Tootfinder

Rank-reduced equation-of-motion coupled cluster formalism with full inclusion of triple excitations
Piotr Michalak, Micha{\l} Lesiuk
https://arxiv.org/abs/2508.19799 https://

Rank-reduced equation-of-motion coupled cluster formalism with full inclusion of triple excitations
In this work we describe the rank-reduced variant of the equation-of-motion coupled cluster theory with complete inclusion of single, double, and triple excitations. The advantage of the proposed formalism in comparison with the canonical theory stems from the application of Tucker decomposition format to the ground- and excited-states triply-excited amplitudes tensors. By exploiting the linear scaling of the dimension of the decomposed amplitudes with respect to the system size $N$, one can re…

Broadband Relaxation Dynamics of Boron-Vacancy Centers in Hexagonal Boron Nitride
Abhishek Bharatbhai Solanki, Yueh-Chun Wu, Hamza Ather, Priyo Adhikary, Aravindh Shankar, Ian Gallagher, Xingyu Gao, Owen M. Matthiessen, Demid Sychev, Alexei Lagoutchev, Tongcang Li, Yong P. Chen, Vladimir M. Shalaev, Benjamin Lawrie, Pramey Upadhyaya
https://

Broadband Relaxation Dynamics of Boron-Vacancy Centers in Hexagonal Boron Nitride
The negatively charged boron vacancy center ($\mathrm{V_B^-}$) in hexagonal boron nitride ($\mathrm{hBN}$) has attracted attention for its potential applications in quantum sensing. While GHz-scale sensing at low magnetic fields has been demonstrated with these defects, their behavior at high fields remains largely unexplored. We investigate the spin relaxation dynamics of $\mathrm{V_B^-}$ centers over temperatures of $15-250$ K and magnetic fields of up to $7$ T, corresponding to a ground-stat…

Quantum algorithm for solving generalized eigenvalue problems with application to the Schr\"odinger equation
Grzegorz Rajchel-Mieldzio\'c, Szymon Pli\'s, Emil Zak
https://arxiv.org/abs/2506.13534

Quantum algorithm for solving generalized eigenvalue problems with application to the Schrödinger equation
Accurate computation of multiple eigenvalues of quantum Hamiltonians is essential in quantum chemistry, materials science, and molecular spectroscopy. Estimating excited-state energies is challenging for classical algorithms due to exponential scaling with system size, posing an even harder problem than ground-state calculations. We present a quantum algorithm for estimating eigenvalues and singular values of parameterized matrix families, including solving generalized eigenvalue problems that …

A Fully Adaptive Frank-Wolfe Algorithm for Relatively Smooth Problems and Its Application to Centralized Distributed Optimization
A. A. Vyguzov, F. S. Stonyakin
https://arxiv.org/abs/2507.05669

A Fully Adaptive Frank-Wolfe Algorithm for Relatively Smooth Problems and Its Application to Centralized Distributed Optimization
We study the Frank-Wolfe algorithm for constrained optimization problems with relatively smooth and relatively strongly convex objectives. Building upon our previous work, we propose a fully adaptive variant of the Frank-Wolfe method that dynamically adjusts the step size based on both the relative smoothness constant and the Triangle Scaling Exponent (TSE) of the Bregman divergence. Our method does not require prior knowledge of the function parameters and guarantees convergence using only loc…

Normalized Radon Cumulative Distribution Transforms for Invariance and Robustness in Optimal Transport Based Image Classification
Matthias Beckmann, Robert Beinert, Jonas Bresch
https://arxiv.org/abs/2506.08761

Normalized Radon Cumulative Distribution Transforms for Invariance and Robustness in Optimal Transport Based Image Classification
The Radon cumulative distribution transform (R-CDT), is an easy-to-compute feature extractor that facilitates image classification tasks especially in the small data regime. It is closely related to the sliced Wasserstein distance and provably guaranties the linear separability of image classes that emerge from translations or scalings. In many real-world applications, like the recognition of watermarks in filigranology, however, the data is subject to general affine transformations originating…

Exploring Quantum Annealing for Coarse-Grained Protein Folding
Timon Scheiber, Matthias Heller, Andreas Giebel
https://arxiv.org/abs/2508.10660 https://arx…

Exploring Quantum Annealing for Coarse-Grained Protein Folding
We explore the potential application of quantum annealing to address the protein structure problem. To this end, we compare several proposed ab initio protein folding models for quantum computers and analyze their scaling and performance for classical and quantum heuristics. Furthermore, we introduce a novel encoding of coordinate based models on the tetrahedral lattice, based on interleaved grids. Our findings reveal significant variations in model performance, with one model yielding unphysic…