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Computational Methods for Neutrino Transportin Core-Collapse Supernovae
Eirik [email protected]
March 22, 2017
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Outline
1 Background
2 Neutrino Transport Equations
3 Solving the Equations on a Computer
4 Some Examples
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Core-Collapse Supernovae (CCSNe)Explosion of Massive Star (M & 8 M�). Dominant Source of Heavy Elements.
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Computational Challenge
Computational models needed to interpret observations
Neutrino transport most compute-intensive component of models
I Exascale computing challenge
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Core-Collapse Supernovae (CCSNe)Neutrinos Play Fundamental Role
40 H.-Th. Janka et al. / Physics Reports 442 (2007) 38–74
Fig. 1. Schematic representation of the evolutionary stages from stellar core collapse through the onset of the supernova explosion to the neutrino-drivenwind during the neutrino-cooling phase of the proto-neutron star (PNS). The panels display the dynamical conditions in their upper half, with arrowsrepresenting velocity vectors. The nuclear composition as well as the nuclear and weak processes are indicated in the lower half of each panel. Thehorizontal axis gives mass information. MCh means the Chandrasekhar mass and Mhc the mass of the subsonically collapsing, homologous innercore. The vertical axis shows corresponding radii, with RFe, Rs, Rg, Rns, and R! being the iron core radius, shock radius, gain radius, neutron starradius, and neutrinosphere, respectively. The PNS has maximum densities " above the saturation density of nuclear matter ("0).
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Core-Collapse Supernovae (CCSNe)Neutrinos Play Fundamental Role
40 H.-Th. Janka et al. / Physics Reports 442 (2007) 38–74
Fig. 1. Schematic representation of the evolutionary stages from stellar core collapse through the onset of the supernova explosion to the neutrino-drivenwind during the neutrino-cooling phase of the proto-neutron star (PNS). The panels display the dynamical conditions in their upper half, with arrowsrepresenting velocity vectors. The nuclear composition as well as the nuclear and weak processes are indicated in the lower half of each panel. Thehorizontal axis gives mass information. MCh means the Chandrasekhar mass and Mhc the mass of the subsonically collapsing, homologous innercore. The vertical axis shows corresponding radii, with RFe, Rs, Rg, Rns, and R! being the iron core radius, shock radius, gain radius, neutron starradius, and neutrinosphere, respectively. The PNS has maximum densities " above the saturation density of nuclear matter ("0).
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Neutrino Mean-Free Path
Shock&Radius&Gain&Radius&
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Neutrino Transport: Boltzmann Equation
Stellar fluid semi-transparent to neutrinos in heating region
Classical description based on non-negative distribution function
dN = f (p, x , t) dp dx
Kinetic equation: balance between advection and collisions
L(f ) = C(f )
I Advection: Ballistic transport, relativistic effects
I Collisions: Emission/absorption, scattering, pair processes
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Boltzmann Equation: Left-Hand SidePhase-Space Advection
Relativistic Liouville operator
L(f ) = pµ∂f
∂xµ− pν pρ Γi
νρ
∂f
∂pi
Neutrino four-momentum
pµ = ε(
1, cosϑ, sinϑ cosϕ, sinϑ sinϕ)T
Chirstoffel symbols
Γµνρ =1
2gµσ
( ∂gσν∂xρ
+∂gσρ∂xν
− ∂gνρ∂xσ
)
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Boltzmann Equation: Right-Hand SideNeutrino-Matter Interactions
Electron capture
e− + p n + νe
e− + (A,Z ) (A,Z − 1) + νe
e+ + n p + ν̄e
Scattering
ν + α,A α,A + ν
ν + e−, e+, n, p ν′ + (e−)′, (e+)′, n′, p′
Pair processes
e− + e+ ν + ν̄
N + N N ′ + N ′ + ν + ν̄
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Boltzmann Equation: Right-Hand SideIntegral Operators
Example: Neutrino-electron scattering
C(f)(p) =
(1− f (p)
) ∫R3
R(p ← q) f (q) dq
− f (p)
∫R3
R(p → q)(
1− f (q))dq
Computationally expensive to evaluate
C(f)(pi ) =
Np∑k=1
Mik(f ) f (pk)
O(N2p) operations
Must be evaluated for every x and t
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Solving the Equations
Challenges:
High dimensionality f (p, x , t) ∈ R3 × R3 × R+
I High-order accurate methods
Multiple time scales τcol � τadv
I Efficient time-integration methods
Robustness
I Distribution function bounded: f ∈ [0, 1] for Fermions
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Model Equation
Consider Boltzmann equation in “slab symmetry” with simple collision term
∂t f + µ∂x f = η − χ f
f = f (x , t; ε, µ). Consider fixed ε ∈ R+ and µ = cosϑ ∈ [−1, 1]
η(x ; ε) > 0 Emissivity
χ(x ; ε) > 0 Absorption opacity
Collision term drives f towards equilibrium value fEq
fEq = η/χ (= Fermi Dirac)
