### Install Cirq and qsim

Source: https://quantumai.google/cirq/simulate/qvm_basic_example

Installs the necessary Cirq libraries and the qsimcirq simulator. This is a prerequisite for running the examples.

```python
# @title Install `cirq_google` and `qsimcirq`

try:
    import cirq
    import cirq_google
except ImportError:
    print("installing cirq...")
    !pip install --quiet cirq-google
    print("installed cirq.")
    import cirq
    import cirq_google

try:
    import qsimcirq
except ImportError:
    print("installing qsimcirq...")
    !pip install --quiet qsimcirq
    print(f"installed qsimcirq.")
    import qsimcirq

# Other modules used in this colab
import matplotlib.pyplot as plt
import time

```

--------------------------------

### Install Unitary Library and Import Alpha Module

Source: https://quantumai.google/cirq/experiments/unitary/unitary/tic_tac_toe

Installs the Unitary library from GitHub and imports the alpha module for use in the tutorial. This is the initial setup step.

```python
!pip install --quiet git+https://github.com/quantumlib/Unitary@main

import unitary.alpha as alpha
```

--------------------------------

### Install Unitary Library

Source: https://quantumai.google/cirq/experiments/quantum_chess/concepts

Installs the unitary library if it's not already present. This is a prerequisite for running the Quantum Chess examples.

```python
try:
    import unitary
except ImportError:
    !pip install --quiet git+https://github.com/quantumlib/unitary
```

--------------------------------

### Setup Cirq and Cirq-Google Libraries

Source: https://quantumai.google/cirq/simulate/virtual_engine_interface

Installs and imports the necessary Cirq and Cirq-Google libraries. This setup is required before interacting with Cirq's simulation or hardware interfaces.

```python
try:
    import cirq
    import cirq_google
except ImportError:
    print("installing cirq...")
    !pip install --quiet cirq
    print("installed cirq.")
    import cirq
    import cirq_google

import sympy

```

--------------------------------

### Setup Cirq and Dependencies

Source: https://quantumai.google/cirq/hardware/qubit_picking

Imports the necessary Cirq library, Cirq Google extensions, NumPy, and Matplotlib. Includes a check to install Cirq if it's not already present.

```python
# @title Setup
try:
    import cirq
except ImportError:
    print("installing cirq...")
    !pip install --quiet cirq
    print("installed cirq.")
    import cirq

import cirq_google
import numpy as np
from matplotlib import pyplot as plt

```

--------------------------------

### Install Cirq

Source: https://quantumai.google/cirq/build/qudits

Installs the Cirq library if it is not already present. This is a common setup step for Cirq projects.

```python
try:
    import cirq
except ImportError:
    print("installing cirq...")
    !pip install --quiet cirq
    print("installed cirq.")

```

--------------------------------

### Install Unitary from Source

Source: https://quantumai.google/cirq/experiments/unitary/unitary/getting_started

Install the Unitary library using pip after cloning the repository and navigating to its directory.

```bash
pip install .
```

--------------------------------

### Install and Import Cirq

Source: https://quantumai.google/cirq/start/basics

Installs Cirq if not already present and imports the library along with cirq_google. This is a common setup for Cirq projects.

```python
try:
    import cirq
except ImportError:
    print("installing cirq...")
    !pip install --quiet cirq
    print("installed cirq.")
    import cirq

import cirq_google
```

--------------------------------

### Setup Cirq and Dependencies

Source: https://quantumai.google/cirq/build/pauli_observables

Imports the necessary Cirq library and its Google-specific extensions, along with sympy and numpy. Includes a check to install Cirq if it's not already present.

```python
try:
    import cirq
except ImportError:
    print("installing cirq...")
    !pip install --quiet cirq
    print("installed cirq.")
    import cirq

import cirq_google
import sympy
import numpy as np

```

--------------------------------

### Install and Import Cirq

Source: https://quantumai.google/cirq/build/qubits

Ensures Cirq is installed and imported for use in the current environment. This is a common setup step for Cirq projects.

```python
try:
    import cirq
except ImportError:
    print("installing cirq...")
    !pip install --quiet cirq
    print("installed cirq.")
    import cirq
```

