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feat: changed backend generation mechanism + updated tutorial

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BrunoLiegiBastonLiegi
2025-10-27 16:25:38 +01:00
parent b9fe861848
commit 7ea8dc861b
3 changed files with 419 additions and 382 deletions
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216
examples/quimb_intro/quimb_introduction.ipynb
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@@ -67,7 +67,7 @@
"# set numpy random seed\n",
"np.random.seed(42)\n",
"\n",
"quimb_backend.setup_backend_specifics(qimb_backend=\"jax\")"
"quimb_backend.setup_backend_specifics(quimb_backend=\"jax\")"
]
},
{
@@ -180,12 +180,10 @@
"name": "stderr",
"output_type": "stream",
"text": [
"/home/mattia/main_env/lib/python3.12/site-packages/quimb/tensor/circuit.py:215: SyntaxWarning: Unsupported operation ignored: creg\n",
"/home/andrea/python_envs/3.11/lib/python3.11/site-packages/quimb/tensor/circuit.py:215: SyntaxWarning: Unsupported operation ignored: creg\n",
" warnings.warn(\n",
"/home/mattia/main_env/lib/python3.12/site-packages/quimb/tensor/circuit.py:215: SyntaxWarning: Unsupported operation ignored: measure\n",
" warnings.warn(\n",
"/home/mattia/main_env/lib/python3.12/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
" from .autonotebook import tqdm as notebook_tqdm\n"
"/home/andrea/python_envs/3.11/lib/python3.11/site-packages/quimb/tensor/circuit.py:215: SyntaxWarning: Unsupported operation ignored: measure\n",
" warnings.warn(\n"
]
},
{
@@ -193,49 +191,53 @@
"text/plain": [
"{'nqubits': 4,\n",
" 'backend': qibotn (quimb),\n",
" 'measures': Counter({'1010': 9,\n",
" '0100': 8,\n",
" '1101': 15,\n",
" '1011': 4,\n",
" '1111': 12,\n",
" '1000': 13,\n",
" 'measures': Counter({'1101': 14,\n",
" '1000': 12,\n",
" '0010': 11,\n",
" '0011': 11,\n",
" '0110': 9,\n",
" '0000': 8,\n",
" '0010': 6,\n",
" '0011': 6,\n",
" '0101': 8,\n",
" '1110': 5,\n",
" '0110': 5,\n",
" '0111': 1}),\n",
" 'measured_probabilities': {'1101': np.float64(0.12331159869893256),\n",
" '1000': np.float64(0.11330883548333587),\n",
" '1111': np.float64(0.10184806171791962),\n",
" '1010': np.float64(0.03872758515126756),\n",
" '0100': np.float64(0.07142939529687138),\n",
" '0000': np.float64(0.08390937969317269),\n",
" '0101': np.float64(0.05622305772698622),\n",
" '0010': np.float64(0.09466860481989385),\n",
" '0011': np.float64(0.07571277233522114),\n",
" '1110': np.float64(0.07174919872959985),\n",
" '0110': np.float64(0.05146064807369214),\n",
" '1011': np.float64(0.053499396925872744),\n",
" '0111': np.float64(0.04029185074729259)},\n",
" '1010': 7,\n",
" '1110': 6,\n",
" '0100': 5,\n",
" '1111': 5,\n",
" '1011': 5,\n",
" '0101': 4,\n",
" '0111': 1,\n",
" '0001': 1,\n",
" '1100': 1}),\n",
" 'measured_probabilities': {'1101': np.float64(0.12331159869893284),\n",
" '1000': np.float64(0.11330883548333684),\n",
" '0010': np.float64(0.0946686048198943),\n",
" '0011': np.float64(0.07571277233522157),\n",
