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1/25
Optimized Ogata quadrature andapplications to the Sivers Asymmetry
John Terry
University of California, Los Angeles
QCD Evolution WorkshopArgonne National Lab
May 15, 2019
2/25
Fit to Sivers asymmetry done in collaboration with
Miguel Echevarriaand Zhongbo Kang.
Optimized Ogata method is done in collaboration with
Zhongbo Kang,Alexei Prokudin,and Nobuo Sato.
3/25
Overview
1 Introduction to the Sivers Asymmetry
2 TMD Formalism for Sivers Asymmetry
3 Why we need high efficiency Fourier transforms
4 Preliminary Fit Results
5 Conclusions
4/25
Why Sivers Asymmetry
By measuring the Sivers asymmetry, one probes quark Sivers functions
Modified universality (sign change between SIDIS and DY)
f⊥q1T (x, k⊥)|SIDIS = −f⊥q1T (x, k⊥)|DY
fq1 (x,~k⊥, ~S) = fq1 (x, k⊥)−1
Mf⊥q1T (x, k⊥)~S · (p× ~k⊥)
5/25
SIDIS: e(`) + p(P,~s⊥) → e(`′) + h(Ph) + X
The differential cross section with TMD factorization
dσ
dxBdydzhd2q⊥= σDIS
0
[FUU + sin(φh − φs)F
sin(φh−φs)UT
]
Asin(φh−φs)UT =
Fsin(φh−φs)UT
FUU
FUU (q⊥, Q) = H(Q,µ)∑q
e2q
∫d2k⊥d
2p⊥fq/p(xB , k2⊥)Dh/q(zh, p
2⊥)δ(2)
(k⊥ +
p⊥zh− q⊥
)
Fsin(φh−φs)UT (q⊥, Q) = − H(Q,µ)
∑q
e2q
∫d2k⊥d
2p⊥k⊥Mf⊥q1T (xB , k
2⊥)Dh/q(zh, p
2⊥)
δ(2)
(k⊥ +
p⊥zh− q⊥
)
6/25
FUU in b⊥ space
Unpolarized structure function in the TMD formalism
FUU (Q, q⊥) =
∫ ∞0
b⊥db⊥2π
J0(b⊥q⊥) FUU (Q, b⊥)
FUU (b⊥;x, z,Q) ≡ HDIS(µ,Q)Cq←i ⊗ f iA (xB , µb) Cj←q ⊗Dih/j (zh, µb)
× exp
(∫ Q
µb∗
dµ′
µ′
[2γ(µ′)− ln
(Q2
µ′2
)γK(µ′)
]+ K(b⊥, µb∗ )ln
(Q2
µ2b∗
))
× exp
(−gf (x, b⊥)− gD(z, b⊥)− 2gK(b⊥, bmax)ln
(Q
Q0
))
7/25
F sinφh−φsUT in b⊥ space
Polarized structure function in the TMD formalism
Fsin(φh−φs)UT (Q, q⊥) =
∫ ∞0
b2⊥db⊥
4πJ1(b⊥q⊥) F
sin(φh−φs)UT (Q, b⊥)
Fsin(φh−φs)UT (b⊥;x, z,Q) ≡ HDIS(µ,Q)∆Cq←i ⊗ f
⊥(1)1T (xB , µb∗ )Cj←q ⊗Dih/j (zh, µb∗ )
× exp
(∫ Q
µb∗
dµ′
µ′
[2γ(µ′)− ln
(Q2
µ′2
)γK(µ′)
]+ K(b⊥, µb∗ )ln
(Q2
µ2b∗
))
× exp
(−gT (x, b⊥)− gD(z, b⊥)− 2gK(b⊥, bmax)ln
(Q
Q0
))
8/25
Qiu-Sterman function
f⊥(1)1T (xB , µb∗ ) = −
1
2MTq,F (xB , xB , µb∗ ).
Initial condition
Tq/F (x, x,Q0) = Nq(αq + βq)(αq+βq)
ααqq β
βqq
xαq (1− x)βqfq/A(x,Q0)
fit parameters: αu, αd, Nu, Nd are the valence fit parameters and αsea, Nu, Nd, Ns,and Ns are the sea fit paramters and βq = β is the same for all flavors.Evolve the Qiu-Sterman function according to the following approximate form
∂
∂lnµ2Tq,F
(x, x;µ2
)=αs(µ2)
2π
∫ 1
x
dx′
x′PQSq←q
(x′, αs
(µ2))Tq,F
( xx′,x
x′;µ2)
The splitting kernel is
PQSq←q(z) = Pq←q(z)−NCδ(1− z).
9/25
NLO and NNLL
Coefficient functions at NLO, e.g., NLO TMD PDF coefficient functions
Cq←q′ (x, µb) = δqq′
[δ(1− x) +
αs
π
CF
2(1− x)
]Cq←g(x, µb) =
αs
πTRx(1− x) .
