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Yichen Zhang

Publications and source records attributed to Yichen Zhang.

At least 91 records · Page 5Linked to original sources

Active Contact Engagement for Aerial Navigation in Unknown Environments with Glass

Autonomous aerial robots are increasingly being deployed in real-world scenarios, where transparent glass obstacles present significant challenges to reliable navigation. Researchers have investigated the use of non-contact sensors and passive contact-resilient aerial vehicle designs to detect glass surfaces, which are often limited in terms of robustness and efficiency. In this work, we propose a novel approach for robust autonomous aerial navigation in unknown environments with transparent glass obstacles, combining the strengths of both sensor-based and contact-based glass detection. The proposed system begins with the incremental detection and information maintenance about potential glass surfaces using visual sensor measurements. The vehicle then actively engages in touch actions with the visually detected potential glass surfaces using a pair of lightweight contact-sensing modules to confirm or invalidate their presence. Following this, the volumetric map is efficiently updated with the glass surface information and safe trajectories are replanned on the fly to circumvent the glass obstacles. We validate the proposed system through real-world experiments in various scenarios, demonstrating its effectiveness in enabling efficient and robust autonomous aerial navigation in complex real-world environments with glass obstacles.

cs.RO↗

Fully Integrated Vacuum-based Quantum Random Number Generator

Quantum random number generators play a crucial role in securing high-demand information contexts by producing true random numbers. Nevertheless, the large volume and high-cost limit their widespread use. Here, we propose a system on chip that fully leverages the advantages of different photonic integrated platforms, where the interference optical paths and photodiodes are integrated on a standard silicon process, while the laser source on-chip is realized on a III-V platform. Using micro-lens coupling package technology, which contributes to a topnotch coupling loss lower than 2dB, the components on different platforms are combined and packaged with the amplifier circuits in a 42mm* 24mm footprint in a butterfly form. This complete miniaturized and cost-effective entropy source enables outputting a vacuum noise signal with a 3dB bandwidth of over 500MHz. After sampling and post-processing, a random number generation rate of up to 6.57Gbps is achieved. The results show a feasible way of overcoming the laser integration problem with silicon-based integrated quantum photonics. Foreseeable, commercial applications on a large scale are significantly promoted.

physics.optics↗

Online Statistical Inference in Decision-Making with Matrix Context

The study of online decision-making problems that leverage contextual information has drawn notable attention due to their significant applications in fields ranging from healthcare to autonomous systems. In modern applications, contextual information can be rich and is often represented as a matrix. Moreover, while existing online decision algorithms mainly focus on reward maximization, less attention has been devoted to statistical inference. To address these gaps, in this work, we consider an online decision-making problem with a matrix context where the true model parameters have a low-rank structure. We propose a fully online procedure to conduct statistical inference with adaptively collected data. The low-rank structure of the model parameter and the adaptive nature of the data collection process make this difficult: standard low-rank estimators are biased and cannot be obtained in a sequential manner while existing inference approaches in sequential decision-making algorithms fail to account for the low-rankness and are also biased. To overcome these challenges, we introduce a new online debiasing procedure to simultaneously handle both sources of bias. Our inference framework encompasses both parameter inference and optimal policy value inference. In theory, we establish the asymptotic normality of the proposed online debiased estimators and prove the validity of the constructed confidence intervals for both inference tasks. Our inference results are built upon a newly developed low-rank stochastic gradient descent estimator and its convergence result, which are also of independent interest.

