Heavy pseudoscalar mesons in a Schwinger-Dyson--Bethe-Salpeter approach

The mass spectrum of heavy pseudoscalar mesons, described as quark-antiquark bound systems, is considered within the Bethe-Salpeter formalism with momentum-dependent masses of the constituents. This dependence is found by solving the Schwinger-Dyson equation for quark propagators in rainbow-ladder approximation. Such an approximation is known to provide both a fast convergence of numerical methods and accurate results for lightest mesons. However, as the meson mass increases, the method becomes less stable and special attention must be devoted to details of numerical means of solving the corresponding equations. We focus on the pseudoscalar sector and show that our numerical scheme describes fairly accurately the $\pi$, $K$, $D$, $D_s$ and $\eta_c$ ground states. Excited states are considered as well. Our calculations are directly related to the future physics programme at FAIR.Comment: 9 pages, 3 figures; Based on materials of the contribution "Relativistic Description of Two- and Three-Body Systems in Nuclear Physics", ECT*, October 19-23, 200

Time dependent mean field theory of the superfluid-insulator phase transition

We develop a time-dependent mean field approach, within the time-dependent variational principle, to describe the Superfluid-Insulator quantum phase transition. We construct the zero temperature phase diagram both of the Bose-Hubbard model (BHM), and of a spin-S Heisenberg model (SHM) with the XXZ anisotropy. The phase diagram of the BHM indicates a phase transition from a Mott insulator to a compressibile superfluid phase, and shows the expected lobe-like structure. The SHM phase diagram displays a quantum phase transition between a paramagnetic and a canted phases showing as well a lobe-like structure. We show how the BHM and Quantum Phase model (QPM) can be rigorously derived from the SHM. Based on such results, the phase boundaries of the SHM are mapped to the BHM ones, while the phase diagram of the QPM is related to that of the SHM. The QPM's phase diagram obtained through the application of our approach to the SHM, describes the known onset of the macroscopic phase coherence from the Coulomb blockade regime for increasing Josephson coupling constant. The BHM and the QPM phase diagrams are in good agreement with Quantum Monte Carlo results, and with the third order strong coupling perturbative expansion.Comment: 15 pages, 8 figures. To be published in Phys. Rev.

The therapeutic ratio in BNCT: Assessment using the Rat 9L gliosarcoma brain tumor and spinal cord models

During any radiation therapy, the therapeutic tumor dose is limited by the tolerance of the surrounding normal tissue within the treatment volume. The short ranges of the products of the {sup 10}B(n,{alpha}){sup 7}Li reaction produced during boron neutron capture therapy (BNCT) present an opportunity to increase the therapeutic ratio (tumor dose/normal tissue dose) to levels unprecedented in photon radiotherapy. The mixed radiation field produced during BNCT comprises radiations with different linear energy transfer (LET) and different relative biological effectiveness (RBE). The short ranges of the two high-LET products of the `B(n,a)`Li reaction make the microdistribution of the boron relative to target cell nuclei of particular importance. Due to the tissue specific distribution of different boron compounds, the term RBE is inappropriate in defining the biological effectiveness of the {sup 10}B(n,{alpha}){sup 7}Li reaction. To distinguish these differences from true RBEs we have used the term {open_quotes}compound biological effectiveness{close_quotes} (CBE) factor. The latter can be defined as the product of the true, geometry-independent, RBE for these particles times a {open_quotes}boron localization factor{close_quotes}, which will most likely be different for each particular boron compound. To express the total BNCT dose in a common unit, and to compare BNCT doses with the effects of conventional photon irradiation, multiplicative factors (RBEs and CBEs) are applied to the physical absorbed radiation doses from each high-LET component. The total effective BNCT dose is then expressed as the sum of RBE-corrected physical absorbed doses with the unit Gray-equivalent (Gy-Eq)

