AGN Feedback models: Correlations with star formation and observational implications of time evolution

We examine the correlation between the star formation rate (SFR) and black hole accretion rate (BHAR) across a suite of different AGN feedback models, using the time evolution of a merger simulation. By considering three different stages of evolution, and a distinction between the nuclear and outer regions of star formation, we consider 63 different cases. Despite many of the feedback models fitting the M-\sigma\ relationship well, there are often distinct differences in the SFR-BHAR correlations, with close to linear trends only being present after the merger. Some of the models also show evolution in the SFR-BHAR parameter space that is at times directly across the long-term averaged SFR-BHAR correlation. This suggests that the observational SFR-BHAR correlation found for ensembles of galaxies is an approximate statistical trend, as suggested by Hickox et al. Decomposing the SFR into nuclear and outer components also highlights notable differences between models and there is only modest agreement with observational studies examining this in Seyfert galaxies. For the fraction of the black hole mass growth from the merger event relative to the final black hole mass, we find as much as a factor of three variation among models. This also translates into a similar variation in the post-starburst black hole mass growth. Overall, we find that while qualitative features are often similar amongst models, precise quantitative analysis shows there can be quite distinct differences.Comment: Accepted to MNRAS. Comments welcom

On the Spatial Correlations of Lyman Break Galaxies

Motivated by the observed discrepancy between the strong spatial correlations of Lyman break galaxies (LBGs) and their velocity dispersions, we consider a theoretical model in which these starbursting galaxies are associated with dark matter halos that experience appreciable infall of material. We show using numerical simulation that selecting halos that substantially increase in mass within a fixed time interval introduces a ``temporal bias'' which boosts their clustering above that of the underlying population. If time intervals consistent with the observed LBGs star formation rates of 50 solar masses per year are chosen, then spatial correlations are enhanced by up to a factor of two. These values roughly correspond to the geometrical bias of objects three times as massive. Thus, it is clear that temporal biasing must be taken into account when interpreting the properties of Lyman break galaxies.Comment: 5 Pages, 2 Figures, Accepted for Publication in ApJ Letter

Modeling of a Modern Aircraft Through Calibration Techniques

NASA is seeking a new baseline aircraft model to assess the state-of-the-art technology for aircraft noise, emissions, and fuel/energy consumption as an update to a 2005 baseline. The process of modeling engine and airframe models as a system has historically required many iterations at NASA between the airframe and engine models. A new internal process presented in this paper contains a method that simultaneously calibrates an airframe and engine model to known data to create an aircraft system model. The work presented in this paper proposes a new framework in creating new aircraft models for future NASA research. This approach is presented as a general outline applicable to any chosen commercial aircraft. As an applied example, the B737 MAX 8 aircraft is chosen as the integrated engine and airframe model subjected to calibration. Initial results show a close match to available data but further refinement in the process is necessary for this ongoing work

New verification method for embedded systems

Journal ArticleAbstract-Verification of embedded systems is complicated by the fact that they are composed of digital hardware, analog sensors and actuators, and low level software. In order to verify the interaction of these heterogeneous components, it would be beneficial to have a single modeling formalism that is capable of representing all of these components. To address this need, this paper describes an extended labeled hybrid Petri net (LHPN) model that includes constructs for Boolean, discrete, and continuous variables as well as constructs to model timing. This paper also presents a method to verify these extended LHPNs. Finally, this paper presents a case study to illustrate the application of this model to the verification of a fault-tolerant temperature sensor

Timed circuit synthesis using implicit methods

Journal ArticleThe design and synthesis of asynchronous circuits is gaining importance in both the industrial and academic worlds. Timed circuits are a class of asynchronous circuits that incorporate explicit timing information in the specification. This information is used throughout the synthesis procedure to optimize the design. In order to synthesize a timed circuit, it is necessary to exp lore the timed state space of the specification. The memory required to store the timed state space of a complex specification can be prohibitive for large designs when explicit representation methods are used. This paper describes the application of BDDs and MTBDDs to the representation of timed state spaces and the synthesis of timed circuits. These implicit techniques significantly improve the memory efficiency of timed state space exploration and allow more complex designs to be synthesized. Implicit methods also allow the derivation of solution spaces containing all valid solutions to the synthesis problem facilitating subsequent optimization and technology mapping steps

Synthesis of timed circuits using BDDs*

Journal ArticleThis paper presents a tool which synthesizes timed circuits from reduced state graphs. Using timing information to reduce state graphs can lead to significantly smaller and faster circuits. The tool uses implicit techniques (binary decision diagrams) to represent these graphs. This allows us to synthesize larger, more complex systems which may be intractable with an explicit representation. We are also able to create a parameterized family of solutions, facilitating technology mapping

Toward an Improved Analytical Description of Lagrangian Bias

We carry out a detailed numerical investigation of the spatial correlation function of the initial positions of cosmological dark matter halos. In this Lagrangian coordinate system, which is especially useful for analytic studies of cosmological feedback, we are able to construct cross-correlation functions of objects with varying masses and formation redshifts and compare them with a variety of analytical approaches. For the case in which both formation redshifts are equal, we find good agreement between our numerical results and the bivariate model of Scannapieco & Barkana (2002; SB02) at all masses, redshifts, and separations, while the model of Porciani et al. (1998) does well for all parameters except for objects with different masses at small separations. We find that the standard mapping between Lagrangian and Eulerian bias performs well for rare objects at all separations, but fails if the objects are highly-nonlinear (low-sigma) peaks. In the Lagrangian case in which the formation redshifts differ, the SB02 model does well for all separations and combinations of masses, apart from a discrepancy at small separations in situations in which the smaller object is formed earlier and the difference between redshifts or masses is large. As this same limitation arises in the standard approach to the single-point progenitor distribution developed by Lacey & Cole (1993), we conclude that a more complete understanding of the progenitor distribution is the most important outstanding issue in the analytic modeling of Lagrangian bias.Comment: 22 pages, 8 figures, ApJ, in pres