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tankya2
2023-08-17 13:23:29 +08:00
parent 3fafe2b3ff
commit 89bdbfbe68
3 changed files with 89 additions and 77 deletions
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94
src/qibotn/MPSContractionHelper.py
View File

@@ -1,59 +1,64 @@
from cuquantum import contract, contract_path, CircuitToEinsum, tensor
class MPSContractionHelper:
"""
A helper class to compute various quantities for a given MPS.
Interleaved format is used to construct the input args for `cuquantum.contract`.
Interleaved format is used to construct the input args for `cuquantum.contract`.
A concrete example on how the modes are populated for a 7-site MPS is provided below:
0 2 4 6 8 10 12 14
0 2 4 6 8 10 12 14
bra -----A-----B-----C-----D-----E-----F-----G-----
| | | | | | |
1| 3| 5| 7| 9| 11| 13|
| | | | | | |
| | | | | | |
1| 3| 5| 7| 9| 11| 13|
| | | | | | |
ket -----a-----b-----c-----d-----e-----f-----g-----
15 16 17 18 19 20 21 22
The follwing compute quantities are supported:
- the norm of the MPS.
- the equivalent state vector from the MPS.
- the expectation value for a given operator.
- the equivalent state vector after multiplying an MPO to an MPS.
Note that for the nth MPS tensor (rank-3), the modes of the tensor are expected to be `(i,p,j)`
where i denotes the bonding mode with the (n-1)th tensor, p denotes the physical mode for the qubit and
Note that for the nth MPS tensor (rank-3), the modes of the tensor are expected to be `(i,p,j)`
where i denotes the bonding mode with the (n-1)th tensor, p denotes the physical mode for the qubit and
j denotes the bonding mode with the (n+1)th tensor.
Args:
num_qubits: The number of qubits for the MPS.
"""
def __init__(self, num_qubits):
self.num_qubits = num_qubits
self.bra_modes = [(2*i, 2*i+1, 2*i+2) for i in range(num_qubits)]
offset = 2*num_qubits+1
self.ket_modes = [(i+offset, 2*i+1, i+1+offset) for i in range(num_qubits)]
self.bra_modes = [(2 * i, 2 * i + 1, 2 * i + 2) for i in range(num_qubits)]
offset = 2 * num_qubits + 1
self.ket_modes = [
(i + offset, 2 * i + 1, i + 1 + offset) for i in range(num_qubits)
]
def contract_norm(self, mps_tensors, options=None):
"""
Contract the corresponding tensor network to form the norm of the MPS.
Args:
mps_tensors: A list of rank-3 ndarray-like tensor objects.
The indices of the ith tensor are expected to be bonding index to the i-1 tensor,
mps_tensors: A list of rank-3 ndarray-like tensor objects.
The indices of the ith tensor are expected to be bonding index to the i-1 tensor,
the physical mode, and then the bonding index to the i+1th tensor.
options: Specify the contract and decompose options.
options: Specify the contract and decompose options.
Returns:
The norm of the MPS.
"""
interleaved_inputs = []
for i, o in enumerate(mps_tensors):
interleaved_inputs.extend([o, self.bra_modes[i], o.conj(), self.ket_modes[i]])
interleaved_inputs.append([]) # output
interleaved_inputs.extend(
[o, self.bra_modes[i], o.conj(), self.ket_modes[i]]
)
interleaved_inputs.append([]) # output
return self._contract(interleaved_inputs, options=options).real
def contract_state_vector(self, mps_tensors, options=None):
@@ -61,10 +66,10 @@ class MPSContractionHelper:
Contract the corresponding tensor network to form the state vector representation of the MPS.
Args:
mps_tensors: A list of rank-3 ndarray-like tensor objects.
