Tootfinder

The weather was too good to not run outside, and skip the treadmill last Thursday! First time running outside at my work running route this year after returning to the work FT this month, and it was spectacular!
Not expecting to hit a sub 8 minute mile, especially with my health issues, but if it happens, I'll be elated!
#running

Parallel Complexity of Depth-First-Search and Maximal path
Archit Chauhan, Samir Datta, M. Praveen
https://arxiv.org/abs/2506.14974 https://

Parallel Complexity of Depth-First-Search and Maximal path
Constructing a Depth First Search (DFS) tree is a fundamental graph problem, whose parallel complexity is still not settled. Reif showed parallel intractability of lex-first DFS. In contrast, randomized parallel algorithms (and more recently, deterministic quasipolynomial parallel algorithms) are known for constructing a DFS tree in general (di)graphs. However a deterministic parallel algorithm for DFS in general graphs remains an elusive goal. Working towards this, a series of works gave deter…

Six-DoF Hand-Based Teleoperation for Omnidirectional Aerial Robots
Jinjie Li, Jiaxuan Li, Kotaro Kaneko, Liming Shu, Moju Zhao
https://arxiv.org/abs/2506.15009

Six-DoF Hand-Based Teleoperation for Omnidirectional Aerial Robots
Omnidirectional aerial robots offer full 6-DoF independent control over position and orientation, making them popular for aerial manipulation. Although advancements in robotic autonomy, operating by human remains essential in complex aerial environments. Existing teleoperation approaches for multirotors fail to fully leverage the additional DoFs provided by omnidirectional rotation. Additionally, the dexterity of human fingers should be exploited for more engaged interaction. In this work, we p…

A Machine Learning Framework for Modeling Ensemble Properties of Atomically Disordered Materials
Zhenyao Fang, Ting-Wei Hsu, Qimin Yan
https://arxiv.org/abs/2506.15652

A Machine Learning Framework for Modeling Ensemble Properties of Atomically Disordered Materials
Disorder, though naturally present in experimental samples and strongly influencing a wide range of material phenomena, remains underexplored in first-principles studies due to the computational cost of sampling the large supercell and configurational space. The recent development of machine learning techniques, particularly graph neural networks (GNNs), has enabled the efficient and accurate predictions of complex material properties, offering promising tools for studying disordered systems. I…

Candidate Dark Galaxy-2: Validation and Analysis of an Almost Dark Galaxy in the Perseus Cluster
Dayi Li, Qing Liu, Gwendolyn Eadie, Roberto Abraham, Francine Marleau, William Harris, Pieter van Dokkum, Aaron Romanowsky, Shany Danieli, Patrick Brown, Alex Stringer
https://arxiv.org/abs/2506.15644…

Candidate Dark Galaxy-2: Validation and Analysis of an Almost Dark Galaxy in the Perseus Cluster
Candidate Dark Galaxy-2 (CDG-2) is a potential dark galaxy consisting of four globular clusters (GCs) in the Perseus cluster, first identified in Li et al. (2025) through a sophisticated statistical method. The method searched for over-densities of GCs from a \textit{Hubble Space Telescope} (\textit{HST}) survey targeting Perseus. Using the same \textit{HST} images and the new imaging data from the \textit{Euclid} survey, we report the detection of extremely faint but significant diffuse emissi…

Graffitti along the road downhill from Bertinoro castle taken while coming back from the daily morning run. Love & passion ;-)
#isws2025 #running #summerschool

An old friend of mine is a Hasher. Shout-out to Pollywaffle from Canberra. https://sudomakecake.com/@woollypigs/114640950327552671

Device Independent Quantum Key Activation
Bora Ulu, Nicolas Brunner, Mirjam Weilenmann
https://arxiv.org/abs/2506.09772 https://arxiv…

Device Independent Quantum Key Activation
Device-independent quantum key distribution (DIQKD) allows two distant parties to establish a secret key, based only on the observed Bell nonlocal distribution. It remains however, unclear what the minimal resources for enabling DIQKD are and how to maximize the key rate from a given distribution. In the present work, we consider a scenario where several copies of a given quantum distribution are jointly processed via a local and classical wiring operation. We find that, under few assumptions, …

From Sharpness to Better Generalization for Speech Deepfake Detection
Wen Huang, Xuechen Liu, Xin Wang, Junichi Yamagishi, Yanmin Qian
https://arxiv.org/abs/2506.11532

From Sharpness to Better Generalization for Speech Deepfake Detection
Generalization remains a critical challenge in speech deepfake detection (SDD). While various approaches aim to improve robustness, generalization is typically assessed through performance metrics like equal error rate without a theoretical framework to explain model performance. This work investigates sharpness as a theoretical proxy for generalization in SDD. We analyze how sharpness responds to domain shifts and find it increases in unseen conditions, indicating higher model sensitivity. Bas…