Many problems in the experimental estimation of parameters for models can be solved through use of the likelihood ratio test. Applications of the likelihood ratio, with particular attention to photon counting experiments, are discussed. The procedures presented solve a greater range of problems than those currently in use, yet are no more difficult to apply. The procedures are proved analytically, and examples from current problems in astronomy are discussed.

Parameter estimation in astronomy through application of the likelihood ratio. [satellite data analysis techniques

Data Reduction And Error Analysis For The Physical Sciences

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Radiative Processes In Astrophysics

High-contrast adaptive optics imaging is a powerful technique to probe the architectures of planetary systems from the outside-in and survey the atmospheres of self-luminous giant planets. Direct imaging has rapidly matured over the past decade and especially the last few years with the advent of high-order adaptive optics systems, dedicated planet-finding instruments with specialized coronagraphs, and innovative observing and post-processing strategies to suppress speckle noise. This review summarizes recent progress in high-contrast imaging with particular emphasis on observational results, discoveries near and below the deuterium-burning limit, and a practical overview of large-scale surveys and dedicated instruments. I conclude with a statistical meta-analysis of deep imaging surveys in the literature. Based on observations of 384 unique and single young ($\approx$5--300~Myr) stars spanning stellar masses between 0.1--3.0~\Msun, the overall occurrence rate of 5--13~\Mjup \ companions at orbital distances of 30--300~AU is 0.6$^{+0.7}_{-0.5}$\% assuming hot-start evolutionary models. The most massive giant planets regularly accessible to direct imaging are about as rare as hot Jupiters are around Sun-like stars. Dividing this sample into individual stellar mass bins does not reveal any statistically-significant trend in planet frequency with host mass: giant planets are found around 2.8$^{+3.7}_{-2.3}$\% of BA stars, $<$4.1\% of FGK stars, and $<$3.9\% of M dwarfs. Looking forward, extreme adaptive optics systems and the next generation of ground- and space-based telescopes with smaller inner working angles and deeper detection limits will increase the pace of discovery to ultimately map the demographics, composition, evolution, and origin of planets spanning a broad range of masses and ages.

https://iopscience.iop.org/article/10.1088/1538-3873/128/968/102001/pdf

Imaging Extrasolar Giant Planets

With the advent of the Heliophysics/Geospace System Observatory (H/GSO), a complement of multi-spacecraft missions and ground-based observatories to study the space environment, data retrieval, analysis, and visualization of space physics data can be daunting. The Space Physics Environment Data Analysis System (SPEDAS), a grass-roots software development platform (
 www.spedas.org
 ), is now officially supported by NASA Heliophysics as part of its data environment infrastructure. It serves more than a dozen space missions and ground observatories and can integrate the full complement of past and upcoming space physics missions with minimal resources, following clear, simple, and well-proven guidelines. Free, modular and configurable to the needs of individual missions, it works in both command-line (ideal for experienced users) and Graphical User Interface (GUI) mode (reducing the learning curve for first-time users). Both options have “crib-sheets,” user-command sequences in ASCII format that can facilitate record-and-repeat actions, especially for complex operations and plotting. Crib-sheets enhance scientific interactions, as users can move rapidly and accurately from exchanges of technical information on data processing to efficient discussions regarding data interpretation and science. SPEDAS can readily query and ingest all International Solar Terrestrial Physics (ISTP)-compatible products from the Space Physics Data Facility (SPDF), enabling access to a vast collection of historic and current mission data. The planned incorporation of Heliophysics Application Programmer’s Interface (HAPI) standards will facilitate data ingestion from distributed datasets that adhere to these standards. Although SPEDAS is currently Interactive Data Language (IDL)-based (and interfaces to Java-based tools such as Autoplot), efforts are under-way to expand it further to work with python (first as an interface tool and potentially even receiving an under-the-hood replacement). We review the SPEDAS development history, goals, and current implementation. We explain its “modes of use” with examples geared for users and outline its technical implementation and requirements with software developers in mind. We also describe SPEDAS personnel and software management, interfaces with other organizations, resources and support structure available to the community, and future development plans.

/pdf/the-space-physics-environment-data-analysis-system-spedas-dm12usgumn.pdf

The Space Physics Environment Data Analysis System (SPEDAS)

IR heterodyne spectrometer MILAHI for continuous monitoring observatory of Martian and Venusian atmospheres at Mt. Haleakalā, Hawaii

[1] The Io plasma torus is composed mainly of sulfur and oxygen ions and their compounds, together with a background of electrons. In addition to those basic components, several in situ observations have shown that a small percentage of the electrons there have been excited to be as much as 100 times hotter than the background electrons. They have a significant impact on the energy balance in the Jovian inner magnetosphere. However, their generation process has not yet been clarified. One difficulty is that the available data about the hot electrons all come from in situ observations which cannot explore the temporal and spatial distributions explicitly. Therefore, remote sensing which can take a direct picture of the plasma dynamics is necessary in order to clarify the hot electron problem. In this study, a plasma diagnosis method was used for the Io plasma torus EUV spectra taken from the Cassini spacecraft. Agreement with previous observations confirmed the background electron temperature and ion compositions as determined by our model. In addition, the available data are matched even better when the model is run with a hot electron component. This consistent confirmation by remote sensing is a first. Because of the limited temporal resolution and observational coverage, the results could not be used to explain the generation process of the hot electrons. However, we expect that this method will be useful in studying the hot electron generation process when data from future missions with better temporal resolution and more complete coverage become available.

https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/2011JA016583

Hot electron component in the Io plasma torus confirmed through EUV spectral analysis

https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/2018JA026038

Azimuthal Variation in the Io Plasma Torus Observed by the Hisaki Satellite From 2013 to 2016

https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/2018GL079264

Masato Kagitani

Papers

IR heterodyne spectrometer MILAHI for continuous monitoring observatory of Martian and Venusian atmospheres at Mt. Haleakalā, Hawaii

Hot electron component in the Io plasma torus confirmed through EUV spectral analysis

Azimuthal Variation in the Io Plasma Torus Observed by the Hisaki Satellite From 2013 to 2016

The Influence of Io's 2015 Volcanic Activity on Jupiter's Magnetospheric Dynamics

Plan for Observing Magnetospheres of Outer Planets by Using the EUV Spectrograph Onboard the Sprint-A Mission