Efficient learning of tt-doped stabilizer states with single-copy measurements

One of the primary objectives in the field of quantum state learning is to develop algorithms that are time-efficient for learning states generated from quantum circuits. Earlier investigations have demonstrated time-efficient algorithms for states generated from Clifford circuits with at most $\log(n)$ non-Clifford gates. However, these algorithms necessitate multi-copy measurements, posing implementation challenges in the near term due to the requisite quantum memory. On the contrary, using solely single-qubit measurements in the computational basis is insufficient in learning even the output distribution of a Clifford circuit with one additional $T$ gate under reasonable post-quantum cryptographic assumptions. In this work, we introduce an efficient quantum algorithm that employs only nonadaptive single-copy measurement to learn states produced by Clifford circuits with a maximum of $O(\log n)$ non-Clifford gates, filling a gap between the previous positive and negative results.Comment: 6 page

Hyper-Restormer: A General Hyperspectral Image Restoration Transformer for Remote Sensing Imaging

The deep learning model Transformer has achieved remarkable success in the hyperspectral image (HSI) restoration tasks by leveraging Spectral and Spatial Self-Attention (SA) mechanisms. However, applying these designs to remote sensing (RS) HSI restoration tasks, which involve far more spectrums than typical HSI (e.g., ICVL dataset with 31 bands), presents challenges due to the enormous computational complexity of using Spectral and Spatial SA mechanisms. To address this problem, we proposed Hyper-Restormer, a lightweight and effective Transformer-based architecture for RS HSI restoration. First, we introduce a novel Lightweight Spectral-Spatial (LSS) Transformer Block that utilizes both Spectral and Spatial SA to capture long-range dependencies of input features map. Additionally, we employ a novel Lightweight Locally-enhanced Feed-Forward Network (LLFF) to further enhance local context information. Then, LSS Transformer Blocks construct a Single-stage Lightweight Spectral-Spatial Transformer (SLSST) that cleverly utilizes the low-rank property of RS HSI to decompose the feature maps into basis and abundance components, enabling Spectral and Spatial SA with low computational cost. Finally, the proposed Hyper-Restormer cascades several SLSSTs in a stepwise manner to progressively enhance the quality of RS HSI restoration from coarse to fine. Extensive experiments were conducted on various RS HSI restoration tasks, including denoising, inpainting, and super-resolution, demonstrating that the proposed Hyper-Restormer outperforms other state-of-the-art methods

Rapid identification of Mycobacterium tuberculosis infection by a new array format-based surface plasmon resonance method

Tubercle bacillus [TB] is one of the most important chronic infectious diseases that cause millions of deaths annually. While conventional smear microscopy and culture methods are widely used for diagnosis of TB, the former is insensitive, and the latter takes up to 6 to 8 weeks to provide a result, limiting the value of these methods in aiding diagnosis and intermediate decisions on treatment. Therefore, a rapid detection method is essential for the diagnosis, prognosis assessment, and recurrence monitoring. A new surface plasmon resonance [SPR] biosensor based on an array format, which allowed immobilizing nine TB antigens onto the sensor chip, was constructed. Simultaneous determination of multiple TB antibodies in serum had been accomplished with this array-based SPR system. The results were compared with enzyme-linked immunosorbent assay, a conventional immunological method. Array-based SPR showed more advantages in providing label-free and real-time detection. Additionally, the high sensitivity and specificity for the detection of TB infection showed its potential for future development of biosensor arrays for TB diagnosis

Multi-Operator Fairness in Transparent RAN Sharing by Soft-Partition With Blocking and Dropping Mechanism

Radio access network (RAN) sharing has attracted significant attention from telecom operators as a means of accommodating data surges. However, current mechanisms for RAN sharing ignore the fairness issue among operators, and hence the RAN may be under- or over-utilized. Furthermore, the fairness among different operators cannot be guaranteed, since the RAN resources are distributed on a first come, first served basis. Accordingly, the present study proposes a “soft-partition with blocking and dropping” (SBD) mechanism that offers inter-operator fairness using a “soft-partition” approach. In particular, the operator subscribers are permitted to overuse the resources specified in the predefined service-level-agreement when the shared RAN is under-utilized, but are blocked (or even dropped) when the RAN is over-utilized. The simulation results show that SBD achieves an inter-operator fairness of 0.997, which is higher than that of both a hard-partition approach (0.98) and a no-partition approach (0.6) while maintaining a shared RAN utilization rate of 98%. Furthermore, SBD reduces the blocking rate from 35% (hard partition approach) to almost 0%, whereas controlling the dropping rate at 5%. Notably, the dropping rate can be reduced to almost 0% using a newly proposed bandwidth scale down procedure.This work was supported in part by H2020 collaborative Europe/Taiwan research project 5G-CORAL under Grant 761586, and in part by the Ministry of Science and Technology, Taiwan under Contract MOST 106-2218- E-009-018

Determining the physical conditions of extremely young Class 0 circumbinary disk around VLA1623A

