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Jie Zhao

Publications and source records attributed to Jie Zhao.

At least 145 records · Page 8Linked to original sources
arXiv2023

Properties of Two-Mode Quadrature Squeezing from Four-wave Mixing in Rubidium Vapor

We present a study of homodyne measurements of two-mode, vacuum-seeded, quadrature-squeezed light generated by four-wave mixing in warm rubidium vapor. Our results reveal that the vacuum squeezing can extend down to measurement frequencies of less than 1 Hz, and the squeezing bandwidth, similar to the seeded intensity-difference squeezing measured in this system, reaches up to approximately 20 MHz for typical pump parameters. By dividing the squeezing bandwidth into smaller frequency bins, we show that different sideband frequencies represent independent sources of two-mode squeezing. Such frequency bins may provide useful qumodes for quantum information processing experiments. We also investigate the impact of group velocity delays on the correlations in the system.

quant-ph↗
arXiv2023

Silicon Photonic Direct-Detection Phase Retrieval Receiver

We demonstrate a direct-detection phase retrieval receiver based on silicon photonics. The receiver implements strong dispersion and delay lines on a compact chip. We retrieve the full field of a 30-GBd QPSK signal without a carrier or local oscillator.

physics.optics↗
arXiv2023

Few-Shot Domain Adaptation for Charge Prediction on Unprofessional Descriptions

Recent works considering professional legal-linguistic style (PLLS) texts have shown promising results on the charge prediction task. However, unprofessional users also show an increasing demand on such a prediction service. There is a clear domain discrepancy between PLLS texts and non-PLLS texts expressed by those laypersons, which degrades the current SOTA models' performance on non-PLLS texts. A key challenge is the scarcity of non-PLLS data for most charge classes. This paper proposes a novel few-shot domain adaptation (FSDA) method named Disentangled Legal Content for Charge Prediction (DLCCP). Compared with existing FSDA works, which solely perform instance-level alignment without considering the negative impact of text style information existing in latent features, DLCCP (1) disentangles the content and style representations for better domain-invariant legal content learning with carefully designed optimization goals for content and style spaces and, (2) employs the constitutive elements knowledge of charges to extract and align element-level and instance-level content representations simultaneously. We contribute the first publicly available non-PLLS dataset named NCCP for developing layperson-friendly charge prediction models. Experiments on NCCP show the superiority of our methods over competitive baselines.

cs.CL↗
arXiv2023

Leveraging the Power of Data Augmentation for Transformer-based Tracking

Due to long-distance correlation and powerful pretrained models, transformer-based methods have initiated a breakthrough in visual object tracking performance. Previous works focus on designing effective architectures suited for tracking, but ignore that data augmentation is equally crucial for training a well-performing model. In this paper, we first explore the impact of general data augmentations on transformer-based trackers via systematic experiments, and reveal the limited effectiveness of these common strategies. Motivated by experimental observations, we then propose two data augmentation methods customized for tracking. First, we optimize existing random cropping via a dynamic search radius mechanism and simulation for boundary samples. Second, we propose a token-level feature mixing augmentation strategy, which enables the model against challenges like background interference. Extensive experiments on two transformer-based trackers and six benchmarks demonstrate the effectiveness and data efficiency of our methods, especially under challenging settings, like one-shot tracking and small image resolutions.

cs.CV↗
arXiv2023

Environmental radon control in the 700-m underground laboratory at JUNO

The Jiangmen Underground Neutrino Observatory is building the world's largest liquid scintillator detector with a 20 kt target mass and about 700 m overburden. The total underground space of civil construction is about 300,000 m$^3$ with the main hall volume of about 120,000 m$^3$, which is the biggest laboratory in the world. Radon concentration in the underground air is quite important for not only human beings' health but also the background of experiments with rare decay detection, such as neutrino and dark matter experiments. The radon concentration is the main hall is required to be around 100 Bq/m$^3$. Optimization of the ventilation with fresh air is effective to control the radon underground. To find the radon sources in the underground laboratory, we made a benchmark experiment in the refuge room near the main hall. The result shows that the radon emanating from underground water is one of the main radon sources in the underground air. The total underground ventilation rate is about 160,000 m$^3$/h fresh air with about 30 Bq/m$^3$ $^{222}$Rn from the bottom of the vertical tunnel after optimization, and 55,000 m$^3$/h is used for the ventilation in the main hall. Finally, the radon concentration inside the main hall decreased from 1600 Bq/m$^3$ to around 100 Bq/m$^3$. The suggested strategies for controlling radon concentration in the underground air are described in this paper.

