AI & ML
Symmetric Zassenhaus splittings for bounded and unbounded operators
arXiv cs.NA0 views
arXiv:2611.09571v1 Announce Type: new Abstract: We establish rigorous local-error bounds for the entire family of symmetric Zassenhaus splittings for possibly unbounded operators, under explicit assumptions on commutator bounds, regularity-preserving flows, and conjugation identities. Truncated symmetric Baker-Campbell-Hausdorff expansions yield an explicit coefficient formula for the Zassenhaus exponents and identify vanishing commutator expressions. In order to extend these cancellations to the realm of unbounded operators, we prove a general theorem on finite expansions of multiple operator conjugations with controlled integral remainders. For splittings of order 2n, our argument gives the sufficient commutator-length bound 4n-1, revealing regularity requirements that are not apparent from the formal order calculation. Using the Schr\"odinger equation with a quadratic potential as an example, we show that the order-dependent regularity requirements can reduce to one fixed weighted Sobolev space for all splitting orders.
Source:https://arxiv.org/abs/2611.09571PreviousMathematical analysis and vectorized FEM implementation of logarithmic strain space framework for finite strains: a case study on elastoplasticityNextBayesian Inverse Problems for EUV reflectometry with regularized JKO scheme
Related posts
How to Check a PDF’s Metadata: Acrobat, Windows, macOS and the Command Line
0dev.to
![AMR AI and Embodied Intelligence — Ch.20: Multi Agent Robotics [KR]](https://media2.dev.to/dynamic/image/width=800%2Cheight=%2Cfit=scale-down%2Cgravity=auto%2Cformat=auto/https%3A%2F%2Fdev-to-uploads.s3.us-east-2.amazonaws.com%2Fuploads%2Farticles%2Fzd2oflt3xqsm741q8o02.png)
AMR AI and Embodied Intelligence — Ch.20: Multi Agent Robotics [KR]
0dev.to
![AMR AI and Embodied Intelligence — Ch.21: AI Safety for Robotics [KR]](https://media2.dev.to/dynamic/image/width=800%2Cheight=%2Cfit=scale-down%2Cgravity=auto%2Cformat=auto/https%3A%2F%2Fdev-to-uploads.s3.us-east-2.amazonaws.com%2Fuploads%2Farticles%2F9sq8mphrqy5pbxzp0qga.png)
AMR AI and Embodied Intelligence — Ch.21: AI Safety for Robotics [KR]
0dev.to
![AMR AI and Embodied Intelligence — Ch.22: AI Monitoring and Validation [KR]](https://media2.dev.to/dynamic/image/width=800%2Cheight=%2Cfit=scale-down%2Cgravity=auto%2Cformat=auto/https%3A%2F%2Fdev-to-uploads.s3.us-east-2.amazonaws.com%2Fuploads%2Farticles%2Frp5vkcklv9459tfg1ofm.png)
AMR AI and Embodied Intelligence — Ch.22: AI Monitoring and Validation [KR]
0dev.to
![AMR AI and Embodied Intelligence — Ch.23: Industrial AI Case Studies [KR]](https://media2.dev.to/dynamic/image/width=800%2Cheight=%2Cfit=scale-down%2Cgravity=auto%2Cformat=auto/https%3A%2F%2Fdev-to-uploads.s3.us-east-2.amazonaws.com%2Fuploads%2Farticles%2Fmsj1xplv6sfdhinvuall.png)
AMR AI and Embodied Intelligence — Ch.23: Industrial AI Case Studies [KR]
0dev.to
![AMR AI and Embodied Intelligence — Ch.24: AGI and Robotics [KR]](https://media2.dev.to/dynamic/image/width=800%2Cheight=%2Cfit=scale-down%2Cgravity=auto%2Cformat=auto/https%3A%2F%2Fdev-to-uploads.s3.us-east-2.amazonaws.com%2Fuploads%2Farticles%2Ff8fkrvqxhhe8cw6dlk94.png)
AMR AI and Embodied Intelligence — Ch.24: AGI and Robotics [KR]
0dev.to