stat.ML↗

Distributed Tensor Principal Component Analysis with Data Heterogeneity

As tensors become widespread in modern data analysis, Tucker low-rank Principal Component Analysis (PCA) has become essential for dimensionality reduction and structural discovery in tensor datasets. Motivated by the common scenario where large-scale tensors are distributed across diverse geographic locations, this paper investigates tensor PCA within a distributed framework where direct data pooling is impractical. We offer a comprehensive analysis of three specific scenarios in distributed Tensor PCA: a homogeneous setting in which tensors at various locations are generated from a single noise-affected model; a heterogeneous setting where tensors at different locations come from distinct models but share some principal components, aiming to improve estimation across all locations; and a targeted heterogeneous setting, designed to boost estimation accuracy at a specific location with limited samples by utilizing transferred knowledge from other sites with ample data. We introduce novel estimation methods tailored to each scenario, establish statistical guarantees, and develop distributed inference techniques to construct confidence regions. Our theoretical findings demonstrate that these distributed methods achieve sharp rates of accuracy by efficiently aggregating shared information across different tensors, while maintaining reasonable communication costs. Empirical validation through simulations and real-world data applications highlights the advantages of our approaches, particularly in managing heterogeneous tensor data.

stat.ME↗

The SOFIA Massive (SOMA) Star Formation Survey. V. Clustered Protostars

We present $\sim8-40\,μ$m SOFIA-FORCAST images of seven regions of ``clustered" star formation as part of the SOFIA Massive (SOMA) Star Formation Survey. We identify a total of 34 protostar candidates and build their spectral energy distributions (SEDs). We fit these SEDs with a grid of radiative transfer models based on the Turbulent Core Accretion (TCA) theory to derive key protostellar properties, including initial core mass, $M_c$, clump environment mass surface density, $Σ_{\rm cl}$, and current protostellar mass, $m_*$. We also carry out empirical graybody (GB) estimation of $Σ_{\rm cl}$, which allows a case of restricted SED fitting within the TCA model grid. We also release version 2.0 of the open-source Python package \emph{sedcreator}, designed to automate the aperture photometry and SED building and fitting process for sources in clustered environments, where flux contamination from close neighbors typically complicates the process. Using these updated methods, SED fitting yields values of $M_c\sim30-200\:M_{\odot}$, $Σ_{\text{cl,SED}}\sim0.1-3\:{\rm{g\:cm}}^{-2}$, and $m_*\sim4-50\:M_{\odot}$. The graybody fitting yields smaller values of $Σ_{\text{cl,GB}}\lesssim1\:{\rm{g\:cm}}^{-2}$. From these results, we do not find evidence for a critical $Σ_{\rm{cl}}$ needed to form massive ($\gtrsim 8\:M_\odot$) stars. However, we do find tentative evidence for a dearth of the most massive ($m_*\gtrsim30\:M_\odot$) protostars in the clustered regions suggesting a potential impact of environment on the stellar initial mass function.

astro-ph.GA↗

High-rate continuous-variable quantum key distribution over 100 km fiber with composable security

Quantum key distribution (QKD), providing a way to generate secret keys with information-theoretic security,is arguably one of the most significant achievements in quantum information. The continuous-variable QKD (CV-QKD) offers the potential advantage of achieving a higher secret key rate (SKR) within a metro area, as well as being compatible with the mature telecom industry. However, the SKR and transmission distance of state-of-the-art CV-QKD systems are currently limited. Here, based on the novelly proposed orthogonal-frequency-division-multiplexing (OFDM) CV-QKD protocol, we demonstrate for the first time a high-rate multi-carrier (MC) CV-QKD with a 10 GHz symbol rate that chieves Gbps SKR within 10km and Mbps SKR over 100 km in the finite-size regime under composable security against collective attacks. The record-breaking results are achieved by suitable optimization of subcarrier number and modulation variance, well-controlled excess noise induced by both OFDM mechanism and efficient DSP scheme, and high-performance post-processing capacity realized by heterogeneous computing scheme. The composable finite-size SKR reaches 1779.45 Mbps@5km, 1025.49 Mbps@10km, 370.50 Mbps@25km, 99.93 Mbps@50km, 25.70 Mbps@75km,and 2.25 Mbps@100km, which improves the SKR by two orders of magnitude and quintuples the maximal transmission distance compared to most recently reported CV-QKD results [Nature Communications, 13, 4740 (2022)]. Interestingly, it is experimentally verified that the SKR of the proposed MC CV-QKD can approach five times larger than that of the single-carrier CV-QKD with the same symbol rate without additional hardware costs. Our work constitutes a critical step towards future high-speed quantum metropolitan and access networks.

