arXiv subjects

Yiming Xing

Publications and source records attributed to Yiming Xing.

11 recordsLinked to original sources

arXiv2026

Sequential multiple testing with multiple hypotheses and prior information on the hypothesis configuration

In this work, we study the problem of testing the marginal distributions of multiple independent, sequentially observed data streams, where for each stream there are multiple candidate hypotheses to select from, in the presence of prior information on the unknown hypothesis configuration. The goal is to understand the benefit of such information and to design a sequential testing procedure that effectively leverages it. We start with arbitrary prior information and specialize to concrete examples, including known number or known lower bound on the number of streams following each hypothesis, and the presence of exclusive hypotheses. The designed procedure is three-fold: (i) reliable, i.e., controlling all types of familywise error probabilities below arbitrary user-specified levels, (ii) computationally efficient, i.e., focusing on minimal sets of alternative hypothesis configurations in making decisions, and (iii) asymptotically optimal, i.e., achieving the minimum expected sample size among all reliable procedures asymptotically as the error levels go to zero. Numerical studies are presented for illustration.

stat.ME↗

arXiv2026

Active Sequential Signal Detection with Asynchronous Decisions

This work considers the problem of detecting signals from multiple sequentially observed data streams, where only one stream can be observed at every time instant. The goal is to detect signals as quickly as possible while controlling the global probabilities of false alarm and missed detection. In this active sampling setup, it is impossible to minimize the expected detection time simultaneously for every signal, so we formulate a novel set of performance criteria that aim to minimize the expectations of the order statistics of the detection times. A novel procedure is proposed, which incorporates an exploration mechanism to a "follow-the-leader" procedure, and is shown to optimize all the criteria asymptotically as the global error probabilities go to zero. Its finite-sample performance is compared with existing and oracle procedures in simulation studies.

stat.ME↗

arXiv2026

Evidence for Vortex Rings with Multiquantum Circulation in He II

Quantized vortex dynamics in superfluid $^4$He (He~II) are widely regarded as well established: circulation is quantized in units of $\kappa=h/m_4$, vortices carrying more than one quantum are expected to split into singly quantized filaments, and vortex rings shrink while accelerating due to dissipation from thermal-quasiparticle scattering. Using particle tracking velocimetry with frozen deuterium tracers, we uncover rare vortex-bound particle events that disrupt this canonical picture. In a class of events exhibiting the acceleration characteristic of shrinkage driven vortex ring motion, the measured kinematics cannot be reconciled with a singly quantized ring. Instead, they require an effective circulation $n\kappa$ with $n>1$, directly challenging the standard expectation that multiquantum vortices are short lived. A more prosaic possibility is that the inferred $n\kappa$ arises from a bundle of closely spaced singly quantized rings, which could generate similar large-scale motion. However, this scenario is disfavored by vortex-filament simulations that show rapid bundle dispersion. Furthermore, the persistence of particle trapping at the observed high speeds suggests a much deeper core trapping potential, consistent only with a truly multiquantum core. Together, these results point to anomalously long-lived multiquantum rings, a striking puzzle that calls for dedicated scrutiny beyond the prevailing paradigm.

cond-mat.other↗

arXiv2026

Active Hypothesis Testing for Correlated Combinatorial Anomaly Detection

We study the problem of identifying an anomalous subset of streams under correlated noise, motivated by monitoring and security in cyber-physical systems. This problem can be viewed as a form of combinatorial pure exploration, where each stream plays the role of an arm and measurements must be allocated sequentially under uncertainty. Existing combinatorial bandit and hypothesis testing methods typically assume independent observations and fail to exploit correlation for efficient measurement design. We propose ECC-AHT, an adaptive algorithm that selects continuous, constrained measurements to maximize Chernoff information between competing hypotheses, enabling active noise cancellation through differential sensing. ECC-AHT achieves optimal sample complexity guarantees and significantly outperforms state-of-the-art baselines in both synthetic and real-world correlated environments. The code is available on https://github.com/VincentdeCristo/ECC-AHT

