Tootfinder

Search for Dark Matter Scattering from Optically Levitated Nanoparticles
Yu-Han Tseng, T. W. Penny, Benjamin Siegel, Jiaxiang Wang, David C. Moore
https://arxiv.org/abs/2508.00815

Search for Dark Matter Scattering from Optically Levitated Nanoparticles
The development of levitated optomechanics has enabled precise force sensors that operate in the quantum measurement regime, opening up unique opportunities to search for new physics whose weak interactions may have evaded existing sensors. We demonstrate the detection of impulsive forces acting on optically levitated nanoparticles, where the dominant noise source is provided by measurement backaction. Using these sensors, we search for momentum transfers that may originate from scattering of p…

Unifi3D: A Study on 3D Representations for Generation and Reconstruction in a Common Framework
Nina Wiedemann, Sainan Liu, Quentin Leboutet, Katelyn Gao, Benjamin Ummenhofer, Michael Paulitsch, Kai Yuan
https://arxiv.org/abs/2509.02474

Unifi3D: A Study on 3D Representations for Generation and Reconstruction in a Common Framework
Following rapid advancements in text and image generation, research has increasingly shifted towards 3D generation. Unlike the well-established pixel-based representation in images, 3D representations remain diverse and fragmented, encompassing a wide variety of approaches such as voxel grids, neural radiance fields, signed distance functions, point clouds, or octrees, each offering distinct advantages and limitations. In this work, we present a unified evaluation framework designed to assess t…

Back to the Features: DINO as a Foundation for Video World Models
Federico Baldassarre, Marc Szafraniec, Basile Terver, Vasil Khalidov, Francisco Massa, Yann LeCun, Patrick Labatut, Maximilian Seitzer, Piotr Bojanowski
https://arxiv.org/abs/2507.19468

Back to the Features: DINO as a Foundation for Video World Models
We present DINO-world, a powerful generalist video world model trained to predict future frames in the latent space of DINOv2. By leveraging a pre-trained image encoder and training a future predictor on a large-scale uncurated video dataset, DINO-world learns the temporal dynamics of diverse scenes, from driving and indoor scenes to simulated environments. We show that DINO-world outperforms previous models on a variety of video prediction benchmarks, e.g. segmentation and depth forecasting, a…

Neutralization of Levitated Charged Nanodiamond: Towards matter-wave interferometry with massive objects
Sela Liran, Or Dobkowski, Rafael Benjaminov, Peter Skakunenko, Michael Averbukh, Yaniv Bar-Haim, David Groswasser, Joshua H. Baraban, Ron Folman
https://arxiv.org/abs/2508.15625

Neutralization of Levitated Charged Nanodiamond: Towards matter-wave interferometry with massive objects
Quantum mechanics (QM) and General relativity (GR), also known as the theory of gravity, are the two pillars of modern physics. A matter-wave interferometer with a massive particle, can test numerous fundamental ideas, including the spatial superposition principle - a foundational concept in QM - in completely new regimes, as well as the interface between QM and GR, e.g., testing the quantization of gravity. Consequently, there exists an intensive effort to realize such an interferometer. While…