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Spatial Discretization
Divide space into N intervals Ii = {x : x ∈ [xi−1/2, xi+1/2]} ∀ i = 1, . . . ,N
xi-1/2 xi+1/2Δx
xi-1 xi xi+1
In each interval Ii , define the average
f̄i (t) =1
∆x
∫Ii
f (x , t) dx
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Spatial Discretization
Integrate Boltzmann equation over interval Ii
∂t f̄i = − 1
∆x
(µf |i+1/2 − µf |i−1/2
)+ η̄i −
1
∆x
∫Ii
χ f dx (Exact Equation)
Need to approximate
µf |i+1/2 ≈ µ̂f |i+1/2 =1
2
(µ+ |µ|
)f̄i +
1
2
(µ− |µ|
)f̄i+1
η̄i ≈ ηi and1
∆x
∫Ii
χ f dx ≈ χi f̄i
So that
∂t f̄i = − 1
∆x
(µ̂f |i+1/2 − µ̂f |i−1/2
)+ ηi − χi f̄i
= A(f̄i−1, f̄i , f̄i+1) + C(f̄i ) = F(f̄i−1, f̄i , f̄i+1)
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Spatial DiscretizationUpwind Method
∂t f + µ∂x f = 0 has solution f (x , t) = f0(x − µ t)
xi-1/2 xi+1/2
μ>0
μΔt
µ̂f |i+1/2 =1
2
(µ+ |µ|
)f̄i +
1
2
(µ− |µ|
)f̄i+1
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Time IntegrationDivide time domain t0 < t1, t2, . . . , tn, tn+1, . . . ,T
Define solution vector f̄ (t) = (f̄1(t), . . . , f̄N(t))T and write dt f̄ = F(f̄ )
Explicit
f̄n+1
= f̄n
+
∫ tn+1
tnF(f̄ (τ)) dτ
≈ f̄n
+ ∆tF(f̄n) (easy)
Implicit
f̄n+1
= f̄n
+
∫ tn+1
tnF(f̄ (τ)) dτ
≈ f̄n
+ ∆tF(f̄n+1
) (hard)
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Time IntegrationRestrictions on the Time Step ∆t
AssumefEq,i , f̄
ni ∈ [0, 1]
Explicit method for collision term:
f̄ n+1i = (∆t χi ) fEq,i + (1−∆t χi ) f̄
ni
Need ∆t ≤ 1/χi for f̄ n+1i ∈ [0, 1] (not practical)
Implicit method for collision term:
f̄ n+1i =
( ∆t χi
1 + ∆t χi
)fEq,i +
( 1
1 + ∆t χi
)f̄ ni
f̄ n+1i ∈ [0, 1] for any ∆t ≥ 0
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Time IntegrationUse combination of Explicit and Implicit methods
dt f̄i = A(f̄i−1, f̄i , f̄i+1)︸ ︷︷ ︸Explicit
+ C(f̄i )︸︷︷︸Implicit
= +
I : f̄ ?i = f̄ ni + ∆tA(f̄ ni−1, f̄ni , f̄
ni+1) II : f̄ n+1
i = f̄ ?i + ∆t C(f̄ n+1i )
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Bound-Preserving Spatial DiscretizationNeed to preserve f ∈ [0, 1] in advection step
Set of admissible states
R = { f | f ≥ 0 and f ≤ 1} (convex set)
Explicit advection step (λ = ∆t/∆x)
f̄ ?i = f̄ ni − λ(µ̂f |i+1/2 − µ̂f |i−1/2
)=
1
2λ(|µ|+ µ
)f̄ ni−1 +
(1− λ |µ|
)f̄ ni +
1
2λ(|µ| − µ
)f̄ ni+1
=1∑
k=−1
αk f̄ni+k where
1∑k=−1
αk = 1
For αk ≥ 0, f̄ ?i is a convex combination of {f̄ ni−1, f̄ni , f̄
ni+1}
Need: ∆t ≤ ∆x
|µ|(acceptable)
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Numerical Examples
Journal of Computational Physics 287 (2015) 151–183
Contents lists available at ScienceDirect
Journal of Computational Physics
www.elsevier.com/locate/jcp
Bound-preserving discontinuous Galerkin methods for
conservative phase space advection in curvilinear
coordinates ✩
Eirik Endeve a,c,∗, Cory D. Hauck a,b, Yulong Xing a,b, Anthony Mezzacappa c
a Computational and Applied Mathematics Group, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USAb Department of Mathematics, University of Tennessee Knoxville, TN 37996-1320, USAc Department of Physics and Astronomy, University of Tennessee Knoxville, TN 37996-1200, USA
a r t i c l e i n f o a b s t r a c t
Article history:Received 24 October 2014Received in revised form 3 February 2015Accepted 5 February 2015Available online 11 February 2015
Keywords:Boltzmann equationRadiation transportHyperbolic conservation lawsDiscontinuous GalerkinMaximum principleHigh order accuracy
We extend the positivity-preserving method of Zhang and Shu [49] to simulate the advection of neutral particles in phase space using curvilinear coordinates. The ability to utilize these coordinates is important for non-equilibrium transport problems in general relativity and also in science and engineering applications with specific geometries. The method achieves high-order accuracy using Discontinuous Galerkin (DG) discretization of phase space and strong stability-preserving, Runge–Kutta (SSP-RK) time integration. Special care is taken to ensure that the method preserves strict bounds for the phase space distribution function f ; i.e., f ∈ [0, 1]. The combination of suitable CFL conditions and the use of the high-order limiter proposed in [49] is sufficient to ensure positivity of the distribution function. However, to ensure that the distribution function satisfies the upper bound, the discretization must, in addition, preserve the divergence-free property of the phase space flow. Proofs that highlight the necessary conditions are presented for general curvilinear coordinates, and the details of these conditions are worked out for some commonly used coordinate systems (i.e., spherical polar spatial coordinates in spherical symmetry and cylindrical spatial coordinates in axial symmetry, both with spherical momentum coordinates). Results from numerical experiments — including one example in spherical symmetry adopting the Schwarzschild metric — demonstrate that the method achieves high-order accuracy and that the distribution function satisfies the maximum principle.
