The Master Field of QCD2_2 and the 'T Hooft Equation

We rewrite the action for $QCD_2$ in the light cone gauge only in terms of a bilocal mesonic field. In this formalism the $1/N$ expansion can be done in a straightforward way by a saddle point technique that determines the master field to be identified with the vacuum expectation value of the bilocal field. Finally we show that the equation of motion for the fluctuations around the master field is identical with the 't Hooft meson equation.Comment: 7 pages, Latex, NORDITA-93-4

A Bilocal Field Approach to the Large-N Expansion of Two-Dimensional (Gauge) Theories

We consider a wide class of two-dimensional models as gauge theories, Gross-Neveu model, $O(N)$ and $CP^{N-1}$-like models using a formalism based on the introduction of bilocal fields that permits to perform easily the large-N expansion of this set of models in a unified and general way. We mainly discuss the $SU(N)$ gauge field theory minimally coupled to fermionic plus bosonic matter in the fundamental representation, and we obtain within the path integral approach exact equations for the particle spectrum, also in presence of renormalizable polynomial potentials. Finally, we discuss the correspondence between this new approach and the one previously used in the context of the $O(N)$ vector models.Comment: 36 pages + 7 uuencoded postcript figures, Latex, Preprint DFUB-93-1

Two dimensional QCD and abelian bosonization

A bosonized action, that reproduces the structure of the 't Hooft equation for $QCD_2$ in the large-$N$ limit, up to regularization dependent terms, is derived.Comment: paper revised, several signs and coefficients corrected. A comment on regularization dependence and several references adde

Progress toward the development of dual junction GaAs/Ge solar cells

Large area GaAs/Ge cells offer substantial promise for increasing the power output from existing silicon solar array designs and for providing an enabled technology for missions hitherto impossible using silicon. Single junction GaAs/Ge cells offer substantial advantages in both size, weight, and cost compared to GaAs cells but the efficiency is limited to approximately 19.2 to 20 percent AMO. The thermal absorptance of GaAs/Ge cells is also worse than GaAs/GaAs cells (0.88 vs 0.81 typ.) due to the absorption in the Ge substrate. On the other hand dual junction GaAs/Ge cells offer efficiencies up to ultimately 24 percent AMO in sizes up to 8 x 8 cm but there are still technological issues remaining to achieve current matching in the GaAs and Ge cells. This can be achieved through tuned antireflection (AR) coatings, improved quality of the GaAs growth, improved quality Ge wafers and the use of a Back Surface Field (BSF)/Back Surface Reflector (BSR) in the Ge cell. Although the temperature coefficients of efficiency and voltage are higher for dual junction GaAs/Ge cells, it has been shown elsewhere that for typical 28 C cell efficiencies of 22 percent (dual junction) vs 18.5 percent (single junction) there is a positive power tradeoff up to temperatures as high as 120 C. Due to the potential ease of fabrication of GaAs/Ge dual junction cells there is likely to be only a small cost differential compared to single junction cells

Design and performance of a fixed, nonaccelerating, guide vane cascade that operates over an inlet flow angle range of 60 deg

A unique set of wind tunnel guide vanes are designed with an inverse design code and analyzed with a panel method and an integral boundary layer code developed at the NASA Lewis Research Center. The fixed guide vanes, 80 feet long with 6-foot chord length, were designed for the NASA Ames 40 x 80/80 x 120 ft Wind Tunnel. Low subsonic flow is accepted over a 60 deg range of inlet angle from either the 40 x 80 leg or the 80 x 120 leg of the wind tunnel, and directed axially into the main leg of the tunnel where drive fans are located. Experimental tests of 1/10-scale models were conducted to verify design calculations

Visual-cortical enhancement by acoustic distractors: The effects of endogenous spatial attention and visual working memory load

