Tootfinder

An informal invitation to Laurie Anderson was issued in fall 2020, no word back yet

A new paper projecting Joshua tree habitat under future climate based on incredibly high-resolution distribution data, from Joshua Tree Genome Project collaborators at USGS. They estimate up to 80% loss of suitable habitat by 2100 under the worst-case climate scenario.
#JoshuaTree #science

Improved geometric and recollision estimates for the invariance principle of the random Lorentz gas
Raphael Winter, Karsten Matthies
https://arxiv.org/abs/2506.18539

Improved geometric and recollision estimates for the invariance principle of the random Lorentz gas
By improving geometric recollision estimates for a random Lorentz gas, we extend the timescale $T(r)$ of the invariance principle for a Lorentz gas with particle size $r$ obtained by Lutsko and Toth (2020) from $\lim_{r \rightarrow 0} T(r) r^{2} |\log(r)|^2 =0$ to $\lim_{r \rightarrow 0} T(r) r^{2} |\log(r)| =0$. We show that this is the maximal reachable timescale with the coupling of stochastic processes introduced in the original result. In our improved geometric estimate…

SETI@home: Data Acquisition and Front-End Processing
Eric J. Korpela (Space Sciences Laboratory, University of California, Berkeley), David P. Anderson (Space Sciences Laboratory, University of California, Berkeley), Jeff Cobb (Space Sciences Laboratory, University of California, Berkeley), Matt Lebofsky (Space Sciences Laboratory, University of California, Berkeley), Wei Liu (Space Sciences Laboratory, University of California, Berkeley), Dan Werthimer (Space Sciences Laboratory, Univ…

SETI@home: Data Acquisition and Front-End Processing
SETI@home is a radio Search for Extraterrestrial Intelligence (SETI) project, looking for technosignatures in data recorded at multiple observatories from 1998 to 2020. Most radio SETI projects analyze data using dedicated processing hardware. SETI@home uses a different approach: time-domain data is distributed over the Internet to $\gt 10^{5}$ volunteered home computers, which analyze it. The large amount of computing power this affords ($\sim 10^{15}$ floating-point operations per second (FPO…

Characterization of Higher-Order Sobolev Spaces on the Sphere via Generalized Averaging of Function
Ikhsan Maulidi, Hiroshi Ohtsuka
https://arxiv.org/abs/2506.17736

Characterization of Higher-Order Sobolev Spaces on the Sphere via Generalized Averaging of Function
We present a new characterization of higher-order Sobolev spaces on the sphere. Building on the approach of Barceló et al. (2020), we refine the square function they introduced for this purpose. In particular, we provide a detailed analysis of the weight function and the averaging range in its definition. Our results demonstrate that averaging can be performed using a weight function from a broad class, and that the averaging domain can be restricted to a local coordinate patch on the sphere.