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Rui Luo

Publications and source records attributed to Rui Luo.

At least 19 recordsLinked to original sources

Constant-depth adaptive preparation of Dicke and symmetric states

Efficient preparation of Dicke states and, more generally, permutation-symmetric states is important for quantum metrology, quantum networking, and collective quantum information processing. Measurements and classical feedforward enable low-depth preparations of these states, with a cost of ancillary qubits. In this work, we introduce an exact constant-depth adaptive preparation protocol for arbitrary Dicke-$(n,k)$ states and further symmetric states. We first provide a protocol preparing the uniform subset superposition state, as a primitive, using constant-depth adaptive circuit with $O(k^2\log^2 n)$ ancillary qubits and success probability at least $1/k$. This yields an exact, probabilistic, constant-depth Dicke-state preparation protocol using $O\left(n^2+k^2\log^2 n+kn\log n\log\log n\right)$ ancillary qubits. Parallel repetition suppresses the failure probability exponentially without increasing the quantum depth. Moreover, the uniform subset superposition state is also of independent interest as the uniform vertex state of the Johnson graph and as the compact uniform subset state appearing in quantum-walk and topological-data-analysis algorithms. We further establish a general lifting framework that coherently combines clean unitary Dicke-state preparation circuits to prepare arbitrary symmetric states with only polynomial ancillary overhead. Combined with recent constant-depth unitary Dicke-state constructions, this gives an exact constant-depth preparation protocol for arbitrary $n$-qubit symmetric states using $O(n^3\sqrt{\log n})$ ancillary qubits.

quant-ph

QAdapt: A Noise-Adaptive Neural Pre-Decoding Framework for Quantum Error Correction

Fault-tolerant quantum computing (FTQC) relies on quantum error correction to suppress physical errors and preserve logical information at scale. In practice, however, performance is constrained not only by physical noise but also by the latency of classical decoders processing rapidly generated syndrome data. This challenge is exacerbated by hardware noise that is strong, heterogeneous, and nonstationary, as well as by the simulation-to-hardware distribution shift that can substantially degrade fixed neural decoders. We present QAdapt, a noise-adaptive neural pre-decoding framework for surface-code quantum error correction. QAdapt captures local spatiotemporal correlations in syndrome data, sequentially adapts to evolving noise conditions while mitigating catastrophic forgetting, and forwards the residual syndrome to a conventional global decoder. Across 110 synthetic out-of-distribution noise configurations for rotated surface-code memory circuits, QAdapt consistently reduces the logical error rate relative to the neural pre-decoding baseline. On Google's Willow benchmark data, without target-domain fine-tuning, it achieves reductions of up to 5.79 percent in logical error rate and 9.32 percent in backend decoding latency on the residual syndrome. These results demonstrate that QAdapt provides a practical and decoder-compatible approach to improving the robustness and backend decoding efficiency of quantum error correction under evolving hardware noise.

cs.LG

OneShot: Index-in-Ranking with Neural Scoring for Large-Scale Retrieval

In modern recommendation systems, retrieval serves as a primary stage responsible for filtering billions of candidate items down to thousands prior to refined ranking. To make this massive search effective and efficient, the system relies on ranking accuracy and indexing efficiency. However, these two objectives are traditionally misaligned: while the former optimizes for the alignment between ranking predictions and user behavior, the latter optimizes for a structural grouping of item representations which enables fast search among billions of candidates. Thus, despite extensive efforts to scale up interaction modeling for retrieval, they remain fundamentally limited by the structural misalignment between the ranking objectives and the proximity-learned index. In this work, we address this long-standing dichotomy by proposing a new holistic retrieval framework, OneShot. It is an end-to-end, in-model index learning framework that natively aligns index learning with ranking objectives. Using this joint learning as a structural foundation, OneShot pushes the boundaries of retrieval expressiveness by scaling interaction modeling with neural scoring beyond the persistent dot-product bottleneck. OneShot is fully deployed in Instagram's industrial short-video recommendation system, driving significant wins in user daily sessions, engagement, and time-spent. Additionally, OneShot achieves a $20\%$ recall gain at the operational ranking volume and a 10x efficiency improvement at an equivalent recall level.

cs.IR

Clock-noise subtraction in geometric time-delay interferometry for space-based gravitational-wave parameter estimation

