Topological Order and Memory Time in Marginally Self-Correcting Quantum Memory

We examine two proposals for marginally self-correcting quantum memory, the cubic code by Haah and the welded code by Michnicki. In particular, we prove explicitly that they are absent of topological order above zero temperature, as their Gibbs ensembles can be prepared via a short-depth quantum circuit from classical ensembles. Our proof technique naturally gives rise to the notion of free energy associated with excitations. Further, we develop a framework for an ergodic decomposition of Davies generators in CSS codes which enables formal reduction to simpler classical memory problems. We then show that memory time in the welded code is doubly exponential in inverse temperature via the Peierls argument. These results introduce further connections between thermal topological order and self-correction from the viewpoint of free energy and quantum circuit depth.Comment: 19 pages, 18 figure

Exploiting Treg Plasticity and Immune Cell Metabolism to Control Stromal Keratitis

Ocular infections with Herpes Simplex virus (HSV) can have damaging consequences one of which is the loss of vision due to a chronic inflammatory reaction. T cells of the Th1 subset appear to be the main orchestrators of the inflammatory reaction. Certain components of the host immunity help to suppress the severity of lesions. My research focuses on one such protective component - CD4 regulatory T cells (Treg). We showed that Treg can initially function to suppress lesion development but this function can be lost and become pro-inflammatory. This provided the challenge of why this so-called plasticity occurred and how might it be prevented from developing. I was able to show that inhibiting the epigenetic modification occurring within the Foxp3 gene curbed the Treg plasticity. This reversal of plasticity was sufficient to enhance the control of SK lesion severity.Another focus of my research was to find ways to rebalance immune subsets in SK lesions. We pioneered a new approach which exploited different metabolic requirements for the pro-inflammatory and regulatory T cells in lesions. Pro-inflammatory T cells such as Th1 use glucose for its function, whereas Treg rely on fatty acid oxidation and to a lesser extent on glucose. Using 2-Deoxyglucose which inhibits glucose utilization, the pro-inflammatory Th1 were affected but not Treg thereby reducing lesion severity. It was important not to impair glucose utilization when replicating virus was present since this could result in virus spreading to the brain to cause encephalitis.We also evaluated if Treg were involved in repairing SK lesions. We could show that Treg within the cornea made a tissue repair molecule called Amphiregulin peaking during lesion development. This expression of Amphiregulin was partly dependent on the cytokines IL-18 and IL-12 which acted together to induce the expression of Amphiregulin. Moreover, enhancing the levels of IL-18 in the cornea using an expression plasmid helped resolve SK lesion severity, an effect which correlated with increased Amphiregulin expression by Treg.In conclusion, my studies revealed several innovative approaches which might be moved to the clinic to help minimize the consequence of an important cause of human blindness

Exploiting the ability of Self Organizing Networks for inter-cell interference coordination for emergency communications in cellular networks

Title from PDF of title page, viewed on June 15, 2015Thesis advisor: Cory BeardVitaIncludes bibliographic references (pages 56-57)Thesis (M.S.)--School of Computing and Engineering. University of Missouri--Kansas City, 2014In the current scenario, radio planning of wireless cellular networks and analysis of radio performance should be agile because it is expected that in the near future we will be reaching to the point where there will be as many mobile devices as people in the world. So, there should be a rapid revolution in technology which can aid in the management of resources and maximization of throughput to satisfy users effectively. LTE and LTE-Advanced is designed to meet high bit rate service requirements; however, the initial challenge of the wireless channel, such as limited spectrum, leads to frequency reuse but also irrevocable interference. This thesis gives a holistic conspectus of interference coordination in LTE cellular systems utilizing the ability of Self Organizing Networks (SON). LTE uses a universal frequency reuse concept and the only interference observed in LTE is inter-cell interference. In a network where users are randomly distributed over three cells, it manages resources between the base stations by restricting some resource blocks for Cell Edge Users (CEU) of the neighboring cell and other resource blocks for Cell Center Users (CCU). This is done in a semi-static approach by taking into account the location of the user and varying channel conditions. Cell edge users and cell center users are distinguished based upon the SINR level. The management of the resources are regulated as per the user requirements and coordinated by the neighboring cells. The results have been simulated in two different ambiances viz., normal traffic and the emergency condition to show its performance in exigency. The throughput of the CCUs and CEUs in normal traffic has been compared. Also, the approach and results are shown to be highly reliable.Introduction -- Background -- Our work -- MATLAB code implementation -- Results and analysis -- Conclusion and future scop

Augmented Reality Meets Computer Vision : Efficient Data Generation for Urban Driving Scenes

The success of deep learning in computer vision is based on availability of large annotated datasets. To lower the need for hand labeled images, virtually rendered 3D worlds have recently gained popularity. Creating realistic 3D content is challenging on its own and requires significant human effort. In this work, we propose an alternative paradigm which combines real and synthetic data for learning semantic instance segmentation and object detection models. Exploiting the fact that not all aspects of the scene are equally important for this task, we propose to augment real-world imagery with virtual objects of the target category. Capturing real-world images at large scale is easy and cheap, and directly provides real background appearances without the need for creating complex 3D models of the environment. We present an efficient procedure to augment real images with virtual objects. This allows us to create realistic composite images which exhibit both realistic background appearance and a large number of complex object arrangements. In contrast to modeling complete 3D environments, our augmentation approach requires only a few user interactions in combination with 3D shapes of the target object. Through extensive experimentation, we conclude the right set of parameters to produce augmented data which can maximally enhance the performance of instance segmentation models. Further, we demonstrate the utility of our approach on training standard deep models for semantic instance segmentation and object detection of cars in outdoor driving scenes. We test the models trained on our augmented data on the KITTI 2015 dataset, which we have annotated with pixel-accurate ground truth, and on Cityscapes dataset. Our experiments demonstrate that models trained on augmented imagery generalize better than those trained on synthetic data or models trained on limited amount of annotated real data

Topological order and memory time in marginally-self-correcting quantum memory

We examine two proposals for marginally-self-correcting quantum memory: the cubic code by Haah and the welded code by Michnicki. In particular, we prove explicitly that they are absent of topological order above zero temperature, as their Gibbs ensembles can be prepared via a short-depth quantum circuit from classical ensembles. Our proof technique naturally gives rise to the notion of free energy associated with excitations. Further, we develop a framework for an ergodic decomposition of Davies generators in CSS codes which enables formal reduction to simpler classical memory problems. We then show that memory time in the welded code is doubly exponential in inverse temperature via the Peierls argument. These results introduce further connections between thermal topological order and self-correction from the viewpoint of free energy and quantum circuit depth

Universal tripartite entanglement in one-dimensional many-body systems

Motivated by conjectures in holography relating the entanglement of purification and reflected entropy to the entanglement wedge cross-section, we introduce two related non-negative measures of tripartite entanglement $g$ and $h$. We prove structure theorems which show that states with nonzero $g$ or $h$ have nontrivial tripartite entanglement. We then establish that in 1D these tripartite entanglement measures are universal quantities that depend only on the emergent low-energy theory. For a gapped system, we argue that either $g\neq 0$ and $h=0$ or $g=h=0$, depending on whether the ground state has long-range order. For a critical system, we develop a numerical algorithm for computing $g$ and $h$ from a lattice model. We compute $g$ and $h$ for various CFTs and show that $h$ depends only on the central charge whereas $g$ depends on the whole operator content.Comment: 5+16 pages, 4+5 figure