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Chao Chen

Publications and source records attributed to Chao Chen.

At least 595 records · Page 33Linked to original sources

Improved measurement of the decays $η' \to π^{+}π^{-}π^{+(0)}π^{-(0)}$ and search for the rare decay $η' \to 4π^{0}$

Using a sample of 10 billion $J/ψ$ events collected with the BESIII detector, the decays $η' \to π^{+}π^{-}π^{+}π^{-}$, $η' \to π^{+}π^{-}π^{0}π^{0}$ and $η' \to 4 π^{0}$ are studied via the process $J/ψ\toγη'$. The branching fractions of $η' \to π^{+}π^{-}π^{+}π^{-}$ and $η' \to π^{+}π^{-}π^{0}$ $π^{0}$ are measured to be $( 8.56 \pm 0.25({\rm stat.}) \pm 0.23({\rm syst.}) ) \times {10^{ - 5}}$ and $(2.12 \pm 0.12({\rm stat.}) \pm 0.10({\rm syst.})) \times {10^{ - 4}}$, respectively, which are consistent with previous measurements but with improved precision. No significant $η' \to 4 π^{0}$ signal is observed, and the upper limit on the branching fraction of this decay is determined to be less than $1.24 \times {10^{-5}}$ at the $90\%$ confidence level. In addition, an amplitude analysis of $η' \to π^{+}π^{-}π^{+}π^{-}$ is performed to extract the doubly virtual isovector form factor $α$ for the first time. The measured value of $α=1.22 \pm 0.33({\rm stat.}) \pm 0.04({\rm syst.})$, is in agreement with the prediction of the VMD model.

hep-ex↗

Study of the decay $J/ψ\to ϕπ^{0}η$

Based on $(10.09 \pm 0.04) \times 10^9$ $J/ψ$ events collected with the BESIII detector operating at the BEPCII collider, a partial wave analysis of the decay $J/ψ\to ϕπ^{0}η$ is performed. We observe for the first time two new structures on the $ϕη$ invariant mass distribution, with statistical significances of $24.0σ$ and $16.9σ$; the first with $J^{\rm PC}$ = $1^{+-}$, mass M = (1911 $\pm$ 6 (stat.) $\pm$ 14 (sys.))~MeV/$c^{2}$, and width $Γ= $ (149 $\pm$ 12 (stat.) $\pm$ 23 (sys.))~MeV, the second with $J^{\rm PC}$ = $1^{--}$, mass M = (1996 $\pm$ 11 (stat.) $\pm$ 30 (sys.))~MeV/$c^{2}$, and width $Γ$ = (148 $\pm$ 16 (stat.) $\pm$ 66 (sys.))~MeV. These measurements provide important input for the strangeonium spectrum. In addition, the $f_0(980)-a_0(980)^0$ mixing signal in $J/ψ\to ϕf_0(980) \to ϕa_0(980)^0$ and the corresponding electromagnetic decay $J/ψ\to ϕa_0(980)^0$ are measured with improved precision, providing crucial information to understand the nature of $a_0(980)^0$ and $f_0(980)$.

hep-ex↗

NewsGPT: ChatGPT Integration for Robot-Reporter

The integration of large language models (LLMs) with social robots has emerged as a promising avenue for enhancing human-robot interactions at a time when news reports generated by artificial intelligence (AI) are gaining in credibility. This integration is expected to intensify and become a more productive resource for journalism, media, communication, and education. In this paper a novel system is proposed that integrates AI's generative pretrained transformer (GPT) model with the Pepper robot, with the aim of improving the robot's natural language understanding and response generation capabilities for enhanced social interactions. By leveraging GPT's powerful language processing capabilities, this system offers a comprehensive pipeline that incorporates voice input recording, speech-to-text transcription, context analysis, and text-to-speech synthesis action generation. The Pepper robot is enabled to comprehend user queries, generate informative responses with general knowledge, maintain contextually relevant conversations, and act as a more domain-oriented news reporter. It is also linked with a news resource and powered with a Google search capability. To evaluate the performance of the framework, experiments were conducted involving a set of diverse questions. The robot's responses were assessed on the basis of eight criteria, including relevance, context, and fluency. Despite some identified limitations, this system contributes to the field of journalism and human-robot interaction by showcasing the potential of integrating LLMs with social robots. The proposed framework opens up opportunities for improving the conversational capabilities of robots, enabling interactions that are smoother, more engaging, and more context aware.

