arXiv subjects

Yi Zheng

Publications and source records attributed to Yi Zheng.

At least 55 records · Page 3Linked to original sources

arXiv2026

First Cosmological Constraints from the Joint Analysis of Galaxy Clustering and the Kinetic Sunyaev-Zel'dovich Effect

We perform the first joint analysis of galaxy clustering (GC) and the kinetic Sunyaev-Zel'dovich (kSZ) effect to simultaneously constrain cosmological and astrophysical parameters in this work, utilizing a combination of the Atacama Cosmology Telescope (ACT) Data Release 6 (DR6) map and the Constant Stellar Mass (CMASS) galaxy sample. As a complementary probe to the galaxy density power spectrum, we incorporate the pairwise kSZ power spectrum detected with a high signal-to-noise ratio (S/N $\sim 7$) to derive constraints on cosmological parameters ($H_0 = 70.82^{+4.94}_{-5.01}$, $Ω_{\rm m} = 0.290^{+0.092}_{-0.068}$, $w_0 = -1.038^{+0.245}_{-0.437}$) and the average optical depth of the galaxy sample ($\lg\barτ = -4.24 \pm 0.10$). Compared to the GC-only analysis, the joint analysis yields tighter constraints on these cosmological parameters: the Figures of Merit improve by 20.5\%, 19.7\% and 10.0\% for the $H_0$--$Ω_{\rm m}$, $H_0$--$w_0$ and $Ω_{\rm m}$--$w_0$ contours, respectively. For the first time, we demonstrate the complementary applicability of the kSZ effect in constraining cosmological parameters from real observational data.

astro-ph.CO↗

arXiv2026

Observation of robust macroscale structural superlubricity

Structural superlubricity (SSL) promises nearly frictionless and wearless sliding, but has until now been considered a special and extreme interfacial phenomenon limited to micro- and nanoscale contacts. Here, we demonstrate robust macroscale SSL within a single sub-millimeter graphite contact. Previously reported near-zero friction coefficients, where friction is nearly independent of normal load, have only been observed at microscale contacts under low loads. Our system expands both contact size and load into the macroscopic regime, exhibiting friction coefficients that fluctuate around zero and reach values as low as $10^{-6}$ across a broad load range from 1 mN to 0.5 N. Negative friction coefficients are also observed. Similar behavior is observed at graphite/MoS$_2$ interfaces, indicating that macroscale SSL is a generalizable phenomenon across flat layered materials. These findings overturn long-standing scaling limitations and establish macroscale SSL as a paradigm-shifting platform for next-generation mechanical and electromechanical systems.

cond-mat.mtrl-sci↗

arXiv2025

Octave-spanning, deterministic single soliton generation in 4H-silicon carbide-on-insulator microring resonators

The miniaturization of self-referencing frequency comb systems enables emerging applications in metrology and spectroscopy. One major challenge in realizing the chip-scale self-referencing function is to generate octave-spanning soliton microcombs with low operation power. Accessing soliton states is also not trivial due to the thermal effect. Though an auxiliary laser was utilized to compensate for the thermal effect, deterministic single soliton generation is still elusive, especially for broadband operation. In this work, dispersion management is performed for a 4H-silicon carbide-on-insulator (SiCOI) multi-mode microring resonator, benefiting from the submicron-confinement waveguide layout. The fundamental transverse electric (TE) mode is engineered to anomalous dispersion for two dispersive waves generation over an octave span. While a higher order TE mode is engineered to normal dispersion to accommodate the auxiliary light for thermal compensation. The normal dispersion prevents modulation-instability Kerr comb generation, allowing for a large soliton existence range. We achieve microring resonators with Q up to 5.8 million and sub-milli-watt-threshold Kerr comb generation. Combining the dispersion-managed design and high Q device, we demonstrate the deterministic generation of a single soliton comb spanning beyond an octave with a low on-chip power of 60 mW. Our demonstration paves the way to realize chip-scale, turn-key, self-referenced frequency combs.

physics.optics↗

arXiv2025

Breaking the bandwidth-efficiency trade-off in soliton microcombs via mode coupling

