arXiv subjects

Lei Ren

Publications and source records attributed to Lei Ren.

At least 55 records · Page 3Linked to original sources

arXiv2023

Hybrid-Supervised Deep Learning for Domain Transfer 3D Protoacoustic Image Reconstruction

Protoacoustic imaging showed great promise in providing real-time 3D dose verification of proton therapy. However, the limited acquisition angle in protoacoustic imaging induces severe artifacts, which significantly impairs its accuracy for dose verification. In this study, we developed a deep learning method with a Recon- Enhance two-stage strategy for protoacoustic imaging to address the limited view issue. Specifically, in the Recon-stage, a transformer-based network was developed to reconstruct initial pressure maps from radiofrequency signals. The network is trained in a hybrid-supervised approach, where it is first trained using supervision by the iteratively reconstructed pressure map and then fine-tuned using transfer learning and self-supervision based on the data fidelity constraint. In the Enhance-stage, a 3D U-net is applied to further enhance the image quality with supervision from the ground truth pressure map. The final protoacoustic images are then converted to dose for proton verification. The results evaluated on a dataset of 126 prostate cancer patients achieved an average RMSE of 0.0292, and an average SSIM of 0.9618, significantly out-performing related start-of-the-art methods. Qualitative results also demonstrated that our approach addressed the limit-view issue with more details reconstructed. Dose verification achieved an average RMSE of 0.018, and an average SSIM of 0.9891. Gamma index evaluation demonstrated a high agreement (94.7% and 95.7% for 1%/3 mm and 1%/5 mm) between the predicted and the ground truth dose maps. Notably, the processing time was reduced to 6 seconds, demonstrating its feasibility for online 3D dose verification for prostate proton therapy.

physics.med-ph↗

arXiv2023

Flow states and heat transport in liquid metal convection

We present an experimental study of Rayleigh-Bénard convection using liquid metal alloy gallium-indium-tin as the working fluid with a Prandtl number of $Pr=0.029$. The flow state and the heat transport were measured in a Rayleigh number range of $1.2\times10^{4} \le Ra \le 1.3\times10^{7}$. The temperature fluctuation at the cell centre is used as a proxy for the flow state. It is found that, as $Ra$ increases from the lower end of the parameter range, the flow evolves from a convection state to an oscillation state, a chaotic state, and finally a turbulent state for $Ra>10^5$. The study suggests that the large-scale circulation in the turbulent state is a residual of the cell structures near the onset of convection, which is in contrast with the case of $Pr\sim1$, where the cell structure is replaced by high-order flow modes transiently before the emergence of the large-scale circulation in the turbulent state. The evolution of the flow state is also reflected by the heat transport characterised by the Nusselt number $Nu$ and the probability density function (PDF) of the temperature fluctuation at the cell centre. It is found that the effective local heat transport scaling exponent $γ$, i.e., $Nu\sim Ra^γ$, changes continuously from $γ=0.49$ at $Ra\sim 10^4$ to $γ=0.25$ for $Ra>10^6$. Meanwhile, the PDF at the cell centre gradually evolves from a Gaussian-like shape before the transition to turbulence to an exponential-like shape in the turbulent state. For $Ra>10^6$, the flow shows self-similar behaviour, which is revealed by the universal shape of the PDF of the temperature fluctuation at the cell centre and a $Nu=0.19Ra^{0.25}$ scaling for the heat transport.

physics.flu-dyn↗

arXiv2023

Radiation-induced Acoustic Signal Denoising using a Supervised Deep Learning Framework for Imaging and Therapy Monitoring

Radiation-induced acoustic (RA) imaging is a promising technique for visualizing radiation energy deposition in tissues, enabling new imaging modalities and real-time therapy monitoring. However, it requires measuring hundreds or even thousands of averages to achieve satisfactory signal-to-noise ratios (SNRs). This repetitive measurement increases ionizing radiation dose and degrades the temporal resolution of RA imaging, limiting its clinical utility. In this study, we developed a general deep inception convolutional neural network (GDI-CNN) to denoise RA signals to substantially reduce the number of averages. The multi-dilation convolutions in the network allow for encoding and decoding signal features with varying temporal characteristics, making the network generalizable to signals from different radiation sources. The proposed method was evaluated using experimental data of X-ray-induced acoustic, protoacoustic, and electroacoustic signals, qualitatively and quantitatively. Results demonstrated the effectiveness and generalizability of GDI-CNN: for all the enrolled RA modalities, GDI-CNN achieved comparable SNRs to the fully-averaged signals using less than 2% of the averages, significantly reducing imaging dose and improving temporal resolution. The proposed deep learning framework is a general method for few-frame-averaged acoustic signal denoising, which significantly improves RA imaging's clinical utilities for low-dose imaging and real-time therapy monitoring.

