Coarse-Grained Picture for Controlling Complex Quantum Systems

We propose a coarse-grained picture to control ``complex'' quantum dynamics, i.e., multi-level-multi-level transition with a random interaction. Assuming that optimally controlled dynamics can be described as a Rabi-like oscillation between an initial and final state, we derive an analytic optimal field as a solution to optimal control theory. For random matrix systems, we numerically confirm that the analytic optimal field steers an initial state to a target state which both contains many eigenstates.Comment: jpsj2.cls, 2 pages, 3 figure files; appear in J. Phys. Soc. Jpn. Vol.73, No.11 (Nov. 15, 2004

Magnetic shielding properties of GdBCO bulks with different crystal orientation

AbstractHigh-temperature bulk superconductors have significant potential for superconductivity applications. For this paper, the magnetic shielding properties of GdBCO bulk with different crystal orientations were investigated at different temperatures for the purpose of determining its application as field concentrators. Four discs with a diameter of 20mm and thickness of 5mm were cut from the GdBCO single domain. In two discs, the c-axis of crystal was parallel to the disc radius, and, in the others, the c-axis was perpendicular to it. The magnetic shielding effects in a couple of bulks with a gap of 2mm were measured in background fields up to 11 T. The magnetic fields were measured at the center and edge points between the two bulks at LN2, LHe, and temperatures controlled with a cryocooler. In LHe, the discs whose c-axes were parallel to the external magnetic fields maintained a zero field up to 11 T. Even in LN2, the field was shielded to 1 T. The results confirmed the strong magnetic shield effects of GdBCO bulk and can be used for the design of a field concentrator

Effects of nonlinear sweep in the Landau-Zener-Stueckelberg effect

We study the Landau-Zener-Stueckelberg (LZS) effect for a two-level system with a time-dependent nonlinear bias field (the sweep function) W(t). Our main concern is to investigate the influence of the nonlinearity of W(t) on the probability P to remain in the initial state. The dimensionless quantity epsilon = pi Delta ^2/(2 hbar v) depends on the coupling Delta of both levels and on the sweep rate v. For fast sweep rates, i.e., epsilon << l and monotonic, analytic sweep functions linearizable in the vicinity of the resonance we find the transition probability 1-P ~= epsilon (1+a), where a>0 is the correction to the LSZ result due to the nonlinearity of the sweep. Further increase of the sweep rate with nonlinearity fixed brings the system into the nonlinear-sweep regime characterized by 1-P ~= epsilon ^gamma with gamma neq 1 depending on the type of sweep function. In case of slow sweep rates, i.e., epsilon >>1 an interesting interference phenomenon occurs. For analytic W(t) the probability P=P_0 e^-eta is determined by the singularities of sqrt{Delta ^2+W^2(t)} in the upper complex plane of t. If W(t) is close to linear, there is only one singularity, that leads to the LZS result P=e^-epsilon with important corrections to the exponent due to nonlinearity. However, for, e.g., W(t) ~ t^3 there is a pair of singularities in the upper complex plane. Interference of their contributions leads to oscillations of the prefactor P_0 that depends on the sweep rate through epsilon and turns to zero at some epsilon. Measurements of the oscillation period and of the exponential factor would allow to determine Delta, independently.Comment: 11 PR pages, 12 figures. To be published in PR

Photoacoustic Signal Enhancement by Localized Surface Plasmon of Gold Nanoparticles

Photoacoustic imaging has been widely studied as a deep biological tissue imaging modality combining optical absorption and ultrasonic detection. It enables multi-scale high resolution imaging of optical absorbing intrinsic molecules as well as exogenous molecules. Gold nanoparticles have the primary advantages of large absorption cross section and bioconjugation capability for the imaging contrast agents. In order to design the photoacoustic imaging agents for enhancing the contrast with high specificity to targeted molecules and / or cell, we measured and analyzed time-of-flight photoacoustic signals of aqueous solutions of various shapes and sizes of gold nanoparticles. The signal intensities were sensitive to the shapes and sizes of the gold nanoparticles. We found a strong photoacoustic signal of the polyhedral gold nanoparticle due to the localized surface plasmon resonance. The experimental results derive the strategy of designing the optimum photoacoustic contrast agents. When you are citing the document, use the following link http://essuir.sumdu.edu.ua/handle/123456789/3543

Analyzing the Performance Portability of Tensor Decomposition

We employ pressure point analysis and roofline modeling to identify performance bottlenecks and determine an upper bound on the performance of the Canonical Polyadic Alternating Poisson Regression Multiplicative Update (CP-APR MU) algorithm in the SparTen software library. Our analyses reveal that a particular matrix computation, $\Phi^{(n)}$, is the critical performance bottleneck in the SparTen CP-APR MU implementation. Moreover, we find that atomic operations are not a critical bottleneck while higher cache reuse can provide a non-trivial performance improvement. We also utilize grid search on the Kokkos library parallel policy parameters to achieve 2.25x average speedup over the SparTen default for $\Phi^{(n)}$ computation on CPU and 1.70x on GPU. We conclude our investigations by comparing Kokkos implementations of the STREAM benchmark and the matricized tensor times Khatri-Rao product (MTTKRP) benchmark from the Parallel Sparse Tensor Algorithm (PASTA) benchmark suite to implementations using vendor libraries. We show that with a single implementation Kokkos achieves performance comparable to hand-tuned code for fundamental operations that make up tensor decomposition kernels on a wide range of CPU and GPU systems. Overall, we conclude that Kokkos demonstrates good performance portability for simple data-intensive operations but requires tuning for algorithms with more complex dependencies and data access patterns.Comment: 28 pages, 19 figure

Evaluation of OpenAI Codex for HPC Parallel Programming Models Kernel Generation

We evaluate AI-assisted generative capabilities on fundamental numerical kernels in high-performance computing (HPC), including AXPY, GEMV, GEMM, SpMV, Jacobi Stencil, and CG. We test the generated kernel codes for a variety of language-supported programming models, including (1) C++ (e.g., OpenMP [including offload], OpenACC, Kokkos, SyCL, CUDA, and HIP), (2) Fortran (e.g., OpenMP [including offload] and OpenACC), (3) Python (e.g., numba, Numba, cuPy, and pyCUDA), and (4) Julia (e.g., Threads, CUDA.jl, AMDGPU.jl, and KernelAbstractions.jl). We use the GitHub Copilot capabilities powered by OpenAI Codex available in Visual Studio Code as of April 2023 to generate a vast amount of implementations given simple + + prompt variants. To quantify and compare the results, we propose a proficiency metric around the initial 10 suggestions given for each prompt. Results suggest that the OpenAI Codex outputs for C++ correlate with the adoption and maturity of programming models. For example, OpenMP and CUDA score really high, whereas HIP is still lacking. We found that prompts from either a targeted language such as Fortran or the more general-purpose Python can benefit from adding code keywords, while Julia prompts perform acceptably well for its mature programming models (e.g., Threads and CUDA.jl). We expect for these benchmarks to provide a point of reference for each programming model's community. Overall, understanding the convergence of large language models, AI, and HPC is crucial due to its rapidly evolving nature and how it is redefining human-computer interactions.Comment: Accepted at the Sixteenth International Workshop on Parallel Programming Models and Systems Software for High-End Computing (P2S2), 2023 to be held in conjunction with ICPP 2023: The 52nd International Conference on Parallel Processing. 10 pages, 6 figures, 5 table