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// Compile and run with: | ||
// ``` | ||
// nvq++ noise_callback.cpp --target density-matrix-cpu -o dyn.x | ||
// && ./dyn.x | ||
// ``` | ||
// | ||
// Note: You must set the target to a density matrix backend for the noise | ||
// to successfully impact the system. | ||
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#include <cudaq.h> | ||
#include <iostream> | ||
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// CUDA-Q supports several different models of noise. In this | ||
// case, we will examine the dynamic noise channel specified as a callback | ||
// function. | ||
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int main() { | ||
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// We will begin by defining an empty noise model that we will add | ||
// our channel to. | ||
cudaq::noise_model noise; | ||
// Noise model callback function | ||
const auto rx_noise = [](const auto &qubits, | ||
const auto ¶ms) -> cudaq::kraus_channel { | ||
// Model a pulse-length based rotation gate: | ||
// the bigger the angle, the longer the pulse, i.e., more amplitude damping. | ||
auto angle = params[0]; | ||
// Normalize the angle into the [0, 2*pi] range | ||
while (angle > 2. * M_PI) | ||
angle -= 2. * M_PI; | ||
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while (angle < 0) | ||
angle += 2. * M_PI; | ||
// Damping rate is linearly proportional to the angle | ||
const auto damping_rate = angle / (2. * M_PI); | ||
std::cout << "Angle = " << params[0] | ||
<< ", amplitude damping rate = " << damping_rate << "\n"; | ||
return cudaq::amplitude_damping_channel(damping_rate); | ||
}; | ||
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// Bind the noise model callback function to the `rx` gate | ||
noise.add_channel<cudaq::types::rx>(rx_noise); | ||
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auto kernel = [](double angle) __qpu__ { | ||
cudaq::qubit q; | ||
rx(angle, q); | ||
mz(q); | ||
}; | ||
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// Now let's set the noise and we're ready to run the simulation! | ||
cudaq::set_noise(noise); | ||
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// Our results should show measurements in both the |0> and |1> states, | ||
// indicating that the noise has successfully impacted the system. Note: a | ||
// `rx(pi)` is equivalent to a Pauli X gate, and thus, it should be in the |1> | ||
// state if no noise is present. | ||
auto noisy_counts = cudaq::sample(kernel, M_PI); | ||
std::cout << "Noisy result:\n"; | ||
noisy_counts.dump(); | ||
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// To confirm this, we can run the simulation again without noise. | ||
cudaq::unset_noise(); | ||
auto noiseless_counts = cudaq::sample(kernel, M_PI); | ||
std::cout << "Noiseless result:\n"; | ||
noiseless_counts.dump(); | ||
return 0; | ||
} |
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import cudaq | ||
import numpy as np | ||
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# Set the target to our density matrix simulator. | ||
cudaq.set_target('density-matrix-cpu') | ||
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noise = cudaq.NoiseModel() | ||
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# Noise model callback function | ||
def rx_noise(qubits, params): | ||
# Model a pulse-length based rotation gate: | ||
# the bigger the angle, the longer the pulse, i.e., more amplitude damping. | ||
angle = params[0] | ||
angle = angle % (2 * np.pi) | ||
# Damping rate is linearly proportional to the angle | ||
damping_rate = np.abs(angle / (2 * np.pi)) | ||
print(f"Angle = {angle}, amplitude damping rate = {damping_rate}.") | ||
return cudaq.AmplitudeDampingChannel(damping_rate) | ||
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# Bind the noise model callback function to the `rx` gate | ||
noise.add_channel('rx', rx_noise) | ||
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@cudaq.kernel | ||
def kernel(angle: float): | ||
qubit = cudaq.qubit() | ||
rx(angle, qubit) | ||
mz(qubit) | ||
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# Now we're ready to run the noisy simulation of our kernel. | ||
# Note: We must pass the noise model to sample via keyword. | ||
noisy_result = cudaq.sample(kernel, np.pi, noise_model=noise) | ||
print(noisy_result) | ||
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# Our results should show measurements in both the |0> and |1> states, indicating | ||
# that the noise has successfully impacted the system. | ||
# Note: a `rx(pi)` is equivalent to a Pauli X gate, and thus, it should be | ||
# in the |1> state if no noise is present. | ||
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# To confirm this, we can run the simulation again without noise. | ||
noiseless_result = cudaq.sample(kernel, np.pi) | ||
print(noiseless_result) |
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/******************************************************************************* | ||
* Copyright (c) 2022 - 2024 NVIDIA Corporation & Affiliates. * | ||
* All rights reserved. * | ||
* * | ||
* This source code and the accompanying materials are made available under * | ||
* the terms of the Apache License 2.0 which accompanies this distribution. * | ||
******************************************************************************/ | ||
#include "py_CustomOpRegistry.h" | ||
#include "common/CustomOp.h" | ||
#include <pybind11/complex.h> | ||
#include <pybind11/functional.h> | ||
#include <pybind11/stl.h> | ||
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namespace cudaq { | ||
struct py_unitary_operation : public unitary_operation { | ||
std::vector<std::complex<double>> | ||
unitary(const std::vector<double> ¶meters = | ||
std::vector<double>()) const override { | ||
throw std::runtime_error("Attempt to invoke the placeholder for Python " | ||
"unitary op. This is illegal."); | ||
return {}; | ||
} | ||
}; | ||
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void bindCustomOpRegistry(py::module &mod) { | ||
mod.def( | ||
"register_custom_operation", | ||
[&](const std::string &opName) { | ||
cudaq::customOpRegistry::getInstance() | ||
.registerOperation<py_unitary_operation>(opName); | ||
}, | ||
"Register a custom operation"); | ||
} | ||
} // namespace cudaq |
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/****************************************************************-*- C++ -*-**** | ||
* Copyright (c) 2022 - 2024 NVIDIA Corporation & Affiliates. * | ||
* All rights reserved. * | ||
* * | ||
* This source code and the accompanying materials are made available under * | ||
* the terms of the Apache License 2.0 which accompanies this distribution. * | ||
******************************************************************************/ | ||
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#include <pybind11/pybind11.h> | ||
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namespace py = pybind11; | ||
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namespace cudaq { | ||
/// @brief Bind the custom operation registry to Python. | ||
void bindCustomOpRegistry(py::module &mod); | ||
} // namespace cudaq |
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