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8.3 Exercise: Adding a new observable

This exercise illustrates the modifications that are required to implement a new observable, the correlation function of the bond-hopping in the 1-dimensional Hubbard chain. This observable is interesting in many different setups. For example, the model studied here exhibits an emergent SO(4)SO(4) symmetry that relates the anti-ferromagnetic order parameter and the bond dimerization (I. Affleck, PRL 55 (1985) pp. 1355; I. Affleck and F. D. M. Haldane, PRB 36 (1987) pp. 5291). Another example where this quantity is useful to investigate is the 1-dimensional Su-Schrieffer-Heeger model describing an electron-phonon system.

8.3.1Applying Wick’s theorem

Here the task is to define a new equal-time observable, the kinetic energy correlation, given by

⟨O^i,δO^j,δ′⟩−⟨O^i,δ⟩⟨O^j,δ′⟩=SO(i−j,δ,δ′)\left\langle \hat{O}_{i,\delta} \hat{O}_{j,\delta'} \right\rangle - \left\langle \hat{O}_{i,\delta} \right\rangle \left\langle \hat{O}_{j,\delta'} \right\rangle = S_O\big(i-j,\delta,\delta'\big)

where i,ji,j refer to the unit cells and δ\delta encodes the bond label. Since we are working in 1D, there is only one bond per unit cell and δ=ax\delta=ax such that

O^i,x=∑σ(c^i,σ†c^i+ax,σ†+H.c.).\hat{O}_{i,x} = \sum_{\sigma}\left( \hat{c}^\dagger_{i,\sigma}\hat{c}^{\phantom\dagger}_{i+ax,\sigma} +\mathrm{H.c.} \right).

Note that the first term of Eq. (1) is of the generic form ∑σ,σ′⟨c^i1,σ†c^i2,σ†c^j1,σ′†c^j2,σ′†⟩\sum_{\sigma,\sigma'}\left\langle \hat{c}^\dagger_{i_1,\sigma}\hat{c}^{\phantom\dagger}_{i_2,\sigma} \hat{c}^\dagger_{j_1,\sigma'}\hat{c}^{\phantom\dagger}_{j_2,\sigma'} \right\rangle. This expectation value can be readily decomposed into single-particle Green functions by using Wick’s theorem. It can be applied for a fixed field configuration Φ\Phi since the Hamiltonian H^(Φ)\hat{H}(\Phi) is then bi-linear in the fermion operators.

∑σ,σ′⟨c^i1,σ†c^i2,σ†c^j1,σ′†c^j2,σ′†⟩Φ=∑σ,σ′(⟨c^i1,σ†c^i2,σ†⟩Φ⟨c^j1,σ′†c^j2,σ′†⟩Φ+⟨c^i1,σ†c^j2,σ′†⟩Φ⟨c^i2,σ†c^j1,σ′†⟩Φ)\sum_{\sigma,\sigma'}\left\langle \hat{c}^\dagger_{i_1,\sigma}\hat{c}^{\phantom\dagger}_{i_2,\sigma} \hat{c}^\dagger_{j_1,\sigma'}\hat{c}^{\phantom\dagger}_{j_2,\sigma'} \right\rangle_\Phi = \sum_{\sigma,\sigma'}\left(\left\langle \hat{c}^\dagger_{i_1,\sigma}\hat{c}^{\phantom\dagger}_{i_2,\sigma}\right\rangle_\Phi \left\langle\hat{c}^\dagger_{j_1,\sigma'}\hat{c}^{\phantom\dagger}_{j_2,\sigma'} \right\rangle_\Phi +\left\langle \hat{c}^\dagger_{i_1,\sigma}\hat{c}^{\phantom\dagger}_{j_2,\sigma'}\right\rangle_\Phi \left\langle\hat{c}^{\phantom\dagger}_{i_2,\sigma}\hat{c}^\dagger_{j_1,\sigma'} \right\rangle_\Phi \right)

The second term vanishes for σ≠σ′\sigma\neq\sigma' due to flavor symmetry (Mz-decoupling used here in the vanilla version) or due to the SU(2)SU(2) symmetry (density decoupling available in the generic implementation of Hubbard model). The single-particle Green functions are provided in the Obser routine, where all equal-time observables are measured, as

GRC(i,j,σ)=⟨c^i,σ†c^j,σ†⟩ΦGR(i,j,σ)=⟨c^i,σ†c^j,σ†⟩Φ.\begin{align*} GRC(i,j,\sigma) & = \left\langle \hat{c}^\dagger_{i,\sigma}\hat{c}^{\phantom\dagger}_{j,\sigma}\right\rangle_\Phi\\ GR(i,j,\sigma) & = \left\langle \hat{c}^{\phantom\dagger}_{i,\sigma}\hat{c}^\dagger_{j,\sigma}\right\rangle_\Phi . \end{align*}

8.3.2Necessary code modifications

In solution we have the modified submodule Hamiltonian_Hubbard_Plain_Vanilla_smod.F90, as well as the parameter file. The following are the essential steps to be carried out:

The 1-D Hubbard exhibits an emergent SO(4)SO(4) symmetry:

⟨Sˉ(r)S(0)⟩∼(−1)rrln⁡d(r)⟨O^r,xO^0,x⟩−⟨O^r,x⟩⟨O^0,x⟩∼(−1)rrln⁡β(r)\begin{align*} \left\langle \bar{S}(r)S(0) \right\rangle &\sim \frac{(-1)^r}{r}\ln^d(r)\\ \left\langle \hat{O}_{r,x} \hat{O}_{0,x} \right\rangle - \left\langle \hat{O}_{r,x} \right\rangle \left\langle \hat{O}_{0,x} \right\rangle &\sim \frac{(-1)^r}{r}\ln^\beta(r) \end{align*}

where d=1/2d=1/2 and β=−3/2\beta=-3/2 (T. Sato, M. Hohenadler et al., Phys. Rev. B 104 (2021) L161105) and this exercise provides all the tools required to study it. Beware of the large system sizes, and therefore long run times, that are required to extract the logarithmic scaling corrections. More details are discussed in the appendix of above reference.

Finally, it is straightforward to implement the time-displaced version of this correlation function, following essentially the same steps as described above. The observable is now stored in Obs_tau, the measurements are taken in ObserT, and you can find the implementation in the solution to this exercise as well.