Millihertz gravitational-wave observations with space-based interferometers require time-delay interferometry (TDI) observables whose residual instrumental noise is sufficiently controlled for both detection and parameter inference. Although TDI suppresses laser phase noise in unequal and time-dependent arms, clock jitter from onboard ultra-stable oscillators can remain above the secondary-noise floor and bias the effective noise weighting used in data analysis. We formulate a clock-noise subtraction scheme directly in the geometric-TDI framework. The construction introduces generalized clock-noise observables for the four space-time link structures that arise when both delay and time-advance operators are allowed. This makes the clock-noise residual algebraically parallel to the laser-noise residual and yields explicit subtraction terms for arbitrary two-path geometric TDI observables. We illustrate the method with representative first- and second-generation geometric TDI combinations, and test it with time-domain simulations using LISA-like orbits and noise levels. For a modified second-generation U-type observable, the subtraction suppresses the clock-noise residual below the signal region, restores the expected sensitivity to a monochromatic source, and improves the Fisher and Markov-chain Monte Carlo parameter constraints on the source amplitude, frequency and phase. These results show that clock-noise calibration is a necessary component of precision data analysis for future space-based gravitational-wave detectors.

gr-qc

No Strong Evidence for Plasma Lensing in FRB 20240114A

FRB~20240114A is an extremely active repeating fast radio burst for which plasma lensing has been proposed to explain its burst-rate variations, spectral evolution, and apparently ``carbon-copy'' burst pairs. Using FAST data and publicly available Parkes observations, we test this interpretation with a one-dimensional Gaussian plasma-lens model. Although the burst-rate enhancements can be fitted separately, the corresponding magnification peaks and demagnification troughs are offset by far more than predicted and show no consistent periodicity. Moreover, with more than 10,000 bursts detected, a few apparently ``carbon-copy'' pairs can readily occur by chance. The burst bandwidth is not systematically narrower during the proposed lensing interval, nor are the burst energies significantly enhanced during the predicted magnification interval. These results provide no compelling evidence that a single Gaussian plasma lens explains the observed variability, which is more likely dominated by intrinsic source activity.

astro-ph.HE

Gravitational-wave response functions for space-borne detectors based on multiple geometric time-delay interferometry links

The primary challenge for space-borne gravitational wave (GW) detectors lies in extracting the weak GW signal from instrumental noise that exceeds the signal level by many orders of magnitude. Time-delay interferometry (TDI) addresses this by suppressing the dominant laser phase noise through recombination of time-delayed measurement data. The detector's response to a GW signal is represented in the frequency domain by a response function. Currently, the GW signal response is first expressed in terms of the Doppler frequency shift in a single detection arm, and this formulation is then incorporated into specific TDI combinations to derive the corresponding response function. This paper introduces a generalized formulation for TDI combinations based on multiple geometric links. By extending the representation of the laser Doppler frequency shift to include various geometric configurations, such as round-trip and non-round-trip links, we reformulate 45 second-generation TDI combinations. For several of these, the new formulation significantly streamlines their mathematical expressions and enhances physical clarity. Our results demonstrate that the proposed link-mapping rules not only enable efficient construction of response functions for these TDI combinations but also reduce computational complexity. This approach provides a reliable theoretical and algorithmic foundation for data processing in future space-borne GW missions.

gr-qc

NO molecule in massive star forming regions

Context. Among diatomic molecules composed of the abundant elements C, N and O, NO has been detected far less than the well studied CN and CO, making it a crucial yet under-observed component in nitrogen-containing chemical networks. NO was thought to serve as a potential tracer of shocks, as evidenced with orders abundance enhancements reported in literature. Aims. Large-sample observations for NO molecule in widespread interstellar environments are needed to confirm if the enhancement of NO is due to shock chemistry or not. Methods. Single-point survey for NO lines around 150 GHz was carried out by Arizona Radio Observatory 12-meter telescope towards a sample of 36 massive star forming regions containing SiO emission, which include three evolutionary stages: 4 IRDCs, 6 protostars and 26 H II regions. Results. The NO emission was detected in 28 sources with a detection rate of 78%. Beam-averaged NO column densities and abundances relative to H2 were derived from integrated intensities of two main hyperfine lines. Correlations between NO and SiO in integrated intensity and relative abundance are similar to the corresponding correlations of c-C3H2, indicating that NO enrichment may not significantly involve pronounced shock activities, which coincides with the trend in line widths: NO is close to c-C3H2, both smaller than H2CO and far smaller than SiO. Conclusions. Observational evidence does not strongly support significant NO enhancement by shock chemistry in the observed sources, indicating that the formation of NO does not necessarily require shocks.

