arXiv subjects

J. Zhu

Publications and source records attributed to J. Zhu.

At least 37 records · Page 2Linked to original sources

arXiv2022

Mixed Diagnostics for Longitudinal Properties of Electron Bunches in a Free-Electron Laser

Longitudinal properties of electron bunches are critical for the performance of a wide range of scientific facilities. In a free-electron laser, for example, the existing diagnostics only provide very limited longitudinal information of the electron bunch during online tuning and optimization. We leverage the power of artificial intelligence to build a neural network model using experimental data, in order to bring the destructive longitudinal phase space (LPS) diagnostics online virtually and improve the existing current profile online diagnostics which uses a coherent transition radiation (CTR) spectrometer. The model can also serve as a digital twin of the real machine on which algorithms can be tested efficiently and effectively. We demonstrate at the FLASH facility that the encoder-decoder model with more than one decoder can make highly accurate predictions of megapixel LPS images and coherent transition radiation spectra concurrently for electron bunches in a bunch train with broad ranges of LPS shapes and peak currents, which are obtained by scanning all the major control knobs for LPS manipulation. Furthermore, we propose a way to significantly improve the CTR spectrometer online measurement by combining the predicted and measured spectra. Our work showcases how to combine virtual and real diagnostics in order to provide heterogeneous and reliable mixed diagnostics for scientific facilities.

physics.acc-ph↗

arXiv2021

Performance study of large-area glass resistive plate chambers with different spacer configurations

Optimization of spacer and gas distribution inside glass resistive plate chamber (RPC) is reported. Simulation studies demonstrate improvements on the gas flow velocity homogeneity and lower vorticity inside the gas chamber. The optimized spacer configuration (76 spacers) decreases the number of spacers by $24\%$ compared to the original design (100 spacers), thus helps significantly reduce the non-active or low-efficiency area caused by spacers while maintaining similar deformation uniformity of the electrodes. Large area glass RPCs with 1x1 m$^2$ size using two types of spacer configurations are constructed and tested with cosmic muons events. The muon detection efficiencies for RPCs are greater than $95\%$.

physics.ins-det↗

arXiv2021

Scenario adaptive disruption prediction study for next generation burning-plasma tokamaks

Next generation high performance (HP) tokamaks risk damage from unmitigated disruptions at high current and power. Achieving reliable disruption prediction for a device's HP operation based on its low performance (LP) data is key to success. In this letter, through explorative data analysis and dedicated numerical experiments on multiple existing tokamaks, we demonstrate how the operational regimes of tokamaks can affect the power of a trained disruption predictor. First, our results suggest data-driven disruption predictors trained on abundant LP discharges work poorly on the HP regime of the same tokamak, which is a consequence of the distinct distributions of the tightly correlated signals related to disruptions in these two regimes. Second, we find that matching operational parameters among tokamaks strongly improves cross-machine accuracy which implies our model learns from the underlying scalings of dimensionless physics parameters like q_{95}, β_{p} and confirms the importance of these parameters in disruption physics and cross machine domain matching from the data-driven perspective. Finally, our results show how in the absence of HP data from the target devices, the best predictivity of the HP regime for the target machine can be achieved by combining LP data from the target with HP data from other machines. These results provide a possible disruption predictor development strategy for next generation tokamaks, such as ITER and SPARC, and highlight the importance of developing on existing machines baseline scenario discharges of future tokamaks to collect more relevant disruptive data.

physics.plasm-ph↗

arXiv2021

The orbital effect on the anomalous magnetism and evolution in La$_x$Y$_{1-x}$VO$_3$($0\le x \le 0.2$) single crystals

The orbital effect on the anomalous magnetism and evolution of low La-doping single crystals, La$_x$Y$_{1-x}$VO$_{3}$ (x = 0, 0.1, and 0.2), has been investigated by applying the X-ray diffraction, specific heat, magnetization and Raman scattering techniques. The larger nearest-neighbor (NN) exchange interaction along c-axis stabilizes the fluctuant G-type orbital ordering (G-OO) which favors the exotic C-type antiferromagnetic order (C-AF). It is found that the NN exchange interaction in ab plane is anisotropy relating to the in plane magnetic anisotropy, which becomes smaller in high La-doped sample. Most interestingly, with increasing the La$^{3+}$ content the orbital fluctuation and hybridization are decreased which stabilizes the C-OO phase and destabilizes the G-OO phase. Meanwhile, the diamagnetism in the exotic C-AF phase becomes weak and the possible mechanism relates to the change of the competition between the single-ion magnetic anisotropy and the Dzyaloshinsky-Moriya (DM) interaction with increasing x. Finally, the strong spin-orbital coupling has been observed at temperature just above T$_N$ in La$_{0.2}$Y$_{0.8}$VO$_{3}$ and a short range spin-orbital correlation is suggested.

