Nonequilibrium fluid-dynamics in the early stage of ultrarelativistic heavy-ion collisions

To describe ultrarelativistic heavy-ion collisions we construct a three-fluid hydrodynamical model. In contrast to one-fluid hydrodynamics, it accounts for the finite stopping power of nuclear matter, i.e. for nonequilibrium effects in the early stage of the reaction. Within this model, we study baryon dynamics in the BNL-AGS energy range. For the system Au+Au we find that kinetic equilibrium between projectile and target nucleons is established only after a time $t_{CM}^{eq}\approx 5~fm/c\simeq 2R_{Au}/\gamma_{CM}$. Observables which are sensitive to the early stage of the collision (like e.g. nucleon flow) therefore differ considerably from those calculated in the one-fluid model.Comment: 36 pages, Late

Direct, Indirect and Collider Detection of Neutralino Dark Matter In SUSY Models with Non-universal Higgs Masses

In supersymmetric models with gravity-mediated SUSY breaking, universality of soft SUSY breaking sfermion masses m_0 is motivated by the need to suppress unwanted flavor changing processes. The same motivation, however, does not apply to soft breaking Higgs masses, which may in general have independent masses from matter scalars at the GUT scale. We explore phenomenological implications of both the one-parameter and two-parameter non-universal Higgs mass models (NUHM1 and NUHM2), and examine the parameter ranges compatible with Omega_CDM h^2, BF(b --> s,gamma) and (g-2)_mu constraints. In contrast to the mSUGRA model, in both NUHM1 and NUHM2 models, the dark matter A-annihilation funnel can be reached at low values of tan(beta), while the higgsino dark matter annihilation regions can be reached for low values of m_0. We show that there may be observable rates for indirect and direct detection of neutralino cold dark matter in phenomenologically aceptable ranges of parameter space. We also examine implications of the NUHM models for the Fermilab Tevatron, the CERN LHC and a Sqrt(s)=0.5-1 TeV e+e- linear collider. Novel possibilities include: very light s-top_R, s-charm_R squark and slepton_L masses as well as light charginos and neutralinos and H, A and H^+/- Higgs bosons.Comment: LaTeX, 48pages, 26 Figures. The version with high resolution Figures is available at http://hep.pa.msu.edu/belyaev/public/projects/nuhm/nuhm.p

A discursive approach to narrative accounts of hearing voices and recovery

Substantive objective: To research the range of discursive constructions ‘recovered’ voice hearers employ to describe hearing voices and the implications for positioning and subjectivity (what can be thought and felt) using each construction. Methodological objective and method: To explore a ‘sympathetic’ application of Foucauldian discourse analysis, adapting Willig’s (2008 Willig, C. 2008. Introducing Qualitative Research in Psychology, Maidenhead: Open University Press. ) method, analysing two published accounts. Results and conclusions: Heterogeneous discursive constructions for talking about hearing voices were identified, including: ‘many-’selves’’, ‘taking-the-lead-in-your-own-recovery’, ‘voices-as-an-’imagined-world’’ and ‘voices-as-a-coping-strategy-for-dealing-with-trauma’. The discourse of the biomedical model was not prominent, suggesting alternate discursive constructions may create subjects with a greater capacity for ‘living with voices’ and create a subjectivity from which vantage point the experience holds meaning and value and can be integrated into life experiences. This research may have useful clinical applications for mental health services aiming to collaboratively explore service users’ ways of understanding hearing voices

Graph Neural Networks for low-energy event classification & reconstruction in IceCube

