- Generated by
1.12.0
|
HiRep 0.1
|
First we choose interpolating operators with the quantum numbers of the meson we would like to study:
\begin{equation}O_M = \bar{\psi}^{(1)}(x) \Gamma \psi^{(2)}(x)\end{equation}
\begin{equation}\bar{O}_M = \bar{\psi}^{(2)}(x) \bar{ \Gamma } \psi^{(1)}(x)\end{equation}
where \( \bar{ \Gamma } = \gamma_0 \Gamma^\dagger \gamma_0 \). The gamma matrix is chosen to have the same \( J^{PC} \) quantum numbers as the meson we want to create. We then calculate the expectation value to create a meson at \( y \) and destroy it again at \( x \) :
\begin{equation} \begin{aligned} \langle O_M(x) \bar{O}_M'(y) \rangle =& \langle \bar{\psi}^{(1)}(x) \Gamma \psi^{(2)}(x) \bar{\psi}^{(2)}(y) \bar{ \Gamma }' \psi^{(1)}(y) \rangle \\ =& \Gamma_{\alpha \beta} \bar{ \Gamma }'_{\gamma \delta} \langle \bar{\psi}^{(1)}_\alpha(x) \psi^{(2)}_\beta(y) \bar{\psi}^{(2)}_\gamma(y) \psi^{(1)}_\delta(x) \rangle \\ =& -\Gamma_{\alpha \beta} \bar{ \Gamma }'_{\gamma \delta} \langle \psi^{(2)}_\beta(x) \bar{\psi}^{(2)}_\gamma(y) \psi^{(1)}_\delta(y) \bar{\psi}^{(1)}_\alpha (x) \rangle \end{aligned} \label{eq:2ptcorr} \end{equation}
where the sign in the last line comes from exchanging the anticommuting \( \bar{\psi}_\alpha \) three times. Wick contracting where \( \langle \psi_\alpha(x) \bar{\psi}_\beta(y) \rangle = S_{\alpha \beta}(x,y) \) gives
\begin{equation}\begin{aligned} \langle O_M(x) \bar{O}_M'(y) \rangle =& -\Gamma_{\alpha \beta} S^{(2)}_{\beta \gamma} (x,y) \bar{ \Gamma }'_{\gamma \delta} S^{(1)}_{\delta \alpha} (y,x) \\ =& -\text{Tr}\left[ \Gamma S^{(2)} (x,y) \bar{ \Gamma }' S^{(1)} (y,x) \right]\end{aligned} \end{equation}
To get correlation functions we Fourier transform, ie. sum over all source and sink seperations while projecting onto the momentum we want to give to the particle:
\begin{equation}\begin{aligned} C(t - \tau, \vec{p}) =& \sum_{\vec{x} \vec{y}} e^{-i \vec{p}(\vec{x} - \vec{y}) } \langle O_M(\vec{x}, t) O_M'(\vec{y}, \tau)\rangle \\ =& -\sum_{\vec{x} \vec{y}} e^{-i \vec{p}(\vec{x} - \vec{y}) } \text{Tr}\left[ \Gamma S^{(2)} (x,y) \bar{ \Gamma }' S^{(1)} (y,x) \right]\end{aligned}\end{equation}
here \( x = (\vec{x}, t) \) and \( y = (\vec{y}, \tau) \) and the zero momentum correlator is:
\begin{equation}C(t - \tau, 0) = -\sum_{\vec{x} \vec{y}} \text{Tr}\left[ \Gamma S^{(2)} (x,y) \bar{ \Gamma }' S^{(1)} (y,x) \right]\end{equation}
We now use \( \gamma_5 \) Hermiticity: \( \gamma_5 S^\dagger(x,y) \gamma_5 = S(y,x) \),
\begin{equation}C(t - \tau, 0) = -\sum_{\vec{x} \vec{y}} \text{Tr}\left[ \gamma_5 \Gamma S^{(2)} (x,y) \bar{ \Gamma }' \gamma_5 S^{\dagger (1)} (x,y) \right]\label{eqn:corr}\end{equation}
Using a delta function source and solving the Dirac equation gives a point propagator,
\begin{equation}D_{\alpha a, \beta b} (x,y) S_{\beta b, \gamma c} (y, z) = \delta(x,z) \delta_{ac} \delta_{\alpha \gamma}\end{equation}
usually \( z = (\vec{0}, 0) \) so we get \( S(y,0) = \gamma_5 S^{\dagger} (0,y) \gamma_5 \). Then we use these to calculate correlation functions,
\begin{equation}C(t, 0) = -\sum_{\vec{x}} \text{Tr} e^{-i \vec{p} \vec{x}} \left[ \gamma_5 \Gamma S (x,0) \bar{ \Gamma }' \gamma_5 S (x,0) \right]\label{eqn:pointcorr}\end{equation}
Translational invariance in the limit of infinitely many gauge configurations implies \( S(x,y) = S(|x - y|) \), so the sum over \( \vec{y} \) in equation eq. \((\ref{eqn:corr})\) just gives \( V \) times equation eq. \((\ref{eqn:pointcorr})\). We place the source at the time origin so \( \tau = 0 \).
For this method it helps to write all the indices out,
\begin{equation}C(t - \tau, 0) = -\sum_{\vec{x} \vec{y}} (\gamma_5 \Gamma)_{\alpha \beta} S^{(2)}_{\beta\gamma,bc} (x,y) (\bar{ \Gamma }' \gamma_5)_{\gamma \delta} S^{\dagger (1)}_{\delta \alpha, cb} (x,y)\end{equation}
Greek indices \( \alpha, \beta, \gamma, \delta, ... \) are spinor indices and Latin indices \( a, b, c, d... \) are colour indices. The one-end trick involves inserting a delta function in colour, spin and space.
\begin{equation}C(t - \tau, 0) = -\sum_{\vec{x} \vec{y} \vec{z}} (\gamma_5 \Gamma)_{\alpha \beta} S^{(2)}_{\beta\gamma,b c} (\vec{x}, t; \vec{y}, \tau) \delta_{\gamma \lambda} \delta_{cd} \delta(\vec{y}, \vec{z}) (\bar{ \Gamma }' \gamma_5)_{\lambda \delta} S^{\dagger (1)}_{\delta \alpha, d b} (\vec{x}, t;\vec{z}, \tau)\end{equation}
The delta function is aproximated with a \( Z(2) \times Z(2) \) noise source on timeslice \( \tau \)
\begin{equation}\delta_{\gamma \lambda} \delta_{cd} \delta(\vec{y}, \vec{z}) \approx \frac{1}{K} \sum_{k = 0}^{K} | \eta^{(k)}_{\gamma c }(\vec{y})\rangle \langle \eta^{(k)}_{\lambda d }(\vec{z}) |\end{equation}
which is exact in the limit \( K \rightarrow \infty \).
