arXiv subjects

Zhi Zeng

Publications and source records attributed to Zhi Zeng.

At least 55 records · Page 3Linked to original sources

arXiv2023

Proposal for the complete high-dimensional Greenberger-Horne-Zeilinger state measurement

A theoretical proposal for the complete analysis of high-dimensional Greenberger-Horne-Zeilinger (GHZ) state is presented in this Letter. We first demonstrate the approach for the complete three-photon GHZ state measurement in three dimensions, and then generalize it to the situation of N-photon system in d dimensions. In our approach, the photonic hyperentanglement and quantum Fourier transform are both utilized. The presented proposal will be useful for the high-dimensional multi-photon quantum computation and quantum communication.

quant-ph↗

arXiv2023

Investigations of pressurized Lu-N-H materials by using the hybrid functional

Recently, Lu-N-H materials were reported to have room-temperature superconductivity, and the Hubbard U correction on the Lu's $\textit{f}$-electrons is necessary, and a constant U = 5.5 eV was applied to different Lu-N-H configurations (Nature 615, 244 (2023)). Following simulations indicate that the superconducting transition temperature (T$_{c}$) of LuH$_{3}$ with U = 0 eV is 50 ~ 60 K, while the N-doped LuH$_{3}$ is below 30 K. Quite recently, calculations with U = 5 eV shows that the T$_{c}$ of N-doped LuH$_{3}$ exceeds 100 K. The properties of Lu-N-H are sensitive to the applied U values. Here, the structural and electronic Lu-N-H properties at high-pressure (0 ~ 10 GPa) are systematically investigated based on the hybrid functional. We show that different Lu-N-H configurations should possess different U values varying from 6.4 eV to 7.4 eV. Furthermore, at pressure ranging from 0 GPa to 1 GPa, the $\textit{f}$ and $\textit{d}$ band centers of N-doped LuH$_{3}$ show oscillation or even plateau, and the band gap of insulators also shows a platform near this pressure, this is consistent with the pressure range where room-temperature superconductivity appeared in Lu-N-H. Our work provides insights into the understanding of Lu-N-H materials and other hydrogen-rich superconductors based on the rare-earth elements.

cond-mat.str-el↗

arXiv2023

Possible high-temperature magnetically topological material Mn$_{3}$Bi$_{2}$Te$_{6}$

The Mn-Bi-Te family displaying magnetism and non-trivial topological properties has received extensive attention. Here, we predict that the antiferromagnetic structure of Mn$_{3}$Bi$_{2}$Te$_{6}$ with three MnTe layers is energetically stable and the magnetic coupling strength of Mn-Mn is enhanced four times compared with that in the single MnTe layer of MnBi$_{2}$Te$_{4}$. The predicted Néel transition point is higher than 77 K, the liquid-nitrogen temperature. The topological properties show that with the variation of the MnTe layer from a single layer to three layers, the system transforms from a nontrivial topological phase to a trivial topological phase. Interestingly, the ferromagnetic state of Mn$_{3}$Bi$_{2}$Te$_{6}$ is a topological semimetal and it exhibits a topological transition from trivial to nontrivial induced by the magnetic transition. Our results enrich the Mn-Bi-Te family system, offer a new platform for studying topological phase transitions, and pave a new way to improve the working temperature of magnetically topological devices.

cond-mat.str-el↗

arXiv2023

Route to stabilize cubic gauche polynitrogen to ambient conditions via surface-saturation by hydrogen

Cubic gauche polynitrogen (cg-N) is an attractive high-energy density material. However, high-pressure synthesized cg-N will decompose at low-pressure and cannot exist at ambient conditions. Here, the stabilities of cg-N surfaces with and without saturations at different pressures and temperatures are investigated systematically. Pristine surfaces at 0 GPa are very brittle and will decompose at 300 K, especially (1 1 0) surface will collapse completely just after structural relaxation, whereas the decompositions of surfaces can be suppressed by applying pressure, indicating that surface instability causes the cg-N decomposition at low-pressure. Due to the saturation of dangling bonds and transferring electrons to the surfaces, saturation with H can stabilize surfaces at ambient conditions, while OH saturation cannot because of getting electrons from the surfaces. An acidic environment or surface saturation with less electronegative adsorbates is more favorable for the stability of polymerized nitrogen.

cond-mat.mtrl-sci↗

arXiv2023

Probing the electronic topological transitions of WTe2 under pressure using ultrafast spectroscopy

