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Mappings of open quantum systems onto chain representations and Markovian embeddings

We study systems coupled linearly to a bath of oscillators. In an iterative process, the bath is transformed into a chain of oscillators with nearest neighbour interactions. A systematic procedure is provided to obtain the spectral density of the residual bath in each step, and it is shown that under general conditions these data converge. That is, the asymptotic part of the chain is universal, translation invariant with semicircular spectral density. The methods are based on orthogonal polynomials, in which we also solve the outstanding so-called “sequence of secondary measures problem” and give them a physical interpretation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Eigenvalue Solvers for Modeling Nuclear Reactors on Leadership Class Machines

In this paper, three complementary methods have been implemented in the code Denovo that accelerate neutral particle transport calculations with methods that use leadership-class computers fully and effectively: a multigroup block (MG) Krylov solver, a Rayleigh quotient iteration (RQI) eigenvalue solver, and a multigrid in energy (MGE) preconditioner. The MG Krylov solver converges more quickly than Gauss Seidel and enables energy decomposition such that Denovo can scale to hundreds of thousands of cores. RQI should converge in fewer iterations than power iteration (PI) for large and challenging problems. RQI creates shifted systems that would not be tractable without the MG Krylov solver. It also creates ill-conditioned matrices. The MGE preconditioner reduces iteration count significantly when used with RQI and takes advantage of the new energy decomposition such that it can scale efficiently. Each individual method has been described before, but this is the first time they have been demonstrated to work together effectively. The combination of solvers enables the RQI eigenvalue solver to work better than the other available solvers for large reactors problems on leadership-class machines. Using these methods together, RQI converged in fewer iterations and in less time than PI for a full pressurized water reactor core. These solvers also performed better than an Arnoldi eigenvalue solver for a reactor benchmark problem when energy decomposition is needed. The MG Krylov, MGE preconditioner, and RQI solver combination also scales well in energy. Finally, this solver set is a strong choice for very large and challenging problems.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

A new approach to approximate equation-of-motion coupled cluster with triple excitations

Accurate methods for excited, ionized, and electron-attached states are critical to the study of many chemical species such as reactive intermediates, radicals, and ionized systems. The equation-of-motion coupled cluster singles, doubles, and triples (EOM-CCSDT) family of methods is very accurate (roughly similar in accuracy as for CCSDT calculations of the ground state), but the computational cost scales iteratively as the eighth power of the system size. Many approximations already exist, although most either correct only the excited state or require an iterative $\mathscr{O}$(n 7 ) procedure which can also be prohibitively expensive. In this paper, new methods, termed EOM-CCSD(T)(a) and EOM-CCSD(T)(a)*, are proposed which correct both the ground and excited states based on a shared effective Hamiltonian, and the latter of which includes only non-iterative corrections to both the CCSD and EOM-CCSD energies. These methods are found to significantly improve the description of excited and ionized potential energy surfaces, equilibrium geometries, and harmonic frequencies; the accuracy is very close to that of full EOM-CCSDT.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Iterative multi-task learning and inference from seismic images

Seismic interpretation aims to extract quantitative and interpretable attributes from a seismic image produced using some migration method to inform characteristics of a subsurface reservoir or target of interest. Current paradigms for computing seismic attributes mostly rely on single-task algorithms. We develop an iterative, multi-task machine learning method to learn and infer multiple attributes from a seismic image. This method is composed of two stages: a multi-task inference stage and a multi-modal, multi-task refinement stage. The basic mechanism of this method is that we train a multi-task inference neural network (NN) to estimate a set of attributes, including a relative geological time (RGT), a denoised higher-resolution (DHR) seismic image, and multiple fault attributes (including probability, dip, and strike), from a low-resolution, noisy seismic image; then we input the inferred attributes to a multi-task refinement NN to enhance the raw inference results iteratively. The two multi-task NNs are trained separately based on synthetic seismic images and associated attributes generated by a geological modeling algorithm. The software we intend to release is a PyTorch implementation of this multi-task learning method for both 2D and 3D cases along with scripts to run the training/validation. The algorithm and software can be a useful tool for automatic seismic interpretation.