physics.med-ph↗

arXiv2023

Stability of the In-Plane Room Temperature van der Waals Ferromagnet Chromium Ditelluride and Its Conversion to Chromium-Interleaved CrTe$_2$ Compounds

Van der Waals magnetic materials are building blocks for novel kinds of spintronic devices and playgrounds for exploring collective magnetic phenomena down to the two-dimensional limit. Chromium-tellurium compounds are relevant in this perspective. In particular, the 1$T$ phase of CrTe$_2$ has been argued to have a Curie temperature above 300~K, a rare and desirable property in the class of lamellar materials, making it a candidate for practical applications. However, recent literature reveals a strong variability in the reported properties, including magnetic ones. Using electron microscopy, diffraction and spectroscopy techniques, together with local and macroscopic magnetometry approaches, our work sheds new light on the structural, chemical and magnetic properties of bulk 1$T$-CrTe$_2$ exfoliated in the form of flakes having a thickness ranging from few to several tens of nanometers. We unambiguously establish that 1$T$-CrTe$_2$ flakes are ferromagnetic above room temperature, have an in-plane easy axis of magnetization, low coercivity, and we confirm that their Raman spectroscopy signatures are two modes, $E_{2\text{g}}$ (103.5~cm$^{-1}$) and $A_{1\text{g}}$ (136.5~cm$^{-1}$). We also prove that thermal annealing causes a phase transformation to monoclinic Cr$_5$Te$_8$ and, to a lesser extent, to trigonal Cr$_5$Te$_8$. In sharp contrast with 1$T$-CrTe$_2$, none of these compounds have a Curie temperature above room temperature, and they both have perpendicular magnetic anisotropy. Our findings reconcile the apparently conflicting reports in the literature and open opportunities for phase-engineered magnetic properties.

cond-mat.mtrl-sci↗

arXiv2022

Making Pretrained Language Models Good Long-tailed Learners

Prompt-tuning has shown appealing performance in few-shot classification by virtue of its capability in effectively exploiting pre-trained knowledge. This motivates us to check the hypothesis that prompt-tuning is also a promising choice for long-tailed classification, since the tail classes are intuitively few-shot ones. To achieve this aim, we conduct empirical studies to examine the hypothesis. The results demonstrate that prompt-tuning makes pretrained language models at least good long-tailed learners. For intuitions on why prompt-tuning can achieve good performance in long-tailed classification, we carry out in-depth analyses by progressively bridging the gap between prompt-tuning and commonly used finetuning. The summary is that the classifier structure and parameterization form the key to making good long-tailed learners, in comparison with the less important input structure. Finally, we verify the applicability of our finding to few-shot classification. Good long-tailed learners can be abbreviated as Glee.

cs.CL↗

arXiv2022

XPrompt: Exploring the Extreme of Prompt Tuning

Prompt tuning learns soft prompts to condition frozen Pre-trained Language Models (PLMs) for performing downstream tasks in a parameter-efficient manner. While prompt tuning has gradually reached the performance level of fine-tuning as the model scale increases, there is still a large performance gap between prompt tuning and fine-tuning for models of moderate and small scales (typically less than 11B parameters). In this paper, we empirically show that the trained prompt tokens can have a negative impact on a downstream task and thus degrade its performance. To bridge the gap, we propose a novel Prompt tuning model with an eXtremely small scale (XPrompt) under the regime of lottery tickets hypothesis. Specifically, XPrompt eliminates the negative prompt tokens at different granularity levels through a hierarchical structured pruning, yielding a more parameter-efficient prompt yet with a competitive performance. Comprehensive experiments are carried out on SuperGLUE tasks, and the extensive results indicate that XPrompt is able to close the performance gap at smaller model scales.