cond-mat.str-el↗

arXiv2021

Multi-task single channel speech enhancement using speech presence probability as a secondary task training target

To cope with reverberation and noise in single channel acoustic scenarios, typical supervised deep neural network~(DNN)-based techniques learn a mapping from reverberant and noisy input features to a user-defined target. Commonly used targets are the desired signal magnitude, a time-frequency mask such as the Wiener gain, or the interference power spectral density and signal-to-interference ratio that can be used to compute a time-frequency mask. In this paper, we propose to incorporate multi-task learning in such DNN-based enhancement techniques by using speech presence probability (SPP) estimation as a secondary task assisting the target estimation in the main task. The advantage of multi-task learning lies in sharing domain-specific information between the two tasks (i.e., target and SPP estimation) and learning more generalizable and robust representations. To simultaneously learn both tasks, we propose to use the adaptive weighting method of losses derived from the homoscedastic uncertainty of tasks. Simulation results show that the dereverberation and noise reduction performance of a single-task DNN trained to directly estimate the Wiener gain is higher than the performance of single-task DNNs trained to estimate the desired signal magnitude, the interference power spectral density, or the signal-to-interference ratio. Incorporating the proposed multi-task learning scheme to jointly estimate the Wiener gain and the SPP increases the dereverberation and noise reduction further.

eess.AS↗

arXiv2021

Numerical study of COVID-19 spatial-temporal spreading in London

Recent study reported that an aerosolised virus (COVID-19) can survive in the air for a few hours. It is highly possible that people get infected with the disease by breathing and contact with items contaminated by the aerosolised virus. However, the aerosolised virus transmission and trajectories in various meteorological environments remain unclear. This paper has investigated the movement of aerosolised viruses from a high concentration source across a dense urban area. The case study looks at the highly air polluted areas of London: University College Hospital (UCH) and King Cross and St Pancras International Station (KCSPI). We explored the spread and decay of COVID-19 released from the hospital and railway stations with the prescribed meteorological conditions. The study has three key findings: the primary result is that it is possible for the virus to travel from meters up to hundred meters from the source location. The secondary finding shows viruses released into the atmosphere from entry and exit points at KCSPI remain trapped within a small radial distance of < 50m. This strengthens the case for the use of face coverings to reduce the infection rate. The final finding shows that there are different levels of risk at various door locations for UCH, depending on which door is used there can be a higher concentration of COVID-19. Although our results are based on London, since the fundamental knowledge processes are the same, our study can be further extended to other locations (especially the highly air polluted areas) in the world.

physics.med-ph↗

arXiv2020

An Improved Approximation Algorithm for the Matching Augmentation Problem

We present a $\frac53$-approximation algorithm for the matching augmentation problem (MAP): given a multi-graph with edges of cost either zero or one such that the edges of cost zero form a matching, find a 2-edge connected spanning subgraph (2-ECSS) of minimum cost. A $\frac74$-approximation algorithm for the same problem was presented recently, see Cheriyan, et al., "The matching augmentation problem: a $\frac{7}{4}$-approximation algorithm," {\em Math. Program.}, 182(1):315--354, 2020; arXiv:1810.07816. Our improvement is based on new algorithmic techniques, and some of these may lead to advances on related problems.

cs.DS↗

arXiv2020

Imaging orbital ferromagnetism in a moiré Chern insulator

Electrons in moiré flat band systems can spontaneously break time reversal symmetry, giving rise to a quantized anomalous Hall effect. Here we use a superconducting quantum interference device to image stray magnetic fields in one such system composed of twisted bilayer graphene aligned to hexagonal boron nitride. We find a magnetization of several Bohr magnetons per charge carrier, demonstrating that the magnetism is primarily orbital in nature. Our measurements reveal a large change in the magnetization as the chemical potential is swept across the quantum anomalous Hall gap consistent with the expected contribution of chiral edge states to the magnetization of an orbital Chern insulator. Mapping the spatial evolution of field-driven magnetic reversal, we find a series of reproducible micron scale domains whose boundaries host chiral edge states.

cond-mat.mes-hall↗

arXiv2019

Acceleration of three-dimensional Tokamak magnetohydrodynamical code with graphics processing unit and OpenACC heterogeneous parallel programming

In this paper, the OpenACC heterogeneous parallel programming model is successfully applied to modification and acceleration of the three-dimensional Tokamak magnetohydrodynamical code (CLTx). Through combination of OpenACC and MPI technologies, CLTx is further parallelized by using multiple-GPUs. Significant speedup ratios are achieved on NVIDIA TITAN Xp and TITAN V GPUs, respectively, with very few modifications of CLTx. Furthermore, the validity of the double precision calculations on the above-mentioned two graphics cards has also been strictly verified with m/n=2/1 resistive tearing mode instability in Tokamak.

