{ "cells": [ { "cell_type": "markdown", "id": "43da1168-b444-4dd6-b0cb-40d2ea7d819f", "metadata": {}, "source": [ "(real-time-simple-update)=\n", "\n", "# Real time simple update (SU)" ] }, { "cell_type": "code", "execution_count": 1, "id": "20a665ab-9aef-4e19-b3e2-168fd53c77c2", "metadata": {}, "outputs": [], "source": [ "%config InlineBackend.figure_formats = ['svg']\n", "import autoray as ar\n", "import matplotlib as mpl\n", "import matplotlib.pyplot as plt\n", "import tqdm # for progress bar\n", "\n", "import quimb as qu\n", "import quimb.tensor as qtn\n", "\n", "mpl.style.use(qu.NEUTRAL_STYLE)" ] }, { "cell_type": "code", "execution_count": 2, "id": "4ddbbf97-1c89-4cce-8eac-dfb3d1bda235", "metadata": {}, "outputs": [], "source": [ "Lx = 11\n", "Ly = 11\n", "\n", "edges = qtn.edges_2d_square(Lx, Ly, cyclic=False)\n", "sites = sorted({s for e in edges for s in e})\n", "\n", "# heisenberg interaction\n", "h2 = -qu.pauli(\"X\") & qu.pauli(\"X\")\n", "# quenched random onsite z-fields\n", "h1 = -3.04438 * qu.pauli(\"Z\")" ] }, { "cell_type": "code", "execution_count": 3, "id": "74f52899-8450-4cb6-8960-5eaba3dd20f2", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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Tensor(shape=(1, 1, 1, 2), inds=[_3a1604AAAAF, _3a1604AAAAE, _3a1604AAAAC, k(0, 2)], tags={I(0, 2)}),backend=numpy, dtype=float64, data=array([[[[1., 0.]]]])
Tensor(shape=(1, 1, 1, 2), inds=[_3a1604AAAAH, _3a1604AAAAG, _3a1604AAAAE, k(0, 3)], tags={I(0, 3)}),backend=numpy, dtype=float64, data=array([[[[1., 0.]]]])
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Tensor(shape=(1, 1, 1, 2), inds=[_3a1604AAAAp, _3a1604AAAAn, _3a1604AAAAU, k(1, 10)], tags={I(1, 10)}),backend=numpy, dtype=float64, data=array([[[[1., 0.]]]])
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Tensor(shape=(1, 1, 1, 1, 2), inds=[_3a1604AAAAx, _3a1604AAAAw, _3a1604AAAAu, _3a1604AAAAc, k(2, 3)], tags={I(2, 3)}),backend=numpy, dtype=float64, data=array([[[[[1., 0.]]]]])
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Tensor(shape=(1, 1, 1, 1, 2), inds=[_3a1604AAABB, _3a1604AAABA, _3a1604AAAAy, _3a1604AAAAg, k(2, 5)], tags={I(2, 5)}),backend=numpy, dtype=float64, data=array([[[[[1., 0.]]]]])
Tensor(shape=(1, 1, 1, 1, 2), inds=[_3a1604AAABD, _3a1604AAABC, _3a1604AAABA, _3a1604AAAAi, k(2, 6)], tags={I(2, 6)}),backend=numpy, dtype=float64, data=array([[[[[1., 0.]]]]])
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Tensor(shape=(1, 1, 1, 1, 2), inds=[_3a1604AAABH, _3a1604AAABG, _3a1604AAABE, _3a1604AAAAm, k(2, 8)], tags={I(2, 8)}),backend=numpy, dtype=float64, data=array([[[[[1., 0.]]]]])
Tensor(shape=(1, 1, 1, 1, 2), inds=[_3a1604AAABJ, _3a1604AAABI, _3a1604AAABG, _3a1604AAAAo, k(2, 9)], tags={I(2, 9)}),backend=numpy, dtype=float64, data=array([[[[[1., 0.]]]]])
Tensor(shape=(1, 1, 1, 2), inds=[_3a1604AAABK, _3a1604AAABI, _3a1604AAAAp, k(2, 10)], tags={I(2, 10)}),backend=numpy, dtype=float64, data=array([[[[1., 0.]]]])
Tensor(shape=(1, 1, 1, 2), inds=[_3a1604AAABM, _3a1604AAABL, _3a1604AAAAr, k(3, 0)], tags={I(3, 0)}),backend=numpy, dtype=float64, data=array([[[[1., 0.]]]])
Tensor(shape=(1, 1, 1, 1, 2), inds=[_3a1604AAABO, _3a1604AAABN, _3a1604AAABL, _3a1604AAAAt, k(3, 1)], tags={I(3, 1)}),backend=numpy, dtype=float64, data=array([[[[[1., 0.]]]]])
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Tensor(shape=(1, 1, 1, 1, 2), inds=[_3a1604AAABS, _3a1604AAABR, _3a1604AAABP, _3a1604AAAAx, k(3, 3)], tags={I(3, 3)}),backend=numpy, dtype=float64, data=array([[[[[1., 0.]]]]])
Tensor(shape=(1, 1, 1, 1, 2), inds=[_3a1604AAABU, _3a1604AAABT, _3a1604AAABR, _3a1604AAAAz, k(3, 4)], tags={I(3, 4)}),backend=numpy, dtype=float64, data=array([[[[[1., 0.]]]]])
Tensor(shape=(1, 1, 1, 1, 2), inds=[_3a1604AAABW, _3a1604AAABV, _3a1604AAABT, _3a1604AAABB, k(3, 5)], tags={I(3, 5)}),backend=numpy, dtype=float64, data=array([[[[[1., 0.]]]]])
Tensor(shape=(1, 1, 1, 1, 2), inds=[_3a1604AAABY, _3a1604AAABX, _3a1604AAABV, _3a1604AAABD, k(3, 6)], tags={I(3, 6)}),backend=numpy, dtype=float64, data=array([[[[[1., 0.]]]]])
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Tensor(shape=(1, 1, 1, 1, 2), inds=[_3a1604AAABc, _3a1604AAABb, _3a1604AAABZ, _3a1604AAABH, k(3, 8)], tags={I(3, 8)}),backend=numpy, dtype=float64, data=array([[[[[1., 0.]]]]])
Tensor(shape=(1, 1, 1, 1, 2), inds=[_3a1604AAABe, _3a1604AAABd, _3a1604AAABb, _3a1604AAABJ, k(3, 9)], tags={I(3, 9)}),backend=numpy, dtype=float64, data=array([[[[[1., 0.]]]]])
