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At least 523 records · Page 29

Demonstration of Automatically-Generated Adjoint Code for Use in Aerodynamic Shape Optimization

Gradient-based optimization requires accurate derivatives of the objective function and constraints. These gradients may have previously been obtained by manual differentiation of analysis codes, symbolic manipulators, finite-difference approximations, or existing automatic differentiation (AD) tools such as ADIFOR (Automatic Differentiation in FORTRAN). Each of these methods has certain deficiencies, particularly when applied to complex, coupled analyses with many design variables. Recently, a new AD tool called ADJIFOR (Automatic Adjoint Generation in FORTRAN), based upon ADIFOR, was developed and demonstrated. Whereas ADIFOR implements forward-mode (direct) differentiation throughout an analysis program to obtain exact derivatives via the chain rule of calculus, ADJIFOR implements the reverse-mode counterpart of the chain rule to obtain exact adjoint form derivatives from FORTRAN code. Automatically-generated adjoint versions of the widely-used CFL3D computational fluid dynamics (CFD) code and an algebraic wing grid generation code were obtained with just a few hours processing time using the ADJIFOR tool. The codes were verified for accuracy and were shown to compute the exact gradient of the wing lift-to-drag ratio, with respect to any number of shape parameters, in about the time required for 7 to 20 function evaluations. The codes have now been executed on various computers with typical memory and disk space for problems with up to 129 x 65 x 33 grid points, and for hundreds to thousands of independent variables. These adjoint codes are now used in a gradient-based aerodynamic shape optimization problem for a swept, tapered wing. For each design iteration, the optimization package constructs an approximate, linear optimization problem, based upon the current objective function, constraints, and gradient values. The optimizer subroutines are called within a design loop employing the approximate linear problem until an optimum shape is found, the design loop limit is reached, or no further design improvement is possible due to active design variable bounds and/or constraints. The resulting shape parameters are then used by the grid generation code to define a new wing surface and computational grid. The lift-to-drag ratio and its gradient are computed for the new design by the automatically-generated adjoint codes. Several optimization iterations may be required to find an optimum wing shape. Results from two sample cases will be discussed. The reader should note that this work primarily represents a demonstration of use of automatically- generated adjoint code within an aerodynamic shape optimization. As such, little significance is placed upon the actual optimization results, relative to the method for obtaining the results.

Green, Lawrence↗

Center for Extended Magnetohydrodynamic Modeling (CEMM), Final Technical Report for UW-Madison Engineering Physics

The Center for Extended Magnetohydrodynamic Modeling (CEMM) focused on the further development, verification, validation, and application of two scientific computation programs, the NIMROD and M3D-C1 codes, for modeling macroscopic dynamics in magnetized plasma. Both NIMROD and M3D-C1 solve the mathematical equations that model two-fluid 3D magnetohydrodynamic (MHD). They are designed and optimized to be efficient and accurate for toroidal confinement physics calculations. The effort improved the fidelity of the physics models, the realism of the treatment of the surrounding vessel, coils, and other structures, the accuracy and efficiency of the algorithms, and the ability to scale calculations to thousands of processors in order to take advantage of leading-edge computers. The primary application areas of Resonant Magnetic Perturbations (RMP), Edge Harmonic Oscillations (EHO), Edge Localized Modes (ELMs), Disruption Studies, Sawteeth and Stationary States, and Kinetic MHD and Neoclassical Tearing Modes (NTM) are of concern for the international ITER experiment, which is under construction in France. The effort by the UW-Madison Engineering Physics component of CEMM improved the numerical methods in the NIMROD code with respect to modeling MHD interchange and two-fluid effects. It also improved the algorithm for solving large algebraic systems to enhance NIMROD's computational performance when running the code in parallel on increasing numbers of processor cores. The modeling efforts included a study of the nonlinear evolution of ballooning, and the findings were supported by analytical theory and computation. Numerical MHD modeling also examined the influences of two-fluid effects on ELMs and RMPs, where "two-fluid" refers to separation of electron dynamics from ion dynamics. Another related aspect considered the effects of a localized layer of electrical current density near the edge of the plasma confinement region. Two-fluid effects on resonant reconnecting instabilities were verified and applied to computations of sawtooth and drift-tearing dynamics.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Random circuit block-encoded matrix and a proposal of quantum LINPACK benchmark