physics.ins-det↗
arXiv2023

iEDA: An Open-Source Intelligent Physical Implementation Toolkit and Library

Open-source EDA shows promising potential in unleashing EDA innovation and lowering the cost of chip design. This paper presents an open-source EDA project, iEDA, aiming for building a basic infrastructure for EDA technology evolution and closing the industrial-academic gap in the EDA area. iEDA now covers the whole flow of physical design (including Floorplan, Placement, CTS, Routing, Timing Optimization etc.), and part of the analysis tools (Static Timing Analysis and Power Analysis). To demonstrate the effectiveness of iEDA, we implement and tape out three chips of different scales (from 700k to 1.5M gates) on different process nodes (110nm and 28nm) with iEDA. iEDA is publicly available from the project home page http://ieda.oscc.cc.

cs.AR↗
arXiv2023

Utilizing Large Language Models for Natural Interface to Pharmacology Databases

The drug development process necessitates that pharmacologists undertake various tasks, such as reviewing literature, formulating hypotheses, designing experiments, and interpreting results. Each stage requires accessing and querying vast amounts of information. In this abstract, we introduce a Large Language Model (LLM)-based Natural Language Interface designed to interact with structured information stored in databases. Our experiments demonstrate the feasibility and effectiveness of the proposed framework. This framework can generalize to query a wide range of pharmaceutical data and knowledge bases.

cs.CL↗
arXiv2023

Unveiling the origins of quasi-phase matching spectral imperfections in thin-film lithium niobate frequency doublers

Thin-film lithium niobate (TFLN) based frequency doublers have been widely recognized as essential components for both classical and quantum optical communications. Nonetheless, the efficiency of these devices is hindered by imperfections present in the quasi-phase matching (QPM) spectrum. In this study, we present a thorough analysis of the spectral imperfections in TFLN frequency doublers with varying lengths, ranging from 5 mm to 15 mm. Employing a non-destructive diagnostic method based on scattered light imaging, we identify the sources and waveguide sections that contribute to the imperfections in the QPM spectrum. Furthermore, by mapping the TFLN film thickness across the entire waveguiding regions, we successfully reproduce the QPM spectra numerically, thus confirming the prominent influence of film thickness variations on the observed spectral imperfections. This comprehensive investigation provides valuable insights into the identification and mitigation of spectral imperfections in TFLN-based frequency doublers, paving the way toward the realization of nonlinear optical devices with enhanced efficiency and improved spectral fidelity.

physics.optics↗
arXiv2023

Nonlocal phase modulation of multimode, continuous-variable twin beams

We investigate experimentally the nonlocal phase modulation of multiple-frequency-mode, continuous-variable entangled twin beams. We use a pair of electro-optical phase modulators to modulate the entangled probe and conjugate light beams produced by four-wave mixing in hot Rb vapor. A single phase modulator in either one of the twin beams reduces the two-mode squeezing signal, and we find that the modulations interfere nonlocally to modify the beam correlations. The nonlocal modulation of the beams can produce quantum correlations among frequency modes of the multimode fields.

quant-ph↗
arXiv2023

MedFMC: A Real-world Dataset and Benchmark For Foundation Model Adaptation in Medical Image Classification