physics.comp-ph↗

arXiv2019

Intrinsic quantized anomalous Hall effect in a moiré heterostructure

We report the observation of a quantum anomalous Hall effect in twisted bilayer graphene showing Hall resistance quantized to within .1\% of the von Klitzing constant $h/e^2$ at zero magnetic field.The effect is driven by intrinsic strong correlations, which polarize the electron system into a single spin and valley resolved moiré miniband with Chern number $C=1$. In contrast to extrinsic, magnetically doped systems, the measured transport energy gap $Δ/k_B\approx 27$~K is larger than the Curie temperature for magnetic ordering $T_C\approx 9$~K, and Hall quantization persists to temperatures of several Kelvin. Remarkably, we find that electrical currents as small as 1~nA can be used to controllably switch the magnetic order between states of opposite polarization, forming an electrically rewritable magnetic memory.

cond-mat.str-el↗

arXiv2019

Coupled dynamics of long-range and internal spin cluster order in Cu$_{2}$OSeO$_{3}$

Cu$_4$ triplet clusters form the relevant spin entity for the formation of long-range magnetic order in the cluster magnet Cu$_2$OSeO$_3$. Using time-resolved Raman spectroscopy, we probed photoinduced spin and lattice dynamics in this Mott insulator. Multiple ps-decade spin-lattice relaxation dynamics is observed, evidencing a separation of the order parameter dynamics into disordering of long-range and internal spin cluster order. Our study exemplifies the double order parameter dynamics of generalized molecular crystals of charge, spin, and orbital nature.

cond-mat.str-el↗

arXiv2019

Dynamical resonance quench and Fano interference in spontaneous Raman scattering from quasiparticle and collective excitations

Time-resolved spontaneous Raman spectroscopy serves as a probe for incoherent quasiparticle and collective excitation dynamics, and allows to distinguish symmetry changes across a photoinduced phase transition through the inelastic light scattering selection rules. Largely unexplored is the role of the Raman resonance enhancement in the time-domain, and the transient interaction between scattering from quasiparticles and collective excitations, with the latter interaction leading to a Fano interference. In this work, we report on the observation of a phonon Raman tensor quench and Fano interference after strong photoexcitation of an intrinsic semiconductor. We observed a dynamic phonon scattering rate asymmetry and spectral asymmetry through simultaneous detection of both the anti-Stokes and Stokes response. The asymmetric phonon scattering rate is ascribed to the combined effect of the transient phonon population and the reduction of the phonon Raman tensor resulting from the photoexcited hole population. This same hole population results in a strong enhancement of the Fano spectral asymmetry.

cond-mat.mtrl-sci↗

arXiv2019

3-D Motion Correction for Volumetric Super-Resolution Ultrasound (SR-US) Imaging

Motion during image acquisition can cause image degradation in all medical imaging modalities. This is particularly relevant in 2-D ultrasound imaging, since out-of-plane motion can only be compensated for movements smaller than elevational beamwidth of the transducer. Localization based super-resolution imaging creates even a more challenging motion correction task due to the requirement of a high number of acquisitions to form a single super-resolved frame. In this study, an extension of two-stage motion correction method is proposed for 3-D motion correction. Motion estimation was performed on high volumetric rate ultrasound acquisitions with a handheld probe. The capability of the proposed method was demonstrated with a 3-D microvascular flow simulation to compensate for handheld probe motion. Results showed that two-stage motion correction method reduced the average localization error from 136 to 18 micrometres.

physics.med-ph↗

arXiv2019

3-D Super-Resolution Ultrasound (SR-US) Imaging using a 2-D Sparse Array with High Volumetric Imaging Rate

Super-resolution ultrasound imaging has been so far achieved in 3-D by mechanically scanning a volume with a linear probe, by co-aligning multiple linear probes, by using multiplexed 3-D clinical ultrasound systems, or by using 3-D ultrasound research systems. In this study, a 2-D sparse array was designed with 512 elements according to a density-tapered 2-D spiral layout and optimized to reduce the sidelobes of the transmitted beam profile. High frame rate volumetric imaging with compounded plane waves was performed using two synchronized ULA-OP 256 systems. Localization-based 3-D super-resolution images of two touching sub-wavelength tubes were generated from a 120 second acquisition.

