The strange-quark chemical potential as an experimentally accessible "order parameter" of the deconfinement phase transition for finite baryon-density

We consider the change of the strange-quark chemical potential in the phase diagram of nuclear matter, employing the Wilson loop and scalar quark condensate order parameters, mass-scaled partition functions and enforcing flavor conservation. Assuming the region beyond the hadronic phase to be described by massive, correlated and interacting quarks, in the spirit of lattice and effective QCD calculations, we find the strange-quark chemical potential to change sign: from positive in the hadronic phase - to zero upon deconfinement - to negative in the partonic domain. We propose this change in the sign of the strange-quark chemical potential to be an experimentally accessible order parameter and a unique, concise and well-defined indication of the quark-deconfinement phase transition in nuclear matter.Comment: 22 pages, 14 figures within text, 2 figures(6,B3) as separate files. To be published in J.Phys.G: Nucl.&Part.Phys. G28 (2002

Model of Centauro and strangelet production in heavy ion collisions

We discuss the phenomenological model of Centauro event production in relativistic nucleus-nucleus collisions. This model makes quantitative predictions for kinematic observables, baryon number and mass of the Centauro fireball and its decay products. Centauros decay mainly to nucleons, strange hyperons and possibly strangelets. Simulations of Centauro events for the CASTOR detector in Pb-Pb collisions at LHC energies are performed. The signatures of these events are discussed in detail.Comment: 19 pages, LaTeX+revtex4, 14 eps-figures and 3 table

Agnostic Learning for Packing Machine Stoppage Prediction in Smart Factories

The cyber-physical convergence is opening up new business opportunities for industrial operators. The need for deep integration of the cyber and the physical worlds establishes a rich business agenda towards consolidating new system and network engineering approaches. This revolution would not be possible without the rich and heterogeneous sources of data, as well as the ability of their intelligent exploitation, mainly due to the fact that data will serve as a fundamental resource to promote Industry 4.0. One of the most fruitful research and practice areas emerging from this data-rich, cyber-physical, smart factory environment is the data-driven process monitoring field, which applies machine learning methodologies to enable predictive maintenance applications. In this paper, we examine popular time series forecasting techniques as well as supervised machine learning algorithms in the applied context of Industry 4.0, by transforming and preprocessing the historical industrial dataset of a packing machine's operational state recordings (real data coming from the production line of a manufacturing plant from the food and beverage domain). In our methodology, we use only a single signal concerning the machine's operational status to make our predictions, without considering other operational variables or fault and warning signals, hence its characterization as ``agnostic''. In this respect, the results demonstrate that the adopted methods achieve a quite promising performance on three targeted use cases

Performance Studies of Prototype II for the CASTOR forward Calorimeter at the CMS Experiment

We present results of the performance of the second prototype of the CASTOR quartz-tungsten sampling calorimeter, to be installed in the very forward region of the CMS experiment at the LHC. The energy linearity and resolution, as well as the spatial resolution of the prototype to electromagnetic and hadronic showers are studied with E=20-200 GeV electrons, E=20-350 GeV pions, and E=50,150 GeV muons from beam tests carried out at CERN/SPS in 2004. The responses of the calorimeter using two different types of photodetectors (avalanche photodiodes APDs, and photomultiplier tubes PMTs) are compared.Comment: 16 pages, 22 figs., submitted to EPJ-

How asynchrony affects rumor spreading time

International audienceIn standard randomized (push-pull) rumor spreading, nodes communicate in synchronized rounds. In each round every node contacts a random neighbor in order to exchange the rumor (i.e., either push the rumor to its neighbor or pull it from the neighbor). A natural asynchronous variant of this algorithm is one where each node has an independent Poisson clock with rate 1, and every node contacts a random neighbor whenever its clock ticks. This asynchronous variant is arguably a more realistic model in various settings, including message broadcasting in communication networks, and information dissemination in social networks. In this paper we study how asynchrony affects the rumor spreading time, that is, the time before a rumor originated at a single node spreads to all nodes in the graph. Our first result states that the asynchronous push-pull rumor spreading time is asymptotically bounded by the standard synchronous time. Precisely, we show that for any graph G on n nodes, where the synchronous push-pull protocol informs all nodes within T (G) rounds with high probability, the asynchronous protocol needs at most time O(T (G) + log n) to inform all nodes with high probability. On the other hand, we show that the expected synchronous push-pull rumor spreading time is bounded by O(√ n) times the expected asynchronous time. These results improve upon the bounds for both directions shown recently by Acan et al. (PODC 2015). An interesting implication of our first result is that in regular graphs, the weaker push-only variant of synchronous rumor spreading has the same asymptotic performance as the synchronous push-pull algorithm

Information entropy in fragmenting systems

The possibility of facing critical phenomena in nuclear fragmentation is a topic of great interest. Different observables have been proposed to identify such a behavior, in particular, some related to the use of information entropy as a possible signal of critical behavior. In this work we critically examine some of the most widespread used ones comparing its performance in bond percolation and in the analysis of fragmenting Lennard Jones Drops.Comment: 3 pages, 3 figure

Formation of Centauro and Strangelets in Nucleus-Nucleus Collisions at the LHC and their Identification by the ALICE Experiment

We present a phenomenological model which describes the formation of a Centauro fireball in nucleus-nucleus interactions in the upper atmosphere and at the LHC, and its decay to non-strange baryons and Strangelets. We describe the CASTOR detector for the ALICE experiment at the LHC. CASTOR will probe, in an event-by-event mode, the very forward, baryon-rich phase space 5.6 < \eta < 7.2 in 5.5 A TeV central Pb + Pb collisions. We present results of simulations for the response of the CASTOR calorimeter, and in particular to the traversal of Strangelets.Comment: 4 pages, 4 figures, to appear in the proceedings of the 26th ICR

Lambda^0 polarization as a probe for production of deconfined matter in ultra-relativistic heavy-ion collisions

We study the polarization change of Lambda^0's produced in ultra-relativistic heavy-ion collisions with respect to the polarization observed in proton-proton collisions as a signal for the formation of a Quark-Gluon Plasma (QGP). Assuming that, when the density of participants in the collision is larger than the critical density for QGP formation, the Lambda^0 production mechanism changes from recombination type processes to the coalescence of free valence quarks, we find that the Lambda^0 polarization depends on the relative contribution of each process to the total number of Lambda^0's produced in the collision. To describe the polarization of Lambda^0's in nuclear collisions for densities below the critical density for the QGP formation, we use the DeGrand-Miettinen model corrected for the effects introduced by multiple scattering of the produced Lambda^0 within the nuclear environment.Comment: 9 pages, 6 figures, uses ReVTeX and epsfig.st