Tootfinder

Neural Feature Geometry Evolves as Discrete Ricci Flow
Moritz Hehl, Max von Renesse, Melanie Weber
https://arxiv.org/abs/2509.22362 https://arxiv.org/pdf/2…

Neural Feature Geometry Evolves as Discrete Ricci Flow
Deep neural networks learn feature representations via complex geometric transformations of the input data manifold. Despite the models' empirical success across domains, our understanding of neural feature representations is still incomplete. In this work we investigate neural feature geometry through the lens of discrete geometry. Since the input data manifold is typically unobserved, we approximate it using geometric graphs that encode local similarity structure. We provide theoretical resul…

I won’t stay silent because I’m not a man or a woman, I’m non-binary and gender-fluid.
:bisexual_pride: 🏳️‍⚧️ :genderfluid_flag: :nonbinary_flag: :heart_trans: 🏳️‍🌈
#Man #Woman #NonBinary

UniLat3D: Geometry-Appearance Unified Latents for Single-Stage 3D Generation
Guanjun Wu, Jiemin Fang, Chen Yang, Sikuang Li, Taoran Yi, Jia Lu, Zanwei Zhou, Jiazhong Cen, Lingxi Xie, Xiaopeng Zhang, Wei Wei, Wenyu Liu, Xinggang Wang, Qi Tian
https://arxiv.org/abs/2509.25079

UniLat3D: Geometry-Appearance Unified Latents for Single-Stage 3D Generation
High-fidelity 3D asset generation is crucial for various industries. While recent 3D pretrained models show strong capability in producing realistic content, most are built upon diffusion models and follow a two-stage pipeline that first generates geometry and then synthesizes appearance. Such a decoupled design tends to produce geometry-texture misalignment and non-negligible cost. In this paper, we propose UniLat3D, a unified framework that encodes geometry and appearance in a single latent s…

Composite nonadiabatic geometric quantum gates with optimization on superconducting circuits
Cheng-Yun Ding, Wan-Fang Liu, Li-Hua Zhang, Jian Zhou, Zheng-Yuan Xue
https://arxiv.org/abs/2509.24737

Composite nonadiabatic geometric quantum gates with optimization on superconducting circuits
Due to its fast and robust characteristics, nonadiabatic geometric quantum computation with various optimized techniques has received much attention. However, these strategies either require precise pulse control or can only mitigate partial systematic errors, hindering their experimental development. Here, we propose a scheme for optimized composite nonadiabatic geometric quantum gates (OCNGQGs), which can further enhance the gate performance of the composite nonadiabatic geometric scheme. Spe…

#Shoutout geht raus an #Bürgermeister Lars Keitel von den @…
In Friedrichsdorf sorgt eine neue

Nur weibliche Formen in Satzung: Gender-Zoff bei der Feuerwehr in Friedrichsdorf
Streit um geschlechtergerechte Sprache: In Friedrichsdorf sorgt eine Feuerwehr-Satzung, die nur noch weibliche Amtsbezeichnungen kennt, für reichlich Zündstoff zwischen Bürgermeister und CDU-Fraktion.

GeoSketch: A Neural-Symbolic Approach to Geometric Multimodal Reasoning with Auxiliary Line Construction and Affine Transformation
Shichao Weng, Zhiqiang Wang, Yuhua Zhou, Rui Lu, Ting Liu, Zhiyang Teng, Xiaozhang Liu, Hanmeng Liu
https://arxiv.org/abs/2509.22460

GeoSketch: A Neural-Symbolic Approach to Geometric Multimodal Reasoning with Auxiliary Line Construction and Affine Transformation
Geometric Problem Solving (GPS) poses a unique challenge for Multimodal Large Language Models (MLLMs), requiring not only the joint interpretation of text and diagrams but also iterative visuospatial reasoning. While existing approaches process diagrams as static images, they lack the capacity for dynamic manipulation - a core aspect of human geometric reasoning involving auxiliary line construction and affine transformations. We present GeoSketch, a neural-symbolic framework that recasts geome…

The combinatorial geometry of particle physics
Thomas Lam
https://arxiv.org/abs/2509.25372 https://arxiv.org/pdf/2509.25372

The combinatorial geometry of particle physics
Recent breakthroughs in the study of scattering amplitudes have uncovered profound and unexpected connections with combinatorial geometry. These connections range from classical structures -- such as polytopes, matroids, and Grassmannians -- to more modern developments including positroid varieties and the amplituhedron. Together they point toward the unifying framework of positive geometry, in which geometric domains canonically determine analytic functions governing scattering processes. This…

🔪 On design, analysis, and hybrid manufacturing of microstructured blade-like geometries
#manufacturing

On design, analysis, and hybrid manufacturing of microstructured blade-like geometries
With the evolution of new manufacturing technologies such as multi-material 3D printing, one can think of new type of objects that consist of considerably less, yet heterogeneous, material, consequently being porous, lighter and cheaper, while having the very same functionality as the original object when manufactured from one single solid material. We aim at questioning five decades of traditional paradigms in geometric CAD and focus at new generation of CAD objects that are not solid, but con…

From variational principles to geometry
Jordi Gaset Rif\`a
https://arxiv.org/abs/2509.22171 https://arxiv.org/pdf/2509.22171…

From variational principles to geometry
A method to construct a geometric structure with the same solutions as a given variational principle is presented. The method applies to large families of variational principles. In particular, the known results that assign cosymplectic geometry to Hamilton's principle and cocontact geometry to Herglotz's principle for regular Lagrangians are recovered. The unified Lagrangian-Hamiltonian formalism is also recovered via the absorption of the holonomy conditions. The method is applied to singular…

Sure, call me a :nonbinary_flag: #NonBinary, :genderfluid_flag: #GenderFluid person!