\begin{equation} C(t - \tau, 0) = -\frac{1}{K} \sum_{k = 0}^{K} \sum_{\vec{x} \vec{y} \vec{z}} (\gamma_5 \Gamma)_{\alpha \beta} S^{(2)}_{\beta\gamma,b c} (\vec{x}, t; \vec{y}, \tau) | \eta^{(k)}_{\gamma c }(\vec{y})\rangle \langle \eta^{(k)}_{\lambda d }(\vec{z}) | (\bar{ \Gamma }' \gamma_5)_{\lambda \delta} S^{\dagger (1)}_{\delta \alpha, d b} (\vec{x}, t;\vec{z}, \tau)\label{eq:oet}\end{equation}
Defining
\begin{equation}\phi^{(k)}_{\beta, b}(\vec{x}, t; \tau) = \sum_{\vec{y}} S^{(2)}_{\beta\gamma,b c} (\vec{x}, t; \vec{y}, \tau) | \eta^{(k)}_{\gamma c }(\vec{y})\rangle\end{equation}
and
\begin{equation}\phi^{\Gamma (k)}_{\alpha, b}(\vec{x}, t; \tau) = \sum_{\vec{z}} S^{(1)}_{\alpha \delta , b d} (\vec{x}, t;\vec{z}, \tau) (\bar{ \Gamma }' \gamma_5)^{\dagger}_{\delta \lambda} | \eta^{(k)}_{\lambda d }(\vec{z}) \rangle\end{equation}
the correlator can be evaluated as,
\begin{equation}C(t - \tau, 0) = -\frac{1}{K} \sum_{k = 0}^{K} \sum_{\vec{x} } (\gamma_5 \Gamma)_{\alpha \beta} \phi^{(k)}_{\beta, b}(\vec{x}, t; \tau) \phi^{\Gamma \dagger (k)}_{\alpha, b}(\vec{x}, t; \tau)\end{equation}
In HiRep the code Spectrum/mk_mesons_with_z2semwall.c does two solves to calculate \( S^{(1)} | \eta \rangle \) and \( S^{(2)} (\bar{ \Gamma }' \gamma_5)^{\dagger} | \eta \rangle \). HiRep has
\begin{equation}\rho = \rho_{ c }(\vec{y})\end{equation}
a \( Z(2) \times Z(2) \) colour vector at all (even) spatial sites \( \vec{y} \) and non-zero only on timeslice \( \tau \).
\begin{equation}\rho^{\alpha}_\beta = \delta_{\alpha \beta} \rho^\alpha\end{equation}
eg.
\begin{equation}\rho^1_\beta = \left( \begin{matrix} 0 \\ \rho^1 \\ 0 \\ 0 \end{matrix} \right)\end{equation}
It then solves for the four objects
\begin{equation}\chi^\alpha_\beta = S_{\beta \gamma} \rho^{\alpha}_\gamma\end{equation}
eg.
\begin{equation}\chi^0_\beta = \left( \begin{matrix} S_{00} \rho^0 \\ S_{10} \rho^0 \\ S_{20} \rho^0 \\ S_{30} \rho^0 \end{matrix} \right)\end{equation}
For every different \( \Gamma \) that is required it does four more inversions,
\begin{equation}\chi^{\Gamma \alpha}_\beta = S_{\beta \gamma} (\Gamma \gamma_5)^\dagger_{\gamma \delta} \rho^{\alpha}_\delta\end{equation}
before calculating the correlator as,
\begin{equation}C(t - \tau, 0) = -\frac{1}{K} \sum_{k = 0}^{K} \sum_{\lambda = 0}^{3}\sum_{\vec{x} } (\gamma_5 \Gamma)_{\alpha \beta} \chi^{\lambda}_{\beta, b}(\vec{x}, t; \tau) \chi^{\Gamma \lambda \dagger}_{\alpha, b}(\vec{x}, t; \tau)\end{equation}
where the \( \lambda \) sum is over the \( 4 \) spinor components.
We should be able to improve the signal and reduce the number of inversions with two modifications. First, instead of having a different noise vector for every spin component we reuse the same noise, i.e.
\begin{equation}\rho^{\alpha}_\beta = \delta_{\alpha \beta} \rho\end{equation}
for fixed \( \rho \). Using less noise seems to be generally preferred.
Secondly there is no need to invert for every different \( \Gamma \). Let,
\begin{equation}\chi^{\Gamma \alpha}_\beta = (\Gamma \gamma_5)^\dagger_{\gamma \alpha} \chi^{\gamma}_\beta\end{equation}
This is true because,
\begin{equation}(\Gamma \gamma_5)^\dagger_{\gamma \alpha} \chi^{\gamma}_\beta = (\Gamma \gamma_5)^\dagger_{\gamma \alpha} S_{\beta \delta} \rho^{\gamma}_\delta = (\Gamma \gamma_5)^\dagger_{\gamma \alpha} S_{\beta \delta} \delta_{\gamma \delta} \rho = (\Gamma \gamma_5)^\dagger_{\gamma \alpha} S_{\beta \gamma} \rho = S_{\beta \gamma} (\Gamma \gamma_5)^\dagger_{\gamma \alpha} \rho\end{equation}
then the correlation function is
\begin{equation}C(t - \tau, 0) = -\frac{1}{K} \sum_{k = 0}^{K} \sum_{\lambda = 0}^{3}\sum_{\vec{x} } (\gamma_5 \Gamma)_{\alpha \beta} \chi^{\lambda}_{\beta, b}(\vec{x}, t; \tau) \chi^{\Gamma \lambda \dagger}_{\alpha, b}(\vec{x}, t; \tau)\end{equation}
as before. By using the spin_matrix object in HiRep to construct the objects \( \chi^{\lambda}_{\beta, b} \) the correlators can be calculated with only \( 4 N_F \) inversions.
The disconnected contributions occur when we have fermion species of the same type in the hadron interpolator \( O_M \) :
\begin{equation}O_M(x) = \bar{ \psi } (x) \Gamma \psi(x)\end{equation}
The same manipulations that lead to equation eq. \((\ref{eq:2ptcorr})\) give,
\begin{equation}\langle O_M(x) \bar{O}_M'(y) \rangle = \langle \bar{\psi}(x) \Gamma \psi(x) \bar{\psi}(y) \bar{ \Gamma }' \psi(y) \rangle = \Gamma_{\alpha \beta} \bar{ \Gamma }'_{\gamma \delta} \langle \bar{\psi}_\alpha(x) \psi_\beta(y) \bar{\psi}_\gamma(y) \psi_\delta(x) \rangle\end{equation}
There are two allowed Wick contractions,
\begin{equation}\langle O_M(x) \bar{O}_M'(y) \rangle = -\text{Tr}\left[ \Gamma S (x,y) \bar{ \Gamma }' S (y,x) \right] + \text{Tr}\left[ \Gamma S (x,x) \right] \text{Tr} \left[ \bar{ \Gamma }' S (y,y) \right]\end{equation}
the connected and disconnected contributions. Fourier transforming the first term gives us the same result as before. For the disconnected part,
\begin{equation}\begin{aligned} D(t - \tau, \vec{p}) = \sum_{\vec{x} \vec{y}} e^{-i \vec{p} (\vec{x} - \vec{y} )} \text{Tr}\left[ \Gamma S (x,x) \right] \text{Tr} \left[ \bar{ \Gamma }' S (y,y) \right]\end{aligned}\end{equation}
again \( x = (\vec{x}, t) \) and \( y = (\vec{y}, \tau) \), the zero-momentum correlator is
\begin{equation}D(t - \tau, 0) = \sum_{\vec{x} \vec{y}} \text{Tr}\left[ \Gamma S (x,x) \right] \text{Tr} \left[ \bar{ \Gamma }' S (y,y) \right] = \sum_{\vec{x}} \text{Tr}\left[ \Gamma S (x,x) \right] \sum_{\vec{y}} \text{Tr} \left[ \bar{ \Gamma }' S (y,y) \right]\,.\end{equation}
This means we have to evaluate objects like
