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""" Spin/chirality-resolved magnon splitting in a minimal d-wave altermagnetic model.
This script starts from a linear spin-wave Hamiltonian and diagonalizes the bosonic BdG dynamical matrices.
Output: All figures are saved as PNG only in
magnon_altermagnet_results/figures/
Main plots: 01_spin_resolved_magnon_bands.png Spin/chirality-resolved magnon bands along Gamma-X-M-Gamma.
02_chiral_splitting_path.png Splitting omega_+ - omega_- along Gamma-X-M-Gamma.
03_chiral_splitting_map.png d-wave splitting map in the 2D Brillouin zone.
04_near_gamma_spin_split_dispersion.png Near-Gamma split dispersion shown on a combined axis: left side -> Gamma to X (q_y = 0, displayed as q_x side) right side -> Gamma to Y (q_x = 0, displayed as q_y side) Only the two split branches are plotted, so the sign reversal of the d-wave splitting becomes visually clear.
Model: A and B sublattices form a compensated collinear AFM. Nearest-neighbor A-B exchange is antiferromagnetic: J1 > 0. Same-sublattice exchange is treated as spin stiffness and is anisotropic. The anisotropy pattern on B is rotated by 90 degrees relative to A.
Linear spin-wave Hamiltonian:
H_sw = E0 + sum_q [ A_A(q) a_q^† a_q + A_B(q) b_q^† b_q + B(q) (a_q b_-q + a_q^† b_-q^†) ]
with
A_A(q) = z J1 S + 2 S [K_Ax (1 - cos qx) + K_Ay (1 - cos qy)] + h_gap
A_B(q) = z J1 S + 2 S [K_Bx (1 - cos qx) + K_By (1 - cos qy)] + h_gap
B(q) = z J1 S gamma_q
gamma_q = (cos qx + cos qy) / 2
d-wave altermagnetic exchange pattern:
K_Ax = K0 + dK, K_Ay = K0 - dK K_Bx = K0 - dK, K_By = K0 + dK
Then
omega_+(q) - omega_-(q) is proportional to cos(qy) - cos(qx),
which is the d-wave chiral magnon splitting. """
from pathlib import Path import numpy as np import matplotlib.pyplot as plt from matplotlib.ticker import MaxNLocator
OUT_DIR = Path("magnon_altermagnet_results") FIG_DIR = OUT_DIR / "figures" FIG_DIR.mkdir(parents=True, exist_ok=True)
USE_TEX = False
FONT_SIZE = 16 LINE_WIDTH = 2.5 AXIS_WIDTH = 1.0 DPI = 300
plt.rcParams.update({ "text.usetex": USE_TEX, "font.family": "serif", "font.serif": ["Times New Roman", "Times", "DejaVu Serif"], "mathtext.fontset": "stix", "font.size": FONT_SIZE, "axes.labelsize": FONT_SIZE, "axes.titlesize": FONT_SIZE, "xtick.labelsize": FONT_SIZE - 2, "ytick.labelsize": FONT_SIZE - 2, "legend.fontsize": FONT_SIZE - 4, "axes.linewidth": AXIS_WIDTH, "xtick.direction": "in", "ytick.direction": "in", "xtick.top": True, "ytick.right": True, "savefig.bbox": "tight", "savefig.dpi": DPI, })
S = 1.0 J1 = 1.0 K0 = 0.25 dK = 0.14 h_gap = 0.00 a_lat = 1.0 z = 4
QMAX_GAMMA = 1.10 N_GAMMA = 601
COLOR_PLUS = "#0072B2" COLOR_MINUS = "#D55E00" COLOR_SPLIT = "#009E73" COLOR_ZERO = "0.35"
LS_PLUS = "-" LS_MINUS = "--"
def set_max_three_ticks(ax, x=True, y=True): """ Limit major ticks to at most three. Do not use this on the high-symmetry path x-axis. """ if x: ax.xaxis.set_major_locator(MaxNLocator(nbins=3)) if y: ax.yaxis.set_major_locator(MaxNLocator(nbins=3))
def savefig(fig, name): """ Save PNG only. """ png_path = FIG_DIR / f"{name}.png" fig.savefig(png_path, dpi=DPI) print(f"Saved: {png_path}")
def positive_eigenvalue(matrix): """ Return the positive bosonic BdG eigenvalue from the dynamical matrix. """ evals = np.linalg.eigvals(matrix) evals = np.real_if_close(evals, tol=1000).real
positive = evals[evals >= -1e-10] if len(positive) == 0: return np.max(evals)
return np.max(positive)
