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Adams Building along Stoney Street, Nottingham, September 2023
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Period matrices and homological quasi-trees on discrete Riemann surfaces
Wai Yeung Lam, On-Hei Solomon Lo, Chi Ho Yuen
https://arxiv.org/abs/2506.02317 htt…

Period matrices and homological quasi-trees on discrete Riemann surfaces
We study discrete period matrices associated with graphs cellularly embedded on closed surfaces, resembling classical period matrices of Riemann surfaces. Defined via integrals of discrete harmonic 1-forms, these period matrices are known to encode discrete conformal structure in the sense of circle patterns. We obtain a combinatorial interpretation of the discrete period matrix, where its minors correspond to weighted sums over certain spanning subgraphs, which we call homological quasi-trees.…

Decoupling Local Electrostatic Potential and Temperature-Driven Atomistic Forming Mechanisms in TaOx/HfO2-Based ReRAMs using Reactive Molecular Dynamics Simulations
Simanta Lahkar, Valeria Bragaglia, Behnaz Bagheri, Donato Francesco Falcone, Matteo Galetta, Marilyne Sousa, Aida Todri-Sanial
https://arxiv.org/abs/2505.24468

Decoupling Local Electrostatic Potential and Temperature-Driven Atomistic Forming Mechanisms in TaOx/HfO2-Based ReRAMs using Reactive Molecular Dynamics Simulations
Resistive random access memories (ReRAMs) with a bilayer TaOx/HfO2 stack structure have been shown to possess uniquely promising resistive switching characteristics. However, the key atomistic forming mechanisms and the physical processes that govern the behavior of this kind of device remain to be clarified. Here, we present a detailed analysis of the physical mechanisms underlying its forming at the atomistic level through molecular dynamics (MD) simulations using an extended charge equilibra…

State-aware protein-ligand complex prediction using AlphaFold3 with purified sequences
Enming Xing, Junjie Zhang, Shen Wang, Xiaolin Cheng
https://arxiv.org/abs/2506.00147

State-aware protein-ligand complex prediction using AlphaFold3 with purified sequences
Deep learning-based prediction of protein-ligand complexes has advanced significantly with the development of architectures such as AlphaFold3, Boltz-1, Chai-1, Protenix, and NeuralPlexer. Multiple sequence alignment (MSA) has been a key input, providing coevolutionary information critical for structural inference. However, recent benchmarks reveal a major limitation: these models often memorize ligand poses from training data and perform poorly on novel chemotypes or dynamic binding events inv…

Adams Building, Nottingham, September 2023
#photography #ukphotographer #nottingham #monochrome

Adams Building, Nottingham, September 2023
#photography #ukphotographer #nottingham #monochrome