Abstract: The identification of the correct model for physics beyond the Standard Model requires the determination of the spin of new particles. We investigate to which extent the spin of a new particle X can be identified in scenarios where it decays dominantly in three-body decays X -> f (f) over barY. Here we assume that Y is a candidate for dark matter and escapes direct detection at a high energy collider such as the LHC. We show that in the case that all intermediate particles are heavy, one can get information on the spins of X and Y at the LHC by exploiting the invariant mass distribution of the two standard model fermions. We develop a model-independent strategy to determine the spins without prior knowledge of the unknown couplings and test it in a series of Monte Carlo studies.

Abstract: We study the impact of the cosmological parameters uncertainties on the measurements of primordial non-Gaussianity through the large-scale non-Gaussian halo bias effect. While this is not expected to be an issue for the standard Lambda CDM model, it may not be the case for more general models that modify the large-scale shape of the power spectrum. We consider the so-called local non-Gaussianity model, parametrized by the f(NL) non-Gaussianity parameter which is zero for a Gaussian case, and make forecasts on f(NL) from planned surveys, alone and combined with a Planck CMB prior. In particular, we consider EUCLID- and LSST-like surveys and forecast the correlations among f(NL) and the running of the spectral index alpha(s), the dark energy equation of state w, the effective sound speed of dark energy perturbations c(s)(2), the total mass of massive neutrinos M-nu = Sigma m(nu), and the number of extra relativistic degrees of freedom N-nu(rel). Neglecting CMB information on f(NL) and scales k > 0.03h/Mpc, we find that, if N-nu(rel) is assumed to be known, the uncertainty on cosmological parameters increases the error on f(NL) by 10 to 30% depending on the survey. Thus the f(NL) constraint is remarkable robust to cosmological model uncertainties. On the other hand, if N-nu(rel) is simultaneously constrained from the data, the f(NL) error increases by similar to 80%. Finally, future surveys which provide a large sample of galaxies or galaxy clusters over a volume comparable to the Hubble volume can measure primordial non-Gaussianity of the local form with a marginalized 1-sigma error of the order Delta f(NL) similar to 2 – 5, after combination with CMB priors for the remaining cosmological parameters. These results are competitive with CMB bispectrum constraints achievable with an ideal CMB experiment.

Abstract: We consider an idealized situation where the Quark-Gluon Plasma (QGP) is described by a perfect, (3 + 1)-dimensional fluid dynamic model starting from an initial state and expanding until a final state where freeze-out and/or hadronization takes place. We study the entropy production with attention to effects of (i) numerical viscosity, (ii) late stages of flow where the Bag Constant and the partonic pressure are becoming similar, (iii) and the consequences of final freeze-out and constituent quark matter formation.

Abstract: Purpose: In the present work, the authors compare geometrical and Monte Carlo projectors in detail. The geometrical projectors considered were the conventional geometrical Siddon ray-tracer (S-RT) and the orthogonal distance-based ray-tracer (OD-RT), based on computing the orthogonal distance from the center of image voxel to the line-of-response. A comparison of these geometrical projectors was performed using different point spread function (PSF) models. The Monte Carlo-based method under consideration involves an extensive model of the system response matrix based on Monte Carlo simulations and is computed off-line and stored on disk. Methods: Comparisons were performed using simulated and experimental data of the commercial small animal PET scanner rPET. Results: The results demonstrate that the orthogonal distance-based ray-tracer and Siddon ray-tracer using PSF image-space convolutions yield better images in terms of contrast and spatial resolution than those obtained after using the conventional method and the multiray-based S-RT. Furthermore, the Monte Carlo-based method yields slight improvements in terms of contrast and spatial resolution with respect to these geometrical projectors. Conclusions: The orthogonal distance-based ray-tracer and Siddon ray-tracer using PSF image-space convolutions represent satisfactory alternatives to factorizing the system matrix or to the conventional on-the-fly ray-tracing methods for list-mode reconstruction, where an extensive modeling based on Monte Carlo simulations is unfeasible.

Abstract: We present a novel intrinsic method for joint reconstruction of both image and motion in positron emission tomography (PET). Intrinsic motion compensation methods exclusively work on the measured data, without any external motion measurements. Most of these methods separate image from motion estimation: They use deformable image registration/optical flow techniques in order to estimate the motion from individually reconstructed gates. Then, the image is estimated based on this motion information. With these methods, a main problem lies in the motion estimation step, which is based on the noisy gated frames. The more noise is present, the more inaccurate the image registration becomes. As we show both visually and quantitatively, joint reconstruction using a simple deformation field motion model can compete with state-of-the-art image registration methods which use robust multilevel B-spline motion models.