Dissipative Kerr solitons in optical microresonators have emerged as a powerful tool for compact and coherent frequency comb generation. Advances in nanofabrication have allowed precise dispersion engineering, unlocking octave-spanning soliton combs that are essential for applications such as optical atomic clocks, frequency synthesis, precision spectroscopy, and astronomical spectrometer calibration. However, a key challenge hindering their practical deployment is the intrinsic bandwidth-efficiency trade-off: achieving broadband soliton generation requires large pump detuning, which suppresses power coupling and limits pump-to-comb conversion efficiencies to only a few percent. Recent efforts using pulsed pumping or coupled-resonator architectures have improved efficiency to several tens of percent, yet their bandwidths remain below one-tenth of an octave, inadequate for applications demanding wide spectral coverage. Here, we overcome this limitation by harnessing mode interactions between spatial modes within a single microresonator. The mode hybridization creates an additional power-transfer channel that supports large pump detuning while maintaining strong pump-to-resonator coupling, enabling broadband soliton formation at substantially reduced pump power. Using this approach, we demonstrate an octave-spanning soliton microcomb with a record pump-to-comb conversion efficiency exceeding 50%. These results resolve the fundamental bandwidth-efficiency dilemma in soliton microcombs and paves the way toward fully-integrated, high-efficiency, ultrabroad comb sources for next-generation photonic systems.

physics.optics↗

arXiv2025

Adiabatic pumping of topological corner states by coherent tunneling in a 2D SSH model

The active manipulation of topologically protected states represents a pivotal frontier for quantum technologies, offering a unique confluence of topological robustness and precise quantum control. We propose an adiabatic pumping scheme for the long-range transfer of topological corner states in a two-dimensional Su-Schrieffer-Heeger model. The protocol utilizes a modular lattice architecture composed of four topologically distinct subblocks, enabling the modulation of a topological dark state by precise tuning of lattice couplings. This approach is based on coherent tunneling by adiabatic passage among topological corner and interface states. We establish a multi-level model for the adiabatic pumping that provides an accurate description of the underlying mechanism. In comparison with a sequential two-stage Thouless pumping, our protocol offers superior performance in both transfer fidelity and efficiency.

quant-ph↗

arXiv2025

DRUM: Diffusion-based runoff model for probabilistic flood forecasting

Extreme floods pose escalating risks in a changing climate, yet forecasting remains challenging due to peak flow underestimation and high uncertainty. We introduce DRUM, a diffusion-based probabilistic deep learning approach that advances extreme flood forecasting across representative basins in the contiguous United States. DRUM outperforms state-of-the-art benchmarks, enhancing nowcasting skill for the top 0.1% of flows in 72.3% of studied basins. Under operational scenarios, DRUM extends reliable lead times by nearly a full day for 20- and 50-year floods. When evaluated with measured precipitation, an ideal condition, recall improves by 0.3-0.4 and the early warning window extends by 2.3 days for 50-year floods. The enhancement potential varies regionally, with precipitation-driven flood zones in the eastern and northwestern U.S. benefiting most, gaining 3-7 days in lead time. These findings highlight the transformative potential of diffusion models as a cutting-edge generative AI technique for advancing hydrology and broader Earth system sciences.

physics.geo-ph↗

arXiv2025

Testing the Equivalence Principle on Cosmological Scales Using Peculiar Acceleration Power Spectrum

While the (weak) Equivalence Principle (EP) has been rigorously tested within the solar system, its validity on cosmological scales, particularly in the context of dark matter and dark energy, remains uncertain. In this study, we propose a novel method to test EP on cosmological scales by measuring the peculiar acceleration power spectrum of galaxies using the redshift drift technique. We develop an EP estimator, $E_{\rm ep}$, to evaluate the consistency of the peculiar acceleration power spectrum across different tracers. By calculating the ratio of the peculiar acceleration power spectra of tracers, the ensemble average of $E_{\rm ep}$ is expected to be unity if EP holds on cosmological scales for these tracers. We validate this estimator using N-body simulations, focusing on four redshift bins with $z\leq 1.5$ and scales of $k$ in the range of $0.007$ and $0.2$ $h/\rm Mpc$. By fitting a single parameter $δ_{\rm ep}$ across redshifts, we find that DM particle mocks without EP violation yield $δ_{\rm ep}$ consistent with zero under the small redshift measurement uncertainty case, while the large redshift uncertainty case slightly induces biases at low redshifts. In addition, when using DM halo mocks with controlled EP violations, no-violation and mild-violation cases show no significant detection, while moderate and strong violations produce statistically significant $δ_{\rm ep}$ values and high $χ^2$, especially at low redshifts, confirming the estimator's sensitivity. Taking advantage of advanced observing capabilities, such as next-generation facilities that extend beyond the Square Kilometer Array, the proposed method offers a promising approach for future cosmological tests of EP.

astro-ph.CO↗

arXiv2025

Constraining the Baryon Content of Cosmic Filaments Using Localized Fast Radio Bursts and DESI Imaging Data

