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Merged
NadavClassiq merged 3 commits into from
Feb 20, 2025
Merged

added quantum tree solution for mit iquhack 2025 #777

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09ba38e
adding hackathons folder and iquhack2025 solution
NadavClassiq Feb 19, 2025
ffcb34b
adding timeouts
NadavClassiq Feb 19, 2025
d5d3b95
added quantum tree solution for mit iquhack 2025
easonoob Feb 19, 2025
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98 changes: 60 additions & 38 deletions ...n_2025/advection_equation/advection.ipynb → ...n_2025/advection_equation/advection.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -26,15 +26,16 @@
"metadata": {},
"outputs": [],
"source": [
"import numpy as np\n",
"from matplotlib import pyplot as plt\n",
"\n",
"from classiq import *\n",
"from classiq.execution import (\n",
" ClassiqBackendPreferences,\n",
" ExecutionPreferences,\n",
" ClassiqSimulatorBackendNames,\n",
" ExecutionPreferences,\n",
")\n",
"from classiq.synthesis import set_execution_preferences\n",
"import numpy as np\n",
"from matplotlib import pyplot as plt"
"from classiq.synthesis import set_execution_preferences"
]
},
{
Expand All @@ -50,13 +51,14 @@
"metadata": {},
"outputs": [],
"source": [
"n_qbits = 7 # number of qubit to use\n",
"t = 1.0 # evolution time\n",
"tau = 1.0/32 # time step for trotterization\n",
"n_qbits = 7 # number of qubit to use\n",
"t = 1.0 # evolution time\n",
"tau = 1.0 / 32 # time step for trotterization\n",
"shots = 4096 # Number of shots to sample\n",
"\n",
"\n",
"def get_steps(t: float, tau: float) -> int:\n",
" return int(np.floor(t/tau))"
" return int(np.floor(t / tau))"
]
},
{
Expand Down Expand Up @@ -111,9 +113,10 @@
" else:\n",
" return 0\n",
"\n",
"n = 2 ** n_qbits\n",
"\n",
"n = 2**n_qbits\n",
"x_axis = np.linspace(0, 4, n)\n",
"boundary = [phi_0_x(x) for x in x_axis]\n"
"boundary = [phi_0_x(x) for x in x_axis]"
]
},
{
Expand Down Expand Up @@ -159,10 +162,11 @@
"source": [
"def step(phi: list[float], dt: float, dx: float) -> list[float]:\n",
" new_phi = np.zeros(len(phi))\n",
" for i in range(1, len(phi)-1):\n",
" new_phi[i] = phi[i] - dt * (phi[i+1] - phi[i-1]) / (2*dx)\n",
" for i in range(1, len(phi) - 1):\n",
" new_phi[i] = phi[i] - dt * (phi[i + 1] - phi[i - 1]) / (2 * dx)\n",
" return new_phi\n",
"\n",
"\n",
"def evolve(initial, t, dt, dx):\n",
" phi = initial\n",
" cur_t = dt\n",
Expand All @@ -189,7 +193,7 @@
}
],
"source": [
"dx = x_axis[1]-x_axis[0]\n",
"dx = x_axis[1] - x_axis[0]\n",
"dt = 0.001\n",
"solution = evolve(boundary, t, dt, dx)\n",
"fig, ax = plt.subplots()\n",
Expand Down Expand Up @@ -376,43 +380,46 @@
" # CNOT ladder\n",
" repeat(count=j, iteration=lambda i: CX(qbits[j], qbits[i]))\n",
"\n",
"\n",
"@qfunc\n",
"def controlled_rotate(control_qbits: QArray[QBit], target: QBit, dt: CReal):\n",
" control(ctrl=control_qbits, stmt_block=lambda: RY(2*dt, target))\n",