\begin{equation}\begin{aligned} d(t) = \sum_{\vec{x}} \text{Tr}\left[ \Gamma S (x,x) \right] = \sum_{\vec{x}} \Gamma_{\alpha \beta} S_{\beta \alpha}(x,x)\,,\end{aligned}\end{equation}
using
\begin{equation}\phi^{(k)}_{\beta, b}(\vec{x}, t; \tau) = \sum_{\vec{y}} S_{\beta\gamma,b c} (\vec{x}, t; \vec{y}, \tau) | \eta^{(k)}_{\gamma c }(\vec{y})\rangle\,,\end{equation}
which implies
\begin{equation}\begin{aligned} \frac{1}{K} \sum_{k}^K \sum_{\vec{x}} \text{Tr} \left[ \langle \eta^{(k)}(\vec{x}) | \Gamma | \phi^{(k)} (\vec{x}, t; \tau) \rangle \right] =& \frac{1}{K} \sum_{k}^K \sum_{\vec{x}} \Gamma_{\beta \gamma} | \phi^{(k)}_{\gamma, b}(\vec{x}, t; \tau) \rangle \langle \eta^{(k)}_{\beta b }(\vec{x}) | \\ =& \frac{1}{K} \sum_{k}^K \sum_{\vec{x}} \Gamma_{\beta \gamma} \sum_{\vec{y}} S_{\gamma \alpha,b c} (\vec{x}, t; \vec{y}, \tau) | \eta^{(k)}_{\alpha c }(\vec{y})\rangle \langle \eta^{(k)}_{\beta b }(\vec{x}) |\end{aligned} \end{equation}
Using the limit \( K \rightarrow \infty \) this becomes,
\begin{equation}\sum_{\vec{x}} \Gamma_{\beta \gamma} \sum_{\vec{y}} S_{\gamma \alpha,b c} (\vec{x}, t; \vec{y}, \tau) \delta_{bc} \delta_{\alpha \beta} \delta(\vec{y}, \vec{x}) = \sum_{\vec{x}} \Gamma_{\beta \gamma} S_{\gamma \beta,b b} (\vec{x}, t; \vec{x}, \tau)\,,\end{equation}
\begin{equation}d(t, \tau) = \text{Tr} \left[ \Gamma S(\vec{x}, t; \vec{x}, \tau) \right]\,.\end{equation}
We want only cases where \( t = \tau \) so we need either four noise vectors on every timeslice or noise vectors that are nonzero on all timeslices. In the latter case we would evaluate,
\begin{equation}\begin{aligned}\frac{1}{K} \sum_{k}^K \sum_{\vec{x}} \text{Tr} \left[ \langle \eta^{(k)}(\vec{x}, t) | \Gamma | \phi^{(k)} (\vec{x}, t) \rangle \right] \end{aligned}\end{equation}
with
\begin{equation}\phi^{(k)}_{\beta, b}(\vec{x}, t) = \sum_{\vec{y}} S_{\beta\gamma,b c} (\vec{x}, t; \vec{y}, \tau) | \eta^{(k)}_{\gamma c }(\vec{y}, \tau)\,.\rangle\end{equation}
The two-point function evaluated in the center of the lattice is (including the backward propagating part to give the extra factor of $2$),
\begin{equation}C(T/2, \vec{p}) = \frac{ |Z_\pi|^2 }{ 2 E_\pi(\vec{p}) } 2 e^{- E_\pi(\vec{p}) (T/2) }\end{equation}
therefore
\begin{equation}\frac{1}{2} C(T/2, \vec{p}) e^{ - E_\pi(\vec{p}) (T/2 - t) } = \frac{ |Z_\pi|^2 }{ 2 E_\pi(\vec{p}) } e^{- E_\pi(\vec{p}) (T - t) }\end{equation}
then
\begin{equation}C_{\rightarrow}(t, \vec{p}) = C(t, \vec{p}) - \frac{1}{2} C(T/2, \vec{p}) e^{ - E_\pi(\vec{p}) (T/2 - t) }\end{equation}
is the forward propagating part only. \( E_\pi(\vec{p}) \) is obtained by fitting the zero momentum correlator and using \( E(\vec{p}) = \sqrt{m_\pi^2 + \vec{p}^2} \). The factor \( C(T/2, \vec{p}) \) can be obtained also from the zero momentum correlator, by fitting to obtain \( |Z_\pi|^2 \) and using the fact that this is momentum independent. Since \( 0 \) momentum results are used this might not be too noisy.
Alternatively the Wilson action is invariant under
\begin{equation}\begin{aligned}\psi(x) \rightarrow {\cal P_\mu}[ \psi(x) ] = \gamma_\mu \psi( P_\mu[x]) \\ \bar{ \psi } (x) \rightarrow {\cal P_\mu}[ \bar{ \psi } (x) ] = \bar{ \psi }( P_\mu[x]) \gamma_\mu \end{aligned}\end{equation}
where \( P_\mu[x] \) reverses the sign of all the components of \( x \) except the \( \mu \) one. Time reversal corresponds to \( {\cal T} = {\cal P}_1{\cal P}_2{\cal P}_3 \).
\begin{equation}\begin{aligned}\psi(x) \rightarrow {\cal T}[ \psi(x) ] = \gamma_0 \gamma_5 \psi( T[x]) \\ \bar{ \psi } (x) \rightarrow {\cal T}[ \bar{ \psi } (x) ] = \bar{ \psi }( T[x]) \gamma_5 \gamma_0 \end{aligned}\end{equation}
Using this the T symmetry of operators used to construct the correlators can be calculated to calculate the sign on the backwards propagating part.
\begin{equation}\langle O_1(t) O_2(0) \rangle = C(t) = A \left( e^{ -Et} + \tau_1 \tau_2 e^{-E(T - t)}\right)\end{equation}
Here \( \tau_i = \pm 1 \) is the \( {\cal T} \) eigenvalue of \( O_i \). We mostly use correlators where \( O_1 = O_2 \) so \( \tau_1 \tau_2 = 1 \) then the correlator is
\begin{equation}C_{pp}(t, \vec{p}) = \frac{ |Z_\pi|^2 }{ 2 E_\pi(\vec{p}) } \left( e^{- E_\pi(\vec{p})t } + e^{- E_\pi(\vec{p})(T - t) } + e^{- E_\pi(\vec{p})(2T - t) } + \ldots \right)\end{equation}
The subscript on \( C_{pp} \) refers to the fact that both propagators used periodic boundary conditions. We want to cancel the backwards propagating part which can be done by solving the forward propagator \( S(0,x) \) using antiperiodic time bc's and the backward \( S(x,0) \) with periodic time bc's to give an extra minus sign,
\begin{equation}C_{ap}(t, \vec{p}) = \frac{ |Z_\pi|^2 }{ 2 E_\pi(\vec{p}) } \left( e^{- E_\pi(\vec{p})t } - e^{- E_\pi(\vec{p})(T - t) } + e^{- E_\pi(\vec{p})(2T - t) } - \ldots \right)\end{equation}
so,
\begin{equation}C_{ap}(t, \vec{p}) + C_{p}(t, \vec{p}) = \frac{ 2 |Z_\pi|^2 }{ 2 E_\pi(\vec{p}) } \left( e^{- E_\pi(\vec{p})t } + e^{- E_\pi(\vec{p})(2T - t) } + \ldots \right)\end{equation}
cancelling the subleading exponential. This method requires two inversions and the calculation of
\begin{equation}S_{A \pm P} (x,y) = S_A(x,y) \pm S_P(x,y)\end{equation}
Where the subscript refers to (A)ntiperiodic/(P)eriodic boundary conditions. Then,
\begin{equation}C_{\pm}(t - \tau, 0) = -\sum_{\vec{x} \vec{y}} \text{Tr}\left[ \gamma_5 \Gamma S_{A \pm P} (x,y) \bar{ \Gamma }' \gamma_5 S_{A \pm P} (x,y) \right]\end{equation}
where \( C_{+}(t - \tau, 0) \) gives the forward propagating part from \( 0 \) to \( T \) and \( C_{-}(t - \tau, 0) \) gives the backwards propagating part from \( 2T \) to \( T \).
