Using the SDK¶
In Running your first app we have seen how to execute applications on a simulated quantum network. We will now learn how to write an application ourselves. Below are a few sample applications which we will go through, ranging from a very simple application on a single node to a more complicated examples further on.
Writing a first application¶
We will now create an very simple hello-world-application which consists of a single node that creates a qubit, performs a Hadamard gate and measures the qubit.
Let’s first create a new folder my-app:
mkdir my-app
cd my-app
In this folder we will now create our application
touch app_alice.py
Open the file app_alice.py in your favorite editor/IDE and add the following code
from netqasm.sdk.external import NetQASMConnection
def main(app_config=None):
# Setup a connection to QNodeOS
with NetQASMConnection("alice", log_config=app_config.log_config) as alice:
print("Started NetQASM connection to QNodeOS")
Note
The reason NetQASMConnection is imported from netqasm.sdk.external is that the class used
will depend on which simulator is specified. The information about which simulator is used is
stored in the environement varible NETQASM_SIMULATOR, and makes netqasm.sdk.external
load different classes depending on its value. What this allows us to do is to simulate an
application on different simulators, without changing anything, even imports.
What this code does is to setup a connection to the underlying (simulated) quantum node controller called QNodeOS, which can handle the NetQASM-instructions.
You can already run this application by doing netqasm simulate, and if everything was correct you will see the message being printed.
In the context of the connection, we can now create a qubit
from netqasm.sdk.external import NetQASMConnection
from netqasm.sdk import Qubit
def main(app_config=None):
# Setup a connection to QNodeOS
with NetQASMConnection("alice", log_config=app_config.log_config) as alice:
# Create a qubit
q = Qubit(alice)
Running the application now seems perhaps to not do anything.
To make sure that a qubit is actually created we can set the log-level to INFO
netqasm simulate --log-level=DEBUG
You will then see that a subroutine is flushed and handled by the SubroutineHandler, which is a simplified version of a QNodeOS used in simulation.
Let’s now perform a gate on the qubit and also measure it.
from netqasm.sdk.external import NetQASMConnection
from netqasm.sdk import Qubit
def main(app_config=None):
# Setup a connection to QNodeOS
with NetQASMConnection("alice", log_config=app_config.log_config) as alice:
# Create a qubit
q = Qubit(alice)
# Perform a Hadamard gate
q.H()
# Measure the qubit
m = q.measure()
# Print the outcome
print(f"Outcome is: {m}")
Let’s run this now (without setting the --log-level-flag) and see what the outcome is.
Hmm, it doesn’t print the outcome but rather says:
Outcome is: Future to be stored in array with address 0 at index 0.
To access the value, the subroutine must first be executed which can be done by flushing.
The reason this happens is because the operations specified are in fact not directly executed on the (simulated) quantum hardware.
Rather, they are buffered into a NetQASM-subroutine, until the subroutine is flushed and sent to QNodeOS.
Let’s fix our code by adding an explicit flush before the print.
from netqasm.sdk.external import NetQASMConnection
from netqasm.sdk import Qubit
def main(app_config=None):
# Setup a connection to QNodeOS
with NetQASMConnection("alice", log_config=app_config.log_config) as alice:
# Create a qubit
q = Qubit(alice)
# Perform a Hadamard gate
q.H()
# Measure the qubit
m = q.measure()
# Flush the current subroutine
alice.flush()
# Print the outcome
print(f"Outcome is: {m}")
Running the application again will now either print Outcome is: 0 or Outcome is: 1.
Run it a few times to see the different outcomes.
Note
A connection is automatically flushed whenever it goes out of scope. So in the above example we could have just as well done:
from netqasm.sdk.external import NetQASMConnection
from netqasm.sdk import Qubit
def main(app_config=None):
# Setup a connection to QNodeOS
with NetQASMConnection("alice", log_config=app_config.log_config) as alice:
# Create a qubit
q = Qubit(alice)
# Perform a Hadamard gate
q.H()
# Measure the qubit
m = q.measure()
# Print the outcome
print(f"Outcome is: {m}")
Tip
It is important to understand how the execution happens when running the application.
Try adding some print statements in the application, turn on INFO-logging and see if you
can understand why the print-statements and logging-statements are in the order you see.
Creating entanglement between nodes¶
Let’s now extend our application by adding another node bob and have the two nodes create entanglement with each other.
To do this we will need to setup an EPR socket.
We do this by instanciating an object of EPRSocket and give this to the NetQASMConnection.