--------------------------------

### Install Quantum Chess Package

Source: https://quantumai.google/cirq/experiments/quantum_chess/quantum_chess_rest_api

Install the Quantum Chess package from its GitHub repository using pip. The '-q' flag suppresses installation output.

```bash
pip install -q git+https://github.com/quantumlib/unitary/

```

--------------------------------

### Install Cirq and qsim

Source: https://quantumai.google/cirq/simulate/qvm_builder_code

Installs the `cirq-google` and `qsimcirq` libraries if they are not already present. This is a prerequisite for using the Quantum Virtual Machine.

```python
# @title Install `cirq_google` and `qsimcirq`

try:
    import cirq
    import cirq_google
except ImportError:
    print("installing cirq...")
    !pip install --quiet cirq-google
    print("installed cirq.")
    import cirq
    import cirq_google

try:
    import qsimcirq
except ImportError:
    print("installing qsimcirq...")
    !pip install --quiet qsimcirq
    print(f"installed qsimcirq.")
    import qsimcirq

import time

```

--------------------------------

### Install ReCirq

Source: https://quantumai.google/cirq/experiments/qcqmc/high_level

Installs the recirq library. Use this if the library is not already installed.

```python
try:
    import recirq
except ImportError:
    %pip install git+https://github.com/quantumlib/ReCirq
```

--------------------------------

### Install Dependencies

Source: https://quantumai.google/cirq/experiments/quantum_chess/quantum_chess_client

Installs the 'unitary' and 'requests' libraries if they are not already present. This is a prerequisite for running the client.

```python
try:
    import unitary
except ImportError:
    !pip install git+https://github.com/quantumlib/unitary -q

try:
    import requests
except ImportError:
    !pip install requests -q
```

--------------------------------

### Install Cirq and qsimcirq

Source: https://quantumai.google/cirq/simulate/qvm_stabilizer_example

Installs the necessary Cirq and qsimcirq libraries. This is required before creating a Quantum Virtual Machine.

```python
# @title Install `cirq_google` and `qsimcirq`

try:
    import cirq
    import cirq_google
except ImportError:
    print("installing cirq...")
    !pip install --quiet cirq-google
    print("installed cirq.")
    import cirq
    import cirq_google

try:
    import qsimcirq
except ImportError:
    print("installing qsimcirq...")
    !pip install --quiet qsimcirq
    print(f"installed qsimcirq.")
    import qsimcirq

# Other modules used in this colab
import numpy as np
import matplotlib.pyplot as plt
import time
import random

```

--------------------------------

### Install Cirq Google and QSimCirq

Source: https://quantumai.google/cirq/simulate/quantum_virtual_machine

Installs the `cirq_google` and `qsimcirq` libraries if they are not already present. This is a prerequisite for using the quantum virtual machine.

```python
# @title Install `cirq_google` and `qsimcirq`

try:
    import cirq
    import cirq_google
except ImportError:
    print("installing cirq...")
    !pip install --quiet cirq-google
    print("installed cirq.")
    import cirq
    import cirq_google

try:
    import qsimcirq
except ImportError:
    print("installing qsimcirq...")
    !pip install --quiet qsimcirq
    print(f"installed qsimcirq.")
    import qsimcirq

```

--------------------------------

### Example Output of Processor Listing

Source: https://quantumai.google/cirq/tutorials/google/colab

This is an example output demonstrating the format of available processors when listed using `engine.list_processors()`.

```text
Successful authentication using project !
Available Processors: 
[<cirq_google.engine.simulated_local_processor.SimulatedLocalProcessor object at 0x7f3c18e0b490>, <cirq_google.engine.simulated_local_processor.SimulatedLocalProcessor object at 0x7f3c18e55660>]
Using processor: rainbow


```

--------------------------------

### Install Quantum Chess Package

Source: https://quantumai.google/cirq/experiments/unitary/quantum_chess/quantum_chess_rest_api

Installs the Quantum Chess package from its GitHub repository. Use this command in your terminal or notebook environment.

```bash
pip install -q git+https://github.com/quantumlib/unitary.

