Amazon Braket SDK

# Core SDK components
from braket._sdk import __version__

# Circuit construction and gates
from braket.circuits import Circuit, Gate, AngledGate, DoubleAngledGate
from braket.circuits.gates import H, CNot, Rx, Ry, Rz, X, Y, Z
from braket.circuits.observables import X as ObsX, Y as ObsY, Z as ObsZ, TensorProduct
from braket.circuits.result_types import StateVector, Expectation, Sample, Probability

# AWS integration
from braket.aws import AwsDevice, AwsQuantumTask, AwsSession, AwsDeviceType

# Local simulation
from braket.devices import LocalSimulator

# Quantum information utilities
from braket.quantum_information import PauliString

# Job management
from braket.jobs import hybrid_job

# Cost tracking
from braket.tracking import Tracker

# Parametric circuits and free parameters
from braket.circuits import FreeParameter, FreeParameterExpression, Parameterizable

# Program sets and parameter binding
from braket.program_sets import ProgramSet, ParameterSets, CircuitBinding

# Registers and qubit management
from braket.circuits import Qubit, QubitInput, QubitSet, QubitSetInput

# Circuit emulation and compilation
from braket.emulation import PassManager

# Timing data structures
from braket.timings import TimeSeries, TimeSeriesItem

from braket.circuits import Circuit
from braket.circuits.gates import H, CNot
from braket.devices import LocalSimulator
from braket.aws import AwsDevice

# Create a Bell state circuit
def create_bell_circuit() -> Circuit:
    """
    Creates a Bell state quantum circuit.
    
    Returns:
        Circuit: A quantum circuit that creates a Bell state
    """
    circuit = Circuit()
    circuit.h(0)
    circuit.cnot(0, 1)
    return circuit

# Run on local simulator
def run_local_simulation(circuit: Circuit, shots: int = 1000) -> dict:
    """
    Run circuit on local simulator.
    
    Args:
        circuit: The quantum circuit to execute
        shots: Number of measurement shots
        
    Returns:
        dict: Measurement results
    """
    device = LocalSimulator()
    task = device.run(circuit, shots=shots)
    return task.result().measurement_counts

# Run on AWS device
def run_aws_device(circuit: Circuit, device_arn: str, shots: int = 1000) -> dict:
    """
    Run circuit on AWS quantum device.
    
    Args:
        circuit: The quantum circuit to execute
        device_arn: AWS device ARN
        shots: Number of measurement shots
        
    Returns:
        dict: Measurement results from AWS task
    """
    device = AwsDevice(device_arn)
    task = device.run(circuit, shots=shots)
    return task.result().measurement_counts

from braket.circuits import Circuit
from braket.circuits.gates import H, CNot, Rx, Ry, Rz, U
from braket.circuits.observables import Z, X
from braket.circuits.result_types import Expectation
import numpy as np

# Parameterized quantum circuit
def variational_circuit(params: list[float]) -> Circuit:
    """
    Creates a parameterized variational quantum circuit.
    
    Args:
        params: List of rotation parameters
        
    Returns:
        Circuit: Variational quantum circuit
    """
    circuit = Circuit()
    
    # Layer of Hadamard gates
    for qubit in range(2):
        circuit.h(qubit)
    
    # Parameterized rotation layers
    for i, param in enumerate(params):
        qubit = i % 2
        circuit.ry(qubit, param)
        
    # Entangling layer
    circuit.cnot(0, 1)
    
    # Observable measurement
    circuit.expectation(observable=Z(0) @ Z(1))
    
    return circuit

from braket.aws import AwsDevice, AwsDeviceType, AwsSession
from braket.circuits import Circuit

# Device discovery and selection
def get_available_devices() -> dict[str, AwsDevice]:
    """
    Get all available AWS Braket devices.
    
    Returns:
        dict: Mapping of device names to AwsDevice instances
    """
    # Get QPU devices
    qpu_devices = AwsDevice.get_devices(device_types=[AwsDeviceType.QPU])
    
    # Get simulator devices  
    sim_devices = AwsDevice.get_devices(device_types=[AwsDeviceType.SIMULATOR])
    
    devices = {}
    for device in qpu_devices + sim_devices:
        devices[device.name] = device
        
    return devices

# Session management
def create_aws_session(region: str = "us-east-1") -> AwsSession:
    """
    Create authenticated AWS session for Braket.
    
    Args:
        region: AWS region for quantum computing resources
        
    Returns:
        AwsSession: Authenticated session
    """
    return AwsSession(boto_session=None, braket_user_agents=None)

from braket.jobs import hybrid_job, save_job_result, get_job_device_arn
from braket.aws import AwsDevice
from braket.circuits import Circuit

@hybrid_job(device="ml.m5.large")
def quantum_optimization_job():
    """
    Hybrid job for quantum optimization algorithm.
    
    This job runs a variational quantum algorithm combining
    quantum circuit execution with classical optimization.
    """
    # Get the quantum device for this job
    device_arn = get_job_device_arn()
    device = AwsDevice(device_arn)
    
    # Define cost function using quantum circuits
    def cost_function(params: list[float]) -> float:
        circuit = variational_circuit(params)
        task = device.run(circuit, shots=1000)
        result = task.result()
        return result.values[0]  # Expectation value
    
    # Classical optimization loop
    import scipy.optimize
    initial_params = [0.1, 0.2]
    result = scipy.optimize.minimize(cost_function, initial_params)
    
    # Save results
    save_job_result({
        "optimal_params": result.x.tolist(),
        "optimal_value": float(result.fun)
    })

from braket.tracking import Tracker
from braket.aws import AwsDevice
from braket.circuits import Circuit

def tracked_quantum_execution(circuit: Circuit, device_arn: str) -> dict:
    """
    Execute quantum circuit with cost tracking.
    
    Args:
        circuit: Quantum circuit to execute
        device_arn: AWS device ARN
        
    Returns:
        dict: Results including cost information
    """
    with Tracker() as tracker:
        # Execute quantum task
        device = AwsDevice(device_arn)
        task = device.run(circuit, shots=1000)
        result = task.result()
        
        # Get cost information
        cost_info = {
            "quantum_tasks_cost": tracker.quantum_tasks_cost(),
            "simulator_tasks_cost": tracker.simulator_tasks_cost(),
            "total_cost": tracker.quantum_tasks_cost() + tracker.simulator_tasks_cost()
        }
        
    return {
        "measurement_counts": result.measurement_counts,
        "cost_tracking": cost_info
    }