Consider the following code-example for the node with role alice:
from netqasm.sdk.external import NetQASMConnection
from netqasm.sdk import EPRSocket
def main(app_config=None):
# Specify an EPR socket to bob
epr_socket = EPRSocket("bob")
alice = NetQASMConnection(
"alice",
log_config=app_config.log_config,
epr_sockets=[epr_socket],
)
with alice:
# Create an entangled pair using the EPR socket to bob
q_ent = epr_socket.create()[0]
# Measure the qubit
m = q_ent.measure()
# Print the outcome
print(f"alice's outcome is: {m}")
The code for bob will be very similar, with the only difference being that
bob receives an entangled pair by calling recv on the EPR socket
object. Create a new file app_bob.py in the same directory as
app_alice.py:
from netqasm.sdk.external import NetQASMConnection
from netqasm.sdk import EPRSocket
def main(app_config=None):
# Specify an EPR socket to bob
epr_socket = EPRSocket("alice")
bob = NetQASMConnection(
"bob",
log_config=app_config.log_config,
epr_sockets=[epr_socket],
)
with bob:
# Receive an entangled pair using the EPR socket to alice
q_ent = epr_socket.recv()[0]
# Measure the qubit
m = q_ent.measure()
# Print the outcome
print(f"bob's outcome is: {m}")
Running this application files using netqasm simulate prints the outcomes of the two nodes.
Since by default no noise is used, their outcomes will always be equal.
Tip
Check out the documentation of EPRSocket to see what arguments create() and recv() can take.
For example you will see that a number of pairs can be specified, which is why these methods return a list of Qubit-objects.
Also check out the methods create_context() and recv_context(), which allows to specify what to do whenever a pair is generated, using a context.
Adding classical communication¶
Applications generally also need to communicate classicaly between nodes, to for example communicate measurement outcomes.
We will extend our example by having alice communicate her outcome to bob.
bob will use this outcome to possible apply a correction in order to make his qubit be in the state \(|0\rangle\) in both cases.
Consider the following code-snippets for alice and bob:
from netqasm.sdk.external import NetQASMConnection, Socket
from netqasm.sdk import EPRSocket
def main(app_config=None):
# Setup a classical socket to bob
socket = Socket("alice", "bob", log_config=app_config.log_config)
# Specify an EPR socket to bob
epr_socket = EPRSocket("bob")
alice = NetQASMConnection(
"alice",
log_config=app_config.log_config,
epr_sockets=[epr_socket],
)
with alice:
# Create an entangled pair using the EPR socket to bob
q_ent = epr_socket.create()[0]
# Measure the qubit
m = q_ent.measure()
# Print the outcome
print(f"alice's outcome is: {m}")
# Send the outcome to bob
socket.send(str(m))
from netqasm.sdk.external import NetQASMConnection, Socket
from netqasm.sdk import EPRSocket
def main(app_config=None):
# Setup a classical socket to alice
socket = Socket("bob", "alice", log_config=app_config.log_config)
# Specify an EPR socket to bob
epr_socket = EPRSocket("alice")
bob = NetQASMConnection(
"bob",
log_config=app_config.log_config,
epr_sockets=[epr_socket],
)
with bob:
# Receive an entangled pair using the EPR socket to alice
q_ent = epr_socket.recv()[0]
# Receive the outcome from alice
m = int(socket.recv())
# Apply correction depending on outcome
if m == 1:
q_ent.X()
# Measure the qubit
m = q_ent.measure()
# Print the outcome
print(f"bob's outcome is: {m}")
Running the above example we can see that the outcome of bob is always 0, independently of the outcome of alice.
A more complex example¶
We will now look at a more complicated example, where we will use quantum error correction to protect an entangled qubit from errors.
In this example we will use the most simple quantum error-correction code, namely the repition code on three qubits.
Before implementing the actual quantum error-correction code, let’s define how we want the main functions to look like.
On alice’s side we will
Create encode the qubit
Randomly apply a bit-flip
Correct any error
Decode the qubit again.
Measure the qubit and print the outcome
def main(app_config=None):
# Specify an EPR socket to bob
epr_socket = EPRSocket("bob")
alice = NetQASMConnection(
"alice",
log_config=app_config.log_config,
epr_sockets=[epr_socket],
)
with alice:
# Create an entangled pair using the EPR socket to bob
q_ent = epr_socket.create()[0]
# Encode into repitition code
logical_qubit = encode(q_ent)
# Randomly introduce a bit-flip
if random.randint(0, 1):
i = random.choice(range(3))
print(f"applying bit flip on qubit {i}")
# q = random.choice(logical_qubit)
q = logical_qubit[i]
q.X()
# Correct a possible bit-flip
correct(logical_qubit)
# Decode back
decode(logical_qubit)
# Measure the qubit
m = logical_qubit[0].measure()
# Print the outcome
print(f"alice's outcome is: {m}")
bob on the other hand will simple measure his entangled qubit and print the outcome.