" '0110': np.float64(0.051460648073692314),\n",
" '0000': np.float64(0.08390937969317334),\n",
" '1010': np.float64(0.03872758515126775),\n",
" '1110': np.float64(0.07174919872960006),\n",
" '0100': np.float64(0.07142939529687146),\n",
" '1111': np.float64(0.10184806171791994),\n",
" '1011': np.float64(0.053499396925872716),\n",
" '0101': np.float64(0.05622305772698606),\n",
" '0111': np.float64(0.040291850747292815),\n",
" '0001': np.float64(0.004677011195208322),\n",
" '1100': np.float64(0.013605984872668443)},\n",
" 'prob_type': 'default',\n",
" 'statevector': Array([[ 0.08809624-0.27594998j],\n",
" [-0.05174781+0.04471217j],\n",
" [ 0.00470147+0.30764672j],\n",
" [-0.27208942+0.0409893j ],\n",
" [ 0.18807822+0.18988408j],\n",
" [ 0.2237706 +0.07842042j],\n",
" [-0.18900308+0.12545314j],\n",
" [ 0.17105256-0.10503749j],\n",
" [ 0.24859734-0.22695419j],\n",
" [-0.0411739 -0.06230037j],\n",
" [ 0.17371392-0.09247189j],\n",
" [-0.22748128+0.0418529j ],\n",
" [ 0.09444095+0.06846087j],\n",
" [-0.21784972-0.2754144j ],\n",
" [-0.17359753+0.20399286j],\n",
" [-0.01729754-0.31866732j]], dtype=complex64)}"
" 'statevector': Array([[ 0.08809626-0.27595j ],\n",
" [-0.05174781+0.04471214j],\n",
" [ 0.00470146+0.30764672j],\n",
" [-0.27208942+0.04098931j],\n",
" [ 0.18807825+0.1898841j ],\n",
" [ 0.22377063+0.07842041j],\n",
" [-0.18900302+0.12545316j],\n",
" [ 0.17105258-0.10503745j],\n",
" [ 0.24859732-0.22695422j],\n",
" [-0.04117391-0.0623003j ],\n",
" [ 0.17371394-0.09247189j],\n",
" [-0.22748126+0.04185291j],\n",
" [ 0.09444097+0.06846087j],\n",
" [-0.21784975-0.2754144j ],\n",
" [-0.17359754+0.20399287j],\n",
" [-0.01729751-0.31866732j]], dtype=complex64)}"
]
},
"execution_count": 8,
@@ -272,25 +274,25 @@
"output_type": "stream",
"text": [
"Probabilities:\n",
" {'1101': np.float64(0.12331159869893256), '1000': np.float64(0.11330883548333587), '1111': np.float64(0.10184806171791962), '1010': np.float64(0.03872758515126756), '0100': np.float64(0.07142939529687138), '0000': np.float64(0.08390937969317269), '0101': np.float64(0.05622305772698622), '0010': np.float64(0.09466860481989385), '0011': np.float64(0.07571277233522114), '1110': np.float64(0.07174919872959985), '0110': np.float64(0.05146064807369214), '1011': np.float64(0.053499396925872744), '0111': np.float64(0.04029185074729259)}\n",
" {'1101': np.float64(0.12331159869893284), '1000': np.float64(0.11330883548333684), '0010': np.float64(0.0946686048198943), '0011': np.float64(0.07571277233522157), '0110': np.float64(0.051460648073692314), '0000': np.float64(0.08390937969317334), '1010': np.float64(0.03872758515126775), '1110': np.float64(0.07174919872960006), '0100': np.float64(0.07142939529687146), '1111': np.float64(0.10184806171791994), '1011': np.float64(0.053499396925872716), '0101': np.float64(0.05622305772698606), '0111': np.float64(0.040291850747292815), '0001': np.float64(0.004677011195208322), '1100': np.float64(0.013605984872668443)}\n",