Cosmic filaments are thought to host a substantial fraction of the missing baryons at redshifts $z<2$. In this study, we constraint the baryonic content of these filaments using localized Fast Radio Bursts (FRBs). Filaments are identified from the galaxy distribution in the Dark Energy Spectroscopic Instrument (DESI) imaging surveys using the DisPerSE algorithm. We find tentative evidence ($\sim 3 σ$ significance) for a divergence in the relationship between the dispersion measure (DM) contributed by the intergalactic medium and redshift for FRBs whose signals intersect cosmic filaments compared to those that do not, suggesting excess baryons in the filamentary structures. Assuming an isothermal $β$-model gas profile with $β=2/3$, this discrepancy is best explained by a central baryon overdensity of $δ_0 = 21^{+13}_{-12}$, broadly consistent with previous simulation and observational results. The inferred baryon fraction residing in filaments decreases with redshift, from approximately $0.25$-$0.30\,Ω_b$ at $z=0.02$ to $0.15$-$0.30\,Ω_b$ at $z=0.5$, and $0.03$-$0.04\,Ω_b$ at $z=0.8$. These estimates are likely lower bounds, particularly at $z>0.5$, due to the limited number of identified filaments and localized FRBs at higher redshifts. We also examine various factors that may affect the statistical significance of our results. Our method offers an independent approach to tracing baryons in cosmic filaments and underscores the importance of expanding localized FRB samples and deepening galaxy surveys, i.e., key steps toward refining these estimates and addressing the missing baryon problem.

astro-ph.CO↗

arXiv2025

Nonlinear-linear duality for multipath quantum interference

In quantum optics, the postselection amplitude of a nondegenerate parametric down-conversion (PDC) process is linked to a beamsplitter (BS) via partial time reversal, up to a normalization coefficient which is related to the parametric gain [Proc. Natl. Acad. Sci. USA 117, 33107 (2020)]. A special example where the gain is low is reminiscent of Klyshko's advanced-wave picture in quantum imaging. Here, we propose and prove a generalized duality for multiple spatial paths connecting a quantum nonlinear interference setup consisting of nondegenerate PDCs and linear optical systems to a linear one, where the PDCs are directly replaced by hypothetical wavelength-shifting BSs. This replacement preserves the geometry of the original setup, and cascaded PDCs become optical cavities whose calculation involves the Redheffer star product. Additional terms in the normalization coefficient are related to the contribution of looping photons inside the cavities. Then, we discuss the case of coherent state input and postselection for $Q$-function calculation. This theorem will be helpful in the development of quantum photonic devices beyond the low-gain limit.

quant-ph↗

arXiv2025

Practical security of local local oscillator continuous-variable quantum key distribution systems with pulse width mismatch

In continuous-variable quantum key distribution (CVQKD) systems, using a local local oscillator (LLO) scheme removes the local oscillator side channel, enhances Bob's detection performance and reduces the excess noise caused by photon leakage, thereby effectively improves the system's security and performance. However, in this scheme, since the signal and the LO are generated by different lasers and the signal propagates through the untrusted quantum channel, their pulse widths may become mismatched. Such mismatches may reduce the precision of detection at Bob, affecting parameter estimation processes and leading to inaccurate calculations of the secret key rate. Moreover, mismatches may introduce potential security loopholes. Thus, this paper investigates the practical security issues of the LLO-CVQKD system when pulse width mismatch occurs between the local oscillator and the signal. We first model the case of pulse width mismatch and analyze its impact on Bob's detection. Then, we simulate the secret key rate under different mismatch levels. Based on the analysis, we find that under such mismatch, the key parameters involved in secret key rate calculation are incorrectly estimated, leading to an overestimation of the system's secret key rate. Therefore, this imperfect mismatch can open a loophole for Eve to perform attacks in practical systems. To close this loophole, we design a scheme at Bob to monitor the pulse widths of both the signal and the local oscillator, and to reshape the waveform of the local oscillator so that the two lights are matched again. This method eliminates the adverse effects caused by pulse width mismatch and effectively resists Eve's attacks which exploit this loophole.

quant-ph↗

arXiv2025

HERO: Rethinking Visual Token Early Dropping in High-Resolution Large Vision-Language Models