Gao, Kai↗

Radiation Mapping at JET and ITER using advanced computational acceleration techniques and tools - Paper 63

The Applied Radiation Physics group at the Culham Centre for Fusion Energy (CCFE) have developed and applied state-of-the-art radiation mapping methods and tools to enable complex shielding calculations in fusion devices during plasma operations, and associated maintenance in the device and surrounding areas. Here, we present the description and application of those tools to produce radiation maps both to support the JET safety case (the EU experimental tokamak device based at Culham) and the planned DT campaign in the next few years; and the ITER device. Radiation mapping of fusion facilities are essential for assessing radiation hardness of electronics during operations, and to define safe working dose limits to staff during routine maintenance. At CCFE the Monte Carlo radiation transport code MCNP6 is one of the codes used to perform radiation transport calculations. Due to the size and complexity of the JET and ITER devices, and their surrounding buildings, a suite of tools have been created at CCFE to reduce the computational requirements of the calculations. This paper describes three of these tools, which have been developed and applied to nuclear and radiological field mapping in fusion devices. The results presented in this paper highlight the application of three methods that have been used to improve the computational efficiency and capabilities for radiation mapping in fusion devices such as JET and ITER. These methods are Global Variance Reduction, the Surface Source Mesh routine and the Smeared Source routine. This paper demonstrates the three techniques used in combination, enabling a very computationally challenging fusion problem to become tractable (with acceptable computing effort), also enabling improved capability to allow the mapping of radiations fields during transport operations for activated materials. (authors)

61 RADIATION PROTECTION AND DOSIMETRY↗

Metrics for Intercomparison of Remapping Algorithms (MIRA) protocol applied to Earth system models

Abstract. Strongly coupled nonlinear phenomena such as those described by Earth system models (ESMs) are composed of multiple component models with independent mesh topologies and scalable numerical solvers. A common operation in ESMs is to remap or interpolate component solution fields defined on their computational mesh to another mesh with a different combinatorial structure and decomposition, e.g., from the atmosphere to the ocean, during the temporal integration of the coupled system. Several remapping schemes are currently in use or available for ESMs. However, a unified approach to compare the properties of these different schemes has not been attempted previously. We present a rigorous methodology for the evaluation and intercomparison of remapping methods through an independently implemented suite of metrics that measure the ability of a method to adhere to constraints such as grid independence, monotonicity, global conservation, and local extrema or feature preservation. A comprehensive set of numerical evaluations is conducted based on a progression of scalar fields from idealized and smooth to more general climate data with strong discontinuities and strict bounds. We examine four remapping algorithms with distinct design approaches, namely ESMF Regrid (Hill et al., 2004), TempestRemap (Ullrich and Taylor, 2015), generalized moving least squares (GMLS) (Trask and Kuberry, 2020) with post-processing filters, and WLS-ENOR (Li et al., 2020). By repeated iterative application of the high-order remapping methods to the test fields, we verify the accuracy of each scheme in terms of their observed convergence order for smooth data and determine the bounded error propagation using challenging, realistic field data on both uniform and regionally refined mesh cases. In addition to retaining high-order accuracy under idealized conditions, the methods also demonstrate robust remapping performance when dealing with non-smooth data. There is a failure to maintain monotonicity in the traditional L2-minimization approaches used in ESMF and TempestRemap, in contrast to stable recovery through nonlinear filters used in both meshless GMLS and hybrid mesh-based WLS-ENOR schemes. Local feature preservation analysis indicates that high-order methods perform better than low-order dissipative schemes for all test cases. The behavior of these remappers remains consistent when applied on regionally refined meshes, indicating mesh-invariant implementations. The MIRA intercomparison protocol proposed in this paper and the detailed comparison of the four algorithms demonstrate that the new schemes, namely GMLS and WLS-ENOR, are competitive compared to standard conservative minimization methods requiring computation of mesh intersections. The work presented in this paper provides a foundation that can be extended to include complex field definitions, realistic mesh topologies, and spectral element discretizations, thereby allowing for a more complete analysis of production-ready remapping packages.

