Study of isolated prompt photon production in p p -Pb collisions for the ALICE kinematics

Prompt photon production is known as a powerful tool for testing perturbative QCD predictions and also the validity of parton densities in the nucleon and nuclei especially of the gluon. In this work, we have performed a detailed study on this subject focusing on the isolated prompt photon production in $p$-Pb collisions at forward rapidity at the LHC. The impact of input nuclear modifications obtained from different global analyses by various groups on several quantities has been investigated to estimate the order of magnitude of the difference between their predictions. We have also studied in detail the theoretical uncertainties in the results due to various sources. We found that there is a remarkable difference between the predictions from the nCTEQ15 and other groups in all ranges of photon transverse momentum $p_\textrm{T}^\gamma$. Their differences become more explicit in the calculation of the nuclear modification ratio and also the yield asymmetry between the forward and backward rapidities rather than single differential cross sections. We emphasize that future measurements with ALICE will be very useful not only for decreasing the uncertainty of the gluon nuclear modification, but also to accurately determine its central values, especially in the shadowing region.Comment: 12 pages, 10 figure

Approximating the Permanent of a Random Matrix with Vanishing Mean

We show an algorithm for computing the permanent of a random matrix with vanishing mean in quasi-polynomial time. Among special cases are the Gaussian, and biased-Bernoulli random matrices with mean 1/lnln(n)^{1/8}. In addition, we can compute the permanent of a random matrix with mean 1/poly(ln(n)) in time 2^{O(n^{\eps})} for any small constant \eps>0. Our algorithm counters the intuition that the permanent is hard because of the "sign problem" - namely the interference between entries of a matrix with different signs. A major open question then remains whether one can provide an efficient algorithm for random matrices of mean 1/poly(n), whose conjectured #P-hardness is one of the baseline assumptions of the BosonSampling paradigm

Approximate unitary tt-designs by short random quantum circuits using nearest-neighbor and long-range gates

We prove that $poly(t) \cdot n^{1/D}$-depth local random quantum circuits with two qudit nearest-neighbor gates on a $D$-dimensional lattice with n qudits are approximate $t$-designs in various measures. These include the "monomial" measure, meaning that the monomials of a random circuit from this family have expectation close to the value that would result from the Haar measure. Previously, the best bound was $poly(t)\cdot n$ due to Brandao-Harrow-Horodecki (BHH) for $D=1$. We also improve the "scrambling" and "decoupling" bounds for spatially local random circuits due to Brown and Fawzi. One consequence of our result is that assuming the polynomial hierarchy (PH) is infinite and that certain counting problems are $\#P$-hard on average, sampling within total variation distance from these circuits is hard for classical computers. Previously, exact sampling from the outputs of even constant-depth quantum circuits was known to be hard for classical computers under the assumption that PH is infinite. However, to show the hardness of approximate sampling using this strategy requires that the quantum circuits have a property called "anti-concentration", meaning roughly that the output has near-maximal entropy. Unitary 2-designs have the desired anti-concentration property. Thus our result improves the required depth for this level of anti-concentration from linear depth to a sub-linear value, depending on the geometry of the interactions. This is relevant to a recent proposal by the Google Quantum AI group to perform such a sampling task with 49 qubits on a two-dimensional lattice and confirms their conjecture that $O(\sqrt n)$ depth suffices for anti-concentration. We also prove that anti-concentration is possible in depth O(log(n) loglog(n)) using a different model

Coupling between time series: a network view

Recently, the visibility graph has been introduced as a novel view for analyzing time series, which maps it to a complex network. In this paper, we introduce new algorithm of visibility, "cross-visibility", which reveals the conjugation of two coupled time series. The correspondence between the two time series is mapped to a network, "the cross-visibility graph", to demonstrate the correlation between them. We applied the algorithm to several correlated and uncorrelated time series, generated by the linear stationary ARFIMA process. The results demonstrate that the cross-visibility graph associated with correlated time series with power-law auto-correlation is scale-free. If the time series are uncorrelated, the degree distribution of their cross-visibility network deviates from power-law. For more clarifying the process, we applied the algorithm to real-world data from the financial trades of two companies, and observed significant small-scale coupling in their dynamics

THE PROINFLAMMATORY EFFECT OF STRUCTURALLY ALTERED ELASTIC FIBERS IN A HAMSTER MODEL OF COPD EXACERBATION

To further understand the effect of superimposed lung inflammation on COPD, our laboratory developed a hamster model of COPD exacerbations using sequential intratracheal instillations of lipopolysaccharide (LPS) and elastase. Using this model, the superimposed inflammatory effect of LPS on elastase-induced emphysema was studied through morphological and biochemical parameters. Total leukocyte and percent neutrophil count in bronchoalveolar lavage fluid (BALF), and elastin-specific desmosine crosslinks (DID) were measured 48 hours after LPS treatment. Morphometric changes were evaluated with mean linear intercept (MLI) methods, and interstitial elastic fiber and lung surface area measurements 1 week post-LPS treatment. Compared to controls, animals treated with elastase/LPS showed a significant increase in BALF leukocytes (187 vs 47.7 x 104 cells), neutrophils (39 vs 4.8 percent), and free DID levels (182 vs 97 percent). Additionally, MLI was significantly elevated in the elastase/LPS group compared to controls (156.2 vs 81.7micrometer). Due to enhanced splaying and fragmentation of elastic fibers, interstitial elastic fiber surface area was significantly increased in animals treated with elastase/LPS than controls (49 vs 26 percent). On the other hand, lung surface area was decreased in elastase/LPS group compared to controls (17.8 vs 25.5 percent). Furthermore, intratracheal instillations of elastin peptides and LPS demonstrated significant effects on BALF neutrophils, free DID levels and leukocyte chemotactic properties. The results suggest that structural alterations in elastic fibers during exacerbations make them more susceptible to breakdown and may have a proinflammatory effect further accelerating loss of lung parenchyma and function

Non-Classical Symmetry Solutions to the Fitzhugh Nagumo Equation.

In Reaction-Diffusion systems, some parameters can influence the behavior of other parameters in that system. Thus reaction diffusion equations are often used to model the behavior of biological phenomena. The Fitzhugh Nagumo partial differential equation is a reaction diffusion equation that arises both in population genetics and in modeling the transmission of action potentials in the nervous system. In this paper we are interested in finding solutions to this equation. Using Lie groups in particular, we would like to find symmetries of the Fitzhugh Nagumo equation that reduce this non-linear PDE to an Ordinary Differential Equation. In order to accomplish this task, the non-classical method is utilized to find the infinitesimal generator and the invariant surface condition for the subgroup where the solutions for the desired PDE exist. Using the infinitesimal generator and the invariant surface condition, we reduce the PDE to a mildly nonlinear ordinary differential equation that could be explored numerically or perhaps solved in closed form