By cropping high-resolution images into local tiles and encoding them independently, High-Resolution Large Vision-Language Models (HR-LVLMs) have demonstrated remarkable fine-grained visual understanding capabilities. However, this divide-and-conquer paradigm significantly increases the number of visual tokens, resulting in substantial computational and memory overhead. To better understand and address this challenge, we empirically investigate visual token utilization in HR-LVLMs and uncover three key findings: (1) the local tiles have varying importance, jointly determined by visual saliency and task relevance; (2) the CLS token in CLIP-based vision encoders exhibits a two-stage attention pattern across layers, with each stage attending to different types of visual tokens; (3) the visual tokens emphasized at different stages encode information at varying levels of granularity, playing complementary roles within LVLMs. Building on these insights, we propose HERO, a High-resolution visual token early dropping framework that integrates content-adaptive token budget allocation with function-aware token selection. By accurately estimating tile-level importance and selectively retaining visual tokens with complementary roles, HERO achieves superior efficiency-accuracy trade-offs across diverse benchmarks and model scales, all in a training-free manner. This study provides both empirical insights and practical solutions toward efficient inference in HR-LVLMs.

cs.CV↗

arXiv2025

Pyramid Token Pruning for High-Resolution Large Vision-Language Models via Region, Token, and Instruction-Guided Importance

Large Vision-Language Models (LVLMs) have recently demonstrated strong multimodal understanding, yet their fine-grained visual perception is often constrained by low input resolutions. A common remedy is to partition high-resolution images into multiple sub-images for separate encoding, but this approach drastically inflates the number of visual tokens and introduces prohibitive inference overhead. To overcome this challenge, we propose Pyramid Token Pruning (PTP), a training-free strategy that hierarchically integrates bottom-up visual saliency at both region and token levels with top-down instruction-guided relevance. Inspired by human visual cognition, PTP selectively preserves more tokens from salient regions while further emphasizing those most relevant to task instructions. Extensive experiments on 13 diverse benchmarks show that PTP substantially reduces computational cost, memory usage, and inference latency, with negligible performance degradation.

cs.CV↗

arXiv2025

Half-order Fine-Tuning for Diffusion Model: A Recursive Likelihood Ratio Optimizer

The probabilistic diffusion model (DM), generating content by inferencing through a recursive chain structure, has emerged as a powerful framework for visual generation. After pre-training on enormous data, the model needs to be properly aligned to meet requirements for downstream applications. How to efficiently align the foundation DM is a crucial task. Contemporary methods are either based on Reinforcement Learning (RL) or truncated Backpropagation (BP). However, RL and truncated BP suffer from low sample efficiency and biased gradient estimation, respectively, resulting in limited improvement or, even worse, complete training failure. To overcome the challenges, we propose the Recursive Likelihood Ratio (RLR) optimizer, a Half-Order (HO) fine-tuning paradigm for DM. The HO gradient estimator enables the computation graph rearrangement within the recursive diffusive chain, making the RLR's gradient estimator an unbiased one with lower variance than other methods. We theoretically investigate the bias, variance, and convergence of our method. Extensive experiments are conducted on image and video generation to validate the superiority of the RLR. Furthermore, we propose a novel prompt technique that is natural for the RLR to achieve a synergistic effect.

cs.CV↗

arXiv2025

Exploring Magnetic Phases in Dual-Species Mott insulating Spinor Lattice Gases

We explore the Mott insulating phases of dual-species bosonic spinor lattice gases, emphasizing the intriguing interplay between synthetic flux and inter-species spin exchange interaction. One of the species is subjected to Raman assisted tunneling, which leads to a synthetic flux within the framework of synthetic dimensions. In the deep Mott regime, the low energy physics is governed by an unconventional and highly tunable spin model, which is characterized by two distinct spin chains. The synthetic flux serves as an effective spin-orbit coupling, inducing Dzyaloshinskii-Moriya interactions in one of the spin chains. The inter-species spin exchange interaction gives rise to the inter-chain coupling embodied as an isotropic XX interaction. Using time-evolving block decimation method for tensor network states, we compute order parameters, correlation functions and structure factors to identify the ground state magnetic phases. The DM interaction in one species, when combined with the inter-species spin-exchange interaction, can induce spiral magnetic order in the second, otherwise non-chiral species. Besides, the interplay of a transverse field applied to one spin chain and the inter-species coupling can drive both spin chains into a paramagnetic phase simultaneously. These results reveal that inter-species coupling serves as a powerful conduit for transmitting magnetic correlations, enabling exotic phases beyond the single-component perspective.

