1. Introduction
The axial charge,
, gives the strength of the coupling of the weak current to the nucleons. It has been determined very accurately from the asymmetry parameter
A (relative to the plane defined by the directions of the neutron spin and the emitted electron) in the decay distribution of the neutron,
. The best determination of the ratio of the axial to the vector charge,
, comes from using (i) polarized ultracold neutrons (UCN) using the the UCNA collaboration,
[
1,
2], and (ii) cold neutron beam using the PERKEO III,
[
3,
4]. Note that, in the SM,
up to second-order corrections in isospin breaking [
5,
6] as a result of the conservation of the vector current.
The axial charge enters in many analyses of nucleon structure and of the Standard Model (SM) and probes of beyond-the-SM (BSM) physics [
7,
8]. For example, it enters in the relation between the Cabibbo–Kobayashi–Maskawa (CKM) matrix element
and the neutron lifetime,
. High precision extraction of
, knowing
and
, is important for the test of the unitarity of the first row of the CKM matrix [
9,
10,
11]. It is needed in the analysis of neutrinoless double-beta decay [
12] and in the rate of proton–proton fusion [
13], which is the first step in the thermonuclear reaction chains that power low-mass hydrogen-burning stars like the sun.
The axial vector form factor (AVFF) gives the dependence of this coupling on the momentum squared transferred by the weak current to the nucleon. It is an input in the theoretical calculation of the neutrino–nuclei scattering cross-section needed for the analysis of neutrino oscillation experiments [
14,
15,
16]. The cleanest experimental measurement would be from scattering neutrinos off liquid hydrogen targets; however, these are not being carried out due to safety concerns. Extractions from ongoing neutrino scattering experiments (T2K, NOvA, MINERvA, MicroBooNE, SBN) have uncertainty due to the lack of precise knowledge of the incoming neutrino energy and the reconstruction of the final state of the struck nucleus and thus of the cross-section.
The MINER
A experiment [
17] has recently shown that the axial vector form factor of the nucleon can be extracted from the charged current elastic scattering process
in which the free proton in hydrogen (H) (part of the hydrocarbon in the target) is converted into a neutron. This opens the door to direct measurements of the nucleon axial vector form factor without the need for extraction from scattering off nuclei, whose analysis involves nuclear corrections that have unresolved systematics. On the theoretical front, lattice QCD provides the best method for first principal nonperturbative predictions with control over all sources of uncertainty [
14,
15].
A recent comparison [
18] of results for the AVFF from lattice QCD [
19], the MINER
A experiment [
17], and the phenomenological extraction from neutrino–deuterium data from 1980s and 1990s [
20] showed that, in the near term, the best prospects for determining the AVFF will be a combination of lattice QCD calculations and MINER
A-like experiments. Lattice QCD will provide the best estimates for
GeV
2 and be competitive with MINER
A for
GeV
2. For
GeV
2; new ideas are needed for robust predictions using lattice QCD.
The goal of theory efforts in support of neutrino oscillation experiments is robust calculations of the cross-section for targets, such as
,
, and
, being used in experiments. This involves a four step process: a precise determination of the AVFF, nuclear models of the ground state of the nuclei from which the neutrino scatters, the intranucleus evolution of the struck nucleon using many-body theory to include complex nuclear effects up to
GeV for the DUNE experiment, and the evolution of the final state particles to the detectors. The overall program requires complete implementation of these within Monte Carlo neutrino event generators [
14,
15,
16]. The output of the generators provides the input essential to experimentalists for determining neutrino oscillation parameters from current and future experiments.
Here, I review the status of lattice QCD calculations of the axial charge,
, and the AVFF. In addition, note that the flavor diagonal axial charges
provide the contribution of each quark flavor to the spin of the nucleon, whose calculation is computationally more expensive due to the additional disconnected contributions. The current status of the results for these nucleon charges has been reviewed by the Flavor Lattice Averaging Group (FLAG) in 2019 and 2021 [
21,
22]). Including results post FLAG 2021 [
23,
24,
25,
26,
27], the values from the various calculations with 2+1- and 2+1+1-flavors of sea quarks lie in the ranges
,
,
, and
. There have been no substantial new results for flavor diagonal charges since the FLAG reports, so I will not discuss them further in this work.
