framework for joint constraints on the CO luminosity function based on power spectra (PS) and voxel intensity distributions (VID), and apply this to simulations of COMAP, a CO intensity mapping experiment. This Bayesian framework is based on a Markov chain Monte Carlo (MCMC) sampler coupled to a Gaussian likelihood with a joint PS + VID covariance matrix computed from a large number of fiducial simulations, and re-calibrated with a small number of simulations per MCMC step. The simulations are based on dark matter halos from fast peak patch simulations combined with the $L_\text{CO}(M_\text{halo})$ model of Li et al. (2016). We find that the relative power to constrain the CO luminosity function depends on the luminosity range of interest. In particular, the VID is more sensitive at both small and large luminosities, while the PS is more sensitive at intermediate luminosities. The joint analysis is superior to using either observable separately. When averaging over CO luminosities ranging between $L_\text{CO} = 10^4-10^7L_\odot$, and over 10 cosmological realizations of COMAP Phase 2, the uncertainties (in dex) are larger by 58 % and 30 % for the PS and VID, respectively, when compared to the joint analysis (PS + VID). This method is generally applicable to any other random field, with a complicated likelihood, as long a fast simulation procedure is available.Comment: 13 pages, 5 figures. As accepted to Ap