tqec architecture#

This document is mainly targeted at a developer wanting to contribute to the tqec library. It provides a high-level overview of the different pieces that compose the tqec library and how they interact with each other.

Warning

This is a rapidly evolving project — codebase might change. If you encounter any inconsistencies, please open an issue.

This is done by presenting each of the sub-modules and their main classes / methods in the order in which they are used internally to go from a topological computation to an instance of stim.Circuit that can be executed on compatible hardware.

The diagram below provides a high-level overview of the dependencies between tqec submodules. It is not 100% accurate, as for example the tqec.circuit submodule defines a few core data-structures that are used in tqec.plaquette, but this is the order in which the sub-modules will be covered here.

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graph
    A[tqec.interop] --> B[tqec.computation]
    B --> E[tqec.compile]
    C[tqec.templates] --> E
    D[tqec.plaquette] --> E
    E --> F[tqec.circuit]
    F --> G[tqec.utils.noise_models]
    G --> H[tqec.simulation]

A user starts with a computation and an observable. The input computation can be provided as a BlockGraph structure while an observable is represented as a correlation surface. The end goal of tqec is to generate a stim.Circuit such that the input is transformed into a topologically quantum error corrected quantum computation protected by a surface code.

interop#

Allows a user to provide a .dae file or a pyzx graph as an input to tqec.

  • A BlockGraph can be constructed through a Collada .dae file through read_block_graph_from_dae_file() and vice versa through write_block_graph_to_dae_file().

  • A ZX graph can be mapped to a BlockGraph through block_synthesis().

Standard color representations as described in Terminology are predefined in TQECColor.

Some conventional implementations of computations in .dae format are available in the Computation Gallery.

computation#

Defines data structures for the high-level BlockGraph representations of a fault-tolerant computation protected by the surface code.

The 3D structures discussed in detail in Terminology are defined in this module.

  • A CorrelationSurface represents a set of parity measurements between the input and output logical operators.

  • A Cube is a fundamental building block constituting of a block of quantum operations that occupy a specific spacetime volume. Quantum information encoded in the logical qubits can be preserved or manipulated by these blocks.

  • A Pipe is a block that connects Cube objects in a BlockGraph but does not occupy spacetime volume on its own. The exception here are temporal hadamard pipes that have a volume when compiled using the fixed bulk convention.

  • PipeKind helps determine the kind of a pipe in a BlockGraph based on the wall bases at the head of the pipe in addition to a Hadamard transition.

  • Port depicts the open ports in a BlockGraph.

  • A YHalfCube represents Y-basis initialization and measurements.

  • ZXCube defines cubes with only X or Z basis boundaries.

compile#

Responsible for translations between internal representations.

BlockGraph obtained from the functionality in interop is further translated into a TopologicalComputationGraph represented by Block instances.

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config:
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---
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init: {
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    }
}
}%%

graph
    A[BlockGraph] --> B[Topological <br> Computation Graph] --> C[ScheduledCircuit]--> D[stim.Circuit]

Multiple block builder protocols defined in tqec.compile.spec.library will take the high-level structure of a block to templates and plaquettes, that can in turn be used to generate a fully annotated stim.Circuit.

templates#

Generates an array of numbers representing a 2-dimensional, scalable, arrangement of plaquettes. This allows us to describe a circuit that can scale the desired code distance.

plaquette#

A plaquette is the representation of a local quantum circuit. A surface code patch implements one layer in time or one round of the surface code. Same as templates, this module allows us to define scalable quantum circuits.

circuit#

Implementation of ScheduledCircuit, a quantum circuit representation in tqec, where each and every gate of a regular quantum circuit is associated with the time of execution. This module maps from the numbered templates to some plaquettes that implement small local circuits to measure a stabilizer as a ScheduledCircuit instance.

NoiseModel#

Note

The code for this module was modified from the code for [1].

This module implements the following noise models for Stim simulations:

  1. Superconducting Inspired Circuit Error Model (SI1000): A modified version of the noise model introduced in [2] which represents the noise on Google’s superconducting quantum chip.

    In si1000():

    • Depolarizing noise on measured qubits from the noise modeil in [2] has been removed because tqec measurements are immediately followed by resets.

    • The measurement result is probabilistically flipped instead of the input qubit.

  2. Uniform Depolarizing Noise: Single qubit depolarizing noise is uniformly applied to both single qubit and two qubit Clifford gates.

    In uniform_depolarizing():

    • The result of dissipative gates is probabilistically bit or phase flipped.

    • Result of non-demolition measurements is flipped instead of the input qubit.

simulation#

Utilities related to quantum circuit simulations through sinter, a Python submodule in stim. Plotting functions are in this module too.

References#