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Rank-revealing matrix decompositions provide an essential tool in spectral analysis of matrices, including the Singular Value Decomposition (SVD) and related low-rank approximation techniques. QR with Column Pivoting (QRCP) is usually suitable for these purposes, but it can be much slower than the unpivoted QR algorithm. For large matrices, the difference in performance is due to increased communication between the processor and slow memory, which QRCP needs in order to choose pivots during decomposition. Our main algorithm, Randomized QR with Column Pivoting (RQRCP), uses randomized projection to make pivot decisions from a much smaller sample matrix, which we can construct to reside in a faster level of memory than the original matrix. This technique may be understood as trading vastly reduced communication for a controlled increase in uncertainty during the decision process. For rank-revealing purposes, the selection mechanism in RQRCP produces results that are the same quality as the standard algorithm, but with performance near that of unpivoted QR (often an order of magnitude faster for large matrices). We also propose two formulas that facilitate further performance improvements. The first efficiently updates sample matrices to avoid computing new randomized projections. The second avoids large trailing updates during the decomposition in truncated low-rank approximations. Our truncated version of RQRCP also provides a key initial step in our truncated SVD approximation, TUXV. These advances open up a new performance domain for large matrix factorizations that will support efficient problem-solving techniques for challenging applications in science, engineering, and data analysis., Comment: Revised from Randomized QR with Column Pivoting for publication in SIGEST

The Hitomi results for the Perseus cluster have shown that accurate atomic models are essential to the success of X-ray spectroscopic missions, and just as important as knowledge on instrumental calibration and astrophysical modeling. Preparing the models requires a multifaceted approach, including theoretical calculations, laboratory measurements, and calibration using real observations. In a previous paper, we presented a calculation of the electron impact cross sections on the transitions forming the Fe-L complex. In the present work, we systematically test the calculation against cross sections of ions measured in an electron beam ion trap experiment. A two-dimensional analysis in the electron beam energies and X-ray photon energies is utilized to disentangle radiative channels following dielectronic recombination, direct electron-impact excitation, and resonant excitation processes in the experimental data. The data calibrated through laboratory measurements are further fed into global modeling of the Chandra grating spectrum of Capella. We investigate and compare the fit quality, as well as sensitivity of the derived physical parameters to the underlying atomic data and the astrophysical plasma modeling. We further list the potential areas of disagreement between the observation and the present calculations, which in turn calls for renewed efforts in theoretical calculations and targeted laboratory measurements., Comment: Accepted for publication in A&A

ART$^2$ is a 3D multi-wavelength Monte Carlo radiative transfer (RT) code that couples continuum and emission lines to track the propagation of photons and their interactions with the interstellar medium (ISM). The previous version of ART$^2$, which included continuum and Ly$\alpha$ line, has been extensively applied to hydrodynamics simulations to study multi-band properties of galaxies and ISM. Here, we describe new implementations of non-local thermodynamic equilibrium RT of molecular and atomic fine structure emission lines, and the parallelization of the code using a number of novel methods. The new ART$^2$ can efficiently and self-consistently produce a full spectrum that includes both continuum and lines such as [CII], [NII], [OIII], Ly$\alpha$, and CO. These essential features, together with the multi-phase ISM model and the adaptive grid, make ART$^2$ a multi-purpose code to study multi-wavelength properties of a wide range of astrophysical systems from planetary disks to large-scale structures. To demonstrate the capability of the new ART$^2$, we applied it to two hydrodynamics simulations: the zoom-in Milky Way Simulation to obtain panchromatic properties of individual galaxies, and the large-scale IllustrisTNG100 Simulation to obtain global properties such as the line intensity mappings. These products are essential for a broad array of studies such as the correlations between physical and panchromatic properties and their evolution. By enabling direct comparison between numerical simulations and multi-band observations, ART$^2$ provides a crucial theoretical framework for the interpretations of existing observations, the plan for future surveys, and the synergy between multi-band galaxy surveys and line intensity mappings. Therefore, ART$^2$ is a powerful and versatile tool to bridge the gap between theories and observations of cosmic structures., Comment: Accepted for publication in MNRAS; 20 pages, 26 figures

