fermioniq 1.0.0

Python client library for the OpenAI API

Fermioniq client for pure state emulation

Installation

Dev

Run locally: pip install -e .[dev]

Setup:

Sending jobs to the emulator requires 'access_token_id' and 'access_token_secret'. Set these as environment variables:

- export FERMIONIQ_ACCESS_TOKEN_ID=""
- export FERMIONIQ_ACCESS_TOKEN_SECRET=""

Or alternatively provide them as input arguments when initializing a ClientConfig.

Relevant Examples

    - step_by_step_example.py         -- general overview
    - run_with_json.py                -- using cirq circuits stored in json format
    - run_with_local_noisemodel.py    -- mixed state emulation with a custom noise model

---

The emulator can be used as follows:

1: Initialize the Client:

    client = fermioniq.Client()

  Be sure to provide `access_token_id` and `access_token_secret` if they are not set as environment variables.
  Additionally you can set `verbosity` to 0, 1 or 2

2: Initialize a configuration for the emulator, as a python dict or stored as json or yaml. A default configuration with context for each parameter can be found in examples/example_settings/.

    i.e.
    config = {}

    or
    config = {"mode" : "dmrg", "dmrg" : {"D" : 500}}
    Here ``qubits` can be set as a sequence of qubits (qiskit.circuit.Qubit or cirq.Qid), determining the order of output bitstrings.

3. Make a fermioniq.EmulatorJob:

    emulator_job = fermioniq.EmulatorJob(
        circuit = circuit,
        config = config,
    )

    The circuit to emulate should be a qiskit.QuantumCircuit or cirq.Circuit.
    For mixed-state emulation, a `noise_model` must be given as dict or yaml. An example can be found in examples/example_settings/

4. Schedule:

    output = client.schedule_and_wait(emulator_job)

5. Pretty print the output:

    import rich
    rich.print(output)