Tootfinder

Parity solves the Strong CP problem
Ravi Kuchimanchi
https://arxiv.org/abs/2506.01911 https://arxiv.org/pdf/2506.01911

Parity solves the Strong CP problem
A recent paper "What can solve the strong CP problem?" goes counter to conventional wisdom by arguing that the universe was in an initial state that combines different eigenstates of $θ$ (of the theta vacuum of QCD), and asserts that for such an initial state, axionless solutions to the Strong CP Problem based on P and CP symmetries will not work. We discuss the nature of the theta vacuum in light of this work, and find that the conventional framing and solutions based on P and CP symmetries a…

This https://arxiv.org/abs/2408.01155 has been replaced.
initial toot: https://mastoxiv.page/@arX…

Efficient conversion from fermionic Gaussian states to matrix product states
Fermionic Gaussian states are eigenstates of quadratic Hamiltonians and are widely used in quantum many-body problems. We propose a highly efficient algorithm that converts fermionic Gaussian states to matrix product states. It can be formulated for finite-size systems without translation invariance, but becomes particularly appealing when applied to infinite systems with translation invariance. If the ground states of a topologically ordered system on infinite cylinders are expressed as matrix…

This https://arxiv.org/abs/2411.11824 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Theoretical Foundations of Conformal Prediction
This book is about conformal prediction and related inferential techniques that build on permutation tests and exchangeability. These techniques are useful in a diverse array of tasks, including hypothesis testing and providing uncertainty quantification guarantees for machine learning systems. Much of the current interest in conformal prediction is due to its ability to integrate into complex machine learning workflows, solving the problem of forming prediction sets without any assumptions on …