arXiv subjects

Dongwei Li

Publications and source records attributed to Dongwei Li.

At least 19 recordsLinked to original sources

arXiv2026

Explicit Full-Spark and Quantitatively Phase-Retrievable Gabor Windows via Algebraic Perturbations

We construct explicit finite Gabor windows whose orbits are simultaneously full spark and phase retrievable. In every cyclic dimension, algebraic specialization preserves all Gabor minors while removing every zero of the self-ambiguity function, thereby resolving the explicit simultaneous- construction problem arising in finite nilpotent-group phase retrieval. We isolate the underlying regularization principle: a sufficiently small algebraic perturbation transfers full spark from one seed while retaining an ambiguity gap from another. In every prime dimension $p\geq5$, this gives an explicit full-spark window with normalized ambiguity margin at least $c_0p^{-1/2}$, for an absolute constant $c_0>0$; the order is sharp by the finite Moyal identity. Chinese-remainder tensorization followed by the same regularization extends the $N^{-1/2}$ scale to squarefree cyclic dimensions having a bounded number of prime factors. The resulting full-data lifted intensity map has a dimension-independent lower stability bound on each such family. A second explicit seed gives a polynomial ambiguity margin, of order $N^{-2}$, in every cyclic dimension, and we prove that this order is sharp within the geometric-seed construction. We also identify why the sharper cubic-chirp argument itself cannot cross that boundary: the unmodified cubic chirp has systematic ambiguity zeros at every modulus $p^a$, $a\geq2$. For a smaller fixed character perturbation and $p\geq2^{14}$, we additionally prove uniform stability after a fixed fraction of arbitrary erasures on each fixed two-atom Gabor subspace. This last statement is deliberately local to one two-atom subspace and does not compare signals supported on different pairs.

math.FA↗

arXiv2026

Sharp Conditioning for Matrix Recovery by Finite Affine Orbits

Let $q=p^h$ be an odd prime power, and let the affine group $\mathbb F_q\rtimes\mathbb F_q^\times$ act through its canonical $(q-1)$-dimensional irreducible representation. Qualitative matrix recovery for these rank-one orbits is known. We determine sharp lower singular-value bounds for explicit real generating windows. First, we compute the exact least singular value for every nonnegative two-level window over $\mathbb F_{p^h}$ with $h\geq2$, and identify the unique optimizer when $q-1\geq10$. The resulting conditioning stays bounded away from zero on every fixed odd-characteristic tower and is within an explicit characteristic-dependent factor of the best possible value over all real windows. For every $q=3^h$, $h\geq2$, we construct a real three-level absolute-trace window (constant on the fibers of $\operatorname{Tr}_{\mathbb F_q/\mathbb F_3}$) whose least singular value is \[ \frac{q(\sqrt2-1)}{q(2-\sqrt2)-1}>\frac1{\sqrt2}. \] For the full class of real windows constant on the three trace classes, we reduce the least singular value to four scalar expressions and a symmetric $2\times2$ matrix. This yields the exact global optimum and all equality cases: the displayed trace window is uniquely optimal up to global sign and interchange of the two nonzero trace classes. Thus zero trace mean follows from optimality. The proof combines an explicit sum-of-squares identity, uniform quadratic-form certificates, and a finite-geometric block decomposition of the orbit measurement operator.

math.FA↗

arXiv2026

JoyAI-RA 0.1: A Foundation Model for Robotic Autonomy

Robotic autonomy in open-world environments is fundamentally limited by insufficient data diversity and poor cross-embodiment generalization. Existing robotic datasets are often limited in scale and task coverage, while relatively large differences across robot embodiments impede effective behavior knowledge transfer. To address these challenges, we propose JoyAI-RA, a vision-language-action (VLA) embodied foundation model tailored for generalizable robotic manipulation. JoyAI-RA presents a multi-source multi-level pretraining framework that integrates web data, large-scale egocentric human manipulation videos, simulation-generated trajectories, and real-robot data. Through training on heterogeneous multi-source data with explicit action-space unification, JoyAI-RA effectively bridges embodiment gaps, particularly between human manipulation and robotic control, thereby enhancing cross-embodiment behavior learning. JoyAI-RA outperforms state-of-the-art methods in both simulation and real-world benchmarks, especially on diverse tasks with generalization demands.

cs.RO↗

arXiv2026

Validating Computational Markers of Depressive Behavior: Cross-Linguistic Speech-Based Depression Detection with Neurophysiological Validation