quant-ph↗

High-rate discrete-modulated continuous-variable quantum key distribution with composable security

Continuous-variable quantum key distribution holds the potential to generate high secret key rates, making it a prime candidate for high-rate metropolitan quantum network applications. However, despite these promising opportunities, the realization of high-rate continuous-variable quantum key distribution systems with composable security remains an elusive goal. Here, we report a discrete-modulated continuous-variable quantum key distribution system with a composable secret key rate of 18.93 Mbps against collective attacks over a 25 km fiber channel. This record breaking rate is achieved through the probability shaped 16QAM-modulated protocol, which employs semidefinite programming to ensure its composable security. Furthermore, we have employed a fully digital and precise quantum signal processing technique to reduce excess noise to extremely low levels, thereby facilitating efficient broadband system operation. While ensuring low complexity and cost,our system achieves a performance advantage of over an order of magnitude compared to previous continuous-variable quantum key distribution systems, providing a promising solution for future deployment of quantum key distribution.

quant-ph↗

High-rate discrete-modulated continuous-variable quantum key distribution with composable security

Continuous-variable quantum key distribution holds the potential to generate high secret key rates, making it a prime candidate for high-rate metropolitan quantum network applications. However, despite these promising opportunities, the realization of high-rate continuous-variable quantum key distribution systems with composable security remains an elusive goal. Here, we report a discrete-modulated continuous-variable quantum key distribution system with a composable secret key rate of 18.93 Mbps against collective attacks over a 25 km fiber channel. This record-breaking rate is achieved through the probability shaped 16QAM-modulated protocol, which employs semidefinite programming to ensure its composable security. Furthermore, we have employed a fully digital and precise quantum signal processing technique to reduce excess noise to extremely low levels, thereby facilitating efficient broadband system operation. While ensuring low complexity and cost, our system achieves a performance advantage of over an order of magnitude compared to previous continuous-variable quantum key distribution systems, providing a promising solution for future deployment of quantum key distribution.

quant-ph↗

Online Estimation and Inference for Robust Policy Evaluation in Reinforcement Learning

Reinforcement learning has emerged as one of the prominent topics attracting attention in modern statistical learning, with policy evaluation being a key component. Unlike the traditional machine learning literature on this topic, our work emphasizes statistical inference for the model parameters and value functions of reinforcement learning algorithms. While most existing analyses assume random rewards to follow standard distributions, we embrace the concept of robust statistics in reinforcement learning by simultaneously addressing issues of outlier contamination and heavy-tailed rewards within a unified framework. In this paper, we develop a fully online robust policy evaluation procedure, and establish the Bahadur-type representation of our estimator. Furthermore, we develop an online procedure to efficiently conduct statistical inference based on the asymptotic distribution. This paper connects robust statistics and statistical inference in reinforcement learning, offering a more versatile and reliable approach to online policy evaluation. Finally, we validate the efficacy of our algorithm through numerical experiments conducted in simulations and real-world reinforcement learning experiments.

stat.ML↗

ALMA observations of massive clouds in the central molecular zone: slim filaments tracing parsec-scale shocks

The central molecular zone (CMZ) of our Galaxy exhibits widespread emission from SiO and various complex organic molecules (COMs), yet the exact origin of such emission is uncertain. Here we report the discovery of a unique class of long ($>$0.5 pc) and narrow ($<$0.03 pc) filaments in the emission of SiO 5$-$4 and eight additional molecular lines, including several COMs, in our ALMA 1.3 mm spectral line observations toward two massive molecular clouds in the CMZ, which we name as slim filaments. However, these filaments are not detected in the 1.3 mm continuum at the 5$σ$ level. Their line-of-sight velocities are coherent and inconsistent with being outflows. The column densities and relative abundances of the detected molecules are statistically similar to those in protostellar outflows but different from those in dense cores within the same clouds. Turbulent pressure in these filaments dominates over self gravity and leads to hydrostatic inequilibrium, indicating that they are a different class of objects than the dense gas filaments in dynamical equilibrium ubiquitously found in nearby molecular clouds. We argue that these newly detected slim filaments are associated with parsec-scale shocks, likely arising from dynamic interactions between shock waves and molecular clouds. The dissipation of the slim filaments may replenish SiO and COMs in the interstellar medium and lead to their widespread emission in the CMZ.

