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Xi Chen

Publications and source records attributed to Xi Chen.

At least 1,009 records · Page 56Linked to original sources

Population Based Augmentation: Efficient Learning of Augmentation Policy Schedules

A key challenge in leveraging data augmentation for neural network training is choosing an effective augmentation policy from a large search space of candidate operations. Properly chosen augmentation policies can lead to significant generalization improvements; however, state-of-the-art approaches such as AutoAugment are computationally infeasible to run for the ordinary user. In this paper, we introduce a new data augmentation algorithm, Population Based Augmentation (PBA), which generates nonstationary augmentation policy schedules instead of a fixed augmentation policy. We show that PBA can match the performance of AutoAugment on CIFAR-10, CIFAR-100, and SVHN, with three orders of magnitude less overall compute. On CIFAR-10 we achieve a mean test error of 1.46%, which is a slight improvement upon the current state-of-the-art. The code for PBA is open source and is available at https://github.com/arcelien/pba.

cs.CV↗

Deep Cascade Multi-task Learning for Slot Filling in Online Shopping Assistant

Slot filling is a critical task in natural language understanding (NLU) for dialog systems. State-of-the-art approaches treat it as a sequence labeling problem and adopt such models as BiLSTM-CRF. While these models work relatively well on standard benchmark datasets, they face challenges in the context of E-commerce where the slot labels are more informative and carry richer expressions. In this work, inspired by the unique structure of E-commerce knowledge base, we propose a novel multi-task model with cascade and residual connections, which jointly learns segment tagging, named entity tagging and slot filling. Experiments show the effectiveness of the proposed cascade and residual structures. Our model has a 14.6% advantage in F1 score over the strong baseline methods on a new Chinese E-commerce shopping assistant dataset, while achieving competitive accuracies on a standard dataset. Furthermore, online test deployed on such dominant E-commerce platform shows 130% improvement on accuracy of understanding user utterances. Our model has already gone into production in the E-commerce platform.

cs.CL↗

Reentrance of Topological Phase in Spin-1 Frustrated Heisenberg Chain

For the Haldane phase, the magnetic field usually tends to break the symmetry and drives the system into a topologically trivial phase. Here, we report a novel reentrance of the Haldane phase at zero temperature in the spin-1 antiferromagnetic Heisenberg model on sawtooth chain. A partial Haldane phase is induced by the magnetic field, which is the combination of the Haldane state in one sublattice and a ferromagnetically ordered state in the other sublattice. Such a partial topological order is a result of the zero-temperature entropy due to quantum fluctuations caused by geometrical frustration.

cond-mat.str-el↗

A 6.7 GHz Methanol Maser Survey at High Galactic Latitudes

We performed a systematic 6.7 GHz Class \uppercase\expandafter{\romannumeral2} methanol maser survey using the Shanghai Tianma Radio Telescope toward targets selected from the all-sky \emph{Wide-Field Infrared Survey Explorer (WISE)} point catalog. In this paper, we report the results from the survey of those at high Galactic latitudes, i.e. $|b|>$ 2$^\circ$. Of 1473 selected \emph{WISE} point sources at high latitude, 17 point positions that were actually associated with 12 sources were detected with maser emission, reflecting the rarity (1$-$2\%) of methanol masers in the region away from the Galactic plane. Out of the 12 sources, 3 are detected for the first time. The spectral energy distribution (SED) at infrared bands shows that these new detected masers occur in the massive star forming regions. Compared to previous detections, the methanol maser changes significantly in both spectral profiles and flux densities. The infrared \emph{WISE} images show that almost all of these masers are located in the positions of the bright \emph{WISE} point sources. Compared with the methanol masers at the Galactic plane, these high-latitude methanol masers provide good tracers for investigating the physics and kinematics around massive young stellar objects, because they are believed to be less affected by the surrounding cluster environment.

astro-ph.GA↗

Magnetic Susceptibility and Simulated Neutron Signal in the 2D Hubbard Model

We compute dynamic spin susceptibilities in the two-dimensional Hubbard model using the method of Dual Fermions and provide comparison to lattice Monte Carlo and cluster dynamical mean field theory. We examine the energy dispersion identified by peaks in ${\rm Im}χ(ω,q)$ which define spin modes and compare the exchange scale and magnon dispersion to neutron experiments on the parent La$_2$CuO$_4$ cuprate. We present the evolution of the spin excitations as a function of Hubbard interaction strengths and doping and explore the particle-hole asymmetry of the spin excitations. We also study the correlation lengths and the spin excitation dispersion peak structure and find a `Y'-shaped dispersion similar to neutron results on doped HgBa$_2$CuO$_{4+δ}$.