Speech-based depression detection has shown promise as an objective diagnostic tool, yet the cross-linguistic robustness of acoustic markers and their neurobiological underpinnings remain underexplored. This study extends Cross-Data Multilevel Attention (CDMA) framework, initially validated on Italian, to investigate these dimensions using a Chinese Mandarin dataset with Electroencephalography (EEG) recordings. We systematically fuse read speech with spontaneous speech across different emotional valences (positive, neutral, negative) to investigate whether emotional arousal is a more critical factor than valence polarity in enhancing detection performance in speech. Additionally, we establish the first neurophysiological validation for a speech-based depression model by correlating its predictions with neural oscillatory patterns during emotional face processing. Our results demonstrate strong cross-linguistic generalizability of the CDMA framework, achieving state-of-the-art performance (F1-score up to 89.6%) on the Chinese dataset, which is comparable to the previous Italian validation. Critically, emotionally valenced speech (both positive and negative) significantly outperformed neutral speech. This comparable performance between positive and negative tasks supports the emotional arousal hypothesis. Most importantly, EEG analysis revealed significant correlations between the model's speech-derived depression estimates and neural oscillatory patterns (theta and alpha bands), demonstrating alignment with established neural markers of emotional dysregulation in depression. This alignment, combined with the model's cross-linguistic robustness, not only supports that the CDMA framework's approach is a universally applicable and neurobiologically validated strategy but also establishes a novel paradigm for the neurophysiological validation of computational mental health models.

eess.AS↗

arXiv2023

The Qitai Radio Telescope

This study presents a general outline of the Qitai radio telescope (QTT) project. Qitai, the site of the telescope, is a county of Xinjiang Uygur Autonomous Region of China, located in the east Tianshan Mountains at an elevation of about 1800 m. The QTT is a fully steerable, Gregorian type telescope with a standard parabolic main reflector of 110 m diameter. The QTT has adopted an um-brella support, homology-symmetric lightweight design. The main reflector is active so that the deformation caused by gravity can be corrected. The structural design aims to ultimately allow high-sensitivity observations from 150 MHz up to 115 GHz. To satisfy the requirements for early scientific goals, the QTT will be equipped with ultra-wideband receivers and large field-of-view mul-ti-beam receivers. A multi-function signal-processing system based on RFSoC and GPU processor chips will be developed. These will enable the QTT to operate in pulsar, spectral line, continuum and Very Long Baseline Interferometer (VLBI) observing modes. Electromagnetic compatibility (EMC) and radio frequency interference (RFI) control techniques are adopted throughout the system design. The QTT will form a world-class observational platform for the detection of low-frequency (nanoHertz) gravitational waves through pulsar timing array (PTA) techniques, pulsar surveys, the discovery of binary black-hole systems, and exploring dark matter and the origin of life in the universe.

astro-ph.IM↗

arXiv2022

Few-cycle vortex beam generated from self-compression of mid-infrared femtosecond vortex beam in thin plates

We demonstrate theoretically that few-cycle vortex beam with subterawatt peak power can be generated by self-compression of mid-infrared femtosecond vortex beam using the thin-plate scheme. The 3 μm femtosecond vortex beam with input duration of 90 fs is compressed to 15.1 fs with the vortex characteristics preserved. The conversion efficiency is as high as 91.5% and the peak power reaches 0.18 TW. The generation of the high-peak-power few-cycle vortex beam is owing to the proper spatiotemporal match by this novel scheme, where the spectrum is broadened enough, the negative group velocity dispersion can compensate the positive chirp induced by nonlinear effects, and multiple filamentation is inhibited for the keeping of the vortex characteristics. Our work will help to generate isolated attosecond vortices, opening a new perspective in ultrafast science.

physics.optics↗

arXiv2022

Cost-effective Land Cover Classification for Remote Sensing Images

Land cover maps are of vital importance to various fields such as land use policy development, ecosystem services, urban planning and agriculture monitoring, which are mainly generated from remote sensing image classification techniques. Traditional land cover classification usually needs tremendous computational resources, which often becomes a huge burden to the remote sensing community. Undoubtedly cloud computing is one of the best choices for land cover classification, however, if not managed properly, the computation cost on the cloud could be surprisingly high. Recently, cutting the unnecessary computation long tail has become a promising solution for saving the cost in the cloud. For land cover classification, it is generally not necessary to achieve the best accuracy and 85% can be regarded as a reliable land cover classification. Therefore, in this paper, we propose a framework for cost-effective remote sensing classification. Given the desired accuracy, the clustering algorithm can stop early for cost-saving whilst achieving sufficient accuracy for land cover image classification. Experimental results show that achieving 85%-99.9% accuracy needs only 27.34%-60.83% of the total cloud computation cost for achieving a 100% accuracy. To put it into perspective, for the US land cover classification example, the proposed approach can save over $1,593,490.18 for the government in each single-use when the desired accuracy is 90%.

