using QuantumSavory
using QuantumSavory.ProtocolZoo: AbstractProtocol
using ConcurrentSim
using ResumableFunctions
using Gabs
using Revise

"""
    RESOURCE_SQUEEZE

Shared squeezing strength used for the three-mode entangled resource.

Larger values make the teleportation closer to the ideal protocol, while smaller
values leave more finite-squeezing noise in Bob's output mode.
"""
const RESOURCE_SQUEEZE = 5.5

###
# Use Gabs.jl as a numerical backend for `Qumode`s and build the three-node network.
###

"""
    simulation_setup(; repr = GabsRepr(QuadBlockBasis))

Create the small register network used in the assisted continuous-variable
teleportation tutorial.

Alice owns two modes: her share of the entangled resource and the unknown input
mode to be teleported. Bob and Charlie each own one resource mode.
"""
function simulation_setup(; repr = GabsRepr(QuadBlockBasis))
    # initialize registers
    regA = Register([Qumode(), Qumode()], [repr, repr]) # mode a and input mode
    regB = Register([Qumode()], [repr]) # mode b
    regC = Register([Qumode()], [repr]) # mode c
    # create a network (a chain) of registers
    network = RegisterNet([regA, regB, regC])
    sim = get_time_tracker(network)
    return sim, network
end

"""
    prepare_states!(net, input_state; squeezes)

Load the unknown input state into Alice's register and prepare the three-mode
Gaussian resource shared by Alice, Bob, and Charlie.

The resource is generated from three single-mode squeezed states followed by the
beam-splitter network used in the assisted teleportation setup.
"""
function prepare_states!(net, input_state; squeezes)
    regA, regB, regC = net[1], net[2], net[3]
    # Alice's second slot holds the unknown input that will be teleported.
    initialize!(regA, 2, input_state)

    # Prepare the shared three-mode entangled resource across Alice, Bob, and Charlie.
    # In a more complete simulation, there will be some other networked protocols that establish this state.
    # Here we just create it manually, disregarding the "local operations" constraint that one
    # would usually expect from a networking simulation.
    initialize!(regA, 1, SqueezedState(-squeezes[1]))
    initialize!(regB, 1, SqueezedState(squeezes[2]))
    initialize!(regC, 1, SqueezedState(squeezes[3]))
    apply!([regA[1], regB[1]], BeamSplitterOp(2/3))
    apply!(regB[1], PhaseShiftOp(1.0 * pi))
    apply!([regB[1], regC[1]], BeamSplitterOp(1/2))
    apply!(regC[1], PhaseShiftOp(1.0 * pi))

    # Alice mixes her resource mode with the unknown input to create the Bell-like measurement.
    apply!(regA[1:2], BeamSplitterOp(1/2))
end

"""
    AssistedTeleport(sim, net, nodeA, nodeB, nodeC)

Protocol object representing the assisted continuous-variable teleportation run.

Alice (`nodeA`) performs the Bell-like homodyne measurement, Charlie (`nodeC`)
provides the assisting quadrature, and Bob (`nodeB`) applies the final
displacement correction.

You could have just as well used another `@resumable` function here,
but the "Protocol" style of a "callable struct" is a convenient way to create
the equivalent of a `@resumable` function with neatly packaged configuration options.

For a more realistic simulation you would probably want to split the protocol
into a protocol instance per node in order to make locality constraints more explicit
(and more easily enforced).
Such separate protocols would then message each other through their classical message buffers.
"""
struct AssistedTeleport <: AbstractProtocol
    sim::Simulation
    net::RegisterNet
    nodeA::Int # Alice (sender)
    nodeB::Int # Bob (receiver)
    nodeC::Int # Charlie (assister)
end

"""
    homodyne_alice!(net, nodeA, nodeB)

Perform Alice's Bell-like homodyne measurement and send the classical outcomes
to Bob.

With the beam-splitter convention used here, the measured `x_-` contribution is
stored with an explicit minus sign before transmission.
"""
function homodyne_alice!(net, nodeA, nodeB)
    regA = net[nodeA]
    # project Alice's register onto the eigenstates |x₋, p₊⟩
    quads₋ = project_traceout!(regA[2], HomodyneMeasurement([0.0]))
    quads₊ = project_traceout!(regA[1], HomodyneMeasurement([pi/2]))
    # put quadrature measurements in channel
    chAB = channel(net, nodeA=>nodeB)
    put!(chAB, Tag(:quadsA, -quads₋[1], quads₊[2]))
end

"""
    homodyne_charlie!(net, nodeB, nodeC)

Measure Charlie's mode in the `p` quadrature and send the result to Bob.
"""
function homodyne_charlie!(net, nodeB, nodeC)
    regC = net[nodeC]
    # project Charlie's register onto the eigenstate |p⟩
    quads = project_traceout!(regC[1], HomodyneMeasurement([pi/2]))
    # put quadrature measurement in channel
    chBC = channel(net, nodeC=>nodeB)
    put!(chBC, Tag(:quadsC, quads[2]))
end

"""
    (prot::AssistedTeleport)()

Run one assisted teleportation round.

After Alice and Charlie send their measurement outcomes, Bob applies the
displacement that reconstructs the input state on his output mode.

Here we are turning all instances of the type AssistedTeleport into callables,
so that they can be used as functions with neatly packaged configuration options inside of them.
"""
@resumable function (prot::AssistedTeleport)()
    (; sim, net, nodeA, nodeB, nodeC) = prot
    homodyne_alice!(net, nodeA, nodeB)
    homodyne_charlie!(net, nodeB, nodeC)

    # Bob waits for the classical messages and converts them into his correction.
    regB = net[nodeB]
    mb = messagebuffer(regB)
    quadsAtag = @yield query_wait(mb, :quadsA, ❓, ❓)
    quadsA = [quadsAtag.tag[2], quadsAtag.tag[3]]
    quadsCtag = @yield query_wait(mb, :quadsC, ❓)
    quadC = quadsCtag.tag[2]
    D = DisplaceOp((-sqrt(2) * quadsA[1] + im * (sqrt(2) * quadsA[2] + quadC)) / 2)
    apply!(regB[1], D)
end

###
# Run the actual simulation!
# A single teleportation instance for a random coherent input state.
###

sim, net = simulation_setup()
initial_state = CoherentState(rand(ComplexF64))
prepare_states!(
    net,
    initial_state;
    squeezes = fill(RESOURCE_SQUEEZE, 3)
)
teleport = AssistedTeleport(sim, net, 1, 2, 3)
@process teleport()

run(sim)

###
# Compare the input state with Bob's final output state.
# For sufficiently large `RESOURCE_SQUEEZE`, these should be very similar.
###

initial_state = express(initial_state, GabsRepr(QuadBlockBasis))
teleported_state = QuantumSavory.stateof(net[2,1]).state[]

@assert ≈(initial_state, teleported_state, atol=1e-2)