Tensor(shape=(1, 1, 1, 2), inds=[_3a1604AAABf, _3a1604AAABd, _3a1604AAABK, k(3, 10)], tags={I(3, 10)}),backend=numpy, dtype=float64, data=array([[[[1., 0.]]]])
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Tensor(shape=(1, 1, 1, 1, 2), inds=[_3a1604AAABj, _3a1604AAABi, _3a1604AAABg, _3a1604AAABO, k(4, 1)], tags={I(4, 1)}),backend=numpy, dtype=float64, data=array([[[[[1., 0.]]]]])
Tensor(shape=(1, 1, 1, 1, 2), inds=[_3a1604AAABl, _3a1604AAABk, _3a1604AAABi, _3a1604AAABQ, k(4, 2)], tags={I(4, 2)}),backend=numpy, dtype=float64, data=array([[[[[1., 0.]]]]])
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Tensor(shape=(1, 1, 1, 1, 2), inds=[_3a1604AAABr, _3a1604AAABq, _3a1604AAABo, _3a1604AAABW, k(4, 5)], tags={I(4, 5)}),backend=numpy, dtype=float64, data=array([[[[[1., 0.]]]]])
Tensor(shape=(1, 1, 1, 1, 2), inds=[_3a1604AAABt, _3a1604AAABs, _3a1604AAABq, _3a1604AAABY, k(4, 6)], tags={I(4, 6)}),backend=numpy, dtype=float64, data=array([[[[[1., 0.]]]]])
Tensor(shape=(1, 1, 1, 1, 2), inds=[_3a1604AAABv, _3a1604AAABu, _3a1604AAABs, _3a1604AAABa, k(4, 7)], tags={I(4, 7)}),backend=numpy, dtype=float64, data=array([[[[[1., 0.]]]]])
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Tensor(shape=(1, 1, 1, 1, 2), inds=[_3a1604AAACG, _3a1604AAACF, _3a1604AAACD, _3a1604AAABl, k(5, 2)], tags={I(5, 2)}),backend=numpy, dtype=float64, data=array([[[[[1., 0.]]]]])
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Tensor(shape=(1, 1, 1, 1, 2), inds=[_3a1604AAADI, _3a1604AAADH, _3a1604AAADF, _3a1604AAACn, k(7, 8)], tags={I(7, 8)}),backend=numpy, dtype=float64, data=array([[[[[1., 0.]]]]])
Tensor(shape=(1, 1, 1, 1, 2), inds=[_3a1604AAADK, _3a1604AAADJ, _3a1604AAADH, _3a1604AAACp, k(7, 9)], tags={I(7, 9)}),backend=numpy, dtype=float64, data=array([[[[[1., 0.]]]]])
Tensor(shape=(1, 1, 1, 2), inds=[_3a1604AAADL, _3a1604AAADJ, _3a1604AAACq, k(7, 10)], tags={I(7, 10)}),backend=numpy, dtype=float64, data=array([[[[1., 0.]]]])
Tensor(shape=(1, 1, 1, 2), inds=[_3a1604AAADN, _3a1604AAADM, _3a1604AAACs, k(8, 0)], tags={I(8, 0)}),backend=numpy, dtype=float64, data=array([[[[1., 0.]]]])
Tensor(shape=(1, 1, 1, 1, 2), inds=[_3a1604AAADP, _3a1604AAADO, _3a1604AAADM, _3a1604AAACu, k(8, 1)], tags={I(8, 1)}),backend=numpy, dtype=float64, data=array([[[[[1., 0.]]]]])
Tensor(shape=(1, 1, 1, 1, 2), inds=[_3a1604AAADR, _3a1604AAADQ, _3a1604AAADO, _3a1604AAACw, k(8, 2)], tags={I(8, 2)}),backend=numpy, dtype=float64, data=array([[[[[1., 0.]]]]])
Tensor(shape=(1, 1, 1, 1, 2), inds=[_3a1604AAADT, _3a1604AAADS, _3a1604AAADQ, _3a1604AAACy, k(8, 3)], tags={I(8, 3)}),backend=numpy, dtype=float64, data=array([[[[[1., 0.]]]]])
Tensor(shape=(1, 1, 1, 1, 2), inds=[_3a1604AAADV, _3a1604AAADU, _3a1604AAADS, _3a1604AAADA, k(8, 4)], tags={I(8, 4)}),backend=numpy, dtype=float64, data=array([[[[[1., 0.]]]]])
Tensor(shape=(1, 1, 1, 1, 2), inds=[_3a1604AAADX, _3a1604AAADW, _3a1604AAADU, _3a1604AAADC, k(8, 5)], tags={I(8, 5)}),backend=numpy, dtype=float64, data=array([[[[[1., 0.]]]]])
Tensor(shape=(1, 1, 1, 1, 2), inds=[_3a1604AAADZ, _3a1604AAADY, _3a1604AAADW, _3a1604AAADE, k(8, 6)], tags={I(8, 6)}),backend=numpy, dtype=float64, data=array([[[[[1., 0.]]]]])
Tensor(shape=(1, 1, 1, 1, 2), inds=[_3a1604AAADb, _3a1604AAADa, _3a1604AAADY, _3a1604AAADG, k(8, 7)], tags={I(8, 7)}),backend=numpy, dtype=float64, data=array([[[[[1., 0.]]]]])
Tensor(shape=(1, 1, 1, 1, 2), inds=[_3a1604AAADd, _3a1604AAADc, _3a1604AAADa, _3a1604AAADI, k(8, 8)], tags={I(8, 8)}),backend=numpy, dtype=float64, data=array([[[[[1., 0.]]]]])
Tensor(shape=(1, 1, 1, 1, 2), inds=[_3a1604AAADf, _3a1604AAADe, _3a1604AAADc, _3a1604AAADK, k(8, 9)], tags={I(8, 9)}),backend=numpy, dtype=float64, data=array([[[[[1., 0.]]]]])
Tensor(shape=(1, 1, 1, 2), inds=[_3a1604AAADg, _3a1604AAADe, _3a1604AAADL, k(8, 10)], tags={I(8, 10)}),backend=numpy, dtype=float64, data=array([[[[1., 0.]]]])
Tensor(shape=(1, 1, 1, 2), inds=[_3a1604AAADi, _3a1604AAADh, _3a1604AAADN, k(9, 0)], tags={I(9, 0)}),backend=numpy, dtype=float64, data=array([[[[1., 0.]]]])

