A picture (or a gif !) is worth a thousand words. Wouldn't it be nice if people could just see in practice how Tangelo works on simple tasks without having to dig into documentation, tutorials, etc ? They'd just "get it" and be able to decide if that's relevant to them or not.
Well, a gif in our README would be pretty neat. To win this:
upload a gif in the docs folder on the repo
alongside a simple text or rst file describing how you did it (don't worry about the README file, leave it alone). Mention the tools / website / techniques and the text used.
Here is what we want to see in that gif:
a sequence of code snippets (provided below) gradually typed on screen, accompanied with the output
try to keep the size of the text consistent across snippets.
Snippets and their results:
Snippet 1
# Run circuits on your favorite simulators
from tangelo.linq import Gate, Circuit, get_backend
c = Circuit([Gate('H', 0), Gate('X', 1)])
sim = get_backend("qiskit") # or "qulacs", "cirq" ...
bitstring_frequencies, statevector = sim.simulate(c, return_statevector=True)
print(f'{bitstring_frequencies=} \n{statevector=}')
Snippet 2
# Use all the projects in the quantum ecosystem !
from tangelo.linq import translate_circuit
c_qiskit = translate_circuit(c, target="qiskit") # to or from "qiskit", "pennylane", "cirq", ...
c_qiskit.draw(output='mpl', style={'backgroundcolor': '#EEEEEE'}) # it's a qiskit object !
(this is not the actual output, just run the above code with qiskit and pylatexenc in your environment)
Snippet 3
# Compute ground state of a molecule with VQE
# Check out the computational resources needed
from tangelo import SecondQuantizedMolecule
from tangelo.algorithms import VQESolver
xyz_H2 = [("H", (0., 0., 0.)), ("H", (0., 0., 0.7414))]
mol = SecondQuantizedMolecule(xyz_H2, q=0, spin=0, basis="sto-3g")
vqe_options = {"molecule": mol} # Plenty options for qubit mappings etc
vqe_solver = VQESolver(vqe_options)
vqe_solver.build()
opt_energy = vqe_solver.simulate()
print(opt_energy)
print(vqe_solver.get_resources())
Snippet 4
from tangelo.linq.qpu_connection import IBMConnection
conn = IBMConnection(ibm_quantum_token='your_ibm_token')
job_id = conn.job_submit('sampler', 'ibmq_qasm_simulator', n_shots=100, circuit)
job_res = conn.job_results(job_id) # Your job on IBM Quantum eventually completes
A picture (or a gif !) is worth a thousand words. Wouldn't it be nice if people could just see in practice how Tangelo works on simple tasks without having to dig into documentation, tutorials, etc ? They'd just "get it" and be able to decide if that's relevant to them or not.
Well, a gif in our README would be pretty neat. To win this:
docsfolder on the repoHere is what we want to see in that gif:
Snippets and their results:
Snippet 1
Snippet 2
(this is not the actual output, just run the above code with qiskit and pylatexenc in your environment)
Snippet 3
Snippet 4
(no output needed)