Basic Examples (2) 

Run a controlled-Hadamard automaton from a bit-list initial layer:

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Visualize the result:

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Scope (4) 

Use a QuantumState initial condition and a named QuantumOperator rule:

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Use the explicit global state vector for |1001〉 and a raw unitary matrix:

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Define the two-qubit state vector |00〉 before passing it to the automaton:

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Compare an exact qubit string with a machine-real amplitude vector of the same printed values:

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Generalizations & Extensions (2) 

Evolve a coherent superposition instead of a computational-basis state:

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Supply the Margolus phase as the fourth positional argument:

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Options (4) 

Compare the one-block circuit diagrams produced by the two Margolus phases:

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Force the general tensor backend while changing the initial phase:

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Use a tighter numerical tolerance with automatic backend selection:

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Combine plot views while hiding the matrix and retaining backend metadata:

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Applications (2) 

Visualize the spreading of a local excitation under a controlled-Hadamard rule:

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Extract the final site purities from the reduced Bloch-vector lengths:

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Properties and Relations (3) 

Each requested step contributes two Margolus substeps and two stored state transitions:

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The automatically selected classical backend agrees with the general tensor backend:

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The returned circuit always represents one complete Margolus block:

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Possible Issues (3) 

Mixed-state QuantumState objects are not accepted because density-matrix evolution is not implemented.

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The state-vector dimension grows exponentially with the number of qubits:

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Bit-list initial conditions must contain an even number of binary entries:

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Neat Examples (1) 

Compare phase-zero and phase-one controlled-Hadamard evolutions side by side:

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