def main(app_config=None):
# Specify an EPR socket to bob
epr_socket = EPRSocket("alice")
bob = NetQASMConnection(
"bob",
log_config=app_config.log_config,
epr_sockets=[epr_socket],
)
with bob:
# Receive an entangled pair using the EPR socket to alice
q_ent = epr_socket.recv()[0]
# Measure the qubit
m = q_ent.measure()
# Print the outcome
print(f"bob's outcome is: {m}")
Let’s now implement the functions: encode, correct and decode:
import random
from netqasm.sdk.external import NetQASMConnection, Socket
from netqasm.sdk import EPRSocket, Qubit, parity_meas, t_inverse, toffoli_gate
def encode(qubit):
"""Encodes a qubit into a repitition code by intializing two more
Parameters
----------
qubit : :class:`~.Qubit`
Qubit to be encoded
Returns
-------
list : list of encoded qubits
"""
conn = qubit.connection
logical_qubit = [qubit, Qubit(conn), Qubit(conn)]
for q in logical_qubit[1:]:
logical_qubit[0].cnot(q)
return logical_qubit
def correct(logical_qubit):
"""Tries to correct a bit flip
Parameters
----------
logical_qubit : list of :class:`~.Qubit`
"""
# Check code syndromes
s1 = parity_meas(logical_qubit, 'ZZI')
s2 = parity_meas(logical_qubit, 'IZZ')
print(f"syndrome is ({s1}, {s2})")
if (s1, s2) == (0, 0): # No error
pass
elif (s1, s2) == (0, 1): # Error on third
logical_qubit[2].X()
elif (s1, s2) == (1, 0): # Error on first qubit
logical_qubit[0].X()
else: # Error on second qubit
logical_qubit[1].X()
def decode(logical_qubit):
"""Decodes the repitition code on three qubits
After the first qubit in the list will be the decode qubit.
Parameters
----------
logical_qubit : list of :class:`~.Qubit
"""
for q in logical_qubit[1:]:
logical_qubit[0].cnot(q)
# Toffoli with first qubit as target
toffoli_gate(*reversed(logical_qubit))
Let’s now run our application and see what happens. Hmm, we get an error.
Tip
Try to figure out what goes wrong before reading the solution below.
Our mistake is that we are trying to use the outcomes s1 and s2, in the correct-function, before the subroutine is flushed.
One way to solve this is to add a flush-statement as follows:
def correct(logical_qubit):
"""Tries to correct a bit flip
Parameters
----------
logical_qubit : list of :class:`~.Qubit`
"""
# Check code syndromes
s1 = parity_meas(logical_qubit, 'ZZI')
s2 = parity_meas(logical_qubit, 'IZZ')
conn = logical_qubit[0].connection
conn.flush()
print(f"syndrome is ({s1}, {s2})")
if (s1, s2) == (0, 0): # No error
pass
elif (s1, s2) == (0, 1): # Error on third
logical_qubit[2].X()
elif (s1, s2) == (1, 0): # Error on first qubit
logical_qubit[0].X()
else: # Error on second qubit
logical_qubit[1].X()
The application now works :)
You can see that independently on which qubit the bit-flip might occur, alice and bob always receive the same outcome, meaning that our error-correction code is working.
However, there is something we can still improve.
Namely, we can avoid the call to flush and instead make use of classical logic in NetQASM and let this be handled by QNodeOS.
The reason we would want to do this is that whenever a flush happens, extra communication between the application layer and QNodeOS is needed, see our paper for more details.
We can see this happen if we increase the logging.
Run the above example by netqasm simulate --log-level=INFO, which will produce a lot of logging.
Importantly, you can see that alice submits two subroutines to QNodeOS and not only one.
In the next part we look at how to use simple built-in classical logic in NetQASM to minimize the communication needed between the application layer and QNodeOS.
Simple classical logic¶
Let’s now improve our correct-function above by avoiding the call to flush and use the simple logic built-in to NetQASM.
We can rewrite the function to instead do:
def correct2(logical_qubit):
"""Tries to correct a bit flip
Parameters
----------
logical_qubit : list of :class:`~.Qubit`
"""
# Check code syndromes
s1 = parity_meas(logical_qubit, 'ZZI')
s2 = parity_meas(logical_qubit, 'IZZ')
with s1.if_eq(0):
with s2.if_eq(1): # outcomes (0, 1) error on third qubit
logical_qubit[2].X()
with s1.if_eq(1):
with s2.if_eq(0): # outcomes (1, 0) error on first qubit
logical_qubit[0].X()
with s2.if_eq(1): # outcomes (1, 1) error on second qubit
logical_qubit[1].X()
If you now run the application with the updated function and with INFO logging, you will see that alice only uses one subroutine.
What happens under the hood, is that these if-statements are compiled into branching instructions in the NetQASM-language.
Note
The current syntax, e.g. with s1.if_eq(0): might change.
Ideally, we would be able to write plain Python-if-statements in the future.
Tip
Check out the documentation for Future.
This is what’s returned when measuring a qubit and on which one can apply simple logical statements such as if_eq().
You can also for example use the methods if_ez() and if_nz().
As a next step, you can read more about how to configure the simulation of the application, what network to use, noise etc, in the section Application file structure. In SDK objects the main functions and classes to be used are documented. For the full API of the package, refer to the API Reference. Enjoy programming applications for a quantum internet!