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Researcher profile

Jianyun Zhang

Jianyun Zhang contributes to research discovery and scholarly infrastructure.

ResearcherAffiliation not importedOpen to collaborate
eess.SPInformation Theorymath.ITArtificial Intelligencemath.GM

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Published work

4 published item(s)

preprint2026arXiv

KISS - Knowledge Infrastructure for Scientific Simulation: A Scaffolding for Agentic Earth Science

Process-based simulation models encode decades of scientific understanding across the Earth sciences, yet the communities most exposed to climate risk and resource scarcity are the least able to use them. Here, we introduce knowledge infrastructure (KI), an agent-actionable scaffold that externalizes expertise into validated modelling operators, staged domain protocols, and diagnostic recovery mechanisms. Across a 3,000-trial coupled-hydrology benchmark, agents equipped with KI produced physically plausible, verifiable end-to-end simulations in up to 84% of trials, while agents without KI plateaued below 40%. KI generalizes across disciplines. We packaged its construction into a Knowledge Dissection Toolkit (KDT) that autonomously produced KI enabling end-to-end agent execution of 117 additional process-based models across 14 Earth-science domains. Across all 119 KIs, modelling decisions and failure remedies converged despite different underlying physics, showing that operational expertise is structured and extractable rather than ad hoc. Demonstrations show KI-equipped agents lowering both the access barrier between non-specialist users and process-based simulation, and the integration barrier between modelling communities. Through this scaffold, process-based science can then evolve as a living scientific commons, answerable to whoever needs to know and extendable by whoever can contribute.

0 citations0 reviewsNo code linkedOpen access
preprint2021arXiv

Multi-Antenna Joint Radar and Communications: Precoder Optimization and Weighted Sum-Rate vs Probing Power Tradeoff

In order to further exploit the potential of joint multi-antenna radar-communication (RadCom) system, we propose two transmission techniques respectively based on separated and shared antenna deployments. Both techniques are designed to maximize the weighted sum rate (WSR) and the probing power at target's location under average power constraints at the antennas such that the system can simultaneously communicate with downlink users and detect the target within the same frequency band. Based on a Weighted Minimized Mean Square Errors (WMMSE) method, the separated deployment transmission is designed via semidefinite programming (SDP) while the shared deployment problem is solved by majorization-minimization (MM) algorithm. Numerical results show that the shared deployment outperforms the separated deployment in radar beamforming. The tradeoffs between WSR and probing power at target are compared among both proposed transmissions and two practically simpler dual-function implementations i.e., time division and frequency division. Results show that although the separated deployment enables spectrum sharing, it experiences a performance loss compared with frequency division, while the shared deployment outperforms both and surpasses time division in certain conditions.

0 citations0 reviewsNo code linkedOpen access
preprint2020arXiv

Rate-Splitting Multiple Access for Multi-Antenna Joint Communication and Radar Transmissions

Rate-Splitting Multiple Access (RSMA), relying on multi-antenna Rate-Splitting (RS) techniques, has emerged as a powerful strategy for multi-user multi-antenna systems. In this paper, RSMA is introduced as a unified multiple access for multi-antenna radar-communication (RadCom) system, where the base station has a dual communication and radar capability to simultaneously communicate with downlink users and probe detection signals to azimuth angles of interests. Using RS, messages are split into common and private parts, then encoded into common and private streams before being precoded and transmitted. We design the message split and the precoders for this RadCom system such that the Weighted Sum Rate (WSR) is maximized and the transmit beampattern is approximated to the desired radar beampattern under an average transmit power constraint at each antenna. We then propose a framework based on Alternating Direction Method of Multipliers (ADMM) to solve the complicated non-convex optimization problem. Results highlight the benefits of RSMA to unify RadCom transmissions and to manage the interference among radar and communications, over the conventional Space-Division Multiple Access (SDMA) technique.

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preprint2020arXiv

The Distribution of the Nontrivial Zeros of Riemann Zeta Function

We improve the estimation of the distribution of the nontrivial zeros of Riemann zeta function $ζ(σ+it)$ for sufficiently large $t$, which is based on an exact calculation of some special logarithmic integrals of nonvanishing $ζ(σ+it)$ along well-chosen contours. A special and single-valued coordinate transformation $s=τ(z)$ is chosen as the inverse of $z=χ(s)$, and the functional equation $ζ(s) = χ(s)ζ(1-s)$ is simplified as $G(z) = z\, G_-(\frac{1}{z})$ in the $z$ coordinate, where $G(z)=ζ(s)=ζ\circτ(z)$ and $G_-$ is the conjugated branch of $G$. Two types of special and symmetric contours $\partial D_ε^1$ and $\partial D_ε^2$ in the $s$ coordinate are specified, and improper logarithmic integrals of nonvanishing $ζ(s)$ along $\partial D_ε^1$ and $\partial D_ε^2$ can be calculated as $2πi$ and $0$ respectively, depending on the total increase in the argument of $z=χ(s)$. Any domains in the critical strip for sufficiently large $t$ can be covered by the domains $D_ε^1$ or $D_ε^2$, and the distribution of nontrivial zeros of $ζ(s)$ is revealed in the end, which is more subtle than Riemann's initial hypothesis and in rhythm with the argument of $χ(\frac{1}{2}+it)$.

0 citations0 reviewsNo code linkedOpen access