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

The scientific objectives and future requirements of high energy x-ray astronomy are discussed and concepts for imaging instruments based on CdZnTe detectors and coded masks are reviewed. An instrument concept based on CdZnTe strip detectors, HEXIS, is described in detail. Technical requirements for large area CdZnTe strip detectors are discussed and recent work at UCSD and WU on the capabilities of CdZnTe strip detectors is described in detail. Studies with small, approximately 50 micron beams demonstrate that crossed strip detectors have good properties for both spatial and spectral measurements.

CdZnTe strip detectors for high-energy x-ray astronomy

Diffuse imaging in the gamma-ray energy range is a challenging problem, since faint radiation is usually mixed with strong instrumental background components. This situation results in data sets that are not very informative, so they lead to non robust image reconstruction. In this paper, we used a Bayesian approach to produce sky-maps with high resolution features. This method is then compared with the standard Richardson-Lucy algorithm on the basis of mock data sets that were generated from the SPI/INTEGRAL in-flight model.

/pdf/imaging-techniques-for-gamma-ray-diffuse-emission-3hb5hnpx36.pdf

Imaging techniques for gamma-ray diffuse emission: application to INTEGRAL/SPI

Abstract The detection of the gravitational wave (GW) counterpart GRB 170817A, underluminous compared to the cosmological gamma-ray burst (GRB) population by a factor of 10,000, motivates significant effort in detecting and localizing a dim, nearby, and slightly off-axis population of short GRBs. Swift’s Burst Alert Telescope (BAT) is one of the most sensitive GRB detectors in operation, and the only one that regularly localizes GRBs to arcminute precision, critical to rapid follow-up studies. However, the utility of BAT in targeted subthreshold searches had been historically curtailed by the unavailability of the necessary raw data for analysis. The new availability of time-tagged event data from the GUANO system motivates a renewed focus on developing sensitive targeted search analysis techniques to maximally exploit these data. While computationally cheap, we show that the typical coded-mask deconvolution imaging is limited in its sensitivity due to several factors. We formalize a maximum likelihood framework for the analysis of BAT data wherein signals are forward modeled through the full instrument response, and—coupled with the development of new response models—demonstrate its superior sensitivity to typical imaging via archival comparisons, injection campaigns, and a large number of low-latency GRB discoveries and confirmed arcminute localizations to date. We also demonstrate independent localization of some out-of-field-of-view GRBs for the first time. NITRATES’s increased sensitivity boosts the discovery rate of GRB 170817A–like events in BAT by a factor of at least 3−4×, along with enabling joint analyses and searches with other GRB, GW, neutrino, and FRB instruments. We provide public access to the response functions and search pipeline code. 

https://iopscience.iop.org/article/10.3847/1538-4357/ac9d38/pdf

Harvesting BAT-GUANO with NITRATES (Non-Imaging Transient Reconstruction and Temporal Search): Detecting and Localizing the Faintest Gamma-Ray Bursts with a Likelihood Framework

Recently, a lot of research has been done on compressed sensing, capturing compressible signals using random linear projections to a space of radically lower dimension than the ambient dimension of the signal. The main impetus of this is that the radically dimension-lowering linear projection step can be done totally in analog hardware, in some cases even in constant time, to avoid the bottleneck in sensing and quantization steps where a large number of samples need to be sensed and quantized in short order, mandating the use of a large number of fast expensive sensors and A/D converters. Reconstruction algorithms from these projections have been found that come within distortion levels comparable to the state of the art in lossy compression algorithms. This paper considers a variation on compressed sensing that makes it resistant to spiky noise. This is achieved by an analog real-field error-correction coding step. It results in a small asymptotic overhead in the number of samples, but makes exact reconstruction under spiky measurement noise, one type of which is the salt and pepper noise in imaging devices, possible. Simulations are performed that corroborate our claim and in fact substantially improve reconstruction under unreliable sensing characteristics and are stable even under small perturbations with Gaussian noise.

/pdf/inflating-compressed-samples-a-joint-source-channel-coding-1oo7mx8qgb.pdf

Inflating compressed samples: A joint source-channel coding approach for noise-resistant compressed sensing

Coded mask telescopes have proved of great utility in X- and γ-ray astronomy. A coded mask telescope of a non-cyclic “box-camera” design can in some circumstances have a sensitivity advantage over an optimally coded cyclic configuration, but images reconstructed by a simple correlation technique are subject to various imperfections. A new method, maximum likelihood fitting (MALF), for the analysis of data from non-cyclic coded mask telescopes is presented. MALF avoids artifacts due to strong sources and handles in an optimum way data affected by small-number statistics, by partial coding and by aspects of real systems such as finite detector depth and obscurations of parts of the detector.

Analysis of data from coded-mask telescopes by maximum likelihood

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Analysis of data from coded-mask telescopes by maximum likelihood