Based on the results in Refs. [
19,
23,
26,
27,
28,
29], I present the case that lattice results for AVFF, over the range
GeV
2, are also available with
uncertainty and agree with MINER
A results to within a combined sigma as discussed in Ref. [
18] but disagree with the neutrino–deuterium results for
GeV
2. At the same time, I also highlight the need for much higher statistics and better control over excited state contributions to nucleon correlators in lattice calculations for the uncertainty to be reduced to the few percent level.
The outline of this review is as follows. I will summarize the methodology and steps in the calculation of the axial and pseudoscalar form factors in
Section 2. This includes a discussion of the nucleon three-point correlation functions calculated in
Section 2.1, how form factors are obtained from them in
Section 2.2, and possible excited state contributions (ESC) that must be removed in
Section 2.3. I then review the operator constraint imposed on the three form factors, the axial,
, the induced pseudoscalar,
, and the pesudoscalar
by the axial Ward–Takahashi (also referred to in the literature as the partially conserved axial current (PCAC)) identity in
Section 2.4, and how it provides a data-driven method for validating the enhanced contributions of multihadron,
, excited states. These enhanced excited state contributions are due to the coupling of the axial and pseudoscalar currents to a pion, i.e., the pion pole dominance hypothesis. Extrapolation of the lattice results in the physical point defined by the continuum (
) and infinite volume (
) limits at physical light quark masses in the isospin symmetric limit, i.e.,
set using the neutral pion mass (
MeV) is discussed in
Section 2.5. A consistency check on the extraction of the axial charge is discussed in
Section 2.6. I will then review the results for the AVFF obtained by the various lattice collaborations after extrapolation to the physical point in
Section 3, the comparison of the lattice QCD result, the recent MINER
A data, and the phenomenological extraction from the old neutrino–deuterium scattering data, along with my perspective on future improvements in
Section 4. I end with a few concluding remarks in
Section 5.
2. Calculation of the Axial Vector form Factors Using Lattice QCD
The quark line diagrams for the two-point
and the three-point
(with the insertion of the axial,
, and pseudoscalar,
P, currents) correlators are shown in
Figure 1. The methodology for calculating these is the same in all ongoing calculations. For
, two kinds of quark propagators are calculated—the original moving forward from the source point (say from the left blob), and a sequential propagator moving backwards from a nucleon source with definite momentum
at the sink (the right blob). This nucleon source is constructed by tying together two original propagators shown by the two bottom quark lines. The insertion of the current with three-momentum
between the source and sink nucleons then reduces to that between the original propagator and the sequential propagator, as shown by the top line. By momentum conservation, the source nucleon is projected to momentum
. The Euclidean four-momentum transfer squared is given by
.
In current calculations (standard method) the nucleon interpolating operator,
, used is
where
, and the optional factor
projects on to positive parity nucleon states propagating forward/backward in time for zero momentum correlators. Developing a variational basis of interpolating operators that includes all significant
states, the holy grail of taming the ESC, is still a work in progress [
30,
31].
2.1. Correlation functions and
Two kinds of smeared sources have been used to generate the original and sequential quark propagators in most lattice calculations: (i) the Wuppertal source [
32] and (ii) the exponential source [
25]. These quark propagators are stitched together to construct the gauge-invariant time-ordered correlation functions
and
shown in
Figure 1, whose spectral decompositions are
and
where
,
is the quark bilinear current inserted at time
t with momentum
, and
is the vacuum state. In the
, the nucleon state
is, by construction, projected to zero momentum, i.e.,
, whereas
is projected onto definite momentum
, with
by momentum conservation. The prime in
indicates that this state can have nonzero momentum. Consequently, the states on the two sides of the inserted operator
J are different for all
. The goal is to extract the ground-state matrix elements (GSME),
, from fits to Equation (
3).
