Tootfinder

#photography #bloomScrolling #red

OH MY GOD!
There will be a second Spaceballs movie!!!
https://www.msn.com/en-us/video/peopleandplaces/spaceballs-2-official-announcement-teaser/vi-AA1GBgTH

Somehow... "Spaceballs: The Search for More Money" returned. 😁
▶️ Spaceballs 2 - Official Announcement Teaser (2027) Mel Brooks
https://youtu.be/ewKuhclROA0?si=NpacqU_cmLXGBZ3s

Quantum block Krylov subspace projector algorithm for computing low-lying eigenenergies
Maria Gabriela Jord\~ao Oliveira, Nina Glaser
https://arxiv.org/abs/2506.09971

Quantum block Krylov subspace projector algorithm for computing low-lying eigenenergies
Determining eigenvalues is a computationally expensive task that is crucial for countless applications in natural sciences. Toward this end, we introduce the quantum block Krylov subspace projector (QBKSP) algorithm, a multireference quantum variant of the Lanczos algorithm designed to accurately compute low-lying eigenvalues, including degenerate states. We present three different compact quantum circuits to evaluate the required expectation values, each suited to different problem settings. T…

Sampling-Based Planning Under STL Specifications: A Forward Invariance Approach
Gregorio Marchesini, Siyuan Liu, Lars Lindemann, Dimos V. Dimarogonas
https://arxiv.org/abs/2506.10739

Sampling-Based Planning Under STL Specifications: A Forward Invariance Approach
We propose a variant of the Rapidly Exploring Random Tree Star (RRT$^{\star}$) algorithm to synthesize trajectories satisfying a given spatio-temporal specification expressed in a fragment of Signal Temporal Logic (STL) for linear systems. Previous approaches for planning trajectories under STL specifications using sampling-based methods leverage either mixed-integer or non-smooth optimization techniques, with poor scalability in the horizon and complexity of the task. We adopt instead a contro…

Oh look at that! #Spaceballs
https://www.youtube.com/watch?v=kdlFlL0Zg_A
If Mel Brooks is 98 he will be exactly 100 years old when that sequel comes out (and he makes …

Logic Mining from Process Logs: Towards Automated Specification and Verification
Radoslaw Klimek, Julia Witek
https://arxiv.org/abs/2506.08628 https://

Logic Mining from Process Logs: Towards Automated Specification and Verification
Logical specifications play a key role in the formal analysis of behavioural models. Automating the derivation of such specifications is particularly valuable in complex systems, where manual construction is time-consuming and error-prone. This article presents an approach for generating logical specifications from process models discovered via workflow mining, combining pattern-based translation with automated reasoning techniques. In contrast to earlier work, we evaluate the method on both ge…

Cross-Channel Unlabeled Sensing over a Union of Signal Subspaces
Taulant Koka, Manolis C. Tsakiris, Benjam\'in B\'ejar Haro, Michael Muma
https://arxiv.org/abs/2506.09773 …

Cross-Channel Unlabeled Sensing over a Union of Signal Subspaces
Cross-channel unlabeled sensing addresses the problem of recovering a multi-channel signal from measurements that were shuffled across channels. This work expands the cross-channel unlabeled sensing framework to signals that lie in a union of subspaces. The extension allows for handling more complex signal structures and broadens the framework to tasks like compressed sensing. These mismatches between samples and channels often arise in applications such as whole-brain calcium imaging of freely…

Mel Brooks lebt ja auch noch… 😱
#spaceballs

Subspace-constrained randomized coordinate descent for linear systems with good low-rank matrix approximations
Jackie Lok, Elizaveta Rebrova
https://arxiv.org/abs/2506.09394

Subspace-constrained randomized coordinate descent for linear systems with good low-rank matrix approximations
The randomized coordinate descent (RCD) method is a classical algorithm with simple, lightweight iterations that is widely used for various optimization problems, including the solution of positive semidefinite linear systems. As a linear solver, RCD is particularly effective when the matrix is well-conditioned; however, its convergence rate deteriorates rapidly in the presence of large spectral outliers. In this paper, we introduce the subspace-constrained randomized coordinate descent (SC-RCD…