The electromagnetic form factor of a 'pion' requires the evaluation of the matrix element
\begin{equation}\langle \pi(p_f) | V_\mu | \pi(p_i) \rangle = (p_i + p_f)_\mu f(q^2)\end{equation}
where \( q^2 = (p_i - p_f)^2 \) and
\begin{equation}V_\mu = q_u \bar{u} \gamma_\mu u + q_d \bar{d} \gamma_\mu d\end{equation}
is the electromagnetic current and \( q_i \) is the charge of the fermion \( i \). This is the local (not conserved) current, so there will be a factor \( Z_V \) for renormalization. The matrix elements required look like:
\begin{equation}\begin{aligned} C_3(t_f,t,t_i,\vec{p_i}, \vec{p_f}) = Z_V \sum_{\vec{x} \vec{y} \vec{z}} e^{-i\vec{p_f}(\vec{x} - \vec{y}) } e^{i\vec{p_i} (\vec{y} - \vec{z)}}\langle 0 | \bar{u} \gamma_5 d ( \vec{x}, t_f) V_0(\vec{y}, t) \bar{d} \gamma_5 u (\vec{z}, t_i) | 0 \rangle\end{aligned}\end{equation}
We take the \( \mu = 0 \) component since this is statistically cleaner and also nonzero independent of the momentum direction. The contractions give three propagators eg. taking the \( \bar{d} \gamma_\mu d \) part of \(V_\mu \),
\begin{equation}\begin{aligned} Z_V \sum_{\vec{x} \vec{y} \vec{z}} e^{-i\vec{p_f}(\vec{x} - \vec{y}) } e^{-i\vec{p_i} (\vec{y} - \vec{z} ) } Tr \left[ S_u(\vec{z},t_i;\vec{x},t_f) \gamma_5 S_d(\vec{x},t_f;\vec{y},t) \gamma_0 S_d(\vec{y},t;\vec{z},t_i) \gamma_5 \right]\end{aligned}\end{equation}
There are also disconnected contributions from contracting the two fermions in the current together but we ignore those. The usual sequential source trick consists of solving
\begin{equation}S_u(\vec{x}, t; \vec{z}, t_i) = \sum_{\vec{y},\tau} D_u ( \vec{x}, t; \vec{y},\tau) \delta(\vec{y}, \tau; \vec{z}, t_i)\end{equation}
to get the point-to-all propagator (for a specific \( \vec{z} \) and \( t_i \) as well as dropping the sum over \( \vec{z} \) and using translational invariance). Then taking a single timeslice of the propagator \( S_u(\vec{x}, t_f; \vec{z}, t_i) \) and solving,
\begin{equation}D_d ( \vec{x},t_f; \vec{y}, t ) G_{du}(\vec{y}, t; \vec{p_f}; t_f; \vec{z}, t_i) = e^{i\vec{p_f} \vec{x}} \gamma_5 S_u(\vec{x}, t_f; \vec{z}, t_i)\end{equation}
\begin{equation}G_{du}(\vec{y}, t; \vec{p_f}; t_f; \vec{z}, t_i) = \sum_{ \vec{x} } e^{i\vec{p_f} \vec{x}} S_d(\vec{y},t; \vec{x}, t_f ) \gamma_5 S_u(\vec{x}, t_f; \vec{z}, t_i)\end{equation}
to get the all-to-all-to-point contribution. Then
\begin{equation}\begin{aligned}\gamma_5 \left[ G_{du}(\vec{y}, t; \vec{p_f}; t_f; \vec{z}, t_i) \right]^\dagger \gamma_5 =& \sum_{ \vec{x} } e^{-i\vec{p_f} \vec{x}} \gamma_5 S_u^\dagger (\vec{x}, t_f;\vec{y},t ) \gamma_5 \gamma_5 \gamma_5 \gamma_5 \gamma_5 S_d^\dagger (\vec{z}, t_i;\vec{x}, t_f) \gamma_5 \\ =& \sum_{ \vec{x} } e^{-i\vec{p_f} \vec{x}} S_u (\vec{z}, t_i;\vec{x}, t_f) \gamma_5 S_d (\vec{x}, t_f;\vec{y},t ) \\ =& G_{ud}(\vec{z}, t_i; t_f; \vec{p_f}; \vec{y}, t )\end{aligned}\end{equation}
\begin{equation}\begin{aligned} C_3(t_f,t,t_i, \vec{p_i}, \vec{p_f}) = Z_V \sum_{\vec{y} } e^{-i(\vec{p_i} - \vec{p_f})\vec{y}} Tr \left[ G_{ud}(\vec{z}, t_i; t_f; \vec{p_f}; \vec{y}, t ) \gamma_0 S_d(\vec{y},t;\vec{z},t_i) \gamma_5 \right]\end{aligned}\label{eq:3ptfn}\end{equation}
This \( Z_V \) factor is unknown. We show how to calculate it later, or cancel it, but an alternative is to use the conserved vector current in place of the local current
\begin{equation}V_\mu = \frac{1}{2} \left[ \bar{\psi}(x + \mu)(1 + \gamma_\mu)U_\mu^\dagger(x) \psi(x) - \bar{\psi}(x)(1 - \gamma_\mu)U_\mu^\dagger(x) \psi(x + \mu) \right]\,.\end{equation}
The trace in eq. \((\ref{eq:3ptfn})\) becomes
\begin{equation}\begin{aligned}Tr[ S_d(\vec{y},t+1;\vec{z},t_i) &\gamma_5 (1 + \gamma_0)U_0^\dagger(\vec{y},t) G_{ud}(\vec{z}, t_i; t_f; \vec{p_f}; \vec{y}, t ) -\\ &S_d(\vec{y},t;\vec{z},t_i) \gamma_5 (1 - \gamma_0)U_0(\vec{y},t) G_{ud}(\vec{z}, t_i; t_f; \vec{p_f}; \vec{y}, t+1 ) ]\end{aligned}\end{equation}
If we use this then all the following formulas are the same except \( Z_V \rightarrow 1 \).
There is an alternative that doesn't require the sequential source trick. Using the properties of our noise sources
\begin{equation}S_d(\vec{x},t_f;\vec{y},t) \approx \frac{1}{K} \sum_{i=0}^K | \psi^{(i)}(\vec{x},t_f) \rangle \langle \eta^{(i)}(\vec{y},t) |\end{equation}
the three point correlation function becomes
\begin{equation}\begin{aligned} Z_V \frac{1}{K} \sum_{i=0}^K \sum_{\vec{x} \vec{y} } e^{-i\vec{p_f}(\vec{x} - \vec{y}) } e^{i\vec{p_i} \vec{y}} Tr \left[ \langle \eta^{(i)}(\vec{y},t) | \gamma_0 S_d(\vec{y},t;\vec{0},0) \gamma_5 S_u(\vec{0},0;\vec{x},t_f) \gamma_5 | \psi^{(i)}(\vec{x},t_f) \rangle \right] \\ Z_V \frac{1}{K} \sum_{i=0}^K \sum_{\vec{x} \vec{y} } e^{-i\vec{p_f}(\vec{x} - \vec{y}) } e^{i\vec{p_i} \vec{y}} Tr \left[ \langle \eta^{(i)}(\vec{y},t) | \gamma_0 S_d(\vec{y},t;\vec{0},0) S_u^{\dagger}(\vec{x},t_f;\vec{0},0) | \psi^{(i)}(\vec{x},t_f) \rangle \right]\end{aligned}\end{equation}
Using this method we can inject arbitrary momentum at the source without the need for extra inversions.