We investigate the nonequilibrium photocarrier dynamics of WTe2 under pressure using the optical pump-probe spectroscopy. The pressure dependences of the electronic relaxation manifest anomalous changes around 0.8, 3.5, and 6 GPa, indicating the abruptions in the electron-phonon interactions. In addition, the coherent phonon oscillations originating from shear mode suddenly disappears above 3.5 GPa, which marks the onset of Td-1T' structural phase transition. Supported by the theoretical calculation, we unveil the electronic topological transitions (ETTs), especially an emergence of a new type-II Weyl point for Td-WTe2 under pressure. Our work demonstrates a novel route to probe the ETTs under pressure.

cond-mat.str-el↗

arXiv2023

Approaching the Limit of Image Rescaling via Flow Guidance

Image downscaling and upscaling are two basic rescaling operations. Once the image is downscaled, it is difficult to be reconstructed via upscaling due to the loss of information. To make these two processes more compatible and improve the reconstruction performance, some efforts model them as a joint encoding-decoding task, with the constraint that the downscaled (i.e. encoded) low-resolution (LR) image must preserve the original visual appearance. To implement this constraint, most methods guide the downscaling module by supervising it with the bicubically downscaled LR version of the original high-resolution (HR) image. However, this bicubic LR guidance may be suboptimal for the subsequent upscaling (i.e. decoding) and restrict the final reconstruction performance. In this paper, instead of directly applying the LR guidance, we propose an additional invertible flow guidance module (FGM), which can transform the downscaled representation to the visually plausible image during downscaling and transform it back during upscaling. Benefiting from the invertibility of FGM, the downscaled representation could get rid of the LR guidance and would not disturb the downscaling-upscaling process. It allows us to remove the restrictions on the downscaling module and optimize the downscaling and upscaling modules in an end-to-end manner. In this way, these two modules could cooperate to maximize the HR reconstruction performance. Extensive experiments demonstrate that the proposed method can achieve state-of-the-art (SotA) performance on both downscaled and reconstructed images.

eess.IV↗

arXiv2022

A feasibility study of multi-electrode high-purity germanium detector for Ge-76 neutrinoless double beta decay searching

Experiments to search for neutrinoless double-beta (0ν\b{eta}\b{eta}) decay of 76Ge using a high-purity germanium (HPGe) detector rely heavily on background suppression technologies to enhance their sensitivities. In this work, we proposed a pulse-shape analysis method based on a neural network (NN) and a light gradient boosting machine (lightGBM; LGB) to discriminate single-electron (background) and double-electrons (0ν\b{eta}\b{eta} signal) events in a multi-electrode HPGe detector. In this paper, we describe a multi-electrode HPGe detector system, a data-processing system, and pulse-shape simulation procedures. We built a fully connected (FC) neural network and an LGB model to classify the single- and double-electron events. The FC network is trained with simulated single- and double-electron-induced pulses and tested in an independent dataset generated by the pulse-shape simulation. The discrimination efficiency of the FC neural network in the test set for the 0ν\b{eta}\b{eta} double-electron events signal was 77.4%, the precision was 57.7%, and the training time was 430 min. The discrimination efficiency of LGB model was 73.1%, the precision was 64.0%, and the training time was 1.5 min. This study demonstrated that it is feasible to realize single- and double-electron discrimination on multi-electrode HPGe detectors using an FC neural network and LGB model. These results can be used as a reference for future 76Ge 0ν\b{eta}\b{eta} experiments.

physics.ins-det↗

arXiv2022

Neural Copula: A unified framework for estimating generic high-dimensional Copula functions

The Copula is widely used to describe the relationship between the marginal distribution and joint distribution of random variables. The estimation of high-dimensional Copula is difficult, and most existing solutions rely either on simplified assumptions or on complicating recursive decompositions. Therefore, people still hope to obtain a generic Copula estimation method with both universality and simplicity. To reach this goal, a novel neural network-based method (named Neural Copula) is proposed in this paper. In this method, a hierarchical unsupervised neural network is constructed to estimate the marginal distribution function and the Copula function by solving differential equations. In the training program, various constraints are imposed on both the neural network and its derivatives. The Copula estimated by the proposed method is smooth and has an analytic expression. The effectiveness of the proposed method is evaluated on both real-world datasets and complex numerical simulations. Experimental results show that Neural Copula's fitting quality for complex distributions is much better than classical methods. The relevant code for the experiments is available on GitHub. (We encourage the reader to run the program for a better understanding of the proposed method).

cs.LG↗

arXiv2022

In-orbit Radiation Damage Characterization of SiPMs in the GRID-02 CubeSat Detector