Past work has shown that when a peripheral sound captures our attention, it activates the contralateral visual cortex as revealed by an event-related potential component labelled the auditory-evoked contralateral occipital positivity (ACOP). This cross-modal activation of the visual cortex has been observed even when the sounds were not relevant to the ongoing task (visual or auditory), suggesting that peripheral sounds automatically activate the visual cortex. However, it is unclear whether top-down factors such as visual working memory (VWM) load and endogenous attention, which modulate the impact of task-irrelevant information, may modulate this spatially-specific component. Here, we asked participants to perform a lateralized VWM task (change detection), whose performance is supported by both endogenous spatial attention and VWM storage. A peripheral sound that was unrelated to the ongoing task was delivered during the retention interval. The amplitude of sound-elicited ACOP was analyzed as a function of the spatial correspondence with the cued hemifield, and of the memory array set-size. The typical ACOP modulation was observed over parieto-occipital sites in the 280–500 ms time window after sound onset. Its amplitude was not affected by VWM load but was modulated when the location of the sound did not correspond to the hemifield (right or left) that was cued for the change detection task. Our results suggest that sound-elicited activation of visual cortices, as reflected in the ACOP modulation, is unaffected by visual working memory load. However, endogenous spatial attention affects the ACOP, challenging the hypothesis that it reflects an automatic process

Large N limit of SO(N) gauge theory of fermions and bosons

In this paper we study the large N_c limit of SO(N_c) gauge theory coupled to a Majorana field and a real scalar field in 1+1 dimensions extending ideas of Rajeev. We show that the phase space of the resulting classical theory of bilinears, which are the mesonic operators of this theory, is OSp_1(H|H )/U(H_+|H_+), where H|H refers to the underlying complex graded space of combined one-particle states of fermions and bosons and H_+|H_+ corresponds to the positive frequency subspace. In the begining to simplify our presentation we discuss in detail the case with Majorana fermions only (the purely bosonic case is treated in our earlier work). In the Majorana fermion case the phase space is given by O_1(H)/U(H_+), where H refers to the complex one-particle states and H_+ to its positive frequency subspace. The meson spectrum in the linear approximation again obeys a variant of the 't Hooft equation. The linear approximation to the boson/fermion coupled case brings an additonal bound state equation for mesons, which consists of one fermion and one boson, again of the same form as the well-known 't Hooft equation.Comment: 27 pages, no figure

The Proteus Navier-Stokes code

An effort is currently underway at NASA Lewis to develop two- and three-dimensional Navier-Stokes codes, called Proteus, for aerospace propulsion applications. The emphasis in the development of Proteus is not algorithm development or research on numerical methods, but rather the development of the code itself. The objective is to develop codes that are user-oriented, easily-modified, and well-documented. Well-proven, state-of-the-art solution algorithms are being used. Code readability, documentation (both internal and external), and validation are being emphasized. This paper is a status report on the Proteus development effort. The analysis and solution procedure are described briefly, and the various features in the code are summarized. The results from some of the validation cases that have been run are presented for both the two- and three-dimensional codes

Do Humans and Deep Convolutional Neural Networks Use Visual Information Similarly for the Categorization of Natural Scenes?

The investigation of visual categorization has recently been aided by the introduction of deep convolutional neural networks (CNNs), which achieve unprecedented accuracy in picture classification after extensive training. Even if the architecture of CNNs is inspired by the organization of the visual brain, the similarity between CNN and human visual processing remains unclear. Here, we investigated this issue by engaging humans and CNNs in a two-class visual categorization task. To this end, pictures containing animals or vehicles were modified to contain only low/high spatial frequency (HSF) information, or were scrambled in the phase of the spatial frequency spectrum. For all types of degradation, accuracy increased as degradation was reduced for both humans and CNNs; however, the thresholds for accurate categorization varied between humans and CNNs. More remarkable differences were observed for HSF information compared to the other two types of degradation, both in terms of overall accuracy and image-level agreement between humans and CNNs. The difficulty with which the CNNs were shown to categorize high-passed natural scenes was reduced by picture whitening, a procedure which is inspired by how visual systems process natural images. The results are discussed concerning the adaptation to regularities in the visual environment (scene statistics); if the visual characteristics of the environment are not learned by CNNs, their visual categorization may depend only on a subset of the visual information on which humans rely, for example, on low spatial frequency information