A major challenge in the analysis of all nucleon correlators is that the signal-to-noise ratio decays exponentially as
with the source–sink separation
[
33,
34]. In current calculations (
measurements), a good signal in
and
extends to ≈2 and ≈1.5 fm, respectively.
At these
, the residual contribution of many theoretically allowed radial and multihadron excited states are observed to be significant. These states arise because the standard nucleon interpolating operator
, defined in Equation (
1), used to construct the correlation functions in Equations (
2) and (
3), couples to a nucleon and all its excitations with positive parity including multihadron states, the lowest of which are
and
. Since it is not known a priori which excited states contribute significantly to a given
, the first goal is to develop methods to identify these and remove their contributions. Operationally, this boils down to determining the energies
to put in fits to data using the theoretically rigorous spectral decomposition given in Equation (
3).
2.2. Extracting the form Factors
Once the GSME,
, have been extracted, their Lorentz covariant decomposition into the axial
, induced pseudoscalar
, and pseudoscalar
form factors is
and
where
is the nucleon spinor with momentum
,
is the four-momentum transferred by the current, and
is the space-like four-momentum squared transferred. On the lattice, the discrete momenta are
with
. The spinor normalization used is
It is important to note that the excited states have to be removed from the
C, which have the spectral decomposition given in Equation (
3), and not from the form factors, i.e., after the decompositions. Equations (
4) and (
5) are only valid for the GSME. If there are residual ESC, then additional “transition” form factors have to be included in the rhs of Equations (
4) and (
5).
Assuming the GSME and choosing the nucleon spin projection to be in the “3” direction, the explicit forms of the decompositions in Equations (
4) and (
5) become
where the kinematic factor
. In each case, data with all equivalent momenta that have the same
are averaged to improve the statistical signal. These correlation functions are complex valued, and the signal for the CP symmetric theory is in
,
, and
.
It is clear that
is determined uniquely from
(Equation (10)) and for certain momenta
from
using Equation (
7). The
and
give linear combinations of
and
, and Equation (8) gives only
when
.
2.3. Extracting the Ground State Matrix Elements: Exposing and Incorporating States
The most direct way to extract
is to make fits to Equation (
3) keeping as many intermediate states as allowed by the data’s precision that demonstrate convergence. The problem is that even unconstrained two-state fits are numerically ill behaved. The next option is to take the
and
from
, as
creates the same set of states in
and
and input these in fits to
, either by doing simultaneous fits or via priors within say a bootstrap process to correctly propagate the errors. Of these, the ground states
,
, and
are well determined from fits to the two-point function. Similarly, one would expect that
can also be taken from
. This was the strategy used until 2017 when it was shown in Ref. [
35] that the resulting form factors do not satisfy the constraint imposed on them by the PCAC. Deviations from the PCAC due to discretization effects of about
were expected; however, almost a factor of two was found on the physical pion mass ensembles.
The reason was provided by Bär [
36,
37] using
PT: enhanced contributions to ME from multihadron,
, which are excited states that have much smaller mass gaps than those of radial excitations, with the lowest being
versus N(1440). These states were not evident in fits to
, as they have small amplitudes. A different approach to analysis to include the
states was needed.
It turned out that two-state fits to
provided a data-driven method [
38] that exposed these states and confirmed that the lowest of the tower of
states makes a very significant contribution. By itself,
is dominated by excited states and fits to it using the
from
, which gave very poor
. Making fits leaving
a free parameter dramatically improved the
(compare left two panels in top row of
Figure 2), and the resulting output values of
on either side of operator insertion were roughly consistent with
as shown in
Figure 3 (reproduced from Ref. [
38]). An illustration of the current understanding of the transitions contributing to the GSME and of the lowest-contributing excited states is shown in
Figure 4 (right).