...

" ], "text/plain": [ "TensorNetworkGenVector(tensors=121, indices=341)" ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# all zero-state\n", "psi = qtn.TN_from_sites_product_state(\n", " site_map={site: [1.0, 0.0] for site in sites}\n", ")\n", "\n", "# make size 1 lattice bonds\n", "for cooa, coob in edges:\n", " psi[cooa].new_bond(psi[coob])\n", "\n", "psi" ] }, { "cell_type": "code", "execution_count": 4, "id": "bceaa850-9f48-4268-b2d0-75e6774be13e", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
TensorNetworkGenVector(tensors=121, indices=341)
Tensor(shape=(1, 1, 2), inds=[_3a1604AAAAB, _3a1604AAAAA, k(0, 0)], tags={I(0, 0)}),backend=numpy, dtype=float64, data=array([[[1., 0.]]])
Tensor(shape=(1, 1, 1, 2), inds=[_3a1604AAAAD, _3a1604AAAAC, _3a1604AAAAA, k(0, 1)], tags={I(0, 1)}),backend=numpy, dtype=float64, data=array([[[[1., 0.]]]])
Tensor(shape=(1, 1, 1, 2), inds=[_3a1604AAAAF, _3a1604AAAAE, _3a1604AAAAC, k(0, 2)], tags={I(0, 2)}),backend=numpy, dtype=float64, data=array([[[[1., 0.]]]])
Tensor(shape=(1, 1, 1, 2), inds=[_3a1604AAAAH, _3a1604AAAAG, _3a1604AAAAE, k(0, 3)], tags={I(0, 3)}),backend=numpy, dtype=float64, data=array([[[[1., 0.]]]])
Tensor(shape=(1, 1, 1, 2), inds=[_3a1604AAAAJ, _3a1604AAAAI, _3a1604AAAAG, k(0, 4)], tags={I(0, 4)}),backend=numpy, dtype=float64, data=array([[[[1., 0.]]]])
Tensor(shape=(1, 1, 1, 2), inds=[_3a1604AAAAL, _3a1604AAAAK, _3a1604AAAAI, k(0, 5)], tags={I(0, 5)}),backend=numpy, dtype=float64, data=array([[[[1., 0.]]]])
Tensor(shape=(1, 1, 1, 2), inds=[_3a1604AAAAN, _3a1604AAAAM, _3a1604AAAAK, k(0, 6)], tags={I(0, 6)}),backend=numpy, dtype=float64, data=array([[[[1., 0.]]]])
Tensor(shape=(1, 1, 1, 2), inds=[_3a1604AAAAP, _3a1604AAAAO, _3a1604AAAAM, k(0, 7)], tags={I(0, 7)}),backend=numpy, dtype=float64, data=array([[[[1., 0.]]]])
Tensor(shape=(1, 1, 1, 2), inds=[_3a1604AAAAR, _3a1604AAAAQ, _3a1604AAAAO, k(0, 8)], tags={I(0, 8)}),backend=numpy, dtype=float64, data=array([[[[1., 0.]]]])
Tensor(shape=(1, 1, 1, 2), inds=[_3a1604AAAAT, _3a1604AAAAS, _3a1604AAAAQ, k(0, 9)], tags={I(0, 9)}),backend=numpy, dtype=float64, data=array([[[[1., 0.]]]])
Tensor(shape=(1, 1, 2), inds=[_3a1604AAAAU, _3a1604AAAAS, k(0, 10)], tags={I(0, 10)}),backend=numpy, dtype=float64, data=array([[[1., 0.]]])
Tensor(shape=(1, 1, 1, 2), inds=[_3a1604AAAAW, _3a1604AAAAV, _3a1604AAAAB, k(1, 0)], tags={I(1, 0)}),backend=numpy, dtype=float64, data=array([[[[1., 0.]]]])
Tensor(shape=(1, 1, 1, 1, 2), inds=[_3a1604AAAAY, _3a1604AAAAX, _3a1604AAAAV, _3a1604AAAAD, k(1, 1)], tags={I(1, 1)}),backend=numpy, dtype=float64, data=array([[[[[1., 0.]]]]])
Tensor(shape=(1, 1, 1, 1, 2), inds=[_3a1604AAAAa, _3a1604AAAAZ, _3a1604AAAAX, _3a1604AAAAF, k(1, 2)], tags={I(1, 2)}),backend=numpy, dtype=float64, data=array([[[[[1., 0.]]]]])
Tensor(shape=(1, 1, 1, 1, 2), inds=[_3a1604AAAAc, _3a1604AAAAb, _3a1604AAAAZ, _3a1604AAAAH, k(1, 3)], tags={I(1, 3)}),backend=numpy, dtype=float64, data=array([[[[[1., 0.]]]]])
Tensor(shape=(1, 1, 1, 1, 2), inds=[_3a1604AAAAe, _3a1604AAAAd, _3a1604AAAAb, _3a1604AAAAJ, k(1, 4)], tags={I(1, 4)}),backend=numpy, dtype=float64, data=array([[[[[1., 0.]]]]])
Tensor(shape=(1, 1, 1, 1, 2), inds=[_3a1604AAAAg, _3a1604AAAAf, _3a1604AAAAd, _3a1604AAAAL, k(1, 5)], tags={I(1, 5)}),backend=numpy, dtype=float64, data=array([[[[[1., 0.]]]]])
Tensor(shape=(1, 1, 1, 1, 2), inds=[_3a1604AAAAi, _3a1604AAAAh, _3a1604AAAAf, _3a1604AAAAN, k(1, 6)], tags={I(1, 6)}),backend=numpy, dtype=float64, data=array([[[[[1., 0.]]]]])
Tensor(shape=(1, 1, 1, 1, 2), inds=[_3a1604AAAAk, _3a1604AAAAj, _3a1604AAAAh, _3a1604AAAAP, k(1, 7)], tags={I(1, 7)}),backend=numpy, dtype=float64, data=array([[[[[1., 0.]]]]])
Tensor(shape=(1, 1, 1, 1, 2), inds=[_3a1604AAAAm, _3a1604AAAAl, _3a1604AAAAj, _3a1604AAAAR, k(1, 8)], tags={I(1, 8)}),backend=numpy, dtype=float64, data=array([[[[[1., 0.]]]]])
Tensor(shape=(1, 1, 1, 1, 2), inds=[_3a1604AAAAo, _3a1604AAAAn, _3a1604AAAAl, _3a1604AAAAT, k(1, 9)], tags={I(1, 9)}),backend=numpy, dtype=float64, data=array([[[[[1., 0.]]]]])
