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Recovering images from optical interferometric observations is one of the major challenges in the field. Unlike the case of observations at radio wavelengths, in the optical the atmospheric turbulence changes the phases on a very short time scale, which results in corrupted phase measurements. In order to overcome these limitations, several groups developed image reconstruction techniques based only on squared visibility and closure phase information, which are unaffected by atmospheric turbulence. We present the results of two techniques used by our group, which employed coherently integrated data from the Navy Prototype Optical Interferometer. Based on these techniques we were able to recover complex visibilities for several sources and image them using standard radio imaging software. We describe these techniques, the corrections applied to the data, present the images of a few sources, and discuss the implications of these results.
This paper deals with linear algebraic equations where the global coefficient matrix and constant vector are given respectively, by the summation of the coefficient matrices and constant vectors of the individual agents. Our approach is based on refo
An accurate knowledge of the neutron capture cross sections of 62,63Ni is crucial since both isotopes take key positions which affect the whole reaction flow in the weak s process up to A=90. No experimental value for the 63Ni(n,gamma) cross section
Many intellectual endeavors require mathematical problem solving, but this skill remains beyond the capabilities of computers. To measure this ability in machine learning models, we introduce MATH, a new dataset of 12,500 challenging competition math
Sturmfels offered 100 Swiss Francs in 2005 to a conjecture, which deals with a special case of the maximum likelihood estimation for a latent class model. This paper confirms the conjecture positively.
Despite significant advances on distributed continuous-time optimization of multi-agent networks, there is still lack of an efficient algorithm to achieve the goal of distributed optimization at a pre-specified time. Herein, we design a specified-tim