def exchange_parameters(K0=K0, dK=dK): """ d-wave altermagnetic exchange-stiffness pattern: A sublattice: stronger stiffness along x B sublattice: stronger stiffness along y """ K_Ax = K0 + dK K_Ay = K0 - dK K_Bx = K0 - dK K_By = K0 + dK return K_Ax, K_Ay, K_Bx, K_By
def coefficients(qx, qy, S=S, J1=J1, K0=K0, dK=dK, h_gap=h_gap): """ Return A_A(q), A_B(q), B(q), A0(q), deltaA(q), gamma(q). q values are dimensionless if a_lat = 1. """ K_Ax, K_Ay, K_Bx, K_By = exchange_parameters(K0, dK)
cx = np.cos(qx * a_lat) cy = np.cos(qy * a_lat)
gamma = 0.5 * (cx + cy)
AA = ( z * J1 * S + h_gap + 2.0 * S * (K_Ax * (1.0 - cx) + K_Ay * (1.0 - cy)) )
AB = ( z * J1 * S + h_gap + 2.0 * S * (K_Bx * (1.0 - cx) + K_By * (1.0 - cy)) )
B = z * J1 * S * gamma
A0 = 0.5 * (AA + AB) deltaA = 0.5 * (AA - AB)
return AA, AB, B, A0, deltaA, gamma
def dynamic_matrix_plus(qx, qy): """ Bosonic dynamical matrix for the Nambu block: Psi_+ = (a_q, b_-q^†)^T """ AA, AB, B, _, _, _ = coefficients(qx, qy) return np.array([[AA, B], [-B, -AB]], dtype=float)
def dynamic_matrix_minus(qx, qy): """ Bosonic dynamical matrix for the Nambu block: Psi_- = (b_q, a_-q^†)^T """ AA, AB, B, _, _, _ = coefficients(qx, qy) return np.array([[AB, B], [-B, -AA]], dtype=float)
def magnon_energies(qx, qy): """ Diagonalize the two bosonic BdG dynamical matrices.
Returns omega_plus, omega_minus, spin_plus, spin_minus """ omega_plus = positive_eigenvalue(dynamic_matrix_plus(qx, qy)) omega_minus = positive_eigenvalue(dynamic_matrix_minus(qx, qy))
spin_plus = +1.0 spin_minus = -1.0
return omega_plus, omega_minus, spin_plus, spin_minus
def interpolate_path(points, n_per_segment=240): """ Return kpts, xcoord, xticks for a piecewise linear path. """ kpts = [] xcoord = [] xticks = [0.0] total = 0.0
for iseg in range(len(points) - 1): start = np.array(points[iseg], dtype=float) end = np.array(points[iseg + 1], dtype=float)
for j in range(n_per_segment): t = j / n_per_segment q = (1.0 - t) * start + t * end
if kpts: total += np.linalg.norm(q - kpts[-1])
kpts.append(q) xcoord.append(total)
xticks.append(total + np.linalg.norm(end - kpts[-1]))
kpts.append(np.array(points[-1], dtype=float)) total += np.linalg.norm(kpts[-1] - kpts[-2]) xcoord.append(total) xticks[-1] = total
return np.array(kpts), np.array(xcoord), xticks
def compute_high_symmetry_bands(): Gamma = (0.0, 0.0) X = (np.pi, 0.0) M = (np.pi, np.pi)
kpts, xcoord, xticks = interpolate_path([Gamma, X, M, Gamma], n_per_segment=240)
omega_p = np.zeros(len(kpts)) omega_m = np.zeros(len(kpts))
for i, (qx, qy) in enumerate(kpts): omega_p[i], omega_m[i], _, _ = magnon_energies(qx, qy)
return kpts, xcoord, xticks, omega_p, omega_m
def plot_spin_resolved_bands(): _, xcoord, xticks, omega_p, omega_m = compute_high_symmetry_bands()
fig, ax = plt.subplots(figsize=(5.4, 4.0))
ax.plot( xcoord, omega_p, color=COLOR_PLUS, lw=LINE_WIDTH, ls=LS_PLUS, label=r"$s_{\mathrm{m}}=+\hbar$", ) ax.plot( xcoord, omega_m, color=COLOR_MINUS, lw=LINE_WIDTH, ls=LS_MINUS, label=r"$s_{\mathrm{m}}=-\hbar$", )
for x in xticks: ax.axvline(x, color="0.75", lw=0.8, ls="--", zorder=0)
ax.set_xlim(xcoord[0], xcoord[-1]) ax.set_xticks(xticks) ax.set_xticklabels([r"$\Gamma$", r"$X$", r"$M$", r"$\Gamma$"]) ax.set_ylabel(r"$\hbar\omega_{\mathbf{q}}$") ax.legend(frameon=False, loc="best")
set_max_three_ticks(ax, x=False, y=True)
fig.tight_layout() savefig(fig, "01_spin_resolved_magnon_bands") plt.close(fig)
def plot_splitting_along_path(): _, xcoord, xticks, omega_p, omega_m = compute_high_symmetry_bands() split = omega_p - omega_m
fig, ax = plt.subplots(figsize=(5.4, 3.6))
ax.plot(xcoord, split, color=COLOR_SPLIT, lw=LINE_WIDTH, ls="-") ax.axhline(0.0, color=COLOR_ZERO, lw=0.9, ls="--", zorder=0)