astro-ph.GA↗

CascadeV: An Implementation of Wurstchen Architecture for Video Generation

Recently, with the tremendous success of diffusion models in the field of text-to-image (T2I) generation, increasing attention has been directed toward their potential in text-to-video (T2V) applications. However, the computational demands of diffusion models pose significant challenges, particularly in generating high-resolution videos with high frame rates. In this paper, we propose CascadeV, a cascaded latent diffusion model (LDM), that is capable of producing state-of-the-art 2K resolution videos. Experiments demonstrate that our cascaded model achieves a higher compression ratio, substantially reducing the computational challenges associated with high-quality video generation. We also implement a spatiotemporal alternating grid 3D attention mechanism, which effectively integrates spatial and temporal information, ensuring superior consistency across the generated video frames. Furthermore, our model can be cascaded with existing T2V models, theoretically enabling a 4$\times$ increase in resolution or frames per second without any fine-tuning. Our code is available at https://github.com/bytedance/CascadeV.

cs.CV↗

ALMA 0.1 pc View of Molecular Clouds Associated with High-Mass Protostellar Systems in the Small Magellanic Cloud: Are Low-Metallicity Clouds Filamentary or Not?

Filamentary molecular clouds are an essential intermediate stage in the star formation process. To test whether these structures are universal throughout cosmic star formation history, it is crucial to study low-metallicity environments within the Local Group. We present an ALMA analysis of the ALMA archival data at the spatial resolution of $\sim$0.1 pc for 17 massive young stellar objects (YSOs) in the Small Magellanic Cloud (SMC; Z $\sim$0.2 $Z_{\odot}$). This sample represents approximately 30% of the YSOs confirmed by Spitzer spectroscopy. Early ALMA studies of the SMC have shown that the CO emission line traces an H$_2$ number density of $\gtrsim$10$^4$ cm$^{-3}$, an order of magnitude higher than in the typical Galactic environments. Using the CO($J$ = 3-2) data, we investigated the spatial and velocity distribution of molecular clouds. Our analysis shows that about 60% of the clouds have steep radial profiles from the spine of the elongated structures, while the remaining clouds have a smooth distribution and are characterized by lower brightness temperatures. We categorized the former as filaments and the latter as non-filaments. Some of the filamentary clouds are associated with YSOs with outflows and exhibit higher temperatures, likely reflecting their formation conditions, suggesting that these clouds are younger than non-filamentary ones. This indicates that even if filaments form during star formation, their steep structures may become less prominent and transit to a lower-temperature state. Such transitions in structure and temperature have not been reported in metal-rich regions, highlighting a key behavior for characterizing the evolution of the interstellar medium and star formation in low-metallicity environments.

astro-ph.GA↗

Journey into Automation: Image-Derived Pavement Texture Extraction and Evaluation

Mean texture depth (MTD) is pivotal in assessing the skid resistance of asphalt pavements and ensuring road safety. This study focuses on developing an automated system for extracting texture features and evaluating MTD based on pavement images. The contributions of this work are threefold: firstly, it proposes an economical method to acquire three-dimensional (3D) pavement texture data; secondly, it enhances 3D image processing techniques and formulates features that represent various aspects of texture; thirdly, it establishes multivariate prediction models that link these features with MTD values. Validation results demonstrate that the Gradient Boosting Tree (GBT) model achieves remarkable prediction stability and accuracy (R2 = 0.9858), and field tests indicate the superiority of the proposed method over other techniques, with relative errors below 10%. This method offers a comprehensive end-to-end solution for pavement quality evaluation, from images input to MTD predictions output.

cs.CV↗

The JWST-NIRCam View of Sagittarius C. II. Evidence for Magnetically Dominated HII Regions in the CMZ

