arXiv subjects

Zijin Zhang

Publications and source records attributed to Zijin Zhang.

3 recordsLinked to original sources

arXiv2026

Properties of current sheets in two-dimensional tearing-mediated incompressible magnetohydrodynamic turbulence

It is well known that the nonlinear evolution of magnetohydrodynamic (MHD) turbulence generates current sheets. In the solar wind turbulence, current sheets are frequently observed and they are believed to be an important pathway for the turbulence energy to dissipate and heat the plasma. In this study, we perform a comprehensive analysis of current sheets in a high-resolution two-dimensional simulation of balanced, incompressible MHD turbulence. The simulation parameters are selected such that tearing mode instability is triggered and plasmoids are generated throughout the simulation domain. We develop an automated method to identify current sheets and accurately quantify their key parameters including thickness ($a$), length ($L$), and Lundquist number ($S$). Before the triggering of tearing instability, the current sheet lengths are mostly comparable to the energy injection scale. After the tearing mode onsets, smaller current sheets with lower Lundquist numbers are generated. While power-law scaling relations between $L$ and $a$ and between $a/L$ and $S$ are observed, no clear correlation is found between the upstream magnetic field strength and thickness $a$. Finally, although the turbulence energy shows anisotropy between the directions parallel and perpendicular to the local magnetic field increment, we do not observe a direct correspondence between the shape of the current sheets and that of the turbulence ``eddies.'' These results suggest that one needs to be cautious when applying the scale-dependent dynamic alignment model to the analysis of current sheets in MHD turbulence.

astro-ph.SR↗

arXiv2026

Multi-LLM Query Optimization

Deploying multiple large language models (LLMs) in parallel to classify an unknown ground-truth label is a common practice, yet the problem of optimally allocating queries across heterogeneous models remains poorly understood. In this paper, we formulate a robust, offline query-planning problem that minimizes total query cost subject to statewise error constraints which guarantee reliability for every possible ground-truth label. We first establish that this problem is NP-hard via a reduction from the minimum-weight set cover problem. To overcome this intractability, we develop a surrogate by combining a union bound decomposition of the multi-class error into pairwise comparisons with Chernoff-type concentration bounds. The resulting surrogate admits a closed-form, multiplicatively separable expression in the query counts and is guaranteed to be feasibility-preserving. We further show that the surrogate is asymptotically tight at the optimization level: the ratio of surrogate-optimal cost to true optimal cost converges to one as error tolerances shrink, with an explicit rate of $O\left(\log\log(1/α_{\min}) / \log(1/α_{\min})\right)$. Finally, we design an asymptotic fully polynomial-time approximation scheme (AFPTAS) that returns a surrogate-feasible query plan within a $(1+\varepsilon)$ factor of the surrogate optimum.

cs.DS↗

arXiv2023

A Search for Technosignatures Around 11,680 Stars with the Green Bank Telescope at 1.15-1.73 GHz

We conducted a search for narrowband radio signals over four observing sessions in 2020-2023 with the L-band receiver (1.15-1.73 GHz) of the 100 m diameter Green Bank Telescope. We pointed the telescope in the directions of 62 TESS Objects of Interest, capturing radio emissions from a total of ~11,680 stars and planetary systems in the ~9 arcminute beam of the telescope. All detections were either automatically rejected or visually inspected and confirmed to be of anthropogenic nature. In this work, we also quantified the end-to-end efficiency of radio SETI pipelines with a signal injection and recovery analysis. The UCLA SETI pipeline recovers 94.0% of the injected signals over the usable frequency range of the receiver and 98.7% of the injections when regions of dense RFI are excluded. In another pipeline that uses incoherent sums of 51 consecutive spectra, the recovery rate is ~15 times smaller at ~6%. The pipeline efficiency affects calculations of transmitter prevalence and SETI search volume. Accordingly, we developed an improved Drake Figure of Merit and a formalism to place upper limits on transmitter prevalence that take the pipeline efficiency and transmitter duty cycle into account. Based on our observations, we can state at the 95% confidence level that fewer than 6.6% of stars within 100 pc host a transmitter that is detectable in our search (EIRP > 1e13 W). For stars within 20,000 ly, the fraction of stars with detectable transmitters (EIRP > 5e16 W) is at most 3e-4. Finally, we showed that the UCLA SETI pipeline natively detects the signals detected with AI techniques by Ma et al. (2023).

astro-ph.IM↗