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Yichen Zhang

Publications and source records attributed to Yichen Zhang.

At least 127 records · Page 7Linked to original sources
arXiv2024

Continuous-variable quantum key distribution over 28.6 km fiber with an integrated silicon photonic receiver chip

Quantum key distribution, which ensures information-theoretically secret key generation, is currently advancing through photonic integration to achieve high performance, cost reduction and compact size, thereby facilitating the large-scale deployment. Continuous-variable quantum key distribution is an attractive approach for photonic integrations due to its compatibility with off-the-shelf optical communication devices. However, its chip-based systems have encountered significant limitations primarily related to the shot-noise-limited receiver design, which demands low noise, wide bandwidth, high clearance and well stability. Here, we report the implementation of a real local oscillator continuous-variable quantum key distribution system with an integrated silicon photonic receiver chip. Thanks to the well-designed chip-based homodyne detectors with a bandwidth up to 1.5 GHz and a clearance up to 7.42 dB, the transmission distance of the system has been extended to 28.6 km, achieving a secret key generation rate of Mbps level. This technological advancement enables the quantum key distribution systems with photonic integrated receivers to achieve the coverage in both access network scenarios and short-distance metropolitan interconnections, paving the way for the development of the next-generation quantum key distribution networks on a large scale.

quant-ph↗
arXiv2024

Acceleration of stochastic gradient descent with momentum by averaging: finite-sample rates and asymptotic normality

Stochastic gradient descent with momentum (SGDM) has been widely used in many machine learning and statistical applications. Despite the observed empirical benefits of SGDM over traditional SGD, the theoretical understanding of the role of momentum for different learning rates in the optimization process remains widely open. We analyze the finite-sample convergence rate of SGDM under the strongly convex settings and show that, with a large batch size, the mini-batch SGDM converges faster than the mini-batch SGD to a neighborhood of the optimal value. Additionally, our findings, supported by theoretical analysis and numerical experiments, indicate that SGDM permits broader choices of learning rates. Furthermore, we analyze the Polyak-averaging version of the SGDM estimator, establish its asymptotic normality, and justify its asymptotic equivalence to the averaged SGD. The asymptotic distribution of the averaged SGDM enables uncertainty quantification of the algorithm output and statistical inference of the model parameters.

cs.LG↗
arXiv2024

Practical No-Switching Continuous-Variable Quantum Key Distribution with Biased Quadrature Detection

Continuous-variable quantum key distribution protocol using coherent states and heterodyne detection, called No-Switching protocol, is widely used in practical systems due to the simple experimental setup without basis switching and easy assessment to phase information. The security of an ideal No-Switching protocol has been proved against general attacks in finite-size regime and composable security framework, whose heterodyne detector consists of a beam splitter with transmittance of $50\%$ and two ideal homodyne detectors. However, the transmittance of a beam splitter is inaccurate and the two detectors always have different quantum efficiency and electronic noise, which introduce asymmetry into the heterodyne detection, and further lead to the mismatch between the ideal protocol and practical systems, thereby overestimating the secret key rate and resulting in a practical security loophole. In this paper, we close this loophole by proposing a modified No-Switching protocol with biased quadrature detection, where the asymmetry of the heterodyne detection is modeled to match the practical systems, and the security of the protocol is analyzed in asymptotic and finite-size regimes. Further, an optimization strategy is proposed to achieve the optimal secret key rate by adjusting the transmittance of the beam splitter. Simulation results show the necessity of considering the asymmetry in heterodyne detection and the effectiveness of the optimization, which provides a promising way to realize a practical secure and high-performance No-Switching system.

quant-ph↗
arXiv2023

The Security Analysis of Continuous-Variable Quantum Key Distribution under Limited Eavesdropping with Practical Fiber

Research on optimal eavesdropping models under practical conditions will help to evaluate realistic risk when employing quantum key distribution (QKD) system for secure information transmission. Intuitively, fiber loss will lead to the optical energy leaking to the environment, rather than harvested by the eavesdropper, which also limits the eavesdropping ability while improving the QKD system performance in practical use. However, defining the optimal eavesdropping model in the presence of lossy fiber is difficult because the channel is beyond the control of legitimate partners and the leaked signal is undetectable. Here we investigate how the fiber loss influences the eavesdropping ability based on a teleportation-based collective attack model which requires two distant stations and a shared entanglement source. We find that if the distributed entanglement is limited due to the practical loss, the optimal attack occurs when the two teleportation stations are merged to one and placed close to the transmitter site, which performs similar to the entangling-cloning attack but with a reduced wiretapping ratio. Assuming Eve uses the best available hollow-core fiber, the secret key rate in the practical environment can be 20%~40% higher than that under ideal eavesdropping. While if the entanglement distillation technology is mature enough to provide high quality of distributed entanglement, the two teleportation stations should be distantly separated for better eavesdropping performance, where the eavesdropping can even approach the optimal collective attack. Under the current level of entanglement purification technology, the unavoidable fiber loss can still greatly limit the eavesdropping ability as well as enhance the secret key rate and transmission distance of the realistic system, which promotes the development of QKD systems in practical application scenarios.