for x in xticks: ax.axvline(x, color="0.75", lw=0.8, ls="--", zorder=0)
ax.set_xlim(xcoord[0], xcoord[-1]) ax.set_xticks(xticks) ax.set_xticklabels([r"$\Gamma$", r"$X$", r"$M$", r"$\Gamma$"]) ax.set_ylabel(r"$\omega_{+}-\omega_{-}$")
set_max_three_ticks(ax, x=False, y=True)
fig.tight_layout() savefig(fig, "02_chiral_splitting_path") plt.close(fig)
def plot_splitting_map(nk=301): q = np.linspace(-np.pi, np.pi, nk) qx_grid, qy_grid = np.meshgrid(q, q, indexing="xy")
split = np.zeros_like(qx_grid)
for ix in range(nk): for iy in range(nk): op, om, _, _ = magnon_energies(qx_grid[iy, ix], qy_grid[iy, ix]) split[iy, ix] = op - om
vmax = np.max(np.abs(split)) if vmax < 1e-12: vmax = 1.0
fig, ax = plt.subplots(figsize=(4.8, 4.0))
im = ax.imshow( split, origin="lower", extent=(-np.pi, np.pi, -np.pi, np.pi), cmap="RdBu_r", vmin=-vmax, vmax=vmax, interpolation="bicubic", aspect="equal", )
ax.set_xlabel(r"$q_x$") ax.set_ylabel(r"$q_y$")
ax.set_xticks([-np.pi, 0.0, np.pi]) ax.set_xticklabels([r"$-\pi$", r"$0$", r"$\pi$"]) ax.set_yticks([-np.pi, 0.0, np.pi]) ax.set_yticklabels([r"$-\pi$", r"$0$", r"$\pi$"])
cbar = fig.colorbar(im, ax=ax, shrink=0.82, pad=0.03) cbar.set_label(r"$\omega_{+}-\omega_{-}$") cbar.locator = MaxNLocator(nbins=3) cbar.update_ticks()
fig.tight_layout() savefig(fig, "03_chiral_splitting_map") plt.close(fig)
def plot_near_gamma_split_dispersion(qmax=QMAX_GAMMA, nq=N_GAMMA): """ Build a combined near-Gamma axis: x < 0 : Gamma -> X direction, with q = (|x|, 0) x > 0 : Gamma -> Y direction, with q = (0, x)
Only the two split branches are plotted. This makes the sign reversal of the d-wave splitting between qx and qy directions clearly visible. """ x = np.linspace(-qmax, qmax, nq)
omega_p = np.zeros_like(x) omega_m = np.zeros_like(x)
for i, xx in enumerate(x): if xx < 0: qx = -xx qy = 0.0 else: qx = 0.0 qy = xx
omega_p[i], omega_m[i], _, _ = magnon_energies(qx, qy)
fig, ax = plt.subplots(figsize=(5.4, 4.0))
ax.plot( x, omega_p, color=COLOR_PLUS, lw=LINE_WIDTH, ls=LS_PLUS, label=r"$s_{\mathrm{m}}=+\hbar$", ) ax.plot( x, omega_m, color=COLOR_MINUS, lw=LINE_WIDTH, ls=LS_MINUS, label=r"$s_{\mathrm{m}}=-\hbar$", )
ax.axvline(0.0, color="0.75", lw=0.9, ls="--", zorder=0)
ax.set_xlim(-qmax, qmax) ax.set_xticks([-qmax, 0.0, qmax]) ax.set_xticklabels([r"$q_x$", r"$\Gamma$", r"$q_y$"])
ax.set_ylabel(r"$\hbar\omega_{\mathbf{q}}$") ax.legend(frameon=False, loc="best")
set_max_three_ticks(ax, x=False, y=True)
fig.tight_layout() savefig(fig, "04_near_gamma_spin_split_dispersion") plt.close(fig)
def print_model_summary(): K_Ax, K_Ay, K_Bx, K_By = exchange_parameters(K0, dK)
print("\nMinimal d-wave altermagnetic magnon model") print("==========================================") print(f"S = {S}") print(f"J1 = {J1}") print(f"K0 = {K0}") print(f"dK = {dK}") print(f"h_gap = {h_gap}") print("") print("Same-sublattice exchange pattern:") print(f"K_Ax = {K_Ax:.6f}, K_Ay = {K_Ay:.6f}") print(f"K_Bx = {K_Bx:.6f}, K_By = {K_By:.6f}") print("") print("Expected d-wave splitting:") print("omega_+(q) - omega_-(q) ∝ cos(q_y) - cos(q_x)") print("") print("Near-Gamma plot:") print("left side = q_x direction (q_y = 0)") print("right side = q_y direction (q_x = 0)") print("") print(f"Figures saved to: {FIG_DIR.resolve()}")
def main(): print_model_summary()
plot_spin_resolved_bands() plot_splitting_along_path() plot_splitting_map(nk=301) plot_near_gamma_split_dispersion(qmax=QMAX_GAMMA, nq=N_GAMMA)
print("\nDone.")
if __name__ == "__main__": main()
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