The fact that there is an enhancement of the ME in the axial channel has been understood for over 60 years as the “pion pole dominance” (PPD) hypothesis. On the lattice, the creation of a
state by
is suppressed by the 3D volume compared to just the nucleon, as each state has a normalization factor of
for a point (local) source
. The axial current can, however, couple to this pion, and because the pion is light, this coupling can occur anywhere in the time slice at which the current is inserted with momentum
(see
Figure 4 (left)). This gives a factor of
V enhancement, thus approximately canceling the normalization factor
[
36,
37]. Thus, the ME obtains an enhanced contribution that is an artifact to be removed when the the pion comes on shell. Note that since energy is not conserved on the lattice, both the neutron and the pion can come on shell, however, since momentum is conserved, and possible excited states must have the same total momentum as the neutron state. PPD tells us that the axial current with momentum
can be viewed as the insertion of a pion with
, and this has a large coupling to the nucleon. These processes are illustrated in
Figure 4.
Having identified large contributions from the
state, certainly in the extraction of
and
, the question is—do we need to include other multihadron and radial excited state contributions if we want results with percent level precision? What about in
? Note that, in addition to the enhanced contribution shown in
Figure 4,
PT also indicates that the one-loop contributions due to the diagram shown in
Figure 5 (again a
contribution) could be
in all the five
. Thus, the
state could be significant for extracting
(the GSME
) from
at the percent precision desired. Based on these arguments, it is clear that one needs at least three-state fits to the five
in Equation (
3)—the ground state, the
state, and one other that effectively accounts for all other excited state contributions.
The caption of
Figure 2 points out some of the features of the ESC observed in current data and the efficacy of fits to the spectral decomposition of
with and without including the lowest
state to remove the ESC.
In my evaluation, the details of the fits made to remove ESC are the most significant differences between the calculations performed by the different collaborations. With the current methodology, higher statistics data are needed to improve these fits and reduce the dependence on exactly how the analyses are done.
A very important point to keep in mind is that fit parameters in a truncated ansatz (the
and
in say a three-state fit in our case) try to incorporate the effects of all contributions. Thus, the connection between parameters coming out of fits to a truncated Equation (
3) and physical states made in
Figure 3 and
Figure 4 are very approximate at best.
2.4. Satisfying PCAC
The nonsinglet PCAC relation between the bare axial,
, and pseudoscalar,
, currents is the following:
where the quark mass parameter
includes all the renormalization factors, and
is the light quark mass in the isospin symmetric limit. Using the decomposition in Equations (
4) and (
5) of the GSME, the PCAC relation requires that the three form factors
,
, and
must satisfy on each ensemble up to discretization errors; thus, the relation is
All prior Ref. [
35] calculations did not check this relation and missed observing that the data showed large deviations. Calculations subsequent to Ref. [
38] that include the lowest mass gap state
in the analysis obtain form factors that already satisfy the PCAC to within ≈10% at a lattice spacing of
fm. (The ETMC result is an exception, as explained in Ref. [
23] ). An illustration of the size of the deviation from unity of
, without and with the lowest
state included, is shown in
Figure 6 taken from Ref. [
19].
To summarize, satisfying the PCAC relation in Equation (
12) provides a strong and necessary constraint on the extraction of the three axial form factors.
PT analysis by Bär [
36,
37] and data-driven validation in Refs. [
29,
30,
38] show that the lowest
state makes a large contribution and needs to be included in the analysis. For percent level precision, the next question is—what other states need to be included? Current analyses include up to three states, where the third state, if the parameters are left free, is effectively trying to account for all of the residual ESC. Such fits have been implemented in different ways. For example, in Ref. [
29], the
state is hardwired, and the third state is taken to be the lowest excited state in fits to
. In Refs. [
19,
27,
38], a simultaneous fit to all five
and
P correlators is made wherein the
correlator fixes
to being close to the
state. Over time, with much higher statistics data, results from various methods and collaborations should converge.
