Relativistic state reduction dynamics

A mechanism describing state reduction dynamics in relativistic quantum field theory is outlined. The mechanism involves nonlinear stochastic modifications to the standard description of unitary state evolution and the introduction of a relativistic field in which a quantized degree of freedom is associated to each point in spacetime. The purpose of this field is to mediate in the interaction between classical stochastic influences and conventional quantum fields. The equations of motion are Lorentz covariant, frame independent, and do not result in divergent behavior. It is shown that the mathematical framework permits the specification of unambiguous local properties providing a connection between the model and evidence of real world phenomena. The collapse process is demonstrated for an idealized example.Comment: 20 pages, 2 figures, replacement with minor correction

Semi-naive dimensional renormalization

We propose a treatment of $\gamma^5$ in dimensional regularization which is based on an algebraically consistent extension of the Breitenlohner-Maison-'t Hooft-Veltman (BMHV) scheme; we define the corresponding minimal renormalization scheme and show its equivalence with a non-minimal BMHV scheme. The restoration of the chiral Ward identities requires the introduction of considerably fewer finite counterterms than in the BMHV scheme. This scheme is the same as the minimal naive dimensional renormalization in the case of diagrams not involving fermionic traces with an odd number of $\gamma^5$, but unlike the latter it is a consistent scheme. As a simple example we apply our minimal subtraction scheme to the Yukawa model at two loops in presence of external gauge fields.Comment: 28 pages, 3 figure

Joint Image Reconstruction and Nonrigid Motion Estimation with a Simple Penalty That Encourages Local Invertibility

Motion artifacts are a significant issue in medical image reconstruction. There are many methods for incorporating motion information into image reconstruction. However, there are fewer studies that focus on deformation regularization in motioncompensated image reconstruction. The usual choice for deformation regularization has been penalty functions based on the assumption that tissues are elastic. In the image registration field, there have been some methods proposed that impose deformation invertibility using constraints or regularization, assuming that organ motions are invertible transformations. However, most of these methods require very high memory or computation complexity, making them poorly suited for dealing with multiple images simultaneously in motion-compensated image reconstruction. Recently we proposed an image registration method that uses a simple penalty function based on a sufficient condition for the local invertibility of deformations.1 That approach encourages local invertibility in a fast and memory-efficient way. This paper investigates the use of that regularization method for the more challenging problem of joint image reconstruction and nonrigid motion estimation. A 2D PET simulation (based on realistic motion from real patient CT data) demonstrates the benefits of such motion regularization for joint image reconstruction/registration.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/85929/1/Fessler237.pd