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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Non-planar BCFW Grassmannian geometries

In this paper, we study non-adjacent BCFW recursion relations and their connection to positive geometry. For an adjacent BCFW shift, the n-point N k MHV tree-level amplitude in N = 4 SYM theory is expressed as a sum over planar on-shell diagrams, corresponding to canonical “dlog” forms on the cells in the positive Grassmannian G+(k, n). Non-adjacent BCFW shifts naturally lead to an expansion of the amplitude in terms of a different set of objects, which do not manifest the cyclic ordering and the hidden Yangian symmetry of the amplitude. We show that these terms can be interpreted as dlog forms on the non-planar Grassmannian geometries, generalizing the cells of the positive Grassmannian G+(k, n) to a larger class of objects which live in G(k, n). We focus mainly on the case of NMHV amplitudes and discuss in detail the Grassmannian geometries. We also propose an alternative way to calculate the associated on-shell functions and dlog forms using an intriguing connection between Grassmannian configurations and the geometry in the kinematical space.

1/N expansion↗
DOE OSTI2014

Grassmannians for scattering amplitudes in 4d $\mathcal{N}=4 $ SYM and 3d ABJM

Scattering amplitudes in 4d N=4 super Yang-Mills theory (SYM) can be described by Grassmannian contour integrals whose form depends on whether the external data is encoded in momentum space, twistor space, or momentum twistor space. Here, after a pedagogical review, we present a new, streamlined proof of the equivalence of the three integral formulations. A similar strategy allows us to derive a new Grassmannian integral for 3d N = 6 ABJM theory amplitudes in momentum twistor space: it is a contour integral in an orthogonal Grassmannian with the novel property that the internal metric depends on the external data. The result can be viewed as a central step towards developing an amplituhedron formulation for ABJM amplitudes. Various properties of Grassmannian integrals are examined, including boundary properties, pole structure, and a homological interpretation of the global residue theorems for N = 4 SYM.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Grassmannian Diffusion Maps--Based Dimension Reduction and Classification for High-Dimensional Data

This work introduces the Grassmannian diffusion maps (GDMaps), a novel nonlinear dimensionality reduction technique that defines the affinity between points through their representation as low-dimensional subspaces corresponding to points on the Grassmann manifold. Here, the method is designed for applications, such as image recognition and data-based classification of constrained high-dimensional data where each data point itself is a high-dimensional object (i.e., a large matrix) that can be compactly represented in a lower-dimensional subspace. The GDMaps is composed of two stages. The first is a pointwise linear dimensionality reduction wherein each high-dimensional object is mapped onto the Grassmann manifold representing the low-dimensional subspace on which it resides. The second stage is a multipoint nonlinear kernel-based dimension reduction using diffusion maps to identify the subspace structure of the points on the Grassmann manifold. To this end, an appropriate Grassmannian kernel is used to construct the transition matrix of a random walk on a graph connecting points on the Grassmann manifold. Spectral analysis of the transition matrix yields low-dimensional Grassmannian diffusion coordinates embedding the data into a low-dimensional reproducing kernel Hilbert space. Further, a novel data classification/recognition technique is developed based on the construction of an overcomplete dictionary of reduced dimension whose atoms are given by the Grassmannian diffusion coordinates. Three examples are considered. First, a "toy" example shows that the GDMaps can identify an appropriate parametrization of structured points on the unit sphere. The second example demonstrates the ability of the GDMaps to revealing the intrinsic subspace structure of high-dimensional random field data. In the last ex- ample, a face recognition problem is solved considering face images subject to varying illumination conditions, changes in face expressions, and occurrence of occlusions. The technique presented high recognition rates (i.e., 95% in the best case) using a fraction of the data required by conventional methods.

