Tootfinder

Spontaneous emission in dipole approximation -- revisited
Paul R. Berman, Peter W. Milonni
https://arxiv.org/abs/2507.14075 https://a…

Spontaneous emission in dipole approximation -- revisited
Spontaneous emission in dipole approximation is studied theoretically using both source-field theory and a Schrodinger picture approach. Using source-field theory we obtain formal equations for the Poynting vector and energy density without making the rotating wave approximation (RWA) and Weisskopf-Wigner approximation (WWA). The initial condition at t=0 is one in which the atom is in an excited state and the field in the vacuum state. The source-field expressions are evaluated within the the R…

Domain Generalization for Person Re-identification: A Survey Towards Domain-Agnostic Person Matching
Hyeonseo Lee, Juhyun Park, Jihyong Oh, Chanho Eom
https://arxiv.org/abs/2506.12413

Domain Generalization for Person Re-identification: A Survey Towards Domain-Agnostic Person Matching
Person Re-identification (ReID) aims to retrieve images of the same individual captured across non-overlapping camera views, making it a critical component of intelligent surveillance systems. Traditional ReID methods assume that the training and test domains share similar characteristics and primarily focus on learning discriminative features within a given domain. However, they often fail to generalize to unseen domains due to domain shifts caused by variations in viewpoint, background, and l…

An Observation on Lloyd's k-Means Algorithm in High Dimensions
David Silva-S\'anchez, Roy R. Lederman
https://arxiv.org/abs/2506.14952 https://

An Observation on Lloyd's k-Means Algorithm in High Dimensions
Clustering and estimating cluster means are core problems in statistics and machine learning, with k-means and Expectation Maximization (EM) being two widely used algorithms. In this work, we provide a theoretical explanation for the failure of k-means in high-dimensional settings with high noise and limited sample sizes, using a simple Gaussian Mixture Model (GMM). We identify regimes where, with high probability, almost every partition of the data becomes a fixed point of the k-means algorith…

Intrinsic and Extrinsic Organized Attention: Softmax Invariance and Network Sparsity
Oluwadamilola Fasina, Ruben V. C. Pohle, Pei-Chun Su, Ronald R. Coifman
https://arxiv.org/abs/2506.15541

Intrinsic and Extrinsic Organized Attention: Softmax Invariance and Network Sparsity
We examine the intrinsic (within the attention head) and extrinsic (amongst the attention heads) structure of the self-attention mechanism in transformers. Theoretical evidence for invariance of the self-attention mechanism to softmax activation is obtained by appealing to paradifferential calculus, (and is supported by computational examples), which relies on the intrinsic organization of the attention heads. Furthermore, we use an existing methodology for hierarchical organization of tensors …

Jeg er nŸdt til at få overbevist venner, familie og kolleger om at komme med over på Signal el. lign.! I min Messenger-app kom der lige info om at Meta har ændret deres betingelser for behandling af personoplysninger, men at man kan gŸre indsigelse mod det.
Men uanset hvor jeg klikker mig hen, kommer der intet link frem til den indsigelsesformular de henviser til! De gŸr alt hvad de kan for at gŸre det umuligt. Grrrr!!! 🤬
(Se alt-tekst for mere info om hvor skidt det virker, d…

"These meetings are distracting me from the work."
The meetings are the work. Sorry.
The fact that your org doesn't value meetings and doesn't put any effort into making them more effective is a symptom of a broader pattern of ignoring feminized "glue work" in favor of Big Masculine Outputs.
Making the work visible is the first step towards making it valued.

The glue is the work
Tech orgs only function thanks to people who volunteer for thankless "glue work." This is the space where UX lives; for the field to get respect we need to make this work visible.

Thought Purity: Defense Paradigm For Chain-of-Thought Attack
Zihao Xue, Zhen Bi, Long Ma, Zhenlin Hu, Yan Wang, Zhenfang Liu, Qing Sheng, Jie Xiao, Jungang Lou
https://arxiv.org/abs/2507.12314

Thought Purity: Defense Paradigm For Chain-of-Thought Attack
While reinforcement learning-trained Large Reasoning Models (LRMs, e.g., Deepseek-R1) demonstrate advanced reasoning capabilities in the evolving Large Language Models (LLMs) domain, their susceptibility to security threats remains a critical vulnerability. This weakness is particularly evident in Chain-of-Thought (CoT) generation processes, where adversarial methods like backdoor prompt attacks can systematically subvert the model's core reasoning mechanisms. The emerging Chain-of-Thought Atta…

Emulation of Self-Consistent Non-Hermitian Quantum Formalisms
Mario Gonzalez, Karin Sim, R. Chitra
https://arxiv.org/abs/2507.13078 https://

Emulation of Self-Consistent Non-Hermitian Quantum Formalisms
Standard quantum mechanics predicts the non-conservation of state norms and probability when the fundamental requirement of the Hermiticity of the Hamiltonian is relaxed. Biorthogonal quantum mechanics, or the more general metric formalism, provides a rigorous formulation of non-Hermitian quantum mechanics wherein norms and probabilities are conserved. The key feature is that the Hilbert space is endowed with a non-trivial dynamical metric. Beyond theoretical considerations, the physical implem…

A retrospective on DISPEED -- Leveraging heterogeneity in a drone swarm for IDS execution
Vincent Lannurien, Cam\'elia Slimani, Louis Morge-Rollet, Laurent Lemarchand, David Espes, Fr\'ed\'eric Le Roy, Jalil Boukhobza
https://arxiv.org/abs/2506.11800

A retrospective on DISPEED -- Leveraging heterogeneity in a drone swarm for IDS execution
Swarms of drones are gaining more and more autonomy and efficiency during their missions. However, security threats can disrupt their missions' progression. To overcome this problem, Network Intrusion Detection Systems ((N)IDS) are promising solutions to detect malicious behavior on network traffic. However, modern NIDS rely on resource-hungry machine learning techniques, that can be difficult to deploy on a swarm of drones. The goal of the DISPEED project is to leverage the heterogeneity (exec…

Off-Policy Evaluation Under Nonignorable Missing Data
Han Wang, Yang Xu, Wenbin Lu, Rui Song
https://arxiv.org/abs/2507.06961 https://

Off-Policy Evaluation Under Nonignorable Missing Data
Off-Policy Evaluation (OPE) aims to estimate the value of a target policy using offline data collected from potentially different policies. In real-world applications, however, logged data often suffers from missingness. While OPE has been extensively studied in the literature, a theoretical understanding of how missing data affects OPE results remains unclear. In this paper, we investigate OPE in the presence of monotone missingness and theoretically demonstrate that the value estimates remain…