The Beam Dynamics And Beam Related Uncertainties In Fermilab Muon G-2 Experiment

The anomaly of the muon magnetic moment, aμ ≡ (g-2)/2, has played an important role in constraining physics beyond the Standard Model for many years. Currently, the Standard Model prediction for aμ is accurate to 0.42 parts per million (ppm). The most recent muon g-2 experiment was done at Brookhaven National Laboratory (BNL) and determined aμ to 0.54 ppm, with a central value that differs from the Standard Model prediction by 3.3-3.6 standard deviations and provides a strong hint of new physics. The Fermilab Muon g-2 Experiment has a goal to measure aμ to unprecedented precision: 0.14 ppm, which could provide an unambiguous answer to the question whether there are new particles and forces that exist in nature. To achieve this goal, several items have been identified to lower the systematic uncertainties. In this work, we focus on the beam dynamics and beam associated uncertainties, which are important and must be better understood. We will discuss the electrostatic quadrupole system, particularly the hardware-related quad plate alignment and the quad extension and readout system. We will review the beam dynamics in the muon storage ring, present discussions on the beam related systematic errors, simulate the 3D electric fields of the electrostatic quadrupoles and examine the beam resonances. We will use a fast rotation analysis to study the muon radial momentum distribution, which provides the key input for evaluating the electric field correction to the measured aμ

Semi-leptonic Decay of Lambda-b in the Standard Model and with New Physics

Heavy quark decays provide a very advantageous investigation to test the Standard Model (SM). Recently, promising experiments with \textit{b} quark, as well as the analysis of the huge data sets produced at the B factories, have led to an increasing study and sensitive measurements of relative \textit{b} quark decays. In this thesis, I calculate various observables in the semi-leptonic decay process $\Lambda_{b}\to \Lambda_{c}\tau\bar{\nu}_{\tau}$ both in the SM and in the presence of New Physics (NP) operators with different Lorentz structures. The results are relevant for the coming measurement of this semi-leptonic decay at LHC \textit{b} experiment in CERN, and also provide theoretical predictions to refine the physics beyond the SM.Comment: 38 page, 7 figures. arXiv admin note: text overlap with arXiv:1502.0723

CGoDial: A Large-Scale Benchmark for Chinese Goal-oriented Dialog Evaluation

Practical dialog systems need to deal with various knowledge sources, noisy user expressions, and the shortage of annotated data. To better solve the above problems, we propose CGoDial, new challenging and comprehensive Chinese benchmark for multi-domain Goal-oriented Dialog evaluation. It contains 96,763 dialog sessions and 574,949 dialog turns totally, covering three datasets with different knowledge sources: 1) a slot-based dialog (SBD) dataset with table-formed knowledge, 2) a flow-based dialog (FBD) dataset with tree-formed knowledge, and a retrieval-based dialog (RBD) dataset with candidate-formed knowledge. To bridge the gap between academic benchmarks and spoken dialog scenarios, we either collect data from real conversations or add spoken features to existing datasets via crowd-sourcing. The proposed experimental settings include the combinations of training with either the entire training set or a few-shot training set, and testing with either the standard test set or a hard test subset, which can assess model capabilities in terms of general prediction, fast adaptability and reliable robustness.Comment: EMNLP 202

UR4NNV: Neural Network Verification, Under-approximation Reachability Works!

Recently, formal verification of deep neural networks (DNNs) has garnered considerable attention, and over-approximation based methods have become popular due to their effectiveness and efficiency. However, these strategies face challenges in addressing the "unknown dilemma" concerning whether the exact output region or the introduced approximation error violates the property in question. To address this, this paper introduces the UR4NNV verification framework, which utilizes under-approximation reachability analysis for DNN verification for the first time. UR4NNV focuses on DNNs with Rectified Linear Unit (ReLU) activations and employs a binary tree branch-based under-approximation algorithm. In each epoch, UR4NNV under-approximates a sub-polytope of the reachable set and verifies this polytope against the given property. Through a trial-and-error approach, UR4NNV effectively falsifies DNN properties while providing confidence levels when reaching verification epoch bounds and failing falsifying properties. Experimental comparisons with existing verification methods demonstrate the effectiveness and efficiency of UR4NNV, significantly reducing the impact of the "unknown dilemma".Comment: 11 pages, 4 figure

Extracting low energy signals from raw LArTPC waveforms using deep learning techniques -- A proof of concept