physics.med-ph↗

arXiv2019

3-D Super-Resolution Ultrasound (SR-US) Imaging with a 2-D Sparse Array

High frame rate 3-D ultrasound imaging technology combined with super-resolution processing method can visualize 3-D microvascular structures by overcoming the diffraction limited resolution in every spatial direction. However, 3-D super-resolution ultrasound imaging using a full 2-D array requires a system with large number of independent channels, the design of which might be impractical due to the high cost, complexity, and volume of data produced. In this study, a 2-D sparse array was designed and fabricated with 512 elements chosen from a density-tapered 2-D spiral layout. High frame rate volumetric imaging was performed using two synchronized ULA-OP 256 research scanners. Volumetric images were constructed by coherently compounding 9-angle plane waves acquired in 3 milliseconds at a pulse repetition frequency of 3000 Hz. To allow microbubbles sufficient time to move between consequent compounded volumetric frames, a 7-millisecond delay was introduced after each volume acquisition. This reduced the effective volume acquisition speed to 100 Hz and the total acquired data size by 3.3-fold. Localization-based 3-D super-resolution images of two touching sub-wavelength tubes were generated from 6000 volumes acquired in 60 seconds. In conclusion, this work demonstrates the feasibility of 3D super-resolution imaging and super-resolved velocity mapping using a customized 2D sparse array transducer.

physics.med-ph↗

arXiv2018

Advances in Computational Methods for Phylogenetic Networks in the Presence of Hybridization

Phylogenetic networks extend phylogenetic trees to allow for modeling reticulate evolutionary processes such as hybridization. They take the shape of a rooted, directed, acyclic graph, and when parameterized with evolutionary parameters, such as divergence times and population sizes, they form a generative process of molecular sequence evolution. Early work on computational methods for phylogenetic network inference focused exclusively on reticulations and sought networks with the fewest number of reticulations to fit the data. As processes such as incomplete lineage sorting (ILS) could be at play concurrently with hybridization, work in the last decade has shifted to computational approaches for phylogenetic network inference in the presence of ILS. In such a short period, significant advances have been made on developing and implementing such computational approaches. In particular, parsimony, likelihood, and Bayesian methods have been devised for estimating phylogenetic networks and associated parameters using estimated gene trees as data. Use of those inference methods has been augmented with statistical tests for specific hypotheses of hybridization, like the D-statistic. Most recently, Bayesian approaches for inferring phylogenetic networks directly from sequence data were developed and implemented. In this chapter, we survey such advances and discuss model assumptions as well as methods' strengths and limitations. We also discuss parallel efforts in the population genetics community aimed at inferring similar structures. Finally, we highlight major directions for future research in this area.

q-bio.PE↗

arXiv2018

A tunable time-resolved spontaneous Raman spectroscopy setup for probing ultrafast collective excitation and quasiparticle dynamics in quantum materials

We present a flexible and efficient ultrafast time-resolved spontaneous Raman spectroscopy setup to study collective excitation and quasi-particle dynamics in quantum matter. The setup has a broad energy tuning range extending from the visible to near infrared spectral regions for both the pump excitation and Raman probe pulses. Additionally, the balance between energy and time-resolution can be controlled. A high light collecting efficiency is realized by high numerical aperture collection optics and a high-throughput flexible spectrometer. We demonstrate the functionality of the setup with a study of the zone-center longitudinal optical phonon and hole continuum dynamics in silicon, and discuss the role of the Raman tensor in time-resolved Raman scattering. In addition, we show evidence for unequal phonon softening rates at different high symmetry points in the Brillouin zone of silicon by means of detecting pump-induced changes in the two-phonon overtone spectrum. Demagnetization dynamics in the helimagnet Cu2OSeO3 is studied by observing softening and broadening of a magnon after photo-excitation, underlining the unique power of measuring transient dynamics in the frequency domain, and the feasibility to study phase transitions in quantum matter.

cond-mat.mtrl-sci↗

arXiv2018

Status and Objectives of the Dedicated Accelerator R&D Facility "SINBAD" at DESY

We present a status update on the dedicated R\&D facility SINBAD which is currently under construction at DESY. The facility will host multiple independent experiments on the acceleration of ultra-short electron bunches and novel, high gradient acceleration methods. The first experiment is the ARES-experiment with a normal conducting 100\,MeV S-band linac at its core. We present the objectives of this experiment ranging from the study of compression techniques to sub-fs level to its application as injector for various advanced acceleration schemes e.g. the plans to use ARES as a test-site for DLA experiments in the context of the ACHIP collaboration. The time-line including the planned extension with laser driven plasma-wakefield acceleration is presented. The second initial experiment is AXSIS which aims to accelerate fs-electron bunches to 15\,MeV in a THz driven dielectric structure and subsequently create X-rays by inverse Compton scattering.

physics.acc-ph↗