Related papers: Likelihood Analysis of Large-Scale Flows
We present experimental results for water wave turbulence excited by piston-like programmed wavemakers in a water flume with horisontal dimensions 6x12x1.5 meters. Our main finding is that for a wide range of excitation amplitudes the…
We explore the possibility of evaluating flow harmonics by employing the maximum likelihood estimator (MLE). For a given finite multiplicity, the MLE simultaneously furnishes estimations for all the parameters of the underlying distribution…
The gradual fall of the shear viscosity below 2.8K, observed in a liquid helium 4 flowing through a capillary, is examined. The disappearance of the shear viscosity in a capillary flow is a manifestation of superfluidity in dissipative…
We present the first results from the Shellflow program, an all-sky Tully-Fisher (TF) peculiar velocity survey of 276 Sb-Sc galaxies with redshifts between 4500 and 7000 km/s. Shellflow was designed to minimize systematic errors between…
In SUSY models, the fine tuning of the electroweak (EW) scale with respect to their parameters gamma_i={m_0, m_{1/2}, mu_0, A_0, B_0,...} and the maximal likelihood L to fit the experimental data are usually regarded as two different…
We use the presently observed number density of large X-ray clusters and the linear mass power spectra to constrain $\sigma_8$ and the redshift distortion parameter $\beta$, in both OCDM and $\Lambda$CDM models. The best fit to the observed…
More than a dozen papers analyzing the COBE data have now appeared. We review the different techniques and compare them to a ``brute force" likelihood analysis where we invert the full 4038 x 4038 Galaxy-cut pixel covariance matrix. This…
We show that the maximum likelihood estimator (MLE) is an effective tool for mitigating non-flow effects in flow analysis. To this end, one constructs two toy models that simulate non-flow contributions corresponding to particle decay and…
The cascading gauge theory of Klebanov et.al realizes a soluble example of gauge/string correspondence in a non-conformal setting. Such a gauge theory has a strong coupling scale Lambda, below which it confines with a chiral symmetry…
In this work, we propose a non-parametric probabilistic load flow (NP-PLF) technique based on the Gaussian Process (GP) learning to understand the power system behavior under uncertainty for better operational decisions. The technique can…
We study the bivariate size-luminosity distribution of Lyman Break Galaxies (LBGs) selected at redshifts around 4 and 5 in GOODS and the HUDF fields. We model the size-luminosity distribution as a combination of log-normal distribution (in…
The number density of rich galaxy clusters still provides the most robust way of normalizing the power spectrum of dark matter perturbations on scales relevant to large-scale structure. We revisit this constraint in light of several recent…
Many components of data analysis in high energy physics and beyond require morphing one dataset into another. This is commonly solved via reweighting, but there are many advantages of preserving weights and shifting the data points instead.…
Anisotropic flow is sensitive to the shear $(\eta/s)$ and bulk ($\zeta/s$) viscosity of the quark-gluon plasma created in heavy-ion collisions, as well as the initial state of such collisions and hadronization mechanisms. In these…
We perform a detailed comparison of the present LEP data with the one-loop standard-model predictions. It is pointed out that for $m_t= 174$ GeV the ``bulk'' of the data prefers a rather large value of the Higgs mass in the range 500-1000…
The onset mechanism of superfluidity is examined by taking the case of the capillary flow of liquid helium 4. In the capillary flow, a substantial fall of the shear viscosity has been observed in the normal phase (lambda point<T<3.7K). In…
We recently found that Gamma Ray Burst energies and luminosities, in their comoving frame, are remarkably similar. This, coupled with the clustering of energetics once corrected for the collimation factor, suggests the possibility that all…
The likelihood function represents statistical evidence in the context of data and a probability model. Considerable theory has demonstrated that evidence strength for different parameter values can be interpreted from the ratio of…
The likelihood function of a finite mixture model is a non-convex function with multiple local maxima and commonly used iterative algorithms such as EM will converge to different solutions depending on initial conditions. In this paper we…
The most important hint of physics beyond the Standard Model (SM) from the 1995 precision electroweak data is that the most precisely measured quantities, the total, leptonic and hadronic decay widths of the $Z$ and the effective weak…