```

--------------------------------

### Install Cirq using pip

Source: https://quantumai.google/cirq/start/install

Use this command to install or upgrade pip and then install the Cirq library. Ensure you have Python 3.11.0 or greater.

```bash
python -m pip install --upgrade pip
python -m pip install cirq
```

--------------------------------

### Install ReCirq and OpenFermion-pyscf

Source: https://quantumai.google/cirq/experiments/hfvqe/molecular_data

Installs the necessary ReCirq and OpenFermion-pyscf packages if they are not already present. Use the quiet flag to suppress installation output.

```python
try:
    import recirq
except ImportError:
    !pip install --quiet git+https://github.com/quantumlib/ReCirq

try:
    import openfermionpyscf
except ImportError:
    !pip install --quiet openfermionpyscf~=0.5.0
```

--------------------------------

### Example IonQ Targets Output

Source: https://quantumai.google/cirq/hardware/azure-quantum/getting_started_ionq

This is an example output showing available IonQ targets, including their average queue time and availability status.

```text
[<Target name="ionq.qpu", avg. queue time=19 s, Available>,
 <Target name="ionq.simulator", avg. queue time=0 s, Available>

```

--------------------------------

### Example QAOA Cut Size Output

Source: https://quantumai.google/cirq/experiments/qaoa/qaoa_maxcut

This is an example output showing the cut size achieved by the QAOA algorithm.

```text
Cut size: 30.930000000000003
```

--------------------------------

### Install Unitary via Pip (Directly from GitHub)

Source: https://quantumai.google/cirq/experiments/unitary/unitary/getting_started

Install the Unitary library directly from its GitHub repository using pip. It is recommended to do this within a virtual environment.

```bash
pip install --quiet git+https://github.com/quantumlib/unitary.git
```

--------------------------------

### Install Cirq and Cirq-Google

Source: https://quantumai.google/cirq/tutorials/google/start

Installs the cirq-google and cirq libraries if they are not already present. This is a prerequisite for accessing Google's quantum processors.

```python
try:
    import cirq
    import cirq_google as cg
except ImportError:
    print("installing cirq-google and cirq...")
    !pip install --quiet cirq-google cirq
    print("installed cirq-google and cirq.")
    import cirq
    import cirq_google as cg
```

--------------------------------

### Initialize Local Simulator (Ideal)

Source: https://quantumai.google/cirq/hardware/aqt/getting_started

Sets up a local AQT simulator for ideal (noise-free) quantum circuit simulations.

```python
from cirq.aqt.aqt_sampler import AQTSamplerLocalSimulator

aqt_sampler = AQTSamplerLocalSimulator(simulate_ideal=True)

```

--------------------------------

### Initialize AQT Sampler

Source: https://quantumai.google/cirq/hardware/aqt/getting_started

Sets up the AQTSampler with your access token, workspace, and resource name to interact with AQT's quantum devices.

```python
import cirq
from cirq.aqt.aqt_device import get_aqt_device
from cirq.aqt.aqt_sampler import AQTSampler

access_token = 'MY_TOKEN'

```

--------------------------------

### Initialize Local Simulator (With Noise)

Source: https://quantumai.google/cirq/hardware/aqt/getting_started

Sets up a local AQT simulator to simulate quantum circuits with a noise model, estimating real hardware performance.

```python
from cirq.aqt.aqt_sampler import AQTSamplerLocalSimulator

aqt_sampler = AQTSamplerLocalSimulator(simulate_ideal=False)

```

--------------------------------

### Initialize and Run a Circuit with PasqalSampler

Source: https://quantumai.google/cirq/hardware/pasqal/sampler

Demonstrates how to initialize the PasqalSampler with an access token and run a simple quantum circuit. Ensure you replace 'my_token' with your actual PASQAL_API_ACCESS_TOKEN.

```python
import cirq
from cirq_pasqal import ThreeDQubit, PasqalVirtualDevice, PasqalSampler

# A simple sample circuit
qubit = ThreeDQubit(0, 0, 0)
p_circuit = cirq.Circuit()
p_circuit.append(cirq.X(qubit))                        # NOT gate.
p_circuit.append(cirq.measure(qubit, key='result'))    # Measurement.


# Create a PasqalSampler object to use.
# Replace 'my_token' with the access token and uncomment next lines.

PASQAL_API_ACCESS_TOKEN = 'my_token'
sampler = PasqalSampler(remote_host='http://34.98.71.118/v0/pasqal', access_token=PASQAL_API_ACCESS_TOKEN)
results = sampler.run(p_circuit, repetitions=1000) # Runs the circuit and returns the results in a 'Result'