astro-ph.GA

Macroscopic Quantum Interference in Dark Matter Wave Scattering with MICROSCOPE

Ultralight dark matter behaves as a coherent wave, yet its quantum interference effects of elastic scattering with multiple targets have remained unexplored. We show that the nested test masses of MICROSCOPE realize such an ``interferometer'' for dark-matter wave scattering. Amplitudes from the two concentric cylinders interfere and redistribute the induced force between them. This effect produces unique and rotation-modulated signals set by the target geometry. Developing the theoretical framework and applying it to MICROSCOPE data, we obtain leading constraints on quadratic dark-matter--nucleon coupling for masses $10^{-3}$--$10^{-2}\,$eV, reaching cross sections of order $10^{-52}$ cm$^2$.

hep-ph

Random Polarization Position Angle Behaviors across Bursts of Repeating Fast Radio Bursts

Fast radio bursts (FRBs), highly polarized, mostly have a nearly constant polarization position angle (PA) during each burst. Their PAs are observed to vary from burst to burst, with the statistical properties remaining stable across different observation sessions. We found that the intrinsic PAs of repeating FRBs are approximately Gaussian distributed, suggesting that the emission likely originates from a localized region within the neutron star's magnetosphere. A periodicity search of the PA time series using the Lomb-Scargle periodogram reveals no credible periodic signal in the period range from 10 ms to $10^7$ ms, and similar analyses of several active observations also yield null detections. We interpret these properties by extending the rotating vector model to include a dynamically evolving magnetosphere, in which the effective magnetic axis varies from burst to burst due to stochastic perturbations. In this framework, the observed PA distributions can naturally arise from geometric projection effects, and the absence of periodicity reflects the random wandering of the magnetic axis within a confined region. This scenario provides a natural explanation for both repeating and apparently non-repeating FRBs.

astro-ph.HE

On the Difference Between Pulsar Radio Emission Beams from the Two Poles

The long-standing assumption of symmetric radio emission beams from the two magnetic poles of pulsars is challenged by observational evidence of asymmetry and underfill. Direct testing of this symmetry remains difficult for most pulsars. As an indirect test, we collected polarization profiles of 11 interpulse pulsars observed with the Five-hundred-meter Aperture Spherical radio Telescope, MeerKAT, and Parkes. We developed a rotating vector model incorporating aberration and retardation effects to fit the position angle swings of selected pulsars, thereby determining the intrinsic emission region corresponding to the observed pulse windows. Based on both the conal and fan beam models, we compared three key parameters-beam radius, magnetic azimuth width, and emission intensity-between the intrinsic emission regions of the main pulse and interpulse. Among the eight pulsars with a confirmed double-pole geometry, none exhibits similarity in the azimuth width. Only two show potentially similar beam radii, while six demonstrate comparable emission intensities within specific parameter spaces. These results indicate that the emission beams from the two magnetic poles of a pulsar may be generally dissimilar in size, suggesting that the physical conditions governing pair production and particle acceleration differ between the two poles. The random distribution of active emission regions further implies inhomogeneity within the polar cap, which may originate from the differences in local magnetic field structure or surface properties.

astro-ph.HE

Control Barrier Functions Solved with Hierarchical Quadratic Programming for Safe Physical Human-Robot Interaction

Physical human-robot interaction offers the potential to leverage human intelligence and robot physical capabilities to enable a range of exciting applications, e.g., collaborative robots for rehabilitation. Safety is critical for the successful deployment of this kind of robotic system. In recent years, Control Barrier Function (CBF) has emerged as an effective approach to enforce safety guarantees, which has been widely applied in various applications, from adaptive cruise control to navigation of legged robots. CBFs can be solved in a Quadratic Programming (QP) problem, which can include many CBF-formulated tasks. To manage a large number of safety tasks, a hierarchical CBF has been used to allow hierarchical relaxation of safety tasks to ensure the feasibility of a solution in the presence of conflicting tasks. In this work, we propose to use a CBF-based Hierarchical Quadratic Programming (HQP) framework in physical human-robot interaction to allow us to design both performance tasks (e.g., preserve the desired behavior at the human-robot interaction point) and safety tasks at any level of a hierarchy to balance the safety and the performance in a more flexible way. Extensive experiments were carried out on a real redundant robot to validate the effectiveness, flexibility, and generality of this approach.