Tensor(shape=(1, 1, 1, 2), inds=[_3a1604AAAAp, _3a1604AAAAn, _3a1604AAAAU, k(1, 10)], tags={I(1, 10)}),backend=numpy, dtype=float64, data=array([[[[1., 0.]]]])
Tensor(shape=(1, 1, 1, 2), inds=[_3a1604AAAAr, _3a1604AAAAq, _3a1604AAAAW, k(2, 0)], tags={I(2, 0)}),backend=numpy, dtype=float64, data=array([[[[1., 0.]]]])
Tensor(shape=(1, 1, 1, 1, 2), inds=[_3a1604AAAAt, _3a1604AAAAs, _3a1604AAAAq, _3a1604AAAAY, k(2, 1)], tags={I(2, 1)}),backend=numpy, dtype=float64, data=array([[[[[1., 0.]]]]])
Tensor(shape=(1, 1, 1, 1, 2), inds=[_3a1604AAAAv, _3a1604AAAAu, _3a1604AAAAs, _3a1604AAAAa, k(2, 2)], tags={I(2, 2)}),backend=numpy, dtype=float64, data=array([[[[[1., 0.]]]]])
Tensor(shape=(1, 1, 1, 1, 2), inds=[_3a1604AAAAx, _3a1604AAAAw, _3a1604AAAAu, _3a1604AAAAc, k(2, 3)], tags={I(2, 3)}),backend=numpy, dtype=float64, data=array([[[[[1., 0.]]]]])
Tensor(shape=(1, 1, 1, 1, 2), inds=[_3a1604AAAAz, _3a1604AAAAy, _3a1604AAAAw, _3a1604AAAAe, k(2, 4)], tags={I(2, 4)}),backend=numpy, dtype=float64, data=array([[[[[1., 0.]]]]])
Tensor(shape=(1, 1, 1, 1, 2), inds=[_3a1604AAABB, _3a1604AAABA, _3a1604AAAAy, _3a1604AAAAg, k(2, 5)], tags={I(2, 5)}),backend=numpy, dtype=float64, data=array([[[[[1., 0.]]]]])
Tensor(shape=(1, 1, 1, 1, 2), inds=[_3a1604AAABD, _3a1604AAABC, _3a1604AAABA, _3a1604AAAAi, k(2, 6)], tags={I(2, 6)}),backend=numpy, dtype=float64, data=array([[[[[1., 0.]]]]])
Tensor(shape=(1, 1, 1, 1, 2), inds=[_3a1604AAABF, _3a1604AAABE, _3a1604AAABC, _3a1604AAAAk, k(2, 7)], tags={I(2, 7)}),backend=numpy, dtype=float64, data=array([[[[[1., 0.]]]]])
Tensor(shape=(1, 1, 1, 1, 2), inds=[_3a1604AAABH, _3a1604AAABG, _3a1604AAABE, _3a1604AAAAm, k(2, 8)], tags={I(2, 8)}),backend=numpy, dtype=float64, data=array([[[[[1., 0.]]]]])
Tensor(shape=(1, 1, 1, 1, 2), inds=[_3a1604AAABJ, _3a1604AAABI, _3a1604AAABG, _3a1604AAAAo, k(2, 9)], tags={I(2, 9)}),backend=numpy, dtype=float64, data=array([[[[[1., 0.]]]]])
Tensor(shape=(1, 1, 1, 2), inds=[_3a1604AAABK, _3a1604AAABI, _3a1604AAAAp, k(2, 10)], tags={I(2, 10)}),backend=numpy, dtype=float64, data=array([[[[1., 0.]]]])
Tensor(shape=(1, 1, 1, 2), inds=[_3a1604AAABM, _3a1604AAABL, _3a1604AAAAr, k(3, 0)], tags={I(3, 0)}),backend=numpy, dtype=float64, data=array([[[[1., 0.]]]])
Tensor(shape=(1, 1, 1, 1, 2), inds=[_3a1604AAABO, _3a1604AAABN, _3a1604AAABL, _3a1604AAAAt, k(3, 1)], tags={I(3, 1)}),backend=numpy, dtype=float64, data=array([[[[[1., 0.]]]]])
Tensor(shape=(1, 1, 1, 1, 2), inds=[_3a1604AAABQ, _3a1604AAABP, _3a1604AAABN, _3a1604AAAAv, k(3, 2)], tags={I(3, 2)}),backend=numpy, dtype=float64, data=array([[[[[1., 0.]]]]])
Tensor(shape=(1, 1, 1, 1, 2), inds=[_3a1604AAABS, _3a1604AAABR, _3a1604AAABP, _3a1604AAAAx, k(3, 3)], tags={I(3, 3)}),backend=numpy, dtype=float64, data=array([[[[[1., 0.]]]]])
Tensor(shape=(1, 1, 1, 1, 2), inds=[_3a1604AAABU, _3a1604AAABT, _3a1604AAABR, _3a1604AAAAz, k(3, 4)], tags={I(3, 4)}),backend=numpy, dtype=float64, data=array([[[[[1., 0.]]]]])
Tensor(shape=(1, 1, 1, 1, 2), inds=[_3a1604AAABW, _3a1604AAABV, _3a1604AAABT, _3a1604AAABB, k(3, 5)], tags={I(3, 5)}),backend=numpy, dtype=float64, data=array([[[[[1., 0.]]]]])
Tensor(shape=(1, 1, 1, 1, 2), inds=[_3a1604AAABY, _3a1604AAABX, _3a1604AAABV, _3a1604AAABD, k(3, 6)], tags={I(3, 6)}),backend=numpy, dtype=float64, data=array([[[[[1., 0.]]]]])
Tensor(shape=(1, 1, 1, 1, 2), inds=[_3a1604AAABa, _3a1604AAABZ, _3a1604AAABX, _3a1604AAABF, k(3, 7)], tags={I(3, 7)}),backend=numpy, dtype=float64, data=array([[[[[1., 0.]]]]])
Tensor(shape=(1, 1, 1, 1, 2), inds=[_3a1604AAABc, _3a1604AAABb, _3a1604AAABZ, _3a1604AAABH, k(3, 8)], tags={I(3, 8)}),backend=numpy, dtype=float64, data=array([[[[[1., 0.]]]]])
