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Objective: Depth estimation is crucial for endoscopic navigation and manipulation, but obtaining ground-truth depth maps in real clinical scenarios, such as the colon, is challenging. This study aims to develop a robust framework that generalizes well to real colonoscopy images, overcoming challenges like non-Lambertian surface reflection and diverse data distributions. Methods: We propose a framework combining a convolutional neural network (CNN) for capturing local features and a Transformer for capturing global information. An uncertainty-based fusion block was designed to enhance generalization by identifying complementary contributions from the CNN and Transformer branches. The network can be trained with simulated datasets and generalize directly to unseen clinical data without any fine-tuning. Results: Our method is validated on multiple datasets and demonstrates an excellent generalization ability across various datasets and anatomical structures. Furthermore, qualitative analysis in real clinical scenarios confirmed the robustness of the proposed method. Conclusion: The integration of local and global features through the CNN-Transformer architecture, along with the uncertainty-based fusion block, improves depth estimation performance and generalization in both simulated and real-world endoscopic environments. Significance: This study offers a novel approach to estimate depth maps for endoscopy images despite the complex conditions in clinic, serving as a foundation for endoscopic automatic navigation and other clinical tasks, such as polyp detection and segmentation.

Baumgratz, Cramer and Plenio established a rigorous framework (BCP framework) for quantifying the coherence of quantum states [\href{http://dx.doi.org/10.1103/PhysRevLett.113.140401}{Phys. Rev. Lett. 113, 140401 (2014)}]. In BCP framework, a quantum state is called incoherent if it is diagonal in the fixed orthonormal basis, and a coherence measure should satisfy some conditions. For a fixed orthonormal basis, if a quantum state $\rho $ has nonzero imaginary part, then $\rho $ must be coherent. How to quantitatively characterize this fact? In this work, we show that any coherence measure $C$ in BCP framework has the property $C(\rho )-C($Re$\rho )\geq 0$ if $C$ is invariant under state complex conjugation, i.e., $C(\rho )=C(\rho ^{\ast })$, here $\rho ^{\ast }$ is the conjugate of $\rho ,$ Re$\rho $ is the real part of $\rho .$ If $C$ does not satisfy $C(\rho )=C(\rho ^{\ast }),$ we can define a new coherence measure $C^{\prime }(\rho )=\frac{1}{2}[C(\rho )+C(\rho ^{\ast })]$ such that $C^{\prime }(\rho )=C^{\prime }(\rho ^{\ast }).$ We also establish some similar results for bosonic Gaussian states., Comment: 9 pages, 3 figures. Comments welcome!

It is a fundamental question that why quantum mechanics uses complex numbers instead of only real numbers. To address this topic, recently, a rigorous resource theory for the imaginarity of quantum states were established, and several imaginarity measures were proposed. In this work, we propose a new imaginarity measure based on the Tsallis relative entropy. This imaginarity measure has explicit expression, and also, it is computable for bosonic Gaussian states., Comment: 9 pages, 1 figure. Any comments are welcome!

It has been a long-standing debate that why quantum mechanics uses complex numbers but not only real numbers. To address this topic, in recent years, the imaginarity theory has been developed in the way of quantum resource theory. However, the existing imaginarity theory mainly focuses on the quantum systems with finite dimensions. Gaussian states are widely used in many fields of quantum physics, but they are in the quantum systems with infinite dimensions. In this paper we establish a resource theory of imaginarity for bosonic Gaussian states. To do so, under the Fock basis, we determine the real Gaussian states and real Gaussian channels in terms of the means and covariance matrices of Gaussian states. Also, we provide two imaginary measures for Gaussian states based on the fidelity., Comment: 11 pages, 4 figures. Comments are welcome

As the Si-based transistors scale down to atomic dimensions, the basic principle of current electronics, which heavily relies on the tunable charge degree of freedom, faces increasing challenges to meet the future requirements of speed, switching energy, heat dissipation, packing density as well as functionalities. Heterogeneous integration, where dissimilar layers of materials and functionalities are unrestrictedly stacked at an atomic scale, is appealing to next-generation electronics, such as multi-functional, neuromorphic, spintronic and ultra-low power devices, because it unlocks technologically useful interfaces of distinct functionalities. Recently, the combination of functional perovskite oxides and the two-dimensional layered materials (2DLMs) led to unexpected functionalities and enhanced device performance. In this review, we review the recent progress of the heterogeneous integration of perovskite oxides and 2DLMs from the perspectives of fabrication and interfacial properties, electronic applications, challenges as well as outlooks. In particular, we focus on three types of attractive applications, namely field-effect transistors, memory, and neuromorphic electronics. The van der Waals integration approach is extendible to other oxides and 2DLMs, leading to almost unlimited combinations of oxides and 2DLMs and contributing to future high-performance electronic and spintronic devices.

