neuralqx.operators.computational.qr.numba.flux module

class QRFlux(H, *, site, power=1.0, inverse=False)

Bases: ComputationalOperator

QRLG flux operator on a single site site:

  • Diagonal in the computational basis

  • Eigenvalue f(s_site) with

    if inverse == False: f(e) = e^power if inverse == True: f(e) = (1/e)^power, with 0 -> 0.

Discrete representation:

  • Emits exactly one connected configuration (itself)

  • Matrix element is the diagonal eigenvalue

property is_hermitian: bool

This function must return either True or False based on whether your operator is Hermitian or not. Note that unlike for the case of LocalOperator types, you must specify by-hand whether this operator is Hermitian or not, there is no implementation to deduce that information for you as there is no matrices stored in this operator type.

This property plays a role in determining the computational path to be taken when computing gradients. If you specify that the operator is Hermitian while in reality it is not, the computed gradients will be incorrect.

Returns:

True if this operator is Hermitian, False otherwise

property dtype

Specify a JAX NumPy or NumPy dtype for this operator (that is, what is the dtype of the matrix elements returned by this operator)