def config(X):
n = int(np.ceil(np.log2(len(X[0])))) # pylint: disable=no-member
n = 2**int(np.ceil(np.log2(n))) # n tem que ser potência de 2. # pylint: disable=no-member
N = 2**n - 1 # len(X[0])-1 # N precisa ser tal que n seja potência de 2 mais próxima de log_2(X[0]). O hierarchical exige que n seja dessa maneira.
w = 2 * n - 1 # número de parâmetros do circuito (weights)
X = np.c_[X, np.zeros((len(X), 2**n - len(X[0])))] # o número de qubits necessários para codificar os dados (log_2(N)) precisa ser uma potencia de 2. # pylint: disable=no-member
return n, N, w, X
def config(X):
n = int(np.ceil(np.log2(len(X[0])))) # pylint: disable=no-member
n = 2**int(np.ceil(np.log2(n))) # n tem que ser potência de 2. # pylint: disable=no-member
N = n # número total de qubits no circuito.
w = 2*n - 1 # número de parâmetros do circuito (weights)
X = np.c_[X, np.zeros((len(X), 2**n-len(X[0])))] # o número de qubits necessários para codificar os dados (log_2(N)) precisa ser uma potencia de 2. # pylint: disable=no-member
return n, N, w, X
def compute_indices(wires, n_block_wires):
"""Generate a list containing the wires for each block.
Args:
wires (Iterable): wires that the template acts on
n_block_wires (int): number of wires per block
Returns:
layers (array): array of wire labels for each block
"""
n_wires = len(wires)
if n_block_wires % 2 != 0:
raise ValueError(
f"n_block_wires must be an even integer; got {n_block_wires}")
if n_block_wires < 2:
raise ValueError(
f"number of wires in each block must be larger than or equal to 2; got n_block_wires = {n_block_wires}"
)
if n_block_wires > n_wires:
raise ValueError(
f"n_block_wires must be smaller than or equal to the number of wires; "
f"got n_block_wires = {n_block_wires} and number of wires = {n_wires}"
)
if not np.log2(n_wires / n_block_wires).is_integer():
warnings.warn(
f"The number of wires should be n_block_wires times 2^n; got n_wires/n_block_wires = {n_wires/n_block_wires}"
)
n_wires = 2**(int(np.log2(len(wires) / n_block_wires))) * n_block_wires
n_layers = int(np.log2(n_wires // n_block_wires)) + 1
layers = [[
wires[i] for i in range(
x + 2**(j - 1) * n_block_wires // 2 - n_block_wires // 2,
x + n_block_wires // 2 + 2**(j - 1) * n_block_wires // 2 -
n_block_wires // 2,
)
] + [
wires[i] for i in range(
x + 2**(j - 1) * n_block_wires // 2 +
2**(j - 1) * n_block_wires // 2 - n_block_wires // 2,
x + 2**(j - 1) * n_block_wires // 2 + n_block_wires // 2 +
2**(j - 1) * n_block_wires // 2 - n_block_wires // 2,
)
] for j in range(1, n_layers + 1)
for x in range(0, n_wires - n_block_wires // 2, 2**(j - 1) *
n_block_wires)]
return layers
def config(X):
n = 2**int(np.ceil(np.log2(len(X[0])))) # len(X[0]) # número de qubits necessário para armazenar o dado codificado. # pylint: disable=no-member
N = n # número total de qubits no circuito.
w = 2 * n - 1 # número de parâmetros do circuito (weights)
X = np.c_[X, np.zeros((len(X), n - len(X[0])))] # pylint: disable=no-member
return n, N, w, X
def shadow_bound(error, observables, failure_rate=0.01):
"""
Calculate the shadow bound for the Pauli measurement scheme.
Implements Eq. (S13) from https://arxiv.org/pdf/2002.08953.pdf
Args:
error (float): The error on the estimator.
observables (list) : List of matrices corresponding to the observables we intend to
measure.
failure_rate (float): Rate of failure for the bound to hold.
Returns:
An integer that gives the number of samples required to satisfy the shadow bound and
the chunk size required attaining the specified failure rate.
"""
M = len(observables)
K = 2 * np.log(2 * M / failure_rate)
shadow_norm = (
lambda op: np.linalg.norm(
op - np.trace(op) / 2 ** int(np.log2(op.shape[0])), ord=np.inf
)
** 2
)
N = 34 * max(shadow_norm(o) for o in observables) / error ** 2
return int(np.ceil(N * K)), int(K)
def get_n_blocks(wires, n_block_wires):
"""Returns the expected number of blocks for a set of wires and number of wires per block.
Args:
wires (Sequence): number of wires the template acts on
n_block_wires (int): number of wires per block
Returns:
n_blocks (int): number of blocks; expected length of the template_weights argument
"""
n_wires = len(wires)
if not np.log2(n_wires / n_block_wires).is_integer():
warnings.warn(
f"The number of wires should be n_block_wires times 2^n; got n_wires/n_block_wires = {n_wires/n_block_wires}"
)
if n_block_wires > n_wires:
raise ValueError(
f"n_block_wires must be smaller than or equal to the number of wires; got n_block_wires = {n_block_wires} and number of wires = {n_wires}"
)
n_blocks = 2**int(np.log2(n_wires / n_block_wires)) * 2 - 1
return n_blocks
def __init__(
self,
wires,
n_block_wires,
block,
n_params_block,
template_weights=None,
do_queue=True,
id=None,
):
self.ind_gates = compute_indices(wires, n_block_wires)
n_wires = len(wires)
shape = qml.math.shape(template_weights) # (n_params_block, n_blocks)
self.n_params_block = n_params_block
self.n_blocks = 2**int(np.log2(n_wires / n_block_wires)) * 2 - 1
self.block = block
if shape == ():
self.template_weights = np.random.rand(n_params_block,
int(self.n_blocks))
else:
if shape[0] != self.n_blocks:
raise ValueError(
f"Weights tensor must have first dimension of length {self.n_blocks}; got {shape[0]}"
)
if shape[-1] != self.n_params_block:
raise ValueError(
f"Weights tensor must have last dimension of length {self.n_params_block}; got {shape[-1]}"
)
self.template_weights = template_weights
super().__init__(template_weights,
wires=wires,
do_queue=do_queue,
id=id)
dev = qml.device("default.qubit.autograd", wires=num_qubits)
constant_hea_depth = 3
ansatze = [
ttn_circuit(num_qubits),
mera_circuit(num_qubits),
hea_circuit(num_qubits),
hea_circuit(num_qubits),
hea_circuit(num_qubits)
]
num_params_ansatz = [
num_params_per_gate * get_num_ttn_gates(num_qubits),
num_params_per_gate * get_num_mera_gates(num_qubits),
3 * (num_qubits * constant_hea_depth),
3 * (num_qubits * int(np.floor(np.log2(num_qubits)))),
3 * (num_qubits * num_qubits)
]
ansatz_names = [
"TTN", "MERA", "HEA (constant)", "HEA (log)", "HEA (linear)"
]
for (ansatz, ansatz_name, num_params) in zip(ansatze, ansatz_names,
num_params_ansatz):
print(f" --- {ansatz_name} ({num_params} parameters) ---")
for init in initializations:
print(f" +++ {init} +++")
mod_ansatz = ansatz
if init in ["Random |+...+>", "Zero |+...+>"]:
