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🤦 https://huijzer.xyz/posts/123/do-not-p

High-precision luminescence cryothermometry strategy by using hyperfine structure
Marina N. Popova, Mosab Diab, Boris Z. Malkin
https://arxiv.org/abs/2511.19088 https://arxiv.org/pdf/2511.19088 https://arxiv.org/html/2511.19088
arXiv:2511.19088v1 Announce Type: new
Abstract: A novel, to the best of our knowledge, ultralow-temperature luminescence thermometry strategy is proposed, based on a measurement of relative intensities of hyperfine components in the spectra of Ho$^{3 }$ ions doped into a crystal. A $^{7}$LiYF$_4$:Ho$^{3 }$ crystal is chosen as an example. First, we show that temperatures in the range 10-35 K can be measured using the Boltzmann behavior of the populations of crystal-field levels separated by an energy interval of 23 cm$^{-1}$. Then we select the 6089 cm$^{-1}$ line of the holmium $^5I_5 \rightarrow ^5I_7$ transition, which has a well-resolved hyperfine structure and falls within the transparency window of optical fibers (telecommunication S band), to demonstrate the possibility of measuring temperatures below 3 K. The temperature $T$ is determined by a least-squares fit to the measured intensities of all eight hyperfine components using the dependence $I(\nu) = I_1 \exp(-b\nu)$, where $I_1$ and $b = a\nu \frac{\nu}{kT}$ are fitting parameters and a accounts for intensity variations due to mixing of wave functions of different crystal-field levels by the hyperfine interaction. In this method, the absolute and relative thermal sensitivities grow at $T$ approaching zero as $\frac{1}{T^2}$.and $\frac{1}{T}$, respectively. We theoretically considered the intensity distributions within hyperfine manifolds and compared the results with experimental data. Application of the method to experimentally measured relative intensities of hyperfine components of the 6089 cm$^{-1}$ PL line yielded $T = 3.7 \pm 0.2$ K. For a temperature of 1 K, an order of magnitude better accuracy is expected.
toXiv_bot_toot

Series C, Episode 01 - Aftermath
LAUREN: There's no need. I can handle it, Dayna.
MELLANBY: All right, but don't take any chances.
LAUREN: I won't.
DAYNA: Keep your head down.
LAUREN: I always do.
[On the beach]
https://blake.torpidity.net/m/301/377 B…

Replaced article(s) found for cs.LG. https://arxiv.org/list/cs.LG/new
[4/5]:
- Sample, Don't Search: Rethinking Test-Time Alignment for Language Models
Gon\c{c}alo Faria, Noah A. Smith
https://arxiv.org/abs/2504.03790 https://mastoxiv.page/@arXiv_csCL_bot/114301112970577326
- A Survey on Archetypal Analysis
Aleix Alcacer, Irene Epifanio, Sebastian Mair, Morten M{\o}rup
https://arxiv.org/abs/2504.12392 https://mastoxiv.page/@arXiv_statME_bot/114357826909813483
- The Stochastic Occupation Kernel (SOCK) Method for Learning Stochastic Differential Equations
Michael L. Wells, Kamel Lahouel, Bruno Jedynak
https://arxiv.org/abs/2505.11622 https://mastoxiv.page/@arXiv_statML_bot/114539065460187982
- BOLT: Block-Orthonormal Lanczos for Trace estimation of matrix functions
Kingsley Yeon, Promit Ghosal, Mihai Anitescu
https://arxiv.org/abs/2505.12289 https://mastoxiv.page/@arXiv_mathNA_bot/114539035462135281
- Clustering and Pruning in Causal Data Fusion
Otto Tabell, Santtu Tikka, Juha Karvanen
https://arxiv.org/abs/2505.15215 https://mastoxiv.page/@arXiv_statML_bot/114550346291754635
- On the performance of multi-fidelity and reduced-dimensional neural emulators for inference of ph...
Chloe H. Choi, Andrea Zanoni, Daniele E. Schiavazzi, Alison L. Marsden
https://arxiv.org/abs/2506.11683 https://mastoxiv.page/@arXiv_statML_bot/114692410563481289
- Beyond Force Metrics: Pre-Training MLFFs for Stable MD Simulations
Maheshwari, Tang, Ock, Kolluru, Farimani, Kitchin
https://arxiv.org/abs/2506.14850 https://mastoxiv.page/@arXiv_physicschemph_bot/114709402590755731
- Quantifying Uncertainty in the Presence of Distribution Shifts
Yuli Slavutsky, David M. Blei
https://arxiv.org/abs/2506.18283 https://mastoxiv.page/@arXiv_statML_bot/114738165218533987
- ZKPROV: A Zero-Knowledge Approach to Dataset Provenance for Large Language Models
Mina Namazi, Alexander Nemecek, Erman Ayday
https://arxiv.org/abs/2506.20915 https://mastoxiv.page/@arXiv_csCR_bot/114754394485208892
- SpecCLIP: Aligning and Translating Spectroscopic Measurements for Stars
Zhao, Huang, Xue, Kong, Liu, Tang, Beers, Ting, Luo
https://arxiv.org/abs/2507.01939 https://mastoxiv.page/@arXiv_astrophIM_bot/114788369702591337
- Towards Facilitated Fairness Assessment of AI-based Skin Lesion Classifiers Through GenAI-based I...
Ko Watanabe, Stanislav Frolov, Aya Hassan, David Dembinsky, Adriano Lucieri, Andreas Dengel
https://arxiv.org/abs/2507.17860 https://mastoxiv.page/@arXiv_csCV_bot/114912976717523345
- PASS: Probabilistic Agentic Supernet Sampling for Interpretable and Adaptive Chest X-Ray Reasoning
Yushi Feng, Junye Du, Yingying Hong, Qifan Wang, Lequan Yu
https://arxiv.org/abs/2508.10501 https://mastoxiv.page/@arXiv_csAI_bot/115032101532614110
- Unified Acoustic Representations for Screening Neurological and Respiratory Pathologies from Voice
Ran Piao, Yuan Lu, Hareld Kemps, Tong Xia, Aaqib Saeed
https://arxiv.org/abs/2508.20717 https://mastoxiv.page/@arXiv_csSD_bot/115111255835875066
- Machine Learning-Driven Predictive Resource Management in Complex Science Workflows
Tasnuva Chowdhury, et al.
https://arxiv.org/abs/2509.11512 https://mastoxiv.page/@arXiv_csDC_bot/115213444524490263
- MatchFixAgent: Language-Agnostic Autonomous Repository-Level Code Translation Validation and Repair
Ali Reza Ibrahimzada, Brandon Paulsen, Reyhaneh Jabbarvand, Joey Dodds, Daniel Kroening
https://arxiv.org/abs/2509.16187 https://mastoxiv.page/@arXiv_csSE_bot/115247172280557686
- Automated Machine Learning Pipeline: Large Language Models-Assisted Automated Dataset Generation ...
Adam Lahouari, Jutta Rogal, Mark E. Tuckerman
https://arxiv.org/abs/2509.21647 https://mastoxiv.page/@arXiv_condmatmtrlsci_bot/115286737423175311
- Quantifying the Impact of Structured Output Format on Large Language Models through Causal Inference
Han Yuan, Yue Zhao, Li Zhang, Wuqiong Luo, Zheng Ma
https://arxiv.org/abs/2509.21791 https://mastoxiv.page/@arXiv_csCL_bot/115287166674809413
- The Generation Phases of Flow Matching: a Denoising Perspective
Anne Gagneux, S\'egol\`ene Martin, R\'emi Gribonval, Mathurin Massias
https://arxiv.org/abs/2510.24830 https://mastoxiv.page/@arXiv_csCV_bot/115462527449411627
- Data-driven uncertainty-aware seakeeping prediction of the Delft 372 catamaran using ensemble Han...
Giorgio Palma, Andrea Serani, Matteo Diez
https://arxiv.org/abs/2511.04461 https://mastoxiv.page/@arXiv_eessSY_bot/115507785247809767
- Generalized infinite dimensional Alpha-Procrustes based geometries
Salvish Goomanee, Andi Han, Pratik Jawanpuria, Bamdev Mishra
https://arxiv.org/abs/2511.09801 https://mastoxiv.page/@arXiv_statML_bot/115547135711272091
toXiv_bot_toot