"\n",
"State:\n",
" [[ 0.08809624-0.27594998j]\n",
" [-0.05174781+0.04471217j]\n",
" [ 0.00470147+0.30764672j]\n",
" [-0.27208942+0.0409893j ]\n",
" [ 0.18807822+0.18988408j]\n",
" [ 0.2237706 +0.07842042j]\n",
" [-0.18900308+0.12545314j]\n",
" [ 0.17105256-0.10503749j]\n",
" [ 0.24859734-0.22695419j]\n",
" [-0.0411739 -0.06230037j]\n",
" [ 0.17371392-0.09247189j]\n",
" [-0.22748128+0.0418529j ]\n",
" [ 0.09444095+0.06846087j]\n",
" [-0.21784972-0.2754144j ]\n",
" [-0.17359753+0.20399286j]\n",
" [-0.01729754-0.31866732j]]\n",
" [[ 0.08809626-0.27595j ]\n",
" [-0.05174781+0.04471214j]\n",
" [ 0.00470146+0.30764672j]\n",
" [-0.27208942+0.04098931j]\n",
" [ 0.18807825+0.1898841j ]\n",
" [ 0.22377063+0.07842041j]\n",
" [-0.18900302+0.12545316j]\n",
" [ 0.17105258-0.10503745j]\n",
" [ 0.24859732-0.22695422j]\n",
" [-0.04117391-0.0623003j ]\n",
" [ 0.17371394-0.09247189j]\n",
" [-0.22748126+0.04185291j]\n",
" [ 0.09444097+0.06846087j]\n",
" [-0.21784975-0.2754144j ]\n",
" [-0.17359754+0.20399287j]\n",
" [-0.01729751-0.31866732j]]\n",
"\n"
]
}
@@ -338,7 +340,7 @@
"quimb_backend = construct_backend(backend=\"qibotn\", platform=\"quimb\")\n",
"\n",
"quimb_backend.setup_backend_specifics(\n",
" qimb_backend =\"jax\", \n",
" quimb_backend =\"jax\", \n",
" contractions_optimizer='auto-hq'\n",
" )\n",
"\n",
@@ -349,21 +351,21 @@
},
{
"cell_type": "code",
"execution_count": 19,
"execution_count": 18,
"id": "b2a0decb",
"metadata": {},
"outputs": [],
"source": [
"from qibo.symbols import X, Z, Y\n",
"from qibo.hamiltonians import XXZ\n",
"\n",
"# define Hamiltonian\n",
"operators = [\"xzy\", \"yxzy\", \"zy\"]\n",
"qubits = [\"011\", \"0112\", \"01\"]\n",
"coefficients = [\"1\", \"2\", \"j\"]\n",
"hamiltonian = (operators, qubits, coefficients)"
"hamiltonian = XXZ(4, dense=False, backend=quimb_backend)"
]
},
{
"cell_type": "code",
"execution_count": 18,
"execution_count": 19,
"id": "bd734be8",
"metadata": {},
"outputs": [],
@@ -407,19 +409,14 @@
"name": "stdout",
"output_type": "stream",
"text": [
"Expectation value: 0.0\n",
"Elapsed time: 0.1071 seconds\n"
"Expectation value: 2.0\n",
"Elapsed time: 0.0268 seconds\n"
]
}
],
"source": [
"start = time.time()\n",
"expval = quimb_backend.expectation(\n",
" circuit=circuit,\n",
" operators_list=hamiltonian[0],\n",
" sites_list=hamiltonian[1],\n",
" coeffs_list=hamiltonian[2]\n",
" )\n",
"expval = hamiltonian.expectation(circuit)\n",
"\n",
"elapsed = time.time() - start\n",
"print(f\"Expectation value: {expval}\")\n",
@@ -436,24 +433,29 @@
},
{
"cell_type": "code",
"execution_count": 22,
"execution_count": 21,
"id": "fb1436c8",
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"[Qibo 0.2.21|INFO|2025-10-27 16:24:00]: Using numpy backend on /CPU:0\n",
"WARNING:root:Calculation of expectation values starting from the state is deprecated, use the ``expectation_from_state`` method if you really need it, or simply pass the circuit you want to calculate the expectation value from.\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Expectation value: 1.5\n",
