An RMT-based generalized Bayesian information criterion for signal enumeration

Abstract This paper provides a method for enumerating signals impinging on an array of sensors based on the generalized Bayesian information criterion (GBIC). The proposed method motivates by a statistic for testing the sphericity of the covariance matrix when the sample size n is less than the dimension m. The statistic consists of the first four moments of sample eigenvalue distribution and relaxes the assumption of Gaussian distribution. We derive the asymptotical distribution of the statistic as m, n tends to infinity at the same ratio by random matrix theory and propose the expression of GBIC for determining the signal number. Numerical simulations demonstrate that the proposed method has a high probability of detection in both the Gaussian and the non-Gaussian noise, and performs better than other methods

Identification of new M 31 star cluster candidates from PAndAS images using convolutional neural networks

Context. Identification of new star cluster candidates in M 31 is fundamental for the study of the M 31 stellar cluster system. The machine-learning method convolutional neural network (CNN) is an efficient algorithm for searching for new M 31 star cluster candidates from tens of millions of images from wide-field photometric surveys. Aims. We search for new M 31 cluster candidates from the high-quality g- and i-band images of 21 245 632 sources obtained from the Pan-Andromeda Archaeological Survey (PAndAS) through a CNN. Methods. We collected confirmed M 31 clusters and noncluster objects from the literature as our training sample. Accurate double-channel CNNs were constructed and trained using the training samples. We applied the CNN classification models to the PAndAS g- and i-band images of over 21 million sources to search new M 31 cluster candidates. The CNN predictions were finally checked by five experienced human inspectors to obtain high-confidence M 31 star cluster candidates. Results. After the inspection, we identified a catalogue of 117 new M 31 cluster candidates. Most of the new candidates are young clusters that are located in the M 31 disk. Their morphology, colours, and magnitudes are similar to those of the confirmed young disk clusters. We also identified eight globular cluster candidates that are located in the M 31 halo and exhibit features similar to those of confirmed halo globular clusters. The projected distances to the M 31 centre for three of them are larger than 100 kpc

Evolution of the Valley Position in Bulk Transition-Metal Chalcogenides and Their Monolayer Limit

Layered transition metal chalcogenides with large spin orbit coupling have recently sparked much interest due to their potential applications for electronic, optoelectronic, spintronics, and valleytronics. However, most current understanding of the electronic structure near band valleys in momentum space is based on either theoretical investigations or optical measurements, leaving the detailed band structure elusive. For example, the exact position of the conduction band valley of bulk MoS2 remains controversial. Here, using angle-resolved photoemission spectroscopy with submicron spatial resolution (micro-ARPES), we systematically imaged the conduction/valence band structure evolution across representative chalcogenides MoS2, WS2, and WSe2, as well as the thickness dependent electronic structure from bulk to the monolayer limit. These results establish a solid basis to understand the underlying valley physics of these materials, and also provide a link between chalcogenide electronic band structure and their physical properties for potential valleytronics applications

Evolution of the Valley Position in Bulk Transition-Metal Chalcogenides and Their Monolayer Limit.

Layered transition metal chalcogenides with large spin orbit coupling have recently sparked much interest due to their potential applications for electronic, optoelectronic, spintronics, and valleytronics. However, most current understanding of the electronic structure near band valleys in momentum space is based on either theoretical investigations or optical measurements, leaving the detailed band structure elusive. For example, the exact position of the conduction band valley of bulk MoS2 remains controversial. Here, using angle-resolved photoemission spectroscopy with submicron spatial resolution (micro-ARPES), we systematically imaged the conduction/valence band structure evolution across representative chalcogenides MoS2, WS2, and WSe2, as well as the thickness dependent electronic structure from bulk to the monolayer limit. These results establish a solid basis to understand the underlying valley physics of these materials, and also provide a link between chalcogenide electronic band structure and their physical properties for potential valleytronics applications