We provide software with a graphical user interface to calculate the phenomenology of a wide class of dark energy models featuring multiple scalar fields. The user chooses a subclass of models and, if desired, initial conditions, or else a range of i
nitial parameters for Monte Carlo. The code calculates the energy density of components in the universe, the equation of state of dark energy, and the linear growth of density perturbations, all as a function of redshift and scale factor. The output also includes an approximate conversion into the average equation of state, as well as the common $(w_0, w_a)$ parametrization. The code is available here: http://github.com/kahinton/Dark-Energy-UI-and-MC
Two of the most commonly used tools to constrain the primordial non-Gaussianity are the bispectrum and the Minkowski functionals of CMB temperature anisotropies. These two measures of non-Gaussianity in principle provide distinct (though correlated)
information, but in the past constraints from them have only been loosely compared, and not statistically combined. In this work we evaluate, for the first time, the covariance matrix between the local non-Gaussianity coefficient fnl estimated through the bispectrum and Minkowski functionals. We find that the estimators are positively correlated, with corerlation coefficient r ~ 0.3. Using the WMAP7 data to combine the two measures and accounting for the point-source systematics, we find the combined constraint fnl=37+/-28, which has a ~20% smaller error than either of the individual constraints.
We use data from the WMAP temperature maps to constrain a scale-dependent generalization of the popular local model for primordial non-Gaussianity. In the model where the parameter fNL is allowed to run with scale k, fNL(k) = fNL* (k/k_piv)^n, we con
strain the running to be n = 0.30(+1.9)(-1.2) at 95% confidence, marginalized over the amplitude fNL*. The constraints depend somewhat on the prior probabilities assigned to the two parameters. In the near future, constraints from a combination of Planck and large-scale structure surveys are expected to improve this limit by about an order of magnitude and usefully constrain classes of inflationary models.
We forecast combined future constraints from the cosmic microwave background and large-scale structure on the models of primordial non-Gaussianity. We study the generalized local model of non-Gaussianity, where the parameter f_NL is promoted to a fun
ction of scale, and present the principal component analysis applicable to an arbitrary form of f_NL(k). We emphasize the complementarity between the CMB and LSS by using Planck, DES and BigBOSS surveys as examples, forecast constraints on the power-law f_NL(k) model, and introduce the figure of merit for measurements of scale-dependent non-Gaussianity.
We use N-body/photometric galaxy simulations to examine the impact of sample variance of spectroscopic redshift samples on the accuracy of photometric redshift (photo-z) determination and calibration of photo-z errors. We estimate the biases in the c
osmological parameter constraints from weak lensing and derive requirements on the spectroscopic follow-up for three different photo-z algorithms chosen to broadly span the range of algorithms available. We find that sample variance is much more relevant for the photo-z error calibration than for photo-z training, implying that follow-up requirements are similar for different algorithms. We demonstrate that the spectroscopic sample can be used for training of photo-zs and error calibration without incurring additional bias in the cosmological parameters. We provide a guide for observing proposals for the spectroscopic follow-up to ensure that redshift calibration biases do not dominate the cosmological parameter error budget. For example, assuming optimistically (pessimistically) that the weak lensing shear measurements from the Dark Energy Survey could obtain 1-sigma constraints on the dark energy equation of state w of 0.035 (0.055), implies a follow-up requirement of 150 (40) patches of sky with a telescope such as Magellan, assuming a 1/8^2 deg effective field of view and 400 galaxies per patch. Assuming (optimistically) a VVDS-like spectroscopic completeness with purely random failures, this could be accomplished with about 75 (20) nights of observation. For more realistic assumptions regarding spectroscopic completeness, or in the presence of other sources of systematics not considered here, further degradations to dark energy constraints are possible. We test several approaches for reducing the requirements. Abridged
We generalize the local model of primordial non-Gaussianity by promoting the parameter fNL to a general scale-dependent function fNL(k). We calculate the resulting bispectrum and the effect on the bias of dark matter halos, and thus the extent to whi
ch fNL(k) can be measured from the large-scale structure observations. By calculating the principal components of fNL(k), we identify scales where this form of non-Gaussianity is best constrained and estimate the overlap with previously studied local and equilateral non-Gaussian models.
We compare current and forecasted constraints on dynamical dark energy models from Type Ia supernovae and the cosmic microwave background using figures of merit based on the volume of the allowed dark energy parameter space. For a two-parameter dark
energy equation of state that varies linearly with the scale factor, and assuming a flat universe, the area of the error ellipse can be reduced by a factor of ~10 relative to current constraints by future space-based supernova data and CMB measurements from the Planck satellite. If the dark energy equation of state is described by a more general basis of principal components, the expected improvement in volume-based figures of merit is much greater. While the forecasted precision for any single parameter is only a factor of 2-5 smaller than current uncertainties, the constraints on dark energy models bounded by -1<w<1 improve for approximately 6 independent dark energy parameters resulting in a reduction of the total allowed volume of principal component parameter space by a factor of ~100. Typical quintessence models can be adequately described by just 2-3 of these parameters even given the precision of future data, leading to a more modest but still significant improvement. In addition to advances in supernova and CMB data, percent-level measurement of absolute distance and/or the expansion rate is required to ensure that dark energy constraints remain robust to variations in spatial curvature.
A web of interlocking observations has established that the expansion of the Universe is speeding up and not slowing, revealing the presence of some form of repulsive gravity. Within the context of general relativity the cause of cosmic acceleration
is a highly elastic (psim -rho), very smooth form of energy called ``dark energy accounting for about 75% of the Universe. The ``simplest explanation for dark energy is the zero-point energy density associated with the quantum vacuum; however, all estimates for its value are many orders-of-magnitude too large. Other ideas for dark energy include a very light scalar field or a tangled network of topological defects. An alternate explanation invokes gravitational physics beyond general relativity. Observations and experiments underway and more precise cosmological measurements and laboratory experiments planned for the next decade will test whether or not dark energy is the quantum energy of the vacuum or something more exotic, and whether or not general relativity can self consistently explain cosmic acceleration. Dark energy is the most conspicuous example of physics beyond the standard model and perhaps the most profound mystery in all of science.