The quark-Sivers coefficient function
∆CTq←q′ (x, µb) = δqq′
[δ(1− x)−
αs
2π
1
4NC(1− x)
]Perturbative Sudakov to NNLL (γK to O(α3
s) and γ to O(α2s))
exp
(∫ Q
µb∗
dµ′
µ′
[2γ(µ′)− ln
(Q2
µ′2
)γK(µ′)
])
10/25
Non-perturbative Parameterization
Unpolarized SIDIS parameterization
exp
(−gf (x, b⊥)− gD(z, b⊥)− 2gK(b⊥, bmax)ln
(Q
Q0
))
gf (x, b⊥) = 0.106 b2⊥ gD(z, b⊥) = 0.042 b2⊥/z2h gK = 0.42 ln
(b⊥b∗
)Sivers function
exp
(−gT (x1, b⊥)− gK(b⊥, bmax)ln
(Q
Q0
))gT (x1, b⊥) = gSb
2⊥
gS is fit parameter.P. Sun, J. Isaacson, C. P. Yuan, and F. Yuan, Int. J. Mod. Phys. A33 , 1841006(2018), arXiv:1406.3073.Z.-B. Kang, A. Prokudin, P. Sun, and F. Yuan, Phys. Rev. D93 , 014009 (2016),arXiv:1505.05589.
11/25
A need for fast Fourier-Bessel Transforms
For global analysis, need to perform the following types of integrals many times
FUU (Q, q⊥) =1
2π
∫ ∞0
db⊥ b⊥J0(b⊥q⊥)FUU (Q, b⊥)
FUT (Q, q⊥) =1
4π
∫ ∞0
db⊥ b2⊥J1(b⊥q⊥)FUT (Q, b⊥)
b⊥ space functions are expensive to call.
12/25
Ogata Formalism
Original Ogata’s quadrature formula∫ ∞−∞
dx|x|2n+1f(x) = h∞∑
j=−∞,j 6=0
wnj |xnj |2n+1f(xnj) +O(e−c/h
)For an even f(x)∫ ∞
0dx|x|2n+1f(x) = h
∞∑j=0
wnj |xnj |2n+1f(xnj) +O(e−c/h
)The nodes and weights
xnj = hξnj , wnj =2
π2ξn|j|Jn+1(πξn|j|)
πξnj are zeros of the Bessel function Jn(x) : Jn (πξnj) = 0.
13/25
Double exponential transformation
Ogata makes the following change of variables
x =π
hψ(t) with ψ(t) = t tanh
(π2
sinh t)
Quadrature becomes∫ ∞0
dxf(x) Jn(x) ≈ πN∑j=1
wnj f(πhψ(xnj)
)Jn(πhψ(xnj)
)ψ′(xnj),
Asymptotic behavior
π
hψ (hξnj) ≈ πξnj
[1− 2 exp
(−π
2ehξnj
)]
Jn(πhψ(xnj)
)≈ 2πξnjJn+1(πξnj) exp
(−π
2ehξnj
).
14/25
Optimization Scheme: how to choose h
Need to optimize parameters h such that error terms are small for small N .∫ ∞0
dxf(x) Jn(x) = hN∑j=0
wnjf(hξnj) Jn(hξnj) + ...
∫ ∞0
dxf(x) Jn(x) ≈ πN∑j=1
wnj f(πhψ(hξnj)
)Jn(πhψ(hξnj)
)ψ′(hξnj) + ...
Make the first node contribute the most
∂
∂h(hf(hξn1)) = 0 ,
Can make sure that errors in both formulas are similar
huξnN =π
hψ(hξnN ) .
15/25
Efficiency for Toy TMDsWant to test the convergence. Need a function with analytic
W (q⊥) =
∫ ∞0
db⊥b⊥ W (b⊥) J0(b⊥q⊥)
Let’s define the toy TMDs
WE(b⊥;β, σ) =1
b⊥
(βb⊥σ2
)β2/σ21
Γ(β2
σ2 )e− βb⊥
σ2 .
The function peaks at
b⊥ =1
Q=β2 − σ2
β
Take Q = 2 and σ = 1.
16/25
How well was h determined?
%error =exact−Ogata result(N = 15)
exact∗ 100
Optimization conditions
∂
∂h(hf(hξn1)) = 0 , huξnN =
π
hψ(hξnN ) .
10−2 10−1 100 101
b⊥ (GeV−1)
−0.1
0.1
0.3
0.5
0.7
b ⊥Jn(q⊥b ⊥
)WE
(b⊥
;β,σ
)
q⊥ = 0.2 GeV
q⊥ = 2 GeV
q⊥ = 4 GeV
10−4 10−3 10−2 10−1 100
h
100
1
0.01
0.0001
%er
ror
(h)
17/25
How does this method compare with other numerical methods?