58 GEOSCIENCES↗

Electron kinetic effects on optical diagnostics in fusion plasmas

At anticipated high electron temperatures in ITER, the effects of electron thermal motion on Thomson scattering (TS), toroidal interferometer/polarimeter (TIP) and poloidal polarimeter (PoPola) diagnostics will be significant and must be accurately treated. We calculate electron thermal corrections to the interferometric phase and polarization state of an EM wave propagating along tangential and poloidal chords (Faraday and Cotton-Mouton polarimetry) and perform analysis of the degree of polarization for incoherent TS. The precision of the previous lowest order linear in τ = T{sub e}/m{sub e}c{sup 2} model may be insufficient; we present a more precise model with τ{sup 2}-order corrections to satisfy the high accuracy required for ITER TIP and PoPola diagnostics. The linear model is extended from Maxwellian to a more general class of anisotropic electron distributions that allows us to take into account distortions caused by equilibrium current, ECRH and RF current drive effects. The classical problem of degree of polarization of incoherent Thomson scattered radiation is solved analytically exactly without any approximations for the full range of incident polarizations, scattering angles, and electron thermal motion from non-relativistic to ultra-relativistic. The results are discussed in the context of the possible use of the polarization properties of Thomson scattered light as a method of T{sup e} measurement relevant to ITER operational scenarios.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Electron kinetic effects on interferometry, polarimetry and Thomson scattering measurements in burning plasmas (invited)

At anticipated high electron temperatures in ITER, the effects of electron thermal motion on Thomson scattering (TS), toroidal interferometer/polarimeter (TIP), and poloidal polarimeter (PoPola) diagnostics will be significant and must be accurately treated. The precision of the previous lowest order linear in τ = T{sub e}/m{sub e}c{sup 2} model may be insufficient; we present a more precise model with τ{sup 2}-order corrections to satisfy the high accuracy required for ITER TIP and PoPola diagnostics. The linear model is extended from Maxwellian to a more general class of anisotropic electron distributions that allows us to take into account distortions caused by equilibrium current, ECRH, and RF current drive effects. The classical problem of the degree of polarization of incoherent Thomson scattered radiation is solved analytically exactly without any approximations for the full range of incident polarizations, scattering angles, and electron thermal motion from non-relativistic to ultra-relativistic. The results are discussed in the context of the possible use of the polarization properties of Thomson scattered light as a method of T{sub e} measurement relevant to ITER operational scenarios.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Efficient Scalable Parallel Higher Order Direct MoM-SIE Method With Hierarchically Semiseparable Structures for 3-D Scattering

A novel fast scalable parallel algorithm is proposed for the solution of large 3-D scattering problems based on: 1) the double (geometrical and current-approximation) higher order (DHO) method of moments (MoM) in the surface integral equation (SIE) formulation and 2) a direct solver for dense linear systems utilizing hierarchically semiseparable (HSS) structures. Namely, an HSS matrix representation is used for compression, factorization, and solution of the system matrix. In addition, a rank-revealing QR decomposition for memory compression is used, with a stopping criterion in terms of the relative rank tolerance value. One method for geometrical preprocessing of the scatterers based on the cobblestone distance sorting technique is employed in order to enhance the HSS algorithm accuracy and parallelization. Numerical examples show how the accuracy of the DHO HSS-MoM-SIE method is easily controllable by using the relative tolerance for the matrix compression. Furthermore, the examples demonstrate low memory consumption, as well as much faster simulation time, when compared to the direct LU decomposition. The method enables dramatically faster monostatic scattering computations than iterative solvers and reduced number of unknowns when compared to low-order discretizations. Finally, great scalability of the algorithm is demonstrated on more than one thousand processes.