Recently, silicon photomultipliers (SiPMs) have been used in several space-borne missions, owing to their solid state, compact size, low operating voltage, and insensitivity to magnetic fields. However, operating SiPMs in space results in radiation damage and degraded performance. In-orbit quantitative studies on these effects are limited. In this study, we present in-orbit SiPM characterization results obtained by the second detector of the Gamma-Ray Integrated Detectors (GRID-02), which was launched on 6 November 2020. An increase in dark current of $\sim$100 $μ$A/year per SiPM chip (model MicroFJ-60035-TSV) at 28.5 V and 5 $^{\circ}$C was observed. Consequently, the overall noise level (sigma) of the GRID-02 detector increased by $\sim$7.5 keV/year. The estimate of this increase is $\sim$40 $μ$A/year per SiPM chip at -20 $^{\circ}$C, highlighting the positive effect of using a cooling system.

physics.ins-det↗

arXiv2022

Complete hyperentangled Greenberger-Horne-Zeilinger state analysis for polarization and time-bin hyperentanglement

We present an efficient scheme for the complete analysis of hyperentangled Greenberger-Horne-Zeilinger (GHZ) state in polarization and time-bin degrees of freedom with two steps. First, the polarization GHZ state is distinguished completely and nondestructively, resorting to the controlled phase flip (CPF) gate constructed by the cavity-assisted interaction. Subsequently, the time-bin GHZ state is analyzed by using the preserved polarization entanglement. With the help of CPF gate and self-assisted mechanism, our scheme can be directly generalized to the complete N-photon hyperentangled GHZ state analysis, and it may have potential applications in the hyperentanglement-based quantum communication.

quant-ph↗

arXiv2022

Complete analysis of the maximally hyperentangled state via the weak cross-Kerr nonlinearity

We present a simple method for the complete analysis of maximally hyperentangled state in polarization and spatial-mode degrees of freedom assisted by the weak cross-Kerr nonlinearity. Our method not only can be used for two-photon hyperentangled Bell state analysis and three-photon hyperentangled Greenberger-Horne-Zeilinger (GHZ) state analysis, but also is suitable for N-photon hyperentangled GHZ state analysis. In our protocols, the bit information of hyperentanglement is read out via the nonlinear interaction, and the phase information is obtained by using linear optical element and single photon detector. This approach is achievable with the current technology, and will be useful for the practical high-capacity quantum communication schemes.

quant-ph↗

arXiv2022

Absorption bias: An ideal descriptor for radiation tolerance of nanocrystalline BCC metals

To evaluate the radiation tolerance of nanocrystalline (NC) materials, the damage effects of Fe and W as typical body-centered cubic (BCC) metals under uniform irradiation are studied by a sequential multi-scale modelling framework. An ideal descriptor, the absorption bias (the ratio of the absorption abilities of grain boundaries (GBs) to interstitials (I) and vacancies (V)), is proposed to characterize the radiation tolerance of materials with different grain sizes. Low absorption bias promotes defects annihilation through enhancing I-V recombination and optimally tuning its competition with GB absorption. Thus, the lower absorption bias, the higher anti-irradiation performance of NC BCC metals is. Furthermore, by comprehensively considering the mechanical property, thermal stability and radiation resistance, nano-crystals are recommended for Fe-based structural materials but coarse crystals for W-based plasma-facing materials. This work reevaluates the radiation resistance of NC materials, resulting in new strategies for designing structural materials of nuclear devices through manipulating grain sizes.

cond-mat.mtrl-sci↗

arXiv2022

From General to Specific: Online Updating for Blind Super-Resolution

Most deep learning-based super-resolution (SR) methods are not image-specific: 1) They are trained on samples synthesized by predefined degradations (e.g. bicubic downsampling), regardless of the domain gap between training and testing data. 2) During testing, they super-resolve all images by the same set of model weights, ignoring the degradation variety. As a result, most previous methods may suffer a performance drop when the degradations of test images are unknown and various (i.e. the case of blind SR). To address these issues, we propose an online SR (ONSR) method. It does not rely on predefined degradations and allows the model weights to be updated according to the degradation of the test image. Specifically, ONSR consists of two branches, namely internal branch (IB) and external branch (EB). IB could learn the specific degradation of the given test LR image, and EB could learn to super resolve images degraded by the learned degradation. In this way, ONSR could customize a specific model for each test image, and thus get more robust to various degradations. Extensive experiments on both synthesized and real-world images show that ONSR can generate more visually favorable SR results and achieve state-of-the-art performance in blind SR.