We present detailed analysis of high-resolution C18O (2-1), SO (88-77), CO (3-2) and DCO+ (3-2) data obtained by the Atacama Large Millimeter/sub-millimeter Array (ALMA) towards a Class 0 Keplerian circumbinary disk around VLA1623A, which represents one of the most complete analysis towards a Class 0 source. From the dendrogram analysis, we identified several accretion flows feeding the circumbinary disk in a highly anisotropic manner. Stream-like SO emission around the circumbinary disk reveals the complicated shocks caused by the interactions between the disk, accretion flows and outflows. A wall-like structure is discovered south of VLA1623B. The discovery of two outflow cavity walls at the same position traveling at different velocities suggests the two outflows from both VLA1623A and VLA1623B overlays on top of each other in the plane of sky. Our detailed flat and flared disk modeling shows that Cycle 2 C18O J = 2-1 data is inconsistent with the combined binary mass of 0.2 Msun as suggested by early Cycle 0 studies. The combined binary mass for VLA1623A should be modified to 0.3 ~ 0.5 Msun.Comment: 26 pages, 20 figures, accepted by ApJ 2020.2.2

IL-7 receptor signaling is necessary for stage transition in adult B cell development through up-regulation of EBF

Cytokine receptor signals have been suggested to stimulate cell differentiation during hemato/lymphopoiesis. Such action, however, has not been clearly demonstrated. Here, we show that adult B cell development in IL-7−/− and IL-7Rα2/− mice is arrested at the pre–pro-B cell stage due to insufficient expression of the B cell–specific transcription factor EBF and its target genes, which form a transcription factor network in determining B lineage specification. EBF expression is restored in IL-7−/− pre–pro-B cells upon IL-7 stimulation or in IL-7Rα−/− pre–pro-B cells by activation of STAT5, a major signaling molecule downstream of the IL-7R signaling pathway. Furthermore, enforced EBF expression partially rescues B cell development in IL-7Rα−/− mice. Thus, IL-7 receptor signaling is a participant in the formation of the transcription factor network during B lymphopoiesis by up-regulating EBF, allowing stage transition from the pre–pro-B to further maturational stages

Dual regulation by ethanol of the inhibitory effects of ketamine on spinal NMDA-induced pressor responses in rats

<p>Abstract</p> <p>Background</p> <p>Acute exposure of ethanol (alcohol) inhibits NMDA receptor function. Our previous study showed that acute ethanol inhibited the pressor responses induced by NMDA applied intrathecally; however, prolonged ethanol exposure may increase the levels of phosphorylated NMDA receptor subunits leading to changes in ethanol inhibitory potency on NMDA-induced responses. The present study was carried out to examine whether acute ethanol exposure influences the effects of ketamine, a noncompetitive NMDA receptor antagonist, on spinal NMDA-induced pressor responses.</p> <p>Methods</p> <p>The blood pressure responses induced by intrathecal injection of NMDA were recorded in urethane-anesthetized rats weighing 250-275 g. The levels of several phosphorylated residues on NMDA receptor GluN1 subunits were determined by western blot analysis.</p> <p>Results</p> <p>Intravenous injection of ethanol or ketamine inhibited spinal NMDA-induced pressor responses in a dose-dependent and reversible manner. Ketamine inhibition of NMDA-induced responses was synergistically potentiated by ethanol when ethanol was applied just before ketamine. However, ketamine inhibition was significantly reduced when applied at 10 min after ethanol administration. Western blot analysis showed that intravenous ethanol increased the levels of phosphoserine 897 on GluN1 subunits (pGluN1-serine 897), selectively phosphorylated by protein kinase A (PKA), in the lateral horn regions of spinal cord at 10 min after administration. Intrathecal administration of cAMPS-Sp, a PKA activator, at doses elevating the levels of pGluN1-serine 897, significantly blocked ketamine inhibition of spinal NMDA-induced responses.</p> <p>Conclusions</p> <p>The results suggest that ethanol may differentially regulate ketamine inhibition of spinal NMDA receptor function depending on ethanol exposure time and the resulting changes in the levels of pGluN1-serine 897.</p

A Shallow Ritz Method for Elliptic Problems with Singular Sources

In this paper, a shallow Ritz-type neural network for solving elliptic equations with delta function singular sources on an interface is developed. There are three novel features in the present work; namely, (i) the delta function singularity is naturally removed, (ii) level set function is introduced as a feature input, (iii) it is completely shallow, comprising only one hidden layer. We first introduce the energy functional of the problem and then transform the contribution of singular sources to a regular surface integral along the interface. In such a way, the delta function singularity can be naturally removed without introducing a discrete one that is commonly used in traditional regularization methods, such as the well-known immersed boundary method. The original problem is then reformulated as a minimization problem. We propose a shallow Ritz-type neural network with one hidden layer to approximate the global minimizer of the energy functional. As a result, the network is trained by minimizing the loss function that is a discrete version of the energy. In addition, we include the level set function of the interface as a feature input of the network and find that it significantly improves the training efficiency and accuracy. We perform a series of numerical tests to show the accuracy of the present method and its capability for problems in irregular domains and higher dimensions