Constraints on Sterile Neutrino Dark Matter

We present a comprehensive analysis of constraints on the sterile neutrino as a dark matter candidate. The minimal production scenario with a standard thermal history and negligible cosmological lepton number is in conflict with conservative radiative decay constraints from the cosmic X-ray background in combination with stringent small-scale structure limits from the Lyman-alpha forest. We show that entropy release through massive particle decay after production does not alleviate these constraints. We further show that radiative decay constraints from local group dwarf galaxies are subject to large uncertainties in the dark matter density profile of these systems. Within the strongest set of constraints, resonant production of cold sterile neutrino dark matter in non-zero lepton number cosmologies remains allowed.Comment: 9 pages, 3 figures; v2 includes discussion of astro-ph/0605706 and matches version to appear in Phys. Rev.

Galaxy Clustering in Early SDSS Redshift Data

We present the first measurements of clustering in the Sloan Digital Sky Survey (SDSS) galaxy redshift survey. Our sample consists of 29,300 galaxies with redshifts 5,700 km/s < cz < 39,000 km/s, distributed in several long but narrow (2.5-5 degree) segments, covering 690 square degrees. For the full, flux-limited sample, the redshift-space correlation length is approximately 8 Mpc/h. The two-dimensional correlation function \xi(r_p,\pi) shows clear signatures of both the small-scale, ``fingers-of-God'' distortion caused by velocity dispersions in collapsed objects and the large-scale compression caused by coherent flows, though the latter cannot be measured with high precision in the present sample. The inferred real-space correlation function is well described by a power law, \xi(r)=(r/6.1+/-0.2 Mpc/h)^{-1.75+/-0.03}, for 0.1 Mpc/h < r < 16 Mpc/h. The galaxy pairwise velocity dispersion is \sigma_{12} ~ 600+/-100 km/s for projected separations 0.15 Mpc/h < r_p < 5 Mpc/h. When we divide the sample by color, the red galaxies exhibit a stronger and steeper real-space correlation function and a higher pairwise velocity dispersion than do the blue galaxies. The relative behavior of subsamples defined by high/low profile concentration or high/low surface brightness is qualitatively similar to that of the red/blue subsamples. Our most striking result is a clear measurement of scale-independent luminosity bias at r < 10 Mpc/h: subsamples with absolute magnitude ranges centered on M_*-1.5, M_*, and M_*+1.5 have real-space correlation functions that are parallel power laws of slope ~ -1.8 with correlation lengths of approximately 7.4 Mpc/h, 6.3 Mpc/h, and 4.7 Mpc/h, respectively.Comment: 51 pages, 18 figures. Replaced to match accepted ApJ versio

Lagrangian space consistency relation for large scale structure

Consistency relations, which relate the squeezed limit of an (N+1)-point correlation function to an N-point function, are non-perturbative symmetry statements that hold even if the associated high momentum modes are deep in the nonlinear regime and astrophysically complex. Recently, Kehagias & Riotto and Peloso & Pietroni discovered a consistency relation applicable to large scale structure. We show that this can be recast into a simple physical statement in Lagrangian space: that the squeezed correlation function (suitably normalized) vanishes. This holds regardless of whether the correlation observables are at the same time or not, and regardless of whether multiple-streaming is present. The simplicity of this statement suggests that an analytic understanding of large scale structure in the nonlinear regime may be particularly promising in Lagrangian space.Comment: 19 pages, no figure

Efficient Yet Robust Privacy for Video Streaming

MPEG-DASH is a video streaming standard that outlines protocols for sending audio and video content from a server to a client over HTTP. The standard has been widely utilized by the video streaming industry. However, it creates an opportunity for an adversary to invade users’ privacy. While a user is watching a video, information is leaked in the form of meta-data, the size and time that the server sent data to the user. This information is not protected by encryption and can be used to create a fingerprint for a video. Once the fingerprint is created, the adversary can use this to identify whether a target user is watching the corresponding video. Successful attack schemes have been proposed based on this leakage of user data using both Machine Learning (ML) and algorithmic approaches. Only one defense strategy has been proposed to deal with this problem: using differential privacy that adds a sufficient amount of noise in order to muddle the attacks. However, this strategy still suffers from the trade-off between the privacy level and efficiency for both the server and the client. To break through the problem, this paper proposes two schemes. A server-side defense and a client-side defense against the attacks with rigorous privacy and performance constraints, creating a totally private, scalable solution that outperforms the extant schemes. Our two proposed schemes, No Data are Alone (NDA) and a proposed scheme that uses only a single cluster (Single Cluster Solution), are developed based on KMeans clustering and are highly efficient. The experimental results show that our schemes are more than two times as efficient, in terms of excess downloaded video (represented as waste), than the most efficient differential privacy-based scheme. Additionally, no classifier can achieve an accuracy above 7.07% against videos obfuscated with our scheme NDA and 2.5% against our Single Cluster Solution

Turbulence induced collisional velocities and density enhancements: large inertial range results from shell models

To understand the earliest stages of planet formation, it is crucial to be able to predict the rate and the outcome of dust grains collisions, be it sticking and growth, bouncing, or fragmentation. The outcome of such collisions depends on the collision speed, so we need a solid understanding of the rate and velocity distribution of turbulence-induced dust grain collisions. The rate of the collisions depends both on the speed of the collisions and the degree of clustering experienced by the dust grains, which is a known outcome of turbulence. We evolve the motion of dust grains in simulated turbulence, an approach that allows a large turbulent inertial range making it possible to investigate the effect of turbulence on meso-scale grains (millimeter and centimeter). We find three populations of dust grains: one highly clustered, cold and collisionless; one warm; and the third "hot". Our results can be fit by a simple formula, and predict both significantly slower typical collisional velocities for a given turbulent strength than previously considered, and modest effective clustering of the collisional populations, easing difficulties associated with bouncing and fragmentation barriers to dust grain growth. Nonetheless, the rate of high velocity collisions falls off merely exponentially with relative velocity so some mid- or high-velocity collisions will still occur, promising some fragmentation.Comment: 14 pages, 8 figures, 4 tables, Accepted, MNRA