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Sparsity, Stress-Independence and Globally Linked Pairs in Graph Rigidity Theory
D\'aniel Garamv\"olgyi, Bill Jackson, Tibor Jord\'an
https://arxiv.org/abs/2509.03150

Sparsity, Stress-Independence and Globally Linked Pairs in Graph Rigidity Theory
A graph is $\mathcal{R}_d$-independent (resp. $\mathcal{R}_d$-connected) if its $d$-dimensional generic rigidity matroid is free (resp. connected). A result of Maxwell from 1867 implies that every $\mathcal{R}_d$-independent graph satisfies the sparsity condition $|E(H)|\leq d|V(H)|-\binom{d+1}{2}$ for all subgraphs $H$ with at least $d+1$ vertices. Several other families of graphs $G$ arising naturally in rigidity theory, such as minimally globally $d$-rigid graphs, are kno…

Relative discrepancy of hypergraphs
Diep Luong-Le, Tuan Tran, Dilong Yang
https://arxiv.org/abs/2506.23264 https://arxiv.org/pdf/2506…

Relative discrepancy of hypergraphs
Given $k$-uniform hypergraphs $G$ and $H$ on $n$ vertices with densities $p$ and $q$, their relative discrepancy is defined as $\hbox{disc}(G,H)=\max\big||E(G')\cap E(H')|-pq\binom{n}{k}\big|$, where the maximum ranges over all pairs $G',H'$ with $G'\cong G$, $H'\cong H$, and $V(G')=V(H')$. Let $\hbox{bs}(k)$ denote the smallest integer $m \ge 2$ such that any collection of $m$ $k$-uniform hypergraphs on $n$ vertices with moderate densities contains a pair $G,H$ for which $\…

BaMANI: Bayesian Multi-Algorithm causal Network Inference
Habibolla Latifizadeh, Anika C. Pirkey, Alanna Gould, David J. Klinke II
https://arxiv.org/abs/2508.11741 https://

BaMANI: Bayesian Multi-Algorithm causal Network Inference
Improved computational power has enabled different disciplines to predict causal relationships among modeled variables using Bayesian network inference. While many alternative algorithms have been proposed to improve the efficiency and reliability of network prediction, the predicted causal networks reflect the generative process but also bear an opaque imprint of the specific computational algorithm used. Following a ``wisdom of the crowds" strategy, we developed an ensemble learning approach …

Dichography: Two-frame Ultrafast Imaging from a Single Diffraction Pattern
Linos Hecht, Andre Al Haddad, Bj\"orn Bastian, Thomas M. Baumann, Johan Bielecki, Christoph Bostedt, Subhendu De, Alberto De Fanis, Simon Dold, Thomas Fennel, Fanny Goy, Christina Graf, Robert Hartmann, Georg Jakobs, Maximilian Joschko, Gregor Knopp, Katharina Kolatzki, Sivarama Krishnan, Bj\"orn Kruse, Asbj{\o}rn {\O}. L{\ae}gdsmand, Bruno Langbehn, Suddhasattwa Mandal, Tommaso Mazza, Michael Meyer, C…

Dichography: Two-frame Ultrafast Imaging from a Single Diffraction Pattern
X-ray free-electron lasers can nowadays deliver pairs of ultrabright, ultrashort light pulses with controllable delays at different photon energies. When combined with diffraction experiments, the interaction of these pulses with a sample at different times can produce two snapshots of an evolving system, enabling spatial and temporal resolution of ultrafast dynamics in nanomatter at and beyond the terahertz time scale. However, light detectors are orders of magnitude slower. The diffraction si…

Operational machine learning for park-scale irrigation to support urban cooling
Mesut Ko\c{c}yi\u{g}it, Bahman Javadi, Russell Thomson, Sebastian Pfautsch, Oliver Obst
https://arxiv.org/abs/2508.11700 …

Operational machine learning for park-scale irrigation to support urban cooling
Urban parks can mitigate local heat, yet irrigation control is usually tuned for water savings rather than cooling. We report on SIMPaCT (Smart Irrigation Management for Parks and Cool Towns), a park-scale deployment that links per-zone soil-moisture forecasts to overnight irrigation set-points in support of urban cooling. SIMPaCT ingests data from 202 soil-moisture sensors, 50 temperature-relative humidity (TRH) nodes, and 13 weather stations, and trains a per-sensor k-nearest neighbours (kNN)…

Stochastic Modeling of Filtration with Sieving in Graded Pore Networks
Binan Gu, Pejman Sanaei, Lou Kondic, Linda J. Cummings
https://arxiv.org/abs/2508.11820 https://

Stochastic Modeling of Filtration with Sieving in Graded Pore Networks
We model filtration of a feed solution, containing both small and large foulant particles, by a membrane filter. The membrane interior is modeled as a network of pores, allowing for the simultaneous adsorption of small particles and sieving of large particles, two fouling mechanisms typically observed during the early stages of commercial filtration applications. In our model, first-principles continuum partial differential equations model transport of the small particles and adsorptive fouling…

Competition Between Controllable Non-Radiative and Intrinsic Radiative Second-Order Recombination in Halide Perovskites
Dengyang Guo, Alan R. Bowman, Sebastian Gorgon, Changsoon Cho, Youngkwang Jung, Jiashang Zhao, Linjie Dai, Jaewang Park, Kyung Mun Yeom, Satyawan Nagane, Stuart Macpherson, Weidong Xu, Jun Hong Noh, Sang Il Seok, Tom Savenije, Samuel D. Stranks

Competition Between Controllable Non-Radiative and Intrinsic Radiative Second-Order Recombination in Halide Perovskites
Halide perovskite solar cells have demonstrated a rapid increase in power conversion efficiencies. Understanding and mitigating remaining carrier losses in halide perovskites is now crucial to enable further increases to approach their practical efficiency limits. Whilst the most widely known non-radiative recombination from solar cells relates to carrier trapping and is first order in carrier density, recent reports have revealed a non-radiative pathway that is second order. However, the origi…

Chiral quantum magnets with optically and catalytically active spin ladders
Bum Chul Park, Sung-Chul Kim, Dae Beom Lee, Young Kwang Kim, Bomin Kim, Sonny H. Rhim, Eunsoo Lee, Yongju Hong, Kwangyeol Lee, Sang Hyun Lee, Jessica Ma, Michal Sawczyk, Jun Lu, Jason Manassa, Nishkarsh Agarwal, Robert Hovden, Sung Ok Won, Min Jun Ko, Minkyu Park, Jiung Cho, Xiaoming Mao, Kai Sun, Young Keun Kim, Nicholas A. Kotov

Chiral quantum magnets with optically and catalytically active spin ladders
Chiral quantum magnets with spin-states separated by a large energy gap are technologically attractive but difficult to realize. Geometrically frustrated topological states with nanoscale chirality may offer a chemical pathway to such materials. However, room temperature spin misalignment, weakness of Dzyaloshinskii-Moriya interactions, and high energy requirements for lattice distortions set high physicochemical barriers for their realization. Here, we show that layered iron oxyhydroxides (LIO…