Signal strength determines the nature of the relationship between perception and working memory

Neurophysiological and behavioral studies have shown that perception and memory share neural substrates and functional properties. But are perception and the active working memory of a stimulus one and the same? To address this question in the spatial domain, we compared the percept and the working memory of the position of a target stimulus embedded within a surround of moving dots. Motion in a particular direction after the target's offset biased the memory of target location in the same direction. However, motion simultaneous with a high-contrast, perceptually strong target biased the percept of target location in the opposite direction. Thus, perception and working memory can be modified by motion in qualitatively different ways. Manipulations to strengthen the memory trace had no effect on the direction of the memory bias, indicating that memory signal strength can never equal that of the percept of a strong stimulus. However, the percept of a weak stimulus was biased in the direction of motion. Thus, although perception and working memory are not inherently different, they can differ behaviorally depending on the strength of the perceptual signal. Understanding how a changing surround biases neural representations in general, and postsensory processes in particular, can help one understand past reports of spatial mislocalization

Small Scale Anisotropies of UHECRs from Super-Heavy Halo Dark Matter

The decay of very heavy metastable relics of the Early Universe can produce ultra-high energy cosmic rays (UHECRs) in the halo of our own Galaxy. In this model, no Greisen-Zatsepin-Kuzmin cutoff is expected because of the short propagation distances. We show here that, as a consequence of the hierarchical build up of the halo, this scenario predicts the existence of small scale anisotropies in the arrival directions of UHECRs, in addition to a large scale anisotropy, known from previous studies. We also suggest some other observable consequences of this scenario which will be testable with upcoming experiments, as Auger, EUSO and OWL.Comment: Contribution given at ICRC 2001 - August 7-15, 2001 - Hambur

The Mass Function of Dark Halos in Superclusters and Voids

A modification of the Press-Schechter theory allowing for presence of a background large-scale structure (LSS) - a supercluster or a void, is proposed. The LSS is accounted as the statistical constraints in form of linear functionals of the random overdensity field. The deviation of the background density within the LSS is interpreted in a pseudo-cosmological sense. Using the constraints formalism may help us to probe non-trivial spatial statistics of haloes, e.g. edge and shape effects on boundaries of the superclusters and voids. Parameters of the constraints are connected to features of the LSS: its mean overdensity, a spatial scale and a shape, and spatial momenta of higher orders. It is shown that presence of a non-virialized LSS can lead to an observable deviation of the mass function. This effect is exploited to build a procedure to recover parameters of the background perturbation from the observationally estimated mass function.Comment: 23 pages, 6 figures; to be appeared in Astronomy Reports, 2014, Vol. 58, No. 6, pp. 386-39

On the Distribution of Haloes, Galaxies and Mass

The stochasticity in the distribution of dark haloes in the cosmic density field is reflected in the distribution function $P_V(N_h|\delta_m)$ which gives the probability of finding $N_h$ haloes in a volume $V$ with mass density contrast $\delta_m$. We study the properties of this function using high-resolution $N$-body simulations, and find that $P_V(N_n|\delta_m)$ is significantly non-Poisson. The ratio between the variance and the mean goes from $\sim 1$ (Poisson) at $1+\delta_m\ll 1$ to $<1$ (sub-Poisson) at $1+\delta_m\sim 1$ to $>1$ (super-Poisson) at $1+\delta_m\gg 1$. The mean bias relation is found to be well described by halo bias models based on the Press-Schechter formalism. The sub-Poisson variance can be explained as a result of halo-exclusion while the super-Poisson variance at high $\delta_m$ may be explained as a result of halo clustering. A simple phenomenological model is proposed to describe the behavior of the variance as a function of $\delta_m$. Galaxy distribution in the cosmic density field predicted by semi-analytic models of galaxy formation shows similar stochastic behavior. We discuss the implications of the stochasticity in halo bias to the modelling of higher-order moments of dark haloes and of galaxies.Comment: 10 pages, 6 figures, Latex using MN2e style. Minor changes. Accepted for publication in MNRA

Selection bias in dynamically-measured super-massive black hole samples: consequences for pulsar timing arrays

Supermassive black hole -- host galaxy relations are key to the computation of the expected gravitational wave background (GWB) in the pulsar timing array (PTA) frequency band. It has been recently pointed out that standard relations adopted in GWB computations are in fact biased-high. We show that when this selection bias is taken into account, the expected GWB in the PTA band is a factor of about three smaller than previously estimated. Compared to other scaling relations recently published in the literature, the median amplitude of the signal at $f=1$yr$^{-1}$ drops from $1.3\times10^{-15}$ to $4\times10^{-16}$. Although this solves any potential tension between theoretical predictions and recent PTA limits without invoking other dynamical effects (such as stalling, eccentricity or strong coupling with the galactic environment), it also makes the GWB detection more challenging.Comment: 6 pages 4 figures, submitted to MNRAS letter

Large scale bias and the inaccuracy of the peak-background split

The peak-background split argument is commonly used to relate the abundance of dark matter halos to their spatial clustering. Testing this argument requires an accurate determination of the halo mass function. We present a Maximum Likelihood method for fitting parametric functional forms to halo abundances which differs from previous work because it does not require binned counts. Our conclusions do not depend on whether we use our method or more conventional ones. In addition, halo abundances depend on how halos are defined. Our conclusions do not depend on the choice of link length associated with the friends-of-friends halo-finder, nor do they change if we identify halos using a spherical overdensity algorithm instead. The large scale halo bias measured from the matter-halo cross spectrum b_x and the halo autocorrelation function b_xi (on scales k~0.03h/Mpc and r ~50 Mpc/h) can differ by as much as 5% for halos that are significantly more massive than the characteristic mass M*. At these large masses, the peak background split estimate of the linear bias factor b1 is 3-5% smaller than b_xi, which is 5% smaller than b_x. We discuss the origin of these discrepancies: deterministic nonlinear local bias, with parameters determined by the peak-background split argument, is unable to account for the discrepancies we see. A simple linear but nonlocal bias model, motivated by peaks theory, may also be difficult to reconcile with our measurements. More work on such nonlocal bias models may be needed to understand the nature of halo bias at this level of precision.Comment: MNRAS accepted. New section with Spherical Overdensity identified halos included. Appendix enlarge

Self-consistency of the Excursion Set Approach

The excursion set approach provides a framework for predicting how the abundance of dark matter halos depends on the initial conditions. A key ingredient of this formalism comes from the physics of halo formation: the specification of a critical overdensity threshold (barrier) which protohalos must exceed if they are to form bound virialized halos at a later time. Another ingredient is statistical, as it requires the specification of the appropriate statistical ensemble over which to average when making predictions. The excursion set approach explicitly averages over all initial positions, thus implicitly assuming that the appropriate ensemble is that associated with randomly chosen positions in space, rather than special positions such as peaks of the initial density field. Since halos are known to collapse around special positions, it is not clear that the physical and statistical assumptions which underlie the excursion set approach are self-consistent. We argue that they are at least for low mass halos, and illustrate by comparing our excursion set predictions with numerical data from the DEUS simulations.Comment: 5 pages, 2 figure