```

--------------------------------

### InsertStrategy.NEW_THEN_INLINE Example

Source: https://quantumai.google/cirq/build/circuits

Demonstrates InsertStrategy.NEW_THEN_INLINE, which starts by creating a new moment and then uses the INLINE strategy for subsequent operations.

```python
circuit = cirq.Circuit()
circuit.append([cirq.H(q0)])
circuit.append([cirq.CZ(q1, q2), cirq.H(q0)], strategy=InsertStrategy.NEW_THEN_INLINE)

print(circuit)

```

--------------------------------

### Example: Executing Shor's Algorithm and Post-processing

Source: https://quantumai.google/cirq/experiments/shor

This example demonstrates how to create an order finding circuit, execute it, and then use the `process_measurement` function to find the order 'r'. Note that the quantum part of the algorithm has a probability of success, so re-running may be necessary.

```python
"""Example of the classical post-processing."""

# Set n and x here
n = 6
x = 5

print(f"Finding the order of x = {x} modulo n = {n}\n")
measurement = cirq.sample(circuit, repetitions=1)
print("Raw measurements:")
print(measurement)

print("\nInteger in exponent register:")
print(measurement.data)

r = process_measurement(measurement, x, n)
print("\nOrder r =", r)
if r is not None:
    print(f"x^r mod n = {x}^{r} mod {n} = {x**r % n}")

```

--------------------------------

### Get Benchmark Configuration by Name

Source: https://quantumai.google/cirq/experiments/ftbbl

Retrieve a specific benchmark configuration using its full name. This is useful for selecting a particular setup for execution or analysis.

```python
config = algo.get_config_by_full_name('loschmidt.tilted_square_lattice.small-cz-v1')
print(config.description)
```

--------------------------------

### Create AQT Sampler Instance

Source: https://quantumai.google/cirq/hardware/aqt/getting_started

Instantiates an AQTSampler for a specific workspace and resource, using your provided access token.

```python
workspace = 'WORKSPACE_NAME'
resource = 'RESOURCE_NAME'
aqt_sampler = AQTSampler(workspace=workspace, resource=resource, access_token=access_token)

```

--------------------------------

### Initialize PasqalVirtualDevice

Source: https://quantumai.google/cirq/hardware/pasqal/devices

Shows how to initialize a PasqalVirtualDevice with a specified control radius and a predefined set of qubits. The control radius influences qubit connectivity.

```python
from cirq_pasqal import PasqalVirtualDevice

# A PasqalVirtualDevice with a control radius of 2.0 times the lattice spacing.
p_device = PasqalVirtualDevice(control_radius=2.0, qubits=p_qubits)
```

--------------------------------

### Set up Sampler (Simulator or Device)

Source: https://quantumai.google/cirq/noise/qcvv/isolated_xeb

Configures a sampler for noisy simulations using `cirq.DensityMatrixSimulator` or retrieves a sampler for a real device via `cirq_google`. For real devices, it also sets up device information and routing graphs.

```python
device_name = None  # change me!

if device_name is None:
    sampler = cirq.DensityMatrixSimulator(noise=cirq.depolarize(5e-3))
else:
    import cirq_google as cg

    sampler = cg.get_engine_sampler(device_name, gate_set_name='sqrt_iswap')
    device = cg.get_engine_device(device_name)

    import cirq.contrib.routing as ccr

    graph = ccr.gridqubits_to_graph_device(device.qubits)
    pos = {q: (q.row, q.col) for q in graph.nodes}
    import networkx as nx

    nx.draw_networkx(graph, pos=pos)