cond-mat.str-el↗

United test of the equivalence principle at $10^{-10}$ level using mass and internal energy specified atoms

We use both mass and internal energy specified rubidium atoms to jointly test the weak equivalence principle (WEP). We improve the four-wave double-diffraction Raman transition method (FWDR) we proposed before to select atoms with certain mass and angular momentum state, and perform dual-species atom interferometer. By combining $^{87}$Rb and $^{85}$Rb atoms with different angular momenta, we compare the differential gravitational acceleration of them, and determine the value of Eötvös parameter, $η$, which measures the strength of the violation of WEP. For one case ($^{87}$Rb$|\emph{F}=1\rangle$ - $^{85}$Rb$|\emph{F}=2\rangle$),the statistical uncertainty of $η$ is $1.8 \times 10^{-10}$ at integration time of 8960 s. With various systematic errors correction, the final value is $η=(-4.4 \pm 6.7) \times 10^{-10}$. Comparing with the previous WEP test experiments using atoms, this work gives a new upper limit of WEP violation for $^{87}$Rb and $^{85}$Rb atom pairs.

quant-ph↗

Noise-tolerant Detection of $Z_N$ Topological Orders in Quantum Many-body States

Topologically ordered states are fundamentally important in theoretical physics, which are also suggested as promising candidates to build fault-tolerant quantum devices. However, it is still elusive how topological orders can be affected or detected under noises. In this work, we find a quantity, termed as the ring degeneracy $\mathcal{D}$, which is robust under pure noise to detect both trivial and intrinsic topological orders. The ring degeneracy is defined as the degeneracy of the solutions of the self-consistent equations that encode the contraction of the corresponding tensor network(TN). For the $Z_N$ orders, we find that the ring degeneracy satisfies a simple relation $\mathcal{D} = (N + 1)/2 + d$, with $d = 0$ for odd $N$ and $d = 1/2$ for even $N$. Simulations on several non-trivial states (two-dimensional Ising model, $Z_N$ topological states, and resonating valence bond states) show that the ring degeneracy can tolerate noises up to a strength associated to the gap of the TN boundary theory.

cond-mat.stat-mech↗

Comparison-Based Algorithms for One-Dimensional Stochastic Convex Optimization

Stochastic optimization finds a wide range of applications in operations research and management science. However, existing stochastic optimization techniques usually require the information of random samples (e.g., demands in the newsvendor problem) or the objective values at the sampled points (e.g., the lost sales cost), which might not be available in practice. In this paper, we consider a new setup for stochastic optimization, in which the decision maker has access to only comparative information between a random sample and two chosen decision points in each iteration. We propose a comparison-based algorithm (CBA) to solve such problems in one dimension with convex objective functions. Particularly, the CBA properly chooses the two points in each iteration and constructs an unbiased gradient estimate for the original problem. We show that the CBA achieves the same convergence rate as the optimal stochastic gradient methods (with the samples observed). We also consider extensions of our approach to multi-dimensional quadratic problems as well as problems with non-convex objective functions. Numerical experiments show that the CBA performs well in test problems.

math.OC↗

Disorder induced multifractal superconductivity in monolayer niobium dichalcogenides

The interplay between disorder and superconductivity is a subtle and fascinating phenomenon in quantum many body physics. The conventional superconductors are insensitive to dilute nonmagnetic impurities, known as the Anderson's theorem. Destruction of superconductivity and even superconductor-insulator transitions occur in the regime of strong disorder. Hence disorder-enhanced superconductivity is rare and has only been observed in some alloys or granular states. Because of the entanglement of various effects, the mechanism of enhancement is still under debate. Here we report well-controlled disorder effect in the recently discovered monolayer NbSe$_2$ superconductor. The superconducting transition temperatures of NbSe$_2$ monolayers are substantially increased by disorder. Realistic theoretical modeling shows that the unusual enhancement possibly arises from the multifractality of electron wave functions. This work provides the first experimental evidence of the multifractal superconducting state.

