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We present an open-source software package, VAN-DAMME (Versatile Approaches to Numerically Design, Accelerate, and Manipulate Magnetic Excitations), for massively-parallelized quantum optimal control (QOC) calculations of multi-qubit systems. To enable large QOC calculations, the VAN-DAMME software package utilizes symmetry-based techniques with custom GPU-enhanced algorithms. This combined approach allows for the simultaneous computation of hundreds of matrix exponential propagators that efficiently leverage the intra-GPU parallelism found in high-performance GPUs. In addition, to maximize the computational efficiency of the VAN-DAMME code, we carried out several extensive tests on data layout, computational complexity, memory requirements, and performance. These extensive analyses allowed us to develop computationally efficient approaches for evaluating complex-valued matrix exponential propagators based on Padé approximants. To assess the computational performance of our GPU-accelerated VAN-DAMME code, we carried out QOC calculations of systems containing 10 - 15 qubits, which showed that our GPU implementation is 18.4× faster than the corresponding CPU implementation. Our GPU-accelerated enhancements allow efficient calculations of multi-qubit systems, which can be used for the efficient implementation of QOC applications across multiple domains. Program summary: Program Title: VAN-DAMME CPC Library link to program files:: https://doi.org/10.17632/zcgw2n5bjf.1 Licensing provisions: GNU General Public License 3 Programming language: C++ and CUDA Nature of problem: The VAN-DAMME software package utilizes GPU-accelerated routines and new algorithmic improvements to compute optimized time-dependent magnetic fields that can drive a system from a known initial qubit configuration to a specified target state with a large (≈1) transition probability. Solution method: Quantum control, GPU acceleration, analytic gradients, matrix exponential, and gradient ascent optimization.

We present a new software module, QRCODE (Quantum Research for Calculating Optically Driven Excitations), for massively parallelized real-time time-dependent density functional theory (RT-TDDFT) calculations of periodic systems in the open-source Qbox software package. Our approach utilizes a custom implementation of a fast Fourier transformation scheme that significantly reduces inter-node message passing interface (MPI) communication of the major computational kernel and shows impressive scaling up to 16,344 CPU cores. In addition to improving computational performance, QRCODE contains a suite of various time propagators for accurate RT-TDDFT calculations. As benchmark applications of QRCODE, we calculate the current density and optical absorption spectra of hexagonal boron nitride (h-BN) and photo-driven reaction dynamics of the ozone-oxygen reaction. We also calculate the second and higher harmonic generation of monolayer and multi-layer boron nitride structures as examples of large material systems. Our optimized implementation of RT-TDDFT in QRCODE enables large-scale calculations of real-time electron dynamics of chemical and material systems with enhanced computational performance and impressive scaling across several thousand CPU cores.

We extend our recently developed sparse-stochastic fragmented exchange formalism for ground-state near-gap hybrid DFT to calculate absorption spectra within linear-response time-dependent generalized Kohn-Sham DFT (LR-GKS-TDDFT) for systems consisting of thousands of valence electrons within a grid-based/plane-wave representation. A mixed deterministic/fragmented-stochastic compression of the exchange kernel, here using long-range explicit exchange functionals, provides an efficient method for accurate optical spectra. Both real-time propagation as well as frequency-resolved Casida-equation-type approaches for spectra are presented, and the method is applied to large molecular dyes.

We present an open-source software package, TRAVOLTA (Terrific Refinements to Accelerate, Validate, and Optimize Large Time-dependent Algorithms), for carrying out massively parallelized quantum optimal control calculations on GPUs. The TRAVOLTA software package is a significant overhaul of our previous NIC-CAGE algorithm and also includes algorithmic improvements to the gradient ascent procedure to enable faster convergence. We examine three different variants of GPU parallelization to assess their performance in constructing optimal control fields in a variety of quantum systems. In addition, we provide several examples with extensive benchmarks of our GPU-enhanced TRAVOLTA code to show that it generates the same results as previous CPU-based algorithms but with a speedup that is more than ten times faster. Our GPU enhancements and algorithmic improvements enable large quantum optimal control calculations that can be efficiently and routinely executed on modern multi-core computational hardware. Program summary: Program Title: TRAVOLTA CPC Library link to program files: https://doi.org/10.17632/grwppm37rn.1 Licensing provisions: GNU General Public License 3 Programming language: C++, openBLAS, and CUDA Supplementary material: Brief review of LU decomposition, raw numerical values used to generate Fig. 6 in the main text, and input examples for the TRAVOLTA software package. Nature of problem: The TRAVOLTA software package utilizes GPU accelerated routines and new algorithmic improvements to compute optimized electric fields that can drive a system from a known initial vibrational eigenstate to a specified final quantum state with a large (≈1) transition probability. Solution method: Quantum control, GPU acceleration, analytic gradients, Crank-Nicolson propagation, and gradient ascent optimization.

We present a new velocity-gauge real-time, time-dependent density functional tight-binding (VG-rtTDDFTB) implementation in the open-source DFTB+ software package (https://dftbplus.org) for probing electronic excitations in large, condensed matter systems. Our VG-rtTDDFTB approach enables real-time electron dynamics simulations of large, periodic, condensed matter systems containing thousands of atoms with a favorable computational scaling as a function of system size. We provide computational details and benchmark calculations to demonstrate its accuracy and computational parallelizability on a variety of large material systems. As a representative example, we calculate laser-induced electron dynamics in a 512-atom amorphous silicon supercell to highlight the large periodic systems that can be examined with our implementation. Taken together, our VG-rtTDDFTB approach enables new electron dynamics simulations of complex systems that require large periodic supercells, such as crystal defects, complex surfaces, nanowires, and amorphous materials.