Went to hear Elephant Sessions at the Usher Hall #Edinburgh, somewhat randomly, and came away looking up
➡️ www.belugalagoon.com
Solo band, great following who knew the words, and danced. Andrew O'Donnell, owned the space.
And nature documentary series on the BBC, it seems.
#Polymath #Creative

Modern applications require search capabilities that go beyond basic text matching. They must be fast, accurate, personalised and context-aware. At this year's Berlin Buzzwords, Saurabh Singh demonstrated how OpenSearch’s latest AI/ML enhancements and engine improvements enable organisations to build intelligent, scalable search experiences that meet these evolving needs.
Watch the full session: #bbuzz 2026: https://tickets.plainschwarz.com/bbuzz26/c/8Hvk0ZvJA/

First Data of the 3000 km$^2$ Radio Detector at the Pierre Auger Observatory
Bjarni Pont (for the Pierre Auger Collaboration)
https://arxiv.org/abs/2509.19984 https://

First Data of the 3000 km$^2$ Radio Detector at the Pierre Auger Observatory
In this contribution, we present the status and first data from the Radio Detector (RD) at the Pierre Auger Observatory, consisting of $1660$ radio antennas deployed across the $3000$ km$^2$ surface detector array. These antennas measure the radio emission from extensive air showers in the $30-80$ MHz band, enabling electromagnetic energy measurements for air showers with zenith angles above $65°$. Combined with the muonic measurements from the water-Cherenkov detectors (WCDs), this allows mas…

Beyond adjacency: Graph encoding with reachability and shortest paths
Shiqiang Zhang, Ruth Misener
https://arxiv.org/abs/2509.20247 https://arxiv.org/pdf/2…

Beyond adjacency: Graph encoding with reachability and shortest paths
Graph-structured data is central to many scientific and industrial domains, where the goal is often to optimize objectives defined over graph structures. Given the combinatorial complexity of graph spaces, such optimization problems are typically addressed using heuristic methods, and it remains unclear how to systematically incorporate structural constraints to effectively reduce the search space. This paper introduces explicit optimization formulations for graph search space that encode prope…

Für ein buntes Stadtbild - gegen rassistische Hetze!
Diesen Samstag 25.10. ab 12h auf dem Friedrichsplatz #Karlsruhe. Kundgebung und anschließende Laufdemo
Weitere Infos folgen
#Töchter