Tootfinder

Russland droht Ukraine mit Vergeltung
Nach ukrainischen Angriffen auf Luftwaffenstützpunkte, die teils weit im russischen Hinterland befinden, hat der stellvertretende Vorsitzende des nationalen Sicherheitsrates, Dmitri Medwedew mit Gegenschlägen gedroht. "Vergeltung ist unvermeidlich", schrieb er auf Telegram.
Mit Blick auf die gestrigen Gespräche zwischen der russischen und der ukrainischen Delegation in der Türkei betonte…
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Ukraine-Liveblog: ++ Ukraine-Verbündete beraten über weitere Hilfen ++
Auf Einladung Deutschlands und Großbritanniens kommt am Mittwoch die sogenannte Ramstein-Gruppe zusammen, um über weitere Hilfen für die Ukraine zu beraten - die USA nehmen nicht teil. Moskau fordert die Anerkennung der eroberten Gebiete.

Agile laser wavelength tuning using dynamic targeting
Robbe de Mey, Spencer W. Jolly, Alexandre Locquet, Martin Virte
https://arxiv.org/abs/2506.02861 http…

Agile laser wavelength tuning using dynamic targeting
Tunable lasers are essential and versatile tools in photonics, with applications spanning telecommunications, spectroscopy, and sensing. Advancements have aimed to expand tuning ranges, suppress mode hopping, and enable photonic integration. In this work, we explore the adaptation of dynamic targeting, a technique originally developed to stabilize lasers under optical feedback, as a method for achieving agile, fast, and continuous wavelength tuning. By adjusting the feedback rate and phase, we …

Optimization by VarQITE on Adaptive Variational Quantum Kolmogorov-Arnold Network
Hikaru Wakaura, Rahmat Mulyawan, Andriyan B. Suksmono
https://arxiv.org/abs/2506.22801

Optimization by VarQITE on Adaptive Variational Quantum Kolmogorov-Arnold Network
Quantum imaginary time evolution (QITE) is a powerful method to derive the ground states of the systems. Only the damping of quantum states leads it; hence, reaching the ground state is guaranteed by nature without any external manipulation. Numerous QITE methods by many groups are used to improve speed and accuracy, derive excited states, and solve combined optimization problems. However, the QITE methods have not been used for quantum machine learning to predict the ideal values for multiple …

Skill-Nav: Enhanced Navigation with Versatile Quadrupedal Locomotion via Waypoint Interface
Dewei Wang, Chenjia Ba, Chenhui Li, Jiyuan Shi, Yan Ding, Chi Zhang, Bin Zhao
https://arxiv.org/abs/2506.21853

Skill-Nav: Enhanced Navigation with Versatile Quadrupedal Locomotion via Waypoint Interface
Quadrupedal robots have demonstrated exceptional locomotion capabilities through Reinforcement Learning (RL), including extreme parkour maneuvers. However, integrating locomotion skills with navigation in quadrupedal robots has not been fully investigated, which holds promise for enhancing long-distance movement capabilities. In this paper, we propose Skill-Nav, a method that incorporates quadrupedal locomotion skills into a hierarchical navigation framework using waypoints as an interface. Spe…

SurgPIS: Surgical-instrument-level Instances and Part-level Semantics for Weakly-supervised Part-aware Instance Segmentation
Meng Wei, Charlie Budd, Oluwatosin Alabi, Miaojing Shi, Tom Vercauteren
https://arxiv.org/abs/2507.19592

SurgPIS: Surgical-instrument-level Instances and Part-level Semantics for Weakly-supervised Part-aware Instance Segmentation
Consistent surgical instrument segmentation is critical for automation in robot-assisted surgery. Yet, existing methods only treat instrument-level instance segmentation (IIS) or part-level semantic segmentation (PSS) separately, without interaction between these tasks. In this work, we formulate a surgical tool segmentation as a unified part-aware instance segmentation (PIS) problem and introduce SurgPIS, the first PIS model for surgical instruments. Our method adopts a transformer-based mask …

Matrix-Free Evaluation of High-Order Shifted Boundary Finite Element Operators
Micha{\l} Wichrowski
https://arxiv.org/abs/2507.17053 https://arxiv.org/pdf/…

Matrix-Free Evaluation of High-Order Shifted Boundary Finite Element Operators
This paper presents a matrix-free approach for implementing the shifted boundary method (SBM) in finite element analysis. The SBM is a versatile technique for solving partial differential equations on complex geometries by shifting boundary conditions to nearby surrogate boundaries. We focus on the efficient evaluation of shifted boundary operators using precomputed data and tensor-product structures. The proposed method avoids the explicit assembly of global matrices, achieving a computational…

Russland kümmert Ultimatum laut Medwedew nicht
Der Vize-Vorsitzende des russischen Sicherheitsrates, Dmitri Medwedew, hat die Sanktions- und Zolldrohung von US-Präsident Donald Trump als "theatralisches Ultimatum" zurückgewiesen, um das sich die Führung in Moskau nicht schere. "Trump hat dem Kreml ein theatralisches Ultimatum gestellt. Die Welt schauderte und erwartete die Konsequenzen", schreibt der Vertraute von Präsident W…
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Ukraine-Liveblog: ++ Rutte fordert von China Druck auf Putin ++
NATO-Generalsekretär Rutte hat an China, Indien und Brasilien appelliert, Druck auf Russland auszuüben - andernfalls würden Sekundärsanktionen drohen. Die EU-Länder verlängern ihren Schutz für Ukrainer bis 2027.

Replaced article(s) found for physics.ins-det. https://arxiv.org/list/physics.ins-det/new
[1/1]:
- A versatile experimental method to measure the traction forces at interfaces
Yingwei Hou, Tao Liu

General theory of perturbation of infinite resistor networks
J\'ozsef Cserti, Gyula D\'avid
https://arxiv.org/abs/2506.18654 https://

General theory of perturbation of infinite resistor networks
The effective resistance between any two nodes in a perturbed resistor network is determined by removing multiple bonds from an infinite resistor lattice. We have developed an efficient method for calculating the Green operator of the Laplacian for such perturbed networks, which is directly related to the two-point resistance. Unlike the recursive techniques that remove bonds one at a time, our approach handles all bond modifications simultaneously. To demonstrate the versatility of our m…

Local Dense Logit Relations for Enhanced Knowledge Distillation
Liuchi Xu, Kang Liu, Jinshuai Liu, Lu Wang, Lisheng Xu, Jun Cheng
https://arxiv.org/abs/2507.15911

Local Dense Logit Relations for Enhanced Knowledge Distillation
State-of-the-art logit distillation methods exhibit versatility, simplicity, and efficiency. Despite the advances, existing studies have yet to delve thoroughly into fine-grained relationships within logit knowledge. In this paper, we propose Local Dense Relational Logit Distillation (LDRLD), a novel method that captures inter-class relationships through recursively decoupling and recombining logit information, thereby providing more detailed and clearer insights for student learning. To furthe…