The study aimed to identify the predictive ability of social anxiety in Internet addiction among university students, by relying on the relational descriptive approach. The study sample consisted of (462) male and female students from the Faculty of Educational Sciences at the Hashemite University who were selected through the available random method and were assessed by the social anxiety scale and the Internet addiction scale prepared by Young (1997) which was modified by Widyanto and McMurran (2004) after confirming the appropriateness of its psychometric properties. The study results found that social anxiety level and Internet addiction level were high among the study sample and indicated a statically significant correlation at level (0.01) between the social anxiety level and the level of Internet addiction, which indicates that the higher the social anxiety level, the higher the internet addiction level and that social anxiety works as a predictor of the internet addiction. Results also indicated a nonexistence of statistically significant differences in the social anxiety level as well as the level of Internet addiction due to gender. The current study recommended the activation of students' counseling services for students within the university and society as a whole to train them on controlling and self-control, which reduce the social anxiety and increase the university's interest about Internet addiction phenomenon in addition to holding awareness programs to help solve problems of this phenomenon.

In [Van Beeumen, et. al, HPC Asia 2020,https://www.doi.org/10.1145/3368474.3368497] a scalable and matrix-freeeigensolver was proposed for studying the many-body localization (MBL)transition of two-level quantum spin chain models with nearest-neighbor $XX+YY$interactions plus $Z$ terms. This type of problem is computationallychallenging because the vector space dimension grows exponentially with thephysical system size, and averaging over different configurations of the randomdisorder is needed to obtain relevant statistical behavior. For each eigenvalueproblem, eigenvalues from different regions of the spectrum and theircorresponding eigenvectors need to be computed. Traditionally, the interioreigenstates for a single eigenvalue problem are computed via theshift-and-invert Lanczos algorithm. Due to the extremely high memory footprintof the LU factorizations, this technique is not well suited for large number ofspins $L$, e.g., one needs thousands of compute nodes on modern highperformance computing infrastructures to go beyond $L = 24$. The matrix-freeapproach does not suffer from this memory bottleneck, however, its scalabilityis limited by a computation and communication imbalance. We present a fewstrategies to reduce this imbalance and to significantly enhance thescalability of the matrix-free eigensolver. To optimize the communicationperformance, we leverage the consistent space runtime, CSPACER, and show itsefficiency in accelerating the MBL irregular communication patterns at scalecompared to optimized MPI non-blocking two-sided and one-sided RMAimplementation variants. The efficiency and effectiveness of the proposedalgorithm is demonstrated by computing eigenstates on a massively parallelmany-core high performance computer.

Network communication on GPU-based systems is a significant roadblock for many applications with small but frequent messaging requirements. One common question for application developers is, "How can they reduce the overheads and achieve the best communication performance on GPUs?"This work examines device initiated versus host initiated inter-node GPU communication using NVSHMEM. We derive basic communication model parameters for single message and batched communication before validating our model against distributed GEMM benchmarks. We use our model to estimate performance benefits for applications transitioning from CPUs to GPUS for fixed-size and scaled workloads and provide general guidelines for reducing communication overheads. Our findings show that the host-initiated approach generally outperforms the device-initiated approach for the system evaluated.

Students are essential parts of society, and their mental health and emotional safety as well as a sense of purpose, achievement, and success are the major objectives of successful education. They need to be armed with self-aid constructs to overcome academic setbacks and challenges. Despite the attributions of academic emotion regulation (AER), the core of self-assessment (CSA) to academic buoyancy (AB), no study has ever uncovered their relationships. To this end, the current research intended to test a structural model of English as a foreign language (EFL) university learners' AER, CSA, and AB. The academic emotion regulation questionnaire (AERQ), the core of self-assessment questionnaire (CSAQ), and the academic buoyancy scale (ABS) were administered to 395 Iranian EFL university learners. Based on the results of structural equation modeling (SEM), AER and CSA predict learners' AB. Additionally, the contribution of CSA to AB was confirmed. The implications of the findings are to raise learners' awareness of their personality traits and self-assessment that can foster practical learning and assessment. This study opens new doors for future academic research. The implications of the study may help learners, teachers, administrators, policymakers, and curriculum designers.

Due to subjectivity in oral assessment, much concentration has been put on obtaining a satisfactory measure of consistency among raters. However, the process for obtaining more consistency might not result in valid decisions. One matter that is at the core of both reliability and validity in oral assessment is rater training. Recently, multifaceted Rasch measurement (MFRM) has been adopted to address the problem of rater bias and inconsistency in scoring; however, no research has incorporated the facets of test takers' ability, raters' severity, task difficulty, group expertise, scale criterion category, and test version together in a piece of research along with their two-sided impacts. Moreover, little research has investigated how long rater training effects last. Consequently, this study explored the influence of the training program and feedback by having 20 raters score the oral production produced by 300 test-takers in three phases. The results indicated that training can lead to more degrees of interrater reliability and diminished measures of severity/leniency, and biasedness. However, it will not lead the raters into total unanimity, except for making them more self-consistent. Even though rater training might result in higher internal consistency among raters, it cannot simply eradicate individual differences related to their characteristics. That is, experienced raters, due to their idiosyncratic characteristics, did not benefit as much as inexperienced ones. This study also showed that the outcome of training might not endure in long term after training; thus, it requires ongoing training throughout the rating period letting raters regain consistency.