" control(ctrl=control_qbits, stmt_block=lambda: RY(2 * dt, target))\n",
"\n",
"\n",
"@qfunc\n",
"def step(qbits: QArray[QBit], j: CInt, dt: CReal):\n",
" within_apply(\n",
" within=lambda: u(qbits, j),\n",
" apply=lambda: controlled_rotate(qbits[0:j], qbits[j], dt)\n",
" apply=lambda: controlled_rotate(qbits[0:j], qbits[j], dt),\n",
" )\n",
"\n",
"\n",
"@qfunc\n",
"def ladder(qbits: QArray[QBit], dt: CReal):\n",
" \"\"\"Use second order approximation\n",
" \"\"\"\n",
" \"\"\"Use second order approximation\"\"\"\n",
" # W1(-$\\tau$/2)\n",
" RY(-dt, qbits[0])\n",
"\n",
" # V\n",
" RY(2*dt, qbits[0])\n",
" repeat(count=qbits.len-1, iteration=lambda i: step(qbits[0:i+2], i+1, dt))\n",
" \n",
" RY(2 * dt, qbits[0])\n",
" repeat(count=qbits.len - 1, iteration=lambda i: step(qbits[0 : i + 2], i + 1, dt))\n",
"\n",
" # W1($\\tau$/2)\n",
" RY(dt, qbits[0])\n",
"\n",
"\n",
"def model_factory(n_qbits: int, t: CReal, tau: CReal) -> QCallable:\n",
" steps = get_steps(t, tau)\n",
" initial = np.zeros(2**n_qbits)\n",
" domain_length = 4\n",
" segment_one = 2**n_qbits // domain_length\n",
" l = 1 / segment_one\n",
" initial[segment_one:2*segment_one] = np.sqrt(1/segment_one)\n",
" initial[segment_one : 2 * segment_one] = np.sqrt(1 / segment_one)\n",
"\n",
" @qfunc\n",
" def main(qbits: Output[QArray[n_qbits]]):\n",
" prepare_amplitudes(amplitudes=initial.tolist(), bound=0.01, out=qbits)\n",
" repeat(count=steps, iteration=lambda i: ladder(qbits, t/(2*l)/steps))\n",
" repeat(count=steps, iteration=lambda i: ladder(qbits, t / (2 * l) / steps))\n",
"\n",
" return main"
]
Expand All @@ -430,8 +437,12 @@
"metadata": {},
"outputs": [],
"source": [
"def create_program(n_qbits: int, t: float, tau: float, factory: callable=model_factory):\n",
" backend_preferences = ClassiqBackendPreferences(backend_name=ClassiqSimulatorBackendNames.SIMULATOR_STATEVECTOR)\n",
"def create_program(\n",
" n_qbits: int, t: float, tau: float, factory: callable = model_factory\n",
"):\n",
" backend_preferences = ClassiqBackendPreferences(\n",
" backend_name=ClassiqSimulatorBackendNames.SIMULATOR_STATEVECTOR\n",
" )\n",
" model = create_model(factory(n_qbits, t, tau))\n",
" model = set_execution_preferences(\n",
" model,\n",
Expand All @@ -456,7 +467,7 @@
"metadata": {},
"outputs": [],
"source": [
"def solve(n_qbits: int, t: float, tau: float, factory: callable=model_factory):\n",
"def solve(n_qbits: int, t: float, tau: float, factory: callable = model_factory):\n",
" qprog = create_program(n_qbits, t, tau, factory)\n",
" result = execute(qprog)\n",
" return (result.result())[0].value.model_dump(), qprog"
Expand Down Expand Up @@ -496,10 +507,10 @@
"cx_count = circuit.transpiled_circuit.count_ops[\"cx\"]\n",
"print(f\"width={width}\\ndepth={depth}\\ncx count={cx_count}\")\n",
"\n",
"position = np.linspace(0.0, 4.0, 2 ** n_qbits)\n",
"states = [f\"{i:0{n_qbits}b}\" for i in range(2 ** n_qbits)]\n",
"scale = ((2 ** n_qbits) // 4)\n",
