add qpu conf

Author: liwt31

tencirchem/static/engine_hea.py

@@ -16,6 +16,15 @@
 from tencirchem.utils.backend import jit
 
 
+class QpuConf:
+ def __init__(self, device=None, provider=None, initial_mapping=None):
+ if device is None:
+ device = "tianji_s2"
+ self.device = device
+ self.privider = provider
+ self.initial_mapping = initial_mapping
+
+
 @partial(jit, static_argnums=[1])
 def get_statevector(params, get_circuit):
  return get_circuit(params).state()
@@ -73,7 +82,7 @@ def get_energy_tensornetwork_noise_shot(params, paulis, coeffs, get_dmcircuit, n
  return sample_expectation_pauli(c, paulis, coeffs, shots, noise_conf)
 
 
-def get_energy_qpu(params, paulis, coeffs, get_circuit, shots: int):
+def get_energy_qpu(params, paulis, coeffs, get_circuit, qpu_conf: QpuConf, shots: int):
  c: Circuit = get_circuit(params)
  pss = []
  symbol_mapping = {"X": 1, "Y": 2, "Z": 3}
@@ -91,7 +100,7 @@ def get_energy_qpu(params, paulis, coeffs, get_circuit, shots: int):
  assert len(pss) == len(coeffs_non_identity)
  es = []
  for _ in range((shots - 1) // 8192 + 1):
- e = batch_expectation_ps(c, pss, device="tianji_s2", ws=coeffs_non_identity, shots=8192)
+ e = batch_expectation_ps(c, pss, device=qpu_conf.device, ws=coeffs_non_identity, shots=8192)
  es.append(e)
  print(paulis)
  print(coeffs)
@@ -158,10 +167,3 @@ def get_energy_and_grad_qpu(params, paulis, coeffs, get_circuit, shots: int, gra
  shots=shots,
  )
  return _get_energy_and_grad(partial_get_energy, params, grad)
-
-
-class QpuConf:
- def __init__(self, device=None, provider=None, initial_mapping=None):
- self.device = device
- self.privider = provider
- self.initial_mapping = initial_mapping

tencirchem/static/hea.py

@@ -31,6 +31,7 @@
 from tensorcircuit.noisemodel import NoiseConf, circuit_with_noise
 
 from tencirchem.static.engine_hea import (
+ QpuConf,
  get_statevector,
  get_densitymatrix,
  get_energy_tensornetwork,
@@ -436,7 +437,7 @@ def __init__(
  circuit: Union[Callable, QuantumCircuit],
  init_guess: Union[List[float], np.ndarray],
  engine: str = None,
- engine_conf: NoiseConf = None,
+ engine_conf: [NoiseConf, QpuConf] = None,
  ):
  """
  Construct the HEA class from Hamiltonian in :class:`QubitOperator` form and the ansatz.
@@ -463,8 +464,11 @@ def __init__(
  engine = "tensornetwork"
  if engine == "tensornetwork" and engine_conf is not None:
  raise ValueError("Tensornetwork engine does not have engine configuration")
- if engine.startswith("tensornetwork-noise") and engine_conf is None:
- engine_conf = get_noise_conf()
+ if engine_conf is None:
+ if engine.startswith("tensornetwork-noise"):
+ engine_conf = get_noise_conf()
+ if engine.startswith("qpu"):
+ engine_conf = QpuConf()
 
  init_guess = np.array(init_guess)
 
@@ -738,6 +742,7 @@ def energy(self, params: Tensor = None, engine: str = None) -> float:
  tuple(self.h_qubit_op.terms.keys()),
  list(self.h_qubit_op.terms.values()),
  self.get_circuit,
+ self.engine_conf,
  self.shots,
  )
  return e