quant-ph↗
arXiv2023

Observation of Flat Bands and Dirac Cones in a Pyrochlore Lattice Superconductor

Emergent phases often appear when the electronic kinetic energy is comparable to the Coulomb interactions. One approach to seek material systems as hosts of such emergent phases is to realize localization of electronic wavefunctions due to the geometric frustration inherent in the crystal structure, resulting in flat electronic bands. Recently, such efforts have found a wide range of exotic phases in the two-dimensional kagome lattice, including magnetic order, time-reversal symmetry breaking charge order, nematicity, and superconductivity. However, the interlayer coupling of the kagome layers disrupts the destructive interference needed to completely quench the kinetic energy. Here we demonstrate that an interwoven kagome network-a pyrochlore lattice-can host a three dimensional (3D) localization of electron wavefunctions. Meanwhile, the nonsymmorphic symmetry of the pyrochlore lattice guarantees all band crossings at the Brillouin zone X point to be 3D gapless Dirac points, which was predicted theoretically but never yet observed experimentally. Through a combination of angle-resolved photoemission spectroscopy, fundamental lattice model and density functional theory calculations, we investigate the novel electronic structure of a Laves phase superconductor with a pyrochlore sublattice, CeRu$_2$. We observe flat bands originating from both the Ce 4$f$ orbitals as well as from the 3D destructive interference of the Ru 4$d$ orbitals. We further observe the nonsymmorphic symmetry-protected 3D gapless Dirac cones at the X point. Our work establishes the pyrochlore structure as a promising lattice platform to realize and tune novel emergent phases intertwining topology and many-body interactions.

cond-mat.str-el↗
arXiv2023

Online Statistical Inference for Stochastic Optimization via Kiefer-Wolfowitz Methods

This paper investigates the problem of online statistical inference of model parameters in stochastic optimization problems via the Kiefer-Wolfowitz algorithm with random search directions. We first present the asymptotic distribution for the Polyak-Ruppert-averaging type Kiefer-Wolfowitz (AKW) estimators, whose asymptotic covariance matrices depend on the distribution of search directions and the function-value query complexity. The distributional result reflects the trade-off between statistical efficiency and function query complexity. We further analyze the choice of random search directions to minimize certain summary statistics of the asymptotic covariance matrix. Based on the asymptotic distribution, we conduct online statistical inference by providing two construction procedures of valid confidence intervals.

math.ST↗
arXiv2023

An Ultra-fast Quantum Random Number Generation Scheme Based on Laser Phase Noise

Based on the intrinsic random property of quantum mechanics, quantum random number generators allow for access of truly unpredictable random sequence and are now heading towards high performance and small miniaturization, among which a popular scheme is based on the laser phase noise. However, this scheme is generally limited in speed and implementation complexity, especially for chip integration. In this work, a general physical model based on wiener process for such schemes is introduced, which provides an approach to clearly explain the limitation on the generation rate and comprehensively optimize the system performance. We present an insight to exploit the potential bandwidth of the quantum entropy source that contains plentiful quantum randomness with a simple spectral filtering method and experimentally boost the bandwidth of the corresponding quantum entropy source to 20 GHz, based on which an ultra-fast generation rate of 218 Gbps is demonstrated, setting a new record for laser phase noise based schemes by one order of magnitude. Our proposal significantly enhances the ceiling speed of such schemes without requiring extra complex hardware, thus effectively benefits the corresponding chip integration with high performance and low implementation cost, which paves the way for its large-scale applications.

quant-ph↗
arXiv2023

Manifold-Aware Self-Training for Unsupervised Domain Adaptation on Regressing 6D Object Pose

Domain gap between synthetic and real data in visual regression (e.g. 6D pose estimation) is bridged in this paper via global feature alignment and local refinement on the coarse classification of discretized anchor classes in target space, which imposes a piece-wise target manifold regularization into domain-invariant representation learning. Specifically, our method incorporates an explicit self-supervised manifold regularization, revealing consistent cumulative target dependency across domains, to a self-training scheme (e.g. the popular Self-Paced Self-Training) to encourage more discriminative transferable representations of regression tasks. Moreover, learning unified implicit neural functions to estimate relative direction and distance of targets to their nearest class bins aims to refine target classification predictions, which can gain robust performance against inconsistent feature scaling sensitive to UDA regressors. Experiment results on three public benchmarks of the challenging 6D pose estimation task can verify the effectiveness of our method, consistently achieving superior performance to the state-of-the-art for UDA on 6D pose estimation.