A complete set of hadrons is given by,
\begin{equation}\sum_n \frac{ | n \rangle \langle n |}{ 2 E_n V}\end{equation}
the first term is the pion. The two-point function (from point sources) is,
\begin{equation}C(t, \vec{p}) = \sum_{\vec{x}} e^{-i \vec{p} \vec{x}} \langle O_\pi (\vec{x}, t) O^\dagger_\pi (\vec{0}, 0)\rangle = \sum_{\vec{x}} \sum_n e^{i \vec{p} \vec{x}} \frac{ \langle 0 | O_\pi (\vec{x}, t) | n \rangle \langle n | O^\dagger_\pi (\vec{0}, 0)| 0 \rangle }{ 2 E_n }\end{equation}
Use \( \sum_{ \vec{y} } e^{-i\vec{p} \vec{y}} O^\dagger_n (\vec{y}, 0) | 0 \rangle = | n(\vec{p}) \rangle \), the time evolution operator \( e^{-Ht} \) and also the fact that the lightest meson dominates the sum to get
\begin{equation}\begin{aligned} C(t, \vec{p}) &=& \sum_{\vec{x} \vec{y} \vec{z}} \sum_{\vec{p'} } e^{-i \vec{p} \vec{x}} \frac{ \langle 0 | O_\pi (\vec{x}, 0) O^\dagger_\pi (\vec{y}, 0) e^{i \vec{p'} \vec{y} } | 0 \rangle \langle 0 | e^{i \vec{p'} \vec{z} } O_\pi (\vec{z}, 0) O^\dagger_\pi (\vec{0}, 0)| 0 \rangle }{ 2 E_\pi(\vec{p'}) } e^{- E_\pi(\vec{p'}) t }\end{aligned}\end{equation}
The sum over \( \vec{p'} \) gives a delta function leaving
\begin{equation}\begin{aligned} C(t, \vec{p}) &=& \sum_{\vec{x} \vec{y} } e^{-i \vec{p} \vec{x}} \frac{ \langle 0 | O_\pi (\vec{x}, 0) O^\dagger_\pi (\vec{y}, 0) | 0 \rangle \langle 0 | O_\pi (\vec{y}, 0) O^\dagger_\pi (\vec{0}, 0) | 0 \rangle }{ 2 E_\pi(\vec{p}) } e^{- E_\pi(\vec{p}) t }\end{aligned}\end{equation}
Translational invariance lets us write
\begin{equation}\begin{aligned} C(t, \vec{p}) &=& \sum_{\vec{x} \vec{y} } e^{-i \vec{p} ( \vec{x} - \vec{y} ) } e^{ -i \vec{p} \vec{y} } \frac{ \langle 0 | O_\pi (\vec{0}, 0) O^\dagger_\pi (\vec{x}-\vec{y}, 0) | 0 \rangle \langle 0 | O_\pi (\vec{y}, 0) O^\dagger_\pi (\vec{0}, 0)| 0 \rangle }{ 2 E_\pi(\vec{p}) } e^{- E_\pi(\vec{p}) t }\end{aligned}\end{equation}
Now changing variables gives us two Fourier transforms
\begin{equation}\begin{aligned} C(t, \vec{p}) =& \frac{ \langle 0 | O_\pi (\vec{0}, 0) | \pi(p) \rangle \langle \pi(p) | O^\dagger_\pi (\vec{0}, 0)| 0 \rangle }{ 2 E_\pi(\vec{p}) } e^{- E_\pi(\vec{p}) t }\end{aligned}\end{equation}
and finally using the time evolution operator we get
\begin{equation}\begin{aligned} C(t, \vec{p}) =& \frac{ |Z_\pi|^2 }{ 2 E_\pi(\vec{p}) } e^{- E_\pi(\vec{p}) t }\end{aligned}\end{equation}
where
\begin{equation}Z_\pi = \langle \pi(p) | O^\dagger_\pi (\vec{0}, 0)| 0 \rangle\end{equation}
In less detail we insert two complete sets of states into the correlator ( point sources so \( (\vec{x_i}, t_i) = (\vec{0}, 0) \) )
\begin{equation}\begin{aligned}\langle \pi(p_f) | V_\mu | \pi(p_i) \rangle &=\, \langle 0| O(\vec{p_f}, t_f) V_\mu(\vec{x}, t) O^\dagger(\vec{p_i}, t_i) |0\rangle \\ &=\, \langle 0| O(\vec{0}, 0) | \pi(\vec{p_f}) \rangle \frac{e^{-(t_f - t) E_\pi(\vec{p_f}) }}{2 E_\pi(\vec{p_f}) } \langle \pi(\vec{p_f}) | V_\mu(\vec{0}, 0) | \pi(\vec{p_i}) \rangle \times \frac{e^{-(t - t_i) E_\pi(\vec{p_i}) }} {2 E_\pi(\vec{p_i}) } \langle \pi(\vec{p_i}) | O^\dagger(\vec{0}, 0) |0 \rangle \\ \nonumber &=\, \frac{ Z_{\pi, f}^\dagger Z_{\pi, i} }{4 E(\vec{p_f}) E(\vec{p_i}) } \langle \pi(\vec{p_f}) | V_\mu(\vec{0}, 0) | \pi(\vec{p_i}) \rangle e^{-(t_f - t) E_\pi(\vec{p_f}) -(t-t_i) E_\pi(\vec{p_i}) }\end{aligned}\end{equation}
if \( t < t_f \) we have the backwards contribution and the exponential changes to
\begin{equation}-e^{-(t - t_f) E_\pi(\vec{p_f}) -(T - t + t_i) E_\pi(\vec{p_i}) }\end{equation}
\( Z_V \) can be obtained as follows: The ratio,
\begin{equation}\begin{aligned}\frac{ C_{\rightarrow}(t_f, \vec{0}) }{ C_3(t_f, t, \vec{p_i}, \vec{p_f}) } =& \frac{ \frac{ |Z_\pi( \vec{0} )|^2 }{ 2 m_\pi } e^{- m_\pi t_f } }{ \frac{ |Z_\pi( \vec{0} )|^2 }{4 m_\pi^2 } \langle \pi(\vec{0}) | V_\mu | \pi(\vec{0}) \rangle e^{-(t_f - t) m_\pi -t m_\pi } } \\ =& \frac{ 1 }{ \frac{ 1 }{2 m_\pi } \langle \pi(\vec{0}) | V_\mu | \pi(\vec{0}) \rangle } \\ =& \frac{ 1 }{ \frac{ 1 }{2 m_\pi } 2 m_pi f(0)/Z_V } = Z_V.\end{aligned}\end{equation}
Where we used that the renormalized form factor \( f(0) = 1 \)
There are various ways to cancel the unwanted terms and get \( f(q) \).
We examine the ratio,
\begin{equation}2 m_\pi \frac{ C_{3} (t, t_f, \vec{p}, \vec{0} ) C_{\rightarrow}(t, \vec{0}) }{ C_{3} (t, t_f, \vec{0}, \vec{0} ) C_{\rightarrow}(t, \vec{p}) }\end{equation}
Assuming \( Z_\pi \) is momentum independent. This also works if \( Z_\pi = E(\vec{p}) f_\pi \), which is the case for \( O = \bar{u} \gamma_0 \gamma_5 d \) type interpolators. The numerator is,
\begin{equation}\frac{ Z_V |Z_\pi|^2 }{ 4 E(\vec{p}) E(\vec{0})} f(q^2) ( E(\vec{p}) + m_\pi ) \frac{|Z_\pi|^2}{2 E(\vec{0})} e^{ -E(\vec{p})t - E(\vec{0})(t_f - t) -E(\vec{0})t }\end{equation}
and the denominator is,
\begin{equation}\frac{ Z_V |Z_\pi|^2 }{ 4 E(\vec{0}) E(\vec{0})} f(0) ( m_\pi + m_\pi ) \frac{|Z_\pi|^2}{2 E(\vec{p})} e^{ -E(\vec{0})t - E(\vec{0})(t_f - t) -E(\vec{p})t }\end{equation}
Cancelling leaves,
\begin{equation}2 m_\pi \frac{ C_{3} (t, t_f, \vec{p}, \vec{0} ) C_{\rightarrow}(t, \vec{0}) }{ C_{3} (t, t_f, \vec{0}, \vec{0} ) C_{\rightarrow}(t, \vec{p}) } = f(q^2) ( E(\vec{p}) + m_\pi )\end{equation}
note there is no \( Z_V \) here.