The LINPACK benchmark reports the performance of a computer for solving a system of linear equations with dense random matrices. Although this task was not designed with a real application directly in mind, the LINPACK benchmark has been used to define the list of TOP500 supercomputers since the debut of the list in 1993. We propose that a similar benchmark, called the quantum LINPACK benchmark, could be used to measure the whole machine performance of quantum computers. The success of the quantum LINPACK benchmark should be viewed as the minimal requirement for a quantum computer to perform a useful task of solving linear algebra problems, such as linear systems of equations. We propose an input model called the Random Circuit Block-Encoded Matrix (RACBEM), which is a proper generalization of a dense random matrix in the quantum setting. The RACBEM model is efficient to be implemented on a quantum computer and can be designed to optimally adapt to any given quantum architecture, with relying on a black-box quantum compiler. Besides solving linear systems, the RACBEM model can be used to perform a variety of linear algebra tasks relevant to many physical applications, such as computing spectral measures, time series generated by a Hamiltonian simulation, and thermal averages of the energy. We implement these linear algebra operations on IBM Q quantum devices as well as quantum virtual machines, and demonstrate their performance in solving scientific computing problems.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Fast explicit solutions for neutrino-electron scattering: Explicit asymptotic methods

Here, we present results of explicit asymptotic approximations applied to neutrino-electron scattering in a representative model of neutrino population evolution under conditions characteristic of core-collapse supernova explosions or binary neutron star mergers. It is shown that this approach provides stable solutions of these stiff systems of equations, with accuracy and time stepping comparable to that for standard implicit treatments such as backward Euler, fixed point iteration, and Anderson-accelerated fixed point iteration. Because each time step can be computed more rapidly with the explicit asymptotic approximation than with implicit methods, this suggests that algebraically stabilized explicit integration methods could be used to compute neutrino evolution coupled to hydrodynamics more efficiently in stellar explosions and mergers than the methods currently in use.

79 ASTRONOMY AND ASTROPHYSICS↗

Description of electrical networks using wiring operators.

A scheme is presented for describing the interconnection of elements and subnetworks into networks by means of 'wiring operators.' This scheme is algebraic and is intended for conversing with computers. It is especially suitable for two-ports such as amplifiers, filters, microwave networks, and in general, transmission-type networks with an input and an output. The algebra is direct, convenient, and versatile. Each of the wiring operators corresponds to a specific set of calculations on the parameters of the networks involved.

Penfield, P., Jr.↗

Atmospheric transmittance model for photosynthetically active radiation

A parametric model of the atmospheric transmittance in the PAR band is presented. The model can be straightforwardly applied for calculating the beam, diffuse and global components of the PAR solar irradiance. The required inputs are: air pressure, ozone, water vapor and nitrogen dioxide column content, Ångström's turbidity coefficient and single scattering albedo. Comparison with other models and ground measured data shows a reasonable level of accuracy for this model, making it suitable for practical applications. From the computational point of view the calculus is condensed into simple algebra which is a noticeable advantage. For users interested in speed-intensive computation of the effective PAR solar irradiance, a PC program based on the parametric equations along with a user guide are available online at http://solar.physics.uvt.ro/srms.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Yet Another NLA Library: T-LAPACK

In recent years, Randomized numerical linear algebra (RandNLA) proved to be more than a theoretical novelty: projects like RandLAPACK demonstrate its practical value across architectures, and projects like RandBLAS build trust in randomization as a tool for high-performance NLA. This BoF considers two main questions. First, what are the pressing issues in software standards and implementation that need to be resolved for RandNLA to become a core component of HPC? Second, how can we mobilize a community effort to make progress on these issues? The BoF will engage the audience to discuss the idea of growing the role of RandNLA in high-performance computing and what it would take to scale from niche prototypes to robust, production-quality software libraries.

97 MATHEMATICS AND COMPUTING↗

The topology of the Liouville foliation for the Kovalevskaya integrable case on the Lie algebra so(4)

In this paper we study topological properties of an integrable case for Euler's equations on the Lie algebra so(4), which can be regarded as an analogue of the classical Kovalevskaya case in rigid body dynamics. In particular, for all values of the parameters of the system under consideration, the bifurcation diagrams of the momentum mapping are constructed, the types of critical points of rank 0 are determined, the bifurcations of Liouville tori are described, and the loop molecules are computed for all singular points of the bifurcation diagrams. It follows from the obtained results that some topological properties of the classical Kovalevskaya case can be obtained from the corresponding properties of the considered integrable case on the Lie algebra so(4) by taking a natural limit. Bibliography: 21 titles.