cs.RO↗

High Performance Thin-film Lithium Niobate Modulator Applied ITO Composite Electrode with Modulation Efficiency of 1V*cm

Thin film lithium niobate (TFLN) based electro-optic modulator is widely applied in the field of broadband optical communications due to its advantages such as large bandwidth, high extinction ratio, and low optical loss, bringing new possibilities for the next generation of high-performance electro-optic modulators. However, the modulation efficiency of TFLN modulators is still relatively low when compared with Silicon and Indium-Phosphide (InP) based competitors. Due to the restriction of the trade-off between half-wave voltage and modulation length, it is difficult to simultaneously obtain low driving voltage and large modulating bandwidth. Here, we break this limitation by introducing Transparent Conductive Oxide (TCO) film, resulting in an ultra-high modulation efficiency of 1.02 V*cm in O-Band. The fabricated composite electrode not only achieves high modulation efficiency but also maintains a high electro-optic bandwidth, as demonstrated by the 3 dB roll-off at 108 GHz and the transmission of PAM-4 signals at 224 Gbit/s. Our device presents new solutions for the next generation of low-cost high-performance electro-optic modulators. Additionally, it paves the way for downsizing TFLN-based multi-channel optical transmitter chips.

physics.optics↗

High-fidelity 3D Reconstruction of Plants using Neural Radiance Field

Accurate reconstruction of plant phenotypes plays a key role in optimising sustainable farming practices in the field of Precision Agriculture (PA). Currently, optical sensor-based approaches dominate the field, but the need for high-fidelity 3D reconstruction of crops and plants in unstructured agricultural environments remains challenging. Recently, a promising development has emerged in the form of Neural Radiance Field (NeRF), a novel method that utilises neural density fields. This technique has shown impressive performance in various novel vision synthesis tasks, but has remained relatively unexplored in the agricultural context. In our study, we focus on two fundamental tasks within plant phenotyping: (1) the synthesis of 2D novel-view images and (2) the 3D reconstruction of crop and plant models. We explore the world of neural radiance fields, in particular two SOTA methods: Instant-NGP, which excels in generating high-quality images with impressive training and inference speed, and Instant-NSR, which improves the reconstructed geometry by incorporating the Signed Distance Function (SDF) during training. In particular, we present a novel plant phenotype dataset comprising real plant images from production environments. This dataset is a first-of-its-kind initiative aimed at comprehensively exploring the advantages and limitations of NeRF in agricultural contexts. Our experimental results show that NeRF demonstrates commendable performance in the synthesis of novel-view images and is able to achieve reconstruction results that are competitive with Reality Capture, a leading commercial software for 3D Multi-View Stereo (MVS)-based reconstruction. However, our study also highlights certain drawbacks of NeRF, including relatively slow training speeds, performance limitations in cases of insufficient sampling, and challenges in obtaining geometry quality in complex setups.

cs.CV↗

Topology-Aware Uncertainty for Image Segmentation

Segmentation of curvilinear structures such as vasculature and road networks is challenging due to relatively weak signals and complex geometry/topology. To facilitate and accelerate large scale annotation, one has to adopt semi-automatic approaches such as proofreading by experts. In this work, we focus on uncertainty estimation for such tasks, so that highly uncertain, and thus error-prone structures can be identified for human annotators to verify. Unlike most existing works, which provide pixel-wise uncertainty maps, we stipulate it is crucial to estimate uncertainty in the units of topological structures, e.g., small pieces of connections and branches. To achieve this, we leverage tools from topological data analysis, specifically discrete Morse theory (DMT), to first capture the structures, and then reason about their uncertainties. To model the uncertainty, we (1) propose a joint prediction model that estimates the uncertainty of a structure while taking the neighboring structures into consideration (inter-structural uncertainty); (2) propose a novel Probabilistic DMT to model the inherent uncertainty within each structure (intra-structural uncertainty) by sampling its representations via a perturb-and-walk scheme. On various 2D and 3D datasets, our method produces better structure-wise uncertainty maps compared to existing works. Code available at https://github.com/Saumya-Gupta-26/struct-uncertainty