\begin{equation}\frac{2 Z_V m_\pi}{E(\vec{p}) + m_\pi} \frac{ C_{3} (t, t_f, \vec{p}, \vec{0} ) C_{\rightarrow}(t, \vec{0}) }{ C_{\rightarrow} (t, \vec{p} ) C_{\rightarrow}(t_f, \vec{0}) }\end{equation}
the numerator of the right term is,
\begin{equation}\frac{ |Z_\pi|^2 }{ 4 E(\vec{p}) m_\pi} f_B(q^2) ( E(\vec{p}) + m_\pi ) \frac{|Z_\pi|^2}{2 m_\pi} e^{ -E(\vec{p})t - m_\pi(t_f - t) -m_\pi t }\end{equation}
the denominator of the right term is,
\begin{equation}\frac{ |Z_\pi|^2 }{ 2 m_\pi } \frac{|Z_\pi|^2}{2 E(\vec{p})} e^{ -m_\pi t - m_\pi (t_f - t) -E(\vec{p})t }\end{equation}
Cancelling leaves,
\begin{equation}\frac{ f_B(q^2) ( E(\vec{p}) + m_\pi ) }{ 2 E(\vec{p}) }\end{equation}
the kinematic factors are cancelled
\begin{equation}\frac{2 Z_V m_\pi}{E(\vec{p}) + m_\pi} \frac{ f_B(q^2) ( E(\vec{p}) + m_\pi ) }{ 2 E(\vec{p}) } = Z_V f_B(q^2) = f(q^2)\end{equation}
you need to actually know \( Z_V \) or use the conserved current.
We choose the hermitian basis of gamma matrices given in Tab. 1. Each element of the basis is referred by an index in [0,15] shown in the following table
| No | Matrix |
|---|---|
| 0 | \( \gamma_5 \) |
| 1 | \( \gamma_1 \) |
| 2 | \( \gamma_2 \) |
| 3 | \( \gamma_3 \) |
| 4 | \( -\mathrm{i}\gamma_0\gamma_5 \) |
| 5 | \( -\mathrm{i}\gamma_0\gamma_1 \) |
| 6 | \( -\mathrm{i}\gamma_0\gamma_2 \) |
| 7 | \( -\mathrm{i}\gamma_0\gamma_3 \) |
| 8 | 1 |
| 9 | \( -\mathrm{i}\gamma_5\gamma_1 \) |
| 10 | \( -\mathrm{i}\gamma_5\gamma_2 \) |
| 11 | \( -\mathrm{i}\gamma_5\gamma_3 \) |
| 12 | \( \gamma_0 \) |
| 13 | \( -\mathrm{i}\gamma_5\gamma_0\gamma_1 \) |
| 14 | \( -\mathrm{i}\gamma_5\gamma_0\gamma_2 \) |
| 15 | \( -\mathrm{i}\gamma_5\gamma_0\gamma_3 \) |
Consider a gauge theory on a group G coupled to \( N_f \) fermions in an arbitrary representation \( R \). Let us denote:
\begin{equation}C(t, x_0) = \dfrac{1}{N_f}\sum_{\vec{x}}\langle \bar{q}\Gamma q(x)\bar{q}\Gamma q(x_0)\rangle\end{equation}
where \( q \), \(\bar{q} \) are the \( N_f \) quark fields and \( \Gamma \) denotes as arbitrary Dirac structure. The \( 1/N_f \) factor is only there for convenience. The Wick contractions read:
\begin{equation}C(t, x_0) = \sum_{\vec{x}} \langle -\mathrm{tr}\left(\Gamma S(x,x_0)\Gamma S(x_0,x)\right) + N_f\,\mathrm{tr}\left(\Gamma S(x,x)\right)\mathrm{tr}\left(\Gamma S(x_0,x_0)\right)\rangle\end{equation}
The simple one consist to evaluate stochastically the disconnected contribution without any variance reduction techniques. Considering a general volume source \( \xi \), we define \( \phi \) using the Dirac operator \( D \) :
\begin{equation}\phi = D^{-1}\xi\end{equation}
For a given element X of the basis defined in the previous section, we then have
\begin{equation}\sum \left(\xi^{*}X\phi\right)_{R} = \sum XM^{-1} + \text{noise}\end{equation}
where the symbol \( (\ldots)_{R} \) refers to the average over R samples of the stochastic source.
It should be observed that in evaluating the disconnected contributions to the neutral meson correlators each one of the two quark loops arising from Wick contractions must be averaged over completely independent samples of stochastic sources for the purpose of avoiding unwanted biases.
TODO: XX We use XX noise sources. The user can switch between the following different source types
The code does not perform any average on the stochastic noise or on the dilution indices. This allows to keep as much information as possible and to vary the number of stochastic sources at the analysis level.
The indices are always
TODO: Notation
#T #iGamma #iSrc #\[color and/or e/o \] #Re #Im
where iGamma refers to the index of the Gamma matrix defined in Table 1.
If the code is executed with the following additional arguments
This will read the two files and perform the contraction accordingly computing \( \chi^{\dagger}\Gamma \psi \).
The two fermionic flavors are denoted by \( u \) and \( d \). We are interested in the mesonic correlators
\begin{equation}\begin{aligned} && C_{\Gamma_1,\Gamma_2}(x-y) = \left< \left( \bar{u} \Gamma_1 d \right)^\dagger(x) \left( \bar{u} \Gamma_2 d \right)(y) \right> = \nonumber \\ && \quad = \left< \left( \bar{d} \gamma_0 \Gamma_1^\dagger \gamma_0 u \right)(x) \left( \bar{u} \Gamma_2 d \right)(y) \right>\end{aligned}\end{equation}
where \( \Gamma_i \) are the generic products of the \( \gamma\)-matrices.
We can integrate out the fermionic fields explicitly. Here we use the definition \( H(x,y) = G(x,y) \gamma_5 \) for the hermitian Dirac operator, with \( G(x,y) \) defined as its inverse.