Model View Definition (MVD) is the standard methodology to define the data exchange requirements and rule constraints for Building Information Models (BIMs). In this paper, the MVDLite algorithm is proposed for the fast validation of MVD rules. A "rule chain" structure is introduced to combine the data templates, constraint statements, and logical interconnections in an input mvdXML ruleset, which leads to fast filtering of data nodes through the rule chain. By establishing the correspondence of each prefix of the rule chain with a string, the deep-caching strategy further improves efficiency. The outperforming experimental results show that our algorithm significantly reduces the running time of MVD validation on large real-world BIMs., Comment: Preprint submitted to 29th International Workshop on Intelligent Computing in Engineering (EG-ICE)

Low-rank metric learning aims to learn better discrimination of data subject to low-rank constraints. It keeps the intrinsic low-rank structure of datasets and reduces the time cost and memory usage in metric learning. However, it is still a challenge for current methods to handle datasets with both high dimensions and large numbers of samples. To address this issue, we present a novel fast low-rank metric learning (FLRML) method.FLRML casts the low-rank metric learning problem into an unconstrained optimization on the Stiefel manifold, which can be efficiently solved by searching along the descent curves of the manifold.FLRML significantly reduces the complexity and memory usage in optimization, which makes the method scalable to both high dimensions and large numbers of samples.Furthermore, we introduce a mini-batch version of FLRML to make the method scalable to larger datasets which are hard to be loaded and decomposed in limited memory. The outperforming experimental results show that our method is with high accuracy and much faster than the state-of-the-art methods under several benchmarks with large numbers of high-dimensional data. Code has been made available at https://github.com/highan911/FLRML, Comment: 33rd Conference on Neural Information Processing Systems (NeurIPS 2019)

We have used an electron beam ion trap to measure electron-density-diagnostic line-intensity ratios for extreme ultraviolet lines from F XII, XIII, and XIV at wavelengths of 185-205 255-276 Angstroms. These ratios can be used as density diagnostics for astrophysical spectra and are especially relevant to solar physics. We found that density diagnostics using the Fe XIII 196.53/202.04 and the Fe XIV 264.79/274.21 and 270.52A/274.21 line ratios are reliable using the atomic data calculated with the Flexible Atomic Code. On the other hand, we found a large discrepancy between the FAC theory and experiment for the commonly used Fe XII (186.85 + 186.88)/195.12 line ratio. These FAC theory calculations give similar results to the data tabulated in CHIANTI, which are commonly used to analyze solar observations. Our results suggest that the discrepancies seen between solar coronal density measurements using the Fe XII (186.85 + 186.88)/195.12 and Fe XIII 196.54/202.04 line ratios are likely due to issues with the atomic calculations for Fe XII.

Thanks to high-resolution and non-dispersive spectrometers onboard future X-ray missions such as XRISM and Athena, we are finally poised to answer important questions about the formation and evolution of galaxies and large-scale structure. However, we currently lack an adequate understanding of many atomic processes behind the spectral features we will soon observe. Large error bars on parameters as critical as transition energies and atomic cross sections can lead to unacceptable uncertainties in the calculations of e.g., elemental abundance, velocity, and temperature. Unless we address these issues, we risk limiting the full scientific potential of these missions. Laboratory astrophysics, which comprises theoretical and experimental studies of the underlying physics behind observable astrophysical processes, is therefore central to the success of these missions., Comment: Science white paper submitted to the Astro2020 Decadal Survey

We determined relative X-ray photon emission cross sections in Fe XVII ions that were mono-energetically excited in an electron beam ion trap. Line formation for the 3s (3s-2p) and 3d (3d-2p) transitions of interest proceeds through dielectronic recombination (DR), direct electron-impact excitation (DE), resonant excitation (RE), and radiative cascades. By reducing the electron-energy spread to a sixth of that of previous works and increasing counting statistics by three orders of magnitude, we account for hitherto unresolved contributions from DR and the little-studied RE process to the 3d transitions, and also for cascade population of the 3s line manifold through forbidden states. We found good agreement with state-of-the-art many-body perturbation theory (MBPT) and distorted-wave (DW) method for the 3s transition, while in the 3d transitions known discrepancies were confirmed. Our results show that DW calculations overestimate the 3d line emission due to DE by ~20%. Inclusion of electron-electron correlation effects through the MBPT method in the DE cross section calculations reduces this disagreement by ~11%. The remaining ~9% in 3d and ~11% in 3s/3d discrepancies are consistent with those found in previous laboratory measurements, solar, and astrophysical observations. Meanwhile, spectral models of opacity, temperature, and turbulence velocity should be adjusted to these experimental cross sections to optimize the accuracy of plasma diagnostics based on these bright soft X-ray lines of Fe XVII., Comment: 8 pages, 4 figures, Accepted in ApJ, in press