"quantum_solution = [scale*(r[\"counts\"].get(state, 0)/shots) for state in states]"
"position = np.linspace(0.0, 4.0, 2**n_qbits)\n",
"states = [f\"{i:0{n_qbits}b}\" for i in range(2**n_qbits)]\n",
"scale = (2**n_qbits) // 4\n",
"quantum_solution = [scale * (r[\"counts\"].get(state, 0) / shots) for state in states]"
]
},
{
Expand Down Expand Up @@ -595,13 +606,15 @@
" circuit = QuantumProgram.from_qprog(qprog)\n",
" return circuit.transpiled_circuit.count_ops[\"cx\"]\n",
"\n",
"\n",
"def count_cx_ops(n_qbits: int, t: float, tau: float) -> int:\n",
" qprog = create_program(n_qbits, t, tau)\n",
" return count_cx_ops_in_qprog(qprog)\n",
"\n",
"\n",
"def count_cx_theory(n_qbits: int, t: float, tau: float) -> int:\n",
" steps = get_steps(t, tau)\n",
" return steps*((9*(n_qbits**2)) - (33*n_qbits) + 34)"
" return steps * ((9 * (n_qbits**2)) - (33 * n_qbits) + 34)"
]
},
{
Expand All @@ -627,7 +640,9 @@
"source": [
"classiq_cx_count = count_cx_ops_in_qprog(qprog_t_1)\n",
"paper_cx_estimation = count_cx_theory(n_qbits, t, tau)\n",
"print(f\"Classiq CX count: {classiq_cx_count}; Paper CX estimation: {paper_cx_estimation}\")"
"print(\n",
" f\"Classiq CX count: {classiq_cx_count}; Paper CX estimation: {paper_cx_estimation}\"\n",
")"
]
},
{
Expand Down Expand Up @@ -682,7 +697,7 @@
"outputs": [],
"source": [
"paper_cx_counts = [count_cx_theory(n_qbits, t_, tau) for t_ in times]\n",
"ratio = [cx_counts[i]/paper_cx_counts[i] for i in range(len(times))]"
"ratio = [cx_counts[i] / paper_cx_counts[i] for i in range(len(times))]"
]
},
{
Expand Down Expand Up @@ -774,26 +789,33 @@
}
],
"source": [
"qbits_range = list(range(2, n_qbits+1))\n",
"qbits_range = list(range(2, n_qbits + 1))\n",
"\n",
"\n",
"def count_cx_for_cry(n: CInt) -> int:\n",
" @qfunc\n",
" def main(control_qbits: Output[QArray], target: Output[QBit]):\n",
" allocate(n-1, control_qbits)\n",
" allocate(n - 1, control_qbits)\n",
" allocate(1, target)\n",
" hadamard_transform(control_qbits)\n",
" X(target)\n",
" control(ctrl=control_qbits, stmt_block=lambda: RY(np.pi/4, target))\n",
" control(ctrl=control_qbits, stmt_block=lambda: RY(np.pi / 4, target))\n",
"\n",
" my_model = create_model(main)\n",
" my_qprog = synthesize(my_model)\n",
" circuit = QuantumProgram.from_qprog(my_qprog)\n",
" return circuit.transpiled_circuit.count_ops[\"cx\"]\n",
"\n",
"cx_counts_for_cry = { qbits: (count_cx_for_cry(qbits), 16*qbits - 40 if qbits > 2 else 2) for qbits in qbits_range }\n",
"\n",
"cx_counts_for_cry = {\n",
" qbits: (count_cx_for_cry(qbits), 16 * qbits - 40 if qbits > 2 else 2)\n",
" for qbits in qbits_range\n",
"}\n",
"print(f\"CX count for CRY:\")\n",
"for qbits, counts in cx_counts_for_cry.items():\n",
" print(f\"[{qbits} qubits] classiq's count: {counts[0]}; paper prediction: {counts[1]}\")\n",
"\n"
" print(\n",
" f\"[{qbits} qubits] classiq's count: {counts[0]}; paper prediction: {counts[1]}\"\n",
" )"
]
},
{
Expand Down
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