pygsti.evotypes.stabilizer_slow.stabilizer
Defines the StabilizerState and StabilizerFrame classes
Module Contents
Classes
Encapsulates a stabilizer frame (linear combo of stabilizer states). |
Functions
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Computes a tensor-product StabilizerFrame from a set of factors. |
- class pygsti.evotypes.stabilizer_slow.stabilizer.StabilizerFrame(state_s, state_ps=None, amps=None)
Bases:
objectEncapsulates a stabilizer frame (linear combo of stabilizer states).
Stores stabilizer elements in the first n, and antistabilizer elements in the latter n columns of the “state matrix” (to facilitate composition), and phase vectors & amplitudes in parallel arrays.
Parameters
- state_snumpy.ndarray
A 2n x 2n binary matrix, where n is the number of qubits. The first n columns specify stabilizer elements and the latter n colunns specify anti-stabilizer elements. In each column, bits (i,i+n) encode a Pauli on the i-th qubit: 00 = I, 10 = X, 01 = Z, 11 = -iY. (Note the -iY is different from some representations in the literature which encode 11 = Y.)
- state_psnumpy.ndarray, optional
A mod-4 array of shape (k,2n) where n is the number of qubits and k is the number of components in the stabilizer frame. Each row of state_ps is the phase vector for the corresponding to to an amplitude in amps. A phase vector encodes the overall phase of each of the stabilizer and anti-stabilizer elements (the columns of state_s) by specyfing the number of ‘i’ factors (0 to 3). If None, then no phase vectors are stored.
- ampsnumpy.ndarray, optional
The (complex) amplitudes for each stabilizer-state component of the frame. The length of this 1D array must equal ‘k’, the first dimension of state_ps. amps should be None when and only when state_ps is None, corresponding to the case of zero components.
Attributes
- nqubitsint
The number of qubits in the state this frame represents
Initialize a new StabilizerFrame object.
Parameters
- state_snumpy.ndarray
A 2n x 2n binary matrix, where n is the number of qubits. The first n columns specify stabilizer elements and the latter n colunns specify anti-stabilizer elements. In each column, bits (i,i+n) encode a Pauli on the i-th qubit: 00 = I, 10 = X, 01 = Z, 11 = -iY. (Note the -iY is different from some representations in the literature which encode 11 = Y.)
- state_psnumpy.ndarray, optional
A mod-4 array of shape (k,2n) where n is the number of qubits and k is the number of components in the stabilizer frame. Each row of state_ps is the phase vector for the corresponding to to an amplitude in amps. A phase vector encodes the overall phase of each of the stabilizer and anti-stabilizer elements (the columns of state_s) by specyfing the number of ‘i’ factors (0 to 3). If None, then no phase vectors are stored.
- ampsnumpy.ndarray, optional
The (complex) amplitudes for each stabilizer-state component of the frame. The length of this 1D array must equal ‘k’, the first dimension of state_ps. amps should be None when and only when state_ps is None, corresponding to the case of zero components.
- classmethod from_zvals(nqubits=None, zvals=None)
Create a StabilizerFrame for a computational basis state.
Parameters
- nqubitsint, optional
The number of qubits. If None, inferred from the length of zvals.
- zvalsiterable, optional
An iterable over anything that can be cast as True/False to indicate the 0/1 value of each qubit in the Z basis. If None, the all-zeros state is created.
Returns
StabilizerFrame
- to_rep(state_space)
Return a “representation” object for this StabilizerFrame
Such objects are primarily used internally by pyGSTi to compute things like probabilities more efficiently.
Returns
StateRep
- copy()
Copy this stabilizer frame.
Note that this also copies “view filters” setup via push_view calls.
Returns
StabilizerFrame
- push_view(qubit_filter)
Applies a filter to the action of clifford_update.
After calling push_view, the stabilizer frame looks to some extent as though it were only a frame on the subset of qubits given by qubit_fitler. In particular, calls to clifford_update should specify clifford operations that act only on the filtered qubits. Furthermore, views can be nested. For example, if on a frame starting with 10 qubits (labeled 0 to 9) push_view([3,4,5,6]) and then push_view([0,2]) are called, the current “view” will be of the original qubits 3 and 5.
This is useful for applying “embedded” gates (those acting on just a subset of the state space).
Parameters
- qubit_filterlist
A list of qubit indices to view, relative to the current view.
Returns
None
- pop_view()
Removes the last-applied (via
push_view()) view filter.Returns
- list
A list of qubit indices to view (a “view filter”).
- format_state()
Get a string representing the full ip-th stabilizer state (w/global phase)
Returns
str
- extract_all_amplitudes()
Get a dictionary of the full amplitudes of each present computational basis state.
This may take a while for many-qubit states, as it requires getting 2^(num_qubits) amplitudes.
Returns
- dict
Keys are tuples of z-values specifying the different computational basis states. Values are the complex amplitudes.
- to_statevec()
Convert this stabilizer frame to dense length-2^(num_qubits) complex state vector of amplitudes.
Returns
numpy.ndarray
- extract_amplitude(zvals)
Get the full (not just “canonical”) amplitude of a given computational basis state.
Parameters
- zvalsnumpy.ndarray
An array of 0/1 elements specifying the desired basis state.
Returns
complex
- clifford_update(smatrix, svector, u_mx, qubit_filter=None)
Update this stabilizer frame by the action of a Clifford operation.
The Clifford operation is given in the usual symplectic representation. If there are any active views (from calling
push_view()) and/or if qubit_filter is not None, then smatrix, svector, and u_mx should be sized for just the number of qubits in the current view.Parameters
- smatrixnumpy.ndarray
The symplectic matrix of shape (2n,2n), where n is the number of qubits (in the current view if applicable), representing the Clifford operation.
- svectornumpy.ndarray
The phase vector of shape (2n,) representing the Clifford operation.
- u_mxnumpy.ndarray
The dense unitary representation of the Clifford action, which is needed in order to track the global phase of the frame (state). This is a complex matrix of shape (2^n,2^n), where n is the number of qubits (in the current view if applicable).
- qubit_filterlist, optional
An additional view filter to apply just for this function call (i.e. it is not stored on a stack as it is for
push_view().
Returns
None
- measurement_probability(zvals, qubit_filter=None, return_state=False, check=False)
Extract the probability of obtaining a given computation-basis-measurement outcome.
Parameters
- zvalsnumpy.ndarray
An array of 0/1 elements specifying the computational basis outcomes.
- qubit_filterlist, optional
A list specifying a subset of the qubits to measure. len(zvals) should always equal len(qubit_filter). If None, then all qubits are measured. Currently unsupported.
- return_statebool, optional
Whether the post-measurement state (frame) should be returned. Currently unsupported.
- checkbool, optional
Whether to perform internal self-consistency checks (for debugging, makes function run more slowly).
Returns
float