97 MATHEMATICS AND COMPUTING↗

Shattered pellet penetration in low and high energy plasmas on DIII-D

Shattered Pellet Injection (SPI) was previously adopted as the baseline disruption mitigation system for ITER, as the radiative payload penetration into DIII-D plasmas from SPI is superior to those using the Massive Gas Injection (MGI) method. Because of the substantial differences in the energy content of ITER plasma and those in present experiments, reliable 3d MHD modeling, benchmarked against present experiments is needed to project to ITER plasmas. On account of these needs, the depth of SPI fragment penetration in DIII-D plasmas was investigated by injecting SPI into two discharges with vastly different energy content and pedestal height. 400 Torr-L pure Ne fragmented pellets at a velocity of about 200 m s -1 were injected into a 0.2 MJ L-mode discharge and a 2 MJ super H-mode discharge. Results show deep penetration of SPI fragments into low-energy plasmas in DIII-D. SPI fragment penetration is reduced as the plasma energy content increases, with some discharges exhibiting penetration that is confined to the outer regions of the plasma. The injected SPI fragments are also spread out over a distance of about 20 cm, which results in some fragments arriving near the end of or after the thermal quench is over.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

L-BFGS Class Implementation in C++

This report presents a header-only C++ class implementation of the Limited-memory BroydenFletcher-Goldfarb-Shanno (L-BFGS) algorithm. The L-BFGS method is a general purpose quasi-Netwon optimization method that builds an approximation of the descent direction from consecutive iterate and gradient vectors. The limited-memory aspect stems from the replacement of the N × N approximation matrix of the original BFGS method with M vectors of length N. An example usage of the class is included along with the reference source code.

97 MATHEMATICS AND COMPUTING↗

Shattered pellet penetration in low and high energy plasmas on DIII-D

Shattered pellet injection (SPI) has been adopted as the baseline disruption mitigation system for ITER, as the radiative payload penetration into DIII-D plasmas from SPI is superior to those using the massive gas injection (MGI) method. Because of the substantial differences in the energy content of ITER plasma and those in present experiments, reliable 3D MHD modeling, benchmarked against present experiments is needed to project to ITER plasmas. In support of these needs, the depth of SPI fragment penetration in DIII-D plasmas was investigated by injecting SPI into two discharges with vastly different energy content and pedestal height. 400 Torr-L pure Ne fragmented pellets at a velocity of about 200 m s−1 were injected into a 0.2 MJ L-mode discharge and a 2 MJ super H-mode discharge. Results show deep penetration of SPI fragments into low-energy plasmas in DIII-D. SPI fragment penetration is reduced as the plasma energy content increases, with some discharges exhibiting penetration that is confined to the outer regions of the plasma. The injected SPI fragments are also spread out over a distance of about 20 cm, which results in some fragments arriving near the end of or after the thermal quench is over.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Sparse-view proton computed tomography using modulated proton beams

