SAX

SAX#

S + Autograd + XLA

SAX LOGO

Autograd and XLA for S-parameters - a scatter parameter circuit simulator and optimizer for the frequency domain based on JAX.

The simulator was developed for simulating Photonic Integrated Circuits but in fact is able to perform any S-parameter based circuit simulation. The goal of SAX is to be a thin wrapper around JAX with some basic tools for S-parameter based circuit simulation and optimization. Therefore, SAX does not define any special datastructures and tries to stay as close as possible to the functional nature of JAX. This makes it very easy to get started with SAX as you only need functions and standard python dictionaries. Let’s dive in…

Quick Start#

Full Quick Start page - Documentation.

Let’s first import the SAX library, along with JAX and the JAX-version of numpy:

import sax
import jax
import jax.numpy as jnp

Define a model function for your component. A SAX model is just a function that returns an ‘S-dictionary’. For example a directional coupler:

def coupler(coupling=0.5):
    kappa = coupling**0.5
    tau = (1-coupling)**0.5
    sdict = sax.reciprocal({
        ("in0", "out0"): tau,
        ("in0", "out1"): 1j*kappa,
        ("in1", "out0"): 1j*kappa,
        ("in1", "out1"): tau,
    })
    return sdict

coupler(coupling=0.3)

{('in0', 'out0'): 0.8366600265340756,
 ('in0', 'out1'): 0.5477225575051661j,
 ('in1', 'out0'): 0.5477225575051661j,
 ('in1', 'out1'): 0.8366600265340756,
 ('out0', 'in0'): 0.8366600265340756,
 ('out1', 'in0'): 0.5477225575051661j,
 ('out0', 'in1'): 0.5477225575051661j,
 ('out1', 'in1'): 0.8366600265340756}

Or a waveguide:

def waveguide(wl=1.55, wl0=1.55, neff=2.34, ng=3.4, length=10.0, loss=0.0):
    dwl = wl - wl0
    dneff_dwl = (ng - neff) / wl0
    neff = neff - dwl * dneff_dwl
    phase = 2 * jnp.pi * neff * length / wl
    amplitude = jnp.asarray(10 ** (-loss * length / 20), dtype=complex)
    transmission =  amplitude * jnp.exp(1j * phase)
    sdict = sax.reciprocal({("in0", "out0"): transmission})
    return sdict

waveguide(length=100.0)

{('in0', 'out0'): 0.97953-0.2013j, ('out0', 'in0'): 0.97953-0.2013j}

These component models can then be combined into a circuit:

mzi, _ = sax.circuit(
    netlist={
        "instances": {
            "lft": coupler,
            "top": waveguide,
            "rgt": coupler,
        },
        "connections": {
            "lft,out0": "rgt,in0",
            "lft,out1": "top,in0",
            "top,out0": "rgt,in1",
        },
        "ports": {
            "in0": "lft,in0",
            "in1": "lft,in1",
            "out0": "rgt,out0",
            "out1": "rgt,out1",
        },
    }
)

type(mzi)

function

As you can see, the mzi we just created is just another component model function! To simulate it, call the mzi function with the (possibly nested) settings of its subcomponents. Global settings can be added to the ‘root’ of the circuit call and will be distributed over all subcomponents which have a parameter with the same name (e.g. ‘wl’):

wl = jnp.linspace(1.53, 1.57, 1000)
result = mzi(wl=wl, lft={'coupling': 0.3}, top={'length': 200.0}, rgt={'coupling': 0.8})

plt.plot(1e3*wl, jnp.abs(result['in0', 'out0'])**2, label="in0->out0")
plt.plot(1e3*wl, jnp.abs(result['in0', 'out1'])**2, label="in0->out1", ls="--")
plt.xlabel("λ [nm]")
plt.ylabel("T")
plt.grid(True)
plt.figlegend(ncol=2, loc="upper center")
plt.show()

output

Those are the basics. For more info, check out the full SAX Quick Start page or the rest of the Documentation.