\begin{equation}\begin{aligned} && C_{\Gamma_1,\Gamma_2}(x-y) = - \left< \mathrm{tr} \left[ \gamma_0 \Gamma_1^\dagger \gamma_0 G(x,y) \Gamma_2 G(y,x) \right] \right> = \nonumber \\ && \quad = - \left< \mathrm{tr} \left[ \gamma_0 \Gamma_1^\dagger \gamma_0 G(x,y) \Gamma_2 \gamma_5 G(x,y)^\dagger \gamma_5 \right] \right> = \nonumber \\ && \quad = - \left< \mathrm{tr} \left[ \gamma_0 \Gamma_1^\dagger \gamma_0 H(x,y) \gamma_5 \Gamma_2 H(x,y)^\dagger \gamma_5 \right] \right> \; .\end{aligned}\end{equation}
Since the \( \gamma\)-matrices commute, we can conclude that the matrix \( \gamma_0 \Gamma^\dagger \gamma_0 \) is equal to \( \Gamma \) up to a sign
\begin{equation}\label{eq:gamma0_adj}\gamma_0 \Gamma^\dagger \gamma_0 = s(\Gamma) \Gamma \qquad \text{with } s(\Gamma) = \pm 1 \; .\end{equation}
In addition, a generic matrix \( \Gamma \) has the following properties:
Consequently, we can write
\begin{equation}\label{gamma_ab} \Gamma_{\alpha\beta} = t_\alpha(\Gamma) \delta_{\sigma_\alpha(\Gamma), \beta}\end{equation}
where \( \sigma(\Gamma) \) constitutes a permutation of four elements. Putting this together we find
\begin{equation}\begin{aligned} & C_{\Gamma_1,\Gamma_2}(x-y) = - s(\Gamma_1) \left< \mathrm{tr} \left[ \gamma_5 \Gamma_1 H(x,y) \gamma_5 \Gamma_2 H(x,y)^\dagger \right] \right> = \\ & \quad = - s(\Gamma_1) \sum_{\alpha\beta} t_\alpha(\gamma_5 \Gamma_1) t_\beta(\gamma_5 \Gamma_2) \times \left< \mathrm{tr} \left[ H_{\sigma_\alpha(\gamma_5 \Gamma_1), \beta}(x,y) H_{\alpha, \sigma_\beta(\gamma_5 \Gamma_2)}(x,y)^\dagger \right] \right> \; .\label{triplet_corr}\end{aligned}\end{equation}
In order to calculate mesonic masses we are interested in correlators satisfying \( \Gamma_1=\Gamma_2 \). Using translational invariance, we can set \( y=0 \). In this case the formula simplifies to
\begin{equation}C_{\Gamma}(x) = - s(\Gamma) \sum_{\alpha\beta} t_\alpha(\gamma_5 \Gamma)t_\beta(\gamma_5 \Gamma) \times \left< \mathrm{tr}\left[ H_{\sigma_\alpha(\gamma_5 \Gamma), \beta}(x,0) H_{\alpha, \sigma_\beta(\gamma_5 \Gamma)}(x,0)^\dagger \right]\right> \; .\label{eq:triplet_point_to_all_corr}\end{equation}
This is implemented into HiRep in the following way
The data of the point-like source \( \xi^{(\alpha,a)} \) defined by
\begin{equation}\xi^{(\alpha,a)}_{\beta b}(x) = \delta_{\alpha,\beta} \delta_{a,b} \delta_{x,0} \; ,\end{equation}
The function quark_propagator applies the inverse of the hermitian Dirac operator to the source
\begin{equation}\eta^{(\alpha,a)} = H \xi^{(\alpha,a)} \qquad \eta^{(\alpha,a)}_{\beta b}(x) = H_{\beta \alpha}^{b a}(x,0) \; .\end{equation}
The functions void *_correlator(float *out, suNf_spinor **qp)in Observables/mesons.c implement the formulae eq. \((\ref{eq:triplet_point_to_all_corr})\), where out stands for the correlator and qp for the spinor array. The functions \( s(\Gamma) \), \( t_\alpha(\gamma_5 \Gamma) \) and \( \sigma_\alpha(\gamma_5 \Gamma) \) where calculated using Mathematica, see file mesons.nd and implemented in the code using macros, defined as follows\
\ _C1_ = \(\sigma_1(\gamma_5 \Gamma)\)\ _C2_ = \(\sigma_2(\gamma_5 \Gamma)\)\ _C3_ = \(\sigma_3(\gamma_5 \Gamma)\)\ _C4_ = \(\sigma_4(\gamma_5 \Gamma)\)\
If \( t_\alpha(\gamma_5 \Gamma) \) are read:
\ _S0_ = \(-s(\Gamma)\)\ _S1_ = \(t_1(\gamma_5 \Gamma)\)\ _S2_ = \(t_2(\gamma_5 \Gamma)\)\ _S3_ = \(t_3(\gamma_5 \Gamma)\)\ _S4_ = \(t_4(\gamma_5 \Gamma)\)\
whereas if \( t_\alpha(\gamma_5 \Gamma) \) are imaginary:
\ _S0_ = \(s(\Gamma)\)\ _S1_ = \(-i t_1(\gamma_5 \Gamma)\)\ _S2_ = \(-i t_2(\gamma_5 \Gamma)\)\ _S3_ = \(-i t_3(\gamma_5 \Gamma)\)\ _S4_ = \(-i t_4(\gamma_5 \Gamma)\)\
We are now concerned with the genertic mesonic correlator given by
\begin{equation}\begin{aligned} C_{\Gamma_1,\Gamma_2}(x-y) &=& \left< \left( \bar{u} \gamma_0 \Gamma_1^\dagger \gamma_0 u \right)(x) \left( \bar{u} \Gamma_2 u \right)(y) \right>\end{aligned}\end{equation}
considering only a single flavor \( u \).
Integration of the fermionic fields now yiels one additional term, the hairpin diagram
\begin{equation}\begin{aligned} C_{\Gamma_1,\Gamma_2}(x-y) =&- \left< \mathrm{tr} \left[ \gamma_0 \Gamma_1^\dagger \gamma_0 G(x,y) \Gamma_2 G(y,x) \right] \right> + \left< \mathrm{tr} \left[ \gamma_0 \Gamma_1^\dagger \gamma_0 G(x,x) \right] \mathrm{tr}\left[ \Gamma_2 G(y,y) \right] \right>\\ =& - \left< \mathrm{tr} \left[ \gamma_0 \Gamma_1^\dagger \gamma_0 H(x,y) \gamma_5 \Gamma_2 H(x,y)^\dagger \gamma_5 \right] \right> + \left< \mathrm{tr} \left[ \gamma_5 \gamma_0 \Gamma_1^\dagger \gamma_0 H(x,x) \right] \mathrm{tr}\left[ \gamma_5 \Gamma_2 H(y,y) \right] \right> \; .\end{aligned}\end{equation}
All other contributions are identical to the contributions to the isotriplet correlator. We can, therefore, focus on the contribution through the hairpin diagram. Using the formulae eq. \((\ref{eq:gamma0_adj})\) we can write
\begin{equation}\left< \mathrm{tr} \left[ \gamma_0 \Gamma_1^\dagger \gamma_0 G(x,x) \right] \mathrm{tr}\left[ \Gamma_2 G(y,y) \right] \right> = \quad = s(\Gamma_1) \sum_{\alpha \beta} t_\alpha(\Gamma_1) t_\beta(\Gamma_2) \times \left< \mathrm{tr}G_{\sigma_\alpha(\gamma_5 \Gamma_1),\alpha}(x,x) \; \mathrm{tr}G_{\sigma_\beta(\gamma_5 \Gamma_2),\beta}(y,y) \right> \; .\label{eq:hairpin}\end{equation}
It is clear from eq. \((\ref{eq:hairpin})\), from the fact that we are employing point source, that one must compute the entire inverse matrix of the Dirac operator. The alternative is to use a statistic estimate for \( H \) followed by variance reduction procedures.
Suppose there are \( N_s \) available random fermion sources \( \xi^{(i)} \) such that the only non-zero correlators are
\begin{equation}\left< \xi^{(i)}_{\alpha a}(x)^\dagger \xi^{(j)}_{\beta b}(y) \right> = \delta_{\alpha,\beta} \delta_{a,b} \delta_{x,y} \delta_{i,j} \; .\end{equation}
Current literature proposes mainly either Gaussian noise or \( Z_2 \) noise. In the following, we will choose \( Z_2 \) noise, following [5]. Each component of the spinor is randomly chosen from the values \( \pm 1/\sqrt{2} \).
