This study focuses on the key numerical technique of stencil computations, used in many different scientific disciplines, and illustrates how auto-tuning can be used to produce very efficient implementations across a diverse set of current multicore architectures.

Introduction

Prolonged attentional bias to threat (AB) is associated with posttraumatic stress symptoms (PTSS). However, it is unclear whether this relationship extends to early threat detection (elicited by masked stimuli) and/or varies if AB is measured during an aversive context.

Methods

Two trauma-exposed samples of either intervention-seekers (N = 50) or community members (N = 98) completed a masked dot-probe task to measure early AB to angry faces in safe vs. aversive contexts (i.e., during threat of aversive noises).

Results

Linear mixed effects models showed that an aversive context increased the orienting responses in both samples; however, PTSS did not moderate these effects in either sample.

Limitations

Sample size and heterogeneity of trauma-type may have impacted effect of PTSS on AB.

Conclusion

These results highlight the importance of assessing AB in varying contexts and examining generalizability across populations. Given prior research, the results also suggest that increased AB in PTSS may only be present for later attentional processes rather than early threat detection, at least with behavioral methods.

Quantum materials exhibit a wide array of exotic phenomena and practically useful properties. A better understanding of these materials can provide deeper insights into fundamental physics in the quantum realm as well as advance information processing technology and sustainability. The emergence of digital quantum computers (DQCs), which can efficiently perform quantum simulations that are otherwise intractable on classical computers, provides a promising path forward for testing and analyzing the remarkable, and often counter-intuitive, behavior of quantum materials. Equipped with these new tools, scientists from diverse domains are racing towards achieving physical quantum advantage (i.e. using a quantum computer to learn new physics with a computation that cannot feasibly be run on any classical computer). The aim of this review, therefore, is to provide a summary of progress made towards this goal that is accessible to scientists across the physical sciences. We will first review the available technology and algorithms, and detail the myriad ways to represent materials on quantum computers. Next, we will showcase the simulations that have been successfully performed on currently available DQCs, emphasizing the variety of properties, both static and dynamic, that can be studied with this nascent technology. Finally, we work through three examples of how to perform various materials simulation problems on DQCs, with full code included in the supplementary material (https://stacks.iop.org/QST/6/043002/mmedia). It is our hope that this review can serve as an organized overview of progress in the field for domain experts and an accessible introduction to scientists in related fields interested in beginning to perform their own simulations of quantum materials on DQCs.

A design for a high-resolution scanning instrument is presented for in vivo imaging of the human eye at the cellular scale. This system combines adaptive optics technology with a scanning laser ophthalmoscope (SLO) to image structures with high lateral (∼2 μm) resolution. In this system, the ocular wavefront aberrations that reduce the resolution of conventional SLOs are detected by a Hartmann-Shack wavefront sensor, and compensated with two deformable mirrors in a closed-loop for dynamic correction and feedback control. A laser beam is scanned across the retina and the reflected light is captured by a photodiode, yielding a two-dimensional image of the retina at any depth. The quantity of back-scattered light from the retina is small (0.001% of reflection) and requires the elimination of all parasite reflections. As an in vivo measurement, faint cellular reflections must be detected with a low-energy source, a supraluminescent laser diode, and with brief exposures to avoid artifacts from eye movements. The current design attempts to optimize trade-offs between improved wavefront measurement and compensation of the optical aberrations by fractioning the light coming to the wavefront sensor, better sensitivity by increasing the input light energy or the exposure time and the response speed of the system. This instrument design is expected to provide sufficient resolution for visualizing photoreceptors and ganglion cells, and therefore, may be useful in diagnosing and monitoring the progression of retinal pathologies such as glaucoma or aged-related macular degeneration.