Tensor(shape=(1, 1, 1, 1, 2), inds=[_3a1604AAABe, _3a1604AAABd, _3a1604AAABb, _3a1604AAABJ, k(3, 9)], tags={I(3, 9)}),backend=numpy, dtype=float64, data=array([[[[[1., 0.]]]]])
Tensor(shape=(1, 1, 1, 2), inds=[_3a1604AAABf, _3a1604AAABd, _3a1604AAABK, k(3, 10)], tags={I(3, 10)}),backend=numpy, dtype=float64, data=array([[[[1., 0.]]]])
Tensor(shape=(1, 1, 1, 2), inds=[_3a1604AAABh, _3a1604AAABg, _3a1604AAABM, k(4, 0)], tags={I(4, 0)}),backend=numpy, dtype=float64, data=array([[[[1., 0.]]]])
Tensor(shape=(1, 1, 1, 1, 2), inds=[_3a1604AAABj, _3a1604AAABi, _3a1604AAABg, _3a1604AAABO, k(4, 1)], tags={I(4, 1)}),backend=numpy, dtype=float64, data=array([[[[[1., 0.]]]]])
Tensor(shape=(1, 1, 1, 1, 2), inds=[_3a1604AAABl, _3a1604AAABk, _3a1604AAABi, _3a1604AAABQ, k(4, 2)], tags={I(4, 2)}),backend=numpy, dtype=float64, data=array([[[[[1., 0.]]]]])
Tensor(shape=(1, 1, 1, 1, 2), inds=[_3a1604AAABn, _3a1604AAABm, _3a1604AAABk, _3a1604AAABS, k(4, 3)], tags={I(4, 3)}),backend=numpy, dtype=float64, data=array([[[[[1., 0.]]]]])
Tensor(shape=(1, 1, 1, 1, 2), inds=[_3a1604AAABp, _3a1604AAABo, _3a1604AAABm, _3a1604AAABU, k(4, 4)], tags={I(4, 4)}),backend=numpy, dtype=float64, data=array([[[[[1., 0.]]]]])
Tensor(shape=(1, 1, 1, 1, 2), inds=[_3a1604AAABr, _3a1604AAABq, _3a1604AAABo, _3a1604AAABW, k(4, 5)], tags={I(4, 5)}),backend=numpy, dtype=float64, data=array([[[[[1., 0.]]]]])
Tensor(shape=(1, 1, 1, 1, 2), inds=[_3a1604AAABt, _3a1604AAABs, _3a1604AAABq, _3a1604AAABY, k(4, 6)], tags={I(4, 6)}),backend=numpy, dtype=float64, data=array([[[[[1., 0.]]]]])
Tensor(shape=(1, 1, 1, 1, 2), inds=[_3a1604AAABv, _3a1604AAABu, _3a1604AAABs, _3a1604AAABa, k(4, 7)], tags={I(4, 7)}),backend=numpy, dtype=float64, data=array([[[[[1., 0.]]]]])
Tensor(shape=(1, 1, 1, 1, 2), inds=[_3a1604AAABx, _3a1604AAABw, _3a1604AAABu, _3a1604AAABc, k(4, 8)], tags={I(4, 8)}),backend=numpy, dtype=float64, data=array([[[[[1., 0.]]]]])
Tensor(shape=(1, 1, 1, 1, 2), inds=[_3a1604AAABz, _3a1604AAABy, _3a1604AAABw, _3a1604AAABe, k(4, 9)], tags={I(4, 9)}),backend=numpy, dtype=float64, data=array([[[[[1., 0.]]]]])
Tensor(shape=(1, 1, 1, 2), inds=[_3a1604AAACA, _3a1604AAABy, _3a1604AAABf, k(4, 10)], tags={I(4, 10)}),backend=numpy, dtype=float64, data=array([[[[1., 0.]]]])
Tensor(shape=(1, 1, 1, 2), inds=[_3a1604AAACC, _3a1604AAACB, _3a1604AAABh, k(5, 0)], tags={I(5, 0)}),backend=numpy, dtype=float64, data=array([[[[1., 0.]]]])
Tensor(shape=(1, 1, 1, 1, 2), inds=[_3a1604AAACE, _3a1604AAACD, _3a1604AAACB, _3a1604AAABj, k(5, 1)], tags={I(5, 1)}),backend=numpy, dtype=float64, data=array([[[[[1., 0.]]]]])
Tensor(shape=(1, 1, 1, 1, 2), inds=[_3a1604AAACG, _3a1604AAACF, _3a1604AAACD, _3a1604AAABl, k(5, 2)], tags={I(5, 2)}),backend=numpy, dtype=float64, data=array([[[[[1., 0.]]]]])
Tensor(shape=(1, 1, 1, 1, 2), inds=[_3a1604AAACI, _3a1604AAACH, _3a1604AAACF, _3a1604AAABn, k(5, 3)], tags={I(5, 3)}),backend=numpy, dtype=float64, data=array([[[[[1., 0.]]]]])
Tensor(shape=(1, 1, 1, 1, 2), inds=[_3a1604AAACK, _3a1604AAACJ, _3a1604AAACH, _3a1604AAABp, k(5, 4)], tags={I(5, 4)}),backend=numpy, dtype=float64, data=array([[[[[1., 0.]]]]])
Tensor(shape=(1, 1, 1, 1, 2), inds=[_3a1604AAACM, _3a1604AAACL, _3a1604AAACJ, _3a1604AAABr, k(5, 5)], tags={I(5, 5)}),backend=numpy, dtype=float64, data=array([[[[[1., 0.]]]]])
Tensor(shape=(1, 1, 1, 1, 2), inds=[_3a1604AAACO, _3a1604AAACN, _3a1604AAACL, _3a1604AAABt, k(5, 6)], tags={I(5, 6)}),backend=numpy, dtype=float64, data=array([[[[[1., 0.]]]]])
Tensor(shape=(1, 1, 1, 1, 2), inds=[_3a1604AAACQ, _3a1604AAACP, _3a1604AAACN, _3a1604AAABv, k(5, 7)], tags={I(5, 7)}),backend=numpy, dtype=float64, data=array([[[[[1., 0.]]]]])
Tensor(shape=(1, 1, 1, 1, 2), inds=[_3a1604AAACS, _3a1604AAACR, _3a1604AAACP, _3a1604AAABx, k(5, 8)], tags={I(5, 8)}),backend=numpy, dtype=float64, data=array([[[[[1., 0.]]]]])
Tensor(shape=(1, 1, 1, 1, 2), inds=[_3a1604AAACU, _3a1604AAACT, _3a1604AAACR, _3a1604AAABz, k(5, 9)], tags={I(5, 9)}),backend=numpy, dtype=float64, data=array([[[[[1., 0.]]]]])
