Tootfinder

Messengers: Breaking Echo Chambers in Collective Opinion Dynamics with Homophily
Mohsen Raoufi, Heiko Hamann, Pawel Romanczuk
https://arxiv.org/abs/2406.06440

Messengers: Breaking Echo Chambers in Collective Opinion Dynamics with Homophily
Collective estimation manifests computational intelligence emerging from inter-individual local interactions, e.g., by aggregating opinions from neighbors to estimate a quantity. Use cases of collective estimation may include directed motion in physical space, such that agents, for example, have to collectively explore a distributed feature, and collectively agree on a numerical value. In doing so, collectives face several challenges in achieving precise estimations. These challenges exhibit co…

Multicriteria Adjustable Robustness
Elisabeth Halser, Elisabeth Finhold, Neele Leith\"auser, Jan Schwientek, Katrin Teichert, Karl-Heinz K\"ufer
https://arxiv.org/abs/2406.07959

Multicriteria Adjustable Robustness
Multicriteria adjustable robust optimization (MARO) problems arise in a wide variety of practical settings, for example, in the design of a building's energy supply. However, no general approaches, neither for the characterization of solutions to this problem class, nor potential solution methods, are available in the literature so far. We give different definitions for efficient solutions to MARO problems and look at three computational concepts to deal with the problems. These computational c…

This https://arxiv.org/abs/2406.09851 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Large deviations for the largest singular value of sparse non-Hermitian matrices
We prove a large deviation principle for the largest singular value of sparse non-Hermitian random matrices, or directed Erdős-Rényi networks in the constant average degree regime $p =\frac{d}{n}$ where $d$ is fixed. Entries are assumed to have Weibull distributions with tail decaying at rate $e^{-t^α}$ for $α>0$. While the law of large number results agree with the largest eigenvalue of sparse Hermitian matrices given in (Ganguly and Nam, '22) and (Ganguly, Hiesmayr and Nam, '22), large de…

Representation-protected topology of spin-singlet $s$-wave superconductors
Shingo Kobayashi, Akira Furusaki
https://arxiv.org/abs/2406.07939 https://

Representation-protected topology of spin-singlet $s$-wave superconductors
We show that spin-singlet $s$-wave multi-band superconductors have a topological phase protected by rotation symmetry and time-reversal symmetry without spin-orbit coupling in two and three dimensions. This topological phase, an example of a representation-protected topological phase, has a $\mathbb{Z}_2$ topological index and is stable as long as the bands at the Fermi energy are formed by a doublet of orbital states with finite angular momenta. In the limit of weak superconducting pair potent…

Learning dynamical behaviors in physical systems
Rituparno Mandal, Rosalind Huang, Michel Fruchart, Pepijn G. Moerman, Suriyanarayanan Vaikuntanathan, Arvind Murugan, Vincenzo Vitelli
https://arxiv.org/abs/2406.07856

Learning dynamical behaviors in physical systems
Physical learning is an emerging paradigm in science and engineering whereby (meta)materials acquire desired macroscopic behaviors by exposure to examples. So far, it has been applied to static properties such as elastic moduli and self-assembled structures encoded in minima of an energy landscape. Here, we extend this paradigm to dynamic functionalities, such as motion and shape change, that are instead encoded in limit cycles or pathways of a dynamical system. We identify the two ingredients …

This https://arxiv.org/abs/2406.09851 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Large deviations for the largest singular value of sparse non-Hermitian matrices
We prove a large deviation principle for the largest singular value of sparse non-Hermitian random matrices, or directed Erdős-Rényi networks in the constant average degree regime $p =\frac{d}{n}$ where $d$ is fixed. Entries are assumed to have Weibull distributions with tail decaying at rate $e^{-t^α}$ for $α>0$. While the law of large number results agree with the largest eigenvalue of sparse Hermitian matrices given in (Ganguly and Nam, '22) and (Ganguly, Hiesmayr and Nam, '22), large de…

Large deviations for the largest singular value of sparse non-Hermitian matrices
Hyungwon Han
https://arxiv.org/abs/2406.09851 https://

Large deviations for the largest singular value of sparse non-Hermitian matrices
We prove a large deviation principle for the largest singular value of sparse non-Hermitian random matrices, or directed Erdős-Rényi networks in the constant average degree regime $p =\frac{d}{n}$ where $d$ is fixed. Entries are assumed to have Weibull distributions with tail decaying at rate $e^{-t^α}$ for $α>0$. While the law of large number results agree with the largest eigenvalue of sparse Hermitian matrices given in (Ganguly and Nam, '22) and (Ganguly, Hiesmayr and Nam, '22), large de…