Dispersion of cuprates
When working on high temperature superconducting cuprates, there is one simple model everybody starts from. It is often surprising how much this model captures, and so it is important to compare more sophisticated theories, for example those taking into account strong correlations, to this simple non-interacting model. This post describes this single-band non-interacting model of cuprates.
Two-dimensional dispersion
Since cuprates are highly bidimensional, a 2D model is often enough. The non-interacting starting point in 2D for any cuprates is the following energy function:
where , , and are the first, second and third neighbour hopping, respctively. The chemical potential can be added as . A simplified, and typical dispersion can be obtained with , , and . Of course, such a simple model does not contain superconductivity. As a function of and , this energy function can be visualize as below.
In this animation, the left plot shows as a function of and , with the chemical potential changing in time. In the center, I plot the energy contour as a function of and , and on the right, the spectral weight at the Fermi level . The latter is the same as the energy contour in this case, and it is computed with:
where takes an arbitrary small value, (in this case 0.05). More information on the spectral weight is given in my visual introduction to Green’s function. The Mathemtatica code to produce the above animation is given below.
Three dimensional dispersion
Real cuprates are 3D materials. The extension of the above model to the three-dimensional dispersion is given by (see Horio 2018 for ARPES measurement, and Markiewicz 2005 for theoretical justifications):
The experimental fit by Horio 2018 in Eu-LSCO yields parameters , , meV, , , and .
Doping
The chemical potential is obtained by solving the integral equation for a given doping :
Approximation for the pseudogap
To fit the results for the pseudogap regime at , we need some way to simulate the mysterious pseudogap ``phase’’, which is an active area of research. One way that seems to work fairly well is to start from a two-dimensional antiferromagnetic (AF) reconstruction of the bare band (following recent success of such a model for the Hall number by Storey 2016 (We published a follow-up paper on this):
This may be interpreted as antiferromagnetism uncorrelated between planes.
Mathematica code for the animation
xi[kx_, ky_] = -2*(Cos[kx] + Cos[ky]) +
2*0.35*(Cos[kx + ky] + Cos[kx - ky]);
spectralWeight[kx_, ky_, w_, mu_] :=
0.05/((w - xi[kx, ky] + mu)^2 + 0.05^2)/Pi;
spWeightColor[x_] :=
Blend[{{0, LightGray}, {1, RGBColor[1, 0, 0, 1]}}, x];
SetOptions[Plot3D, Mesh -> None, Boxed -> False, Ticks -> None,
Axes -> False, PlotRange -> Full, BoxRatios -> {1, 1, 0.6},
BoundaryStyle -> None, MaxRecursion -> 7, ClippingStyle -> None,
Ticks -> None,
Lighting -> {{"Point", White, {0, 0, 12}}, {"Point",
White, {-20, -20, 0}}}, ViewPoint -> {-10, -5, 4}];
SetOptions[ContourPlot, FrameTicks -> None, Frame -> None,
AspectRatio -> 1];
SetOptions[DensityPlot, FrameTicks -> None, PlotPoints -> 70,
Frame -> None, AspectRatio -> 1, ColorFunction -> spWeightColor];
x = 0.16;
T = Table[
GraphicsRow[{
Plot3D[{xi[kx, ky], mu - 0.03}, {kx, -Pi, Pi}, {ky, -Pi, Pi},
PlotRange -> {-4, 6},
PlotStyle -> {{RGBColor[0.45, 0.35, 0.7, 1],
Opacity[1]}, {White, Opacity[0.7]}, {White, Opacity[0.8]}},
MeshStyle -> Directive[Thickness -> 0.01, Red],
MeshFunctions -> {#3 &}, Mesh -> {{mu}}
],
GraphicsRow[{
ContourPlot[{xi[kx, ky] == mu}, {kx, -Pi, Pi}, {ky, -Pi, Pi},
ContourStyle -> {Thickness -> 0.01, Red},
Prolog -> {LightGray,
Rectangle[Scaled[{0, 0}], Scaled[{1, 1}]]}
],
DensityPlot[
spectralWeight[kx, ky, 0, mu], {kx, -Pi, Pi}, {ky, -Pi, Pi},
PlotRange -> {0, 10}]
}]
}, ImageSize -> Full, Background -> White]
, {mu, Range[-300, 350, 50]/100.0 + 0.01}];
Export["CupratesMovie.gif", Join[T, Reverse[T]],
"AnimationRepetitions" -> Infinity]