arXiv subjects

Yulong Liu

Publications and source records attributed to Yulong Liu.

At least 55 records · Page 3Linked to original sources

arXiv2022

Modeling of three-dimensional betatron oscillation and radiation reaction in plasma accelerators

Betatron oscillation is a commonly known phenomenon in laser or beam driven plasma wakefield accelerators. In the conventional model, the plasma wake provides a linear focusing force to a relativistic electron, and the electron oscillates in one transverse direction with the betatron frequency proportional to $1/\sqrtγ$, where $γ$ is the Lorentz factor of the electron. In this work, we extend this model to three-dimensional by considering the oscillation in two transverse and one longitudinal directions. The long-term equations, with motion in the betatron time scale averaged out, are obtained and compared with the original equations by numerical methods. In addition to the longitudinal and transverse damping due to radiation reaction which has been found before, we show phenomena including the longitudinal phase drift, betatron phase shift and betatron polarization change based on our long-term equations. This work can be highly valuable for future plasma based high-energy accelerators and colliders.

physics.acc-ph↗

arXiv2022

Hybridized Frequency Combs in Multimode Cavity Electromechanical System

The cavity electromechanical devices with radiation-pressure-interaction induced Kerr-like nonlinearity are promising candidates to generate microwave frequency combs. We construct a silicon-nitride-membrane-based superconducting cavity electromechanical device and study two mechanical modes mediated synergistic frequency combs. Around the threshold of intracavity field instability, we firstly show independent frequency combs with tooth spacing equalling to each mechanical mode frequency. At the overlap boundaries of these two individual mechanical mode mediated instability thresholds, we observe hybridization of frequency combs based on the cavity field mediated indirect coupling between these two mechanical modes. The spectrum lines turn to be unequally spaced but can be recognized into combinations of the coexisting frequency combs. Beyond the boundary, the comb reverts to the single-mode case, and which mechanical mode frequency will the tooth spacing depend on the mode competition. Our work demonstrates mechanical mode competition enabled switchability of frequency comb tooth spacing and can be extended to other devices with multiple nonlinearities.

quant-ph↗

arXiv2022

Time-Data Tradeoffs in Structured Signals Recovery via the Proximal-Gradient Homotopy Method

In this paper, we characterize data-time tradeoffs of the proximal-gradient homotopy method used for solving linear inverse problems under sub-Gaussian measurements. Our results are sharp up to an absolute constant factor. We demonstrate that, in the absence of the strong convexity assumption, the proximal-gradient homotopy update can achieve a linear rate of convergence when the number of measurements is sufficiently large. Numerical simulations are provided to verify our theoretical results.

cs.IT↗

arXiv2022

Quantum backaction evading measurements of a silicon nitride membrane resonator

Quantum backaction disturbs the measurement of the position of a mechanical oscillator by introducing additional fluctuations. In a quantum backaction measurement technique, the backaction can be evaded, although at the cost of losing part of the information. In this work, we carry out such a quantum backaction measurement using a large 0.5 mm diameter silicon nitride membrane oscillator with 707 kHz frequency, via a microwave cavity readout. The measurement shows that quantum backaction noise can be evaded in the quadrature measurement of the motion of a large object.

quant-ph↗

arXiv2022

A Sharp Algorithmic Analysis of Covariate Adjusted Precision Matrix Estimation with General Structural Priors

In this paper, we present a sharp analysis for a class of alternating projected gradient descent algorithms which are used to solve the covariate adjusted precision matrix estimation problem in the high-dimensional setting. We demonstrate that these algorithms not only enjoy a linear rate of convergence in the absence of convexity, but also attain the optimal statistical rate (i.e., minimax rate). By introducing the generic chaining, our analysis removes the impractical resampling assumption used in the previous work. Moreover, our results also reveal a time-data tradeoff in this covariate adjusted precision matrix estimation problem. Numerical experiments are provided to verify our theoretical results.

cs.IT↗

arXiv2021

Optomechanical Anti-lasing with Infinite Group Delay at a Phase Singularity

Singularities that symbolize abrupt changes and exhibit extraordinary behavior are of broad interest. We experimentally study optomechanically induced singularities in a compound system consisting of a three-dimensional aluminum superconducting cavity and a metalized high-coherence silicon nitride membrane resonator. Mechanically-induced coherent perfect absorption and anti-lasing occur simultaneously under a critical optomechanical coupling strength. Meanwhile, the phase around the cavity resonance undergoes an abrupt $π$-phase transition, which further flips the phase slope in the frequency dependence. The observed infinite-discontinuity in the phase slope defines a singularity, at which the group velocity is dramatically changed. Around the singularity, an abrupt transition from an infinite group advance to delay is demonstrated by measuring a Gaussian-shaped waveform propagating. Our experiment may broaden the scope of realizing extremely long group delays by taking advantage of singularities.

quant-ph↗

arXiv2021

Convergence and stability of the semi-tamed Milstein method for commutative stochastic differential equations with non-globally Lipschitz continuous coefficients