cs.DC↗

arXiv2021

Fusion frames for operators and atomic systems

Recently, fusion frames and frames for operators were considered as generalizations of frames in Hilbert spaces. In this paper, we generalize some of the known results in frame theory to fusion frames related to a linear bounded operator K which we call K-fusion frames. We obtain new K-fusion frames by considering K-fusion frames with a class of bounded linear operators. We also study the stability of K-fusion frames under small perturbations. We further give some characterizations of atomic systems with subspace sequences.

math.FA↗

arXiv2021

Powerful supercontinuum vortices generated by femtosecond vortex beams with thin plates

We demonstrate numerically and experimentally the generation of powerful supercontinuum vortices from femtosecond vortex beams by using multiple thin fused silica plates. The supercontinuum vortices are shown to preserve the vortex phase profile of the initial beam for spectral components ranging from 500 nm to 1200 nm. The transfer of the vortex phase profile results from the inhibition of multiple filamentation and the preservation of vortex ring with relatively uniform intensity distribution by means of the thin-plate scheme, where the supercontinuum is mainly generated from the self-phase modulation and self-steepening effects. Our scheme works for vortex beams with different topological charges, which provides a simple and effective method to generate supercontinuum vortices with high power.

physics.optics↗

arXiv2019

Cutting the Unnecessary Long Tail: Cost-Effective Big Data Clustering in the Cloud

Clustering big data often requires tremendous computational resources where cloud computing is undoubtedly one of the promising solutions. However, the computation cost in the cloud can be unexpectedly high if it cannot be managed properly. The long tail phenomenon has been observed widely in the big data clustering area, which indicates that the majority of time is often consumed in the middle to late stages in the clustering process. In this research, we try to cut the unnecessary long tail in the clustering process to achieve a sufficiently satisfactory accuracy at the lowest possible computation cost. A novel approach is proposed to achieve cost-effective big data clustering in the cloud. By training the regression model with the sampling data, we can make widely used k-means and EM (Expectation-Maximization) algorithms stop automatically at an early point when the desired accuracy is obtained. Experiments are conducted on four popular data sets and the results demonstrate that both k-means and EM algorithms can achieve high cost-effectiveness in the cloud with our proposed approach. For example, in the case studies with the much more efficient k-means algorithm, we find that achieving a 99% accuracy needs only 47.71%-71.14% of the computation cost required for achieving a 100% accuracy while the less efficient EM algorithm needs 16.69%-32.04% of the computation cost. To put that into perspective, in the United States land use classification example, our approach can save up to $94,687.49 for the government in each use.

cs.DC↗

arXiv2019

On weaving frames in Hilbert spaces

In this paper, we obtain some new properties of weaving frames and present some conditions under which a family of frames is woven in Hilbert spaces. Some characterizations of weaving frames in terms of operators are given. We also give a condition associated with synthesis operators of frames such that the sequence of frames is woven. Finally, for a family of woven frames, we show that they are stable under invertible operators and small perturbations.

math.FA↗

arXiv2018

Splitting of operator for frame inequalities in Hilbert spaces

In this paper, we obtain a new type of inequalities for frames, which are parametrized by a parameter λ\in R . By suitable choices of λ, one obtains the previous results as special cases. Our new proof also makes the underlying mathematical structure that gives rise to these inequalities more transparent than previous approaches: Our proof shows that the main point is the splitting S = S1 + S2 of the positive denite frame operator S into the two positive semidenite operators S1 and S2 .

math.FA↗

arXiv2018

New inequalities for weaving frames in Hilbert spaces

In this paper, we establish Parseval identities and surprising new inequalities for weaving frames in Hilbert space, which involve scalar $λ\in\rs$. By suitable choices of $λ$, one obtains the previous results as special cases. Our results generalize and improve the remarkable results which have been obtained by Balan et al. and Găvruţa.

math.FA↗

arXiv2017

On weaving g-frames for Hilbert spaces

Weaving frames are powerful tools in wireless sensor networks and pre-processing signals. In this paper, we introduce the concept of weaving for g-frames in Hilbert spaces. We first give some properties of weaving g-frames and present two necessary conditions in terms of frame bounds for weaving g-frames. Then we study the properties of weakly woven g-frames and give a sufficient condition for weaving g-frames. It is shown that weakly woven is equivalent to woven. Two sufficient conditions for weaving g-Riesz bases are given. And a weaving equivalent of an unconditional g-basis for weaving g-Riesz bases is considered. Finally, we present Paley-Wiener-type perturbation results for weaving g-frames.

