def diquark(Q1, Q2):
eps = g.epsilon(Q1.otype.shape[2])
R = g.lattice(Q1)
# D_{a2,a1} = epsilon_{a1,b1,c1}*epsilon_{a2,b2,c2}*spin_transpose(Q1_{b1,b2})*Q2_{c1,c2}
Q1 = g.separate_color(Q1)
Q2 = g.separate_color(Q2)
D = {x: g.lattice(Q1[x]) for x in Q1}
for d in D:
D[d][:] = 0
for i1, sign1 in eps:
for i2, sign2 in eps:
D[i2[0], i1[0]] += (sign1 * sign2 * Q1[i1[1], i2[1]] *
g.transpose(Q2[i1[2], i2[2]]))
g.merge_color(R, D)
return R
def transpose(self):
if not self.transposable():
return gpt.transpose(gpt.expr(self))
return tensor(np.transpose(self.array, self.otype.transposed),
self.otype)
mc[:] = mc_comp vc_comp = g.vcomplex([rng.cnormal() for i in range(ntest)], ntest) vc = g.vcomplex(grid, ntest) vc[:] = vc_comp assert g.norm2(mc[0, 0, 0, 0] - mc_comp) < 1e-10 vc2 = g.eval(mc * vc) vc2_comp = mc_comp * vc_comp vc3 = g.eval(mc_comp * vc) assert g.norm2(vc2[0, 0, 0, 0] - vc2_comp) < 1e-10 eps2 = g.norm2(vc2 - vc3) / g.norm2(vc2) assert eps2 < 1e-10 # test transpose and adjoint of mcomplex mc_adj = g.eval(g.adj(mc)) mc_transpose = g.eval(g.transpose(mc)) mc_array = mc[0, 0, 0, 0].array mc_adj_array = mc_adj[0, 0, 0, 0].array mc_transpose_array = mc_transpose[0, 0, 0, 0].array assert np.linalg.norm(mc_adj_array - mc_array.transpose().conjugate()) < 1e-13 assert np.linalg.norm(mc_transpose_array - mc_array.transpose()) < 1e-13 assert g.norm2(g.adj(mc[0, 0, 0, 0]) - mc_adj[0, 0, 0, 0]) < 1e-25 assert g.norm2(g.transpose(mc[0, 0, 0, 0]) - mc_transpose[0, 0, 0, 0]) < 1e-25 # assign entire lattice cm = g.mcolor(grid) cv = g.vcolor(grid) cv[:] = 0 cm[:] = 0 # assign position and tensor index
g.message(g.trace(g.mspincolor(gr)[0, 0, 0, 0]))
# Expression including numpy array
r = g.eval(u * U[0] + U[1] * u)
g.message(g.norm2(r))
# test inner and outer products
v = g.vspincolor([[0, 0, 0], [0, 0, 2], [0, 0, 0], [0, 0, 0]])
w = g.vspincolor([[0, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0]])
xx = v * g.adj(w)
g.message(xx[1][3][2][0])
g.message(xx)
g.message(g.adj(v) * v)
g.message(g.transpose(v) * v)
u += g.adj(u)
g.message(u)
v = g.vspincolor([[1, 2, 3], [1, 2, 3], [1, 2, 3], [1, 2, 3]])
l = g.vspincolor(gr)
l[:] = 0
l[0, 0, 0, 0] = v
g.message(l)
for mu in [0, 1, 2, 3, 5]:
for nu in [0, 1, 2, 3, 5]:
g.message(
mu, nu,