cs.CV↗
arXiv2023

Astrochemical Diagnostics of the Isolated Massive Protostar G28.20-0.05

We study the astrochemical diagnostics of the isolated massive protostar G28.20-0.05. We analyze data from ALMA 1.3~mm observations with resolution of 0.2 arcsec ($\sim$1,000 au). We detect emission from a wealth of species, including oxygen-bearing (e.g., $\rm{H_2CO}$, $\rm{CH_3OH}$, $\rm{CH_3OCH_3}$), sulfur-bearing (SO$_2$, H$_2$S) and nitrogen-bearing (e.g., HNCO, NH$_2$CHO, C$_2$H$_3$CN, C$_2$H$_5$CN) molecules. We discuss their spatial distributions, physical conditions, correlation between different species and possible chemical origins. In the central region near the protostar, we identify three hot molecular cores (HMCs). HMC1 is part of a mm continuum ring-like structure, is closest in projection to the protostar, has the highest temperature of $\sim300\:$K, and shows the most line-rich spectra. HMC2 is on the other side of the ring, has a temperature of $\sim250\:$K, and is of intermediate chemical complexity. HMC3 is further away, $\sim3,000\:$au in projection, cooler ($\sim70\:$K) and is the least line-rich. The three HMCs have similar mass surface densities ($\sim10\:{\rm{g\:cm}}^{-2}$), number densities ($n_{\rm H}\sim10^9\:{\rm{cm}}^{-3}$) and masses of a few $M_\odot$. The total gas mass in the cores and in the region out to $3,000\:$au is $\sim 25\:M_\odot$, which is comparable to that of the central protostar. Based on spatial distributions of peak line intensities as a function of excitation energy, we infer that the HMCs are externally heated by the protostar. We estimate column densities and abundances of the detected species and discuss the implications for hot core astrochemistry.

astro-ph.GA↗
arXiv2023

Non-Fermi liquid behavior in a correlated flatband pyrochlore lattice

Electronic correlation effects are manifested in quantum materials when either the onsite Coulomb repulsion is large or the electron kinetic energy is small. The former is the dominant effect in the cuprate superconductors or heavy fermion systems while the latter in twisted bilayer graphene or geometrically frustrated metals. However, the simultaneous cooperation of both effects in the same quantum material--the design principle to produce a correlated topological flat bands pinned at the Fermi level--remains rare. Here, using angle-resolved photoemission spectroscopy, we report the observation of a flat band at the Fermi level in a 3$d$ pyrochlore metal CuV$_2$S$_4$. From a combination of first-principles calculations and slave-spin calculations, we understand the origin of this band to be a destructive quantum-interference effect associated with the V pyrochlore sublattice and further renormalization to the Fermi level by electron interactions in the partially filled V $t_{2g}$ orbitals. As a result, we find transport behavior that indicates a deviation from Fermi-liquid behavior as well as a large Sommerfeld coefficient. Our work demonstrates the pathway into correlated topology by constructing and pinning correlated flat bands near the Fermi level out of a pure $d$-electron system by the combined cooperation of local Coulomb interactions and geometric frustration in a pyrochlore lattice system.

cond-mat.str-el↗
arXiv2023

Statistical Inference for Model Parameters in Stochastic Gradient Descent

The stochastic gradient descent (SGD) algorithm has been widely used in statistical estimation for large-scale data due to its computational and memory efficiency. While most existing works focus on the convergence of the objective function or the error of the obtained solution, we investigate the problem of statistical inference of true model parameters based on SGD when the population loss function is strongly convex and satisfies certain smoothness conditions. Our main contributions are two-fold. First, in the fixed dimension setup, we propose two consistent estimators of the asymptotic covariance of the average iterate from SGD: (1) a plug-in estimator, and (2) a batch-means estimator, which is computationally more efficient and only uses the iterates from SGD. Both proposed estimators allow us to construct asymptotically exact confidence intervals and hypothesis tests. Second, for high-dimensional linear regression, using a variant of the SGD algorithm, we construct a debiased estimator of each regression coefficient that is asymptotically normal. This gives a one-pass algorithm for computing both the sparse regression coefficients and confidence intervals, which is computationally attractive and applicable to online data.