42 ENGINEERING↗
DOE OSTI2026

FOILPOLARS (Grassmannian Foil Shape Sweeps for Polar Generation) [SWR-26-095]

FOILPOLARS (Grassmannian Foil Shape Sweeps for Polar Generation): Multifidelity aerodynamic polar data generation for hydrofoil/tidal-turbine airfoil sections. Foilpolars ties together three pieces: *AeroSandbox supplies the baseline airfoil coordinates (UIUC database). *G2Aero parameterizes those shapes on a Grassmannian manifold (Karcher mean + PGA basis) and samples new perturbed shapes around that basis. *XFoil (panel method) and NeuralFoil (neural-network surrogate, shipped with AeroSandbox) each solve the resulting shapes for lift, drag, moment, and pressure at the swept angles of attack, Reynolds numbers, and n_crit values. Design optimization of foil shapes in a computationally efficient way requires polars data across many candidate shapes, not just a handful of baseline foils. However, high-fidelity CFD at that scale is too costly, and naive shape perturbation strays from realistic geometries. FOILPOLARS addresses this by loading baseline airfoils (via AeroSandbox) and mapping them onto a Grassmannian manifold (via G2Aero), computing a Karcher mean and principal geodesic analysis (PGA) basis. New shapes are sampled by perturbing PGA coefficients, keeping them close to the manifold of realistic foils. Each sampled shape is evaluated across a configurable sweep of angle of attack, Reynolds number, and critical amplification factor using two solvers: XFoil (panel method) and NeuralFoil (neural-network surrogate), producing a paired dataset of lift, drag, moment, pressure, convergence, and confidence, indexed alongside each shape's PGA coefficients and shared Grassmannian basis in a single xarray dataset. From this, FOILPOLARS produces convergence summaries and comparison plots per shape, Reynolds number, and n_crit. A command-line interface exposes each pipeline stage independently, supporting data-driven design, optimization, and machine-learning workflows for foils.

Sandhu, Rimple [National Laboratory of the Rockies↗
DOE OSTI2011

Triviality of vector bundles on twisted ind-Grassmannians

Twisted ind-Grassmannians are ind-varieties G obtained as direct limits of Grassmannians G(i{sub m},V{sup n}{sub m}) for m element of Z{sub >0} under embeddings of degree greater than 1. It has been conjectured by Donin and Penkov (2003) that any vector bundle of finite rank on a twisted ind-Grassmannian is trivial. We prove this conjecture. Bibliography: 16 titles.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

The positive orthogonal Grassmannian and loop amplitudes of ABJM

Herein we study the combinatorics associated with the positive orthogonal Grassmannian OG k and its connection to ABJM scattering amplitudes. We present a canonical embedding of OG k into the Grassmannian Gr( k , 2 k ), from which we deduce the canonical volume form that is invariant under equivalence moves. Remarkably the canonical forms of all reducible graphs can be converted into reduced ones with products of d log forms. Unlike super Yang–Mills, here the Jacobian plays a crucial role to ensure the d log form of the reduced representation. Furthermore in the positive region, we identify the functional map that arises from the triangle equivalence move as a 3-string scattering S -matrix which satisfies the tetrahedron equations by Zamolodchikov, implying (2 + 1)-dimensional integrability. We discuss the solution to the BCFW recursion relation for loop amplitudes, and demonstrate the presence of all physical singularities as well as the absence of all spurious ones. The on-shell diagram solution to the loop recursion relation exhibits manifest two-site cyclic symmetry and reveals that, to all loop, four and six-point amplitudes only have logarithmic singularities.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Grassmannian Shape Representations for Aerodynamic Applications: Preprint

Airfoil shape design is a classical problem in engineering, science, and manufacturing. Our motivation is to combine principled physics-based considerations for the shape design problem with modern computational techniques informed by a data-driven approach. Traditional analyses of airfoil shapes emphasize a flow-based sensitivity to deformations which can be represented generally by affine transformations (rotation, scaling, shearing, shifting). We present a novel representation of shapes which decouples affine-style deformations from a rich set of data-driven deformations over a submanifold of the Grassmannian. The Grassmannian representation, informed by a database of physically relevant airfoils, offers (i) a rich set of novel 2D airfoil deformations not previously captured in the data, (ii) improved low-dimensional parameter domain for inferential statistics, and (iii) consistent 3D blade representation and perturbation over a sequence of nominal shapes.