The indices of the ith tensor are expected to be bonding index to the i-1 tensor,
mps_tensors: A list of rank-3 ndarray-like tensor objects.
The indices of the ith tensor are expected to be bonding index to the i-1 tensor,
the physical mode, and then the bonding index to the i+1th tensor.
options: Specify the contract and decompose options.
options: Specify the contract and decompose options.
Returns:
An ndarray-like object as the state vector.
@@ -73,28 +78,30 @@ class MPSContractionHelper:
for i, o in enumerate(mps_tensors):
interleaved_inputs.extend([o, self.bra_modes[i]])
output_modes = tuple([bra_modes[1] for bra_modes in self.bra_modes])
interleaved_inputs.append(output_modes) # output
interleaved_inputs.append(output_modes) # output
return self._contract(interleaved_inputs, options=options)
def contract_expectation(self, mps_tensors, operator, qubits, options=None, normalize=False):
def contract_expectation(
self, mps_tensors, operator, qubits, options=None, normalize=False
):
"""
Contract the corresponding tensor network to form the state vector representation of the MPS.
Args:
mps_tensors: A list of rank-3 ndarray-like tensor objects.
The indices of the ith tensor are expected to be bonding index to the i-1 tensor,
mps_tensors: A list of rank-3 ndarray-like tensor objects.
The indices of the ith tensor are expected to be bonding index to the i-1 tensor,
the physical mode, and then the bonding index to the i+1th tensor.
operator: A ndarray-like tensor object.
The modes of the operator are expected to be output qubits followed by input qubits, e.g,
``A, B, a, b`` where `a, b` denotes the inputs and `A, B'` denotes the outputs.
qubits: A sequence of integers specifying the qubits that the operator is acting on.
options: Specify the contract and decompose options.
operator: A ndarray-like tensor object.
The modes of the operator are expected to be output qubits followed by input qubits, e.g,
``A, B, a, b`` where `a, b` denotes the inputs and `A, B'` denotes the outputs.
qubits: A sequence of integers specifying the qubits that the operator is acting on.
options: Specify the contract and decompose options.
normalize: Whether to scale the expectation value by the normalization factor.
Returns:
An ndarray-like object as the state vector.
"""
interleaved_inputs = []
extra_mode = 3 * self.num_qubits + 2
operator_modes = [None] * len(qubits) + [self.bra_modes[q][1] for q in qubits]
@@ -105,19 +112,18 @@ class MPSContractionHelper:
if i in qubits:
k_modes = (k_modes[0], extra_mode, k_modes[2])
q = qubits.index(i)
operator_modes[q] = extra_mode # output modes
operator_modes[q] = extra_mode # output modes
extra_mode += 1
interleaved_inputs.extend([o.conj(), k_modes])
interleaved_inputs.extend([operator, tuple(operator_modes)])
interleaved_inputs.append([]) # output
interleaved_inputs.append([]) # output
if normalize:
norm = self.contract_norm(mps_tensors, options=options)
else:
norm = 1
return self._contract(interleaved_inputs, options=options) / norm
def _contract(self, interleaved_inputs, options=None):
def _contract(self, interleaved_inputs, options=None):
path = contract_path(*interleaved_inputs, options=options)[0]
return contract(*interleaved_inputs, options=options, optimize={'path':path})
return contract(*interleaved_inputs, options=options, optimize={"path": path})

