Automatic Derivation of Statistical Data Analysis Algorithms: Planetary Nebulae and Beyond

AUTOBAYES is a fully automatic program synthesis system for the data analysis domain. Its input is a declarative problem description in form of a statistical model; its output is documented and optimized C/C++ code. The synthesis process relies on the combination of three key techniques. Bayesian networks are used as a compact internal representation mechanism which enables problem decompositions and guides the algorithm derivation. Program schemas are used as independently composable building blocks for the algorithm construction; they can encapsulate advanced algorithms and data structures. A symbolic-algebraic system is used to find closed-form solutions for problems and emerging subproblems. In this paper, we describe the application of AUTOBAYES to the analysis of planetary nebulae images taken by the Hubble Space Telescope. We explain the system architecture, and present in detail the automatic derivation of the scientists’ original analysis [1] as well as a refined analysis using clustering models. This study demonstrates that AUTOBAYES is now mature enough so that it can be applied to realistic scientific data analysis tasks

Tax Exemption and the Health Care Industry: Are the Challenges to Tax-Exempt Status Justified?

The provision of health care has traditionally been deemed a charitable function.\u27 Therefore, hospitals and other health care institutions have been afforded the benefits of tax exemption. As a standard for determining which entities merit the tax exemption and which do not, the Internal Revenue Service ( IRS or Service ) developed what has come to be known as the community benefit test. At the federal level, this test has been the basis for awarding tax- exempt status to hospitals and other health care entities State legislatures have traditionally followed the federal government\u27s standards for tax exemption and have thus allowed health care organizations to be exempt from state taxes as well. In recent years, the United States health care system has changed dramatically. These changes have altered the ways in which health care services are provided. In seeking to find new and innovative organizational models for health care delivery, the health care industry has been confronted with a major question-namely, whether these new models of health care delivery should be tax-exempt. Critics of the tax exemption afforded health care organizations argue that health care has become more of a business and that non- profit health care entities are no different than their for-profit counterparts. The debate over non-profit health care organizations has reached a critical point, as evidenced by the challenges to the tax- exempt status of hospitals in many states. It is further evidenced by the IRS\u27s recent challenge to the tax-exempt status of a health maintenance organization ( HMO ) in Geisinger Health Plan v. Commissioner. This Note will demonstrate that these challenges to tax exemption have essentially involved the issue of what the community benefit standard should require and what we should expect from our non-profit health care institutions. This Note will argue that the community benefit test is premised on two important aspects of non- profit health care entities, which the courts and the IRS have already implicitly recognized. First, non-profit health care entities must organize and govern themselves in a way that allows them to be responsive to the needs of their communities. Second, these organizations must produce socially desirable outcomes by providing benefits to their communities that the government might otherwise have to provide. Part II of this Note will analyze the legal framework for tax exemption that courts have applied to hospitals, discussing the major inroads on the tax-exempt status of hospitals, particularly at the state level. Part III will discuss the evolution of the health care industry into new organizational models and will analyze the tax-exempt treatment that these entities have received. Finally, Part IV will suggest that a refined version of the community benefit test provides the best means for preserving the beneficial characteristics of non- profit health care entities while not interfering with the taxing purposes of the IRS. This refined community benefit test should be premised explicitly on both the organizational advantages and the beneficial outcomes provided by non-profit health care entities

Scattering into one-dimensional waveguides from a coherently-driven quantum-optical system

We develop a new computational tool and framework for characterizing the scattering of photons by energy-nonconserving Hamiltonians into unidirectional (chiral) waveguides, for example, with coherent pulsed excitation. The temporal waveguide modes are a natural basis for characterizing scattering in quantum optics, and afford a powerful technique based on a coarse discretization of time. This overcomes limitations imposed by singularities in the waveguide-system coupling. Moreover, the integrated discretized equations can be faithfully converted to a continuous-time result by taking the appropriate limit. This approach provides a complete solution to the scattered photon field in the waveguide, and can also be used to track system-waveguide entanglement during evolution. We further develop a direct connection between quantum measurement theory and evolution of the scattered field, demonstrating the correspondence between quantum trajectories and the scattered photon state. Our method is most applicable when the number of photons scattered is known to be small, i.e. for a single-photon or photon-pair source. We illustrate two examples: analytical solutions for short laser pulses scattering off a two-level system and numerically exact solutions for short laser pulses scattering off a spontaneous parametric downconversion (SPDC) or spontaneous four-wave mixing (SFWM) source. Finally, we note that our technique can easily be extended to systems with multiple ground states and generalized scattering problems with both finite photon number input and coherent state drive, potentially enhancing the understanding of, e.g., light-matter entanglement and photon phase gates.Comment: Numerical package in collaboration with Ben Bartlett (Stanford University), implemented in QuTiP: The Quantum Toolbox in Python, Quantum 201