cs.CV↗

Precision Measurements of $D_s^+ \to ηe^+ ν_e$ and $D_s^+ \to η^\prime e^+ ν_e$

Precision measurements of the semileptonic decays $D_s^+ \to ηe^+ ν_e$ and $D_s^+ \to η^\prime e^+ ν_e$ are performed with 7.33\,fb$^{-1}$ of $e^+e^-$ collision data collected at center-of-mass energies between 4.128 and 4.226 GeV with the BESIII detector. The branching fractions obtained are $\mathcal{B}(D_s^+ \to ηe^{+} ν_e)$ = $(2.255\pm0.039_{\rm stat}\pm 0.051_{\rm syst})\%$ and $\mathcal{B}(D_s^+ \to η^{\prime} e^{+} ν_e)$ = $(0.810\pm0.038_{\rm stat}\pm 0.024_{\rm syst})\%$. Combining these results with the $\mathcal{B}(D^+\toηe^+ ν_e)$ and $\mathcal{B}(D^+\toη^\prime e^+ ν_e)$ obtained from previous BESIII measurements, the $η-η^\prime$ mixing angle in the quark flavor basis is determined to be $ϕ_{\rm P} = (40.0\pm2.0_{\rm stat}\pm0.6_{\rm syst})^\circ$. Moreover, from the fits to the partial decay rates of $D_s^+ \to ηe^+ ν_e$ and $D_s^+ \to η^\prime e^+ ν_e$, the products of the hadronic transition form factors $f_+^{η^{(\prime)}}(0)$ and the modulus of the $c\to s$ Cabibbo-Kobayashi-Maskawa matrix element $|V_{cs}|$ are determined by using different hadronic transition form factor parametrizations. Based on the two-parameter series expansion, the products $f^η_+(0)|V_{cs}| = 0.4519\pm0.0071_{\rm stat}\pm0.0065_{\rm syst}$ and $f^{η^\prime}_+(0)|V_{cs}| = 0.525\pm0.024_{\rm stat}\pm0.009_{\rm syst}$ are extracted. All results determined in this work supersede those measured in the previous BESIII analyses based on the 3.19 fb$^{-1}$ subsample of data at 4.178 GeV.

hep-ex↗

The backreaction effect of the sound speed resonance in DBI inflation

We examine the backreaction effect of the enhanced small-scale scalar perturbations from the sound speed resonance (SSR) mechanism for primordial black hole formation in Dirac-Born-Infeld (DBI) inflation on background as well as curvature perturbation, which can generate a considerable amount of primordial black holes (PBH) in the radiation-dominated epoch. Within the perturbative regime, the backreaction effect of perturbations on the background dynamics can be described by an effective action after integrating out the perturbation sector. Starting with the effective field theory of a specific DBI inflation model that incorporates SSR, we obtain the one-loop effective action by integrating out the scalar perturbations at the quadratic level. Using the effective Friedmann equations derived from this one-loop effective action, we solve the Hubble parameter with backreaction and the effective perturbation dynamics on this background as well. Our numerical findings reveal that, for a viable parameter space, the backreaction effect results in a relative correction to the Hubble parameter of approximately $10^{-7}$, whereas the relative correction to the slow-roll parameter can vary between $-0.3$ and $0.1$, before gradually converging to $10^{-7}$. Furthermore, our results show that the backreaction effect on SSR sound speed causes a slight reduction in the resonant peak of the curvature power spectrum, and the subsequent PBH formation predicted by the SSR mechanism remains almost unchanged.

astro-ph.CO↗

Observation of the hindered electromagnetic Dalitz decay $ψ(3686) \to e^+ e^- η_c$

Using a data sample of $(448.1 \pm 2.9)\times10^6 ~ψ(3686)$ decays collected at an $e^+ e^-$ center-of-mass energy of $3.686~\rm{GeV}$ by the BESIII detector at BEPCII, we report an observation of the hindered electromagnetic Dalitz decay $ψ(3686) \to e^+ e^- η_c$ with a significance of $7.9σ$. The branching fraction is determined to be $\mathcal{B} (ψ(3686) \to e^+ e^- η_c) = (3.77 \pm 0.40_{\rm stat.} \pm 0.18_{\rm syst.})\times 10^{-5}$, agreeing well with the prediction of the vector meson dominance model. This is the first measurement of the electromagnetic Dalitz transition between the $ψ(3686)$ and the $η_c$, which provides new insight into the electromagnetic properties of this decay, and offers new opportunities to measure the absolute branching fractions of $η_c$ decays.