stat.ML↗
arXiv2023

Observer-based Leader-following Consensus for Positive Multi-agent Systems Over Time-varying Graphs

This paper addresses the leader-following consensus problem for discrete-time positive multi-agent systems over time-varying graphs. We assume that the followers may have mutually different positive dynamics which can also be different from the leader. Compared with most existing positive consensus works for homogeneous multi-agent systems, the formulated problem is more general and challenging due to the interplay between the positivity requirement and high-order heterogeneous dynamics. To solve the problem, we present an extended version of existing observer-based design for positive multi-agent systems. By virtue of the common quadratic Lyapunov function technique, we show the followers will maintain their state variables in the positive orthant and finally achieve an output consensus specified by the leader. A numerical example is used to verify the efficacy of our algorithms.

eess.SY↗
arXiv2023

Disk Wind Feedback from High-mass Protostars. IV. Shock-Ionized Jets

Massive protostars launch accretion-powered, magnetically-collimated outflows, which play crucial roles in the dynamics and diagnostics of the star formation process. Here we calculate the shock heating and resulting free-free radio emission in numerical models of outflows of massive star formation within the framework of the Turbulent Core Accretion model. We post-process 3D magneto-hydrodynamic simulation snapshots of a protostellar disk wind interacts with an infalling core envelope, and calculate shock temperatures, ionization fractions, and radio free-free emission. We find heating up to ~10^7 K and near complete ionization in shocks at the interface between the outflow cavity and infalling envelope. However, line-of-sight averaged ionization fractions peak around ~10%, in agreement with values reported from observations of massive protostar G35.20-0.74N. By calculating radio continuum fluxes and spectra, we compare our models with observed samples of massive protostars. We find our fiducial models produce radio luminosities similar to those seen from low and intermediate-mass protostars that are thought to be powered by shock ionization. Comparing to more massive protostars, we find our model radio luminosities are ~10 to 100 times less luminous. We discuss how this apparent discrepancy either reflects aspects of our modeling related to the treatment of cooling of the post-shock gas or a dominant contribution in the observed systems from photoionization. Finally, our models exhibit 10-year radio flux variability of ~5%, especially in the inner 1000 au region, comparable to observed levels in some hyper-compact HII regions.

astro-ph.GA↗
arXiv2023

Prototypical Cross-domain Knowledge Transfer for Cervical Dysplasia Visual Inspection

Early detection of dysplasia of the cervix is critical for cervical cancer treatment. However, automatic cervical dysplasia diagnosis via visual inspection, which is more appropriate in low-resource settings, remains a challenging problem. Though promising results have been obtained by recent deep learning models, their performance is significantly hindered by the limited scale of the available cervix datasets. Distinct from previous methods that learn from a single dataset, we propose to leverage cross-domain cervical images that were collected in different but related clinical studies to improve the model's performance on the targeted cervix dataset. To robustly learn the transferable information across datasets, we propose a novel prototype-based knowledge filtering method to estimate the transferability of cross-domain samples. We further optimize the shared feature space by aligning the cross-domain image representations simultaneously on domain level with early alignment and class level with supervised contrastive learning, which endows model training and knowledge transfer with stronger robustness. The empirical results on three real-world benchmark cervical image datasets show that our proposed method outperforms the state-of-the-art cervical dysplasia visual inspection by an absolute improvement of 4.7% in top-1 accuracy, 7.0% in precision, 1.4% in recall, 4.6% in F1 score, and 0.05 in ROC-AUC.

cs.CV↗
arXiv2023

An ALMA Glimpse of Dense Molecular Filaments Associated with High-mass Protostellar Systems in the Large Magellanic Cloud

Recent millimeter/sub-millimeter facilities have revealed the physical properties of filamentary molecular clouds in relation to high-mass star formation. A uniform survey of the nearest, face-on star-forming galaxy, the Large Magellanic Cloud (LMC), complements the Galactic knowledge. We present ALMA survey data with a spatial resolution of $\sim$0.1 pc in the 0.87 mm continuum and HCO$^{+}$(4-3) emission toward 30 protostellar objects with luminosities of 10$^4$-10$^{5.5}$ $L_{\odot}$ in the LMC. The spatial distributions of the HCO$^{+}$(4-3) line and thermal dust emission are well correlated, indicating that the line effectively traces dense, filamentary gas with an H$_2$ volume density of $\gtrsim$10$^5$ cm$^{-3}$ and a line mass of $\sim$10$^3$-10$^{4}$ $M_{\odot}$ pc$^{-1}$. Furthermore, we obtain an increase in the velocity linewidths of filamentary clouds, which follows a power-law dependence on their H$_2$ column densities with an exponent of $\sim$0.5. This trend is consistent with observations toward filamentary clouds in nearby star-forming regions withiin $ \lesssim$1 kpc from us and suggests enhanced internal turbulence within the filaments owing to surrounding gas accretion. Among the 30 sources, we find that 14 are associated with hub-filamentary structures, and these complex structures predominantly appear in protostellar luminosities exceeding $\sim$5 $\times$10$^4$ $L_{\odot}$. The hub-filament systems tend to appear in the latest stages of their natal cloud evolution, often linked to prominent H$\;${\sc ii} regions and numerous stellar clusters. Our preliminary statistics suggest that the massive filaments accompanied by hub-type complex features may be a necessary intermediate product in forming extremely luminous high-mass stellar systems capable of ultimately dispersing the parent cloud.

