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.. bio:: Hayk Tepanyan | ||
:photo: ../_static/authors/hayk_tepanyan.jpeg | ||
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Hayk Tepanyan is the Co-Founder and CTO of BlueQubit — a quantum software and algorithms company. Hayk is coming from a computer science background and is focusing on quantum computing simulations and applications. |
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{ | ||
"title": "Using the BlueQubit (CPU) device with PennyLane", | ||
"authors": [ | ||
{ | ||
"username": "hayk_tepanyan" | ||
} | ||
], | ||
"dateOfPublication": "2024-09-24T00:00:00+00:00", | ||
"dateOfLastModification": "2024-09-24T00:00:00+00:00", | ||
"categories": [ | ||
"Devices and Performance", | ||
"Quantum Computing" | ||
], | ||
"tags": [], | ||
"previewImages": [ | ||
{ | ||
"type": "thumbnail", | ||
"uri": "/_static/demo_thumbnails/regular_demo_thumbnails/thumbnail_bluequbit-pennylane_device.png" | ||
}, | ||
{ | ||
"type": "large_thumbnail", | ||
"uri": "/_static/demo_thumbnails/large_demo_thumbnails/thumbnail_large_bluequbit-pennylane_device.png" | ||
} | ||
], | ||
"seoDescription": "Run large-scale quantum simulations with PennyLane and BlueQubit.", | ||
"doi": "", | ||
"canonicalURL": "/qml/demos/tutorial_bluequbit", | ||
"references": [ | ||
{ | ||
"id": "Draper2000", | ||
"type": "article", | ||
"title": "Addition on a Quantum Computer", | ||
"authors": "Thomas G. Draper", | ||
"year": "2000", | ||
"journal": "", | ||
"url": "https://arxiv.org/abs/quant-ph/0008033" | ||
} | ||
], | ||
"basedOnPapers": [], | ||
"referencedByPapers": [], | ||
"relatedContent": [ | ||
{ | ||
"type": "demonstration", | ||
"id": "tutorial_qft_arithmetics", | ||
"weight": 1.0 | ||
}, | ||
{ | ||
"type": "demonstration", | ||
"id": "tutorial_qft", | ||
"weight": 1.0 | ||
} | ||
], | ||
"hardware": [ | ||
{ | ||
"id": "bluequbit", | ||
"link": "https://app.bluequbit.io/", | ||
"logo": "/_static/hardware_logos/bluequbit.png" | ||
} | ||
] | ||
} |
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r"""Using the BlueQubit (CPU) device with PennyLane | ||
============================================================= | ||
Running large-scale simulations usually requires lots of memory and compute power, regular laptops already struggle above 20 qubits | ||
and most of the time 30+ qubits are a no-go. | ||
Using the `BlueQubit device <https://app.bluequbit.io/sdk-docs/index.html>`_, PennyLane users can now run circuit simulations on souped up machines and go up to 33 qubits! | ||
Also, Bluequbit uses a custom build of `PennyLane-Lightning <https://docs.pennylane.ai/projects/lightning/en/stable/index.html>`__ that | ||
enables multi-threading and other configurations to achieve the best possible performance. | ||
Below we will show 2 examples of how to use BlueQubit with PennyLane. | ||
The first is a very simple example building a Bell pair, and the second one is a large 26-qubit circuit that demonstrates the central limit theorem using quantum arithmetic. | ||
.. note:: | ||
To follow along with this tutorial on your own computer, you will need the | ||
`BlueQubit SDK <https://app.bluequbit.io/sdk-docs/index.html>`_. It can be installed via pip: | ||
.. code-block:: bash | ||
pip install bluequbit | ||
.. figure:: ../_static/demo_thumbnails/opengraph_demo_thumbnails/OGthumbnail_bluequbit-pennylane_device.png | ||
:align: center | ||
:width: 70% | ||
:target: javascript:void(0) | ||
Build your PennyLane circuit | ||
---------------------------- | ||
Here we will build a simple :doc:`Bell pair </glossary/what-are-bell-states>` and simulate it on the BlueQubit backend. | ||
Later in this tutorial we will show a larger example — a 26-qubit circuit that demonstrates the central limit theorem using a `Draper QFT adder <https://pennylane.ai/qml/demos/tutorial_qft_arithmetics>`__. | ||
Here is the example circuit we will be simulating: | ||
""" | ||
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import pennylane as qml | ||
import matplotlib.pyplot as plt | ||
import numpy as np | ||
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def bell_pair(): | ||
qml.Hadamard(0) | ||
qml.CNOT(wires=(0, 1)) | ||
return qml.probs() | ||
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fig = qml.draw_mpl(bell_pair)() | ||
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############################################################################## | ||
# Use the BlueQubit device | ||
# ------------------------ | ||
# Here are the 3 easy steps to simulate the above circuit on the BlueQubit backend: | ||
# | ||
# 1. Open an account at `app.bluequbit.io <https://app.bluequbit.io/>`__ to get a token. You can also view your submitted jobs here later. | ||
# 2. Initialize the `bluequbit` device with your token. | ||
# 3. Submit the circuit for simulation! | ||
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import bluequbit | ||
bluequbit.logger.setLevel("ERROR") | ||
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# STEP 2: Initialize the bluequbit device! | ||
# Using a guest token here. Replace it with your own token for a better experience. | ||
bq_dev = qml.device("bluequbit.cpu", wires=2, token="3hmIGLWGKzKdWmxLoJ5F24P3rivGL04d") | ||
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bell_qnode = qml.QNode(bell_pair, bq_dev) | ||
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# STEP 3: Simulate the circuit! | ||
result = bell_qnode() | ||
print(result) | ||