Then the matrix \( H \) can be estimated as follows:
\begin{equation}H_{\alpha \beta}^{a b}(x,y) \simeq \sum_{i=1}^{N_s} \eta^{(i)}_{\alpha a}(x) \xi^{(i)}_{\beta b}(y)^\dagger \eta^{(i)} \equiv H \xi^{(i)}\label{eq:naive_noisy_estimate}\end{equation}
Stochastic estimation can then be used to calculate the relevant tracks for correlators
\begin{equation}\mathrm{tr}\left[ \Gamma_1 G(x,y) \Gamma_2 G(y,x) \right] = \sum_{ij} \xi^{(i)}(x)^\dagger \gamma_5 \Gamma_1 \eta^{(j)}(x) \times \xi^{(j)}(y)^\dagger \gamma_5 \Gamma_2 \eta^{(i)}(y)\end{equation}
\begin{equation}\mathrm{tr}\left[ \Gamma G(x,x) \right] = \sum_i \xi^{(i)}(x)^\dagger \gamma_5 \Gamma \eta^{(i)}(x)\, .\end{equation}
The noise obtained from stochastic estimation of the matrix \( G \) in the formula eq.naive_noisy_estimate can be reduced using the trick from [9] for Wilson fermions. Here, the Dirac operator has the form \( D = 1 - K \). As a result, for the matrix \( G \) the following formula applies
\begin{equation}\begin{aligned} && G = D^{-1} = \left( 1 - K \right)^{-1} = \\ && \quad = 1 + K + \dots + K^m + K^{n_1} G K^{n_2}\end{aligned}\end{equation}
with \( n_1 + n_2 = n = m+1 \). In particular, for the evaluation of the hairpin diagram
\begin{equation}\begin{aligned} \mathrm{tr}\left[ \Gamma G(x,x) \right] &=& \mathrm{tr}\Gamma + \mathrm{tr}\left[ \Gamma K^4 \right](x,x) + \mathrm{tr}\left[ \Gamma K^6 \right](x,x) + \dots + \\ && + \mathrm{tr}\left[ \Gamma K^{2k} \right](x,x) + \mathrm{tr}\left[ \Gamma K^{n_1} G K^{n_2} \right](x,x)\end{aligned}\end{equation}
with \( m=2k \). (TODO: fix this sentence) Here, we can use the fact that the matrix \( K \) connects first neighboring sites as thus \( K^p(x,x) \neq 0 \) only when \( p \) is even. Further, \( r_0=1 \) and consequently \( K^2(x,x) = 0 \) The first \( k+1 \) terms can be calculated explicitly and we can estimate the last term stochastically.
\begin{equation}\begin{aligned} \mathrm{tr}\left[ \Gamma G(x,x) \right] =& \mathrm{tr}\Gamma + \mathrm{tr}\left[ \Gamma K^4 \right](x,x) + \mathrm{tr}\left[ \Gamma K^6 \right](x,x) + \dots + \nonumber \\ & + \mathrm{tr}\left[ \Gamma K^{2k} \right](x,x) + \sum_{iy} \xi^{(i)}(y)^\dagger \gamma_5 K^{n_2}(y,x) \Gamma K^{n_1}(x,y) \eta^{(i)}(y) \nonumber \\ \end{aligned}\label{eq:hairpin_with_variance_reduction}\end{equation}
[9] use this trick only for the calculation of the hairpin diagram. It might be possible to generalize it to the the isotriplet part as well, as an alternative to the point-to-all propagator.
This is a trick introduced in [4] for noise reduction in the computation of null-moment propagators. Whenever stochastic estimation of the \( H \) matrix is required, such as in eq. \((\ref{eq:naive_noisy_estimate})\), it is possible to replace each stochastic source \( \xi^{(i)} \) with a set of sources each with support on a different time slice.
\begin{equation}\begin{aligned} \label{time_dilution} && \xi^{(i)} \rightarrow \xi^{(i,\tau)}(\mathbf{x},t) = \xi^{(i)}(\mathbf{x},t) \delta_{t,\tau}\end{aligned}\end{equation}
Stochastic estimation is now obtained similarly to the naive case:
\begin{equation}H_{\alpha \beta}^{a b}(x,y) \simeq \sum_{i=1}^{N_s} \sum_{\tau=1}^{N_t} \eta^{(i,\tau)}_{\alpha a}(x) \xi^{(i,\tau)}_{\beta b}(y)^\dagger \eta^{(i,\tau)} \equiv H \xi^{(i,\tau)}\label{eq:diluted_noisy_estimate}\end{equation}
TODO: Add this to function reference instead if this is still implemented this way
The following functions will be implemented
hairpin_with_variance_reduction
\ void GAMMA_variance_reduction_exact_terms(float *out, int k)
Here, out is a real vector with its components equal to the volume and \( k \) corresponds to the index in the \( \gamma\)-matrix.
This function evaluates
\begin{equation}h_k(x) = \mathrm{tr}\left[ \Gamma K^{2k} \right](x,x) = \left( \frac{\kappa}{2} \right)^{2k} \sum_{\mathcal{C}_x} \mathrm{tr}\left( \Gamma \tilde{\gamma}(\mathcal{C}_x) \right) \mathcal{W}(\mathcal{C}_x)\end{equation}
where \( \mathcal{C}_x = (x,\hat{\mu}_1,\hat{\mu}_2,\dots,\hat{\mu}_{2k}) \) is the generic closed path of \( x \) of length \( 2k \) obtained by moving from \( x \) in the directions \( \hat{\mu}_i \). \( \mathcal{W}(\mathcal{C}_x) \) is the trace of the parallel transport through \( \mathcal{C}_x \) in the corresponding fermionic representation. \( \tilde{\gamma}(\mathcal{C}_x) \). is the matrix defined as
\begin{equation}\tilde{\gamma}(\mathcal{C}_x) = (1-\gamma_{\hat{\mu}_1})(1-\gamma_{\hat{\mu}_2})\cdots(1-\gamma_{\hat{\mu}_{2k}})\end{equation}
having defined \( \gamma_{-\hat{\mu}_i} = - \gamma_{\hat{\mu}_i} \).
It should be noted that since \( (1-\gamma_{\hat{\mu}_i})(1-\gamma_{-\hat{\mu}_i}) = 0 \), one can exclude the paths in which a pair of subsequences \( (\dots, \hat{\mu}_i,-\hat{\mu}_i, \dots) \) appears from the sum. In addition, the matrix \( \tilde{\gamma}(\mathcal{C}_x) \) does not depend on \( x \). There is is convenient to compute the list of paths and the matrix \( \tilde{\gamma}(\mathcal{C}_x) \) only once.
void tr_r_pexp(complex *out, int *path, int length)
Here again out is the complex vector with number of components according to the volume and \( \phi(x) \) \ is the number of directions (length) of which the path is composed.
This returns
\begin{equation}\phi(x) = \mathrm{tr}\mathbf{R} \left[ U_{x, \hat{\mu}_1} U_{x+\hat{\mu}_1, \hat{\mu}_2} \cdots \right]\end{equation}
Calculation of the time-diluted estimators
void time_diluted_stochastic_estimate\ (suNf_spinor *csi, suNf_spinor **eta,\ int nm, float *mass, double ac)\
With the parameters: csi is the spinor \( \xi\)\ path is the list of \( N_t \times \textrm{nm} \) spinors along the \( \eta^{(\tau,m)}\) \
This function generates the spinor \( \xi \) with \( Z_2 \) noise. Here the spinors are defined as
\begin{equation}\xi^{(\tau)}(\mathbf{x},t) = \xi(\mathbf{x},t) \delta_{t,\tau}\end{equation}
and then returned as
\begin{equation}\eta^{(\tau,m)} \equiv H_m \xi^{(\tau)}\end{equation}
using the inverter of the Dirac operator with parameters nm, mass and acc.
The calculation of the hairpin term
\ void GAMMA_hairpin_VR_TD(float **out,\ int n1, int n2, int nrs,\ int nm, float *mass, double acc)\
Takes the parameters out = list of real nm vectors with the number of components corresponding to the volume n1, n2 = parameters of the variance reduction algorithm nrs = number of random sources for the statistical estimation nm, mass = number and list of masses acc = inverter parameter \
The functions above implement the formula eq. \((\ref{eq:hairpin_with_variance_reduction})\), summing exact terms and the statistical term, generated with nrs to dilute, for a total of \( \times N_t \) matrix invertions for each mass value and returns the result as out.
1.12.0