Evidence of Unconventional Universality Class in a Two-Dimensional Dimerized Quantum Heisenberg Model

The two-dimensional $J$-$J^\prime$ dimerized quantum Heisenberg model is studied on the square lattice by means of (stochastic series expansion) quantum Monte Carlo simulations as a function of the coupling ratio \hbox{$\alpha=J^\prime/J$}. The critical point of the order-disorder quantum phase transition in the $J$-$J^\prime$ model is determined as \hbox{$\alpha_\mathrm{c}=2.5196(2)$} by finite-size scaling for up to approximately $10 000$ quantum spins. By comparing six dimerized models we show, contrary to the current belief, that the critical exponents of the $J$-$J^\prime$ model are not in agreement with the three-dimensional classical Heisenberg universality class. This lends support to the notion of nontrivial critical excitations at the quantum critical point.Comment: 4+ pages, 5 figures, version as publishe

Academic Service Learning: Bridging the Theory/Practice Gap

This hybrid session/roundtable will provide insight regarding the integration of academic service learning in collegiate curriculum. Nursing and LUCOM faculty will showcase past ASL opportunities, which continue to be community staples. Further discussion will provide insight regarding how academic service learning (ASL) fits in curriculum, the implementation of experiential learning, the importance of working with community partners, and the value of reflection in support of sustainability

Longitudinal Beam Dynamics at Transition Crossing

A brief outline of the longitudinal single particle dynamics at transition is presented in terms of phase-space mappings. Simple quantitative prediction about the phase-space dilution is made. More realistic simulation (ESME) of the transition crossing is carried out (including various collective and single particle effects contributing to the longitudinal emittance blow up). The simulation takes into account the longitudinal space-charge force (bunch length oscillation), the transverse space-charge (the Umstaetter effect) and finally the dispersion of the momentum compaction factor (the Johnsen effect). As a result of this simulation one can separate relative strengths of the above mechanisms and study their individual effects on the longitudinal phase-space evolution, especially filamentation of the bunch and formation of a galaxy-like'' pattern. 7 refs., 2 figs

Simulation of Coupled Bunch Mode Growth Driven by a High-Q Resonator: A Transient Response Approach

In this article the use of a longitudinal phase-space tracking code, ESME, to simulate the growth of a coupled-bunch instability in the Fermilab Booster is examined. A description of the calculation of the resonant response is given, and results are presented for the growth of the coupled bunch instability in a ring in which all of the rf buckets are equally populated and in one in which several consecutive buckets are empty. 4 refs., 6 figs

Coupled Bunch Instability in Fermilab Booster: Longitudinal Phase-Space Simulation

The physical presence of vacuum structures can be expressed in terms of a coupling impedance experienced by the beam. The beam environment considered here consist of parasitic higher order modes of the r.f. cavities. These resonances may have high enough Q's to allow consecutive bunches to interact through mutually induced fields. The cumulative effect of such fields as the particles pass through the cavity may be to induce a coherent buildup in synchrotron motion of the bunches, i.e., a longitudinal coupled-bunch instability. The colliding mode operation of the present generation of high energy synchrotrons and the accompanying r.f. manipulations, make considerations of individual bunch area of paramount importance. Thus, a longitudinal instability in one of a chain of accelerators, while not leading to any immediate reduction in the intensity of the beam in that accelerator, may cause such a reduction of beam quality that later operations are inhibited (resulting in a degradation performance). In this paper we employ a longitudinal phase-space tracking code (ESME) as an effective tool to simulate specific coupled bunch modes arising in a circular accelerator. One of the obvious advantages of the simulation compared to existing analytic formalisms, e.g., based on the Vlasov equation, is that it allows consideration of the instability in a self-consistent manner with respect to the changing accelerating conditions. Furthermore this scheme allows to model nonlinearities of the longitudinal beam dynamics, which are usually not tractable analytically. 5 refs., 3 figs

The NuMAX Long Baseline Neutrino Factory Concept

A Neutrino Factory where neutrinos of all species are produced in equal quantities by muon decay is described as a facility at the intensity frontier for exquisite precision providing ideal conditions for ultimate neutrino studies and the ideal complement to Long Baseline Facilities like LBNF at Fermilab. It is foreseen to be built in stages with progressively increasing complexity and performance, taking advantage of existing or proposed facilities at an existing laboratory like Fermilab. A tentative layout based on a recirculating linac providing opportunities for considerable saving is discussed as well as its possible evolution toward a muon collider if and when requested by Physics. Tentative parameters of the various stages are presented as well as the necessary R&D to address the technological issues and demonstrate their feasibility.Comment: JINST Special Issue on Muon Accelerators. arXiv admin note: text overlap with arXiv:1308.0494, arXiv:1502.0164

Predictive coding networks for temporal prediction

One of the key problems the brain faces is inferring the state of the world from a sequence of dynamically changing stimuli, and it is not yet clear how the sensory system achieves this task. A well-established computational framework for describing perceptual processes in the brain is provided by the theory of predictive coding. Although the original proposals of predictive coding have discussed temporal prediction, later work developing this theory mostly focused on static stimuli, and key questions on neural implementation and computational properties of temporal predictive coding networks remain open. Here, we address these questions and present a formulation of the temporal predictive coding model that can be naturally implemented in recurrent networks, in which activity dynamics rely only on local inputs to the neurons, and learning only utilises local Hebbian plasticity. Additionally, we show that temporal predictive coding networks can approximate the performance of the Kalman filter in predicting behaviour of linear systems, and behave as a variant of a Kalman filter which does not track its own subjective posterior variance. Importantly, temporal predictive coding networks can achieve similar accuracy as the Kalman filter without performing complex mathematical operations, but just employing simple computations that can be implemented by biological networks. Moreover, when trained with natural dynamic inputs, we found that temporal predictive coding can produce Gabor-like, motion-sensitive receptive fields resembling those observed in real neurons in visual areas. In addition, we demonstrate how the model can be effectively generalized to nonlinear systems. Overall, models presented in this paper show how biologically plausible circuits can predict future stimuli and may guide research on understanding specific neural circuits in brain areas involved in temporal prediction