A new explicit stochastic scheme of order 1 is proposed for solving commutative stochastic differential equations (SDEs) with non-globally Lipschitz continuous coefficients. The proposed method is a semi-tamed version of Milstein scheme to solve SDEs with the drift coefficient consisting of non-Lipschitz continuous term and globally Lipschitz continuous term. It is easily implementable and achieves higher strong convergence order. A stability criterion for this method is derived, which shows that the stability condition of the numerical methods and that of the solved equations keep uniform. Compared with some widely used numerical schemes, the proposed method has better performance in inheriting the mean square stability of the exact solution of SDEs. Numerical experiments are given to illustrate the obtained convergence and stability properties.

math.NA↗

arXiv2021

Quantized Corrupted Sensing with Random Dithering

Corrupted sensing concerns the problem of recovering a high-dimensional structured signal from a collection of measurements that are contaminated by unknown structured corruption and unstructured noise. In the case of linear measurements, the recovery performance of different convex programming procedures (e.g., generalized Lasso and its variants) is well established in the literature. However, in practical applications of digital signal processing, the quantization process is inevitable, which often leads to non-linear measurements. This paper is devoted to studying corrupted sensing under quantized measurements. Specifically, we demonstrate that, with the aid of uniform dithering, both constrained and unconstrained Lassos are able to recover signal and corruption from the quantized samples when the measurement matrix is sub-Gaussian. Our theoretical results reveal the role of quantization resolution in the recovery performance of Lassos. Numerical experiments are provided to confirm our theoretical results.

cs.IT↗

arXiv2021

Phase-controlled pathway interferences and switchable fast-slow light in a cavity-magnon polariton system

We study the phase controlled transmission properties in a compound system consisting of a 3D copper cavity and an yttrium iron garnet (YIG) sphere. By tuning the relative phase of the magnon pumping and cavity probe tones, constructive and destructive interferences occur periodically, which strongly modify both the cavity field transmission spectra and the group delay of light. Moreover, the tunable amplitude ratio between pump-probe tones allows us to further improve the signal absorption or amplification, accompanied by either significantly enhanced optical advance or delay. Both the phase and amplitude-ratio can be used to realize in-situ tunable and switchable fast-slow light. The tunable phase and amplitude-ratio lead to the zero reflection of the transmitted light and an abrupt fast-slow light transition. Our results confirm that direct magnon pumping through the coupling loops provides a versatile route to achieve controllable signal transmission, storage, and communication, which can be further expanded to the quantum regime, realizing coherent-state processing or quantum-limited precise measurements.

quant-ph↗

arXiv2021

Phase Transitions in Recovery of Structured Signals from Corrupted Measurements

This paper is concerned with the problem of recovering a structured signal from a relatively small number of corrupted random measurements. Sharp phase transitions have been numerically observed in practice when different convex programming procedures are used to solve this problem. This paper is devoted to presenting theoretical explanations for these phenomenons by employing some basic tools from Gaussian process theory. Specifically, we identify the precise locations of the phase transitions for both constrained and penalized recovery procedures. Our theoretical results show that these phase transitions are determined by some geometric measures of structure, e.g., the spherical Gaussian width of a tangent cone and the Gaussian (squared) distance to a scaled subdifferential. By utilizing the established phase transition theory, we further investigate the relationship between these two kinds of recovery procedures, which also reveals an optimal strategy (in the sense of Lagrange theory) for choosing the tradeoff parameter in the penalized recovery procedure. Numerical experiments are provided to verify our theoretical results.

cs.IT↗

arXiv2020

Prospects for observing gravitational forces between nonclassical mechanical oscillators

Interfacing quantum mechanics and gravity is one of the great open questions in natural science. Micromechanical oscillators have been suggested as a plausible platform to carry out these experiments. We present an experimental design aiming at these goals, inspired by Schmöle et al., Class. Quantum Grav. 33, 125031 (2016). Gold spheres weighing on the order a milligram will be positioned on large silicon nitride membranes, which are spaced at submillimeter distances from each other. These mass-loaded membranes are mechanical oscillators that vibrate at $\sim 2$ kHz frequencies in a drum mode. They are operated and measured by coupling to microwave cavities. First, we show that it is possible to measure the gravitational force between the oscillators at deep cryogenic temperatures, where thermal mechanical noise is strongly suppressed. We investigate the measurement of gravity when the positions of the gravitating masses exhibit significant quantum fluctuations, including preparation of the massive oscillators in the ground state, or in a squeezed state. We also present a plausible scheme to realize an experiment where the two oscillators are prepared in a two-mode squeezed motional quantum state that exhibits nonlocal quantum correlations and gravity the same time. Although the gravity is classical, the experiment will pave the way for testing true quantum gravity in related experimental arrangements. In a proof-of-principle experiment, we operate a 1.7 mm diameter Si$_3$N$_4$ membrane loaded by a 1.3 mg gold sphere. At 10 mK temperature, we observe the drum mode with a quality factor above half a million at 1.7 kHz, showing strong promise for the experiments. Following implementation of vibration isolation, cryogenic positioning, and phase noise filtering, we foresee that realizing the experiments is in reach by combining known pieces of current technology.

cond-mat.mes-hall↗

arXiv2020

Spectrally Sparse Signal Recovery via Hankel Matrix Completion with Prior Information