97 MATHEMATICS AND COMPUTING↗

A Contextually-Aware Sensitivity Analysis to Guide the Design of Randomized Least Squares Solvers in Applications

Our work on the DOE-sponsored project “A Contextually-Aware Sensitivity Analysis to Guide the Design of Randomized Least Squares Solvers in Applications,” was an effort to address critical challenges in nu merical computing and its applications to optimization. The increasing demand for robust and scalable solutions to large-scale linear algebra problems has highlighted the limitations of traditional approaches, particularly in heterogeneous and extreme-scale computing environments. Randomized Numerical Linear Algebra (RandNLA) offers a promising framework to address these challenges, and this proposal builds on this foundation by introducing innovations in sensitivity analysis and computational adaptability.

97 MATHEMATICS AND COMPUTING↗

Hedgehog bases for A n cluster polylogarithms and an application to six-point amplitudes

Multi-loop scattering amplitudes in N=4 Yang-Mills theory possess cluster algebra structure. In order to develop a computational framework which exploits this connection, we show how to construct bases of Goncharov polylogarithm functions, at any weight, whose symbol alphabet consists of cluster coordinates on the A n cluster algebra. As a result, using such a basis we present a new expression for the 2-loop 6-particle NMHV amplitude which makes some of its cluster structure manifest.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Classical affine W-algebras associated to Lie superalgebras

In this paper, we prove classical affine W-algebras associated to Lie superalgebras (W-superalgebras), which can be constructed in two different ways: via affine classical Hamiltonian reductions and via taking quasi-classical limits of quantum affine W-superalgebras. Also, we show that a classical finite W-superalgebra can be obtained by a Zhu algebra of a classical affine W-superalgebra. Using the definition by Hamiltonian reductions, we find free generators of a classical W-superalgebra associated to a minimal nilpotent. Moreover, we compute generators of the classical W-algebra associated to spo(2|3) and its principal nilpotent. In the last part of this paper, we introduce a generalization of classical affine W-superalgebras called classical affine fractional W-superalgebras. We show these have Poisson vertex algebra structures and find generators of a fractional W-superalgebra associated to a minimal nilpotent.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

SPINEQ: A program for determining aircraft equilibrium spin characteristics including stability

A computer program, SPINEQ, is described which can algebraically solve the nonlinear equations of motion for equilibrium spin conditions. Linear characteristics of the airplane about the equilibrium points are also determined. The theoretical basis of the program is outlined, computational flow is shown, the functions of major subroutines are described, and key parameters directing the computations are identified. Program input and output are described and illustrated by means of a test case. The program is available from COSMIC.

Adams, W. M., Jr.↗

Exotic matter on singular divisors in F-theory

We analyze exotic matter representations that arise on singular seven-brane configurations in F-theory. We develop a general framework for analyzing such representations, and work out explicit descriptions for models with matter in the 2-index and 3-index symmetric representations of SU(N) and SU(2) respectively, associated with double and triple point singularities in the seven-brane locus. These matter representations are associated with Weierstrass models whose discriminants vanish to high order thanks to nontrivial cancellations possible only in the presence of a non-UFD algebraic structure. This structure can be described using the normalization of the ring of intrinsic local functions on a singular divisor. We consider the connection between geometric constraints on singular curves and corresponding constraints on the low-energy spectrum of 6D theories, identifying some new examples of apparent “swampland” theories that cannot be realized in F-theory but have no apparent low-energy inconsistency.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Algorithmic Patterns for $$\mathcal {H}$$-Matrices on Many-Core Processors