Foundation models, often pre-trained with large-scale data, have achieved paramount success in jump-starting various vision and language applications. Recent advances further enable adapting foundation models in downstream tasks efficiently using only a few training samples, e.g., in-context learning. Yet, the application of such learning paradigms in medical image analysis remains scarce due to the shortage of publicly accessible data and benchmarks. In this paper, we aim at approaches adapting the foundation models for medical image classification and present a novel dataset and benchmark for the evaluation, i.e., examining the overall performance of accommodating the large-scale foundation models downstream on a set of diverse real-world clinical tasks. We collect five sets of medical imaging data from multiple institutes targeting a variety of real-world clinical tasks (22,349 images in total), i.e., thoracic diseases screening in X-rays, pathological lesion tissue screening, lesion detection in endoscopy images, neonatal jaundice evaluation, and diabetic retinopathy grading. Results of multiple baseline methods are demonstrated using the proposed dataset from both accuracy and cost-effective perspectives.

cs.CV↗
arXiv2023

propnet: Propagating 2D Annotation to 3D Segmentation for Gastric Tumors on CT Scans

**Background:** Accurate 3D CT scan segmentation of gastric tumors is pivotal for diagnosis and treatment. The challenges lie in the irregular shapes, blurred boundaries of tumors, and the inefficiency of existing methods. **Purpose:** We conducted a study to introduce a model, utilizing human-guided knowledge and unique modules, to address the challenges of 3D tumor segmentation. **Methods:** We developed the PropNet framework, propagating radiologists' knowledge from 2D annotations to the entire 3D space. This model consists of a proposing stage for coarse segmentation and a refining stage for improved segmentation, using two-way branches for enhanced performance and an up-down strategy for efficiency. **Results:** With 98 patient scans for training and 30 for validation, our method achieves a significant agreement with manual annotation (Dice of 0.803) and improves efficiency. The performance is comparable in different scenarios and with various radiologists' annotations (Dice between 0.785 and 0.803). Moreover, the model shows improved prognostic prediction performance (C-index of 0.620 vs. 0.576) on an independent validation set of 42 patients with advanced gastric cancer. **Conclusions:** Our model generates accurate tumor segmentation efficiently and stably, improving prognostic performance and reducing high-throughput image reading workload. This model can accelerate the quantitative analysis of gastric tumors and enhance downstream task performance.

eess.IV↗
arXiv2023

Magnetic field extrapolation in active region well comparable with observations in multiple layers

Magnetic field extrapolation is a fundamental tool to reconstruct the three-dimensional magnetic field above the solar photosphere. However, the prevalently used force-free field model might not be applicable in the lower atmosphere with non-negligible plasma \b{eta}, where the crucial process of flux rope formation and evolution could happen. In this work, we perform extrapolation in active region (AR) 12158, based on an recently developed magnetohydrostatic (MHS) method which takes plasma forces into account. By comparing the results with those from the force-free field extrapolation methods, we find that the overall properties, which are characterized by the magnetic free energy and helicity, are roughly the same. The major differences lie in the magnetic configuration and the twist number of magnetic flux rope (MFR). Unlike previous works either obtained sheared arcades or one coherent flux rope, the MHS method derives two sets of MFR, which are highly twisted and slightly coupled. Specifically, the result in the present work is more comparable with the high-resolution observations from the chromosphere, through the transition region to the corona, such as the filament fibrils, pre-eruptive braiding characteristics and the eruptive double-J shaped hot channel. Overall, our work shows that the newly developed MHS method is more promising to reproduce the magnetic fine structures that can well match the observations at multiple layers, and future data-driven simulation based on such extrapolation will benefit in understanding the critical and precise dynamics of flux rope before eruption.

astro-ph.SR↗
arXiv2023

Efficient Gridless DoA Estimation Method of Non-uniform Linear Arrays with Applications in Automotive Radars