cs.CV↗

arXiv2022

Effective minimal model and unconventional spin-singlet pairing in Kagome superconductor CsV3Sb5

Recently synthesized Kagome compounds AV$_3$Sb$_5$ attract great attention due to the unusual coexistence of the topology, charge density wave and superconductivity. In this {\it Letter}, based on the band structures for CsV$_3$Sb$_5$ in pristine phase, we fit an effective 6-band model for the low-energy processes; utilizing the random phase approximation (RPA) on the effective minimal model, we obtain the momentum-resolved static spin susceptibility attributing the spin-fluctuation pairing mechanism, we find that the superconducting pairing strengths increase with the lift of the Coulomb correlation, and the superconductive pairing symmetry is singlet, the gap functions are antisymmetric with respect to the x-axis and the y-axis in the intermediate to strong Coulomb correlated regime,indicating the unconventional superconductivity in Kagome compounds AV$_3$Sb$_5$.

cond-mat.supr-con↗

arXiv2022

Physics-informed ConvNet: Learning Physical Field from a Shallow Neural Network

Big-data-based artificial intelligence (AI) supports profound evolution in almost all of science and technology. However, modeling and forecasting multi-physical systems remain a challenge due to unavoidable data scarcity and noise. Improving the generalization ability of neural networks by "teaching" domain knowledge and developing a new generation of models combined with the physical laws have become promising areas of machine learning research. Different from "deep" fully-connected neural networks embedded with physical information (PINN), a novel shallow framework named physics-informed convolutional network (PICN) is recommended from a CNN perspective, in which the physical field is generated by a deconvolution layer and a single convolution layer. The difference fields forming the physical operator are constructed using the pre-trained shallow convolution layer. An efficient linear interpolation network calculates the loss function involving boundary conditions and the physical constraints in irregular geometry domains. The effectiveness of the current development is illustrated through some numerical cases involving the solving (and estimation) of nonlinear physical operator equations and recovering physical information from noisy observations. Its potential advantage in approximating physical fields with multi-frequency components indicates that PICN may become an alternative neural network solver in physics-informed machine learning.

cs.LG↗

arXiv2022

Construction of Strong-Uniform Fuzzy Partitions of Arbitrary Dimensions

Strong-uniform fuzzy partition is necessary for the accuracy of fuzzy partition-based histograms. Most previous research focused on constructing one-dimensional strong-uniform fuzzy partitions. While to the best of our knowledge, few have been reported for high-dimensional cases. In order to fill this theoretical vacancy, this paper proves the existence of high-dimensional strong-uniform fuzzy partitions via proposing an analytic formula to construct strong-uniform fuzzy partitions of arbitrary dimensions.

math.GM↗

arXiv2021

On-ground calibrations of the GRID-02 gamma-ray detector

The Gamma-Ray Integrated Detectors (GRID) are a space project to monitor the transient gamma-ray sky in the multi-messenger astronomy era using multiple detectors on-board CubeSats. The second GRID detector, GRID-02, was launched in 2020. The performance of the detector, including the energy response, effective area, angular response, and temperature-bias dependence, is calibrated in the laboratory and presented here. These measurements are compared with particle tracing simulations and validate the Geant4 model that will be used for generating detector responses.

astro-ph.IM↗

arXiv2021

Optimal Design of Waveform Digitisers for Both Energy Resolution and Pulse Shape Discrimination

Fast digitisers and digital pulse processing have been widely used for spectral application and pulse shape discrimination (PSD) owing to their advantages in terms of compactness, higher trigger rates, offline analysis, etc. Meanwhile, the noise of readout electronics is usually trivial for organic, plastic, or liquid scintillator with PSD ability because of their poor intrinsic energy resolution. However, LaBr3(Ce) has been widely used for its excellent energy resolution and has been proven to have PSD ability for alpha/gamma particles. Therefore, designing a digital acquisition system for such scintillators as LaBr3(Ce) with both optimal energy resolution and promising PSD ability is worthwhile. Several experimental research studies about the choice of digitiser properties for liquid scintillators have already been conducted in terms of the sampling rate and vertical resolution. Quantitative analysis on the influence of waveform digitisers, that is, fast amplifier (optional), sampling rates, and vertical resolution, on both applications is still lacking. The present paper provides quantitative analysis of these factors and, hence, general rules about the optimal design of digitisers for both energy resolution and PSD application according to the noise analysis of time-variant gated charge integration.

physics.ins-det↗