math.FA↗

arXiv2017

Generalized frames and controlled operators in Hilbert space

Controlled frames and g-frames were considered recently as generalizations of frames in Hilbert spaces. In this paper we generalize some of the known results in frame theory to controlled g-frames. We obtain some new properties of controlled g-frames and obtain new controlled g-frames by considering controlled g-frames for its components. And we obtain some new resolutions of the identity. Furthermore, we study the stabilities of controlled g-frames under small perturbations.

math.FA↗

arXiv2016

The properties of the Higgs bosons and Pair Production of the SM-like Higgs Boson in λ-SUSY at the LHC

Compared with the MSSM or the NMSSM with a low λ, λ-SUSY theory with a large λaround one has been deemed as a most natural realization of NMSSM. In this work, we treat the next-to-lightest CP-even Higgs boson as the SM-like Higgs boson in λ-SUSY and study the properties of the Higgs bosons and the pair production of the SM-like Higgs boson by considering various experiment constraints. We find that naturalness plays an important role in selecting the parameter space of λ-SUSY. In the most natural region of parameter space, the triple self coupling of the SM-like Higgs boson compared with its SM prediction may get enhanced by a factor about 7, and the most dominant contribution to the Higgs pair production comes from the triple self coupling of the SM-like Higgs boson and the production rate can be greatly enhanced, maximally 10 times larger than the SM prediction.

hep-ph↗

arXiv2014

Exploring the Higgs Sector of a Most Natural NMSSM and its Prediction on Higgs Pair Production at the LHC

As a most natural realization of the Next-to Minimal Supersymmetry Standard Model (NMSSM), λ-SUSY is parameterized by a large λ around one and a low tan$β$ below 10. In this work, we first scan the parameter space of λ-SUSY by considering various experimental constraints, including the limitation from the Higgs data updated by the ATLAS and CMS collaborations in the summer of 2014, then we study the properties of the Higgs bosons. We get two characteristic features of λ-SUSY in experimentally allowed parameter space. One is the triple self coupling of the SM-like Higgs boson may get enhanced by a factor over 10 in comparison with its SM prediction. The other is the pair production of the SM-like Higgs boson at the LHC may be two orders larger than its SM prediction. All these features seems to be unachievable in the Minimal Supersymmetric Standard Model and in the NMSSM with a low λ. Moreover, we also find that naturalness plays an important role in selecting the parameter space of λ-SUSY, and that the Higgs $χ^2$ obtained with the latest data is usually significantly smaller than before due to the more consistency of the two collaboration measurements.

hep-ph↗

arXiv2014

Higgs-strahlung production process e^+ e^- \to Z h at the future Higgs factory in the Minimal Dilaton Model

We investigate the Higgs-strahlung production process e^+ e^- \to Z h at the future Higgs factory such as TLEP by including radiative corrections in the Minimal Dilaton Model (MDM), which extends the SM by one singlet scalar called dilaton. We consider various theoretical and experimental constraints on the model, and perform fits to the Higgs data taken from ATLAS, CMS and CDF+D0. Then for the 1σsurviving samples, we calculate the MDM predictions on the inclusive production rate σ(e^+e^-\to Zh) at the 240-GeV Higgs factory, and also the signal rates of e^+e^-\to Zh with the Higgs boson decaying to b\bar b and γγ. We have following observations: (1) In the heavy dilaton scenario, the deviation of σ(e^+e^-\to Zh) from its SM prediction can vary from -15\% to 85\%, which mainly arises from the modification of the tree-level hZZ coupling and also the radiative correction induced by possibly large Higgs self-couplings. (2) The processes e^+e^-\to Zh at the Higgs factory and pp\to hh at 14-TeV LHC are complementary in limiting the MDM parameter space. Requiring the deviation of σ(e^+e^-\to Zh) from its SM prediction to be less than 1\% and that of σ(p p \to h h) to be less than 50\%, \tan θ_S in the MDM will be limited to be -0.1<\tanθ_S<0.3, and the deviations of the signal rates are constrained to be |R_{b\bar b}|<2\% and |R_{γγ}|<7\%. Especially, the Higgs self-coupling normalized to its SM prediction is now upper bounded by about 4. (3) In the light dilaton scenario, the deviation of σ(e^+e^-\to Zh) may reach -7\%, and requiring its size to be less than 1\% will result in 0<\tanθ_S<0.1, and -10\% < R_{b\bar b}, R_{γγ} < 1\%.

hep-ph↗