hep-ex↗

Attention-Enhancing Backdoor Attacks Against BERT-based Models

Recent studies have revealed that \textit{Backdoor Attacks} can threaten the safety of natural language processing (NLP) models. Investigating the strategies of backdoor attacks will help to understand the model's vulnerability. Most existing textual backdoor attacks focus on generating stealthy triggers or modifying model weights. In this paper, we directly target the interior structure of neural networks and the backdoor mechanism. We propose a novel Trojan Attention Loss (TAL), which enhances the Trojan behavior by directly manipulating the attention patterns. Our loss can be applied to different attacking methods to boost their attack efficacy in terms of attack successful rates and poisoning rates. It applies to not only traditional dirty-label attacks, but also the more challenging clean-label attacks. We validate our method on different backbone models (BERT, RoBERTa, and DistilBERT) and various tasks (Sentiment Analysis, Toxic Detection, and Topic Classification).

cs.LG↗

Study of $e^+e^-\toηϕ$ at center-of-mass energies from 3.773 to 4.600 GeV

We present a study of the process $e^{+}e^{-}\toηϕ$ using data samples collected with the BESIII detector corresponding to an integrated luminosity of 15.03 fb$^{-1}$ at 23 center-of-mass energies from 3.773 to 4.600 GeV. The Born cross sections are measured at each energy and a coherent fit to cross-section lineshape is performed using a Breit-Wigner parametrization to search for charmonium-like vector states. No significant signals of the $Y(4230)$ and $Y(4360)$ resonances are observed.

hep-ex↗

Study of the doubly Cabibbo-suppressed decays $D^+_s\to K^+K^+π^-$ and $D^+_s\to K^+K^+π^-π^0$

Based on 7.33 fb$^{-1}$ of $e^+e^-$ collision data collected at center-of-mass energies between 4.128 and 4.226 GeV with the BESIII detector, the experimental studies of the doubly Cabibbo-suppressed decays $D^+_s\to K^+K^+π^-$ and $D^+_s\to K^+K^+π^-π^0$ are reported. We determine the absolute branching fraction of $D^+_s\to K^+K^+π^-$ to be (${1.23^{+0.28}_{-0.25}}({\rm stat})\pm0.06({\rm syst})$) $\times 10^{-4}$. No significant signal of $D^+_s\to K^+K^+π^-π^0$ is observed and the upper limit on its decay branching fraction at 90\% confidence level is set to be $1.7\times10^{-4}$.

hep-ex↗

Observation of the $ψ(3686)$ decays into $Σ^{+}\barΣ^{-}ω$ and $Σ^{+}\barΣ^{-}{\mathcalϕ}$

Based on $(27.08\pm 0.14)\times10^{8}$ $ψ(3686)$ events collected with the BESIII detector operating at the BEPCII collider, the $ψ(3686)\toΣ^{+}\barΣ^{-}ω$ and $Σ^{+}\barΣ^{-}ϕ$ decays are observed for the first time with statistical significances of 13.8$σ$ and 7.6$σ$, respectively. The corresponding branching fractions are measured to be $\mathcal{B}(ψ(3686)\toΣ^{+}\barΣ^{-}ω)=(1.90 \pm 0.18 \pm 0.21) \times 10^{-5}$ and $\mathcal{B}(ψ(3686)\toΣ^{+}\barΣ^{-}ϕ)=(2.96 \pm 0.54 \pm 0.41) \times 10^{-6}$, where the first uncertainties are statistical and the second systematic.

hep-ex↗

Measurement of the branching fractions of the singly Cabibbo-suppressed decays $Λ_{c}^{+}\to pη$ and $Λ_{c}^{+}\to pω$

Based on 4.5 $\mbox{fb$^{-1}$}$ $e^{+}e^{-}$ collision data collected with BESIII detector at seven energy points between 4.600 and 4.699 GeV, the branching fractions for $Λ_{c}^{+}\to pη$ and $Λ_{c}^{+}\to pω$ were measured by means of single-tag method. The branching fractions of $Λ_{c}^{+}\to pη$ and $Λ_{c}^{+}\to pω$ are determined to be $(1.57\pm0.11_{\rm {stat}}\pm0.04_{\rm{syst}})\times10^{-3}$ and $(1.11\pm0.20_{\rm{stat}}\pm0.07_{\rm{syst}})\times10^{-3}$, with a statistical significance of greater than 10 $σ$ and 5.7 $σ$, respectively. These results are consistent with the previous measurements by BESIII, LHCb and Belle, and the result of $Λ_{c}^{+}\to pη$ is the most precise to date.