Phase is a basic ingredient for quantum states since quantum mechanics uses complex numbers to describe quantum states. In this letter, we introduce a rigorous framework to quantify the phase of quantum states. To do so, we regard phase as a quantum resource, and specify the free states and free operations. We determine the conditions a phase measure should satisfy and provide some phase measures. We also propose the notion of intrinsic phase for quantum states., Comment: 8 pages, 3 figures. Any comments are welcome!

Kirkwood-Dirac (KD) distribution is a representation of quantum states. Recently, KD distribution has been employed in many scenarios such as quantum metrology, quantum chaos and foundations of quantum theory. KD distribution is a quasiprobability distribution, and negative or nonreal elements may signify quantum advantages in certain tasks. A quantum state is called KD classical if its KD distribution is a probability distribution. Since most quantum information processings use pure states as ideal resources, then a key problem is to determine whether a quantum pure state is KD classical. In this paper, we provide some characterizations for the general structure of KD classical pure states. As an application of our results, we prove a conjecture raised by De Bi\`{e}vre [Phys. Rev. Lett. 127, 190404 (2021)] which finds out all KD classical pure states for discrete Fourier transformation., Comment: 11 pages, 5 figures. Comments are welcome!

For two orthonormal bases of a $d$-dimensional complex Hilbert space, the notion of complete incompatibility was introduced recently by De Bi\`{e}vre [Phys. Rev. Lett. 127, 190404 (2021)]. In this work, we introduce the notion of $s$-order incompatibility with positive integer $s$ satisfying $2\leq s\leq d+1.$ In particular, $(d+1)$-order incompatibility just coincides with the complete incompatibility. We establish some relations between $s$-order incompatibility, minimal support uncertainty and rank deficiency of the transition matrix. As an example, we determine the incompatibility order of the discrete Fourier transform with any finite dimension., Comment: 7 pages, 3 figures

Automatic detection of polyps is challenging because different polyps vary greatly, while the changes between polyps and their analogues are small. The state-of-the-art methods are based on convolutional neural networks (CNNs). However, they may fail due to lack of training data, resulting in high rates of missed detection and false positives (FPs). In order to solve these problems, our method combines the two-dimensional (2-D) CNN-based real-time object detector network with spatiotemporal information. Firstly, we use a 2-D detector network to detect static images and frames, and based on the detector network, we propose two feature enhancement modules-the FP Relearning Module (FPRM) to make the detector network learning more about the features of FPs for higher precision, and the Image Style Transfer Module (ISTM) to enhance the features of polyps for sensitivity improvement. In video detection, we integrate spatiotemporal information, which uses Structural Similarity (SSIM) to measure the similarity between video frames. Finally, we propose the Inter-frame Similarity Correlation Unit (ISCU) to combine the results obtained by the detector network and frame similarity to make the final decision. We verify our method on both private databases and publicly available databases. Experimental results show that these modules and units provide a performance improvement compared with the baseline method. Comparison with the state-of-the-art methods shows that the proposed method outperforms the existing ones which can meet real-time constraints. It's demonstrated that our method provides a performance improvement in sensitivity, precision and specificity, and has great potential to be applied in clinical colonoscopy., Comment: This paper has been accepted by Biomedical Signal Processing and Control. Please cite the paper as Xu, J., Zhao, R., Yu, Y., Zhang, Q., Bian, X., Wang, J., Ge, Z., Qian, D., 2021. Real-time automatic polyp detection in colonoscopy using feature enhancement module and spatiotemporal similarity correlation unit. Biomedical Signal Processing and Control 66, 102503

Since a rigorous framework for quantifying quantum coherence was established by Baumgratz et al. [T. Baumgratz, M. Cramer, and M. B. Plenio, Phys. Rev. Lett. 113, 140401 (2014)], many coherence measures have been found. For a given coherence measure $C$, extending the values of $C$ on pure states to mixed states by the convex roof construction, we will get a valid coherence measure $\overline{C}$, we call $\overline{C}$ the corresponding convex roof quantifier of $C$. Whether $C=\overline{C}$ for a given coherence measure is an important question. In this work, we show that for the widely used coherence measure, $l_{1}$ norm of coherence $C_{l_{1}}$, it holds that $C_{l_{1}}\neq \overline{C_{l_{1}}}$.