69
src/qibotn/MPSUtils.py
View File

@@ -2,73 +2,80 @@ import cupy as cp
from cuquantum.cutensornet.experimental import contract_decompose
from cuquantum import contract
def initial(num_qubits, dtype):
"""
Generate the MPS with an initial state of |00...00>
Generate the MPS with an initial state of |00...00>
"""
state_tensor = cp.asarray([1, 0], dtype=dtype).reshape(1,2,1)
state_tensor = cp.asarray([1, 0], dtype=dtype).reshape(1, 2, 1)
mps_tensors = [state_tensor] * num_qubits
return mps_tensors
def mps_site_right_swap(
mps_tensors,
i,
**kwargs
):
def mps_site_right_swap(mps_tensors, i, **kwargs):
"""
Perform the swap operation between the ith and i+1th MPS tensors.
"""
# contraction followed by QR decomposition
a, _, b = contract_decompose('ipj,jqk->iqj,jpk', *mps_tensors[i:i+2], algorithm=kwargs.get('algorithm',None), options=kwargs.get('options',None))
mps_tensors[i:i+2] = (a, b)
a, _, b = contract_decompose(
"ipj,jqk->iqj,jpk",
*mps_tensors[i : i + 2],
algorithm=kwargs.get("algorithm", None),
options=kwargs.get("options", None)
)
mps_tensors[i : i + 2] = (a, b)
return mps_tensors
def apply_gate(
mps_tensors,
gate,
qubits,
**kwargs
):
def apply_gate(mps_tensors, gate, qubits, **kwargs):
"""
Apply the gate operand to the MPS tensors in-place.
Args:
mps_tensors: A list of rank-3 ndarray-like tensor objects.
The indices of the ith tensor are expected to be the bonding index to the i-1 tensor,
mps_tensors: A list of rank-3 ndarray-like tensor objects.
The indices of the ith tensor are expected to be the bonding index to the i-1 tensor,
the physical mode, and then the bonding index to the i+1th tensor.
gate: A ndarray-like tensor object representing the gate operand.
The modes of the gate is expected to be output qubits followed by input qubits, e.g,
``A, B, a, b`` where ``a, b`` denotes the inputs and ``A, B`` denotes the outputs.
gate: A ndarray-like tensor object representing the gate operand.
The modes of the gate is expected to be output qubits followed by input qubits, e.g,
``A, B, a, b`` where ``a, b`` denotes the inputs and ``A, B`` denotes the outputs.
qubits: A sequence of integers denoting the qubits that the gate is applied onto.
algorithm: The contract and decompose algorithm to use for gate application.
algorithm: The contract and decompose algorithm to use for gate application.
Can be either a `dict` or a `ContractDecomposeAlgorithm`.
options: Specify the contract and decompose options.
options: Specify the contract and decompose options.
Returns:
The updated MPS tensors.
"""
n_qubits = len(qubits)
if n_qubits == 1:
# single-qubit gate
i = qubits[0]
mps_tensors[i] = contract('ipj,qp->iqj', mps_tensors[i], gate, options=kwargs.get('options',None)) # in-place update
mps_tensors[i] = contract(
"ipj,qp->iqj", mps_tensors[i], gate, options=kwargs.get("options", None)
) # in-place update
elif n_qubits == 2:
# two-qubit gate
i, j = qubits
if i > j:
# swap qubits order
return apply_gate(mps_tensors, gate.transpose(1,0,3,2), (j, i), **kwargs)
elif i+1 == j:
return apply_gate(mps_tensors, gate.transpose(1, 0, 3, 2), (j, i), **kwargs)
elif i + 1 == j:
# two adjacent qubits
a, _, b = contract_decompose('ipj,jqk,rspq->irj,jsk', *mps_tensors[i:i+2], gate, algorithm=kwargs.get('algorithm',None), options=kwargs.get('options',None))
mps_tensors[i:i+2] = (a, b) # in-place update
a, _, b = contract_decompose(
"ipj,jqk,rspq->irj,jsk",
*mps_tensors[i : i + 2],
gate,
algorithm=kwargs.get("algorithm", None),
options=kwargs.get("options", None)
)
mps_tensors[i : i + 2] = (a, b) # in-place update
else:
# non-adjacent two-qubit gate
# step 1: swap i with i+1
mps_site_right_swap(mps_tensors, i, **kwargs)
# step 2: apply gate to (i+1, j) pair. This amounts to a recursive swap until the two qubits are adjacent
apply_gate(mps_tensors, gate, (i+1, j), **kwargs)
apply_gate(mps_tensors, gate, (i + 1, j), **kwargs)
# step 3: swap back i and i+1
mps_site_right_swap(mps_tensors, i, **kwargs)
else:

3
src/qibotn/QiboCircuitConvertor.py
View File

@@ -44,8 +44,7 @@ class QiboCircuitToEinsum:
for key in qubits_frontier:
out_list.append(qubits_frontier[key])
operand_exp_interleave = [x for y in zip(
operands, mode_labels) for x in y]
operand_exp_interleave = [x for y in zip(operands, mode_labels) for x in y]
operand_exp_interleave.append(out_list)
return operand_exp_interleave