Investigation of heavy-heavy pseudoscalar mesons in thermal QCD Sum Rules

We investigate the mass and decay constant of the heavy-heavy pseudoscalar, $B_c$, $\eta_c$ and $\eta_b$ mesons in the framework of finite temperature QCD sum rules. The annihilation and scattering parts of spectral density are calculated in the lowest order of perturbation theory. Taking into account the additional operators arising at finite temperature, the nonperturbative corrections are also evaluated. The masses and decay constants remain unchanged under $T\cong 100 ~MeV$, but after this point, they start to diminish with increasing the temperature. At critical or deconfinement temperature, the decay constants reach approximately to 35% of their values in the vacuum, while the masses are decreased about 7%, 12% and 2% for $B_c$, $\eta_c$ and $\eta_b$ states, respectively. The results at zero temperature are in a good consistency with the existing experimental values as well as predictions of the other nonperturbative approaches.Comment: 11 Pages, 2 Tables and 6 Figure

Perceptually guided Computer-Generated Holography

Computer-Generated Holography (CGH) promises to deliver genuine, high-quality visuals at any depth. We argue that combining CGH and perceptually guided graphics can soon lead to practical holographic display systems that deliver perceptually realistic images. We propose a new CGH method called metameric varifocal holograms. Our CGH method generates images only at a user’s focus plane while displayed images are statistically correct and indistinguishable from actual targets across peripheral vision (metamers). Thus, a user observing our holograms is set to perceive a high quality visual at their gaze location. At the same time, the integrity of the image follows a statistically correct trend in the remaining peripheral parts. We demonstrate our differentiable CGH optimization pipeline on modern GPUs, and we support our findings with a display prototype. Our method will pave the way towards realistic visuals free from classical CGH problems, such as speckle noise or poor visual quality

A perceptual model of motion quality for rendering with adaptive refresh-rate and resolution

Limited GPU performance budgets and transmission bandwidths mean that real-time rendering often has to compromise on the spatial resolution or temporal resolution (refresh rate). A common practice is to keep either the resolution or the refresh rate constant and dynamically control the other variable. But this strategy is non-optimal when the velocity of displayed content varies. To find the best trade-off between the spatial resolution and refresh rate, we propose a perceptual visual model that predicts the quality of motion given an object velocity and predictability of motion. The model considers two motion artifacts to establish an overall quality score: non-smooth (juddery) motion, and blur. Blur is modeled as a combined effect of eye motion, finite refresh rate and display resolution. To fit the free parameters of the proposed visual model, we measured eye movement for predictable and unpredictable motion, and conducted psychophysical experiments to measure the quality of motion from 50 Hz to 165 Hz. We demonstrate the utility of the model with our on-the-fly motion-adaptive rendering algorithm that adjusts the refresh rate of a G-Sync-capable monitor based on a given rendering budget and observed object motion. Our psychophysical validation experiments demonstrate that the proposed algorithm performs better than constant-refresh-rate solutions, showing that motion-adaptive rendering is an attractive technique for driving variable-refresh-rate displays.</jats:p

Beyond blur: real-time ventral metamers for foveated rendering

To peripheral vision, a pair of physically different images can look the same. Such pairs are metamers relative to each other, just as physically-different spectra of light are perceived as the same color. We propose a real-time method to compute such ventral metamers for foveated rendering where, in particular for near-eye displays, the largest part of the framebuffer maps to the periphery. This improves in quality over state-of-the-art foveation methods which blur the periphery. Work in Vision Science has established how peripheral stimuli are ventral metamers if their statistics are similar. Existing methods, however, require a costly optimization process to find such metamers. To this end, we propose a novel type of statistics particularly well-suited for practical real-time rendering: smooth moments of steerable filter responses. These can be extracted from images in time constant in the number of pixels and in parallel over all pixels using a GPU. Further, we show that they can be compressed effectively and transmitted at low bandwidth. Finally, computing realizations of those statistics can again be performed in constant time and in parallel. This enables a new level of quality for foveated applications such as such as remote rendering, level-of-detail and Monte-Carlo denoising. In a user study, we finally show how human task performance increases and foveation artifacts are less suspicious, when using our method compared to common blurring

Beam forming for a laser based auto-stereoscopic multi-viewer display

An auto-stereoscopic back projection display using a RGB multi-emitter laser illumination source and micro-optics to provide a wider view is described. The laser optical properties and the speckle due to the optical system configuration and its diffusers are characterised

Optimizing decomposition of software architecture for local recovery

Cataloged from PDF version of article.The increasing size and complexity of software systems has led to an amplified number of potential failures and as such makes it harder to ensure software reliability. Since it is usually hard to prevent all the failures, fault tolerance techniques have become more important. An essential element of fault tolerance is the recovery from failures. Local recovery is an effective approach whereby only the erroneous parts of the system are recovered while the other parts remain available. For achieving local recovery, the architecture needs to be decomposed into separate units that can be recovered in isolation. Usually, there are many different alternative ways to decompose the system into recoverable units. It appears that each of these decomposition alternatives performs differently with respect to availability and performance metrics. We propose a systematic approach dedicated to optimizing the decomposition of software architecture for local recovery. The approach provides systematic guidelines to depict the design space of the possible decomposition alternatives, to reduce the design space with respect to domain and stakeholder constraints and to balance the feasible alternatives with respect to availability and performance. The approach is supported by an integrated set of tools and illustrated for the open-source MPlayer software