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https://github.com/vale981/two_qubit_model
synced 2025-03-05 09:41:41 -05:00
modularize the two qubit model
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0ea031837c
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3 changed files with 165 additions and 138 deletions
79
model_base.py
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79
model_base.py
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"""A base class for model HOPS configs."""
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from utility import JSONEncoder, object_hook
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import numpy as np
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import json
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import copy
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import hashlib
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class Model:
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"""
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A base class with some data management functionality.
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"""
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__version__: int = 1
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"""
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The version of the model implementation. It is increased for
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breaking changes.
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"""
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def __init__(self, *_, **__):
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del _, __
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pass
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###########################################################################
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# Utility #
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###########################################################################
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def to_json(self):
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"""Returns a json representation of the model configuration."""
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return json.dumps(
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{key: self.__dict__[key] for key in self.__dict__ if key[0] != "_"}
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| {"__version__": self.__version__},
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cls=JSONEncoder,
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ensure_ascii=False,
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)
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def __hash__(self):
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return hashlib.sha256(self.to_json().encode("utf-8")).digest().__hash__()
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@classmethod
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def from_json(cls, json_str: str):
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"""
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Tries to instantiate a model config from the json string
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``json_str``.
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"""
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model_dict = json.loads(json_str, object_hook=object_hook)
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assert (
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model_dict["__version__"] == cls().__version__
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), "Incompatible version detected."
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del model_dict["__version__"]
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return cls(**model_dict)
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def __eq__(self, other):
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this_keys = list(self.__dict__.keys())
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ignored_keys = ["_sigmas"]
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for key in this_keys:
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if key not in ignored_keys:
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this_val, other_val = self.__dict__[key], other.__dict__[key]
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same = this_val == other_val
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if isinstance(this_val, np.ndarray):
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same = same.all()
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if not same:
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return False
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return self.__hash__() == other.__hash__()
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def copy(self):
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"""Return a deep copy of the model."""
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return copy.deepcopy(self)
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@ -33,7 +33,7 @@ from dataclasses import dataclass, field
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import functools
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import itertools
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from numpy.typing import NDArray
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from typing import Any, Optional, SupportsFloat, Type
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from typing import Any, Optional, SupportsFloat
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import hops.util.bcf
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import hops.util.bcf_fits
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import hops.core.hierarchy_parameters as params
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@ -45,30 +45,14 @@ from hops.util.truncation_schemes import (
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BathMemory,
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)
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import stocproc as sp
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import json
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from functools import singledispatchmethod
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import hashlib
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from beartype import beartype
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from utility import StocProcTolerances, operator_norm
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from model_base import Model
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@beartype
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@dataclass
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class StocProcTolerances:
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"""
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An object to hold tolerances for :any:`stocproc.StocProc`
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instances.
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"""
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integration: float = 1e-4
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"""Integration tolerance."""
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interpolation: float = 1e-4
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"""Interpolation tolerance."""
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@beartype
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@dataclass
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class TwoQubitModel:
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@dataclass(eq=False)
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class TwoQubitModel(Model):
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"""
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A class to dynamically calculate all the model parameters and
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generate the HOPS configuration.
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@ -76,12 +60,6 @@ class TwoQubitModel:
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All attributes can be changed after initialization.
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"""
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__version__: int = 1
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"""
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The version of the model implementation. It is increased for
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breaking changes.
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"""
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ω_2: SupportsFloat = 1.0
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"""The second oscilator energy gap."""
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@ -408,54 +386,6 @@ class TwoQubitModel:
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# Utility #
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###########################################################################
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def to_json(self):
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"""Returns a json representation of the model configuration."""
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return json.dumps(
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{
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key: self.__dict__[key]
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for key in self.__dict__
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if key[0] != "_" or key == "__version__"
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},
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cls=JSONEncoder,
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ensure_ascii=False,
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)
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def __hash__(self):
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return hashlib.sha256(self.to_json().encode("utf-8")).digest().__hash__()
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@classmethod
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def from_json(cls, json_str: str):
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"""
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Tries to instantiate a model config from the json string
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``json_str``.
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"""
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model_dict = json.loads(json_str, object_hook=_object_hook)
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assert (
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model_dict["__version__"] == cls().__version__
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), "Incompatible version detected."
