Investigating the cosmic-ray ionization rate in the galactic interstellar medium through observations of H3+

Observations of H3+ in the Galactic diffuse interstellar medium (ISM) have led to various surprising results, including the conclusion that the cosmic-ray ionization rate (zeta_2) is about 1 order of magnitude larger than previously thought. The present survey expands the sample of diffuse cloud sight lines with H3+ observations to 50, with detections in 21 of those. Ionization rates inferred from these detections are in the range (1.7+-1.0)x10^-16 s^-1 < zeta_2 < (10.6+-6.8)x10^-16 s^-1 with a mean value of zeta_2=(3.3+-0.4)x10^-16 s^-1. Upper limits (3sigma) derived from non-detections of H3+ are as low as zeta_2 < 0.4x10^-16 s^-1. These low upper-limits, in combination with the wide range of inferred cosmic-ray ionization rates, indicate variations in zeta_2 between different diffuse cloud sight lines. Calculations of the cosmic-ray ionization rate from theoretical cosmic-ray spectra require a large flux of low-energy (MeV) particles to reproduce values inferred from observations. Given the relatively short range of low-energy cosmic rays --- those most efficient at ionization --- the proximity of a cloud to a site of particle acceleration may set its ionization rate. Variations in zeta_2 are thus likely due to variations in the cosmic-ray spectrum at low energies resulting from the effects of particle propagation. To test this theory, H3+ was observed in sight lines passing through diffuse molecular clouds known to be interacting with the supernova remnant IC 443, a probable site of particle acceleration. Where H3+ is detected, ionization rates of zeta_2=(20+-10)x10^-16 s^-1 are inferred, higher than for any other diffuse cloud. These results support both the concept that supernova remnants act as particle accelerators, and the hypothesis that propagation effects are responsible for causing spatial variations in the cosmic-ray spectrum and ionization rate. Future observations of H3+ near other supernova remnants and in sight lines where complementary ionization tracers (OH+, H2O+, H3O+) have been observed will further our understanding of the subject.

Exact Solution of Bayes and Minimax Change-Detection Problems

The challenge of detecting a change in the distribution of data is a sequential decision problem that is relevant to many engineering solutions, including quality control and machine and process monitoring. This dissertation develops techniques for exact solution of change-detection problems with discrete time and discrete observations. Change-detection problems are classified as Bayes or minimax based on the availability of information on the change-time distribution. A Bayes optimal solution uses prior information about the distribution of the change time to minimize the expected cost, whereas a minimax optimal solution minimizes the cost under the worst-case change-time distribution. Both types of problems are addressed. The most important result of the dissertation is the development of a polynomial-time algorithm for the solution of important classes of Markov Bayes change-detection problems. Existing techniques for epsilon-exact solution of partially observable Markov decision processes have complexity exponential in the number of observation symbols. A new algorithm, called constellation induction, exploits the concavity and Lipschitz continuity of the value function, and has complexity polynomial in the number of observation symbols. It is shown that change-detection problems with a geometric change-time distribution and identically- and independently-distributed observations before and after the change are solvable in polynomial time. Also, change-detection problems on hidden Markov models with a fixed number of recurrent states are solvable in polynomial time. A detailed implementation and analysis of the constellation-induction algorithm are provided. Exact solution methods are also established for several types of minimax change-detection problems. Finite-horizon problems with arbitrary observation distributions are modeled as extensive-form games and solved using linear programs. Infinite-horizon problems with linear penalty for detection delay and identically- and independently-distributed observations can be solved in polynomial time via epsilon-optimal parameterization of a cumulative-sum procedure. Finally, the properties of policies for change-detection problems are described and analyzed. Simple classes of formal languages are shown to be sufficient for epsilon-exact solution of change-detection problems, and methods for finding minimally sized policy representations are described.

What Does Value Matter? The Interest-Relational Theory of the Semantics and Metaphysics of Value

Value and reasons for action are often cited by rationalists and moral realists as providing a desire-independent foundation for normativity. Those maintaining instead that normativity is dependent upon motivation often deny that anything called '"value" or "reasons" exists. According to the interest-relational theory, something has value relative to some perspective of desire just in case it satisfies those desires, and a consideration is a reason for some action just in case it indicates that something of value will be accomplished by that action. Value judgements therefore describe real properties of objects and actions, but have no normative significance independent of desires. It is argued that only the interest-relational theory can account for the practical significance of value and reasons for action. Against the Kantian hypothesis of prescriptive rational norms, I attack the alleged instrumental norm or hypothetical imperative, showing that the normative force for taking the means to our ends is explicable in terms of our desire for the end, and not as a command of reason. This analysis also provides a solution to the puzzle concerning the connection between value judgement and motivation. While it is possible to hold value judgements without motivation, the connection is more than accidental. This is because value judgements are usually but not always made from the perspective of desires that actually motivate the speaker. In the normal case judgement entails motivation. But often we conversationally borrow external perspectives of desire, and subsequent judgements do not entail motivation. This analysis drives a critique of a common practice as a misuse of normative language. The "absolutist" attempts to use and, as philosopher, analyze normative language in such a way as to justify the imposition of certain interests over others. But these uses and analyses are incoherent - in denying relativity to particular desires they conflict with the actual meaning of these utterances, which is always indexed to some particular set of desires.