An Improved Calculation of the Non-Gaussian Halo Mass Function

The abundance of collapsed objects in the universe, or halo mass function, is an important theoretical tool in studying the effects of primordially generated non-Gaussianities on the large scale structure. The non-Gaussian mass function has been calculated by several authors in different ways, typically by exploiting the smallness of certain parameters which naturally appear in the calculation, to set up a perturbative expansion. We improve upon the existing results for the mass function by combining path integral methods and saddle point techniques (which have been separately applied in previous approaches). Additionally, we carefully account for the various scale dependent combinations of small parameters which appear. Some of these combinations in fact become of order unity for large mass scales and at high redshifts, and must therefore be treated non-perturbatively. Our approach allows us to do this, and to also account for multi-scale density correlations which appear in the calculation. We thus derive an accurate expression for the mass function which is based on approximations that are valid over a larger range of mass scales and redshifts than those of other authors. By tracking the terms ignored in the analysis, we estimate theoretical errors for our result and also for the results of others. We also discuss the complications introduced by the choice of smoothing filter function, which we take to be a top-hat in real space, and which leads to the dominant errors in our expression. Finally, we present a detailed comparison between the various expressions for the mass functions, exploring the accuracy and range of validity of each.Comment: 28 pages, 13 figures; v2: text reorganized and some figured modified for clarity, results unchanged, references added. Matches version published in JCA

The Photospheric Poynting Flux and Coronal Heating

Some models of coronal heating suppose that convective motions at the photosphere shuffle the footpoints of coronal magnetic fields and thereby inject sufficient magnetic energy upward to account for observed coronal and chromospheric energy losses in active regions. Using high-resolution observations of plage magnetic fields made with the Solar Optical Telescope aboard the Hinode satellite, we investigate this idea by estimating the upward transport of magnetic energy --- the vertical Poynting flux, S_z --- across the photosphere in a plage region. To do so, we combine: (i) estimates of photospheric horizontal velocities, v_h, determined by local correlation tracking applied to a sequence of line-of-sight magnetic field maps from the Narrowband Filter Imager, with (ii) a vector magnetic field measurement from the SpectroPolarimeter. Plage fields are ideal observational targets for estimating energy injection by convection, because they are: (i) strong enough to be measured with relatively small uncertainties; (ii) not so strong that convection is heavily suppressed (as within umbrae); and (iii) unipolar, so S_z in plage is not influenced by mixed-polarity processes (e.g., flux emergence) unrelated to heating in stable, active-region fields. In this plage region, we found that the average S_z varied in space, but was positive (upward) and sufficient to explain coronal heating, with values near (5 +/- 1) x 10^7 erg/cm^2/s. We find the energy input per unit magnetic flux to be on the order of 10^5 erg/s/Mx. A comparison of intensity in a Ca II image co-registered with the this plage shows stronger spatial correlations with both total field, B, and unsigned vertical field, |B_z|, than either S_z or horizontal field, B_h. The observed Ca II brightness enhancement, however, probably contains a strong contribution from a near-photosphere hot-wall effect unrelated to atmospheric heating.Comment: 30 pages, 11 figures, accepted by Pub. Astron. Soc. Japa

What is the relationship between photospheric flow fields and solar flares?

We estimated photospheric velocities by separately applying the Fourier Local Correlation Tracking (FLCT) and Differential Affine Velocity Estimator (DAVE) methods to 2708 co-registered pairs of SOHO/MDI magnetograms, with nominal 96-minute cadence and ~2" pixels, from 46 active regions (ARs) from 1996-1998 over the time interval t45 when each AR was within 45^o of disk center. For each magnetogram pair, we computed the average estimated radial magnetic field, B; and each tracking method produced an independently estimated flow field, u. We then quantitatively characterized these magnetic and flow fields by computing several extensive and intensive properties of each; extensive properties scale with AR size, while intensive properties do not depend directly on AR size. Intensive flow properties included moments of speeds, horizontal divergences, and radial curls; extensive flow properties included sums of these properties over each AR, and a crude proxy for the ideal Poynting flux, the total |u| B^2. Several magnetic quantities were also computed, including: total unsigned flux; a measure of the amount of unsigned flux near strong-field polarity inversion lines, R; and the total B^2. Next, using correlation and discriminant analysis, we investigated the associations between these properties and flares from the GOES flare catalog, when averaged over both t45 and shorter time windows, of 6 and 24 hours. We found R and total |u| B^2 to be most strongly associated with flares; no intensive flow properties were strongly associated with flares.Comment: 57 pages, 13 figures; revised content; added URL to manuscript with higher-quality image

Decorrelation Times of Photospheric Fields and Flows

We use autocorrelation to investigate evolution in flow fields inferred by applying Fourier Local Correlation Tracking (FLCT) to a sequence of high-resolution (0.3 \arcsec), high-cadence ($\simeq 2$ min) line-of-sight magnetograms of NOAA active region (AR) 10930 recorded by the Narrowband Filter Imager (NFI) of the Solar Optical Telescope (SOT) aboard the {\em Hinode} satellite over 12--13 December 2006. To baseline the timescales of flow evolution, we also autocorrelated the magnetograms, at several spatial binnings, to characterize the lifetimes of active region magnetic structures versus spatial scale. Autocorrelation of flow maps can be used to optimize tracking parameters, to understand tracking algorithms' susceptibility to noise, and to estimate flow lifetimes. Tracking parameters varied include: time interval $\Delta t$ between magnetogram pairs tracked, spatial binning applied to the magnetograms, and windowing parameter $\sigma$ used in FLCT. Flow structures vary over a range of spatial and temporal scales (including unresolved scales), so tracked flows represent a local average of the flow over a particular range of space and time. We define flow lifetime to be the flow decorrelation time, $\tau$. For $\Delta t > \tau$, tracking results represent the average velocity over one or more flow lifetimes. We analyze lifetimes of flow components, divergences, and curls as functions of magnetic field strength and spatial scale. We find a significant trend of increasing lifetimes of flow components, divergences, and curls with field strength, consistent with Lorentz forces partially governing flows in the active photosphere, as well as strong trends of increasing flow lifetime and decreasing magnitudes with increases in both spatial scale and $\Delta t$.Comment: 48 pages, 20 figures, submitted to the Astrophysical Journal; full-resolution images in manuscript (8MB) at http://solarmuri.ssl.berkeley.edu/~welsch/public/manuscripts/flow_lifetimes_v2.pd

Spatial and seasonal relationships between Pacific harbor seals (Phoca vitulina richardii) and their prey, at multiple scales

Knowing where pinnipeds forage is vital to managing and protecting their populations, and for assessing potential interactions with fisheries. We assessed the spatial relationship between the seasonal distribution of Pacific harbor seals (Phoca vitulina richardii) outfitted with satellite transmitters and the seasonal distributions of potential harbor seal prey species in San Francisco Bay, California. Pearson’s correlation coefficients were calculated between the number of harbor seal locations in an area of the San Francisco Bay and the abundance of specific prey species in the same area. The influence of scale on the analyses was assessed by varying the scale of analysis from 1 to 10 km. There was consistency in the prey species targeted by harbor seals year-round, although there were seasonal differences between the most important prey species. The highest correlations between harbor seals and their prey were found for seasonally abundant benthic species, located within about 10 km of the primary haul-out site. Probable foraging habitat for harbor seals was identified, based on areas with high abundances of prey species that were strongly correlated with harbor seal distribution. With comparable local data inputs, this approach has potential application to pinniped management in other areas, and to decisions about the location of marine reserves designed to protect these species