cond-mat.quant-gas↗

arXiv2025

Position-correlated biphoton wavefront sensing for quantum adaptive imaging

Quantum imaging with spatially entangled photons offers advantages such as enhanced spatial resolution, robustness against noise, and counter-intuitive phenomena, while a biphoton spatial aberration generally degrades its performance. Biphoton aberration correction has been achieved by using classical beams to detect the aberration source or scanning the correction phase on biphotons if the source is unreachable. Here, a new method named position-correlated biphoton Shack-Hartmann wavefront sensing is introduced, where the phase pattern added on photon pairs with a strong position correlation is reconstructed from their position centroid distribution at the back focal plane of a microlens array. Experimentally, biphoton phase measurement and adaptive imaging against the disturbance of a plastic film are demonstrated. This single-shot method is a more direct and efficient approach toward quantum adaptive optics, suitable for integration into quantum microscopy, remote imaging, and communication.

quant-ph↗

arXiv2025

Enhancing Optical Performance of Liquid Crystal Lens Arrays via Electrode Design Optimization

A liquid crystal (LC) lens array based on double-layer composite electrodes, characterized by a large aperture, short focal length, and low operating voltage is demonstrated. The lens array consists of an LC layer, a top common electrode, a bottom double-layer composite electrode layer, and an oxide layer. The bottom double-layer composite electrode layer comprises the pixel electrodes and the auxiliary electrode. In focusing mode, the pixel electrodes receive operational voltage to establish the LC layer's electric field, with the auxiliary electrode applying reduced voltage for field optimization. Experiment results show that the proposed LC lens array achieves the shortest focal length of 3.3 mm when the pixel electrodes are set at 5.2 Vrms and the auxiliary electrode is set at 2.6 Vrms. This design addresses the technical challenge of achieving larger apertures (800 μm or more), offering enhanced viewing zones and improved 3D performance. This configuration provides an ideal refractive index distribution in a relatively thick LC layer, enabling 2D/3D switchable display with performance superior to current LC lens arrays of equivalent aperture. Furthermore, the proposed structure demonstrates excellent tolerance to manufacturing errors.

physics.optics↗

arXiv2025

Adacc: An Adaptive Framework Unifying Compression and Activation Recomputation for LLM Training

Training large language models (LLMs) is often constrained by GPU memory limitations. To alleviate memory pressure, activation recomputation and data compression have been proposed as two major strategies. However, both approaches have limitations: recomputation introduces significant training overhead, while compression can lead to accuracy degradation and computational inefficiency when applied naively. In this paper, we propose Adacc, the first adaptive memory optimization framework that unifies activation recomputation and data compression to improve training efficiency for LLMs while preserving model accuracy. Unlike existing methods that apply static, rule-based strategies or rely solely on one technique, Adacc makes fine-grained, tensor-level decisions, dynamically selecting between recomputation, retention, and compression based on tensor characteristics and runtime hardware constraints. Adacc tackles three key challenges: (1) it introduces layer-specific compression algorithms that mitigate accuracy loss by accounting for outliers in LLM activations; (2) it employs a MILP-based scheduling policy to globally optimize memory strategies across layers; and (3) it integrates an adaptive policy evolution mechanism to update strategies during training in response to changing data distributions. Experimental results show that Adacc improves training throughput by 1.01x to 1.37x compared to state-of-the-art frameworks, while maintaining accuracy comparable to the baseline.

cs.LG↗

arXiv2025

On the width and profiles of cosmic filaments

We investigated the widths and profiles of cosmic filaments using the IllustrisTNG simulations. Filaments were identified with DisPerSE, using galaxy samples in simulations as input. Since the width of an individual filament can vary significantly along its spine, we divided each filament into segments with lengths between $1.5\,h^{-1}\,\mathrm{Mpc}$ and $2.5\,h^{-1}\,\mathrm{Mpc}$ and measure their properties. The typical width of these filament segments increases gradually from approximately $0.3\,\mathrm{Mpc}$ at redshift $z = 2.0$ to about $1.0-1.5\,\mathrm{Mpc}$ at $z = 0.0$. We find that the segment width correlates nearly linearly with the linear halo mass density, consistent with previous studies. A similar linear relation is observed between the segment width and the linear stellar mass density, providing a potential estimator for filament width. Furthermore, the density profiles of filaments with different widths exhibit self-similarity and can be described by a unified formula akin to the isothermal $β$-model. For segments with a given width, the rescaled density profiles show only mild evolution from $z = 2.0$ to $z = 0.0$. Within the filament width, the gas temperature decreases slowly from the center to the boundary, with thicker filaments generally containing hotter gas than thinner ones. These trends in filament width, density, and thermal profiles are consistently observed across the TNG50, TNG100, and TNG300 simulations, and align well with results from earlier studies. We briefly discuss the potential implications and applications of our findings.

astro-ph.CO↗