cs.RO

To understand the radiative processes of pulsars and fast radio bursts with the FAST

The radiative mechanism of coherent radio emission has remained an enigma since the discovery of pulsars, even the emergence of fast radio bursts (FRBs), which exhibit similarities to the single-pulse behavior of pulsars and have opened a new view for deciphering the long-standing mystery. Besides tremendous efforts in modelling, advanced facilities matter for solving the problem. The authors review the observational breakthroughs from the Five-hundred-meter Aperture Spherical radio Telescope (FAST), which are providing pivotal insights to unravel the underlying physics of pulsars and FRBs. This study offers a novel perspective in the era when pulsars meet FRBs, and further investigations are encouraged to utilize the highly sensitive telescope, the FAST.

astro-ph.HE

FAST Polarization Catalog of FRB 20240114A

Polarization measurements of fast radio bursts (FRBs) probe the magnetized plasma surrounding their central engines. FRB~20240114A is an exceptionally active repeating source, with 17,356 bursts detected between 2024 January 28 and 2025 May 30 by FAST, enabling time-resolved polarimetric studies. In this work, we present a polarimetric catalog of 6,131 bright bursts (with a signal-to-noise ratio S/N $\geq$ 20, 35.3% of the total sample), including arrival time (MJD$_{\text{topo}}$), dispersion measure (DM), burst width (W$_{\text{eff}}$), bandwidth, Faraday rotation measure (RM), linear and circular polarization degrees (DOL, DOC), and intrinsic polarization angle (PA$_0$). We detect a clear temporal evolution of RM: after an initial stable phase, it decreases linearly by $\sim$200 $\rm rad\ m^{-2}$ over 200 days, forming a bimodal distribution, whereas DM remains stable at 528.9 $\rm pc\ cm^{-3}$. The linear polarization fraction is generally high, with the 3$\sigma$ lower bound around 76%, while circular polarization is low, with 1,157 of 17,356 bursts (6.67%) having DOC $\geq$10%. We perform a power-law fit between $|\textrm{V}|$/I and $|\textrm{RM}|$, which yields an index of $-2.98 \pm 0.80$. It is found that the combined 2D distribution of L/I versus V/I remains stable, implying that the emission mechanism is largely invariant. Our PA$_0$ measurements show a broad, non-uniform distribution, implying a complex emission geometry. These results suggest that FRB~20240114A resides in a dynamically evolving magneto-ionic environment. This catalog provides a foundation for studies of repeating FRB progenitors and their environments.

astro-ph.HE

The Impact of Dark Matter on Gravitational Wave Detection by Space-based Interferometers

The existence of dark matter is supported by multiple astrophysical observations, yet its particle nature remains unknown. The development of gravitational wave astronomy, especially with future space-based detectors such as LISA, provides new opportunities to study the interactions between dark matter and compact-object systems. This review summarizes the main dark matter candidates and their macroscopic distributions, and highlights three mechanisms through which dark matter can affect gravitational wave observations: (1) modifications to compact-object orbits and the dynamics of systems such as extreme mass-ratio inspirals, including dark matter spikes, dynamical friction, and potential perturbations; (2) gravitational lensing effects induced by the spatial distribution of dark matter, altering waveform amplitudes and phases; and (3) direct couplings between ultralight dark matter fields and detectors. As low-frequency gravitational wave detection techniques are proposed and continue to develop, these effects may offer a novel avenue for probing the properties of dark matter, and combining precise waveform modeling with multi-messenger observations could reveal insights into its microscopic structure.

