AMI galactic plane survey at 16 GHz - II. Full data release with extended coverage and improved processing

The Arcminute Microkelvin Imager Galactic Plane Survey (AMIGPS) provides mJy-sensitivity, arcminute-resolution interferometric images of the northern Galactic plane at $\approx$ 16 GHz. The first data release covered $76^{\circ} \lessapprox \ell \lessapprox 170^{\circ}$ between latitudes of $|b| \lessapprox 5^{\circ}$; here we present a second data release, extending the coverage to $53^{\circ} \lessapprox \ell \lessapprox 193^{\circ}$ and including high-latitude extensions to cover the Taurus and California giant molecular cloud regions, and the recently discovered large supernova remnant G159.6+7.3. The total coverage is now 1777 deg$^2$ and the catalogue contains 6509 sources. We also describe the improvements to the data processing pipeline which improves the positional and flux density accuracies of the survey.We thank the staff of the Mullard Radio Astronomy Observatory for their invaluable assistance in the commissioning and operation of AMI, which is supported by Cambridge University and the Science and Technologies Facilities Council. YCP acknowledges support from a CCT/Cavendish Laboratory studentship and a Trinity College Junior Research Fellowship. CR and TZJ acknowledge support from Science and Technology Facilities Council studentships.This is the final version of the article. It first appeared from Oxford University Press via http://dx.doi.org/10.1093/mnras/stv172

AMI-CL J0300+2613: A Galactic anomalous-microwave-emission ring masquerading as a galaxy cluster

The Arcminute Microkelvin Imager (AMI) carried out a blind survey for galaxy clusters via their Sunyaev-Zel'dovich effect decrements between 2008 and 2011. The first detection, known as AMI-CL J0300+2613, has been reobserved with AMI equipped with a new digital correlator with high dynamic range. The combination of the new AMI data and more recent high-resolution sub-mm and infra-red maps now shows the feature in fact to be a ring of positive dust-correlated Galactic emission, which is likely to be anomalous microwave emission (AME). If so, this is the first completely blind detection of AME at arcminute scales

AMI-LA observations of the SuperCLASS supercluster

We present a deep survey of the SuperCLASS super-cluster - a region of sky known to contain five Abell clusters at redshift $z\sim0.2$ - performed using the Arcminute Microkelvin Imager (AMI) Large Array (LA) at 15.5$~$GHz. Our survey covers an area of approximately 0.9 square degrees. We achieve a nominal sensitivity of $32.0~\mu$Jy beam$^{-1}$ toward the field centre, finding 80 sources above a $5\sigma$ threshold. We derive the radio colour-colour distribution for sources common to three surveys that cover the field and identify three sources with strongly curved spectra - a high-frequency-peaked source and two GHz-peaked-spectrum sources. The differential source count (i) agrees well with previous deep radio source count, (ii) exhibits no evidence of an emerging population of star-forming galaxies, down to a limit of 0.24$~$mJy, and (iii) disagrees with some models of the 15$~$GHz source population. However, our source count is in agreement with recent work that provides an analytical correction to the source count from the SKADS Simulated Sky, supporting the suggestion that this discrepancy is caused by an abundance of flat-spectrum galaxy cores as-yet not included in source population models

New Tests of Milli-lensing in the Blazar PKS 1413+135

Symmetric achromatic variability (SAV) is a rare form of radio variability in blazars that has been attributed to gravitational milli-lensing by a similar to 10(2)-10(5) M (circle dot) mass condensate. Four SAVs have been identified between 1980 and 2020 in the long-term radio monitoring data of the blazar PKS 1413 + 135. We show that all four can be fitted with the same, unchanging, gravitational lens model. If SAV is due to gravitational milli-lensing, PKS 1413 + 135 provides a unique system for studying active galactic nuclei with unprecedented microarcsecond resolution, as well as for studying the nature of the milli-lens itself. We discuss two possible candidates for the putative milli-lens: a giant molecular cloud hosted in the intervening edge-on spiral galaxy, and an undetected dwarf galaxy with a massive black hole. We find a significant dependence of SAV crossing time on frequency, which could indicate a fast shock moving in a slower underlying flow. We also find tentative evidence for a 989 day periodicity in the SAVs, which, if real, makes possible the prediction of future SAVs: the next three windows for possible SAVs begin in 2022 August, 2025 May, and 2028 February

