Tootfinder

Quantification of the radiative forcing of #contrails embedded in cirrus clouds: https://www.nature.com/articles/s41467-025-66231-8 -> “Hidden” contrails in cirrus clouds contribute to climate warming: https://www.uni-leipzig.de/en/newsdetail/artikel/study-hidden-contrails-in-cirrus-clouds-contribute-to-climate-warming-2025-12-12 - research team combines aircraft data with satellite observations and computer models.

"Von Seiten der Gemeinde", meine Lieblingsmusiker aus dem Tiroler Oberland haben ein neues Album rausgebracht im November - wie hab ich das nur übersehen können!? 🙃
https://youtu.be/K2bQfSon6n0?si=H3ZHvpG_qMatbKB3
Erster Eindruck: ein sehr politisches Album das p…

Friend, not foe: lowered tissue reactivity to long-term polyimide implants https://www.biorxiv.org/content/10.64898/2026.02.06.703281v1 "insights on optimizing device design parameters as well as surgical insights for improved tissue integration of intracortical electr…

Replaced article(s) found for cs.DS. https://arxiv.org/list/cs.DS/new
[1/1]:
- Fully Dynamic Adversarially Robust Correlation Clustering in Polylogarithmic Update Time
Vladimir Braverman, Prathamesh Dharangutte, Shreyas Pai, Vihan Shah, Chen Wang
https://arxiv.org/abs/2411.09979 https://mastoxiv.page/@arXiv_csDS_bot/113502653187863544
- A Simple and Combinatorial Approach to Proving Chernoff Bounds and Their Generalizations
William Kuszmaul
https://arxiv.org/abs/2501.03488 https://mastoxiv.page/@arXiv_csDS_bot/113791396712128907
- The Structural Complexity of Matrix-Vector Multiplication
Emile Anand, Jan van den Brand, Rose McCarty
https://arxiv.org/abs/2502.21240 https://mastoxiv.page/@arXiv_csDS_bot/114097340825270885
- Clustering under Constraints: Efficient Parameterized Approximation Schemes
Sujoy Bhore, Ameet Gadekar, Tanmay Inamdar
https://arxiv.org/abs/2504.06980 https://mastoxiv.page/@arXiv_csDS_bot/114312444050875805
- Minimizing Envy and Maximizing Happiness in Graphical House Allocation
Anubhav Dhar, Ashlesha Hota, Palash Dey, Sudeshna Kolay
https://arxiv.org/abs/2505.00296 https://mastoxiv.page/@arXiv_csDS_bot/114437013364446063
- Fast and Simple Densest Subgraph with Predictions
Thai Bui, Luan Nguyen, Hoa T. Vu
https://arxiv.org/abs/2505.12600 https://mastoxiv.page/@arXiv_csDS_bot/114538936921930134
- Compressing Suffix Trees by Path Decompositions
Becker, Cenzato, Gagie, Kim, Koerkamp, Manzini, Prezza
https://arxiv.org/abs/2506.14734 https://mastoxiv.page/@arXiv_csDS_bot/114703384646892523
- Improved sampling algorithms and functional inequalities for non-log-concave distributions
Yuchen He, Zhehan Lei, Jianan Shao, Chihao Zhang
https://arxiv.org/abs/2507.11236 https://mastoxiv.page/@arXiv_csDS_bot/114862112197588124
- Deterministic Lower Bounds for $k$-Edge Connectivity in the Distributed Sketching Model
Peter Robinson, Ming Ming Tan
https://arxiv.org/abs/2507.11257 https://mastoxiv.page/@arXiv_csDS_bot/114862223634372292
- Optimally detecting uniformly-distributed $\ell_2$ heavy hitters in data streams
Santhoshini Velusamy, Huacheng Yu
https://arxiv.org/abs/2509.07286 https://mastoxiv.page/@arXiv_csDS_bot/115178875220889588
- Uncrossed Multiflows and Applications to Disjoint Paths
Chandra Chekuri, Guyslain Naves, Joseph Poremba, F. Bruce Shepherd
https://arxiv.org/abs/2511.00254 https://mastoxiv.page/@arXiv_csDS_bot/115490402963680492
- Dynamic Matroids: Base Packing and Covering
Tijn de Vos, Mara Grilnberger
https://arxiv.org/abs/2511.15460 https://mastoxiv.page/@arXiv_csDS_bot/115580946319285096
- Branch-width of connectivity functions is fixed-parameter tractable
Tuukka Korhonen, Sang-il Oum
https://arxiv.org/abs/2601.04756 https://mastoxiv.page/@arXiv_csDS_bot/115864074799755995
- CoinPress: Practical Private Mean and Covariance Estimation
Sourav Biswas, Yihe Dong, Gautam Kamath, Jonathan Ullman
https://arxiv.org/abs/2006.06618
- The Ideal Membership Problem and Abelian Groups
Andrei A. Bulatov, Akbar Rafiey
https://arxiv.org/abs/2201.05218
- Bridging Classical and Quantum: Group-Theoretic Approach to Quantum Circuit Simulation
Daksh Shami
https://arxiv.org/abs/2407.19575 https://mastoxiv.page/@arXiv_quantph_bot/112874282709517475
- Young domination on Hamming rectangles
Janko Gravner, Matja\v{z} Krnc, Martin Milani\v{c}, Jean-Florent Raymond
https://arxiv.org/abs/2501.03788 https://mastoxiv.page/@arXiv_mathCO_bot/113791421814248215
- On the Space Complexity of Online Convolution
Joel Daniel Andersson, Amir Yehudayoff
https://arxiv.org/abs/2505.00181 https://mastoxiv.page/@arXiv_csCC_bot/114437005955255553
- Universal Solvability for Robot Motion Planning on Graphs
Anubhav Dhar, Pranav Nyati, Tanishq Prasad, Ashlesha Hota, Sudeshna Kolay
https://arxiv.org/abs/2506.18755 https://mastoxiv.page/@arXiv_csCC_bot/114737342714568702
- Colorful Minors
Evangelos Protopapas, Dimitrios M. Thilikos, Sebastian Wiederrecht
https://arxiv.org/abs/2507.10467
- Learning fermionic linear optics with Heisenberg scaling and physical operations
Aria Christensen, Andrew Zhao
https://arxiv.org/abs/2602.05058
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Replaced article(s) found for physics.ins-det. https://arxiv.org/list/physics.ins-det/new
[1/1]:
- A nonlinear multiphysics model for the design validation of the ASTAROTH copper-steel cryogenic c...
Alessandria, Armani, Coelli, Cortis, D'Angelo, Martinenghi, Monti, Orlandi, Sorbi, Toso, Zani
https://arxiv.org/abs/2511.22529 https://mastoxiv.page/@arXiv_physicsinsdet_bot/115643479525772405
- Quantum noise in a squeezed-light-enhanced multiparameter quantum sensor
Aleksandra Sierant, Diana M\'endez-Avalos, Santiago Tabares Giraldo, Morgan W. Mitchell
https://arxiv.org/abs/2506.08190 https://mastoxiv.page/@arXiv_quantph_bot/114664134107738542
- Evaluation of PID Performance at CEPC and Optimization with Combined dN/dx and Time-of-Flight Data
Dian Yu, Houqian Ding, Yongfeng Zhu, Ming Qi, Kun Liu, Yunyun Fan
https://arxiv.org/abs/2507.18164 https://mastoxiv.page/@arXiv_hepex_bot/114912892827917148
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If you're interested in how I quantified natural #CO2 emissions from "mofettes" near #Tübingen with a low-cost sensor network, and want to join my PhD defense tomorrow at 10:00, DM me here and i might send you the link (if I don't forget it 😅).
I'll be mostly talking about …