cond-mat.supr-con↗

Bayesian Dynamic Modeling and Monitoring of Network Flows

In the context of a motivating study of dynamic network flow data on a large-scale e-commerce web site, we develop Bayesian models for on-line/sequential analysis for monitoring and adapting to changes reflected in node-node traffic. For large-scale networks, we customize core Bayesian time series analysis methods using dynamic generalized linear models (DGLMs). These are integrated into the context of multivariate networks using the concept of decouple/recouple that was recently introduced in multivariate time series. This method enables flexible dynamic modeling of flows on large-scale networks and exploitation of partial parallelization of analysis while maintaining coherence with an over-arching multivariate dynamic flow model. This approach is anchored in a case-study on internet data, with flows of visitors to a commercial news web site defining a long time series of node-node counts on over 56,000 node pairs. Central questions include characterizing inherent stochasticity in traffic patterns, understanding node-node interactions, adapting to dynamic changes in flows and allowing for sensitive monitoring to flag anomalies. The methodology of dynamic network DGLMs applies to many dynamic network flow studies.

stat.ME↗

Beyond trace reconstruction: Population recovery from the deletion channel

\emph{Population recovery} is the problem of learning an unknown distribution over an unknown set of $n$-bit strings, given access to independent draws from the distribution that have been independently corrupted according to some noise channel. Recent work has intensively studied such problems both for the bit-flip and erasure noise channels. We initiate the study of population recovery under the \emph{deletion channel}, in which each bit is independently \emph{deleted} with some fixed probability and the surviving bits are concatenated and transmitted. This is a far more challenging noise model than bit-flip~noise or erasure noise; indeed, even the simplest case in which the population size is 1 (corresponding to a trivial distribution supported on a single string) corresponds to the \emph{trace reconstruction} problem, a challenging problem that has received much recent attention (see e.g.~\cite{DOS17,NP17,PZ17,HPP18,HHP18}). We give algorithms and lower bounds for population recovery under the deletion channel when the population size is some $\ell>1$. As our main sample complexity upper bound, we show that for any $\ell=o(\log n/\log \log n)$, a population of $\ell$ strings from $\{0,1\}^n$ can be learned under deletion channel noise using $\smash{2^{n^{1/2+o(1)}}}$ samples. On the lower bound side, we show that $n^{Ω(\ell)}$ samples are required to perform population recovery under the deletion channel, for all $\ell \leq n^{1/2-ε}$. Our upper bounds are obtained via a robust multivariate generalization of a polynomial-based analysis, due to Krasikov and Roddity \cite{KR97}, of how the $k$-deck of a bit-string uniquely identifies the string; this is a very different approach from recent algorithms for trace reconstruction (the $\ell=1$ case). Our lower bounds build on moment-matching results of Roos~\cite{Roo00} and Daskalakis and Papadimitriou~\cite{DP15}.

cs.DS↗

Spin entangled state transfer in quantum dot arrays: Coherent adiabatic and speed-up protocols

Long-distance transfer of quantum states is an indispensable part of large-scale quantum information processing. We propose a novel scheme for the transfer of two-electron entangled states, from one edge of a quantum dot array to the other by coherent adiabatic passage. This protocol is mediated by pulsed tunneling barriers. In a second step, we seek for a speed up by shortcut to adiabaticity techniques. This significantly reduces the operation time and, thus, minimizes the impact of decoherence. For typical parameters of state-of-the-art solid state devices, the accelerated protocol has an operation time in the nanosecond range and terminates before a major coherence loss sets in. The scheme represents a promising candidate for entanglement transfer in solid state quantum information processing.

cond-mat.mes-hall↗

Towards Pricing Financial Derivatives with an IBM Quantum Computer

Pricing interest-rate financial derivatives is a major problem in finance, in which it is crucial to accurately reproduce the time-evolution of interest rates. Several stochastic dynamics have been proposed in the literature to model either the instantaneous interest rate or the instantaneous forward rate. A successful approach to model the latter is the celebrated Heath-Jarrow-Morton framework, in which its dynamics is entirely specified by volatility factors. On its multifactor version, this model considers several noisy components to capture at best the dynamics of several time-maturing forward rates. However, as no general analytical solution is available, there is a trade-off between the number of noisy factors considered and the computational time to perform a numerical simulation. Here, we employ the quantum principal component analysis to reduce the number of noisy factors required to accurately simulate the time evolution of several time-maturing forward rates. The principal components are experimentally estimated with the $5$-qubit IBMQX2 quantum computer for $2\times 2$ and $3\times 3$ cross-correlation matrices, which are based on historical data for two and three time-maturing forward rates. This manuscript is a first step towards the design of a general quantum algorithm to fully simulate on quantum computers the Heath-Jarrow-Morton model for pricing interest-rate financial derivatives. It shows indeed that practical applications of quantum computers in finance will be achievable in the near future.