In this work, we consider the reformulation of hierarchical ( \(\mathcal {H}\) ) matrix algorithms for many-core processors with a model implementation on graphics processing units (GPUs). \(\mathcal {H}\) matrices approximate specific dense matrices, e.g., from discretized integral equations or kernel ridge regression, leading to log-linear time complexity in dense matrix–vector products. The parallelization of \(\mathcal {H}\) matrix operations on many-core processors is difficult due to the complex nature of the underlying algorithms. While previous algorithmic advances for many-core hardware focused on accelerating existing \(\mathcal {H}\) matrix CPU implementations by many-core processors, we here aim at totally relying on that processor type. As main contribution, we introduce the necessary parallel algorithmic patterns allowing to map the full \(\mathcal {H}\) matrix construction and the fast matrix–vector product to many-core hardware. In this work, crucial ingredients are space filling curves, parallel tree traversal and batching of linear algebra operations. The resulting model GPU implementation hmglib is the, to the best of the authors knowledge, first entirely GPU-based Open Source \(\mathcal {H}\) matrix library of this kind. We investigate application examples as present in kernel ridge regression, Gaussian Process Regression and kernel-based interpolation. In this context, an in-depth performance analysis and a comparative performance study against a standard multi-core CPU \(\mathcal {H}\) matrix library highlights profound speedups of our many-core parallel approach.

97 MATHEMATICS AND COMPUTING↗

Extending the length and time scales of Gram–Schmidt Lyapunov vector computations

Lyapunov vectors have found growing interest recently due to their ability to characterize systems out of thermodynamic equilibrium. The computation of orthogonal Gram–Schmidt vectors requires multiplication and QR decomposition of large matrices, which grow as N{sup 2} (with the particle count). This expense has limited such calculations to relatively small systems and short time scales. Here, we detail two implementations of an algorithm for computing Gram–Schmidt vectors. The first is a distributed-memory message-passing method using Scalapack. The second uses the newly-released MAGMA library for GPUs. We compare the performance of both codes for Lennard–Jones fluids from N=100 to 1300 between Intel Nahalem/Infiniband DDR and NVIDIA C2050 architectures. To our best knowledge, these are the largest systems for which the Gram–Schmidt Lyapunov vectors have been computed, and the first time their calculation has been GPU-accelerated. We conclude that Lyapunov vector calculations can be significantly extended in length and time by leveraging the power of GPU-accelerated linear algebra.

97 MATHEMATICS AND COMPUTING↗

Verification, Validation, and Solution Quality in Computational Physics: CFD Methods Applied to Ice Sheet Physics

Procedures and methods for veri.cation of coding algebra and for validations of models and calculations used in the aerospace computational fluid dynamics (CFD) community would be ef.cacious if used by the glacier dynamics modeling community. This paper presents some of those methods, and how they might be applied to uncertainty management supporting code veri.cation and model validation for glacier dynamics. The similarities and differences between their use in CFD analysis and the proposed application of these methods to glacier modeling are discussed. After establishing sources of uncertainty and methods for code veri.cation, the paper looks at a representative sampling of veri.cation and validation efforts that are underway in the glacier modeling community, and establishes a context for these within an overall solution quality assessment. Finally, a vision of a new information architecture and interactive scienti.c interface is introduced and advocated.

Thompson, David E.↗

Deep learning symmetries and their Lie groups, algebras, and subalgebras from first principles

Abstract We design a deep-learning algorithm for the discovery and identification of the continuous group of symmetries present in a labeled dataset. We use fully connected neural networks to model the symmetry transformations and the corresponding generators. The constructed loss functions ensure that the applied transformations are symmetries and the corresponding set of generators forms a closed (sub)algebra. Our procedure is validated with several examples illustrating different types of conserved quantities preserved by symmetry. In the process of deriving the full set of symmetries, we analyze the complete subgroup structure of the rotation groups SO (2), SO (3), and SO (4), and of the Lorentz group S O ( 1 , 3 ) . Other examples include squeeze mapping, piecewise discontinuous labels, and SO (10), demonstrating that our method is completely general, with many possible applications in physics and data science. Our study also opens the door for using a machine learning approach in the mathematical study of Lie groups and their properties.

97 MATHEMATICS AND COMPUTING↗

State-of-the-art surveys on computational mechanics

Topics considered include advances in finite difference techniques for computational fluid dynamics, the spectral element methods for the incompressible Navier-Stokes equations, a review of recent developments in time integration, and advances and trends in element-by-element techniques. Also examined are the algebraic multigrid methods applied to problems in computational structural mechanics, grid generation for the solution of partial differential equations, advances in adaptive improvements, and new computing systems and their impact on computational mechanics.

Noor, Ahmed K.↗