We investigate the feasibility of using deep learning techniques, in the form of a one-dimensional convolutional neural network (1D-CNN), for the extraction of signals from the raw waveforms produced by the individual channels of liquid argon time projection chamber (LArTPC) detectors. A minimal generic LArTPC detector model is developed to generate realistic noise and signal waveforms used to train and test the 1D-CNN, and evaluate its performance on low-level signals. We demonstrate that our approach overcomes the inherent shortcomings of traditional cut-based methods by extending sensitivity to signals with ADC values below their imposed thresholds. This approach exhibits great promise in enhancing the capabilities of future generation neutrino experiments like DUNE to carry out their low-energy neutrino physics programs

Effect of vitamin C on intestinal flora disorders in Cr(VI)-contaminated mice

BackgroundHexavalent chromium [Cr(VI)] exposure can cause structural disruption of intestinal flora and functional impairment. Vitamin C (VC) is one of the essential micronutrients, which plays an important role in promoting the growth of intestinal probiotics, improving the intestinal barrier, and maintaining the homeostasis of intestinal flora. However, the regulatory effect of VC on the intestinal flora disorders caused by Cr(VI) exposure remains to be investigated. ObjectiveTo investigate the effect of VC on intestinal flora disruption in mice due to Cr(VI) exposure. MethodsThirty-two SPF-grade C57BL/6 mice were acclimatized and fed for 3 d and randomly divided into control (Con), VC, potassium dichromate [K2Cr2O7, Cr(VI)], and VC+K2Cr2O7 [VC+Cr(VI)] groups. At 8:00 a.m. on day 4, the Con group (double-distilled water given by gavage and injected intraperitoneally), the VC group (VC given by gavage and double-distilled water injected intraperitoneally), the Cr(VI) group (double-distilled water given by gavage and K2Cr2O7 solution injected intraperitoneally), and the VC+Cr(VI) group (VC given by gavage and K2Cr2O7 solution injected intraperitoneally) were treated. The dose of VC was 200 mg·kg−1, and the dose of K2Cr2O7 was 1.25 mg·kg−1. The mice were treated for 45 consecutive days and then executed, the contents of the colon were sampled in sterile freezing tubes, and three replicates were collected from each group. After labeling, the samples were immediately put into liquid nitrogen for rapid freezing. After all the samples were collected, they were transferred to a -80 ℃ ultra-low temperature refrigerator for storage. Samples of colon contents were analyzed for intestinal flora structure by high-throughput sequencing and bioinformatics software. ResultsThe Cr(VI) exposure resulted in reduced body weight gain values in mice compared to the Con group. Pathological changes occurred in the ileal tissue of mice, with significant inflammatory cell infiltration in the Cr(VI) group and reduced inflammatory cell infiltration in the VC+Cr(VI) group. The number of operational taxonomic units (OTUs) of intestinal flora was altered in the Cr(VI) group of mice. In the α diversity analysis, the mean Sobs index in the Cr(VI) group was 240.333±67.796, the Chao index was 258.173±64.813, and the Ace index was 259.481±66.891, which were significantly lower than those in the Con group (P<0.05), the PD whole tree index in the Cr(VI) group was 27.863±2.399, which was significantly higher than that in the Con group (P<0.05), and the VC intervention significantly reversed the changes of the above indexes due to Cr(VI) exposure (P<0.05). In the β diversity analysis, the principal coordinates analysis (PCoA) results showed a significant separation between the Cr(VI) group and the Con group, and after the VC intervention, there was a retraction of the separation trend and the difference was reduced. The multi-sample similarity dendrogram results showed that the control and the VC groups clustered together first, then with the VC+Cr(VI) group, and finally with the Cr(VI) group. The abundances of Bacteroidetes, Saccharibacteria, and Tenericutes in the intestine of mice in the Cr(VI) group were decreased, and the abundance of Firmicutes was increased; the abundances of Lactobacillus, Alistipes, Bacteroides, and Ruminiclostridium were also increased. Included among these, Bacteroides showed a significantly higher abundance compared to the control mice (P<0.05). Changes in the abundances of phyla and genera of the above mentioned gut microorganisms were reversed after the VC intervention. ConclusionCr(VI) exposure can lead to intestinal damage and disorganization of the intestinal flora structure in mice, while VC intervention can ameliorate the above changes to a certain extent and normalize the intestinal flora structure