blade representation↗
DOE OSTI2022

Grassmannian Shape Representations for Aerodynamic Applications

Airfoil shape design is a classical problem in engineering, science, and manufacturing. Our motivation is to combine principled physics-based considerations for the shape design problem with modern computational techniques informed by a data-driven approach. Traditional analyses of airfoil shapes emphasize a flow-based sensitivity to deformations which can be represented generally by affine transformations (rotation, scaling, shearing, shifting). We present a novel representation of shapes which decouples affine-style deformations from a rich set of data-driven deformations over a submanifold of the Grassmannian. The Grassmannian representation, informed by a database of physically relevant airfoils, offers (i) a rich set of novel 2D airfoil deformations not previously captured in the data, (ii) improved low-dimensional parameter domain for inferential statistics, and (iii) consistent 3D blade representation and perturbation over a sequence of nominal shapes.

blade representation↗
DOE OSTI2022

Grassmannian diffusion maps based surrogate modeling via geometric harmonics

Abstract A novel surrogate model based on the Grassmannian diffusion maps (GDMaps) and utilizing geometric harmonics (GH) is developed for predicting the response of complex physical phenomena. The method utilizes GDMaps to obtain a low‐dimensional representation of the underlying behavior of physical/mathematical systems with respect to uncertain input parameters. Using this representation, GH, an out‐of‐sample extension technique, is employed to create a global map from the input parameter space to a Grassmannian diffusion manifold. GH is further employed to locally map points on the diffusion manifold onto the tangent space of a Grassmann manifold. The exponential map is then used to project the points in the tangent space onto the Grassmann manifold, where reconstruction of the full solution is performed. The performance of the proposed surrogate model is verified with three examples. The first problem is a toy example used to illustrate the technique. In the second example, errors associated with the various mappings are assessed by studying response predictions of the electric potential of a dielectric cylinder in a homogeneous electric field. The last example applies the method for uncertainty prediction in the strain field evolution in a model amorphous material using the shear transformation zone theory of plasticity.

42 ENGINEERING↗
DOE OSTI2015

Resurgence and dynamics of O(N) and Grassmannian sigma models

Here, we study the non-perturbative dynamics of the two dimensional O( N ) and Grassmannian sigma models by using compactification with twisted boundary conditions on R× S 1 , semi-classical techniques and resurgence. While the O(N) model has no instantons for N > 3, it has (non-instanton) saddles on R 2 , which we call 2d-saddles. On R× S 1 , the resurgent relation between perturbation theory and non-perturbative physics is encoded in new saddles, which are associated with the affine root system of the o( N ) algebra. These events may be viewed as fractionalizations of the 2d-saddles. The first beta function coefficient, given by the dual Coxeter number, can then be intepreted as the sum of the multiplicities (dual Kac labels) of these fractionalized objects. Surprisingly, the new saddles in O( N ) models in compactified space are in one-to-one correspondence with monopole-instanton saddles in SO( N ) gauge theory on R 3 ×S 1 . The Grassmannian sigma models Gr( N , M ) have 2d instantons, which fractionalize into N kink-instantons. The small circle dynamics of both sigma models can be described as a dilute gas of the one-events and two-events, bions. One-events are the leading source of a variety of non-perturbative effects, and produce the strong scale of the 2d theory in the compactified theory. We show that in both types of sigma models the neutral bion emulates the role of IR-renormalons. We also study the topological theta angle dependence in both the O (3) model and Gr( N , M ), and describe the multi-branched structure of the observables in terms of the theta-angle dependence of the saddle amplitudes, providing a microscopic argument for Haldane’s conjecture.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2019