We benchmark against adaptive quadrature (quad)
10 20 30 40N
0.01
1
100
%er
ror
(N)
q⊥/Q = 0.1
quad
ogata
10 20 30 40N
q⊥/Q = 1
10 30 50 70 90N
q⊥/Q = 2
18/25
Does it work for real TMDs?
SIDIS COMPASS multiplicity given by
M(q⊥;x, z,Q) =π
z2
dσ
dxdydzd2q⊥
/dσ
dxdy,
We normalize the data so that at the first point in each bin the theory is equal tothe data
0 1 2 3
q⊥/Q
10−3
10−2
10−1
100
101
|M(q⊥
;x,z,Q
)|
Ogata
15 ≤ N ≤ 27
18 ≤ N ≤ 30
28 ≤ N ≤ 40
0 1 2 3
q⊥/Q
Quad
N = 65
N = 135
135 ≤ N ≤ 860
0 1 2 3
q⊥/Q
Vegas
231 ≤ N ≤ 263
602 ≤ N ≤ 657
3937 ≤ N ≤ 4054
Figure: Multiplicity for Ogata, quad, and Vegas Monte Carlo.
19/25
Application to Unpolarized SIDIS Continued
10−4
10−2
100
=⇒ Q2 =⇒
10−4
10−2
100
10−4
10−2
100 z =0.2
z =0.3
z =0.4
z =0.6
10−4
10−2
100
|M(q⊥
;x,z,Q
)|=⇒
x=⇒
0 2 4 610−4
10−2
100
0 1 2 3 410−4
10−2
100
0 1 2 3
q⊥/Q
10−4
10−2
100
0.0 0.5 1.0 1.5 2.0
Figure: Comparison of COMPASS multiplicities [?].
20/25
Back to Sivers!
Collaboration Scattering event Number of points Yeare+ P → e+ h+ 128 2017e+ P → e+ h− 128 2017e+ P → e+ h+ 23 2012e+ P → e+ h− 23 2012e+D → e+ π+ 23 2008e+D → e+ π− 23 2008e+D → e+K+ 23 2008e+D → e+K− 23 2008
π− +NH3 → γ∗ +X 15 2017e+ P → e+K− 19 2009e+ P → e+K+ 19 2009e+ P → e+ π0 19 2009e+ P → e+ π+ 19 2009e+ P → e+ π− 19 2009e+ P → e+ π+ 4 2011e+ P → e+ π− 4 2011P + P →W+ 8 2015P + P →W− 8 2015P + P → Z 1 2015
529 points in total, χ2/dof ≈ 1.4
21/25
COMPASS 2017: e− + Ps⊥ → e− + h−
128 points in total
−0.05
0.00
0.05
1 < Q2 < 4
z > 0.1
−0.05
0.00
0.05
AS
iver
sU
T
4 < Q2 < 6.25
−0.05
0.00
0.05
6.25 < Q2 < 16
0.25 0.50 0.75 1.00 1.25
p⊥
−0.05
0.00
0.05
16 < Q2 < 81
0.2 0.4 0.6
xB
0.2 0.4 0.6
zh
22/25
COMPASS P 2012 and JLab 2011
COMPASS 56 pointsJLab 8 points
−0.02
0.00
0.02
0.04
AS
iver
sU
T
h−
COMPASS Proton
0.2 0.4 0.6
p⊥
−0.02
0.00
0.02
0.04h+
0.0 0.1 0.2 0.3
xB
0.2 0.4 0.6 0.8
zh
xB
−0.2
0.0
0.2
AS
iver
sU
T
JLAB Proton
π−
0.15 0.20 0.25 0.30
xB
−0.2
0.0
0.2 π+
23/25
HERMES 2009
95 points
−0.05
0.00
0.05
0.10
K−
HERMES
−0.05
0.00
0.05
0.10
K+
−0.05
0.00
0.05
0.10
AS
iver
sU
T
π0
−0.05
0.00
0.05
0.10
π−
0.0 0.2 0.4 0.6
p⊥
−0.05
0.00
0.05
0.10
π+
0.0 0.1 0.2 0.3
xB
0.3 0.4 0.5 0.6
zh
24/25
Preliminary extraction for Sivers function
0.0 0.2 0.4 0.6 0.8x
−0.03
−0.02
−0.01
0.00
0.01
0.02
0.03
xf⊥
(1)
1T(x,Q
0)
Preliminary
u
d
25/25
Conclusion
• We generated an optimized Ogata method, highly numerically efficient
• The method can be used for global analysis
• Ogata algorithm will be available open source in the future
• We can use the NLO/NNLL parameterization to describe SIDIS Sivers data
• We hope to soon describe the DY and vector boson data
Thanks!!