hep-ex↗

Berry Curvature and Bulk-Boundary Correspondence from Transport Measurement for Photonic Chern Bands

Berry curvature is a fundamental element to characterize topological quantum physics, while a full measurement of Berry curvature in momentum space was not reported for topological states. Here we achieve two-dimensional Berry curvature reconstruction in a photonic quantum anomalous Hall system via Hall transport measurement of a momentum-resolved wave packet. Integrating measured Berry curvature over the two-dimensional Brillouin zone, we obtain Chern numbers corresponding to -1 and 0. Further, we identify bulk-boundary correspondence by measuring topology-linked chiral edge states at the boundary. The full topological characterization of photonic Chern bands from Berry curvature, Chern number, and edge transport measurements enables our photonic system to serve as a versatile platform for further in-depth study of novel topological physics.

quant-ph↗

Adaptive Parallelizable Algorithms for Interpolative Decompositions via Partially Pivoted LU

Interpolative and CUR decompositions involve "natural bases" of row and column subsets, or skeletons, of a given matrix that approximately span its row and column spaces. These low-rank decompositions preserve properties such as sparsity or non-negativity, and are easily interpretable in the context of the original data. For large-scale problems, randomized sketching to sample the row or column spaces with a random matrix can serve as an effective initial step in skeleton selection to reduce computational cost. A by now well-established approach has been to extract a randomized sketch, followed by column-pivoted QR CPQR) on the sketch matrix. This manuscript describes an alternative approach where CPQR is replaced by LU with partial pivoting (LUPP). While LUPP by itself is not rank-revealing, it is demonstrated that when used in a randomized setting, LUPP not only reveals the numerical rank, but also allows the estimation of the residual error as the factorization is built. The resulting algorithm is both adaptive and parallelizable, and attains much higher practical speed due to the lower communication requirements of LUPP over CPQR. The method has been implemented for both CPUs and GPUs, and the resulting software has been made publicly available.

math.NA↗

Search for $J/ψ$ weak decays containing $D$ meson

Using a sample of about 10 billion $J/ψ$ events with the BESIII detector, we search for the weak decays of $J/ψ\to \bar{D}^0π^0 + c.c.$, $J/ψ\to \bar{D}^0η+ c.c.$, $J/ψ\to \bar{D}^0ρ^0 + c.c.$, $J/ψ\to D^-π^+ + c.c.$, and $J/ψ\to D^-ρ^+ + c.c.$. Since no significant signal is observed, we set the upper limits of the branching fractions of these decays to be $\mathcal{B}(J/ψ\to \bar{D}^0π^0 + c.c.) < 4.7 \times 10^{-7}$, $\mathcal{B}(J/ψ\to \bar{D}^0η+ c.c.) < 6.8 \times 10^{-7}$, $\mathcal{B}(J/ψ\to \bar{D}^0ρ^0 + c.c.) < 5.2 \times 10^{-7}$, $\mathcal{B}(J/ψ\to D^-π^+ + c.c.) < 7.0 \times 10^{-8}$, and $\mathcal{B}(J/ψ\to D^-ρ^+ + c.c.) < 6.0 \times 10^{-7}$ at the 90\% confidence level.

hep-ex↗

Collaborative Visual Place Recognition

Visual place recognition (VPR) capabilities enable autonomous robots to navigate complex environments by discovering the environment's topology based on visual input. Most research efforts focus on enhancing the accuracy and robustness of single-robot VPR but often encounter issues such as occlusion due to individual viewpoints. Despite a number of research on multi-robot metric-based localization, there is a notable gap in research concerning more robust and efficient place-based localization with a multi-robot system. This work proposes collaborative VPR, where multiple robots share abstracted visual features to enhance place recognition capabilities. We also introduce a novel collaborative VPR framework based on similarity-regularized information fusion, reducing irrelevant noise while harnessing valuable data from collaborators. This framework seamlessly integrates with well-established single-robot VPR techniques and supports end-to-end training with a weakly-supervised contrastive loss. We conduct experiments in urban, rural, and indoor scenes, achieving a notable improvement over single-agent VPR in urban environments (~12\%), along with consistent enhancements in rural (~3\%) and indoor (~1\%) scenarios. Our work presents a promising solution to the pressing challenges of VPR, representing a substantial step towards safe and robust autonomous systems.

cs.RO↗