The purpose of this study was to evaluate the performance of a bimorph deformable mirror from AOptix, inserted into an adaptive optics system designed for in-vivo retinal imaging at high resolution. We wanted to determine its suitability as a wavefront corrector for vision science and ophthalmological instrumentation. We presented results obtained in a closed-loop system, and compared them with previous open-loop performance measurements. Our goal was to obtain precise wavefront reconstruction with rapid convergence of the control algorithm. The quality of the reconstruction was expressed in terms of root-mean-squared wavefront residual error (RMS), and number of frames required to perform compensation. Our instrument used a Hartmann-Shack sensor for the wavefront measurements. We also determined the precision and ability of the deformable mirror to compensate the most common types of aberrations present in the human eye (defocus, cylinder, astigmatism and coma), and the quality of its correction, in terms of maximum amplitude of the corrected wavefront. In addition to wavefront correction, we had also used the closed-loop system to generate an arbitrary aberration pattern by entering the desired Hartmann-Shack centroid locations as input to the AO controller. These centroid locations were computed in Matlab for a user-defined aberration pattern, allowing us to test the ability of the DM to generate and compensate for various aberrations. We conclude that this device, in combination with another DM based on Micro-Electro Mechanical Systems (MEMS) technology, may provide better compensation of the higher-order ocular wavefront aberrations of the human eye.

Harnessing the full power of nascent quantum processors requires the efficient management of a limited number of quantum bits with finite coherent lifetimes. Hybrid algorithms, such as the variational quantum eigensolver (VQE), leverage classical resources to reduce the required number of quantum gates. Experimental demonstrations of VQE have resulted in calculation of Hamiltonian ground states, and a new theoretical approach based on a quantum subspace expansion (QSE) has outlined a procedure for determining excited states that are central to dynamical processes. We use a superconducting-qubit-based processor to apply the QSE approach to the H2 molecule, extracting both ground and excited states without the need for auxiliary qubits or additional minimization. Further, we show that this extended protocol can mitigate the effects of incoherent errors, potentially enabling larger-scale quantum simulations without the need for complex error-correction techniques.

The recent transformation from an environment where gains in computational performance came from increasing clock frequency and other hardware engineering innovations, to an environment where gains are realized through the deployment of ever increasing numbers of modest performance cores has profoundly changed the landscape of scientific application programming. This exponential increase in core count represents both an opportunity and a challenge: access to petascale simulation capabilities and beyond will require that this concurrency be efficiently exploited. The problem for application programmers is further compounded by the diversity of multicore architectures that are now emerging [4]. From relatively complex out-of-order CPUs with complex cache structures, to relatively simple cores that support hardware multithreading, to chips that require explicit use of software controlled memory, designing optimal code for these different platforms represents a serious impediment. An emerging solution to this problem is auto-tuning: the automatic generation of many versions of a code kernel that incorporate various tuning strategies, and the benchmarking of these to select the highest performing version. Typical tuning strategies might include: maximizing incore performance with loop unrolling and restructuring; maximizing memory bandwidth by exploiting non-uniform memory access (NUMA), engaging prefetch by directives; and minimizing memory traffic by cache blocking or array padding. Often a key parameter is associated with each tuning strategy (e.g., the amount of loop unrolling or the cache blocking factor), and these parameters must be explored in addition to the layering of the basic strategies themselves.

Helicobacter pylori colonizes half of the world's population and is responsible for a significant disease burden by causing gastritis, peptic ulcers, and gastric cancer. The development of host inflammation drives these diseases, but there are still open questions in the field about how H. pylori controls this process. We characterized H. pylori inflammation using an 8-month mouse infection time course and comparison of the wild type (WT) and a previously identified mutant lacking the TlpA chemoreceptor that causes elevated inflammation. Our work shows that H. pylori chronic-stage corpus inflammation undergoes surprising fluctuations, with changes in Th17 and eosinophil numbers. The H. pylori tlpA mutant changed the inflammation temporal characteristics, resulting in different inflammation from the wild type at some time points. tlpA mutants have equivalent total and gland colonization in late-stage infections. During early infection, in contrast, they show elevated gland and total colonization compared to those by WT. Our results suggest the chronic inflammation setting is dynamic and may be influenced by colonization properties of early infection.