```

--------------------------------

### Install Cirq Contrib Dependencies

Source: https://quantumai.google/cirq/start/install

Install optional dependencies for features within cirq.contrib. This command installs the cirq-core package with the 'contrib' extra.

```bash
python -m pip install 'cirq-core[contrib]'

```

--------------------------------

### Create and Visualize a Simple Circuit

Source: https://quantumai.google/cirq/experiments/benchmarks/rabi_oscillations

Builds a quantum circuit with an RX gate and a measurement, then visualizes it using SVGCircuit. Ensure numpy is imported as np.

```python
from cirq.contrib.svg import SVGCircuit

# Create a circuit with X, Ry(pi/2) and H.
my_circuit = cirq.Circuit(
    # Rotate the qubit pi/2 radians around the X axis.
    cirq.rx(np.pi / 2).on(my_qubit),
    # Measure the qubit.
    cirq.measure(my_qubit, key="out"),
)
SVGCircuit(my_circuit)
```

--------------------------------

### Install System Dependencies

Source: https://quantumai.google/cirq/dev/development

Installs system dependencies required for Cirq development using apt. Ensure Python 3.11 or greater is installed.

```bash
cat apt-system-requirements.txt dev_tools/conf/apt-list-dev-tools.txt | xargs sudo apt-get install --yes

```

--------------------------------

### Create a Device-Ready Circuit

Source: https://quantumai.google/cirq/simulate/qvm_builder_code

Prepare a circuit tailored for a specific quantum device. This example demonstrates creating a circuit with a Hadamard gate and a measurement on a specific qubit.

```python
# create your device ready circuit here!
q0 = cirq.GridQubit(6, 3)
your_circuit = cirq.Circuit([(cirq.X**0.5)(q0), cirq.measure(q0)])
print(your_circuit)

```

```text
(6, 3): ───X^0.5───M───

```

--------------------------------

### Install Cirq contrib dependencies

Source: https://quantumai.google/cirq/start/install

Install optional dependencies for features within `cirq.contrib`. This command installs the core Cirq library along with the contrib extras.

```bash
python -m pip install 'cirq-core[contrib]'
```

--------------------------------

### Install ReCirq and Cirq

Source: https://quantumai.google/cirq/experiments/time_crystals/time_crystal_circuit_generation

Installs the necessary libraries, Cirq and ReCirq, for time crystal circuit generation. Includes a fallback to install ReCirq from GitHub if it's not found.

```python
!pip install cirq --quiet
try:
    import recirq
except ImportError:
    !pip install --quiet git+https://github.com/quantumlib/ReCirq

```

--------------------------------

### Editable Installs for Cirq Modules

Source: https://quantumai.google/cirq/dev/development

Install Cirq modules in an editable fashion to pick up code changes immediately. Ensure you install each module separately for effective development.

```bash
pip install -e ./cirq-core -e ./cirq-google -e ./cirq-ionq -e ./cirq-aqt
```

--------------------------------

### Initialize Quantum Chess Board

Source: https://quantumai.google/cirq/experiments/quantum_chess/quantum_chess_client

Initializes a quantum chess board with the starting occupancy state using bitboard representation. The server should be running and accessible via the provided ngrok URL.

```APIDOC
## POST /quantumboard/init

### Description
Initializes a quantum chess board with the starting occupancy state of all pieces. The initial positions are given by the hex 0xFFFF00000000FFFF, occupying ranks 1, 2, 7, and 8.

### Method
POST

### Endpoint
/quantumboard/init

### Request Body
- **init_basis_state** (hex) - Required - The initial state of the board represented as a hexadecimal bitboard.

### Request Example
```json
{
  "init_basis_state": "0xFFFF00000000FFFF"
}
```

### Response
#### Success Response (200)
- **probabilities** (list of floats) - A list representing the probabilities of each state.
- **empty** (integer) - The number of empty squares.
- **full** (integer) - The number of occupied squares.

#### Response Example
```json
{
  "probabilities": [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0],
  "empty": 281474976645120,
  "full": 18446462598732906495
}
```
```

--------------------------------

### Example Counter Output

Source: https://quantumai.google/cirq/start/basics

This is an example of the output format for the Counter object when using samples.histogram().

```python
Counter({0: 533, 3: 467})

