Tootfinder

One-dimensional lattice random walks in a Gaussian random potential
Silvio Kalaj, Enzo Marinari, Gleb Oshanin, Luca Peliti
https://arxiv.org/abs/2509.23985 https://

One-dimensional lattice random walks in a Gaussian random potential
We study random walks evolving in continuous time on a one-dimensional lattice where each site $x$ hosts a quenched random potential $U_x$. The potentials on different sites are independent, identically distributed Gaussian random variables. We analyze three distinct models that specify how the transition rates depend on $U_x$: the random-force-like model, random walks with randomized stepping times, and the Gaussian trap model. Our analysis focuses on five key disorder-dependent quantities def…

Pseudorandom Unitaries in the Haar Random Oracle Model
Prabhanjan Ananth, John Bostanci, Aditya Gulati, Yao-Ting Lin
https://arxiv.org/abs/2509.24432 https://

Pseudorandom Unitaries in the Haar Random Oracle Model
The quantum Haar random oracle model is an idealized model where every party has access to a single Haar random unitary and its inverse. We construct strong pseudorandom unitaries in the quantum Haar random oracle model. This strictly improves upon prior works who either only prove the existence of pseudorandom unitaries in the inverseless quantum Haar random oracle model [Ananth, Bostanci, Gulati, Lin, EUROCRYPT 2025] or prove the existence of a weaker notion (implied by strong pseudorandom un…

Randomized Krylov methods for inverse problems
Julianne Chung, Silvia Gazzola
https://arxiv.org/abs/2508.20269 https://arxiv.org/pdf/2508.20269

Randomized Krylov methods for inverse problems
In this paper we develop randomized Krylov subspace methods for efficiently computing regularized solutions to large-scale linear inverse problems. Building on the recently developed randomized Gram-Schmidt process, where sketched inner products are used to estimate inner products of high-dimensional vectors, we propose a randomized Golub-Kahan approach that works for general rectangular matrices. We describe new iterative solvers based on the randomized Golub-Kahan approach and show how they c…

»Math.random() is not so random — The Illusion of Randomness in JavaScript:
Don’t Trust Math.random() - Uncovering the Hidden Predictability of Random Numbers.«
In some applications random numbers are very useful but not unique and therefore you should consider where to use it. In this regard, there are for example, UUID v4 or Nano ID and the same.
🧑‍💻

Math.random() is not so random: The Illusion of Randomness in JavaScript
Don’t Trust Math.random(): Uncovering the Hidden Predictability of Random Numbers.

Strong Kurtz Randomness and Binary Expansions of Reordered Computable Numbers
Peter Hertling, Philip Janicki
https://arxiv.org/abs/2509.22406 https://arxiv…

Strong Kurtz Randomness and Binary Expansions of Reordered Computable Numbers
A real number is called left-computable if there exists a computable increasing sequence of rational numbers converging to it. In this article we investigate the Kolmogorov complexity and the binary expansions of a very specific subset of the left-computable numbers. We show in our main result that a real number is reordered computable if, and only if, it is left-computable and not strongly Kurtz random. In preparation of this, we characterize strong Kurtz randomness by a suitable notion of ran…

Wonderful Montazh Femmes of Season Eight
#KellyMonaco
Season 8 Episode 19 "Diabolique"
#RandomBaywatch #lvdlpx

#DonnaDErrico always claims to be unable to swim and terrified of water, but she filmed several scenes like this in her years in the Baywatch Universe.
Baywatch Nights 2x08 - Last Breath
#RandomBaywatch

#ChristineElise #BillyWarlock
Season 1 Episode 8 "Rookie School"
#RandomBaywatch #lvdlpx

#BobbiePhillips #DavidHasselhoff
Season 5 Episode 9 "Red Wind"
#RandomBaywatch #lvdlpx

Eddie was pissed off
#BillyWarlock
Season 1 Episode 4 "Second Wave"
#BaywatchStuds #RandomBaywatch