Tootfinder

Zo simpel is het helemaal niet.
“Bij de stemming over het PVV-amendement dat van illegaliteit een misdrijf maakt, beging de fractie van GL/PvdA dinsdag een fout door te pairen met NSC, dat óók tegen de strafbaarstelling is.”
Je pairt niet per amendement Raoul. Oppositie pairt met coalitie, dat is normaal. Je denkt niet over *elk* amendement per se tegengesteld.

Het is heel simpel: bij het stemmen over wetsvoorstellen dienen Kamerleden er gewoon te zijn
Door de afwezigheid van te veel Kamerleden, kwam de strafbaarstelling van illegaliteit dinsdag aan een onverwachte meerderheid. De parlementaire discipline liet veel te wensen over.

🇺🇦 #NowPlaying on KEXP's #AfternoonShow
Sampology:
🎵 Samba Sampo
#Sampology
https://sampology.bandcamp.com/track/samba-sampo
https://open.spotify.com/track/0If1FGdygAT945E4byANCY

Quantum chemistry with provable convergence via randomized sample-based quantum diagonalization
Samuele Piccinelli, Alberto Baiardi, Max Rossmannek, Almudena Carrera Vazquez, Francesco Tacchino, Stefano Mensa, Edoardo Altamura, Ali Alavi, Mario Motta, Javier Robledo-Moreno, William Kirby, Kunal Sharma, Antonio Mezzacapo, Ivano Tavernelli
https://

Quantum chemistry with provable convergence via randomized sample-based quantum diagonalization
Sample-based quantum diagonalization (SQD) is a recently proposed algorithm to approximate the ground-state wave function of many-body quantum systems on near-term and early-fault-tolerant quantum devices. In SQD, the quantum computer acts as a sampling engine that generates the subspace in which the Hamiltonian is classically diagonalized. A recently proposed SQD variant, Sample-based Krylov Quantum Diagonalization (SKQD), uses quantum Krylov states as circuits from which samples are collected…

ASPEN: An Additional Sampling Penalty Method for Finite-Sum Optimization Problems with Nonlinear Equality Constraints
Nata\v{s}a Kreji\'c, Nata\v{s}a Krklec Jerinki\'c, Tijana Ostoji\'c, Nemanja Vu\v{c}i\'cevi\'c
https://arxiv.org/abs/2508.02299

ASPEN: An Additional Sampling Penalty Method for Finite-Sum Optimization Problems with Nonlinear Equality Constraints
We propose a novel algorithm for solving non-convex, nonlinear equality-constrained finite-sum optimization problems. The proposed algorithm incorporates an additional sampling strategy for sample size update into the well-known framework of quadratic penalty methods. Thus, depending on the problem at hand, the resulting method may exhibit a sample size strategy ranging from a mini-batch on one end, to increasing sample size that achieves the full sample eventually, on the other end of the spec…

A quick weekend build of a simple built-in bookshelf, it mirrors a similar shelf on the opposite side wall. The goal was to go strong and simple, and the whole thing only took about 6 hours, which felt good for a non-fancy project!

Lesser Goldfinch eating sunflower seeds. LA Arboretum, Arcadia, California, USA. June, 2025. #laarboretum #goldfinch #lessergoldfinch

Einige der zuletzt hier besonders häufig geteilten #News:
Fiese Schnüffelei: Meta und Yandex spionierten Nutzer ihrer Android-Apps aus

The Hashed Fractal Key Recovery (HFKR) Problem: From Symbolic Path Inversion to Post-Quantum Cryptographic Keys
Mohamed Aly Bouke
https://arxiv.org/abs/2506.04383

The Hashed Fractal Key Recovery (HFKR) Problem: From Symbolic Path Inversion to Post-Quantum Cryptographic Keys
Classical cryptographic systems rely heavily on structured algebraic problems, such as factorization, discrete logarithms, or lattice-based assumptions, which are increasingly vulnerable to quantum attacks and structural cryptanalysis. In response, this work introduces the Hashed Fractal Key Recovery (HFKR) problem, a non-algebraic cryptographic construction grounded in symbolic dynamics and chaotic perturbations. HFKR builds on the Symbolic Path Inversion Problem (SPIP), leveraging symbolic tr…

This https://arxiv.org/abs/2406.18370 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qu…

Learning pure quantum states (almost) without regret
We initiate the study of sample-optimal quantum state tomography with minimal disturbance to the samples. Can we efficiently learn a precise description of a quantum state through sequential measurements of samples while at the same time making sure that the post-measurement state of the samples is only minimally perturbed? Defining regret as the cumulative disturbance of all samples, the challenge is to find a balance between the most informative sequence of measurements on the one hand and me…