This paper focuses on the gridless direction-of-arrival (DoA) estimation for data acquired by non-uniform linear arrays (NLAs) in automotive applications. Atomic norm minimization (ANM) is a promising gridless sparse recovery algorithm under the Toeplitz model and solved by convex relaxation, thus it is only applicable to uniform linear arrays (ULAs) with array manifolds having a Vandermonde structure. In automotive applications, it is essential to apply the gridless DoA estimation to NLAs with arbitrary geometry with efficiency. In this paper, a fast ANM-based gridless DoA estimation algorithm for NLAs is proposed, which employs the array manifold separation technique and the accelerated proximal gradient (APG) technique, making it applicable to NLAs without losing of efficiency. Simulation and measurement experiments on automotive multiple-input multiple-output (MIMO) radars demonstrate the superiority of the proposed method.

eess.SP↗
arXiv2023

Study on U/Th residual radioactivity in acrylic from surface treatment

Acrylic is widely used as material for the target container in low background experiments due to its high light transparency and low intrinsic radioactivity. However, its surface can be easily contaminated during production, so careful treatment of the surface is essential to avoid direct contamination of the target. The Jiangmen Underground Neutrino Observatory will use about 600~t of acrylic to build the spherical vessel of 35.4~m in diameter for a 20~kt liquid scintillator (LS). Since acrylic will contact the LS directly, the cleanliness of the its surface is quite important for the radiopurity of the LS. A new method for measuring the radioactivity of $^{238}$U and $^{232}$Th in acrylic to sub-ppt ($<10^{-12}$~g/g) was developed, and it is crucial for the acrylic radioactivity screening in this study. We performed many background tests on different surface treatments, and the recommended procedure for the treatment of acrylic to achieve low radioactivity and high light transparency could be applicable to other low background experiments.

physics.ins-det↗
arXiv2022

Global constraint on the magnitude of anomalous chiral effects in heavy-ion collisions

When searching for anomalous chiral effects in heavy-ion collisions, one of the most crucial points is the relationship between the signal and the background. In this letter, we present a simulation in a modified blast wave model at LHC energy, which can simultaneously characterize the majority of measurable quantities, in particular, the chiral magnetic effect (CME) and the chiral magnetic wave (CMW) observables. Such a universal description, for the first time, naturally and quantitatively unifies the CME and the CMW studies and brings to light the connection with the local charge conservation (LCC) background. Moreover, a simple phenomenological approach is performed to introduce the signals, aiming at quantifying the maximum allowable strength of the signals within experimental precision. Such a constraint provides a novel perspective to understand the experimental data and sheds new light on the study of anomalous chiral effects as well as charge dependent correlations.

nucl-th↗
arXiv2022

Reinforced Question Rewriting for Conversational Question Answering

Conversational Question Answering (CQA) aims to answer questions contained within dialogues, which are not easily interpretable without context. Developing a model to rewrite conversational questions into self-contained ones is an emerging solution in industry settings as it allows using existing single-turn QA systems to avoid training a CQA model from scratch. Previous work trains rewriting models using human rewrites as supervision. However, such objectives are disconnected with QA models and therefore more human-like rewrites do not guarantee better QA performance. In this paper we propose using QA feedback to supervise the rewriting model with reinforcement learning. Experiments show that our approach can effectively improve QA performance over baselines for both extractive and retrieval QA. Furthermore, human evaluation shows that our method can generate more accurate and detailed rewrites when compared to human annotations.

cs.CL↗
arXiv2022

Extended time-dependent generator coordinate method study of induced fission (II): total kinetic energy distribution

A model is developed to calculate the total kinetic energy (TKE) distribution of fission fragments in the framework of the time-dependent generator coordinate method (TDGCM), extended to include dissipation effects in the description of induced fission dynamics. Starting from an expression for the dissipative term in the GCM Hamiltonian that determines the time evolution of a statistical collective wave function, derived in the first part of this work, the integrated flux of the probability current through the scission hyper-surface can be computed at different temperatures. The kinetic energy at scission for a specific pair of fragments at a given temperature is determined by the energy balance formula. By folding the kinetic energies of the fragments with the flux of the probability current, the TKE distribution is calculated. The method is illustrated with a calculation of the TKE distribution for induced fission of $^{228}$Th, in the 3D space of collective coordinates: axially-symmetric quadrupole and octupole deformations, and nuclear temperature.

nucl-th↗