Tootfinder

Transverse relative locality effects in de Sitter spacetime
Giuseppe Fabiano, Domenico Frattulillo
https://arxiv.org/abs/2507.13192 https://

Transverse relative locality effects in de Sitter spacetime
Doubly Special Relativity (DSR) models are characterized by the deformation of relativistic symmetries at the Planck scale and constitute one of the cornerstones for quantum gravity phenomenology research, due to the possibility of testing them with cosmological messengers. Some of their predictions manifest themselves as relative locality effects, implying that events local to an observer might not appear to be so for a distant one. In this work we focus on transverse relative locality models,…

Deceptive Path Planning: A Bayesian Game Approach
Violetta Rostobaya, James Berneburg, Yue Guan, Michael Dorothy, Daigo Shishika
https://arxiv.org/abs/2506.13650

Deceptive Path Planning: A Bayesian Game Approach
This paper investigates how an autonomous agent can transmit information through its motion in an adversarial setting. We consider scenarios where an agent must reach its goal while deceiving an intelligent observer about its destination. We model this interaction as a dynamic Bayesian game between a mobile Attacker with a privately known goal and a Defender who infers the Attacker's intent to allocate defensive resources effectively. We use Perfect Bayesian Nash Equilibrium (PBNE) as our solut…

Observers and Timekeepers: From the Page-Wootters Mechanism to the Gravitational Path Integral
Zixia Wei
https://arxiv.org/abs/2506.21489 https://

Observers and Timekeepers: From the Page-Wootters Mechanism to the Gravitational Path Integral
Quantum gravity in a closed universe faces two a priori distinct yet seemingly related issues: the problem of time and the fact that its Hilbert space dimension is one. Both have been argued to be resolvable by formulating physics relative to an observer. Using a simple gravitational path integral model, we explain that the two issues arise from two distinct non-perturbative effects: the former from summing over metrics and the latter from summing over topologies. We then revisit the Page-Woott…

Designing Robust Software Sensors for Nonlinear Systems via Neural Networks and Adaptive Sliding Mode Control
Ayoub Farkane, Mohamed Boutayeb, Mustapha Oudani, Mounir Ghogho
https://arxiv.org/abs/2507.06817

Designing Robust Software Sensors for Nonlinear Systems via Neural Networks and Adaptive Sliding Mode Control
Accurate knowledge of the state variables in a dynamical system is critical for effective control, diagnosis, and supervision, especially when direct measurements of all states are infeasible. This paper presents a novel approach to designing software sensors for nonlinear dynamical systems expressed in their most general form. Unlike traditional model-based observers that rely on explicit transformations or linearization, the proposed framework integrates neural networks with adaptive Sliding …