Quantum resource studied from the perspective of quantum state superposition

Quantum resources,such as discord and entanglement, are crucial in quantum information processing. In this paper, quantum resources are studied from the aspect of quantum state superposition. We define the local superposition (LS) as the superposition between basis of single part, and nonlocal superposition (NLS) as the superposition between product basis of multiple parts. For quantum resource with nonzero LS, quantum operation must be introduced to prepare it, and for quantum resource with nonzero NLS, nonlocal quantum operation must be introduced to prepare it. We prove that LS vanishes if and only if the state is classical and NLS vanishes if and only if the state is separable. From this superposition aspect, quantum resources are categorized as superpositions existing in different parts. These results are helpful to study quantum resources from a unified frame.Comment: 9 pages, 4 figure

Negative exponential behavior of image mutual information for pseudo-thermal light ghost imaging: Observation, modeling, and verification

When use the image mutual information to assess the quality of reconstructed image in pseudo-thermal light ghost imaging, a negative exponential behavior with respect to the measurement number is observed. Based on information theory and a few simple and verifiable assumptions, semi-quantitative model of image mutual information under varying measurement numbers is established. It is the Gaussian characteristics of the bucket detector output probability distribution that leads to this negative exponential behavior. Designed experiments verify the model.Comment: 13 pages, 6 figure

Binary sampling ghost imaging: add random noise to fight quantization caused image quality decline

When the sampling data of ghost imaging is recorded with less bits, i.e., experiencing quantization, decline of image quality is observed. The less bits used, the worse image one gets. Dithering, which adds suitable random noise to the raw data before quantization, is proved to be capable of compensating image quality decline effectively, even for the extreme binary sampling case. A brief explanation and parameter optimization of dithering are given.Comment: 8 pages, 7 figure

STGIC: a graph and image convolution-based method for spatial transcriptomic clustering

Spatial transcriptomic (ST) clustering employs spatial and transcription information to group spots spatially coherent and transcriptionally similar together into the same spatial domain. Graph convolution network (GCN) and graph attention network (GAT), fed with spatial coordinates derived adjacency and transcription profile derived feature matrix are often used to solve the problem. Our proposed method STGIC (spatial transcriptomic clustering with graph and image convolution) utilizes an adaptive graph convolution (AGC) to get high quality pseudo-labels and then resorts to dilated convolution framework (DCF) for virtual image converted from gene expression information and spatial coordinates of spots. The dilation rates and kernel sizes are set appropriately and updating of weight values in the kernels is made to be subject to the spatial distance from the position of corresponding elements to kernel centers so that feature extraction of each spot is better guided by spatial distance to neighbor spots. Self-supervision realized by KL-divergence, spatial continuity loss and cross entropy calculated among spots with high confidence pseudo-labels make up the training objective of DCF. STGIC attains state-of-the-art (SOTA) clustering performance on the benchmark dataset of human dorsolateral prefrontal cortex (DLPFC). Besides, it's capable of depicting fine structures of other tissues from other species as well as guiding the identification of marker genes. Also, STGIC is expandable to Stereo-seq data with high spatial resolution.Comment: Major revision has been made to generate the current version as follows: 1. Writing style has been thoroughly changed. 2. Four more datasets have been added. 3. Contrastive learning has been removed since it doesn't make significant difference to the performance. 4. Two more authors are adde

General Physical Properties of Gamma-Ray-emitting Radio Galaxies

We study the radio galaxies with known redshift detected by the Fermi satellite after 10 years of data (4FGL-DR2). We use a one-zone leptonic model to fit the quasi-simultaneous multiwavelength data of these radio galaxies and study the distributions of the derived physical parameter as a function of black hole mass and accretion disk luminosity. The main results are as follows. (1) We find that the jet kinetic power of most radio galaxies can be explained by the hybrid jet model based on ADAFs surrounding Kerr black holes. (2) After excluding the redshift, there is a significant correlation between the radiation jet power and the accretion disk luminosity, while the jet kinetic power is weakly correlated with the accretion disk luminosity. (3) We also find a significant correlation between inverse Compton luminosity and synchrotron luminosity. The slope of the correlation for radio galaxies is consistent with the synchrotron self-Compton (SSC) process. The result may suggest that the high-energy component of radio galaxies is dominated by the SSC process.Comment: 9 pages,7 figures, accept for publication in ApJ

The jet formation mechanism of Gamma-ray Narrow-line Seyfert 1 Galaxies

Under the coronal magnetic field, we estimate the maximal jet power of the Blandford-\Znajek (BZ) mechanism, Blandford-\Payne (BP) mechanism, and hybrid model. The jet power of the BZ and Hybrid model mechanisms depends on the spin of a black hole, while the jet power of the BP mechanism does not depend on the spin of a black hole. At high black hole spin, the jet power of the hybrid model is greater than that of the BZ and BP mechanisms. We find that the jet power of almost all gamma-\ray narrow line Seyfert 1 galaxies (gamma-\NLS1s) can be explained by the hybrid model. However, one source with jet power 0.1~\1 Eddington luminosity can not be explained by the hybrid model. We suggest that the magnetic field dragged inward by the accretion disk with magnetization-\driven outflows may accelerate the jets in this gamma-\NLS1.Comment: 9 pages,6 figures,accepted for publication in MNRA