We present JWST-NIRCam narrow-band, 4.05 $μ$m Brackett-$α$ images of the Sgr C HII region, located in the Central Molecular Zone (CMZ) of the Galaxy. Unlike any HII region in the Solar vicinity, the Sgr C plasma is dominated by filamentary structure in both Brackett-$α$ and the radio continuum. Some bright filaments, which form a fractured arc with a radius of about 1.85 pc centered on the Sgr C star-forming molecular clump, likely trace ionization fronts. The brightest filaments form a `$π$-shaped' structure in the center of the HII region. Fainter filaments radiate away from the surface of the Sgr C molecular cloud. The filaments are emitting optically thin free-free emission, as revealed by spectral index measurements from 1.28 GHz (MeerKAT) to 97 GHz (ALMA). But, the negative in-band 1 to 2 GHz spectral index in the MeerKAT data alone reveals the presence of a non-thermal component across the entire Sgr C HII region. We argue that the plasma flow in Sgr C is controlled by magnetic fields, which confine the plasma to rope-like filaments or sheets. This results in the measured non-thermal component of low-frequency radio emission plasma, as well as a plasma $β$ (thermal pressure divided by magnetic pressure) below 1, even in the densest regions. We speculate that all mature HII regions in the CMZ, and galactic nuclei in general, evolve in a magnetically dominated, low plasma $β$ regime.

astro-ph.GA↗

The SOFIA Massive (SOMA) Star Formation Q-band follow-up I. Carbon-chain chemistry of intermediate-mass protostars

Evidence for similar chemical characteristics around low- and high-mass protostars has been found: in particular, a variety of carbon-chain species and complex organic molecules (COMs) are formed around them. On the other hand, the chemical compositions around intermediate-mass (IM; $2 M_{\odot} < m_* <8 M_{\odot}$) protostars have not been studied with large samples. In particular, it is unclear the extent to which carbon-chain species are formed around them. We aim to obtain the chemical compositions, particularly focusing on carbon-chain species, towards a sample of IM protostars. We have conducted Q-band (31.5-50 GHz) line survey observations towards eleven mainly intermediate-mass protostars with the Yebes 40 m radio telescope. The target protostars were selected from a sub-sample of the source list of the SOFIA Massive (SOMA) Star Formation project. Nine carbon-chain species (HC$_3$N, HC$_5$N, C$_3$H, C$_4$H, $linear-$H$_2$CCC, $cyclic-$C$_3$H$_2$, CCS, C$_3$S, and CH$_3$CCH), three COMs (CH$_3$OH, CH$_3$CHO, and CH$_3$CN), H$_2$CCO, HNCO, and four simple sulfur (S)-bearing species ($^{13}$CS, C$^{34}$S, HCS$^+$, H$_2$CS) have been detected. The rotational temperatures of HC$_5$N are derived to be $\sim20-30$ K in three IM protostars and they are very similar compared to those around low- and high-mass protostars. These results indicate that carbon-chain molecules are formed in lukewarm ($\sim20-30$ K) gas around the IM protostars by the Warm Carbon-Chain Chemistry (WCCC) process. Carbon-chain formation occurs ubiquitously in the warm gas around protostars across a wide range of stellar masses. Carbon-chain molecules and COMs coexist around most of the target IM protostars, which is similar to the situation in low- and high-mass protostars. The chemical characteristics around protostars are common in the low-, intermediate- and high-mass regimes.

astro-ph.GA↗

The ALMA-QUARKS Survey: Fibers' role in star formation unveiled in an intermediate-mass protocluster region of the Vela D cloud