Quantification of natural CO2 emissions from mofettes using a low-cost sensor network at the Starzach site in South-West Germany
We present a top-down method to derive CO2 emissions from mofettes, using only point measurement time series at irregular locations. Notably, no wind vector information is needed, as gas transport is derived from cross-correlations between sensor stations and subsequently integrated using Gauss’ divergence theorem. The method is applied to an existing low-cost sensor network at the Starzach site near the Black Forest in Germany, for which no comprehensive estimate of the total emissions exist…

from my link log —
Python anti-patterns.
https://docs.quantifiedcode.com/python-anti-patterns/
saved 2019-07-24 https://do…

Greg Olson Quantifies the Raiders' Loss of Brock Bowers https://www.si.com/nfl/raiders/onsi/las-vegas-greg-olson-quantifies-loss-of-brock-bowers

Crosslisted article(s) found for cs.DS. https://arxiv.org/list/cs.DS/new
[1/1]:
- Algebraic Reduction to Improve an Optimally Bounded Quantum State Preparation Algorithm
Giacomo Belli, Michele Amoretti
https://arxiv.org/abs/2602.06535 https://mastoxiv.page/@arXiv_quantph_bot/116040046858615026
- Induced Cycles of Many Lengths
Maria Chudnovsky, Ilya Maier
https://arxiv.org/abs/2602.06874 https://mastoxiv.page/@arXiv_mathCO_bot/116039905295882594
- Circuit Diameter of Polyhedra is Strongly Polynomial
Bento Natura
https://arxiv.org/abs/2602.06958 https://mastoxiv.page/@arXiv_mathOC_bot/116040016711065918
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Approximate Cartesian Tree Matching with Substitutions
Panagiotis Charalampopoulos, Jonas Ellert, Manal Mohamed
https://arxiv.org/abs/2602.08570 https://arxiv.org/pdf/2602.08570 https://arxiv.org/html/2602.08570
arXiv:2602.08570v1 Announce Type: new
Abstract: The Cartesian tree of a sequence captures the relative order of the sequence's elements. In recent years, Cartesian tree matching has attracted considerable attention, particularly due to its applications in time series analysis. Consider a text $T$ of length $n$ and a pattern $P$ of length $m$. In the exact Cartesian tree matching problem, the task is to find all length-$m$ fragments of $T$ whose Cartesian tree coincides with the Cartesian tree $CT(P)$ of the pattern. Although the exact version of the problem can be solved in linear time [Park et al., TCS 2020], it remains rather restrictive; for example, it is not robust to outliers in the pattern.
To overcome this limitation, we consider the approximate setting, where the goal is to identify all fragments of $T$ that are close to some string whose Cartesian tree matches $CT(P)$. In this work, we quantify closeness via the widely used Hamming distance metric. For a given integer parameter $k>0$, we present an algorithm that computes all fragments of $T$ that are at Hamming distance at most $k$ from a string whose Cartesian tree matches $CT(P)$. Our algorithm runs in time $\mathcal O(n \sqrt{m} \cdot k^{2.5})$ for $k \leq m^{1/5}$ and in time $\mathcal O(nk^5)$ for $k \geq m^{1/5}$, thereby improving upon the state-of-the-art $\mathcal O(nmk)$-time algorithm of Kim and Han [TCS 2025] in the regime $k = o(m^{1/4})$.
On the way to our solution, we develop a toolbox of independent interest. First, we introduce a new notion of periodicity in Cartesian trees. Then, we lift multiple well-known combinatorial and algorithmic results for string matching and periodicity in strings to Cartesian tree matching and periodicity in Cartesian trees.
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