BPA uptake in rat tissues after partial hepatectomy

In boron neutron capture therapy (BNCT), boron given as boronophenylalanine (BPA) accumulates transiently not only in tumors but also in normal tissues. Average boron concentrations in transplanted 9L gliosarcoma tumors of 20 rats were 2.5 to 3.7 times concentrations found in blood. Although boron levels in a variety of tissues were also higher than blood the concentrations were less than the lowest found in the tumor. Further note than although BPA is a structural analogue of phenylalanine (Phe), the pathway of BPA uptake into regenerating liver may not be linked to Phe uptake mechanisms

The Role of Human-Automation Consensus in Multiple Unmanned Vehicle Scheduling

Objective: This study examined the impact of increasing automation replanning rates on operator performance and workload when supervising a decentralized network of heterogeneous unmanned vehicles. Background: Futuristic unmanned vehicles systems will invert the operator-to-vehicle ratio so that one operator can control multiple dissimilar vehicles connected through a decentralized network. Significant human-automation collaboration will be needed because of automation brittleness, but such collaboration could cause high workload. Method: Three increasing levels of replanning were tested on an existing multiple unmanned vehicle simulation environment that leverages decentralized algorithms for vehicle routing and task allocation in conjunction with human supervision. Results: Rapid replanning can cause high operator workload, ultimately resulting in poorer overall system performance. Poor performance was associated with a lack of operator consensus for when to accept the automation’s suggested prompts for new plan consideration as well as negative attitudes toward unmanned aerial vehicles in general. Participants with video game experience tended to collaborate more with the automation, which resulted in better performance. Conclusion: In decentralized unmanned vehicle networks, operators who ignore the automation’s requests for new plan consideration and impose rapid replans both increase their own workload and reduce the ability of the vehicle network to operate at its maximum capacity. Application: These findings have implications for personnel selection and training for futuristic systems involving human collaboration with decentralized algorithms embedded in networks of autonomous systems.Aurora Flight Sciences Corp.United States. Office of Naval Researc

Two-dimensional SIR epidemics with long range infection

We extend a recent study of susceptible-infected-removed epidemic processes with long range infection (referred to as I in the following) from 1-dimensional lattices to lattices in two dimensions. As in I we use hashing to simulate very large lattices for which finite size effects can be neglected, in spite of the assumed power law $p({\bf x})\sim |{\bf x}|^{-\sigma-2}$ for the probability that a site can infect another site a distance vector ${\bf x}$ apart. As in I we present detailed results for the critical case, for the supercritical case with $\sigma = 2$, and for the supercritical case with $0< \sigma < 2$. For the latter we verify the stretched exponential growth of the infected cluster with time predicted by M. Biskup. For $\sigma=2$ we find generic power laws with $\sigma-$dependent exponents in the supercritical phase, but no Kosterlitz-Thouless (KT) like critical point as in 1-d. Instead of diverging exponentially with the distance from the critical point, the correlation length increases with an inverse power, as in an ordinary critical point. Finally we study the dependence of the critical exponents on $\sigma$ in the regime $0<\sigma <2$, and compare with field theoretic predictions. In particular we discuss in detail whether the critical behavior for $\sigma$ slightly less than 2 is in the short range universality class, as conjectured recently by F. Linder {\it et al.}. As in I we also consider a modified version of the model where only some of the contacts are long range, the others being between nearest neighbors. If the number of the latter reaches the percolation threshold, the critical behavior is changed but the supercritical behavior stays qualitatively the same.Comment: 14 pages, including 29 figure

Development of a tight-binding potential for bcc-Zr. Application to the study of vibrational properties

We present a tight-binding potential based on the moment expansion of the density of states, which includes up to the fifth moment. The potential is fitted to bcc and hcp Zr and it is applied to the computation of vibrational properties of bcc-Zr. In particular, we compute the isothermal elastic constants in the temperature range 1200K < T < 2000K by means of standard Monte Carlo simulation techniques. The agreement with experimental results is satisfactory, especially in the case of the stability of the lattice with respect to the shear associated with C'. However, the temperature decrease of the Cauchy pressure is not reproduced. The T=0K phonon frequencies of bcc-Zr are also computed. The potential predicts several instabilities of the bcc structure, and a crossing of the longitudinal and transverse modes in the (001) direction. This is in agreement with recent ab initio calculations in Sc, Ti, Hf, and La.Comment: 14 pages, 6 tables, 4 figures, revtex; the kinetic term of the isothermal elastic constants has been corrected (Eq. (4.1), Table VI and Figure 4