2.5. Extrapolating Lattice AVFF to The Physical Point for Use in Phenomenology
The next step, once ESC have been removed and form factors have been extracted from GSME on a given ensemble, is to extrapolate these data to the physical point to provide a parameterized form for and that can be used in phenomenology. The challenge is that the discrete set of values at which the data are obtained are different on each ensemble.
One simple way to implement this consists of the following three steps:
This three-step process can be done within a single bootstrap procedure to propagate errors as has been done in Refs. [
19,
27] to produce the NME and PNDME results shown in
Figure 7. Or, these steps can be combined, especially if there are correlations between them. For example, as can be done in step (ii) to account for correlations between the coefficients of the CCFV fits for different values of
.
The plots in
Figure 7 provide two comparisons. In the panels on the left, the physical point results from the RQCD [
24,
29], ETMC [
23], NME [
27], and Mainz [
26] collaborations are compared against those from the PNDME [
19]. On the right, they are overlaid and compared to the phenomenological extraction from the old neutrino–deuterium bubble chamber data [
20]. The PNDME, RQCD, and NME data mostly overlap, whereas the ETMC and Mainz data overlap and fall off slower for
GeV
2. On the other hand, the neutrino–deuterium (
D) data [
20] fall off much faster for
GeV
2. Overall, as shown in the right plot, the five lattice QCD estimates are consistent within
and lie about
above the
D band for
GeV
2.
There also are results from the CalLAT [
16], PACS [
25,
40], and LHP+RBC+UKQCD [
41] collaborations, which have not been included in the comparison because they have not been extrapolated to the physical point. The Fermilab collaboration [
31] has embarked on the much harder problem of calculating transition matrix elements as well, e.g.,
or
.
From the analysis of the NME and PNDME data, my understanding is that the differences in exactly how the ESC values are handled by the various collaborations and the uncertainty in the final results should be considered as a work in progress. The uncertainty from the differences in the overall procedure for parameterization and CCFV extrapolation is, I believe, smaller, especially since the data do not show a large dependence on any of the three parameters
, especially for
fm and
, as illustrated in
Figure 8 [
19,
27]. Hopefully, the next generation calculations will shed light on and possibly resolve the various differences.
Other findings in Refs. [
19,
27] are that (i) the dipole ansatz
gives poor fits (very low
p values) to data on many ensembles. My conclusion, therefore, is that the lattice data already show that the dipole ansatz does not have enough parameters to capture the
behavior over the range
GeV
2. The second finding is that (ii) The PPD relation between
and
works very well.
2.6. Consistency Check in the Extraction of the Axial Charge
There are two ways in which one can extract the axial charge
. The first is from the forward matrix element using
in Equation (8) with
, and the second is by extrapolating the form factor
to
. I am considering them as separate because the extraction from the forward matrix element is computationally clean:
has the smallest errors, and the verification of the symmetry of the data about
is a good test. The errors grow with
, as shown in
Figure 2. On the other hand,
is constrained by being part of the PCAC relation, Equation (
12), that has to be satisfied. The two results must agree after CCFV extrapolation. Based on the data in Ref. [
19], I conclude the following:
The difference between extracted without and with including states is , i.e., on including one (the lowest) state in the analysis. Note that the errors in each result are .
The difference between extracted by extrapolating data obtained without and with including the lowest state is also , i.e., . Again, the errors in each are .
Thus, for each of the two cases, without and with including states, we obtain consistent estimates for the charge from the two methods; however, the results including the state are about larger. This difference is consistent with the expected one-loop correction to the charge in PT; however, it is roughly a one combined effect and, therefore, needs validation. My pick for the final result is the analysis including the state, since it gives form factors that satisfy the PCAC relation. Higher precision data are needed to further clarify the other significant ESCs and how to include them.