Tensor(shape=(1, 1, 1, 2), inds=[_3a1604AAACV, _3a1604AAACT, _3a1604AAACA, k(5, 10)], tags={I(5, 10)}),backend=numpy, dtype=float64, data=array([[[[1., 0.]]]])
Tensor(shape=(1, 1, 1, 2), inds=[_3a1604AAACX, _3a1604AAACW, _3a1604AAACC, k(6, 0)], tags={I(6, 0)}),backend=numpy, dtype=float64, data=array([[[[1., 0.]]]])
Tensor(shape=(1, 1, 1, 1, 2), inds=[_3a1604AAACZ, _3a1604AAACY, _3a1604AAACW, _3a1604AAACE, k(6, 1)], tags={I(6, 1)}),backend=numpy, dtype=float64, data=array([[[[[1., 0.]]]]])
Tensor(shape=(1, 1, 1, 1, 2), inds=[_3a1604AAACb, _3a1604AAACa, _3a1604AAACY, _3a1604AAACG, k(6, 2)], tags={I(6, 2)}),backend=numpy, dtype=float64, data=array([[[[[1., 0.]]]]])
Tensor(shape=(1, 1, 1, 1, 2), inds=[_3a1604AAACd, _3a1604AAACc, _3a1604AAACa, _3a1604AAACI, k(6, 3)], tags={I(6, 3)}),backend=numpy, dtype=float64, data=array([[[[[1., 0.]]]]])
Tensor(shape=(1, 1, 1, 1, 2), inds=[_3a1604AAACf, _3a1604AAACe, _3a1604AAACc, _3a1604AAACK, k(6, 4)], tags={I(6, 4)}),backend=numpy, dtype=float64, data=array([[[[[1., 0.]]]]])
Tensor(shape=(1, 1, 1, 1, 2), inds=[_3a1604AAACh, _3a1604AAACg, _3a1604AAACe, _3a1604AAACM, k(6, 5)], tags={I(6, 5)}),backend=numpy, dtype=float64, data=array([[[[[1., 0.]]]]])
Tensor(shape=(1, 1, 1, 1, 2), inds=[_3a1604AAACj, _3a1604AAACi, _3a1604AAACg, _3a1604AAACO, k(6, 6)], tags={I(6, 6)}),backend=numpy, dtype=float64, data=array([[[[[1., 0.]]]]])
Tensor(shape=(1, 1, 1, 1, 2), inds=[_3a1604AAACl, _3a1604AAACk, _3a1604AAACi, _3a1604AAACQ, k(6, 7)], tags={I(6, 7)}),backend=numpy, dtype=float64, data=array([[[[[1., 0.]]]]])
Tensor(shape=(1, 1, 1, 1, 2), inds=[_3a1604AAACn, _3a1604AAACm, _3a1604AAACk, _3a1604AAACS, k(6, 8)], tags={I(6, 8)}),backend=numpy, dtype=float64, data=array([[[[[1., 0.]]]]])
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" ], "text/plain": [ "TensorNetworkGenVector(tensors=121, indices=341)" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# create simple update gauges\n", "gauges = {}\n", "psi.gauge_all_simple_(gauges=gauges)" ] }, { "cell_type": "code", "execution_count": 5, "id": "3089c388-78a3-4204-ab12-beae05070536", "metadata": {}, "outputs": [], "source": [ "results = {}\n", "\n", "# truncation options\n", "max_bond = 16\n", "cutoff = 1e-6\n", "\n", "t = 0.0\n", "dt = 0.04\n", "\n", "U2 = ar.do(\"linalg.expm\", -1j * dt * h2)\n", "U1 = ar.do(\"linalg.expm\", -1j * dt * h1)" ] }, { "cell_type": "code", "execution_count": 6, "id": "f89821a4-4e10-4cfa-82b4-29081f41b4c8", "metadata": {}, "outputs": [], "source": [ "mag_terms = {(site,): qu.pauli(\"Z\") for site in [(Lx // 2, Ly // 2)]}\n", "\n", "cluster_sets = {c: tuple(psi.gen_gloops_sites(c)) for c in [0, 4, 6]}" ] }, { "cell_type": "code", "execution_count": 7, "id": "4f636b90-e0f0-446f-a292-ec7c35b896f0", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "[0, 100, 280]" ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ "[len(cs) for cs in cluster_sets.values()]" ] }, { "cell_type": "code", "execution_count": 8, "id": "91dfbbb7-131d-4206-9cd9-99de6303411d", "metadata": {}, "outputs": [], "source": [ "def measure():\n", " if \"times\" in results and results[\"times\"][-1] == t:\n", " # already measured this time\n", " return\n", "\n", " results.setdefault(\"times\", []).append(t)\n", "\n", " for c, gloops in cluster_sets.items():\n", " results.setdefault((\"norm\", c), []).append(\n", " psi.norm_gloop_expand(\n", " gauges=gauges,\n", " gloops=gloops,\n", " optimize=\"random-greedy\",\n", " autocomplete=True,\n", " autoreduce=True,\n", " ).real\n", " )\n", "\n", " # store some intermediate state for efficiency\n", " info = {}\n", " for c, gloops in cluster_sets.items():\n", " results.setdefault((\"mag\", c), []).append(\n", " psi.compute_local_expectation_gloop_expand(\n", " mag_terms,\n", " gauges=gauges,\n", " normalized=\"prod\",\n", " gloops=gloops,\n", " optimize=\"random-greedy\",\n", " autocomplete=True,\n", " info=info,\n", " ).real\n", " / len(mag_terms)\n", " )" ] }, { "cell_type": "code", "execution_count": 12, "id": "f44d6063-d39d-4b1a-b295-f43b3fe07ac7", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "100%|███████████████████████████████████████████████████████████████████████████| 10/10 [11:32<00:00, 69.24s/it]\n" ] } ], "source": [ "for i in tqdm.trange(10):\n", " measure()\n", "\n", " for edge in qtn.tnag.tebd.edge_coloring(\n", " edges,\n", " \"random_sequential\",\n", " group=False,\n", " ):\n", " psi.gate_simple_(\n", " U2,\n", " where=edge,\n", " gauges=gauges,\n", " max_bond=max_bond,\n", " cutoff=cutoff,\n", " renorm=False,\n", " )\n", "\n", " for site in sites:\n", " psi.gate_simple_(U1, (site,), gauges=gauges)\n", "\n", " # ensure gauge is equilibrated\n", " psi.gauge_all_simple_(\n", " max_iterations=1000,\n", " tol=1e-6,\n", " gauges=gauges,\n", " progbar=False,\n", " )\n", "\n", " t += dt\n", "\n", "measure()" ] }, { "cell_type": "code", "execution_count": 13, "id": "aa195323-1c15-4030-a2f4-720b4360a4a7", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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Tensor(shape=(16, 16, 16, 16, 2), inds=[_7322eeAAACG, _7322eeAAACF, _7322eeAAACD, _7322eeAAABl, k(5, 2)], tags={I(5, 2)}),backend=numpy, dtype=complex128, data=...