cs.CL↗

arXiv2022

Structural Bias for Aspect Sentiment Triplet Extraction

Structural bias has recently been exploited for aspect sentiment triplet extraction (ASTE) and led to improved performance. On the other hand, it is recognized that explicitly incorporating structural bias would have a negative impact on efficiency, whereas pretrained language models (PLMs) can already capture implicit structures. Thus, a natural question arises: Is structural bias still a necessity in the context of PLMs? To answer the question, we propose to address the efficiency issues by using an adapter to integrate structural bias in the PLM and using a cheap-to-compute relative position structure in place of the syntactic dependency structure. Benchmarking evaluation is conducted on the SemEval datasets. The results show that our proposed structural adapter is beneficial to PLMs and achieves state-of-the-art performance over a range of strong baselines, yet with a light parameter demand and low latency. Meanwhile, we give rise to the concern that the current evaluation default with data of small scale is under-confident. Consequently, we release a large-scale dataset for ASTE. The results on the new dataset hint that the structural adapter is confidently effective and efficient to a large scale. Overall, we draw the conclusion that structural bias shall still be a necessity even with PLMs.

cs.CL↗

arXiv2022

Intervalley electron-hole exchange interaction and impurity-assisted recombination of indirect excitons in WS$_2$ and WSe$_2$ monolayers

The variety of excitonic states in tungsten-based dichalcogenide monolayers stems from unique interplay between the spin and valley degrees of freedom. One of the exciton species is the indirect exciton (momentum or valley dark), which is responsible to a series of resonances when the monolayer is charge neutral. We investigate the short-range electron-hole exchange interaction of the indirect exciton, as well as its recombination mechanism mediated by impurities. The analysis provides thorough understanding of the energy and polarization of the zero-phonon indirect exciton resonance in the emission spectrum.

cond-mat.mes-hall↗

arXiv2022

Polychromatic drivers for inertial fusion energy

Although tremendous achievements have been made toward inertial confinement fusion, laser plasma instabilities (LPIs) remain to be an inevitable problem for current drive schemes. To mitigate these instabilities, significant efforts have been paid to produce high-power broadband ultraviolet lasers. However, no practical scheme has been demonstrated up to now for efficient triple-frequency conversion of broadband laser. Here we propose the design of polychromatic drivers for the generation of multicolor beams mainly based upon the optical parametric amplification, which can significantly enhance the third-harmonic conversion efficiency. Each polychromatic light has four colors of monochromatic beamlets with a full spectrum width of 3\%, and the beamlet colors of any two adjacent flanges are different. The suppression effects of such polychromatic lights have been investigated via large scale particle-in-cell simulations, which indicate that more than 35\% of the incident energy can be saved from the LPIs compared with monochromatic lasers for the direct-drive scheme, or high-density filled target for the indirect-drive scheme. The proposed polychromatic drivers are based on the matured technologies, and thus may pave the way towards realization of robust and high-efficiency fusion ignition.

physics.optics↗

arXiv2022

Optical detection of long electron spin transport lengths in a monolayer semiconductor

Using a spatially-resolved optical pump-probe experiment, we measure the lateral transport of spin/valley polarized electrons over very long distances (tens of micrometers) in a single WSe2 monolayer. By locally pumping the Fermi sea of 2D electrons to a high degree of spin/valley polarization (up to 75%) using circularly-polarized light, the lateral diffusion of the electron polarization can be mapped out via the photoluminescence induced by a spatially-separated and linearly-polarized probe laser. Up to 25% spin-valley polarization is observed at pump-probe separations up to 20 microns. Characteristic spin/valley diffusion lengths of 18 +/- 3 um are revealed at low temperatures. The dependence on temperature, pump helicity, pump intensity, and electron density highlight the key roles played by spin relaxation time and pumping efficiency on polarized electron transport in monolayer semiconductors possessing spin-valley locking.

cond-mat.mes-hall↗

arXiv2022

From the synthesis of hBN crystals to their use as nanosheets for optoelectronic devices

