arXiv subjects

Christian Zimmermann

Publications and source records attributed to Christian Zimmermann.

31 records · Page 2Linked to original sources

arXiv2021

Coherent Spin Preparation of Indium Donor Qubits in Single ZnO Nanowires

Shallow donors in ZnO are promising candidates for photon-mediated quantum technologies. Utilizing the indium donor, we show that favorable donor-bound exciton optical and electron spin properties are retained in isolated ZnO nanowires. The inhomogeneous optical linewidth of single nanowires (60 GHz) is within a factor of 2 of bulk single-crystalline ZnO. Spin initialization via optical pumping is demonstrated and coherent population trapping is observed. The two-photon absorption width approaches the theoretical limit expected due to the hyperfine interaction between the indium nuclear spin and the donor-bound electron.

quant-ph↗

arXiv2021

Double parton distributions in the nucleon from lattice simulations

We provide a first study of Mellin moments of double parton distributions (DPDs) in the nucleon on the lattice, where we consider several combinations of quark flavors and polarizations. These are accessible through two-current correlations, which can be obtained by evaluating four-point functions. In this context we consider all possible Wick contractions, where for almost all of them sufficiently clear signals are obtained. In the present study, we employ an $n_f = 2 + 1$ CLS ensemble on a $96 \times 32^3$ lattice with lattice spacing $a = 0.0856\ \mathrm{fm}$ and the pseudoscalar masses $m_π= 355\ \mathrm{MeV}$ and $m_K = 441\ \mathrm{MeV}$.

hep-lat↗

arXiv2021

Double parton distributions in the nucleon from lattice QCD

We evaluate nucleon four-point functions in the framework of lattice QCD in order to extract the first Mellin moment of double parton distributions (DPDs) in the unpolarized proton. In this first study, we employ an nf = 2 + 1 ensemble with pseudoscalar masses of mpi = 355 MeV and mK = 441 MeV. The results are converted to the scale mu = 2 GeV. Our calculation includes all Wick contractions, and for almost all of them a good statistical signal is obtained. We analyze the dependence of the DPD Mellin moments on the quark flavor and the quark polarization. Furthermore, the validity of frequently used factorization assumptions is investigated.

hep-lat↗

arXiv2021

Determination of the Collins-Soper Kernel from Lattice QCD

We present lattice results for the non-perturbative Collins-Soper (CS) kernel, which describes the energy-dependence of transverse momentum-dependent parton distributions (TMDs). The CS kernel is extracted from the ratios of first Mellin moments of quasi-TMDs evaluated at different nucleon momenta.The analysis is done with dynamical $N_f=2+1$ clover fermions for the CLS ensemble H101 ($a=0.0854\,\mathrm{fm}$, $m_π=m_K=422\,\mathrm{MeV}$). The computed CS kernel is in good agreement with experimental extractions and previous lattice studies.

hep-lat↗

arXiv2021

Contrastive Representation Learning for Hand Shape Estimation

This work presents improvements in monocular hand shape estimation by building on top of recent advances in unsupervised learning. We extend momentum contrastive learning and contribute a structured collection of hand images, well suited for visual representation learning, which we call HanCo. We find that the representation learned by established contrastive learning methods can be improved significantly by exploiting advanced background removal techniques and multi-view information. These allow us to generate more diverse instance pairs than those obtained by augmentations commonly used in exemplar based approaches. Our method leads to a more suitable representation for the hand shape estimation task and shows a 4.7% reduction in mesh error and a 3.6% improvement in F-score compared to an ImageNet pretrained baseline. We make our benchmark dataset publicly available, to encourage further research into this direction.

cs.CV↗

arXiv2021

Double parton distributions in the pion from lattice QCD

We perform a lattice study of double parton distributions in the pion, using the relationship between their Mellin moments and pion matrix elements of two local currents. A good statistical signal is obtained for almost all relevant Wick contractions. We investigate correlations in the spatial distribution of two partons in the pion, as well as correlations involving the parton polarisation. The patterns we observe depend significantly on the quark mass. We investigate the assumption that double parton distributions approximately factorise into a convolution of single parton distributions.

