The vicious cycle: fundraising and perceived visibility in US presidential primaries

Scholars of presidential primaries have long posited a dynamic positive feedback loop between fundraising and electoral success. Yet existing work on both directions of this feedback remains inconclusive and is often explicitly cross-sectional, ignoring the dynamic aspect of the hypothesis. Pairing high-frequency FEC data on contributions and expenditures with Iowa Electronic Markets data on perceived probability of victory, we examine the bidirectional feedback between contributions and viability. We find robust, significant positive feedback in both directions. This might suggest multiple equilibria: a candidate initially anointed as the front-runner able to sustain such status solely by the fundraising advantage conferred despite possessing no advantage in quality. However, simulations suggest the feedback loop cannot, by itself, sustain advantage. Given the observed durability of front-runners, it would thus seem there is either some other feedback at work and/or the process by which the initial front-runner is identified is informative of candidate quality

On Randomized Algorithms for Matching in the Online Preemptive Model

We investigate the power of randomized algorithms for the maximum cardinality matching (MCM) and the maximum weight matching (MWM) problems in the online preemptive model. In this model, the edges of a graph are revealed one by one and the algorithm is required to always maintain a valid matching. On seeing an edge, the algorithm has to either accept or reject the edge. If accepted, then the adjacent edges are discarded. The complexity of the problem is settled for deterministic algorithms. Almost nothing is known for randomized algorithms. A lower bound of $1.693$ is known for MCM with a trivial upper bound of $2$. An upper bound of $5.356$ is known for MWM. We initiate a systematic study of the same in this paper with an aim to isolate and understand the difficulty. We begin with a primal-dual analysis of the deterministic algorithm due to McGregor. All deterministic lower bounds are on instances which are trees at every step. For this class of (unweighted) graphs we present a randomized algorithm which is $\frac{28}{15}$-competitive. The analysis is a considerable extension of the (simple) primal-dual analysis for the deterministic case. The key new technique is that the distribution of primal charge to dual variables depends on the "neighborhood" and needs to be done after having seen the entire input. The assignment is asymmetric: in that edges may assign different charges to the two end-points. Also the proof depends on a non-trivial structural statement on the performance of the algorithm on the input tree. The other main result of this paper is an extension of the deterministic lower bound of Varadaraja to a natural class of randomized algorithms which decide whether to accept a new edge or not using independent random choices

More on A Statistical Analysis of Log-Periodic Precursors to Financial Crashes

We respond to Sornette and Johansen's criticisms of our findings regarding log-periodic precursors to financial crashes. Included in this paper are discussions of the Sornette-Johansen theoretical paradigm, traditional methods of identifying log-periodic precursors, the behavior of the first differences of a log-periodic price series, and the distribution of drawdowns for a securities price.Comment: 12 LaTex pages, no figure

Discrete Scale Invariance and the "Second Black Monday"

Evidence is offered for log-periodic (in time) fluctuations in the S&P 500 stock index during the three years prior to the October 27, 1997 "correction". These fluctuations were expected on the basis of a discretely scale invariant rupture phenomenology of stock market crashes proposed earlier.Comment: LaTeX file, 4 pages, 2 figure

Develop and test fuel cell powered on-site integrated total energy system

Test results are presented for a 24 cell, two sq ft (4kW) stack. This stack is a precursor to a 25kW stack that is a key milestone. Results are discussed in terms of cell performance, electrolyte management, thermal management, and reactant gas manifolding. The results obtained in preliminary testing of a 50kW methanol processing subsystem are discussed. Subcontracting activities involving application analysis for fuel cell on site integrated energy systems are updated

Programming of inhomogeneous resonant guided wave networks

Photonic functions are programmed by designing the interference of local waves in inhomogeneous resonant guided wave networks composed of power-splitting elements arranged at the nodes of a nonuniform waveguide network. Using a compact, yet comprehensive, scattering matrix representation of the network, the desired photonic function is designed by fitting structural parameters according to an optimization procedure. This design scheme is demonstrated for plasmonic dichroic and trichroic routers in the infrared frequency range

Efficient Coupling between Dielectric-Loaded Plasmonic and Silicon Photonic Waveguides

The realization of practical on-chip plasmonic devices will require efficient coupling of light into and out of surface plasmon waveguides over short length scales. In this letter, we report on low insertion loss for polymer-on-gold dielectric-loaded plasmonic waveguides end-coupled to silicon-on-insulator waveguides with a coupling efficiency of 79 ± 2% per transition at telecommunication wavelengths. Propagation loss is determined independently of insertion loss by measuring the transmission through plasmonic waveguides of varying length, and we find a characteristic surface-plasmon propagation length of 51 ± 4 μm at a free-space wavelength of λ = 1550 nm. We also demonstrate efficient coupling to whispering-gallery modes in plasmonic ring resonators with an average bending-loss-limited quality factor of 180 ± 8

Gravitational Analogues of Non-linear Born Electrodynamics

Gravitational analogues of the nonlinear electrodynamics of Born and of Born and Infeld are introduced and applied to the black hole problem. This work is mainly devoted to the 2-dimensional case in which the relevant lagrangians are nonpolynomial in the scalar curvature.Comment: 20 pages, 2 figures, included a detailed discussion of "non-trace" field equation

Fluctuating dynamics at the quasiperiodic onset of chaos, Tsallis q-statistics and Mori's q-phase thermodynamics

We analyze the fluctuating dynamics at the golden-mean transition to chaos in the critical circle map and find that trajectories within the critical attractor consist of infinite sets of power laws mixed together. We elucidate this structure assisted by known renormalization group (RG) results. Next we proceed to weigh the new findings against Tsallis' entropic and Mori's thermodynamic theoretical schemes and observe behavior to a large extent richer than previously reported. We find that the sensitivity to initial conditions has the form of families of intertwined q-exponentials, of which we determine the q-indexes and the generalized Lyapunov coefficient spectra. Further, the dynamics within the critical attractor is found to consist of not one but a collection of Mori's q-phase transitions with a hierarchical structure. The value of Mori's `thermodynamic field' variable q at each transition corresponds to the same special value for the entropic index q. We discuss the relationship between the two formalisms and indicate the usefulness of the methods involved to determine the universal trajectory scaling function and/or the ocurrence and characterization of dynamical phase transitions.Comment: Resubmitted to Physical Review E. The title has been changed slightly and the abstract has been extended. There is a new subsection following the conclusions that explains the role and usefulness of the q-statistics in the problem studied. Other minor changes througout the tex

Linear Programming in the Semi-streaming Model with Application to the Maximum Matching Problem

In this paper, we study linear programming based approaches to the maximum matching problem in the semi-streaming model. The semi-streaming model has gained attention as a model for processing massive graphs as the importance of such graphs has increased. This is a model where edges are streamed-in in an adversarial order and we are allowed a space proportional to the number of vertices in a graph. In recent years, there has been several new results in this semi-streaming model. However broad techniques such as linear programming have not been adapted to this model. We present several techniques to adapt and optimize linear programming based approaches in the semi-streaming model with an application to the maximum matching problem. As a consequence, we improve (almost) all previous results on this problem, and also prove new results on interesting variants