astro-ph.CO

Co-optimization for Adaptive Conformal Prediction

Conformal prediction (CP) provides finite-sample, distribution-free marginal coverage, but standard conformal regression intervals can be inefficient under heteroscedasticity and skewness. In particular, popular constructions such as conformalized quantile regression (CQR) often inherit a fixed notion of center and enforce equal-tailed errors, which can displace the interval away from high-density regions and produce unnecessarily wide sets. We propose Co-optimization for Adaptive Conformal Prediction (CoCP), a framework that learns prediction intervals by jointly optimizing a center $m(x)$ and a radius $h(x)$.CoCP alternates between (i) learning $h(x)$ via quantile regression on the folded absolute residual around the current center, and (ii) refining $m(x)$ with a differentiable soft-coverage objective whose gradients concentrate near the current boundaries, effectively correcting mis-centering without estimating the full conditional density. Finite-sample marginal validity is guaranteed by split-conformal calibration with a normalized nonconformity score. Theory characterizes the population fixed point of the soft objective and shows that, under standard regularity conditions, CoCP asymptotically approaches the length-minimizing conditional interval at the target coverage level as the estimation error and smoothing vanish. Experiments on synthetic and real benchmarks demonstrate that CoCP yields consistently shorter intervals and achieves state-of-the-art conditional-coverage diagnostics.

stat.ML

Detection of Cyclotron Absorption in the Radio Emission of GPM 1839-10

GPM 1839-10 is an intriguing long-period radio transient (LPT), distinguished by its activity spanning at least three decades and its highly unusual emission characteristics. These features include orthogonal polarization mode (OPM) switches, down-drifting sub-structures, and distinct linear-to-circular polarization conversion behaviors. In this work, we present follow-up observations utilizing the FAST telescope at L-band, yielding a total of seven detected radio pulses. We find a consistent association between OPM switches and a decrease in polarized intensity. This feature strongly supports the hypothesis that the OPM switches are generated by the incoherent summation of OPMs. Our measured Rotation Measures (RMs) are consistent with previous observations, indicating that the magneto-ionic environment is stable. If the source is in a binary system, such stability suggests it may host a weakly magnetized companion. Crucially, we firstly observe clear evidence of a cyclotron absorption feature in one radio pulse, a signature rarely observed in radio sources. This feature allows us to infer that the magnetic field strength at the absorption site has a lower limit of tens of Gauss, which is necessary for the phenomenon to occur. This characteristic can be explained in a scenario where GPM 1839-10 possesses a weakly magnetized companion star.

astro-ph.HE

GhostCite: A Large-Scale Analysis of Citation Validity in the Age of Large Language Models

Citations provide the basis for trusting scientific claims; when they are invalid or fabricated, this trust collapses. With the advent of Large Language Models (LLMs), this risk has intensified: LLMs are increasingly used for academic writing, but their tendency to fabricate citations (``ghost citations'') poses a systemic threat to citation validity. To quantify this threat, we develop \citeb, an open-source framework for large-scale citation verification, and conduct a comprehensive study of citation validity in the LLM era through three complementary experiments. First, we benchmark 13 LLMs on citation generation task in various research domains, finding that all models hallucinate citations at rate from 14.23\% to 94.93\%. Second, we analyze 2.2 million citations from 56,381 papers at AI/ML and Security venues (2020--2025), finding that 1.07\% of papers contain invalid citations, with an 80.9\% increase in 2025. Third, we survey 97 researchers, finding that 87.2\% use AI-powered tools in their workflows, 76.7\% of reviewers do not thoroughly check references, and 74.5\% view peer review as ineffective at catching citation errors. Based on these findings, we argue that ghost citations represent a systemic threat to academic integrity, and call for coordinated efforts from community to address this challenge.

cs.CR

Fast Conformal Prediction using Conditional Interquantile Intervals

We introduce Conformal Interquantile Regression (CIR), a conformal regression method that efficiently constructs near-minimal prediction intervals with guaranteed coverage. CIR leverages black-box machine learning models to estimate outcome distributions through interquantile ranges, transforming these estimates into compact prediction intervals while achieving approximate conditional coverage. We further propose CIR+ (Conditional Interquantile Regression with More Comparison), which enhances CIR by incorporating a width-based selection rule for interquantile intervals. This refinement yields narrower prediction intervals while maintaining comparable coverage, though at the cost of slightly increased computational time. Both methods address key limitations of existing distributional conformal prediction approaches: they handle skewed distributions more effectively than Conformalized Quantile Regression, and they achieve substantially higher computational efficiency than Conformal Histogram Regression by eliminating the need for histogram construction. Extensive experiments on synthetic and real-world datasets demonstrate that our methods optimally balance predictive accuracy and computational efficiency compared to existing approaches.

stat.ML