Clustering and Outlier Identification: Fixed Point Cluster Analysis

: Fixed Point Cluster Analysis (FPCA) is introduced in this paper. FPCA is a new method for non-hierarchical cluster analysis. It is related to outlier identification. Its aim is to find groups of points generated by a common stochastic model without assuming a global model for the whole dataset. FPCA allows for points not belonging to any cluster, for the existence of clusters with a different shape, and for overlapping clusters. FPCA is applicated to the clustering of p\Gammadimensional metrical data, 0-1-vectors, and linear regression data. Keywords: Stochastical clustering, overlapping clusters, mixture model, outlier identification, linear regression 1. The cluster concept of Fixed Point Clusters Sometimes, a dataset does not consist of a partition into some "natural clusters", but nevertheless there seem to be clusters, perhaps of different types. The following dataset is taken from Hand et al. (1994), p. 58, and gives the rates of child mortality (y \Gammaaxis) and adult femal..

Comment on: "On discriminative vs. generative classifiers: a comparison of logistic regression and naive Bayes"

Comparison of generative and discriminative classifiers is an ever-lasting topic. As an important contribution to this topic, based on their theoretical and empirical comparisons between the naïve Bayes classifier and linear logistic regression, Ng and Jordan (NIPS 841–848, 2001) claimed that there exist two distinct regimes of performance between the generative and discriminative classifiers with regard to the training-set size. In this paper, our empirical and simulation studies, as a complement of their work, however, suggest that the existence of the two distinct regimes may not be so reliable. In addition, for real world datasets, so far there is no theoretically correct, general criterion for choosing between the discriminative and the generative approaches to classification of an observation x into a class y; the choice depends on the relative confidence we have in the correctness of the specification of either p(y|x) or p(x, y) for the data. This can be to some extent a demonstration of why Efron (J Am Stat Assoc 70(352):892–898, 1975) and O’Neill (J Am Stat Assoc 75(369):154–160, 1980) prefer normal-based linear discriminant analysis (LDA) when no model mis-specification occurs but other empirical studies may prefer linear logistic regression instead. Furthermore, we suggest that pairing of either LDA assuming a common diagonal covariance matrix (LDA-Λ) or the naïve Bayes classifier and linear logistic regression may not be perfect, and hence it may not be reliable for any claim that was derived from the comparison between LDA-Λ or the naïve Bayes classifier and linear logistic regression to be generalised to all generative and discriminative classifiers. instead. Furthermore, we suggest that pairing of either LDA assuming a common diagonal covariance matrix (LDA-) or the naïve Bayes classifier and linear logistic regression may not be perfect, and hence it may not be reliable for any claim that was derived from the comparison between LDA- or the naïve Bayes classifier and linear logistic regression to be generalised to all generative and discriminative classifiers

The Arcminute Microkelvin Imager catalogue of gamma-ray burst afterglows at 15.7 GHz

We present the Arcminute Microkelvin Imager (AMI) Large Array catalogue of 139 gammaray bursts (GRBs). AMI observes at a central frequency of 15.7 GHz and is equipped with a fully automated rapid-response mode, which enables the telescope to respond to high-energy transients detected by Swift. On receiving a transient alert, AMI can be on-target within 2 min, scheduling later start times if the source is below the horizon. Further AMI observations are manually scheduled for several days following the trigger. The AMI GRB programme probes the early-time (&lt;1 d) radio properties of GRBs, and has obtained some of the earliest radio detections (GRB 130427A at 0.36 and GRB 130907A at 0.51 d post-burst). As all Swift GRBs visible to AMI are observed, this catalogue provides the first representative sample of GRB radio properties, unbiased by multiwavelength selection criteria.We report the detection of six GRB radio afterglows that were not previously detected by other radio telescopes, increasing the rate of radio detections by 50 per cent over an 18-month period. The AMI catalogue implies a Swift GRB radio detection rate of ≳15 per cent, down to∼0.2mJy beam−1. However, scaling this by the fraction of GRBs AMI would have detected in the Chandra &amp; Frail sample (all radio-observed GRBs between 1997 and 2011), it is possible ∼44–56 per cent of Swift GRBs are radio bright, down to ∼0.1–0.15 mJy beam−1. This increase from the Chandra &amp; Frail rate (∼30 per cent) is likely due to the AMI rapid-response mode, which allows observations to begin while the reverse-shock is contributing to the radio afterglow.</p