hep-lat↗

arXiv2019

Two-current correlations and DPDs for the nucleon on the lattice

We calculate correlation functions of two local operators within the nucleon carrying momentum. We resolve their dependence on the spatial distance of the currents. This is carried out for all Wick contractions, taking into account several operator insertion types. The resulting four-point functions can be related to parton distribution functions as well as to Mellin moments of double parton distributions. For the latter, we analyze their quark spin and flavor dependency. In this first study, we employ an $N_F = 2 + 1$ CLS ensemble on a $96 \times 32^3$ lattice with lattice spacing $a = 0.0856\ \mathrm{fm}$ and the pseudoscalar masses $m_π= 355\ \mathrm{MeV}$ and $m_K = 441\ \mathrm{MeV}$.

hep-lat↗

arXiv2019

FreiHAND: A Dataset for Markerless Capture of Hand Pose and Shape from Single RGB Images

Estimating 3D hand pose from single RGB images is a highly ambiguous problem that relies on an unbiased training dataset. In this paper, we analyze cross-dataset generalization when training on existing datasets. We find that approaches perform well on the datasets they are trained on, but do not generalize to other datasets or in-the-wild scenarios. As a consequence, we introduce the first large-scale, multi-view hand dataset that is accompanied by both 3D hand pose and shape annotations. For annotating this real-world dataset, we propose an iterative, semi-automated `human-in-the-loop' approach, which includes hand fitting optimization to infer both the 3D pose and shape for each sample. We show that methods trained on our dataset consistently perform well when tested on other datasets. Moreover, the dataset allows us to train a network that predicts the full articulated hand shape from a single RGB image. The evaluation set can serve as a benchmark for articulated hand shape estimation.

cs.CV↗

arXiv2018

Two-current correlations in the pion on the lattice

We perform a systematic study of the correlation functions of two quark currents in a pion using lattice QCD. We obtain good signals for all but one of the relevant Wick contractions of quark fields. We investigate the quark mass dependence of our results and test the importance of correlations between the quark and the antiquark in the pion. Our lattice data are compared with predictions from chiral perturbation theory.

hep-lat↗

arXiv2018

3D Human Pose Estimation in RGBD Images for Robotic Task Learning

We propose an approach to estimate 3D human pose in real world units from a single RGBD image and show that it exceeds performance of monocular 3D pose estimation approaches from color as well as pose estimation exclusively from depth. Our approach builds on robust human keypoint detectors for color images and incorporates depth for lifting into 3D. We combine the system with our learning from demonstration framework to instruct a service robot without the need of markers. Experiments in real world settings demonstrate that our approach enables a PR2 robot to imitate manipulation actions observed from a human teacher.

cs.CV↗

arXiv2017

Learning to Estimate 3D Hand Pose from Single RGB Images

Low-cost consumer depth cameras and deep learning have enabled reasonable 3D hand pose estimation from single depth images. In this paper, we present an approach that estimates 3D hand pose from regular RGB images. This task has far more ambiguities due to the missing depth information. To this end, we propose a deep network that learns a network-implicit 3D articulation prior. Together with detected keypoints in the images, this network yields good estimates of the 3D pose. We introduce a large scale 3D hand pose dataset based on synthetic hand models for training the involved networks. Experiments on a variety of test sets, including one on sign language recognition, demonstrate the feasibility of 3D hand pose estimation on single color images.

cs.CV↗

arXiv2017

Double Parton Distributions of the Pion

The effects of double hard interactions are no longer negligible at energy scales reached at the LHC. Double parton scattering (DPS) processes are often described by taking the product of two single parton scattering processes assuming that interference effects are very small. We calculate four point functions (4pt-functions), which appear in the the DPS cross section, employing lattice techniques. We consider a pion at rest and test the validity of the afore-mentioned factorization assumption by convoluting two pion form factors and comparing the result to the 4pt data. For our calculations we use a $N_f = 2$ gauge ensemble on a $40^3 \times 64$ lattice, with lattice spacing $a = 0.071$ fm and pion mass $m_π = 288.8$ MeV.

hep-lat↗

arXiv2015

A Categorization of Transparency-Enhancing Technologies

A variety of Transparency-Enhancing Technologies has been presented during the past years. However, investigation of frameworks for classification and assessment of Transparency-Enhancing Technologies has lacked behind. The lack of precise classification and categorization approaches poses an obstacle not only to systematic requirements analysis for Transparency-Enhancing Technologies but also to investigation and analysis of their capabilities and their suitability to contribute to privacy protection. This paper addresses this research gap. In particular, it presents a set of categorization parameters for describing the properties and functionality of a Transparency-Enhancing Technology on the one hand, and a categorization of Transparency-Enhancing Technologies on the other hand.

cs.CY↗