Traffic Flow: An Approach towards Modeling the Right Lane Rule

We attempted to model and analyze the effect of the right hand rule for the 2014 COMAP Math Modeling Competition. In order to analyze the right hand rule we started with Greenshield’s macroscopic approach and modified it to simulate the effects of the right hand rule. By analyzing the resulting changes in the flow and density of the system we determined the performance of the rule in varying traffic densities. Next we looked at the performance by modeling traffic flow when the rule is strictly adhered to, as compared to an intermediate, where the rule is followed until the critical density is reached. In the intermediate model we show how traffic flow can be maximized if people no longer follow the right hand rule after the critical density

Future Prospects: Deep Imaging of Galaxy Outskirts using Telescopes Large and Small

The Universe is almost totally unexplored at low surface brightness levels. In spite of great progress in the construction of large telescopes and improvements in the sensitivity of detectors, the limiting surface brightness of imaging observations has remained static for about forty years. Recent technical advances have at last begun to erode the barriers preventing progress. In this Chapter we describe the technical challenges to low surface brightness imaging, describe some solutions, and highlight some relevant observations that have been undertaken recently with both large and small telescopes. Our main focus will be on discoveries made with the Dragonfly Telephoto Array (Dragonfly), which is a new telescope concept designed to probe the Universe down to hitherto unprecedented low surface brightness levels. We conclude by arguing that these discoveries are probably only scratching the surface of interesting phenomena that are observable when the Universe is explored at low surface brightness levels.Comment: 27 pages, 10 figures, Invited review, Book chapter in "Outskirts of Galaxies", Eds. J. H. Knapen, J. C. Lee and A. Gil de Paz, Astrophysics and Space Science Library, Springer, in pres

A Probabilistic proof of the breakdown of Besov regularity in LL-shaped domains

{We provide a probabilistic approach in order to investigate the smoothness of the solution to the Poisson and Dirichlet problems in $L$-shaped domains. In particular, we obtain (probabilistic) integral representations for the solution. We also recover Grisvard's classic result on the angle-dependent breakdown of the regularity of the solution measured in a Besov scale

Structure and Dynamics of the Sun's Open Magnetic Field

The solar magnetic field is the primary agent that drives solar activity and couples the Sun to the Heliosphere. Although the details of this coupling depend on the quantitative properties of the field, many important aspects of the corona - solar wind connection can be understood by considering only the general topological properties of those regions on the Sun where the field extends from the photosphere out to interplanetary space, the so-called open field regions that are usually observed as coronal holes. From the simple assumptions that underlie the standard quasi-steady corona-wind theoretical models, and that are likely to hold for the Sun, as well, we derive two conjectures on the possible structure and dynamics of coronal holes: (1) Coronal holes are unique in that every unipolar region on the photosphere can contain at most one coronal hole. (2) Coronal holes of nested polarity regions must themselves be nested. Magnetic reconnection plays the central role in enforcing these constraints on the field topology. From these conjectures we derive additional properties for the topology of open field regions, and propose several observational predictions for both the slowly varying and transient corona/solar wind.Comment: 26 pages, 6 figure

The Effects of Wave Escape on Fast Magnetosonic Wave Turbulence in Solar Flares

One of the leading models for electron acceleration in solar flares is stochastic acceleration by weakly turbulent fast magnetosonic waves ("fast waves"). In this model, large-scale flows triggered by magnetic reconnection excite large-wavelength fast waves, and fast-wave energy then cascades from large wavelengths to small wavelengths. Electron acceleration by large-wavelength fast-waves is weak, and so the model relies on the small-wavelength waves produced by the turbulent cascade. In order for the model to work, the energy cascade time for large-wavelength fast waves must be shorter than the time required for the waves to propagate out of the solar-flare acceleration region. To investigate the effects of wave escape, we solve the wave kinetic equation for fast waves in weak turbulence theory, supplemented with a homogeneous wave-loss term.We find that the amplitude of large-wavelength fast waves must exceed a minimum threshold in order for a significant fraction of the wave energy to cascade to small wavelengths before the waves leave the acceleration region.We evaluate this threshold as a function of the dominant wavelength of the fast waves that are initially excited by reconnection outflows

Sparse Deterministic Approximation of Bayesian Inverse Problems

We present a parametric deterministic formulation of Bayesian inverse problems with input parameter from infinite dimensional, separable Banach spaces. In this formulation, the forward problems are parametric, deterministic elliptic partial differential equations, and the inverse problem is to determine the unknown, parametric deterministic coefficients from noisy observations comprising linear functionals of the solution. We prove a generalized polynomial chaos representation of the posterior density with respect to the prior measure, given noisy observational data. We analyze the sparsity of the posterior density in terms of the summability of the input data's coefficient sequence. To this end, we estimate the fluctuations in the prior. We exhibit sufficient conditions on the prior model in order for approximations of the posterior density to converge at a given algebraic rate, in terms of the number $N$ of unknowns appearing in the parameteric representation of the prior measure. Similar sparsity and approximation results are also exhibited for the solution and covariance of the elliptic partial differential equation under the posterior. These results then form the basis for efficient uncertainty quantification, in the presence of data with noise

New coins from old, smoothly

Given a (known) function $f:[0,1] \to (0,1)$, we consider the problem of simulating a coin with probability of heads $f(p)$ by tossing a coin with unknown heads probability $p$, as well as a fair coin, $N$ times each, where $N$ may be random. The work of Keane and O'Brien (1994) implies that such a simulation scheme with the probability $\P_p(N<\infty)$ equal to 1 exists iff $f$ is continuous. Nacu and Peres (2005) proved that $f$ is real analytic in an open set $S \subset (0,1)$ iff such a simulation scheme exists with the probability $\P_p(N>n)$ decaying exponentially in $n$ for every $p \in S$. We prove that for $\alpha>0$ non-integer, $f$ is in the space $C^\alpha [0,1]$ if and only if a simulation scheme as above exists with $\P_p(N>n) \le C (\Delta_n(p))^\alpha$, where \Delta_n(x)\eqbd \max \{\sqrt{x(1-x)/n},1/n \}. The key to the proof is a new result in approximation theory: Let \B_n be the cone of univariate polynomials with nonnegative Bernstein coefficients of degree $n$. We show that a function $f:[0,1] \to (0,1)$ is in $C^\alpha [0,1]$ if and only if $f$ has a series representation $\sum_{n=1}^\infty F_n$ with F_n \in \B_n and $\sum_{k>n} F_k(x) \le C(\Delta_n(x))^\alpha$ for all $x \in [0,1]$ and $n \ge 1$. We also provide a counterexample to a theorem stated without proof by Lorentz (1963), who claimed that if some \phi_n \in \B_n satisfy $|f(x)-\phi_n(x)| \le C (\Delta_n(x))^\alpha$ for all $x \in [0,1]$ and $n \ge 1$, then $f \in C^\alpha [0,1]$.Comment: 29 pages; final version; to appear in Constructive Approximatio