Exemple #1
0
def test_svd_compress(comp, mp):

    if mp == "mpo":
        mps = Mpo(holstein_model)
        M = 22
    else:
        mps = Mps.random(holstein_model, 1, 10)
        if mp == "mpdm":
            mps = MpDm.from_mps(mps)
        mps.canonicalise().normalize()
        M = 36
    if comp:
        mps = mps.to_complex(inplace=True)
    print(f"{mps}")

    mpo = Mpo(holstein_model)
    if comp:
        mpo = mpo.scale(-1.0j)
    print(f"{mpo.bond_dims}")

    std_mps = mpo.apply(mps, canonicalise=True).canonicalise()
    print(f"std_mps: {std_mps}")
    mps.compress_config.bond_dim_max_value = M
    mps.compress_config.criteria = CompressCriteria.fixed
    svd_mps = mpo.contract(mps)
    dis = svd_mps.distance(std_mps) / std_mps.dmrg_norm
    print(f"svd_mps: {svd_mps}, dis: {dis}")
    assert np.allclose(dis, 0.0, atol=1e-3)
    assert np.allclose(svd_mps.dmrg_norm, std_mps.dmrg_norm, atol=1e-4)
Exemple #2
0
def test_variational_compress(comp, mp):

    if mp == "mpo":
        mps = Mpo(holstein_model)
        M = 20
    else:
        mps = Mps.random(holstein_model, 1, 10)
        if mp == "mpdm":
            mps = MpDm.from_mps(mps)
        mps.canonicalise().normalize()
        M = 36
    if comp:
        mps = mps.to_complex(inplace=True)
    print(f"{mps}")

    mpo = Mpo(holstein_model)
    if comp:
        mpo = mpo.scale(-1.0j)
    print(f"{mpo.bond_dims}")

    std_mps = mpo.apply(mps, canonicalise=True).canonicalise()
    print(f"std_mps: {std_mps}")

    # 2site algorithm
    mps.compress_config.vprocedure = [[M, 1.0], [M, 0.2], [M, 0.1]] + [
        [M, 0],
    ] * 10
    mps.compress_config.vmethod = "2site"
    var_mps = mps.variational_compress(mpo, guess=None)
    dis = var_mps.distance(std_mps) / std_mps.dmrg_norm
    print(f"var2_mps: {var_mps}, dis: {dis}")
    assert np.allclose(dis, 0.0, atol=1e-4)
    assert np.allclose(var_mps.dmrg_norm, std_mps.dmrg_norm, atol=1e-4)

    # 1site algorithm with 2site result as a guess
    # 1site algorithm is easy to be trapped in a local minimum
    var_mps.compress_config.vprocedure = [
        [M, 0],
    ] * 10
    var_mps.compress_config.vmethod = "1site"
    var_mps = mps.variational_compress(mpo, guess=var_mps)
    dis = var_mps.distance(std_mps) / std_mps.dmrg_norm
    print(f"var1_mps: {var_mps}, dis: {dis}")
    assert np.allclose(dis, 0.0, atol=1e-4)
    assert np.allclose(var_mps.dmrg_norm, std_mps.dmrg_norm, atol=1e-4)