IceCube, a cubic-kilometer array of optical sensors built to detect atmospheric and astrophysical neutrinos between 1 GeV and 1 PeV, is deployed 1.45 km to 2.45 km below the surface of the ice sheet at the South Pole. The classification and reconstruction of events from the in-ice detectors play a central role in the analysis of data from IceCube. Reconstructing and classifying events is a challenge due to the irregular detector geometry, inhomogeneous scattering and absorption of light in the ice and, below 100 GeV, the relatively low number of signal photons produced per event. To address this challenge, it is possible to represent IceCube events as point cloud graphs and use a Graph Neural Network (GNN) as the classification and reconstruction method. The GNN is capable of distinguishing neutrino events from cosmic-ray backgrounds, classifying different neutrino event types, and reconstructing the deposited energy, direction and interaction vertex. Based on simulation, we provide a comparison in the 1 GeV–100 GeV energy range to the current state-of-the-art maximum likelihood techniques used in current IceCube analyses, including the effects of known systematic uncertainties. For neutrino event classification, the GNN increases the signal efficiency by 18% at a fixed background rate, compared to current IceCube methods. Alternatively, the GNN offers a reduction of the background (i.e. false positive) rate by over a factor 8 (to below half a percent) at a fixed signal efficiency. For the reconstruction of energy, direction, and interaction vertex, the resolution improves by an average of 13%–20% compared to current maximum likelihood techniques in the energy range of 1 GeV–30 GeV. The GNN, when run on a GPU, is capable of processing IceCube events at a rate nearly double of the median IceCube trigger rate of 2.7 kHz, which opens the possibility of using low energy neutrinos in online searches for transient events.Peer Reviewe

The "spirit prevails",

"Scripture of the Church of the Firstborn."--Flake 5575.Preface signed: George S. Dove.FlakeMode of access: Internet

Differentiell lobformning för tvådimensionella antennuppställningar i ett LTE-FDD-system

Basstationer med flera antenner kan aktivt styra signalenergi mot en mottagare med hjälp av lobformning, vilket ger högre datatakt och lägre strömförbrukning än med en enda antenn. Lobformning kräver dock att kanalen skattas till varje antenn och i ett FDD-system måste denna skattning återkopplas till basstationen från mottagaren, vilket innebär en opraktiskt stor overhead, speciellt när loberna blir smalare. Differentiell lobformning är en robust teknik som med begränsad overhead möjliggör smala och välriktade lober genom differentiella justeringar av lobformen. Med hjälp av två förkodade referenssignaler från basstationen skattar mottagaren kanalen och rapporterar iterativt hur lobformningen ska förbättras så att SINR hos den mottagna signalen ökar. Den här uppsatsen utvecklar en algoritm som utökar differentiell lobformning till användandet av tvådimensionella antennuppställningar, vilket möjliggör justering av lobformen i två dimensioner och därmed potentiellt sett ökar mottagen signalstyrka. Algoritmen alternerar mellan att differentiellt justera lobformen horisontellt och vertikalt, utan ökad overhead. Algoritmen har testats för olika antennuppställningar i ett stadsscenario och ett landsbygdsscenario med horisontell användarfördelning, vilken dock har visat sig vara en begränsande faktor för att påvisa de potentiella vinster som differentiell lobformning i två dimensioner för med sig. Resultatet visar att det är viktigare att kunna erhålla en smal lob i den dimension där det finns många användare, i detta fall den horisontella dimensionen, än i den ortogonala dimensionen.Base stations with multiple antenna elements can actively direct signal energy towards a user by means of beam-forming, which results in higher data rates and lower energy consumption compared to a single antenna element. However, beam-forming requires channel state estimates to each antenna element and in an FDD system, these estimates must be fed back to the base station from the user. This feedback infer an inconvenient amount of overhead, especially as the beam gets narrow. Differential beam-forming is a robust technique that, through differential adjustments to the beam shape, allows for narrow and well-directed beams at a low overhead cost. By means of two precoded reference signals from the base station, the user estimates the channel and iteratively reports how the beam-forming should be improved in order to increase the SINR of the sent signal. This thesis develops an algorithm that extends differential beam-forming to the usage of two-dimensional antenna arrays, which allows for adjustments of the beam in two dimensions. Thereby, the received signal strength is potentially increased. The algorithm alternates between differential adjustments to the beam horizontally and vertically, without increased overhead. The algorithm is simulated with different array sizes using an urban and a rural scenario with a horizontal user distribution. However, the biased user distribution has proven to constitute a limiting factor in order to demonstrate the potential benefits of differential beam-forming in two dimensions. The result shows that it is more important to obtain a narrow beam in the dimension where many users are located, in this case the horizontal dimension, than in the orthogonal dimension