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return cls(**model_dict)
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def __eq__(self, other):
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this_keys = list(self.__dict__.keys())
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ignored_keys = ["_sigmas"]
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for key in this_keys:
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if key not in ignored_keys:
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this_val, other_val = self.__dict__[key], other.__dict__[key]
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same = this_val == other_val
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if isinstance(this_val, np.ndarray):
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same = same.all()
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if not same:
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return False
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return self.__hash__() == other.__hash__()
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def effective_coupling(self, i: int) -> float:
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"""
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The effective coupling strength of bath ``i``. The maximum pre-factor times the bcf scale
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@ -587,66 +517,3 @@ class TwoQubitModel:
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return False
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return True
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def copy(self):
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"""Return a deep copy of the model."""
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return copy.deepcopy(self)
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class JSONEncoder(json.JSONEncoder):
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"""
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A custom encoder to serialize objects occuring in
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:any:`TwoQubitModel`.
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"""
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@singledispatchmethod
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def default(self, obj: Any):
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return super().default(obj)
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@default.register
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def _(self, arr: np.ndarray):
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return {"type": "array", "value": arr.tolist()}
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@default.register
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def _(self, obj: qt.Qobj):
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return {
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"type": "Qobj",
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"value": obj.full(),
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"dims": obj.dims,
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"obj_type": obj.type,
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}
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@default.register
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def _(self, obj: complex):
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return {"type": "complex", "re": obj.real, "im": obj.imag}
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@default.register
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def _(self, obj: StocProcTolerances):
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return {"type": "StocProcTolerances", "value": dataclasses.asdict(obj)}
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def _object_hook(dct: dict[str, Any]):
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"""A custom decoder for the types introduced in :any:`JSONEncoder`."""
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if "type" in dct:
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type = dct["type"]
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if type == "array":
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return np.array(dct["value"])
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if type == "Qobj":
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return qt.Qobj(dct["value"], dims=dct["dims"], type=dct["obj_type"])
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if type == "complex":
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return dct["re"] + 1j * dct["im"]
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if type == "StocProcTolerances":
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return StocProcTolerances(**dct["value"])
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return dct
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def operator_norm(obj: qt.Qobj) -> float:
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"""Returns the operator norm of ``obj``."""
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return np.sqrt(max(np.abs((obj.dag() * obj).eigenenergies())))
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81
utility.py
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81
utility.py
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@ -0,0 +1,81 @@
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from functools import singledispatchmethod
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import dataclasses
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from dataclasses import dataclass
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from beartype import beartype
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import json
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import numpy as np
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import qutip as qt
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from typing import Any
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@beartype
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@dataclass
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class StocProcTolerances:
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"""
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An object to hold tolerances for :any:`stocproc.StocProc`
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instances.
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"""
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integration: float = 1e-4
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"""Integration tolerance."""
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interpolation: float = 1e-4
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"""Interpolation tolerance."""
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class JSONEncoder(json.JSONEncoder):
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"""
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A custom encoder to serialize objects occuring in
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:any:`TwoQubitModel`.
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"""
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@singledispatchmethod
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def default(self, obj: Any):
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return super().default(obj)
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@default.register
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def _(self, arr: np.ndarray):
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return {"type": "array", "value": arr.tolist()}
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@default.register
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def _(self, obj: qt.Qobj):
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return {
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"type": "Qobj",
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"value": obj.full(),
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"dims": obj.dims,
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"obj_type": obj.type,
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}
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@default.register
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def _(self, obj: complex):
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return {"type": "complex", "re": obj.real, "im": obj.imag}
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@default.register
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def _(self, obj: StocProcTolerances):
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return {"type": "StocProcTolerances", "value": dataclasses.asdict(obj)}
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def object_hook(dct: dict[str, Any]):
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"""A custom decoder for the types introduced in :any:`JSONEncoder`."""
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if "type" in dct:
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type = dct["type"]
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if type == "array":
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return np.array(dct["value"])
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if type == "Qobj":
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return qt.Qobj(dct["value"], dims=dct["dims"], type=dct["obj_type"])
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if type == "complex":
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return dct["re"] + 1j * dct["im"]
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if type == "StocProcTolerances":
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return StocProcTolerances(**dct["value"])
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return dct
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def operator_norm(obj: qt.Qobj) -> float:
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"""Returns the operator norm of ``obj``."""
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return np.sqrt(max(np.abs((obj.dag() * obj).eigenenergies())))
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