Evidence for d-wave superconductivity in the repulsive Hubbard-model

We perform numerical simulations of the Hubbard model using the projector Quantum Monte Carlo method. A novel approach for finite size scaling is discussed. We obtain evidence in favor of d-wave superconductivity in the repulsive Hubbard model. For U=4, $T_c$ is roughly estimated as $T_c\approx 30K$.Comment: 13 pages, 3 figures, 2 tables, submitted to Phys. Rev. Letter

Economic Incentives Versus Command and Control: What's the Best Approach for Solving Environmental Problems?

Now, decades after the first environmental laws were passed in this country, policymakers face many choices when seeking to solve environmental problems. Will taxing polluters for their discharges be more effective than fining them for not meeting certain emissions standards? Will a regulatory agency find it less costly to enforce a ban or oversee a system of tradable permits? Which strategy will reduce a pollutant the quickest? Clearly, there are no "one-size-fits-all" answers. Many factors enter into the decision to favor either policies that lean more toward economic incentives (EI) and toward direct regulation, commonly referred to as command-and-control (CAC) policy. Underlying determinants include a country's governmental and regulatory infrastructure, along with the nature of the environmental problem itself. Even with these contextual factors to consider, we thought it would be useful to compare EI and CAC policies and their outcomes in a real-world setting. To do this, we looked at six environmental problems that the United States and at least one European country dealt with differently (see box on page 14.) For each problem, one approach was more of an EI measure, while the other relied more on CAC. For example, to reduce point-source industrial water pollution, the Netherlands implemented a system of fees for organic pollutants (EI), while the United States established a system of guidelines and permits (CAC). It turned out, in fact, that most policies had at least some elements of both approaches, but we categorized them as EI or CAC based on their dominant features. We then asked researchers who had previously studied these policies on either side of the Atlantic to update or prepare new case studies. We analyzed the 12 case studies (two for each of the six environmental problems) against a list of hypotheses frequently made for or against EI and CAC, such as which instrument is more effective or imposes less administrative burden

Critical Current in the High-T_c Glass model

The high-T_c glass model can be combined with the repulsive tt'--Hubbard model as microscopic description of the striped domains found in the high-T_c materials. In this picture the finite Hubbard clusters are the origin of the d-wave pairing. In this paper we show, that the glass model can also explain the critical currents usually observed in the high-T_c materials. We use two different approaches to calculate the critical current densities of the high-T_c glass model. Both lead to a strongly anisotropic critical current. Finally we give an explanation, why we expect nonetheless a nearly perfect isotropic critical current in the high-T_c superconductors.Comment: 8 pages with 5 eps-figures, LaTeX using RevTeX, accepted by Int.J.Mod.Phys.

Developing processing techniques for Skylab data

The author has identified the following significant results. The effects of misregistration and the scan-line-straightening algorithm on multispectral data were found to be: (1) there is greatly increased misregistration in scan-line-straightening data over conic data; (2) scanner caused misregistration between any pairs of channels may not be corrected for in scan-line-straightened data; and (3) this data will have few pure field center pixels than will conic data. A program SIMSIG was developed implementing the signature simulation model. Data processing stages of the experiment were carried out, and an analysis was made of the effects of spatial misregistration on field center classification accuracy. Fifteen signatures originally used for classifying the data were analyzed, showing the following breakdown: corn (4 signatures), trees (2), brush (1), grasses, weeds, etc. (5), bare soil (1), soybeans (1), and alfalfa (1)

Developing processing techniques for Skylab data

There are no author-identified significant results in this report

Application of ERTS-1 data to analysis of agricultural crops and forests in Michigan

The results reported are based on analysis of ERTS Frame 1033-15580 collected over southwestern Lower Michigan on August 25, 1972. Major agricultural crops such as corn and soybeans were approaching maturity at this data and forest canopies were dense. Extensive ground truth information was gathered by detailed field study of test strips. This detailed information was supplemented over larger areas by interpretation of RB-57 and C-47 photography and MSS imagery. Recognition processing of ERTS-1 MSS data was carried out on a digital computer. Fields and forest stands were selected as training sets and test areas. Aerial imagery was essential for locating the positions of these selected areas on ERTS digital tapes. The recognition process was successful for each type of vegetation which had a dense green canopy such as forests, corn, and soybeans. Bare soil was also recognizable as a category

Developing processing techniques for Skylab data

There are no author-identified significant results in this report

Developing processing techniques for Skylab data

There are no author-identified significant results in this report

Detailed interpretation and analysis of selected corn blight watch data sets

A detailed interpretation and analysis of selected corn blight data set was undertaken in order to better define the present capabilities and limitations of agricultural remote multispectral sensing and automatic processing techniques and to establish the areas of investigation needing futher attention in the development of operational survey systems. While the emphasis of this effort was directed toward the detection of various corn blight levels, problems related to the more general task of crop identification were also investigated. Since the analog recognition computer (SPARC) was fully committed to the more routine aspects of processing and since the detailed interpretation and analysis required more in the way of quantitative information, the CDC 1604 digital computer was employed

Parallelization of the exact diagonalization of the t-t'-Hubbard model

We present a new parallel algorithm for the exact diagonalization of the $t-t'$-Hubbard model with the Lanczos-method. By invoking a new scheme of labeling the states we were able to obtain a speedup of up to four on 16 nodes of an IBM SP2 for the calculation of the ground state energy and an almost linear speedup for the calculation of the correlation functions. Using this algorithm we performed an extensive study of the influence of the next-nearest hopping parameter $t'$ in the $t-t'$-Hubbard model on ground state energy and the superconducting correlation functions for both attractive and repulsive interaction.Comment: 18 Pages, 1 table, 8 figures, Latex uses revtex, submitted to Comp. Phys. Com