jaunatisblue/final-qibotn
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

Allow user to specify Pauli string pattern for expecation calculation [skip CI]

Browse Source
This commit is contained in:
tankya2
2024-01-31 14:56:21 +08:00
committed by yangliwei
parent 928f99e336
commit 784b1a70ef
2 changed files with 38 additions and 15 deletions
Download Patch File Download Diff File Expand all files Collapse all files

33
src/qibotn/backends/gpu.py
View File

@@ -12,12 +12,35 @@ class CuTensorNet(NumpyBackend): # pragma: no cover
super().__init__()
import cuquantum # pylint: disable=import-error
from cuquantum import cutensornet as cutn # pylint: disable=import-error
self.pauli_string_pattern = "XXXZ"
if runcard is not None:
self.MPI_enabled = runcard.get("MPI_enabled", False)
self.MPS_enabled = runcard.get("MPS_enabled", False)
self.NCCL_enabled = runcard.get("NCCL_enabled", False)
self.expectation_enabled = runcard.get("expectation_enabled", False)
expectation_enabled_value = runcard.get('expectation_enabled')
if expectation_enabled_value is True:
self.expectation_enabled = True
print("expectation_enabled is",self.expectation_enabled)
elif expectation_enabled_value is False:
self.expectation_enabled = False
print("expectation_enabled is",self.expectation_enabled)
elif isinstance(expectation_enabled_value, dict):
self.expectation_enabled = True
expectation_enabled_dict = runcard.get('expectation_enabled', {})
self.pauli_string_pattern = expectation_enabled_dict.get('pauli_string_pattern', None)
print("expectation_enabled is a dictionary",self.expectation_enabled,self.pauli_string_pattern )
else:
raise TypeError("expectation_enabled has an unexpected type")
else:
self.MPI_enabled = False
self.MPS_enabled = False
@@ -144,7 +167,7 @@ class CuTensorNet(NumpyBackend): # pragma: no cover
if initial_state is not None:
raise_error(NotImplementedError, "QiboTN cannot support initial state.")
state = eval.expectation_pauli_tn(circuit, self.dtype)
state = eval.expectation_pauli_tn(circuit, self.dtype, self.pauli_string_pattern)
elif (
self.MPI_enabled == True
@@ -155,7 +178,7 @@ class CuTensorNet(NumpyBackend): # pragma: no cover
if initial_state is not None:
raise_error(NotImplementedError, "QiboTN cannot support initial state.")
state, rank = eval.expectation_pauli_tn_MPI(circuit, self.dtype, 32)
state, rank = eval.expectation_pauli_tn_MPI(circuit, self.dtype, self.pauli_string_pattern, 32)
if rank > 0:
state = np.array(0)
@@ -169,7 +192,7 @@ class CuTensorNet(NumpyBackend): # pragma: no cover
if initial_state is not None:
raise_error(NotImplementedError, "QiboTN cannot support initial state.")
state, rank = eval.expectation_pauli_tn_nccl(circuit, self.dtype, 32)
state, rank = eval.expectation_pauli_tn_nccl(circuit, self.dtype, self.pauli_string_pattern, 32)
if rank > 0:
state = np.array(0)

20
src/qibotn/eval.py
View File

@@ -15,10 +15,10 @@ def dense_vector_tn(qibo_circ, datatype):
return contract(*myconvertor.state_vector_operands())
def expectation_pauli_tn(qibo_circ, datatype):
def expectation_pauli_tn(qibo_circ, datatype, pauli_string):
myconvertor = QiboCircuitToEinsum(qibo_circ, dtype=datatype)
return contract(
*myconvertor.expectation_operands(PauliStringGen(qibo_circ.nqubits))
*myconvertor.expectation_operands(PauliStringGen(qibo_circ.nqubits, pauli_string))
)
@@ -204,7 +204,7 @@ def dense_vector_tn_nccl(qibo_circ, datatype, n_samples=8):
return result, rank
def expectation_pauli_tn_nccl(qibo_circ, datatype, n_samples=8):
def expectation_pauli_tn_nccl(qibo_circ, datatype, pauli_string, n_samples=8):
from mpi4py import MPI # this line initializes MPI
import socket
from cuquantum import Network
@@ -232,7 +232,7 @@ def expectation_pauli_tn_nccl(qibo_circ, datatype, n_samples=8):
myconvertor = QiboCircuitToEinsum(qibo_circ, dtype=datatype)
# mem_avail = cp.cuda.Device().mem_info[0]
# print("Mem avail: aft convetor",mem_avail, "rank =",rank)
operands = myconvertor.expectation_operands(PauliStringGen(qibo_circ.nqubits))
operands = myconvertor.expectation_operands(PauliStringGen(qibo_circ.nqubits, pauli_string))
# mem_avail = cp.cuda.Device().mem_info[0]
# print("Mem avail: aft operand interleave",mem_avail, "rank =",rank)
@@ -291,7 +291,7 @@ def expectation_pauli_tn_nccl(qibo_circ, datatype, n_samples=8):
return result, rank
def expectation_pauli_tn_MPI(qibo_circ, datatype, n_samples=8):
def expectation_pauli_tn_MPI(qibo_circ, datatype, pauli_string, n_samples=8):
from mpi4py import MPI # this line initializes MPI
import socket
from cuquantum import Network
@@ -311,7 +311,7 @@ def expectation_pauli_tn_MPI(qibo_circ, datatype, n_samples=8):
myconvertor = QiboCircuitToEinsum(qibo_circ, dtype=datatype)
# mem_avail = cp.cuda.Device().mem_info[0]
# print("Mem avail: aft convetor",mem_avail, "rank =",rank)
operands = myconvertor.expectation_operands(PauliStringGen(qibo_circ.nqubits))
operands = myconvertor.expectation_operands(PauliStringGen(qibo_circ.nqubits, pauli_string))
# mem_avail = cp.cuda.Device().mem_info[0]
# print("Mem avail: aft operand interleave",mem_avail, "rank =",rank)
@@ -379,17 +379,17 @@ def dense_vector_mps(qibo_circ, gate_algo, datatype):
)
def PauliStringGen(nqubits):
def PauliStringGen(nqubits, pauli_string):
if nqubits <= 0:
return "Invalid input. N should be a positive integer."
# characters = 'IXYZ'
characters = "XXXZ"
characters = pauli_string
#characters = "XXXZ"
result = ""
for i in range(nqubits):
char_to_add = characters[i % len(characters)]
result += char_to_add
print("pauli string", result)
return result