Searching for Extra Dimensions in High Energy Cosmic Rays

We present a study of the decay of an intermediate mini black hole at the first impact of a cosmic ray particle with the atmosphere, in the context of D-brane world scenarios with TeV scale gravity and large extra dimensions. We model the decay of the black hole using the semiclassical approximation and include the corrections coming from energy loss into the bulk. Extensive simulations show that mini black hole events are characterized by essentially different multiplicities and wider lateral distributions of the air showers as a function of the energy of the incoming primary, as compared to standard events. Implications for their detection and some open issues on their possible discovery are also briefly addressed.Comment: 4 pages, 4 figures, Presented by C. Coriano' at the XIII Intl. Symp. on High Energy Cosmic Rays Interactions, Pylos, Greece, 6-12 Sept. 200

Parton Distributions, Logarithmic Expansions and Kinetic Evolution

Aspects of the QCD parton densities are briefly reviewed, drawing some parallels to the density matrix formulation of quantum mechanics, exemplified by Wigner functions. We elaborate on the solution of their evolution equations using logarithmic expansions and overview their kinetic interpretation. We illustrate how a Fokker-Planck equation can be derived using the master formulation of the same equations and its construction in the case of the transverse spin distributions. A simple connection of the leading order DGLAP equation to fractional diffusion using fractional calculus is also briefly outlined.Comment: Review article to appear in Lecture Notes of SIM (S. Dragomir ed.) 32 pages, 1 figur

Ultra High Energy Cosmic Rays and Air Shower Simulations: a top-bottom view

Stable Superstring Relics (SSR) provide some of the candidates for the possible origin of the Ultra High Energy Cosmic Rays (UHECR). After a brief overview of the motivations for introducing such relics, we address the question whether statistical fluctuations in the formation of the air showers generated by the primary spectrum of protons can be separated from a possible signal of new physics hidden in the first impact with the atmosphere. Our results are generated by using minimal modifications in the cross section of the primaries, and using available simulation codes used by the experimental collaborations. The results indicate that substantial increases in the cross section of the first impact, possibly due to new interactions, are unlikely to be detected in geometrical and/or variations of multiplicities in the cascade.Comment: 6 pages. 2 figures. Standard Latex. Typos corrected. To appear in the proceedings of the XV Incontri sulla Fisica delle Alte Energie (IFAE), Lecce, Italy, 23-26 April 200

Superstring Relics, Supersymmetric Fragmentation and UHECR

Superstring theory predicts the existence of relic metastable particles whose average lifetime is longer than the age of the universe and which could, in principle, be good dark matter candidates. At the same time, these states would be responsible for the Ultra High Energy Cosmic Rays (UHECR) events which will be searched for by various experimental collaborations in the near future. We describe a possible phenomenological path which could be followed in order to search for new physics in their detection.Comment: 7 pages 4 Figs. Plenary Talk presented by Claudio Coriano' at the 1st Intl. Conf. on String Phenomenology, Oxford, UK, July 6-11, 200

The Center for Medicare and Medicaid Innovation: Activity on Many Fronts

Provides an overview of the Innovation Center's organization, differences from CMS's traditional demonstration authority, payment and delivery reform initiatives, and first-year efforts to solicit and promote new ideas and collaborate with other payers

An Anomalous Extra Z Prime from Intersecting Branes with Drell-Yan and Direct Photons at the LHC

We quantify the impact of gauge anomalies at the Large Hadron Collider by studying the invariant mass distributions in Drell-Yan and in double prompt photon, using an extension of the Standard Model characterized by an additional anomalous U(1) derived from intersecting branes. The approach is rather general and applies to any anomalous abelian gauge current. Anomalies are cancelled using either the Wess-Zumino mechanism with suitable Peccei-Quinn-like interactions and a Stueckelberg axion, or by the Green-Schwarz mechanism. We compare predictions for the corresponding extra Z-prime to anomaly-free realizations such as those involving U(1)_{B-L}. We identify the leading anomalous corrections to both channels, which contribute at higher orders, and compare them against the next-to-next-to-leading order (NNLO) QCD background. Anomalous effects in these inclusive observables are found to be very small, far below the percent level and below the size of the typical QCD corrections quantified by NNLO K-factors.Comment: 46 pages, 36 figures, comments and citations adde

Double transverse-spin asymmetries in Drell--Yan and J/ψJ/\psi production from proton--antiproton collisions

We perform a NLO numerical study of the double transverse-spin asymmetries in the $J/\psi$ resonance region for proton--antiproton collisions. We analyze the large $x$ kinematic region, relevant for the proposed PAX experiment at GSI, and discuss the implication of the results for the extraction of the transversity densities.Comment: 8 pages, 6 figures, Talk given at "Transversity 2005" Como, Italy 7-10 Sep. 2005; eds. World Scientific in pres

Physical Representation-based Predicate Optimization for a Visual Analytics Database

Querying the content of images, video, and other non-textual data sources requires expensive content extraction methods. Modern extraction techniques are based on deep convolutional neural networks (CNNs) and can classify objects within images with astounding accuracy. Unfortunately, these methods are slow: processing a single image can take about 10 milliseconds on modern GPU-based hardware. As massive video libraries become ubiquitous, running a content-based query over millions of video frames is prohibitive. One promising approach to reduce the runtime cost of queries of visual content is to use a hierarchical model, such as a cascade, where simple cases are handled by an inexpensive classifier. Prior work has sought to design cascades that optimize the computational cost of inference by, for example, using smaller CNNs. However, we observe that there are critical factors besides the inference time that dramatically impact the overall query time. Notably, by treating the physical representation of the input image as part of our query optimization---that is, by including image transforms, such as resolution scaling or color-depth reduction, within the cascade---we can optimize data handling costs and enable drastically more efficient classifier cascades. In this paper, we propose Tahoma, which generates and evaluates many potential classifier cascades that jointly optimize the CNN architecture and input data representation. Our experiments on a subset of ImageNet show that Tahoma's input transformations speed up cascades by up to 35 times. We also find up to a 98x speedup over the ResNet50 classifier with no loss in accuracy, and a 280x speedup if some accuracy is sacrificed.Comment: Camera-ready version of the paper submitted to ICDE 2019, In Proceedings of the 35th IEEE International Conference on Data Engineering (ICDE 2019

Link-Prediction Enhanced Consensus Clustering for Complex Networks

Many real networks that are inferred or collected from data are incomplete due to missing edges. Missing edges can be inherent to the dataset (Facebook friend links will never be complete) or the result of sampling (one may only have access to a portion of the data). The consequence is that downstream analyses that consume the network will often yield less accurate results than if the edges were complete. Community detection algorithms, in particular, often suffer when critical intra-community edges are missing. We propose a novel consensus clustering algorithm to enhance community detection on incomplete networks. Our framework utilizes existing community detection algorithms that process networks imputed by our link prediction based algorithm. The framework then merges their multiple outputs into a final consensus output. On average our method boosts performance of existing algorithms by 7% on artificial data and 17% on ego networks collected from Facebook