Purpose: Proton imaging that uses a modulated proton beam and an intensity detector allows a relatively fast image acquisition compared to the imaging approach based on a trajectory tracking detector. In addition, it requires a relatively simple implementation in a conventional proton therapy equipment. The model of geometric straight ray assumed in conventional computed tomography (CT) image reconstruction is however challenged by multiple-Coulomb scattering and energy straggling in the proton imaging. Radiation dose to the patient is another important issue that has to be taken care of for practical applications. In this work, the authors have investigated iterative image reconstructions after a deconvolution of the sparsely view-sampled data to address these issues in proton CT. Methods: Proton projection images were acquired using the modulated proton beams and the EBT2 film as an intensity detector. Four electron-density cylinders representing normal soft tissues and bone were used as imaged object and scanned at 40 views that are equally separated over 360°. Digitized film images were converted to water-equivalent thickness by use of an empirically derived conversion curve. For improving the image quality, a deconvolution-based image deblurring with an empirically acquired point spread function was employed. They have implemented iterative image reconstruction algorithms such as adaptive steepest descent-projection onto convex sets (ASD-POCS), superiorization method–projection onto convex sets (SM-POCS), superiorization method–expectation maximization (SM-EM), and expectation maximization-total variation minimization (EM-TV). Performance of the four image reconstruction algorithms was analyzed and compared quantitatively via contrast-to-noise ratio (CNR) and root-mean-square-error (RMSE). Results: Objects of higher electron density have been reconstructed more accurately than those of lower density objects. The bone, for example, has been reconstructed within 1% error. EM-based algorithms produced an increased image noise and RMSE as the iteration reaches about 20, while the POCS-based algorithms showed a monotonic convergence with iterations. The ASD-POCS algorithm outperformed the others in terms of CNR, RMSE, and the accuracy of the reconstructed relative stopping power in the region of lung and soft tissues. Conclusions: The four iterative algorithms, i.e., ASD-POCS, SM-POCS, SM-EM, and EM-TV, have been developed and applied for proton CT image reconstruction. Although it still seems that the images need to be improved for practical applications to the treatment planning, proton CT imaging by use of the modulated beams in sparse-view sampling has demonstrated its feasibility.

60 APPLIED LIFE SCIENCES↗

Heat loads to divertor nearby components from secondary radiation evolved during plasma instabilities

A fundamental issue in tokamak operation related to power exhaust during plasma instabilities is the understanding of heat and particle transport from the core plasma into the scrape-off layer and to plasma-facing materials. During abnormal and disruptive operation in tokamaks, radiation transport processes play a critical role in divertor/edge-generated plasma dynamics and are very important in determining overall lifetimes of the divertor and nearby components. This is equivalent to or greater than the effect of the direct impact of escaped core plasma on the divertor plate. We have developed and implemented comprehensive enhanced physical and numerical models in the upgraded HEIGHTS package for simulating detailed photon and particle transport in the evolved edge plasma during various instabilities. The paper describes details of a newly developed 3D Monte Carlo radiation transport model, including optimization methods of generated plasma opacities in the full range of expected photon spectra. Response of the ITER divertor's nearby surfaces due to radiation from the divertor-developed plasma was simulated by using actual full 3D reactor design and magnetic configurations. We analyzed in detail the radiation emission spectra and compared the emission of both carbon and tungsten as divertor plate materials. The integrated 3D simulation predicted unexpectedly high damage risk to the open stainless steel legs of the dome structure in the current ITER design from the intense radiation during a disruption on the tungsten divertor plate.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Hydrodynamics of suspensions of passive and active rigid particles: a rigid multiblob approach

We develop a rigid multiblob method for numerically solving the mobility problem for suspensions of passive and active rigid particles of complex shape in Stokes flow in unconfined, partially confined, and fully confined geometries. As in a number of existing methods, we discretize rigid bodies using a collection of minimally resolved spherical blobs constrained to move as a rigid body, to arrive at a potentially large linear system of equations for the unknown Lagrange multipliers and rigid-body motions. Here we develop a block-diagonal preconditioner for this linear system and show that a standard Krylov solver converges in a modest number of iterations that is essentially independent of the number of particles. Key to the efficiency of the method is a technique for fast computation of the product of the blob-blob mobility matrix and a vector. For unbounded suspensions, we rely on existing analytical expressions for the Rotne-Prager-Yamakawa tensor combined with a fast multipole method (FMM) to obtain linear scaling in the number of particles. For suspensions sedimented against a single no-slip boundary, we use a direct summation on a graphical processing unit (GPU), which gives quadratic asymptotic scaling with the number of particles. For fully confined domains, such as periodic suspensions or suspensions confined in slit and square channels, we extend a recently developed rigid-body immersed boundary method by B. Kallemov, A. P. S. Bhalla, B. E. Griffith, and A. Donev (Commun. Appl. Math. Comput. Sci. 11 (2016), no. 1, 79-141) to suspensions of freely moving passive or active rigid particles at zero Reynolds number. We demonstrate that the iterative solver for the coupled fluid and rigid-body equations converges in a bounded number of iterations regardless of the system size. In our approach, each iteration only requires a few cycles of a geometric multigrid solver for the Poisson equation, and an application of the block-diagonal preconditioner, leading to linear scaling with the number of particles. We optimize a number of parameters in the iterative solvers and apply our method to a variety of benchmark problems to carefully assess the accuracy of the rigid multiblob approach as a function of the resolution. We also model the dynamics of colloidal particles studied in recent experiments, such as passive boomerangs in a slit channel, as well as a pair of non-Brownian active nanorods sedimented against a wall.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Detector alignment for X-ray crystallography using Millepede-II