© 2015 Elsevier Inc. All rights reserved.
1. Introduction
In this paper, we design discontinuous Galerkin methods for the solution of the collision-less, conservative Boltzmann equation in general curvilinear coordinates
✩ This research is sponsored, in part, by the Laboratory Directed Research and Development Program of Oak Ridge National Laboratory (ORNL), managed by UT-Battelle, LLC for the U.S. Department of Energy under Contract No. De-AC05-00OR22725. It used resources of the Oak Ridge Leadership Computing Facility at ORNL provided through the INCITE program and a Director’s Discretionary allocation. The research of the second author is supported in part by NSF under Grant No. 1217170. The research of the third author is supported in part by NSF grant DMS-1216454.
* Corresponding author. Tel.: +1 865 576 6349; fax: +1 865 241 0381.E-mail addresses: [email protected] (E. Endeve), [email protected] (C.D. Hauck), [email protected] (Y. Xing), [email protected] (A. Mezzacappa).
http://dx.doi.org/10.1016/j.jcp.2015.02.0050021-9991/© 2015 Elsevier Inc. All rights reserved.
High-order method
Local expansion: f (p, x , t) =∑k
f̂k(t)φk(p, x)
Same principles (but somewhat more intricate)
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Advection Test with Smooth Analytical SolutionHigh-order methods can offer substantial savings in computational cost
102 104 106 108
10−10
10−5
100
Degrees of Freedom
L1 Erro
r Nor
m
DG(1)DG(2)DG(3)
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Numerical Examples in Spherical Symmetryds2 = −α2 dt2 + ψ4 (dr2 + r2 dθ2 + r2 sin2 θ dφ2); f = f (r , µ, ε, t)
Boltzmann equation with relativistic gravity
1
α
∂f
∂t+
1
αψ6 r2
∂
∂r
(αψ4 r2 µ f
)︸ ︷︷ ︸
Spatial advection
− 1
ε2
∂
∂ε
(ε3 1
ψ2 α
∂α
∂rµ f)
︸ ︷︷ ︸Energy advection
+∂
∂µ
( (1− µ2
)ψ−2
{ 1
r+
1
ψ2
∂ψ2
∂r− 1
α
∂α
∂r
}f)
︸ ︷︷ ︸Angular advection
= 0
Schwarzschild metric
α =1− M
2 r
1 + M2 r
and ψ = 1+M
2 r
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Radiating Sphere TestNeutrinos propagating out of gravitational well
M"="0.0"E""="0.5"
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Radiating Sphere TestNeutrinos propagating out of gravitational well
M"="0.0"E""="0.5"
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Varying the Mass M : f (r , µ, ε = const., tend)
M = 0.0 E = 0.5
M = 2/3 E = 0.5
M = 2/3 E = 0.3
M = 0.2 E = 0.5
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Neutrinos Streaming Out of Gravitational WellGravitational Redshift
Fermi-‐Dirac
First Order Second Order Third Order
Emi5ed Spectrum, r=1
Spectra, r=3
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Positivity: f (r , µ, ε, t) and 1− f (r , µ, ε, t)
Fermi-‐Dirac Spectrum at r=3
Without limiter: f and 1-‐f < 0 near Fermi surface
Standard Scheme
BP Scheme
Standard Scheme
BP Scheme
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Homogeneous SphereSmit et al. 1997, A&A, 325, 203-211
Num
ber
Den
sity
Radius
Num
ber
Den
sity
Radius
ε = 10-1 ε = 10-8 Vacuum Vacuum
3rd Order 3rd Order
Transport tests
Optically thin limit Optically thick limit
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Summary
High dimensionality f (p, x , t) ∈ R3 × R3 × R+
I High-order accurate methods
Multiple time scales τcol � τadv
I Efficient time-integration methods
Robustness
I Distribution function bounded: f ∈ [0, 1] for Fermions
There is a lot more to do!
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The End
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