Tensor(shape=(16, 16, 16, 16, 2), inds=[_7322eeAAACI, _7322eeAAACH, _7322eeAAACF, _7322eeAAABn, k(5, 3)], tags={I(5, 3)}),backend=numpy, dtype=complex128, data=...
Tensor(shape=(16, 16, 16, 16, 2), inds=[_7322eeAAACK, _7322eeAAACJ, _7322eeAAACH, _7322eeAAABp, k(5, 4)], tags={I(5, 4)}),backend=numpy, dtype=complex128, data=...
Tensor(shape=(16, 16, 16, 16, 2), inds=[_7322eeAAACM, _7322eeAAACL, _7322eeAAACJ, _7322eeAAABr, k(5, 5)], tags={I(5, 5)}),backend=numpy, dtype=complex128, data=...
Tensor(shape=(16, 16, 16, 16, 2), inds=[_7322eeAAACO, _7322eeAAACN, _7322eeAAACL, _7322eeAAABt, k(5, 6)], tags={I(5, 6)}),backend=numpy, dtype=complex128, data=...
Tensor(shape=(16, 16, 16, 16, 2), inds=[_7322eeAAACQ, _7322eeAAACP, _7322eeAAACN, _7322eeAAABv, k(5, 7)], tags={I(5, 7)}),backend=numpy, dtype=complex128, data=...
Tensor(shape=(16, 16, 16, 16, 2), inds=[_7322eeAAACS, _7322eeAAACR, _7322eeAAACP, _7322eeAAABx, k(5, 8)], tags={I(5, 8)}),backend=numpy, dtype=complex128, data=...
Tensor(shape=(16, 16, 16, 16, 2), inds=[_7322eeAAACU, _7322eeAAACT, _7322eeAAACR, _7322eeAAABz, k(5, 9)], tags={I(5, 9)}),backend=numpy, dtype=complex128, data=...
Tensor(shape=(16, 16, 16, 2), inds=[_7322eeAAACV, _7322eeAAACT, _7322eeAAACA, k(5, 10)], tags={I(5, 10)}),backend=numpy, dtype=complex128, data=...
Tensor(shape=(16, 16, 16, 2), inds=[_7322eeAAACX, _7322eeAAACW, _7322eeAAACC, k(6, 0)], tags={I(6, 0)}),backend=numpy, dtype=complex128, data=...
Tensor(shape=(16, 16, 16, 16, 2), inds=[_7322eeAAACZ, _7322eeAAACY, _7322eeAAACW, _7322eeAAACE, k(6, 1)], tags={I(6, 1)}),backend=numpy, dtype=complex128, data=...
Tensor(shape=(16, 16, 16, 16, 2), inds=[_7322eeAAACb, _7322eeAAACa, _7322eeAAACY, _7322eeAAACG, k(6, 2)], tags={I(6, 2)}),backend=numpy, dtype=complex128, data=...
Tensor(shape=(16, 16, 16, 16, 2), inds=[_7322eeAAACd, _7322eeAAACc, _7322eeAAACa, _7322eeAAACI, k(6, 3)], tags={I(6, 3)}),backend=numpy, dtype=complex128, data=...
Tensor(shape=(16, 16, 16, 16, 2), inds=[_7322eeAAACf, _7322eeAAACe, _7322eeAAACc, _7322eeAAACK, k(6, 4)], tags={I(6, 4)}),backend=numpy, dtype=complex128, data=...
Tensor(shape=(16, 16, 16, 16, 2), inds=[_7322eeAAACh, _7322eeAAACg, _7322eeAAACe, _7322eeAAACM, k(6, 5)], tags={I(6, 5)}),backend=numpy, dtype=complex128, data=...
Tensor(shape=(16, 16, 16, 16, 2), inds=[_7322eeAAACj, _7322eeAAACi, _7322eeAAACg, _7322eeAAACO, k(6, 6)], tags={I(6, 6)}),backend=numpy, dtype=complex128, data=...
Tensor(shape=(16, 16, 16, 16, 2), inds=[_7322eeAAACl, _7322eeAAACk, _7322eeAAACi, _7322eeAAACQ, k(6, 7)], tags={I(6, 7)}),backend=numpy, dtype=complex128, data=...
Tensor(shape=(16, 16, 16, 16, 2), inds=[_7322eeAAACn, _7322eeAAACm, _7322eeAAACk, _7322eeAAACS, k(6, 8)], tags={I(6, 8)}),backend=numpy, dtype=complex128, data=...
Tensor(shape=(16, 16, 16, 16, 2), inds=[_7322eeAAACp, _7322eeAAACo, _7322eeAAACm, _7322eeAAACU, k(6, 9)], tags={I(6, 9)}),backend=numpy, dtype=complex128, data=...
Tensor(shape=(16, 16, 16, 2), inds=[_7322eeAAACq, _7322eeAAACo, _7322eeAAACV, k(6, 10)], tags={I(6, 10)}),backend=numpy, dtype=complex128, data=...
Tensor(shape=(16, 16, 16, 2), inds=[_7322eeAAACs, _7322eeAAACr, _7322eeAAACX, k(7, 0)], tags={I(7, 0)}),backend=numpy, dtype=complex128, data=...
Tensor(shape=(16, 16, 16, 16, 2), inds=[_7322eeAAACu, _7322eeAAACt, _7322eeAAACr, _7322eeAAACZ, k(7, 1)], tags={I(7, 1)}),backend=numpy, dtype=complex128, data=...
Tensor(shape=(16, 16, 16, 16, 2), inds=[_7322eeAAACw, _7322eeAAACv, _7322eeAAACt, _7322eeAAACb, k(7, 2)], tags={I(7, 2)}),backend=numpy, dtype=complex128, data=...
