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In this paper, we want to find out the determining factors of Chernoff information in distinguishing a set of Gaussian graphs. We find that Chernoff information of two Gaussian graphs can be determined by the generalized eigenvalues of their covariance matrices. We find that the unit generalized eigenvalues do not affect Chernoff information and their corresponding dimensions do not provide information for classification purpose. In addition, we can provide a partial ordering using Chernoff information between a series of Gaussian trees connected by independent grafting operations. By exploiting relationship between generalized eigenvalues and Chernoff information, we can do optimal classification linear dimension reduction with least loss of information for classification. 

Abstract. Oxygenated organic molecules (OOMs) are the crucial intermediates linkingvolatile organic compounds (VOCs) to secondary organic aerosols (SOAs) in theatmosphere, but comprehensive understanding of the characteristics of OOMsand their formation from VOCs is still missing. Ambient observations ofOOMs using recently developed mass spectrometry techniques are stilllimited, especially in polluted urban atmospheres where VOCs and oxidants areextremely variable and complex. Here, we investigate OOMs, measured by anitrate-ion-based chemical ionization mass spectrometer at Nanjing ineastern China, through performing positive matrix factorization on binnedmass spectra (binPMF). The binPMF analysis reveals three factors aboutanthropogenic VOC (AVOC) daytime chemistry, three isoprene-relatedfactors, three factors about biogenic VOC (BVOC) nighttime chemistry, andthree factors about nitrated phenols. All factors are influenced by NOxin different ways and to different extents. Over 1000 non-nitro moleculeshave been identified and then reconstructed from the selected solution ofbinPMF, and about 72 % of the total signals are contributed bynitrogen-containing OOMs, mostly regarded as organic nitrates formed throughperoxy radicals terminated by nitric oxide or nitrate-radical-initiatedoxidations. Moreover, multi-nitrates account for about 24 % of the totalsignals, indicating the significant presence of multiple generations,especially for isoprene (e.g., C5H10O8N2 andC5H9O10N3). Additionally, the distribution of OOMconcentration on the carbon number confirms their precursors are driven by AVOCsmixed with enhanced BVOCs during summer. Our results highlight the decisiverole of NOx in OOM formation in densely populated areas, and we encouragemore studies on the dramatic interactions between anthropogenic and biogenicemissions. 

Fast radio bursts (FRBs) are highly dispersed millisecond-duration radio bursts,^[1,2]of which the physical origin is still not fully understood. FRB 20201124A is one of the most actively repeating FRBs. In this paper, we present the collection of 1863 burst dynamic spectra of FRB 20201124A measured with the Five-hundred-meter Aperture Spherical radio Telescope (FAST). The current collection, taken from the observation during the FRB active phase from April to June 2021, is the largest burst sample detected for any FRB so far. The standard PSRFITs format is adopted, including dynamic spectra of the burst, and the time information of the dynamic spectra, in addition, mask files help readers to identify the pulse positions are also provided. The dataset is available in Science Data Bank, with the linkhttps://www.doi.org/10.57760/sciencedb.j00113.00076.