```

--------------------------------

### Create Quantum Virtual Machine

Source: https://quantumai.google/cirq/simulate/qvm_stabilizer_example

Creates a Quantum Virtual Machine using a specified processor ID and the QSimSimulator. It prints the qubit grid of the chosen processor.

```python
# @title Create Quantum Virtual Machine: Choose a processor ("willow_pink", "rainbow" or "weber")
# (see cirq_google.engine.list_virtual_processors() for available names)
processor_id = "willow_pink"  # @param {type:"string"}

# Instantiate the engine.
sim_engine = cirq_google.engine.create_default_noisy_quantum_virtual_machine(
    processor_id=processor_id,
    simulator_class=qsimcirq.QSimSimulator
)
print(
    "Your quantum virtual machine",
    processor_id,
    "is ready, here is the qubit grid:",
    "\n========================\n",
)
print(sim_engine.get_processor(processor_id).get_device())

```

--------------------------------

### Example Kraus Operators Output

Source: https://quantumai.google/cirq/build/operators

An example output showing the Kraus operators for a depolarizing channel.

```text
Kraus operators of depolarize(p=0.01) are:

[[0.99 0.  ]
 [0.   0.99]]

[[0.  +0.j 0.06+0.j]
 [0.06+0.j 0.  +0.j]]

[[0.+0.j   0.-0.06j]
 [0.+0.06j 0.+0.j  ]]

[[ 0.06+0.j  0.  +0.j]
 [ 0.  +0.j -0.06+0.j]]
```

--------------------------------

### Install and Import Cirq

Source: https://quantumai.google/cirq/hardware/ionq/getting_started

Installs Cirq if not already present and imports it. Requires Cirq version >0.9.

```python
try:
    import cirq

    version = cirq.__version__.split(".")
    assert int(version[0]) > 0 or int(version[1]) > 9, "Cirq version >0.9 required"
except (ImportError, AssertionError):
    print("Installing Cirq...")
    !pip install --quiet cirq
    print("Cirq installed.")

```

--------------------------------

### PasqalSampler Initialization and Circuit Execution

Source: https://quantumai.google/cirq/hardware/pasqal/sampler

Demonstrates how to initialize the PasqalSampler with an access token and execute a simple quantum circuit. Note that the Pasqal API is not yet publicly available.

```APIDOC
## PasqalSampler Class

The `PasqalSampler` class is the entry point to communicate with the API. It can be initialized using your PASQAL_API_ACCESS_TOKEN.

### Initialization
```python
import cirq
from cirq_pasqal import PasqalSampler

PASQAL_API_ACCESS_TOKEN = 'my_token' # Replace with your actual token
sampler = PasqalSampler(remote_host='http://34.98.71.118/v0/pasqal', access_token=PASQAL_API_ACCESS_TOKEN)
```

### Circuit Execution
```python
# A simple sample circuit
qubit = cirq.LineQubit(0)
p_circuit = cirq.Circuit()
p_circuit.append(cirq.X(qubit)) # NOT gate.
p_circuit.append(cirq.measure(qubit, key='result')) # Measurement.

results = sampler.run(p_circuit, repetitions=1000) # Runs the circuit and returns the results
```

**Note:** The Pasqal API is not yet open for public access. Please contact Pasqal if you are interested.
```

--------------------------------

### Example Measurement Results

Source: https://quantumai.google/cirq/tutorials/google/colab

This is an example output of measurement results from running a Cirq circuit in Google Colab.

```text
Success!  Results:
1110110001100001011110100000010010110001101111011110101000010011001110010111010001001101100000111101100110101111010010011000010100011111111000010011010000100001001111111011000001100011001000000111011011110011011000001110101100011110010011011010111101100010001110100111100110110100111100011011111110110100101111011000000011000110110011100000100101000110101000100111001010100010101110011010111011010010100110111011011110110011000110110100110000101101011110001011111000110000001100100111011000111010000001011001001010001101110001101111100011110000110010101111100010110001010011101100111110111111111001010011111100110010010111101010111111110110100111111110000001011001111010100101000110101000101011010111111101100001010011111011011000010001111111001000110101010001011011111001010110101011001110101110010101110100101001100010010011101100011000001111110001000011100000100011011111000010110100000011010100111001010101111100011001111111011111011010000010101000111111101001111011111111001101111000001101101
```