In the wide world of 2D materials, hexagonal boron nitride (hBN) holds a special place due to its excellent characteristics. In addition to its thermal, chemical and mechanical stability, hBN demonstrates high thermal conductivity, low compressibility, and wide band gap around 6 eV, making it promising candidate for many groundbreaking applications and more specifically for optoelectronic devices. Millimeters scale hexagonal boron nitride crystals are obtained through a disruptive dual method (PDC/PCS) consisting in a complementary coupling of the Polymer Derived Ceramics route and a Pressure-Controlled Sintering process. In addition to their excellent chemical and crystalline quality, these crystals exhibit a free exciton lifetime of 0.43 ns, as determined by time-resolved cathodoluminescence measurements, confirming their interesting optical properties. To go further in applicative fields, hBN crystals are then exfoliated, and resulting Boron Nitride NanoSheets (BNNSs) are used to encapsulate transition metal dichalcogenides (TMDs). Such van der Waals heterostructures are tested by optical spectroscopy. BNNSs do not luminesce in the emission spectral range of TMDs and the photoluminescence width of the exciton at 4K is in the range 2-3 meV. All these results demonstrate that these BNNSs are relevant for future opto-electronic applications.

cond-mat.mtrl-sci↗

arXiv2021

Relaxation and darkening of excitonic complexes in electrostatically-doped monolayer semiconductors: Roles of exciton-electron and trion-electron interactions

We present photoluminescence measurements in monolayer WSe$_2$, which point to the importance of the interaction between charged particles and excitonic complexes. The theoretical analysis highlights the key role played by exchange scattering, referring to cases wherein the particle composition of the complex changes after the interaction. For example, exchange scattering renders bright excitonic complexes dark in monolayer WSe$_2$ on accounts of the unique valley-spin configuration in this material. In addition to the ultrafast energy relaxation of hot excitonic complexes following their interaction with electrons or holes, our analysis sheds light on several key features that are commonly seen in the photoluminescence of this monolayer semiconductor. In particular, we can understand why the photoluminescence intensity of the neutral bright exciton is strongest when the monolayer is hole-doped rather than charge neutral or electron-doped. Or the reason for the dramatic increase of the photoluminescence intensity of negatively-charged excitons (trions) as soon as electrons are added to the monolayer. To self-consistently explain the findings, we further study the photoluminescence spectra at different excitation energies and analyze the behavior of the elusive indirect exciton.

cond-mat.mtrl-sci↗

arXiv2021

Large perpendicular magnetic anisotropy in Ta/CoFeB/MgO on full coverage monolayer MoS2 and first principle study of its electronic structure

Perpendicularly magnetized spin injector with high Curie temperature is a prerequisite for developing spin optoelectronic devices on 2D materials working at room temperature (RT) with zero applied magnetic field. Here, we report the growth of Ta/CoFeB/MgO structures with a large perpendicular magnetic anisotropy (PMA) on full coverage monolayer (ML) MoS2. A large perpendicular interface anisotropy energy of 0.975mJ/m2 has been obtained at the CoFeB/MgO interface, comparable to that observed in magnetic tunnel junction systems. It is found that the insertion of MgO between the ferromagnetic metal (FM) and the 2D material can effectively prevent the diffusion of the FM atoms into the 2D material. Moreover, the MoS2 ML favors a MgO(001) texture and plays a critical role to establish the large PMA. First principle calculations on a similar Fe/MgO/MoS2 structure reveal that the MgO thickness can modify the MoS2 band structure, from an indirect bandgap with 7ML-MgO to a direct bandgap with 3ML-MgO. Proximity effect induced by Fe results in a splitting of 10meV in the valence band at the Γ point for the 3ML-MgO structure while it is negligible for the 7ML-MgO structure. These results pave the way to develop RT spin optoelectronic devices on 2D transition-metal dichalcogenide materials.

cond-mat.mtrl-sci↗

arXiv2021

Spin/Valley pumping of resident electrons in WSe2 and WS2 monolayers

Monolayers of transition metal dichalcogenides are ideal materials to control both spin and valley degrees of freedom either electrically or optically. Nevertheless, optical excitation mostly generates excitons species with inherently short lifetime and spin/valley relaxation time. Here we demonstrate a very efficient spin/valley optical pumping of resident electrons in n-doped WSe2 and WS2 monolayers. We observe that, using a continuous wave laser and appropriate doping and excitation densities, negative trion doublet lines exhibit circular polarization of opposite sign and the photoluminescence intensity of the triplet trion is more than four times larger with circular excitation than with linear excitation. We interpret our results as a consequence of a large dynamic polarization of resident electrons using circular light.