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############################################# | ||
# And that's it! Circuit details and visualizations will also appear in your BlueQubit account after this run. | ||
# | ||
# Now we can run even larger (up to 33-qubit) circuit simulations the same way! | ||
# | ||
# Larger workloads: 26 qubits | ||
# --------------------------- | ||
# Here we will see a much larger example — a 26-qubit circuit. | ||
# Inspired by `Guillermo Allonso's <https://www.pennylane.ai/profile/ketpuntog>`__ PennyLane Demo `Basic arithmetic with the quantum Fourier transform (QFT) <https://pennylane.ai/qml/demos/tutorial_qft_arithmetics>`__, | ||
# which implements a quantum adder in PennyLane, we build our own adder and use it to add together quantum registers. | ||
# | ||
# In the quantum world we can use the idea of superposition to add multiple numbers at the same time. | ||
# Furthermore, since each number in the superposition can have its own weight, we can use this adder to sum together distributions! | ||
# Below we will use that idea to demonstrate the `central limit theorem <https://en.wikipedia.org/wiki/Central_limit_theorem>`__: we will add together a couple of sequences of independent and identically distributed variables (namely uniformly distributed) | ||
# and see what their outcome will look like. | ||
# | ||
# It should take approximately 1 minute to run the code below. | ||
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def draper_adder(wires_a, wires_b, kind="fixed", include_qft=True, include_iqft=True): | ||
""" | ||
Implement the Draper adder for qubit registers of different sizes using PennyLane. | ||
Args: | ||
wires_a (list): Wires for the first register (smaller or equal size). | ||
wires_b (list): Wires for the second register (larger or equal size). | ||
kind (str): The kind of adder, can be 'half' or 'fixed' (default: 'fixed'). if kind='half' min(wires_b)-1 is the additional qubit of second register | ||
include_qft (bool): Whether to include the QFT part (default: True). | ||
include_iqft (bool): Whether to include the inverse QFT part (default: True). | ||
""" | ||
m = len(wires_a) | ||
n = len(wires_b) | ||
if kind == "half": | ||
wires_sum = [min(wires_b) - 1] + wires_b | ||
else: | ||
wires_sum = wires_b | ||
# QFT part | ||
if include_qft: | ||
qml.QFT(wires=wires_sum) | ||
# Controlled rotations | ||
for j in range(m): | ||
for k in range(n - j): | ||
lam = np.pi / (2**k) | ||
qml.ControlledPhaseShift(lam, wires=[wires_a[-j-1], wires_sum[j+k]]) | ||
if kind == "half": | ||
for j in range(m): | ||
lam = np.pi / (2 ** (j + 1 + n - m)) | ||
qml.ControlledPhaseShift(lam, wires=[wires_a[j], wires_sum[-1]]) | ||
# Inverse QFT part | ||
if include_iqft: | ||
qml.adjoint(qml.QFT)(wires=wires_sum) | ||
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# Using a guest token here. Replace it with your own token for a better experience. | ||
dev = qml.device("bluequbit.cpu", wires = 26, shots = None, token="3hmIGLWGKzKdWmxLoJ5F24P3rivGL04d") | ||
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@qml.qnode(dev) | ||
def add_4_6qubit_uniforms(): | ||
regs = [list(range(0,6)), | ||
list(range(6,12)), | ||
list(range(12,18)), | ||
list(range(18,26))] | ||
# make each register uniform 0-63 | ||
for reg in regs: | ||
for j in range(6): | ||
qml.Hadamard(reg[-j-1]) | ||
# calcualte sum | ||
draper_adder(regs[0], regs[3][-6:], kind="half") | ||
draper_adder(regs[1], regs[3][-7:], kind="half", include_iqft=False) | ||
draper_adder(regs[2], regs[3], include_qft=False) # skip I=QFT+iQFT, a small optimization | ||
return qml.probs(wires=regs[3]) | ||
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res = add_4_6qubit_uniforms() | ||
plt.figure(figsize=(32, 8)) | ||
bar = plt.bar(np.arange(len(res)), res) | ||
plt.tick_params(axis='x', labelsize=30) | ||
plt.tick_params(axis='y', labelsize=30) | ||
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############################################# | ||
# Wow, that looks like a Gaussian distribution! | ||
# | ||
# That's exactly what's expected from the central limit theorem — adding together multiple sequences of independent and identically distributed variables approximates the normal distribution. | ||
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############################################# | ||
# Conclusion | ||
# ---------- | ||
# | ||
# In this tutorial we saw how PennyLane users can run large circuit simulations on BlueQubit's souped up machines. | ||
# We demonstrated this both on a small example, as well as a large 26-qubit simulation where we added together uniform | ||
# distributions to approximate a normal distribution. | ||
# | ||
# PennyLane users can now simulate large circuits of up to 33 qubits for free using `BlueQubit <https://app.bluequbit.io/sdk-docs/index.html>`_ — we are looking forward to seeing the | ||
# creative and innovative ways researchers and quantum enthusiasts will be using this capability! | ||
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############################################# | ||
# References | ||
# ---------- | ||
# | ||
# .. [#Draper2000] | ||
# | ||
# Thomas G. Draper, "Addition on a Quantum Computer". `arXiv:quant-ph/0008033 <https://arxiv.org/abs/quant-ph/0008033>`__. | ||
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############################################################################## | ||
# About the author | ||
# ---------------- | ||
# |
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