--------------------------------

### Example Post-Selection Output

Source: https://quantumai.google/cirq/experiments/quantum_chess/concepts

An example of the output from the `histogram_post_select` function, showing the frequency of measurements for each square after post-selection.

```json
{
'a1': np.int64(0),
'a2': np.int64(0),
'a3': np.int64(0),
'b1': np.int64(0),
'b2': np.int64(503),
'b3': np.int64(0),
'c1': np.int64(246),
'c2': np.int64(257),
'c3': np.int64(0)
}
```

--------------------------------

### Instantiate and Use HardcodedQubitPlacer

Source: https://quantumai.google/cirq/google/qubit-placement

Demonstrates how to create a HardcodedQubitPlacer with a pre-generated mapping and then use it to place a circuit. It also shows how to visualize the resulting placement.

```python
rainbow_mapping = all_offset_placements(rainbow_graph)
hardcoded = HardcodedQubitPlacer(mapping=rainbow_mapping)

placed_c, placement = hardcoded.place_circuit(
    circuit, problem_topology=topo, shared_rt_info=shared_rt_info, rs=rs
)
cirq.draw_placements(rainbow_graph, circuit_graph, [placement])

```

--------------------------------

### Install and Import Cirq

Source: https://quantumai.google/cirq/gatezoo

Installs Cirq if not already present and imports necessary libraries for gate manipulation and display.

```python
try:
    import cirq
except ImportError:
    print("installing cirq...")
    !pip install --quiet cirq
    print("installed cirq.")

import IPython.display as ipd
import cirq
import inspect
```

--------------------------------

### Install ReCirq Package

Source: https://quantumai.google/cirq/experiments/qaoa/example_problems

Installs the ReCirq package if it's not already available. This is a prerequisite for using ReCirq functionalities.

```python
try:
    import recirq
except ImportError:
    !pip install git+https://github.com/quantumlib/ReCirq
```

--------------------------------

### Sample from a Parameterized Circuit with sample

Source: https://quantumai.google/cirq/start/intro

The sample method provides a pandas DataFrame of results from simulating a parameterized circuit with multiple parameter configurations. Each column represents a parameter or measurement.

```python
results = simulator.sample(program=circuit, params=resolvers, repetitions=10)

results.describe()

```

--------------------------------

### Install ReCirq Library

Source: https://quantumai.google/cirq/experiments/fermi_hubbard/publication_results

Installs the ReCirq library if it's not already present. This is a prerequisite for running the Fermi-Hubbard experiments.

```python
try:
    import recirq
except ImportError:
    print("Installing ReCirq...")
    !pip install git+https://github.com/quantumlib/recirq --quiet
    print("Installed ReCirq!")

```

--------------------------------

### Set up Virtual Engine with Noisy Simulator

Source: https://quantumai.google/cirq/simulate/quantum_virtual_machine

Packages the noisy simulator and device into a quantum virtual engine. This ensures the virtual processor interface matches that of a real quantum processor, enabling consistent workflow.

```python
# Package the simulator and device in an Engine.
# The device object
device = cirq_google.engine.create_device_from_processor_id(processor_id)
# Load the median device noise calibration for your processor.
cal = cirq_google.engine.load_median_device_calibration(processor_id)
# The simulated processor object
sim_processor = cirq_google.engine.SimulatedLocalProcessor(
    processor_id=processor_id, sampler=sim, device=device, calibrations={cal.timestamp // 1000: cal}
)
# The virtual engine
sim_engine = cirq_google.engine.SimulatedLocalEngine([sim_processor])
print(
    "Your quantum virtual machine",
    processor_id,
    "is ready, here is the qubit grid:",
    "\n========================\n",
)
print(sim_engine.get_processor(processor_id).get_device())