astro-ph.GA↗
arXiv2023

Quantum hacking against discrete-modulated continuous-variable quantum key distribution using modified local oscillator intensity attack with random fluctuations

The local oscillator in practical continuous-variable quantum key distribution system fluctuates at any time during the key distribution process, which may open security loopholes for the eavesdropper to hide her eavesdropping behaviors. Based on this, we investigate a more stealthy quantum attack where the eavesdroppers simulates random fluctuations of local oscillator intensity in a practical discrete-modulated continuous-variable quantum key distribution system. Theoretical simulations show that both communicating parties will misestimate channel parameters and overestimate the secret key rate due to the modified attack model, even though they have monitored the mean local oscillator intensity and shot-noise as commonly used. Specifically, the eavesdropper's manipulation of random fluctuations in LO intensity disturbs the parameter estimation in realistic discrete-modulated continuous-variable quantum key distribution system, where the experimental parameters are always used for constraints of the semidefinite program modeling. The modified attack introduced by random fluctuations of local oscillator can only be eliminated by monitoring the local oscillator intensity in real time which places a higher demand on the accuracy of monitoring technology. Moreover, similar quantum hacking will also occur in practical local local oscillator system by manipulating the random fluctuations in pilot intensity, which shows the strong adaptability and the important role of the proposed attack.

quant-ph↗
arXiv2023

Beyond Geo-localization: Fine-grained Orientation of Street-view Images by Cross-view Matching with Satellite Imagery with Supplementary Materials

Street-view imagery provides us with novel experiences to explore different places remotely. Carefully calibrated street-view images (e.g. Google Street View) can be used for different downstream tasks, e.g. navigation, map features extraction. As personal high-quality cameras have become much more affordable and portable, an enormous amount of crowdsourced street-view images are uploaded to the internet, but commonly with missing or noisy sensor information. To prepare this hidden treasure for "ready-to-use" status, determining missing location information and camera orientation angles are two equally important tasks. Recent methods have achieved high performance on geo-localization of street-view images by cross-view matching with a pool of geo-referenced satellite imagery. However, most of the existing works focus more on geo-localization than estimating the image orientation. In this work, we re-state the importance of finding fine-grained orientation for street-view images, formally define the problem and provide a set of evaluation metrics to assess the quality of the orientation estimation. We propose two methods to improve the granularity of the orientation estimation, achieving 82.4% and 72.3% accuracy for images with estimated angle errors below 2 degrees for CVUSA and CVACT datasets, corresponding to 34.9% and 28.2% absolute improvement compared to previous works. Integrating fine-grained orientation estimation in training also improves the performance on geo-localization, giving top 1 recall 95.5%/85.5% and 86.8%/80.4% for orientation known/unknown tests on the two datasets.

cs.CV↗
arXiv2023

Kramers nodal lines and Weyl fermions in SmAlSi

Kramers nodal lines (KNLs) have recently been proposed theoretically as a special type of Weyl line degeneracy connecting time-reversal invariant momenta. KNLs are robust to spin orbit coupling and are inherent to all non-centrosymmetric achiral crystal structures, leading to unusual spin, magneto-electric, and optical properties. However, their existence in in real quantum materials has not been experimentally established. Here we gather the experimental evidence pointing at the presence of KNLs in SmAlSi, a non-centrosymmetric metal that develops incommensurate spin density wave order at low temperature. Using angle-resolved photoemission spectroscopy, density functional theory calculations, and magneto-transport methods, we provide evidence suggesting the presence of KNLs, together with observing Weyl fermions under the broken inversion symmetry in the paramagnetic phase of SmAlSi. We discuss the nesting possibilities regarding the emergent magnetic orders in SmAlSi. Our results provide a solid basis of experimental observations for exploring correlated topology in SmAlSi.

cond-mat.mtrl-sci↗