cond-mat.mes-hall↗

arXiv2021

ASAP: A Chinese Review Dataset Towards Aspect Category Sentiment Analysis and Rating Prediction

Sentiment analysis has attracted increasing attention in e-commerce. The sentiment polarities underlying user reviews are of great value for business intelligence. Aspect category sentiment analysis (ACSA) and review rating prediction (RP) are two essential tasks to detect the fine-to-coarse sentiment polarities. %Considering the sentiment of the aspects(ACSA) and the overall review rating(RP) simultaneously has the potential to improve the overall performance. ACSA and RP are highly correlated and usually employed jointly in real-world e-commerce scenarios. While most public datasets are constructed for ACSA and RP separately, which may limit the further exploitation of both tasks. To address the problem and advance related researches, we present a large-scale Chinese restaurant review dataset \textbf{ASAP} including $46,730$ genuine reviews from a leading online-to-offline (O2O) e-commerce platform in China. Besides a $5$-star scale rating, each review is manually annotated according to its sentiment polarities towards $18$ pre-defined aspect categories. We hope the release of the dataset could shed some light on the fields of sentiment analysis. Moreover, we propose an intuitive yet effective joint model for ACSA and RP. Experimental results demonstrate that the joint model outperforms state-of-the-art baselines on both tasks.

cs.CL↗

arXiv2021

First radiative shock experiments on the SG-II laser

We report on the design and first results from experiments looking at the formation of radiative shocks on the Shenguang-II (SG-II) laser at the Shanghai Institute of Optics and Fine Mechanics in China. Laser-heating of a two-layer CH/CH-Br foil drives a $\sim$40 km/s shock inside a gas-cell filled with argon at an initial pressure of 1 bar. The use of gas-cell targets with large (several mm) lateral and axial extent allows the shock to propagate freely without any wall interactions, and permits a large field of view to image single and colliding counter-propagating shocks with time resolved, point-projection X-ray backlighting ($\sim20$ $μ$m source size, 4.3 keV photon energy). Single shocks were imaged up to 100 ns after the onset of the laser drive allowing to probe the growth of spatial non-uniformities in the shock apex. These results are compared with experiments looking at counter-propagating shocks, showing a symmetric drive which leads to a collision and stagnation from $\sim$40 ns onward. We present a preliminary comparison with numerical simulations with the radiation hydrodynamics code ARWEN, which provides expected plasma parameters for the design of future experiments in this facility.

physics.plasm-ph↗

arXiv2020

Bremsstrahlung emission and plasma characterization driven by moderately relativistic laser-plasma interactions

Relativistic electrons generated by the interaction of petawatt-class short laser pulses with solid targets can be used to generate bright X-rays via bremsstrahlung. The efficiency of laser energy transfer into these electrons depends on multiple parameters including the focused intensity and pre-plasma level. This paper reports experimental results from the interaction of a high intensity petawatt-class glass laser pulses with solid targets at a maximum intensity of $10^{19}$ W/cm$^2$. In-situ measurements of specularly reflected light are used to provide an upper bound of laser absorption and to characterize focused laser intensity, the pre-plasma level and the generation mechanism of second harmonic light. The measured spectrum of electrons and bremsstrahlung radiation provide information about the efficiency of laser energy transfer.

physics.plasm-ph↗

arXiv2020

Measurement of Conduction and Valence Bands g-factors in a Transition Metal Dichalcogenide Monolayer

The electron valley and spin degree of freedom in monolayer transition-metal dichalcogenides can be manipulated in optical and transport measurements performed in magnetic fields. The key parameter for determining the Zeeman splitting, namely the separate contribution of the electron and hole g-factor, is inaccessible in most measurements. Here we present an original method that gives access to the respective contribution of the conduction and valence band to the measured Zeeman splitting. It exploits the optical selection rules of exciton complexes, in particular the ones involving inter-valley phonons, avoiding strong renormalization effects that compromise single particle g-factor determination in transport experiments. These studies yield a direct determination of single band g factors. We measure gc1= 0.86, gc2=3.84 for the bottom (top) conduction bands and gv=6.1 for the valence band of monolayer WSe2. These measurements are helpful for quantitative interpretation of optical and transport measurements performed in magnetic fields. In addition the measured g-factors are valuable input parameters for optimizing band structure calculations of these 2D materials.

cond-mat.mtrl-sci↗