Tensor(shape=(16, 16, 16, 16, 2), inds=[_7322eeAAACy, _7322eeAAACx, _7322eeAAACv, _7322eeAAACd, k(7, 3)], tags={I(7, 3)}),backend=numpy, dtype=complex128, data=...
Tensor(shape=(16, 16, 16, 16, 2), inds=[_7322eeAAADA, _7322eeAAACz, _7322eeAAACx, _7322eeAAACf, k(7, 4)], tags={I(7, 4)}),backend=numpy, dtype=complex128, data=...
Tensor(shape=(16, 16, 16, 16, 2), inds=[_7322eeAAADC, _7322eeAAADB, _7322eeAAACz, _7322eeAAACh, k(7, 5)], tags={I(7, 5)}),backend=numpy, dtype=complex128, data=...
Tensor(shape=(16, 16, 16, 16, 2), inds=[_7322eeAAADE, _7322eeAAADD, _7322eeAAADB, _7322eeAAACj, k(7, 6)], tags={I(7, 6)}),backend=numpy, dtype=complex128, data=...
Tensor(shape=(16, 16, 16, 16, 2), inds=[_7322eeAAADG, _7322eeAAADF, _7322eeAAADD, _7322eeAAACl, k(7, 7)], tags={I(7, 7)}),backend=numpy, dtype=complex128, data=...
Tensor(shape=(16, 16, 16, 16, 2), inds=[_7322eeAAADI, _7322eeAAADH, _7322eeAAADF, _7322eeAAACn, k(7, 8)], tags={I(7, 8)}),backend=numpy, dtype=complex128, data=...
Tensor(shape=(16, 16, 16, 16, 2), inds=[_7322eeAAADK, _7322eeAAADJ, _7322eeAAADH, _7322eeAAACp, k(7, 9)], tags={I(7, 9)}),backend=numpy, dtype=complex128, data=...
Tensor(shape=(16, 16, 16, 2), inds=[_7322eeAAADL, _7322eeAAADJ, _7322eeAAACq, k(7, 10)], tags={I(7, 10)}),backend=numpy, dtype=complex128, data=...
Tensor(shape=(16, 16, 16, 2), inds=[_7322eeAAADN, _7322eeAAADM, _7322eeAAACs, k(8, 0)], tags={I(8, 0)}),backend=numpy, dtype=complex128, data=...
Tensor(shape=(16, 16, 16, 16, 2), inds=[_7322eeAAADP, _7322eeAAADO, _7322eeAAADM, _7322eeAAACu, k(8, 1)], tags={I(8, 1)}),backend=numpy, dtype=complex128, data=...
Tensor(shape=(16, 16, 16, 16, 2), inds=[_7322eeAAADR, _7322eeAAADQ, _7322eeAAADO, _7322eeAAACw, k(8, 2)], tags={I(8, 2)}),backend=numpy, dtype=complex128, data=...
Tensor(shape=(16, 16, 16, 16, 2), inds=[_7322eeAAADT, _7322eeAAADS, _7322eeAAADQ, _7322eeAAACy, k(8, 3)], tags={I(8, 3)}),backend=numpy, dtype=complex128, data=...
Tensor(shape=(16, 16, 16, 16, 2), inds=[_7322eeAAADV, _7322eeAAADU, _7322eeAAADS, _7322eeAAADA, k(8, 4)], tags={I(8, 4)}),backend=numpy, dtype=complex128, data=...
Tensor(shape=(16, 16, 16, 16, 2), inds=[_7322eeAAADX, _7322eeAAADW, _7322eeAAADU, _7322eeAAADC, k(8, 5)], tags={I(8, 5)}),backend=numpy, dtype=complex128, data=...
Tensor(shape=(16, 16, 16, 16, 2), inds=[_7322eeAAADZ, _7322eeAAADY, _7322eeAAADW, _7322eeAAADE, k(8, 6)], tags={I(8, 6)}),backend=numpy, dtype=complex128, data=...
Tensor(shape=(16, 16, 16, 16, 2), inds=[_7322eeAAADb, _7322eeAAADa, _7322eeAAADY, _7322eeAAADG, k(8, 7)], tags={I(8, 7)}),backend=numpy, dtype=complex128, data=...
Tensor(shape=(16, 16, 16, 16, 2), inds=[_7322eeAAADd, _7322eeAAADc, _7322eeAAADa, _7322eeAAADI, k(8, 8)], tags={I(8, 8)}),backend=numpy, dtype=complex128, data=...
Tensor(shape=(16, 16, 16, 16, 2), inds=[_7322eeAAADf, _7322eeAAADe, _7322eeAAADc, _7322eeAAADK, k(8, 9)], tags={I(8, 9)}),backend=numpy, dtype=complex128, data=...
Tensor(shape=(16, 16, 16, 2), inds=[_7322eeAAADg, _7322eeAAADe, _7322eeAAADL, k(8, 10)], tags={I(8, 10)}),backend=numpy, dtype=complex128, data=...
Tensor(shape=(16, 16, 16, 2), inds=[_7322eeAAADi, _7322eeAAADh, _7322eeAAADN, k(9, 0)], tags={I(9, 0)}),backend=numpy, dtype=complex128, data=...

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" ], "text/plain": [ "TensorNetworkGenVector(tensors=121, indices=341)" ] }, "execution_count": 13, "metadata": {}, "output_type": "execute_result" } ], "source": [ "psi" ] }, { "cell_type": "code", "execution_count": 14, "id": "ed33fe6b-4ecd-46c8-bf3d-d775b2f970d3", "metadata": {}, "outputs": [ { "data": { "image/svg+xml": [ "" ], "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "for i, c in enumerate(cluster_sets):\n", " plt.plot(\n", " results[\"times\"],\n", " results[\"norm\", c],\n", " \".-\",\n", " label=f\"C{c}\",\n", " color=mpl.cm.Blues((i + 1) / len(cluster_sets)),\n", " linewidth=2 * (i + 1) / len(cluster_sets),\n", " )\n", "\n", "for i, c in enumerate(cluster_sets):\n", " plt.plot(\n", " results[\"times\"],\n", " results[\"mag\", c],\n", " \"|-\",\n", " label=f\"C{c}\",\n", " color=mpl.cm.Greens((i + 1) / len(cluster_sets)),\n", " linewidth=2 * (i + 1) / len(cluster_sets),\n", " )\n", "\n", "plt.legend(bbox_to_anchor=(1, 1))\n", "plt.show()\n", "plt.close()" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3" } }, "nbformat": 4, "nbformat_minor": 4 }