"Elapsed time: 0.0501 seconds\n"
"Expectation value: 2.0\n",
"Elapsed time: 0.0360 seconds\n"
]
}
],
"source": [
"from qibo.symbols import Z, X, I\n",
"# We can create a symbolic Hamiltonian\n",
"form = 0.5 * Z(0) * Z(1) +- 1.5 * X(0) * Z(2) + Z(3)\n",
"sym_hamiltonian = hamiltonians.SymbolicHamiltonian(form)\n",
"sym_hamiltonian = XXZ(4, dense=False, backend=None)\n",
"\n",
"# Let's show it\n",
"sym_hamiltonian.form\n",
@@ -488,40 +490,52 @@
"id": "6a3b26e4",
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/andrea/python_envs/3.11/lib/python3.11/site-packages/quimb/tensor/circuit.py:4927: UserWarning: Unsupported options for computing local_expectation with an MPS circuit supplied, ignoring: R, None, None, jax, None\n",
" warnings.warn(\n",
"/home/andrea/python_envs/3.11/lib/python3.11/site-packages/quimb/tensor/circuit.py:4927: UserWarning: Unsupported options for computing local_expectation with an MPS circuit supplied, ignoring: R, None, None, jax, None\n",
" warnings.warn(\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"[ 8.19939339e-10 -3.14190913e-08 -2.99498648e-09 -1.03641796e-07\n",
" 8.48652704e-10 1.00297093e-07 -6.75429277e-08 -9.78565140e-09\n",
" -5.11915417e-08 1.29225235e-08 -7.44280655e-08 -3.49115048e-08\n",
" -4.98508879e-09 6.80729357e-08 -3.29755920e-08 4.20008526e-08\n",
" -2.89742630e-08 1.18602941e-07 -2.88252178e-08 5.57985391e-09\n",
" -3.17434115e-08 -1.03342952e-08 1.34079716e-08 -7.05437886e-09\n",
" -4.34059650e-08 -2.18019203e-08 -5.36932561e-08 -6.38544009e-08\n",
" 5.85312279e-08 8.45709067e-08 -1.12777876e-09 -6.41545981e-08\n",
" 7.25317406e-08 4.10035668e-08 -1.29046382e-08 6.07501676e-08]\n"
"[-0.24630009 0.8370421 -0.11103702 -0.12855841 0.41325414 -0.0628037\n",
" 0.51638705 0.794163 -0.27972788 -1.0718998 0.02731732 1.0153619\n",
" -0.34494495 1.5744264 0.26920277 -0.36333832 0.12331417 0.5196531\n",
" 1.1294655 0.29257926 -0.18237355 0.8914014 -0.9471657 0.3492473\n",
" -0.3477673 0.24325958 0.04818404 -0.87983793 0.47196424 0.36605012\n",
" 1.005 0.65054715 -0.94860053 0.14459445 0.36571163 -0.2550101 ]\n"
]
}
],
"source": [
"def f(circuit, hamiltonian, params):\n",
" circuit.set_parameters(params)\n",
" return quimb_backend.expectation(\n",
" return hamiltonian.expectation(\n",
" circuit=circuit,\n",
" operators_list=hamiltonian[0],\n",
" sites_list=hamiltonian[1],\n",
" coeffs_list=hamiltonian[2]\n",
" )\n",
"\n",
"parameters = np.random.uniform(-np.pi, np.pi, size=len(circuit.get_parameters()))\n",
"print(jax.grad(f, argnums=2)(circuit, hamiltonian, parameters))\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "aeafa5a6-2afa-429c-a101-effa84bac1d2",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "main_env",
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
@@ -535,7 +549,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.12.3"
"version": "3.11.12"
}
},
"nbformat": 4,