Template Class Measurements¶
Defined in File MeasurementsGPU.hpp
Inheritance Relationships¶
Base Type¶
public MeasurementsBase< StateVectorT, Measurements< StateVectorT > >
Class Documentation¶
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template<class StateVectorT>
class Measurements : public MeasurementsBase<StateVectorT, Measurements<StateVectorT>>¶ Observable’s Measurement Class.
This class couples with a statevector to performs measurements. Observables are defined by its operator(matrix), the observable class, or through a string-based function dispatch.
- Template Parameters
StateVectorT – type of the statevector to be measured.
Public Functions
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inline explicit Measurements(StateVectorT &statevector)¶
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inline auto probs(const std::vector<std::size_t> &wires) -> std::vector<PrecisionT>¶
Utility method for probability calculation using given wires.
- Parameters
wires – List of wires to return probabilities for in lexicographical order.
- Returns
std::vector<PrecisionT>
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inline auto probs() -> std::vector<PrecisionT>¶
Utility method for probability calculation for a full wires.
- Returns
std::vector<PrecisionT>
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inline std::vector<PrecisionT> probs(const Observable<StateVectorT> &obs, std::size_t num_shots = 0)¶
Probabilities to measure rotated basis states.
- Parameters
obs – An observable object.
num_shots – Number of shots(Optional).If specified with a non-zero number, shot-noise will be added to return probabilities
- Returns
Floating point std::vector with probabilities in lexicographic order.
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inline std::vector<PrecisionT> probs(std::size_t num_shots)¶
Probabilities with shot-noise.
- Parameters
num_shots – Number of shots.
- Returns
Floating point std::vector with probabilities.
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inline std::vector<PrecisionT> probs(const std::vector<std::size_t> &wires, std::size_t num_shots)¶
Probabilities with shot-noise for a subset of the full system.
- Parameters
num_shots – Number of shots.
wires – Wires will restrict probabilities to a subset of the full system.
- Returns
Floating point std::vector with probabilities.
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inline auto generate_samples(std::size_t num_samples, const std::optional<std::size_t> &seed = std::nullopt) -> std::vector<std::size_t>¶
Utility method for samples.
- Parameters
num_samples – Number of Samples
- Returns
std::vector<std::size_t> A 1-d array storing the samples. Each sample has a length equal to the number of qubits. Each sample can be accessed using the stride sample_id*num_qubits, where sample_id is a number between 0 and num_samples-1.
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template<class index_type>
inline auto expval(const index_type *csrOffsets_ptr, const int64_t csrOffsets_size, const index_type *columns_ptr, const std::complex<PrecisionT> *values_ptr, const int64_t numNNZ) -> PrecisionT¶ expval(H) calculation with cuSparseSpMV.
- Template Parameters
index_type – Integer type used as indices of the sparse matrix.
- Parameters
csr_Offsets_ptr – Pointer to the array of row offsets of the sparse matrix. Array of size csrOffsets_size.
csrOffsets_size – Number of Row offsets of the sparse matrix.
columns_ptr – Pointer to the array of column indices of the sparse matrix. Array of size numNNZ
values_ptr – Pointer to the array of the non-zero elements
numNNZ – Number of non-zero elements.
- Returns
auto Expectation value.
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inline auto expval(const std::string &operation, const std::vector<std::size_t> &wires) -> PrecisionT¶
Expected value of an observable.
- Parameters
operation – String with the operator name.
wires – Wires where to apply the operator.
- Returns
Floating point expected value of the observable.
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template<typename op_type>
inline auto expval(const std::vector<op_type> &operations_list, const std::vector<std::vector<std::size_t>> &wires_list) -> std::vector<PrecisionT>¶ Expected value for a list of observables.
- Template Parameters
op_type – Operation type.
- Parameters
operations_list – List of operations to measure.
wires_list – List of wires where to apply the operators.
- Returns
Floating point std::vector with expected values for the observables.
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inline auto expval(const Observable<StateVectorT> &ob) -> PrecisionT¶
Calculate expectation value for a general Observable.
- Parameters
ob – Observable.
- Returns
Expectation value with respect to the given observable.
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inline auto expval(const Observable<StateVectorT> &obs, const std::size_t &num_shots, const std::vector<std::size_t> &shot_range) -> PrecisionT¶
Expectation value for a Observable with shots.
- Parameters
obs – Observable.
num_shots – Number of shots used to generate samples
shot_range – The range of samples to use. All samples are used by default.
- Returns
Floating point expected value of the observable.
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inline auto expval(const std::vector<ComplexT> &matrix, const std::vector<std::size_t> &wires) -> PrecisionT¶
Expected value of an observable.
- Parameters
matrix – Square matrix in row-major order.
wires – Wires where to apply the operator.
- Returns
Floating point expected value of the observable.
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inline auto expval(const std::vector<std::string> &pauli_words, const std::vector<std::vector<std::size_t>> &target_wires, const std::complex<PrecisionT> *coeffs) -> PrecisionT¶
Expected value of an observable.
- Parameters
pauli_words – Vector of operators’ name strings.
target_wires – Vector of wires where to apply the operator.
coeffs – Complex buffer of size |pauli_words|
- Returns
Floating point expected value of the observable.
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inline auto var(const Observable<StateVectorT> &ob) -> PrecisionT¶
Calculate variance of a general observable.
- Parameters
ob – An observable object.
- Returns
Variance with respect to the given observable.
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inline auto var(const std::string &operation, const std::vector<std::size_t> &wires) -> PrecisionT¶
Variance of an observable.
- Parameters
operation – String with the operator name.
wires – Wires where to apply the operator.
- Returns
Floating point with the variance of the observable.
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inline auto var(const std::vector<ComplexT> &matrix, const std::vector<std::size_t> &wires) -> PrecisionT¶
Variance of an observable.
- Parameters
matrix – Square matrix in row-major order.
wires – Wires where to apply the operator.
- Returns
Floating point with the variance of the observable.
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template<typename op_type>
inline auto var(const std::vector<op_type> &operations_list, const std::vector<std::vector<std::size_t>> &wires_list) -> std::vector<PrecisionT>¶ Variance for a list of observables.
- Template Parameters
op_type – Operation type.
- Parameters
operations_list – List of operations to measure. Square matrix in row-major order or string with the operator name.
wires_list – List of wires where to apply the operators.
- Returns
Floating point std::vector with the variance of the observables.
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template<class index_type>
inline PrecisionT var(const index_type *csrOffsets_ptr, const int64_t csrOffsets_size, const index_type *columns_ptr, const std::complex<PrecisionT> *values_ptr, const int64_t numNNZ)¶ Variance of a sparse Hamiltonian.
- Template Parameters
index_type – integer type used as indices of the sparse matrix.
- Parameters
row_map_ptr – row_map array pointer. The j element encodes the number of non-zeros above row j.
row_map_size – row_map array size.
entries_ptr – pointer to an array with column indices of the non-zero elements.
values_ptr – pointer to an array with the non-zero elements.
numNNZ – number of non-zero elements.
- Returns
Floating point with the variance of the sparse Hamiltonian.
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inline auto var(const Observable<StateVectorT> &obs, const std::size_t &num_shots) -> PrecisionT¶
Calculate the variance for an observable with the number of shots.
- Parameters
obs – An observable object.
num_shots – Number of shots.
- Returns
Variance of the given observable.