```

--------------------------------

### Example output of measure_observables

Source: https://quantumai.google/cirq/build/pauli_observables

This is an example of the output format from the `measure_observables` function, showing the observable, its estimated mean, and its variance.

```text
Z(q(0))*Z(q(1)) 1.0 0.0
(4+0j)*X(q(0)) -0.24 0.16103434343434342
```

--------------------------------

### Install and Import Cirq and Dependencies

Source: https://quantumai.google/cirq/experiments/fourier_checking

Installs Cirq if not already present and imports necessary libraries like numpy, matplotlib, and pandas for the tutorial. Sets a random seed for reproducible results.

```python
# Initial setup to install Cirq and set up dependencies for the tutorial.
try:
    import cirq
except:
    print("installing cirq...")
    !pip install --quiet cirq
    print("installed cirq.")
    import cirq

from typing import Sequence
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd

# Sets a seed for deterministic results.  Uncomment for random results each run.
np.random.seed(2021)
np.set_printoptions(precision=3, suppress=True, linewidth=200)

```

--------------------------------

### Install ReCirq Package

Source: https://quantumai.google/cirq/experiments/guide/data_analysis

Install the ReCirq package if it's not already present. This is a prerequisite for using the data analysis utilities.

```python
try:
    import recirq
except ImportError:
    !pip install --quiet git+https://github.com/quantumlib/ReCirq
```

--------------------------------

### Example Random Cut Size Output

Source: https://quantumai.google/cirq/experiments/qaoa/qaoa_maxcut

This is an example output showing the cut size achieved by the random guessing method.

```text
Cut size: 30.030000000000005
```

--------------------------------

### Set up HF-VQE experiment

Source: https://quantumai.google/cirq/experiments/hfvqe/quickstart

Generates molecular data, sets up quantum resources (qubits and sampler), and initializes the OpdmFunctional for measurements and optimization.

```python
rhf_objective, molecule, parameters, obi, tbi = make_h6_1_3()
ansatz, energy, gradient = rhf_func_generator(rhf_objective)

# settings for quantum resources
qubits = [cirq.GridQubit(0, x) for x in range(molecule.n_orbitals)]
sampler = cirq.Simulator(dtype=np.complex128)  # this can be a QuantumEngine

# OpdmFunctional contains an interface for running experiments
opdm_func = OpdmFunctional(qubits=qubits,
                           sampler=sampler,
                           constant=molecule.nuclear_repulsion,
                           one_body_integrals=obi,
                           two_body_integrals=tbi,
                           # only simulate spin-up electrons:
                           num_electrons=molecule.n_electrons // 2,
                           clean_xxyy=True,
                           purification=True
                           )
```

--------------------------------

### Build Blueprint and Simulated Experiment

Source: https://quantumai.google/cirq/experiments/qcqmc/full_workflow

Construct a blueprint for the trial wavefunction and set up a simulated experiment using a statevector simulator. This involves defining parameters for the blueprint and the simulation, including noise models and sampling strategies.

```python
from recirq.qcqmc.blueprint import BlueprintParamsTrialWf, BlueprintData
from recirq.qcqmc.experiment import SimulatedExperimentParams, ExperimentData

blueprint_params = BlueprintParamsTrialWf(
    name="blueprint_test_medium",
    trial_wf_params=pp_params,
    n_cliffords=100,
    qubit_partition=(tuple(qubit for qubit in pp_params.qubits_jordan_wigner_ordered),),
    seed=1,
)

blueprint = BlueprintData.build_blueprint_from_dependencies(blueprint_params, dependencies={pp_params: trial_wf})

simulated_experiment_params = SimulatedExperimentParams(
    name="test_1",
    blueprint_params=blueprint.params,
    noise_model_name="None",
    noise_model_params=(0,),
    n_samples_per_clifford=31,
    seed=1,
)
experiment = ExperimentData.build_experiment_from_dependencies(
    params=simulated_experiment_params, dependencies={blueprint.params: blueprint}
)
```

--------------------------------

### Example Output: DataFrame Length

Source: https://quantumai.google/cirq/experiments/guide/data_analysis

This is an example output showing the length of the prepared DataFrame, indicating the number of qubits to be processed.

```text
5

```