quant-ph↗

Testing Unateness Nearly Optimally

We present an $\tilde{O}(n^{2/3}/ε^2)$-query algorithm that tests whether an unknown Boolean function $f\colon\{0,1\}^n\rightarrow \{0,1\}$ is unate (i.e., every variable is either non-decreasing or non-increasing) or $ε$-far from unate. The upper bound is nearly optimal given the $\tildeΩ(n^{2/3})$ lower~bound of [CWX17a]. The algorithm builds on a novel use of the binary search procedure and its analysis over long random paths.

cs.DS↗

Astrophysical constraints on the proton-to-electron mass ratio with FAST

That the laws of physics are the same at all times and places throughout the Universe is one of the basic assumptions of physics. Astronomical observations provide the only means to test this basic assumption on cosmological time and distance scales. The possibility of variations in the dimensionless physical constant μ - the proton-to-electron mass ratio, can be tested by comparing astronomical measurements of the rest frequency of certain spectral lines at radio wavelengths with laboratory determinations. Different types of molecular transitions have different dependencies on μ and so observations of two or more spectral lines towards the same astronomical source can be used to test whether there is any evidence for either temporal or spatial changes in the physical fundamental constants. μ will change if the relative strength of the strong nuclear force compared to the electromagnetic force varies. Theoretical studies have shown that the rotational transitions of some molecules which have transitions in the frequency range that will be covered by FAST (e.g., CH3OH, OH and CH) are sensitive to changes in μ. A number of studies looking for possible variations in μ have been undertaken with existing telescopes, however, the greater sensitivity of FAST means it will open new opportunities to significantly improve upon measurements made to date. In this paper, we discuss which molecular transitions and sources (both in the Galaxy and external galaxies) are likely targets for providing improved constraints on μ with FAST.

astro-ph.IM↗

A High-Performance Energy Management System based on Evolving Graph

As the fast growth and large integration of distributed generation, renewable energy resource, energy storage system and load response, the modern power system operation becomes much more complicated with increasing uncertainties and frequent changes. Increased operation risks are introduced to the existing commercial Energy Management System (EMS), due to its limited computational capability. In this paper, a high-performance EMS analysis framework based on the evolving graph is developed. A power grid is first modeled as an evolving graph and then the power system dynamic analysis applications, like network topology processing (NTP), state estimation (SE), power flow (PF), and contingency analysis (CA), are efficiently implemented on the system evolving graph to build a high-performance EMS analysis framework. Its computation performance is field tested using a 2749-bus power system in Sichuan, China. The results illustrate that the proposed EMS remarkably speeds up the computation performance and reaches the goal of real-time power system analysis.

cs.DC↗

Fast and robust creation of an arbitrary single qubit state by nonadiabatic shortcut pulses in a three-level system

High-fidelity qubit initialization is of significance for efficient error correction in fault tolerant quantum algorithms. Combining two best worlds, speed and robustness, to achieve high-fidelity state preparation and manipulation is challenging in quantum systems, where qubits are closely spaced in frequency. Motivated by the concept of shortcut to adiabaticity, we theoretically propose the shortcut pulses via inverse engineering and further optimize the pulses with respect to systematic errors in frequency detuning and Rabi frequency. Such protocol, relevant to frequency selectivity, is applied to rare-earth ions qubit system, where the excitation of frequency-neighboring qubits should be prevented as well. Furthermore, comparison with adiabatic complex hyperbolic secant pulses shows that these dedicated initialization pulses can reduce the time that ions spend in the excited state by a factor of 6, which is important in coherence time limited systems to approach an error rate manageable by quantum error correction. The approach may also be applicable to superconducting qubits, and any other systems where qubits are addressed in frequency.

quant-ph↗

From atomic layer to the bulk: low-temperature atomistic structure, ferroelectric and electronic properties of SnTe films

SnTe hosts ferroelectricity that competes with its weak non-trivial band topology: in the high-symmetry rocksalt structure--in which its intrinsic electric dipole is quenched--this material develops metallic surface bands, but in its rhombic ground-state configuration--that hosts a non-zero spontaneous electric dipole--the crystalline symmetry is lowered and the presence of surface electronic bands is not guaranteed. Here, the type of ferroelectric coupling and the atomistic and electronic structure of SnTe films ranging from 2 to 40 ALs are examined on freestanding samples, to which atomic layers were gradually added. 4 AL SnTe films are antiferroelectrically-coupled, while thicker freestanding SnTe films are ferroelectrically-coupled. The electronic band gap reduces its magnitude in going from 2 ALs to 40 ALs but it does not close due to the rhombic nature of the structure. These results bridge the structure of SnTe films from the monolayer to the bulk.

cond-mat.mes-hall↗