Geometric linearisation for optimal transport with strongly p-convex cost

We prove a geometric linearisation result for minimisers of optimal transport problems where the cost-function is strongly p-convex and of p-growth. Initial and target measures are allowed to be rough, but are assumed to be close to Lebesgue measure.Comment: Slightly simplified assumptions and improved presentatio

Automobility and the Future of Transport

https://research.library.kutztown.edu/englishENG366posters/1002/thumbnail.jp

A response-matrix-centred approach to presenting cross-section measurements

The current canonical approach to publishing cross-section data is to unfold the reconstructed distributions. Detector effects like efficiency and smearing are undone mathematically, yielding distributions in true event properties. This is an ill-posed problem, as even small statistical variations in the reconstructed data can lead to large changes in the unfolded spectra. This work presents an alternative or complementary approach: the response-matrix-centred forward-folding approach. It offers a convenient way to forward-fold model expectations in truth space to reconstructed quantities. These can then be compared to the data directly, similar to what is usually done with full detector simulations within the experimental collaborations. For this, the detector response (efficiency and smearing) is parametrised as a matrix. The effects of the detector on the measurement of a given model is simulated by simply multiplying the binned truth expectation values by this response matrix. Systematic uncertainties in the detector response are handled by providing a set of matrices according to the prior distribution of the detector properties and marginalising over them. Background events can be included in the likelihood calculation by giving background events their own bins in truth space. To facilitate a straight-forward use of response matrices, a new software framework has been developed: the Response Matrix Utilities (\ReMU). \ReMU is a Python package distributed via the Python Package Index. It only uses widely available, standard scientific Python libraries and does not depend on any custom experiment-specific software. It offers all methods needed to build response matrices from Monte Carlo data sets, use the response matrix to forward-fold truth-level model predictions, and compare the predictions to real data using Bayesian or frequentist statistical inference

On global absence of Lavrentiev gap for functionals with (p,q)-growth

We prove that for convex vectorial functionals with (p,q)-growth the Lavrentiev phenomenon does not occur up to the boundary when (p,q) are suitably restricted. Under minimal assumptions on the regularity of the domain and the boundary data, we obtain results for autonomous and non-autonomous functionals, under natural, controlled and controlled duality growth bounds

Measurement of neutrino interactions in gaseous argon with T2K

The T2K near-detector, ND280, employs three large argon gas TPCs (Time Projection Chambers) for particle tracking and identification. The gas inside the TPCs can be used as an active target to study the neutrino interactions in great detail. The low density of the gas leads to very low track energy thresholds, allowing the reconstruction of very low momentum tracks, e.g. protons with kinetic energies down to O(1 MeV). Since different nuclear interaction models vary considerably in their predictions of those low momentum track multiplicities, this makes neutrino interactions on gases a powerful probe to test those models. The TPCs operate with an argon-based gas mixture (95% by volume) and have been exposed to the T2K neutrino beam since the beginning of the experiment in 2010. Due to the low total mass of the gas, neutrino argon interactions happen only rarely, compared to the surrounding scintillator-based detectors. We expect about 600 such events in the recorded data so far (about 200 in the fiducial volume). We are able to separate those events from the background and thus demonstrate the viability of using gaseous argon as a target for a neutrino beam. This enables us to do a cross-section measurement on gaseous argon, the first measurement of this kind. All previous neutrino cross-section measurements on argon were performed in liquid argon TPCs

Automobility and the Future of Transport

This article explores the history of automobility as ideology, its effect on individuals and its possible future. In the USA in the early 20th century the automobile served to solve the crisis of individualism, created by Taylorism and the rise of the scientific method. To the people of the time the car was associated with freedom and individuality. Freedom through the automobile however was and would never be universally accessible. Furthermore examining the real life consequences of increasing mobility reveals unforeseen effects, mainly pollution, traffic and fragmentation of society. This paper proposes adoption of programs favoring sustainable modes of transportation and a reduction of unhealthy automobility, in order to combat progressing pollution of the environment and fragmentation of society

Treatment of flux shape uncertainties in unfolded, flux-averaged neutrino cross-section measurements

The exact way of treating flux shape uncertainties in unfolded, flux-averaged neutrino cross-section measurements can lead to subtle issues when comparing the results to model predictions. There is a difference between reporting a cross section in the (unknown) real flux, and reporting a cross section that was extrapolated from the (unknown) real flux to a fixed reference flux. A lot of (most?) current analyses do the former, while the results are compared to model predictions as if they were the latter. This leads to (part of) the flux shape uncertainty being ignored, potentially leading to wrong physics conclusions. The size of the effect is estimated to be sub-dominant, but non-negligible in two example measurements from T2K and MINERvA. This paper describes how the issue arises and provides instructions for possible ways how to treat the flux shape uncertainties correctly.Comment: 11 pages, 4 figures, accepted manuscrip

Boundary regularity results for minimisers of convex functionals with (p,q)(p,q)-growth

We prove improved differentiability results for relaxed minimisers of vectorial convex functionals with $(p, q)$-growth, satisfying a H\"older-growth condition in $x$. We consider both Dirichlet and Neumann boundary data. In addition, we obtain a characterisation of regular boundary points for such minimisers. In particular, in case of homogeneous boundary conditions, this allows us to deduce partial boundary regularity of relaxed minimisers on smooth domains for radial integrands. We also obtain some partial boundary regularity results for non-homogeneous Neumann boundary conditions.Comment: Accepted version, 71 pages, 3 figures. Differentiablility results improved to include the limit cas