Installation#

You can install SAX with pip:

pip install sax

If you want to be able to run all the example notebooks, you’ll need python>=3.10 and you should install the development version of SAX:

pip install 'sax[dev]'

License#

Copyright © 2023, Floris Laporte, Apache-2.0 License

Home

Examples

Library Internals

Changelog#

0.14.0#

Added#

  • Backend information to CircuitInfo.

Updated#

  • klujax package.

  • Documentation.

0.13.5#

Added#

  • settings field to netlist.

Updated#

  • GitHub Actions publish.yml workflow.

  • Dependencies.

0.13.4#

Added#

  • forward-only backend (#39).

    • Example to demonstrate usage of forward-only backend.

    • Bug fixes related to forward-only backend.

Fixed#

  • CI configuration.

  • Pinned minimum version of numpy in dependencies.

0.13.3#

Added#

  • Validation for the number of ports.

Fixed#

  • Issues in variability notebook.

  • Layout-aware notebook.

0.13.2#

Added#

  • extra_netlist_cleanup argument.

Updated#

  • Docker image.

  • Makefile.

0.13.1#

Updated#

  • Makefile.

  • Dockerfile.

0.13.0#

Added#

  • Documentation and examples.

  • Coercion of nets into connections.

  • Handle for callable instances in connections.

  • Tests for cleanup and refactoring.

Deprecated#

  • info subdirectory in instance dictionary.

  • sax.nn module.

Updated#

  • Proper transition to pydantic v2.

  • Added docstrings across functions (#34).

0.12.2#

Updated#

  • Pinned minimum version of flax.

0.12.1#

Fixed#

  • Minor bug fixes.

0.12.0#

Added#

  • Config setting to override component in info['model'].

0.11.4#

Updated#

  • Bumped klujax.

0.11.3#

Improved#

  • Flatten netlist functionality.

0.11.2#

Fixed#

  • Ignored ports not following the correct format in flatten_netlist.

0.11.1#

Updated#

  • Notebooks.

  • Bug fixes from 0.11 release.

0.11.0#

Added#

  • flatten_netlist function.

Improved#

  • Error messages.

  • Analysis of dummy models to prevent dense representation during evaluation.

0.10.4#

Added#

  • Handling of complex function arguments (#28).

  • Support for omitting placements in recursive netlist (#27).

Fixed#

  • Issues related to '$' sign in netlist component values.

0.10.3#

Added#

  • Changelog (#23).

Fixed#

  • Changelog formatting.

  • Updated MANIFEST.in.

0.10.2#

Fixed#

  • Evaluation of ports rather than tracing in models.

0.10.1#

Added#

  • bump2version as a development dependency.

  • Test folder exposure as artifact.

Fixed#

  • CI workflows, including Sphinx and Binderhub configurations.

0.10.0#

Added#

  • Type annotations and expanded documentation.

  • Jupyter-book based documentation.

Updated#

  • Notebooks.

  • Improved multimode operations.

0.9.2#

Added#

  • Helper functions for component-to-instance mapping.

0.9.0#

Fixed#

  • Compatibility with both pydantic v1 and v2.

0.8.8#

Fixed#

  • Validation in get_required_circuit_models function.

Added#

  • get_required_circuit_models function.

0.8.6#

Updated#

  • GitHub workflows for pypi publishing.

0.8.5#

Fixed#

  • Various minor cleanups in notebooks.

0.8.4#

Fixed#

  • Consolidation in multimode to singlemode transition.

0.8.3#

Added#

  • Support for circuit dependency DAGs.

0.8.2#

Fixed#

  • Handling of None settings in instances.

0.8.1#

Updated#

  • Notebooks and examples with new API.

Added#

  • Support for dict-based circuits.

0.8.0#

Added#

  • Full type support for SAX.

  • New documentation structure.

0.7.3#

Updated#

  • Layout-aware notebook title.

  • Project logo.

0.7.2#

Fixed#

  • circuit_from_gdsfactory function.

0.7.1#

Updated#

  • Minimal version of SAX availability without JAX.

0.6.0 - 0.7.0#

  • Initial commits with foundational code, refactoring, and early versioning.

API Docs

Other#

Contents