Heat capacity studies of Ce and Rh site substitution in the heavy fermion antiferromagnet CeRhIn_5;: Short-range magnetic interactions and non-Fermi-liquid behavior

In heavy fermion materials superconductivity tends to appear when long range magnetic order is suppressed by chemical doping or applying pressure. Here we report heat capacity measurements on diluted alloyes of the heavy fermion superconductor CeRhIn_5;. Heat capacity measurements have been performed on CeRh_{1-y}Ir_{y}In_5; (y <= 0.10) and Ce_{1-x}La_{x}Rh_{1-y}Ir_{y}In_5; (x <= 0.50) in applied fields up to 90 kOe to study the affect of doping and magnetic field on the magnetic ground state. The magnetic phase diagram of CeRh_{0.9}Ir_{0.1}In_5; is consistent with the magnetic structure of CeRhIn_5; being unchanged by Ir doping. Doping of Ir in small concentrations is shown to slightly increase the antiferromagnetic transition temperature T_{N} (T_{N}=3.8 K in the undoped sample). La doping which causes disorder on the Ce sublattice is shown to lower T_{N} with no long range order observed above 0.34 K for Ce_{0.50}La_{0.50}RhIn_5;. Measurements on Ce_{0.50}La_{0.50}RhIn_5; show a coexistence of short range magnetic order and non-Fermi-liquid behavior. This dual nature of the Ce 4f-electrons is very similar to the observed results on CeRhIn_5; when long range magnetic order is suppressed at high pressure.Comment: 8 pages, 9 figure

ϵ\epsilon-Expansion of the Conductivity at the Superconductor-Mott Insulator Transition

We study the critical behavior of the conductivity $\sigma(\omega)$ at the zero temperature superconductor-Mott insulator transition in $d$ space-time dimensions for a model of bosons with short-range interaction and no disorder. We obtain $\sigma(\omega_n ) = (4e^2/\hbar) \sigma_{\epsilon} \omega_n^{1-\epsilon}$, as predicted by the scaling theory, and the prefactor $\sigma_{\epsilon}$ is calculated in the $\epsilon$-expansion, to order $\epsilon ^2$ ($\epsilon = 4-d$). In two spatial dimensions, ($d=3$), we find a value of the universal conductance $\sigma^\star =0.315 (4e^2/h)$, in good agreement with the known Monte Carlo results.Comment: 8 pages REVTE

Towards Machine Wald

The past century has seen a steady increase in the need of estimating and predicting complex systems and making (possibly critical) decisions with limited information. Although computers have made possible the numerical evaluation of sophisticated statistical models, these models are still designed \emph{by humans} because there is currently no known recipe or algorithm for dividing the design of a statistical model into a sequence of arithmetic operations. Indeed enabling computers to \emph{think} as \emph{humans} have the ability to do when faced with uncertainty is challenging in several major ways: (1) Finding optimal statistical models remains to be formulated as a well posed problem when information on the system of interest is incomplete and comes in the form of a complex combination of sample data, partial knowledge of constitutive relations and a limited description of the distribution of input random variables. (2) The space of admissible scenarios along with the space of relevant information, assumptions, and/or beliefs, tend to be infinite dimensional, whereas calculus on a computer is necessarily discrete and finite. With this purpose, this paper explores the foundations of a rigorous framework for the scientific computation of optimal statistical estimators/models and reviews their connections with Decision Theory, Machine Learning, Bayesian Inference, Stochastic Optimization, Robust Optimization, Optimal Uncertainty Quantification and Information Based Complexity.Comment: 37 page