Modeling the X-ray - UV Correlations in NGC 7469

We model the correlated X-ray - UV observations of NGC 7469, for which well sampled data in both these bands have been obtained recently in a multiwavelength monitoring campaign. To this end we derive the transfer function in wavelength \ls and time lag \t, for reprocessing hard (X-ray) photons from a point source to softer ones (UV-optical) by an infinite plane (representing a cool, thin accretion disk) located at a given distance below the X-ray source, under the assumption that the X-ray flux is absorbed and emitted locally by the disk as a black body of temperature appropriate to the incident flux. Using the observed X-ray light curve as input we have computed the expected continuum UV emission as a function of time at several wavelengths (\l \l 1315 \AA, \l \l 6962 \AA, \l \l 15000 \AA, \l \l 30000 \AA) assuming that the X-ray source is located one \sc radius above the disk plane, with the mass of the black hole $M$ and the latitude angle $\theta$ of the observer relative to the disk plane as free parameters. We have searched the parameter space of black hole masses and observer azimuthal angles but we were unable to reproduce UV light curves which would resemble, even remotely, those observed. We also explored whether particular combinations of the values of these parameters could lead to light curves whose statistical properties (i.e. the autocorrelation and cross correlation functions) would match those corresponding to the observed UV light curve at \l \l 1315 \AA. Even though we considered black hole masses as large as $10^9$ M$_{\odot}$ no such match was possible. Our results indicate that some of the fundamental assumptions of this model will have to be modified to obtain even approximate agreement between the observed and model X-ray - UV light curves.Comment: 16 pages, 13 figures, ApJ in pres

A portfolio approach to massively parallel Bayesian optimization

One way to reduce the time of conducting optimization studies is to evaluate designs in parallel rather than just one-at-a-time. For expensive-to-evaluate black-boxes, batch versions of Bayesian optimization have been proposed. They work by building a surrogate model of the black-box that can be used to select the designs to evaluate efficiently via an infill criterion. Still, with higher levels of parallelization becoming available, the strategies that work for a few tens of parallel evaluations become limiting, in particular due to the complexity of selecting more evaluations. It is even more crucial when the black-box is noisy, necessitating more evaluations as well as repeating experiments. Here we propose a scalable strategy that can keep up with massive batching natively, focused on the exploration/exploitation trade-off and a portfolio allocation. We compare the approach with related methods on deterministic and noisy functions, for mono and multiobjective optimization tasks. These experiments show similar or better performance than existing methods, while being orders of magnitude faster

Strategies for the adaptive reuse of large-scale buildings

Thesis (M. Arch.)--Massachusetts Institute of Technology, Dept. of Architecture; and, (S.M.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, 2006.Some pages folded.Includes bibliographical references.The practice of adaptive reuse has grown in popularity in the United States over the past few decades, with now about 90% of architect-commissioned work involving some interaction with an existing structure. While the practice of reuse has existed informally in the form of garage-as-guest house or barn-as-garage conversions and so on, it is only since the late 1960s that architects and engineers have begun to approach it critically, as a design problem. It is often lauded for fostering the development of a sustainable built environment, however, it has its unique challenges. This thesis traces a brief history of the designer's role in the sustainable development discourse, with focused attention paid to the adaptive reuse solution. Furthermore, it attempts to identify the challenges and discuss how they each pertain to the architect, the preservationist, and the engineer. Through the examination of reuse case studies, a coarse classification of project typologies. The second portion of the thesis tackles a specific reuse problem in the Old Post Office in Chicago, Illinois. The Post Office was selected because of its heavily planned context, its historical and cultural significance, the real interest that has been expressed in its reuse, and its size.(cont.) The thesis builds on the earlier classification system to propose an integrated strategy with which to approach the redevelopment of the building. The final part of the thesis briefly describes a few environmental evaluation methods that might be used to judge the sustainability of the reuse project. The proposed solution is analysed to see if the design decisions made with environmental sustainability in mind can be quantified.by Dana Ozik.S.M.M.Arch