The conventional coherence is defined with respect to a fixed orthonormal basis, i.e., to a von Neumann measurement. Recently, generalized quantum coherence with respect to general positive operator-valued measurements (POVMs) has been presented. Several well-defined coherence measures, such as the relative entropy of coherence $C_{r}$, the $l_{1}$ norm of coherence $C_{l_{1}}$ and the coherence $C_{T,\alpha }$ based on Tsallis relative entropy with respect to general POVMs have been obtained. In this work, we investigate the properties of $C_{r}$, $l_{1}$ and $C_{T,\alpha }$. We estimate the upper bounds of $C_{l_{1}}$; we show that the minimal error probability of the least square measurement state discrimination is given by $C_{T,1/2}$; we derive the uncertainty relations given by $C_{r}$, and calculate the average values of $C_{r}$, $C_{T,\alpha }$ and $C_{l_{1}}$ over random pure quantum states. All these results include the corresponding results of the conventional coherence as special cases., Comment: 8 pages, 2 figures

The standard quantum coherence theory is defined with respect to an orthonormal basis of a Hilbert space. Recently, Bischof, Kampermann and Bru% \ss\ generalized the notion of coherence into the case of general measurements, and also, they established a rigorous resource theory of coherence with respect to general measurements. In this paper, we propose such a coherence measure with respect to general measurements via quantum Fisher information, and provide an application of this measure., Comment: 8 pages, 0 figure. Comments are welcome

The early diagnosis and screening of glaucoma are important for patients to receive treatment in time and maintain eyesight. Nowadays, deep learning (DL) based models have been successfully used for computer-aided diagnosis (CAD) of glaucoma from retina fundus images. However, a DL model pre-trained using a dataset from one hospital center may have poor performance on a dataset from another new hospital center and therefore its applications in the real scene are limited. In this paper, we propose a self-adaptive transfer learning (SATL) strategy to fill the domain gap between multicenter datasets. Specifically, the encoder of a DL model that is pre-trained on the source domain is used to initialize the encoder of a reconstruction model. Then, the reconstruction model is trained using only unlabeled image data from the target domain, which makes the encoder in the model adapt itself to extract useful high-level features both for target domain images encoding and glaucoma classification, simultaneously. Experimental results demonstrate that the proposed SATL strategy is effective in the domain adaptation task between one private and two public glaucoma diagnosis datasets, i.e. pri-RFG, REFUGE, and LAG. Moreover, the proposed strategy is completely independent of the source domain data, which meets the real scene application and the privacy protection policy., Comment: 10 pages, 2 figures

Quantum coherence with respect to orthonormal bases has been studied extensively in the past few years. Recently, Bischof, et al. [Phys. Rev. Lett. 123, 110402 (2019)] generalized it to the case of general positive operator-valued measure (POVM) measurements. Such POVM-based coherence, including the block coherence as a special case, have significant operational interpretations in quantifying the advantage of quantum states in quantum information processing. In this work we first establish an alternative framework for quantifying the block coherence and provide several block coherence measures. We then present several coherence measures with respect to POVM measurements, and prove a conjecture on the $l_{1}$-norm related POVM coherence measure., Comment: 11 pages, no figures

Coherence is a basic notion for quantum states. Instead of quantum states, in this work, We establish a resource theory for quantifying the coherence of Gaussian channels. To do this, we propose the definitions of incoherent Gaussian channels and incoherent Gaussian superchannels., Comment: 6 pages, no figure, any comments are welcome

We investigate the coherence of quantum channels and establish a resource theory for quantifying the coherence of quantum channels via Choi matrix. To this aim, we define the incoherent channels and incoherent superchannels. This theory recovers the case of quantum states when we view quantum states as a special case of quantum channels and also, this theory allows some analytical expressions for coherence measures., Comment: 9 pages, no figure, any comments are welcome

Coherence is a fundamental ingredient for quantum physics and a key resource for quantum information theory. Baumgratz, Cramer, and Plenio established a rigorous framework (BCP framework) for quantifying coherence [T. Baumgratz, M. Cramer, and M. B. Plenio, Phys. Rev. Lett. \textbf{113}, 140401 (2014)]. In this paper, under the BCP framework we provide two classes of coherence measures based on the sandwiched R\'{e}nyi relative entropy. We also prove that we can not get new coherence measures $f(C(\cdot))$ by a function $f$ acting on a given coherence measure $C$, except the case of qubit states., Comment: 4 pages,no figure. Comments are welcome