cs.LG↗

arXiv2025

On-Chip Levitated Neon Particle Arrays for Robust and Scalable Electron Qubits

Electron-on-neon (eNe) qubits have recently emerged as a compelling platform for quantum computing, which combines the vacuum isolation advantages of trapped-ion qubits with the scalability of superconducting circuits. In this system, electrons are trapped in vacuum above a solid neon film deposited on superconducting microwave resonators, where they exhibit strong coupling to the resonators, coherence times of ~0.1 ms, and single-qubit gate fidelities exceeding 99.97%. A central challenge, however, is the spontaneous binding of electrons to neon surface bumps. These bumps, originating from substrate roughness, vary in size: electrons on bumps of suitable sizes within the resonator can couple to microwave photons and function as qubits, whereas those on unfavorable bumps remain inactive yet contribute to background charge noise. Moreover, both the bump landscape and the sites where electrons bind differ from run to run, leading to variable qubit characteristics that hinder scalability. To address this challenging issue, we present an on-chip magnetic-levitation architecture in which arrays of solid-neon microparticles are suspended above the processor chip to act as electron carriers. This design eliminates substrate effects while retaining strong qubit-resonator coupling and supporting inter-qubit connectivity. Our analysis further shows that the qubit transition frequency can be tuned across the gigahertz range and its anharmonicity can reach ~0.8 GHz by tuning the resonator bias voltage. Together, these features suggest a promising pathway toward robust, reproducible, and scalable eNe-based quantum computing.

quant-ph↗

arXiv2025

Signal Detection under Composite Hypotheses with Identical Distributions for Signals and for Noises

In this paper, we consider the problem of detecting signals in multiple, sequentially observed data streams, where the distribution of each stream lies in one of two common composite spaces, depending on whether it is a signal or a noise. For this problem, we study a practical yet underexplored setting where it is a priori known that all signals have an identical distribution and so do all noises. Compared to the general setting where local distributions are free to take any values, this structure facilitates faster decision-making thanks to a smaller joint distribution space. However, it introduces additional challenges to the analysis of problem and design of tests, since the local distributions are now coupled. In this paper, we first establish a universal lower bound on the minimum expected sample size, which characterizes the essential difficulty of the problem and involves constants that are neither the minimum Kullback-Leibler divergences between the signal/noise distribution to the noise/signal distribution space, which appear in the lower bound for the general setting, nor the Kullback-Leibler divergences between the signal distribution and the noise distribution. Besides, we propose a test that controls the two types of familywise error rates below arbitrary levels, and achieves the minimum expected sample size asymptotically as the levels go to zero. Numerical studies are presented to compare with the state-of-the-art test for the general setting and demonstrate robustness against model misspecification.

stat.ME↗

arXiv2025

Turbulent diffusion and dispersion in a superfluid

Single-body diffusion and two-body dispersion are fundamental processes in classical turbulence, governing particle mixing and transport. However, their behaviors in superfluid turbulence remain largely unexplored. In this study, we numerically investigate the diffusion and relative dispersion of quantized vortices and superfluid parcels in the 0 K limit in two distinct turbulence regimes: ultra-quantum turbulence, characterized by a randomized vortex tangle, and quasiclassical turbulence, in which locally polarized vortices create large-scale flows resembling classical turbulence. Our results reveal that while vortex segments exhibit similar superdiffusion behavior at short times in both regimes, superfluid parcels behave differently: following the same superdiffusion scaling in ultra-quantum turbulence but deviating significantly in quasiclassical turbulence. This contrast provides a key clue to the origin of short-time superdiffusion, a puzzle since its recent discovery. Additionally, we show that two-body dispersion of both vortex segments and superfluid parcels exhibits distinct scaling behaviors in ultra-quantum and quasiclassical turbulence, highlighting fundamental differences in these two turbulence regimes. Our findings bridge a critical gap in superfluid turbulence research, offering new insights into turbulent transport in inviscid quantum fluids.

cond-mat.quant-gas↗

arXiv2024

Experimental and theoretical evidence of universality in superfluid vortex reconnections

