Abstract
Physically-based synthesis of high quality imagery, including global illumination light transport phenomena, results in a significant workload, which makes interactive rendering a very challenging task. We propose a VPL-based ray tracing approach that runs entirely in the GPU and achieves interactive frame rates while handling global illumination light transport phenomena. This approach is based on clustering both shading points and VPLs and computing visibility only among clusters' representatives. A new massively parallel K-means clustering algorithm, enables efficient execution in the GPU. Rendering artifacts, that could result from the piecewise constant approximation of the VPLs/shading points visibility function introduced by the clustering, are smoothed away by resorting to an innovative approach based on fuzzy clustering and weighted interpolation of the visibility function. The effectiveness of the proposed approach is experimentally verified for a collection of scenes, with frame rates larger than 3 fps and up to 25 fps being demonstrated.(c) 2022 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Abstract
Variational quantum circuits are being used as versatile quantum machine learning models. Some empirical results exhibit an advantage in supervised and generative learning tasks. However, when applied to reinforcement learning, less is known. In this work, we considered a variational quantum circuit composed of a low-depth hardware-efficient ansatz as the parameterized policy of a reinforcement learning agent. We show that an epsilon-approximation of the policy gradient can be obtained using a logarithmic number of samples concerning the total number of parameters. We empirically verify that such quantum models behave similarly to typical classical neural networks used in standard benchmarking environments and quantum control, using only a fraction of the parameters. Moreover, we study the barren plateau phenomenon in quantum policy gradients using the Fisher information matrix spectrum.

Abstract
Traditional post-hoc high-fidelity scientific visualization (HSV) of numerical simulations requires multiple I/O check-pointing to inspect the simulation progress. The costs of these I/O operations are high and can grow exponentially with increasing problem sizes. In situ HSV dispenses with costly check-pointing I/O operations, but requires additional computing resources to generate the visualization, increasing power and energy consumption. In this paper we present LOOM, a new interweaving approach supported by a task scheduling framework to allow tightly coupled in situ visualization without significantly adding to the overall simulation runtime. The approach exploits the idle times of the numerical simulation threads, due to workload imbalances, to perform the visualization steps. Overall execution time (simulation plus visualization) is minimized. Power requirements are also minimized by sharing the same computational resources among numerical simulation and visualization tasks. We demonstrate that LOOM reduces time to visualization by 3 × compared to a traditional non-interwoven pipeline. Our results here demonstrate good potential for additional gains for large distributed-memory use cases with larger interleaving opportunities. © 2021 ACM.

Abstract
The computational requirements of a full physically-based global illumination solution are significant, currently precluding its solution on even a powerful modern PC in reasonable let alone real time. A key factor to consider if we are ever to achieve so-called "Realism in Real-Time", is that we are computing images for humans to look at. Although the human visual system is very good, it is by no means perfect. By understanding what the human does, or perhaps more importantly, does not see, enables us to save significant computation effort without any loss of perceptual quality of the resultant image. This paper describes the novel techniques of selective rendering which allow us to direct computational resources to those areas of high perceptual importance while avoiding computing any detail which will not be perceived by the viewer. Such selective rendering methods offer us the real possibility of achieving high fidelity graphics of complex scenes at interactive rates.

Abstract
Bidirectional Texture Functions (BTF) allow high quality visualization of real world materials exhibiting complex appearance and details that can not be faithfully represented using simpler analytical or parametric representations. Accurate representations of such materials require huge amounts of data, hindering real time rendering. BTFs compress the raw original data, constituting a compromise between visual quality and rendering time. This paper presents an implementation of a state of the art BTF representation on the GPU, allowing interactive high fidelity visualization of complex geometric models textured with multiple BTFs. Scalability with respect to the geometric complexity, amount of lights and number of BTFs is also studied.

Abstract
Even though three-dimensional (3D) displays have been introduced in relatively recent times in the context of display technology, they have undergone a rapid evolution, to the point that a plethora of equipment able to reproduce dynamic three-dimensional scenes in real time is now becoming commonplace in the consumer market. This paper's main contributions are (1) a clear definition of a 3D display, based on the visual depth cues supported, and (2) a hierarchical taxonomy of classes and subclasses of 3D displays, based on a set of properties that allows an unambiguous and systematic classification scheme for three-dimensional displays. Five main types of 3D displays are thus defined -two of those new-, aiming to provide a taxonomy that is largely backwards-compatible, but that also clarifies prior inconsistencies in the literature. This well-defined outline should also enable exploration of the 3D display space and devising of new 3D display systems.