I describe a method for accurately refining the geometrical parameters of segmented X-ray area detectors on the basis of serial crystallography data, using 'Millepede' – an algorithm created for a very similar problem in high-energy physics. The Millepede method for serial crystallography builds on the approach of Brewster et al. [Acta Cryst. (2018), D74, 877–894], in which the detector parameters are refined simultaneously with the parameters for each individual crystal. This accounts for the mutual dependency between the parameters and thereby avoids the bias and slow convergence problems that have afflicted older approaches in which the deviations between observed and calculated Bragg peak positions were taken directly as the updates for the detector panel positions. The Millepede method uses the special structure of the least-squares normal equations to reduce them to a much smaller form that can be solved very quickly, even compared with the sparse matrix methods used previously. This makes it practical to refine the detector geometry frequently and thereby maintain accurate calibration without specialized alignment campaigns. Tilts of detector panels out of the plane can be reliably refined, as can the overall distance of the detector in the beam direction. With a simulated test case, the new method produced panel shifts within 7% of the correct values with only one iteration, and produced almost exactly correct shifts after a second iteration. A simulated out-of-plane panel rotation was correctly determined to within 0.001°. Applied to experimental data from an X-ray free-electron laser, the method increased the indexable fraction of frames from 30% to 91% in a single iteration, and to 96% after two further iterations. Computing the geometry updates on the basis of 2060 crystals took only 0.819 s on desktop computing hardware, including the time taken to read the required data from disk. The scaling was found to be very close to linear for up to 100 980 sets of crystal parameters, which took only 78.2 s to process under the same conditions. The method has been applied as part of a real-time feedback system at a synchrotron radiation beamline, in which an out-of-plane detector tilt of 0.04° was detected and corrected. Possible further applications are also described here.

Millepede-II↗

CodEx: A Modular Framework for Joint Temporal De-Blurring and Tomographic Reconstruction

In many computed tomography (CT) imaging applications, it is important to rapidly collect data from an object that is moving or changing with time. Tomographic acquisition is generally assumed to be step-and-shoot, where the object is rotated to each desired angle, and a view is taken. However, step-and-shoot acquisition is slow and can waste photons, so in practice fly-scanning is done where the object is continuously rotated while collecting data. However, this can result in motion-blurred views and consequently reconstructions with severe motion artifacts. In this paper, we introduce CodEx, a modular framework for joint de-blurring and tomographic reconstruction that can effectively invert the motion blur introduced in sparse view fly-scanning. The method is a synergistic combination of a novel acquisition method with a novel non-convex Bayesian reconstruction algorithm. CodEx works by encoding the acquisition with a known binary code that the reconstruction algorithm then inverts. Using a well chosen binary code to encode the measurements can improve the accuracy of the inversion process. The CodEx reconstruction method uses the alternating direction method of multipliers (ADMM) to split the inverse problem into iterative deblurring and reconstruction sub-problems, making reconstruction practical to implement. Here we present reconstruction results on both simulated and binned experimental data to demonstrate the effectiveness of our method.

42 ENGINEERING↗

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