Optical measurements of phase steps in segmented mirrors - fundamental precision limits

Phase steps are an important type of wavefront aberrations generated by large telescopes with segmented mirrors. In a closed-loop correction cycle these phase steps have to be measured with the highest possible precision using natural reference stars, that is with a small number of photons. In this paper the classical Fisher information of statistics is used for calculating the Cramer-Rao bound, which determines the limit to the precision with which the height of the steps can be estimated in an unbiased fashion with a given number of photons and a given measuring device. Four types of measurement devices are discussed: a Shack-Hartmann sensor with one small cylindrical lenslet covering a sub-aperture centred over a border, a modified Mach-Zehnder interferometer, a Foucault test, and a curvature sensor. The Cramer-Rao bound is calculated for all sensors under ideal conditions, that is narrowband measurements without additional noise or disturbances apart from the photon shot noise. This limit is compared with the ultimate quantum statistical limit for the estimate of such a step which is independent of the measuring device. For the Shack-Hartmann sensor, the effects on the Cramer-Rao bound of broadband measurements, finite sampling, and disturbances such as atmospheric seeing and detector readout noise are also investigated. The methods presented here can be used to compare the precision limits of various devices for measuring phase steps and for optimising the parameters of the devices. Under ideal conditions the Shack-Hartmann and the Foucault devices nearly attain the ultimate quantum statistical limits, whereas the Mach-Zehnder and the curvature devices each require approximately twenty times as many photons in order to reach the same precision.Comment: 23 pages, 19 figures, to be submitted to Journal of Modern Optic

On defining rules for cancer data fabrication

Funding: This research is partially funded by the Data Lab, and the EU H2020 project Serums: Securing Medical Data in Smart Patient-Centric Healthcare Systems (grant 826278).Data is essential for machine learning projects, and data accuracy is crucial for being able to trust the results obtained from the associated machine learning models. Previously, we have developed machine learning models for predicting the treatment outcome for breast cancer patients that have undergone chemotherapy, and developed a monitoring system for their treatment timeline showing interactively the options and associated predictions. Available cancer datasets, such as the one used earlier, are often too small to obtain significant results, and make it difficult to explore ways to improve the predictive capability of the models further. In this paper, we explore an alternative to enhance our datasets through synthetic data generation. From our original dataset, we extract rules to generate fabricated data that capture the different characteristics inherent in the dataset. Additional rules can be used to capture general medical knowledge. We show how to formulate rules for our cancer treatment data, and use the IBM solver to obtain a corresponding synthetic dataset. We discuss challenges for future work.Postprin

Resource Discovery on the Internet

The prime sources for astronomical information resources on the Internet are the AstroWeb and the Star*s databases. For topics not covered by these databases, the Internet hosts a bewildering variety of resource discovery services including AliWeb, Harvest, InfoSeek, Lycos, WebCrawler, and the WWWWorm. These and other discovery tools are reviewed. They can be used to locate e.g. on-line library services, books and CD-ROMs, software, and people's e-mail addresses. "Information isn't truly free if you can't find it." --- Otis Systems 1995 1 Introduction We are witnessing an explosive growth of the Internet [1] and particularly its World Wide Web (WWW) service, which is now (Spring 1995) being offered by more than 12,000 hosts (Fig. 1) -- a hundred-fold increase within less than 2 years from a mere 130 servers back in June 1993 [2]. While initially one could keep track of interesting sites by using personal `hotlists', these times are long gone. Instead numerous directories and search en..

Abstract Resource Discovery on the Internet

The prime sources for astronomical information resources on the Internet are the AstroWeb and the Star*s databases. For topics not covered by these databases, the Internet hosts a bewildering variety of resource discovery services including AliWeb, Harvest, InfoSeek, Lycos, WebCrawler, and the WWW Worm. These and other discovery tools are reviewed. They can be used to locate e.g. on-line library services, books and CD-ROMs, software, and people's e-mail addresses.