This paper studies the problem of reconstructing spectrally sparse signals from a small random subset of time domain samples via low-rank Hankel matrix completion with the aid of prior information. By leveraging the low-rank structure of spectrally sparse signals in the lifting domain and the similarity between the signals and their prior information, we propose a convex method to recover the undersampled spectrally sparse signals. The proposed approach integrates the inner product of the desired signal and its prior information in the lift domain into vanilla Hankel matrix completion, which maximizes the correlation between the signals and their prior information. Theoretical analysis indicates that when the prior information is reliable, the proposed method has a better performance than vanilla Hankel matrix completion, which reduces the number of measurements by a logarithmic factor. We also develop an ADMM algorithm to solve the corresponding optimization problem. Numerical results are provided to verify the performance of proposed method and corresponding algorithm.

cs.IT↗

arXiv2020

Matrix Completion with Prior Subspace Information via Maximizing Correlation

This paper studies the problem of completing a low-rank matrix from a few of its random entries with the aid of prior information. We suggest a strategy to incorporate prior information into the standard matrix completion procedure by maximizing the correlation between the original signal and the prior information. We also establish performance guarantees for the proposed method, which show that with suitable prior information, the proposed procedure can reduce the sample complexity of the standard matrix completion by a logarithmic factor. To illustrate the theory, we further analyze an important practical application where the prior subspace information is available. Both synthetic and real-world experiments are provided to verify the validity of the theory.

cs.IT↗

arXiv2019

Covariance Matrix Estimation from Correlated Sub-Gaussian Samples

This paper studies the problem of estimating a covariance matrix from correlated sub-Gaussian samples. We consider using the correlated sample covariance matrix estimator to approximate the true covariance matrix. We establish non-asymptotic error bounds for this estimator in both real and complex cases. Our theoretical results show that the error bounds are determined by the signal dimension $n$, the sample size $m$ and the correlation pattern $\textbf{B}$. In particular, when the correlation pattern $\textbf{B}$ satisfies $tr(\textbf{B})=m$, $||\textbf{B}||_{F}=O(m^{1/2})$, and $||\textbf{B}||=O(1)$, these results reveal that $O(n)$ samples are sufficient to accurately estimate the covariance matrix from correlated sub-Gaussian samples. Numerical simulations are presented to show the correctness of the theoretical results.

cs.IT↗

arXiv2019

Observation of anti-PT symmetry phase transition in the magnon-cavity-magnon coupled system

As the counterpart of PT symmetry, abundant phenomena and potential applications of anti-PT symmetry have been predicted or demonstrated theoretically. However, experimental realization of the coupling required in the anti-PT symmetry is difficult. Here, by coupling two YIG spheres to a microwave cavity, the large cavity dissipation rate makes the magnons coupled dissipatively with each other, thereby obeying a two-dimensional anti-PT Hamiltonian. In terms of the magnon-readout method, a new method adopted here, we demonstrate the validity of our method in constructing an anti-PT system and present the counterintuitive level attraction process. Our work provides a new platform to explore the anti-PT symmetry properties and paves the way to study multi-magnoncavity-polariton systems.

quant-ph↗

arXiv2019

The Herbarium Challenge 2019 Dataset

Herbarium sheets are invaluable for botanical research, and considerable time and effort is spent by experts to label and identify specimens on them. In view of recent advances in computer vision and deep learning, developing an automated approach to help experts identify specimens could significantly accelerate research in this area. Whereas most existing botanical datasets comprise photos of specimens in the wild, herbarium sheets exhibit dried specimens, which poses new challenges. We present a challenge dataset of herbarium sheet images labeled by experts, with the intent of facilitating the development of automated identification techniques for this challenging scenario.

cs.CV↗

arXiv2019

Covariance Matrix Estimation from Linearly-Correlated Gaussian Samples

Covariance matrix estimation concerns the problem of estimating the covariance matrix from a collection of samples, which is of extreme importance in many applications. Classical results have shown that $O(n)$ samples are sufficient to accurately estimate the covariance matrix from $n$-dimensional independent Gaussian samples. However, in many practical applications, the received signal samples might be correlated, which makes the classical analysis inapplicable. In this paper, we develop a non-asymptotic analysis for the covariance matrix estimation from correlated Gaussian samples. Our theoretical results show that the error bounds are determined by the signal dimension $n$, the sample size $m$, and the shape parameter of the distribution of the correlated sample covariance matrix. Particularly, when the shape parameter is a class of Toeplitz matrices (which is of great practical interest), $O(n)$ samples are also sufficient to faithfully estimate the covariance matrix from correlated samples. Simulations are provided to verify the correctness of the theoretical results.

cs.IT↗

arXiv2019

Recovery of Structured Signals From Corrupted Non-Linear Measurements

This paper studies the problem of recovering a structured signal from a relatively small number of corrupted non-linear measurements. Assuming that signal and corruption are contained in some structure-promoted set, we suggest an extended Lasso to disentangle signal and corruption. We also provide conditions under which this recovery procedure can successfully reconstruct both signal and corruption.

cs.IT↗