Tootfinder

This https://arxiv.org/abs/2505.14277 has been replaced.
initial toot: https://mastoxiv.page/@a…

Infrared markers of topological phase transitions in quantum spin Hall insulators
Using first principles techniques, we show that infrared optical response can be used to discriminate between the topological and the trivial phases of two-dimensional quantum spin Hall insulators (QSHI). We showcase germanene and jacutingaite, of recent experimental realization, as prototypical systems where the infrared spectrum is discontinuous across the transition, due to sudden and large discretized jumps of the value of Born effective charges (up to 2). For these materials, the topologic…

This https://arxiv.org/abs/2412.20738 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_…

SgrA* spin and mass estimates through the detection of multiple extremely large mass-ratio inspirals
We analyze the parameter estimation accuracy that can be achieved for the mass and spin of SgrA$^\ast$, the SMBH in our Galactic Center, by detecting multiple extremely large mass-ratio inspirals (XMRIs). XMRIs are formed by brown dwarfs (BD) inspiraling into a supermassive black hole (SMBH), thus emitting gravitational waves (GWs) inside the detection band of future space-based detectors such as LISA and TianQin. Theoretical estimates suggest the presence of approximately 10 XMRIs emitting det…

The Lock-in Hypothesis: Stagnation by Algorithm
Tianyi Alex Qiu, Zhonghao He, Tejasveer Chugh, Max Kleiman-Weiner
https://arxiv.org/abs/2506.06166 https://…

The Lock-in Hypothesis: Stagnation by Algorithm
The training and deployment of large language models (LLMs) create a feedback loop with human users: models learn human beliefs from data, reinforce these beliefs with generated content, reabsorb the reinforced beliefs, and feed them back to users again and again. This dynamic resembles an echo chamber. We hypothesize that this feedback loop entrenches the existing values and beliefs of users, leading to a loss of diversity and potentially the lock-in of false beliefs. We formalize this hypothe…

This https://arxiv.org/abs/2409.15104 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csDC_…

PecSched: Preemptive and Efficient Cluster Scheduling for LLM Inference
The scaling of transformer-based Large Language Models (LLMs) has significantly expanded their context lengths, enabling applications where inputs exceed 100K tokens. Our analysis of a recent Azure LLM inference trace reveals a highly skewed long-tail distribution of input lengths, with approximately 80% of inputs shorter than 2K tokens. Long inputs constitute only a small fraction. Existing cluster-level LLM scheduling strategies, including First-In-First-Out (FIFO), reservation-based, and pri…

This https://arxiv.org/abs/2505.06732 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_hepe…

Particle Identification with Deep Neural Networks Across Collision Energies in Simulated Proton-Proton Collisions
This study demonstrates a proof-of-concept application of a deep neural network for particle identification in simulated high transverse momentum proton-proton collisions, with a focus on evaluating model performance under controlled conditions. A model trained on simulated Large Hadron Collider (LHC) proton-proton collisions at $\sqrt{s} = 13\,\mathrm{TeV}$ is used to classify nine particle species based on seven kinematic-level features. The model is then tested on simulated high transverse m…

Last night at the end of the valley, marking & celebrating several occasions/milestones in one of our fave places...
#SilentSunday #LandscapePhotography #NaturePhotography

I just updated the prints on my office door to reflect the kind of photos (particularly event photos) that I am taking now -- as well the the new system which supersedes "three sided cards" that attains better branding in every respect except that it doesn't have a name (yet) #photo #photography

It was an interesting and fulfilling experience to be part of the @… working group on Winter Science in the Great Lakes. There are so many nuances to how #ClimateChange and development are likely to impact ice and seasonality in the

Applying Large Language Models to Issue Classification: Revisiting with Extended Data and New Models
Gabriel Aracena, Kyle Luster, Fabio Santos, Igor Steinmacher, Marco A. Gerosa
https://arxiv.org/abs/2506.00128

Applying Large Language Models to Issue Classification: Revisiting with Extended Data and New Models
Effective prioritization of issue reports in software engineering helps to optimize resource allocation and information recovery. However, manual issue classification is laborious and lacks scalability. As an alternative, many open source software (OSS) projects employ automated processes for this task, yet this method often relies on large datasets for adequate training. Traditionally, machine learning techniques have been used for issue classification. More recently, large language models (LL…

Fast Luminous Extragalactic Transients in the VLA Sky Survey: Implications for the rates of Accretion-Induced Collapse Events, Fast Blue Optical Transients and Gamma Ray Burst Afterglows
Kritti Sharma, Vikram Ravi, Dillon Z. Dong, Gregg Hallinan, Casey Law, Delina Levine, Jean J. Somalwar, Jessie Miller, Nikita Kosogorov, Steven T. Myers
https://

Fast Luminous Extragalactic Transients in the VLA Sky Survey: Implications for the rates of Accretion-Induced Collapse Events, Fast Blue Optical Transients and Gamma Ray Burst Afterglows
Radio wavelengths offer a unique window into high-energy astrophysical phenomena that may be obscured or too rapidly evolving to be captured at other wavelengths. Leveraging data from the Very Large Array Sky Survey, we perform a systematic search for fast, luminous transients with characteristic timescales $\lesssim 3$ years in the nearby universe ($z \leq 0.3$). We report the discovery of five such transients, and classify them based on their synchrotron emission energetics and host galaxy pr…