4. Comparison of the Differential Cross-Section Using Lattice AVFF with MINERA Data
A comparison of the antineutrino–nucleon charged current elastic cross sections calculated using predictions of AVFF from lattice (PNDME 23 [
19]) and neutrino–deuterium analysis [
20] with MINERvA measurement [
17,
42] is presented in
Figure 9, which is reproduced from Ref. [
18]. A
test was performed to determine the significance of the differences between the three. No significant difference was found between MINERvA–lattice QCD (PNDME) and between MINERvA–deuterium results. A
tension was, however, found between the PNDME and the deuterium results. Based on data shown in
Figure 7, the deviation in the deuterium–Mainz and deuterium–ETMC will be even larger. To assess the scope for future progress, three regions of
with different prospects for the extraction of AVFF from lattice QCD and MINERvA-like experiments were identified.
For
, LQCD predictions and fits to the deuterium bubble chamber data are in good agreement. In this region, the experimental errors in the measurement on hydrogen by MINERvA are large, whereas the errors in the parameterization of the deuterium bubble chamber data are smaller. The
D result has often been used as a benchmark; however, note that there is unresolved uncertainty in the deuterium data as discussed in Ref. [
20]. Also, no new deuterium data are expected in the near-term, so I do not comment on its future prospects. Lattice QCD data are competitive and will improve steadily. This region will be well characterized by the axial charge, the axial charge radius, and well parameterized by a low-order
z expansion or a Padé.
For
, the AVFF from PNDME has the smallest errors, and the predicted differential cross-section lies above the hydrogen and
D values, i.e., the same ordering as for the AVFF shown in
Figure 9 (left). Future improvements in both the hydrogen data and lattice calculations will provide robust crosschecks in this region.
The region is where lattice QCD data, even with current methodology, will improve rapidly as more simulations are done closer to MeV, and on larger volumes, because on a given ensemble and for given statistics, the value of with a good signal (usually specified by the lattice momentum ) decreases in these limits.
For
, current LQCD data have large statistical errors and systematic uncertainties—these are discretization and residual excited state contributions. With the current methodology, the lattice AVFF comes mostly from simulations with
MeV [
19]. New methods are needed to obtain data from simulations with physical pion masses,
MeV. Similarly, improvements further MINERvA and follow-up experiments are needed to cover the full range of
relevant for DUNE.
5. Concluding Remarks
Extensive calculations of the AVFF are being carried out by at least the following nine lattice QCD collaborations: PNDME [
19], RQCD [
24,
29], ETMC [
23], NME [
27], Mainz [
26], CalLAT [
16], PACS [
25,
40], LHP+RBC+UKQCD [
41], and Fermilab [
31]. As shown in
Section 3 and
Section 2.5, we now have results to within 10% precision. The major of the uncertainty comes from resolving and removing excited state contributions.
The good news is that the methodology for the calculation of the correlation functions,
and
, is robust. The bad news is that the exponentially falling signal-to-noise ratio in them means that ESC are large at source–sink separations possible in today’s calculations. Second, it is also clear that multihadron,
, excited states give large contributions and must be included in the analysis to remove them. Unfortunately, it is not yet known how many of these states will need to be included in the analysis for percent level precision. The operator constraint that the form factors satisfy the PCAC relation in Equation (
12) provides a valuable check that must be carried out in all calculations. The third challenge is obtaining data at large
, because the discretization and statistical errors grow with
on a given ensemble, and the
, i.e., the lattice momenta
with the largest
that has a good signal-to-noise ratio, decreases as simulations are done closer to the physical point. Thus, to obtain data for
GeV
2 on physical pion mass ensembles will need/benefit from new methodology.
I estimate that a factor of ten increase in statistics will reduce the statistical errors to a level that will provide much more clarity in removing the ESC. Similary new developments, including variational methods [
30] with multihadron states and momentum smearing [
43], will improve the calculations and extend the range of
. I anticipate improvements in both statistics and methods will provide LQCD predictions of AVFF for nucleons in the range
(hopefully higher) with percent level precision by about 2030 in concert with DUNE producing data.