In this paper, we present a detailed analysis of the IRS 17 filament within the intermediate-mass protocluster IRAS 08448-4343 (of $\sim\,10^3\,\rm L_{\odot}$), using ALMA data from the ATOMS 3-mm and QUARKS 1.3-mm surveys. The IRS 17 filament, which spans $\sim$54000 au ($0.26\,\rm pc$) in length and $\sim$4000 au ($0.02\,\rm pc$) in width, exhibits a complex, multi-component velocity field, and harbours hierarchical substructures. These substructures include three bundles of seven velocity-coherent fibers, and 29 dense ($n\sim 10^8\,\rm cm^{-3}$) condensations. The fibers have a median length of $\sim 4500\,\rm au$ and a median width of $\sim 1400\,\rm au$. Among these fibers, four are identified as ``fertile", each hosting at least three dense condensations, which are regarded as the ``seeds" of star formation. While the detected cores are randomly spaced within the IRS\,17 filament based on the 3-mm dust continuum image, periodic spacing ($\sim1600\,\rm au$) of condensations is observed in the fertile fibers according to the 1.3-mm dust map, consistent with the predictions of linear isothermal cylinder fragmentation models. These findings underscore the crucial role of fibers in star formation and suggest a hierarchical fragmentation process that extends from the filament to the fibers, and ultimately, to the smallest-scale condensations.

astro-ph.GA↗

The JWST-NIRCam View of Sagittarius C. I. Massive Star Formation and Protostellar Outflows

We present James Webb Space Telescope (JWST)-NIRCam observations of the massive star-forming molecular cloud Sagittarius C (Sgr C) in the Central Molecular Zone (CMZ). In conjunction with ancillary mid-IR and far-IR data, we characterize the two most massive protostars in Sgr C via spectral energy distribution (SED) fitting, estimating that they each have current masses of $m_* \sim 20\:M_\odot$ and surrounding envelope masses of $\sim 100\:M_\odot$. We report a census of lower-mass protostars in Sgr C via a search for infrared counterparts to mm continuum dust cores found with ALMA. We identify 88 molecular hydrogen outflow knot candidates originating from outflows from protostars in Sgr C, the first such unambiguous detections in the infrared in the CMZ. About a quarter of these are associated with flows from the two massive protostars in Sgr C; these extend for over 1 pc and are associated with outflows detected in ALMA SiO line data. An additional $\sim 40$ features likely trace shocks in outflows powered by lower-mass protostars throughout the cloud. We report the discovery of a new star-forming region hosting two prominent bow shocks and several other line-emitting features driven by at least two protostars. We infer that one of these is forming a high-mass star given an SED-derived mass of $m_* \sim 9\:M_\odot$ and associated massive ($\sim 90\:M_\odot$) mm core and water maser. Finally, we identify a population of miscellaneous Molecular Hydrogen Objects (MHOs) that do not appear to be associated with protostellar outflows.

astro-ph.GA↗

Persistent flat band splitting and strong selective band renormalization in a kagome magnet thin film

Magnetic kagome materials provide a fascinating playground for exploring the interplay of magnetism, correlation and topology. Many magnetic kagome systems have been reported including the binary FemXn (X=Sn, Ge; m:n = 3:1, 3:2, 1:1) family and the rare earth RMn6Sn6 (R = rare earth) family, where their kagome flat bands are calculated to be near the Fermi level in the paramagnetic phase. While partially filling a kagome flat band is predicted to give rise to a Stoner-type ferromagnetism, experimental visualization of the magnetic splitting across the ordering temperature has not been reported for any of these systems due to the high ordering temperatures, hence leaving the nature of magnetism in kagome magnets an open question. Here, we probe the electronic structure with angle-resolved photoemission spectroscopy in a kagome magnet thin film FeSn synthesized using molecular beam epitaxy. We identify the exchange-split kagome flat bands, whose splitting persists above the magnetic ordering temperature, indicative of a local moment picture. Such local moments in the presence of the topological flat band are consistent with the compact molecular orbitals predicted in theory. We further observe a large spin-orbital selective band renormalization in the Fe d_xy+d_(x^2-y^2 ) spin majority channel reminiscent of the orbital selective correlation effects in the iron-based superconductors. Our discovery of the coexistence of local moments with topological flat bands in a kagome system echoes similar findings in magic-angle twisted bilayer graphene, and provides a basis for theoretical effort towards modeling correlation effects in magnetic flat band systems.

cond-mat.mes-hall↗