118 research outputs found
Thermal equilibrium states for quantum fields on non-commutative spacetimes
Fully Poincar\'e covariant quantum field theories on non-commutative Moyal
Minkowski spacetime so far have been considered in their vacuum
representations, i.e. at zero temperature. Here we report on work in progress
regarding their thermal representations, corresponding to physical states at
non-zero temperature, which turn out to be markedly different from both,
thermal representations of quantum field theory on commutative Minkowski
spacetime, and such representations of non-covariant quantum field theory on
Moyal Minkowski space with a fixed deformation matrix.Comment: 20 pages. Contribution to the proceedings of the conference 'Quantum
Mathematical Physics', Regensburg, 29.09.-02.10.201
Local Thermal Equilibrium States and Quantum Energy Inequalities
In this paper we investigate the energy distribution of states of a linear
scalar quantum field with arbitrary curvature coupling on a curved spacetime
which fulfill some local thermality condition. We find that this condition
implies a quantum energy inequality for these states, where the (lower) energy
bounds depend only on the local temperature distribution and are local and
covariant (the dependence of the bounds other than on temperature is on
parameters defining the quantum field model, and on local quantities
constructed from the spacetime metric). Moreover, we also establish the
averaged null energy condition (ANEC) for such locally thermal states, under
growth conditions on their local temperature and under conditions on the free
parameters entering the definition of the renormalized stress-energy tensor.
These results hold for a range of curvature couplings including the cases of
conformally coupled and minimally coupled scalar field.Comment: 26 page
'A net for everyone': fully personalized and unsupervised neural networks trained with longitudinal data from a single patient
With the rise in importance of personalized medicine, we trained personalized
neural networks to detect tumor progression in longitudinal datasets. The model
was evaluated on two datasets with a total of 64 scans from 32 patients
diagnosed with glioblastoma multiforme (GBM). Contrast-enhanced T1w sequences
of brain magnetic resonance imaging (MRI) images were used in this study. For
each patient, we trained their own neural network using just two images from
different timepoints. Our approach uses a Wasserstein-GAN (generative
adversarial network), an unsupervised network architecture, to map the
differences between the two images. Using this map, the change in tumor volume
can be evaluated. Due to the combination of data augmentation and the network
architecture, co-registration of the two images is not needed. Furthermore, we
do not rely on any additional training data, (manual) annotations or
pre-training neural networks. The model received an AUC-score of 0.87 for tumor
change. We also introduced a modified RANO criteria, for which an accuracy of
66% can be achieved. We show that using data from just one patient can be used
to train deep neural networks to monitor tumor change
Analysis of diagnostic climate model cloud parameterisations using large-eddy simulations: Analysis of diagnostic climate model cloud parameterisations usinglarge-eddy simulations
Current climate models often predict fractional cloud cover on the basis of a diagnostic probability density function (PDF) describing the subgrid-scale variability of the total water specific humidity, qt, favouring schemes with limited complexity. Standard shapes are uniform or triangular PDFs the width of which is assumed to scale with the gridbox
mean qt or the grid-box mean saturation specific humidity, qs. In this study, the qt variability is analysed from large-eddy simulations for two stratocumulus, two shallow cumulus, and one deep convective cases. We find that in most cases, triangles are a better approximation to the simulated PDFs than uniform distributions. In two of the 24 slices examined, the actual distributions were so strongly skewed that the simple symmetric shapes could not capture the PDF at all. The distribution width for either shape scales acceptably well with both the mean value of qt and qs, the former being a slightly better choice. The qt variance is underestimated by the fitted PDFs, but overestimated by the existing parameterisations. While the cloud fraction is in general relatively well
diagnosed from fitted or parameterised uniform or triangular PDFs, it fails to capture cases with small partial cloudiness, and in 10 – 30% of the cases misdiagnoses clouds in clear skies or vice-versa. The results suggest choosing a parameterisation with a triangular shape, where the distribution width would scale with the grid-box mean qt using a scaling factor of 0.076. This, however, is subject to the caveat that the reference simulations examined here were partly for rather small domains and driven by idealised boundary conditions
On the equivalence of two deformation schemes in quantum field theory
Two recent deformation schemes for quantum field theories on the
two-dimensional Minkowski space, making use of deformed field operators and
Longo-Witten endomorphisms, respectively, are shown to be equivalent.Comment: 14 pages, no figure. The final version is available under Open
Access. CC-B
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