Award Abstract # 1216866
Collaborative Research: Sparse spectral-tau methods for binary neutron star initial data

NSF Org: DMS
Division Of Mathematical Sciences
Recipient: UNIVERSITY OF NEW MEXICO
Initial Amendment Date: September 11, 2012
Latest Amendment Date: September 11, 2012
Award Number: 1216866
Award Instrument: Standard Grant
Program Manager: rosemary renaut
DMS
 Division Of Mathematical Sciences
MPS
 Directorate for Mathematical and Physical Sciences
Start Date: September 15, 2012
End Date: August 31, 2016 (Estimated)
Total Intended Award Amount: $131,490.00
Total Awarded Amount to Date: $131,490.00
Funds Obligated to Date: FY 2012 = $131,490.00
History of Investigator:
  • Stephen Lau (Principal Investigator)
    lau@math.unm.edu
Recipient Sponsored Research Office: University of New Mexico
1 UNIVERSITY OF NEW MEXICO
ALBUQUERQUE
NM  US  87131-0001
(505)277-4186
Sponsor Congressional District: 01
Primary Place of Performance: University of New Mexico
Mathematics and Statistics
Albuquerque
NM  US  87131-0001
Primary Place of Performance
Congressional District:
01
Unique Entity Identifier (UEI): F6XLTRUQJEN4
Parent UEI:
NSF Program(s): COMPUTATIONAL MATHEMATICS
Primary Program Source: 01001213DB NSF RESEARCH & RELATED ACTIVIT
Program Reference Code(s): 9263, 9150
Program Element Code(s): 127100
Award Agency Code: 4900
Fund Agency Code: 4900
Assistance Listing Number(s): 47.049

ABSTRACT

Binary neutron star inspiral is the most certain source of gravitational waves detectable by Earth-based observatories like the US LIGO project, and simulations of such binaries should facilitate eventual detections. These simulations require initial conditions: solutions to the initial value problem of general relativity for the coupled gravity-matter system. The conformal thin sandwich method is an excellent approach for solving the initial value problem; however, although not an intrinsic assumption of the method, in practice the approach has assumed conformal flatness (as have other valuable approaches). Conformal flatness yields unphysical junk radiation. By numerically constructing helically symmetric solutions to the Einstein equations, the PI will extract initial data (or conformal thin sandwich trial data) which does not rely on conformal flatness, and therefore contains the correct initial gravitational wave content. The mixed PDEs arising from the helical reduction of the Einstein equations (or their approximation in the post-Minkowski formalism) will be solved with innovative techniques: sparse modal spectral-tau methods with new preconditioning strategies. In part, these strategies may rely on randomized algorithms for the interpolative decomposition. Spectral methods deliver superb accuracy for smooth problems(neutron star spacetimes are smooth almost everywhere), and sparsity affords a fast matrix-vector multiply when using a Krylov-subspace method to iteratively solve a linear system. Whereas the preconditioning of nodal (collocation) spectral methods is well studied, less is known about modal preconditioning. Our techniques have been successfully applied to models of the binary neutron star problem. Moreover, the problem's physical structure has already been explored with different, but limited, techniques.

This project is to combine two sets of techniques (each already developed) and further develop the first set (spectral-tau methods), in order to obtain new results for a leading problem in gravitational wave physics. The PI will develop these mathematical methods by applying them to the specific neutron star problem described above. This strategy of specificity is often used in the development of techniques, which then prove to be more general. Because the scientific problem is of great interest, much is known about it, and results therefore exist withwhich comparisons can be made. These comparisons facilitate the development of mathematical algorithms. Conversely, new mathematical methods deliver more and/or better solutions which enhances scientific understanding.

PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH

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M. Beroiz, T. Hagstrom, S. R. Lau, and R. H. Price "Multidomain, sparse, spectral-tau method for helically symmetric flow" Computers & Fluids , v.102 , 2014 , p.250 0045-7930
M. Beroiz, T. Hagstrom, S. R. Lau, and R. H. Price "Multidomain, sparse, spectral-tau method for helically symmetric flow" Computers & Fluids , v.102 , 2014 , p.250
S. R. Lau and R. H. Price "Sparse modal tau-method for helical binary neutron stars." Proceedings of ICOSAHOM 2014 (International Conference on Spectral and High Order Methods). Lecture Notes in Computational Science and Engineering 106, 315-323 (2015). , v.106 , 2015

PROJECT OUTCOMES REPORT

Disclaimer

This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.

In scientific and engineering modelling, computers are often used to
solve partial differential equations, the mathematical foundation    
for many physical phenomena, for example the propagation of waves.
Such modelling can be done in relatively straightforward ways
("finite difference" or basic "finite element" methods), but a more
sophisticated class of techniques, "spectral methods," yield high
accuracy for some problems. In our work we adopt a refined spectral
method that features sparsity; in effect, the first step toward a
solution is taken through the mathematical structure itself, without
requiring significant computer computation. Our sparse spectral
approach had earlier been shown effective for some ordinary differential
equations, but not for the much more difficult challenge of partial
differential equations.

It is often best to develop new mathematical/computational methods in
the context of a specific physical problem. In our case the problem
involves binary neutron stars. A binary pair of such stars emits
gravitational waves and spirals inward, a process that is described
by the partial differential equations of Einstein's general theory of
relativity. The evolution in time of the inspiral can currently be
computed well with highly developed computational infrastructure. What
is missing is a realistic starting point, the initial configuration.

The partial differential equations that must be solved for the initial
configuration have proved to be a stubborn challenge, and researchers
have typically used a solution that is mathematically convenient, but
far from appropriate physically. This starting point evolves into a
correct solution, but it means that the evolution computation must be
carried out for a longer time than would be necessary for a more
physically correct starting solution.

We have endeavored to use sparse spectral methods to solve for a
physically correct initial approximation. The magnitude of the
challenge has required that the problem be broken into a sequence
of ever more advanced projects. The first of these was the solution
not of the Einstein equations, but of Newton's equations for the
initial binary configuration. The main simplification in this model
is that there are no waves. Solving this "simple" problem turned
out, as anticipated, to reveal many important details and to set up
much of the infrastructure for a more realistic model. Indeed, many
unanticipated problems developed in the Newtonian model, in
particular, those involving the stellar surface, that were not
particularly "Einsteinian."

The outcome of this work is a highly precise set of computer
programs that solves for initial neutron star structure. We have
not solved the Einstein equations themselves, but rather an
approximation ("post-Newtonian/post-Minkowskian") to Einstein's
equations. This approximation should be more than adequate for an
improved initial configuration. We have, therefore, partially achieved
our goals for this work. Next steps include looking at the physics
inherent in the initial solutions themselves, and collaborating with
researchers who need initial configurations for their codes that
evolve these initial configurations.


Last Modified: 11/28/2016
Modified by: Stephen R Lau

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