The minimum separation between reconnecting vortices in fluids and superfluids obeys a universal scaling law with respect to time. The pre-reconnection and the post-reconnection prefactors of this scaling law are different, a property related to irreversibility and to energy transfer and dissipation mechanisms. In the present work, we determine the temperature dependence of these prefactors in superfluid helium from experiments and a numeric model which fully accounts for the coupled dynamics of the superfluid vortex lines and the thermal normal fluid component. At all temperatures, we observe a pre- and post-reconnection asymmetry similar to that observed in other superfluids and in classical viscous fluids, indicating that vortex reconnections display a universal behaviour independent of the small-scale regularising dynamics. We also numerically show that each vortex reconnection event represents a sudden injection of energy in the normal fluid. Finally we argue that in a turbulent flow, these punctuated energy injections can sustain the normal fluid in a perturbed state, provided that the density of superfluid vortices is large enough.

cond-mat.quant-gas↗

arXiv2023

Asymptotically Optimal Sequential Multiple Testing with Asynchronous Decisions

The problem of simultaneously testing the marginal distributions of sequentially monitored, independent data streams is considered. The decisions for the various testing problems can be made at different times, using data from all streams, which can be monitored until all decisions have been made. Moreover, arbitrary a priori bounds are assumed on the number of signals, i.e., data streams in which the alternative hypothesis is correct. A novel sequential multiple testing procedure is proposed and it is shown to achieve the minimum expected decision time, simultaneously in every data stream and under every signal configuration, asymptotically as certain metrics of global error rates go to zero. This optimality property is established under general parametric composite hypotheses, various error metrics, and weak distributional assumptions that allow for temporal dependence. Furthermore, the limit of the factor by which the expected decision time in a data stream increases when one is limited to synchronous or decentralized procedures is evaluated. Finally, two existing sequential multiple testing procedures in the literature are compared with the proposed one in various simulation studies.

stat.ME↗

arXiv2022

Signal Recovery With Multistage Tests And Without Sparsity Constraints

A signal recovery problem is considered, where the same binary testing problem is posed over multiple, independent data streams. The goal is to identify all signals, i.e., streams where the alternative hypothesis is correct, and noises, i.e., streams where the null hypothesis is correct, subject to prescribed bounds on the classical or generalized familywise error probabilities. It is not required that the exact number of signals be a priori known, only upper bounds on the number of signals and noises are assumed instead. A decentralized formulation is adopted, according to which the sample size and the decision for each testing problem must be based only on observations from the corresponding data stream. A novel multistage testing procedure is proposed for this problem and is shown to enjoy a high-dimensional asymptotic optimality property. Specifically, it achieves the optimal, average over all streams, expected sample size, uniformly in the true number of signals, as the maximum possible numbers of signals and noises go to infinity at arbitrary rates, in the class of all sequential tests with the same global error control. In contrast, existing multistage tests in the literature are shown to achieve this high-dimensional asymptotic optimality property only under additional sparsity or symmetry conditions. These results are based on an asymptotic analysis for the fundamental binary testing problem as the two error probabilities go to zero. For this problem, unlike existing multistage tests in the literature, the proposed test achieves the optimal expected sample size under both hypotheses, in the class of all sequential tests with the same error control, as the two error probabilities go to zero at arbitrary rates. These results are further supported by simulation studies and extended to problems with non-iid data and composite hypotheses.

stat.ME↗

arXiv2022

3-stage and 4-stage tests with deterministic stage sizes and non-iid data

Given a fixed-sample-size test that controls the error probabilities under two specific, but arbitrary, distributions, a 3-stage and two 4-stage tests are proposed and analyzed. For each of them, a novel, concrete, non-asymptotic, non-conservative design is specified, which guarantees the same error control as the given fixed-sample-size test. Moreover, first-order asymptotic approximation are established on their expected sample sizes under the two prescribed distributions as the error probabilities go to zero. As a corollary, it is shown that the proposed multistage tests can achieve, in this asymptotic sense, the optimal expected sample size under these two distributions in the class of all sequential tests with the same error control. Furthermore, they are shown to be much more robust than Wald's SPRT when applied to one-sided testing problems and the error probabilities under control are small enough. These general results are applied to testing problems in the iid setup and beyond, such as testing the correlation coefficient of a first-order autoregression, or the transition matrix of a finite-state Markov chain, and are illustrated in various numerical studies.

math.ST↗