Unified formalism for 6D superamplitudes based on a symplectic Grassmannian

Recently, twistor-like formulations of tree amplitudes involving n massless particles have been proposed for various 6D supersymmetric theories. The formulas are based on two different forms of the scattering equations: one based on rational maps and the other based on polarized scattering equations. We show that both formulations can be interpreted in terms of a symplectic (or complex Lagrangian) Grassmannian, LG( n , 2 n ), and that they correspond to different ways of fixing the GL( n , C) symmetry of LG( n , 2 n ). This provides an understanding of the equivalence of these different-looking formulas, and it leads to new twistor-like formulas for 6D superamplitudes

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2010

Canonical surfaces associated with projectors in Grassmannian sigma models

We discuss the construction of higher-dimensional surfaces based on the harmonic maps of S{sup 2} into CP{sup N-1} and other Grassmannians. We show that there are two ways of implementing this procedure - both based on the use of the relevant projectors. We study various properties of such projectors and show that the Gaussian curvature of these surfaces, in general, is not constant. We look in detail at the surfaces corresponding to the Veronese sequence of such maps and show that for all of them this curvature is constant but its value depends on which mapping is used in the construction of the surface.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

The Grassmannian Atlas: A General Framework for Exploring Linear Projections of High-Dimensional Data

Linear projections are one of the most common approaches to visualize high-dimensional data. Since the space of possible projections is large, existing systems usually select a small set of interesting projections by ranking a large set of candidate projections based on a chosen quality measure. However, while highly ranked projections can be informative, some lower ranked ones could offer important complementary information. Therefore, selection based on ranking may miss projections that are important to provide a global picture of the data. Here, the proposed work fills this gap by presenting the Grassmannian Atlas, a framework that captures the global structures of quality measures in the space of all projections, which enables a systematic exploration of many complementary projections and provides new insights into the properties of existing quality measures.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Form factors with q{sup 2} = 0 and Grassmannians in N = 4 Sym theory

In this note we consider tree level form factors of operators from stress tensor supermultiplet with light like operator momentum q{sup 2} = 0. The presentation of form factors in terms of the regulated integral over Grassmannian is given. The conjectured formula is verified by successfully reproducing known answers in the MHV and N{sup k−2}MHV, k ≥ 3 sectors as well as appropriate soft limit behavior.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2017

Off-shell amplitudes and Grassmannians

The Grassmannian representation for gauge-invariant amplitudes for arbitrary number of legs with one of them being off-shell is derived for the case of N = 4 SYM. The obtained formula are successfully checked against known BCFW results for MHV{sub n}, NMHV{sub 4} and NMHV{sub 5} amplitudes.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Polynomial chaos expansions on principal geodesic Grassmannian submanifolds for surrogate modeling and uncertainty quantification

In this work we introduce a manifold learning-based surrogate modeling framework for uncertainty quantification in high-dimensional stochastic systems. Our first goal is to perform data mining on the available simulation data to identify a set of low-dimensional (latent) descriptors that efficiently parameterize the response of the high-dimensional computational model. To this end, we employ Principal Geodesic Analysis on the Grassmann manifold of the response to identify a set of disjoint principal geodesic submanifolds, of possibly different dimension, that captures the variation in the data. Since operations on the Grassmann require the data to be concentrated, we propose an adaptive algorithm based on Riemannian K-means and the minimization of the sample Fréchet variance on the Grassmann manifold to identify “local” principal geodesic submanifolds that represent different system behavior across the parameter space. Polynomial chaos expansion is then used to construct a mapping between the random input parameters and the projection of the response on these local principal geodesic submanifolds. Here, the method is demonstrated on four test cases, a toy-example that involves points on a hypersphere, a Lotka-Volterra dynamical system, a continuous-flow stirred-tank chemical reactor system, and a two-dimensional Rayleigh-Bénard convection problem.

42 ENGINEERING↗