Evolution of Discrete Dynamical Systems

We investigate the evolution of three different types of discrete dynamical systems. In each case simple local rules are shown to yield interesting collective global behavior. (a) We introduce a mechanism for the evolution of growing small world networks. We demonstrate that purely local connection rules, when coupled with network growth, can result in short path lengths for the network as a whole. (b) We consider the general character of the spatial distributions of populations that grow through reproduction and subsequent local resettlement of new population members. Several simple one and two-dimensional point placement models are presented to illustrate possible generic behavior of these distributions. We show, both numerically and analytically, that all of the models lead to multifractal spatial distributions of population. (c) We present a discrete lattice model to investigate the segregation of three species granular mixtures in horizontally rotating cylinders. We demonstrate that the simple local rules of the model are able to reproduce many of the experimentally observed global phenomena

Characterization and valuation of uncertainty of calibrated parameters in stochastic decision models

We evaluated the implications of different approaches to characterize uncertainty of calibrated parameters of stochastic decision models (DMs) in the quantified value of such uncertainty in decision making. We used a microsimulation DM of colorectal cancer (CRC) screening to conduct a cost-effectiveness analysis (CEA) of a 10-year colonoscopy screening. We calibrated the natural history model of CRC to epidemiological data with different degrees of uncertainty and obtained the joint posterior distribution of the parameters using a Bayesian approach. We conducted a probabilistic sensitivity analysis (PSA) on all the model parameters with different characterizations of uncertainty of the calibrated parameters and estimated the value of uncertainty of the different characterizations with a value of information analysis. All analyses were conducted using high performance computing resources running the Extreme-scale Model Exploration with Swift (EMEWS) framework. The posterior distribution had high correlation among some parameters. The parameters of the Weibull hazard function for the age of onset of adenomas had the highest posterior correlation of -0.958. Considering full posterior distributions and the maximum-a-posteriori estimate of the calibrated parameters, there is little difference on the spread of the distribution of the CEA outcomes with a similar expected value of perfect information (EVPI) of \$653 and \$685, respectively, at a WTP of \$66,000/QALY. Ignoring correlation on the posterior distribution of the calibrated parameters, produced the widest distribution of CEA outcomes and the highest EVPI of \$809 at the same WTP. Different characterizations of uncertainty of calibrated parameters have implications on the expect value of reducing uncertainty on the CEA. Ignoring inherent correlation among calibrated parameters on a PSA overestimates the value of uncertainty.Comment: 17 pages, 6 figures, 3 table

Trajectory-oriented optimization of stochastic epidemiological models

Epidemiological models must be calibrated to ground truth for downstream tasks such as producing forward projections or running what-if scenarios. The meaning of calibration changes in case of a stochastic model since output from such a model is generally described via an ensemble or a distribution. Each member of the ensemble is usually mapped to a random number seed (explicitly or implicitly). With the goal of finding not only the input parameter settings but also the random seeds that are consistent with the ground truth, we propose a class of Gaussian process (GP) surrogates along with an optimization strategy based on Thompson sampling. This Trajectory Oriented Optimization (TOO) approach produces actual trajectories close to the empirical observations instead of a set of parameter settings where only the mean simulation behavior matches with the ground truth

A deterministic small-world network created by edge iterations

Small-world networks are ubiquitous in real-life systems. Most previous models of small-world networks are stochastic. The randomness makes it more difficult to gain a visual understanding on how do different nodes of networks interact with each other and is not appropriate for communication networks that have fixed interconnections. Here we present a model that generates a small-world network in a simple deterministic way. Our model has a discrete exponential degree distribution. We solve the main characteristics of the model.Comment: 9 pages, 1 figure. to appear in Physica

Farey Graphs as Models for Complex Networks

Farey sequences of irreducible fractions between 0 and 1 can be related to graph constructions known as Farey graphs. These graphs were first introduced by Matula and Kornerup in 1979 and further studied by Colbourn in 1982 and they have many interesting properties: they are minimally 3-colorable, uniquely Hamiltonian, maximally outerplanar and perfect. In this paper we introduce a simple generation method for a Farey graph family, and we study analytically relevant topological properties: order, size, degree distribution and correlation, clustering, transitivity, diameter and average distance. We show that the graphs are a good model for networks associated with some complex systems.Comment: Definitive version published in Theoretical Computer Scienc