Adding MCMInstrument & InstrumentOp

Adding the MCM-specific newly parameterized instrument to pyGSTi for testing.

jupyter_notebooks/Tutorials/algorithms/advanced/GST-LowLevel.ipynb

@@ -417,7 +417,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.13"
+   "version": "3.11.4"
   }
  },
  "nbformat": 4,

pygsti/modelmembers/instruments/__init__.py

@@ -13,6 +13,8 @@
 from .instrument import Instrument
 from .tpinstrument import TPInstrument
 from .tpinstrumentop import TPInstrumentOp
+from .mcminstrument import MCMInstrument
+from .mcminstrumentop import MCMInstrumentOp
 from .embeddedinst import EmbeddedInst
 from .paritycheckinst import ParityCheckInst
 

pygsti/modelmembers/instruments/mcminstrument.py

@@ -0,0 +1,235 @@
+"""
+Defines the MCMInstrument class
+"""
+#***************************************************************************************************
+# Copyright 2015, 2019 National Technology & Engineering Solutions of Sandia, LLC (NTESS).
+# Under the terms of Contract DE-NA0003525 with NTESS, the U.S. Government retains certain rights
+# in this software.
+# Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except
+# in compliance with the License.  You may obtain a copy of the License at
+# http://www.apache.org/licenses/LICENSE-2.0 or in the LICENSE file in the root pyGSTi directory.
+#***************************************************************************************************
+
+import collections as _collections
+import numpy as _np
+from pygsti.modelmembers import modelmember as _mm
+from pygsti.modelmembers.instruments.mcminstrumentop import MCMInstrumentOp as _MCMInstrumentOp
+
+
+from pygsti.modelmembers import operations as _op
+from pygsti.baseobjs import statespace as _statespace
+from pygsti.tools import matrixtools as _mt
+from pygsti.baseobjs.label import Label as _Label
+from pygsti.tools import optools as _ot
+
+class MCMInstrument(_mm.ModelMember, _collections.OrderedDict):
+    """
+    A new class for representing a quantum instrument, the mathematical description 
+    of an intermediate measurement. This class relies on the "auxiliary picture" where 
+    a n-qubit m-outcome intermediate measurement corresponds to a circuit diagram with
+    n plus m auxiliary qubits. 
+
+    Using this picture allows us to extract error generators corresponding to the circuit
+    diagram and lays the ground work for a CPTPLND parameterization. 
+
+    Parameters
+    ----------
+    evotype : Evotype or str, optional
+        The evolution type.  If `None`, the evotype is inferred
+        from the first instrument member.  If `len(member_ops) == 0` in this case,
+        an error is raised.
+
+    state_space : StateSpace, optional
+        The state space for this instrument.  If `None`, the space is inferred
+        from the first instrument member.  If `len(member_ops) == 0` in this case,
+        an error is raised.
+        
+    items : list or dict, optional
+        Initial values.  This should only be used internally in de-serialization.
+        
+    parameterization : string, optional 
+        The parameterization for this instrument, either "CPTPLND" or "GLND" (full TP). 
+    """
+
+    def __init__(self, evotype="default", state_space=None, items=None, parameterization="CPTPLND"):
+        self.parameterization = parameterization
+
+        #Calculate some necessary matrices to define the isometries below 
+        zero = 1/_np.sqrt(2) * _np.array([[1],[0],[0],[1]])
+        one = 1/_np.sqrt(2) * _np.array([[1],[0],[0],[-1]])
+        CNOT = _ot.unitary_to_pauligate(_np.array([[1,0,0,0], [0,1,0,0],[0,0,0,1],[0,0,1,0]]))
+
+        dim = 4
+        self.aux_GATES = CNOT
+
+        #Define the error generator as the all ones string
+        if parameterization == "TP Map":
+            self.noise_map = _op.FullTPOp(_np.identity(16), basis='pp')
+        else: 
+            error_gen = _op.LindbladErrorgen.from_error_generator(_np.zeros((dim*4,dim*4)), parameterization=self.parameterization) 
+            self.noise_map = _op.ExpErrorgenOp(error_gen)
+
+        if state_space is None: 
+            state_space = _statespace.default_space_for_dim(dim)
+
+        #Define the isometries that convert from auxiliary to standard picture 
+        self.left_isometry = [_np.kron(_np.identity(dim), zero.T), _np.kron(_np.identity(dim),  one.T)]
+        self.right_isometry = self.aux_GATES @ _np.kron(_np.identity(dim), zero)
+
+        #Create the ordered dictionary structure characteristic of instruments 
+        items = []
+        for i in range(2): 
+            items.append([f'p{i}', _MCMInstrumentOp(self.noise_map, i, self.right_isometry, self.left_isometry, 'pp')])
+
+        #some necessary initialization 
+        _collections.OrderedDict.__init__(self, items)
+        _mm.ModelMember.__init__(self, state_space, evotype)
+        self.init_gpindices()
+        self._paramlbls = self.noise_map._paramlbls
+
+    def to_vector(self): 
+        """
+        Gives the underlying vector of parameters. 
+
+        Returns
+        -------
+        numpy array
+            a 1D numpy array with length == num_params().
+        """
+        return self.noise_map.to_vector()
+
+    def from_vector(self, v, close=False, dirty_value=True):
+        """
+        Initialize the Instrument using a vector of its parameters.
+
+        Parameters
+        ----------
+        v : numpy array
+            The 1D vector of gate parameters.  Length
+            must == num_params().
+
+        close : bool, optional
+            Whether `v` is close to this Instrument's current
+            set of parameters.  Under some circumstances, when this
+            is true this call can be completed more quickly.
+
+        dirty_value : bool, optional
+            The value to set this object's "dirty flag" to before exiting this
+            call.  This is passed as an argument so it can be updated *recursively*.
+            Leave this set to `True` unless you know what you're doing.
+
+        Returns
+        -------
+        None
+        """
+        self.noise_map.from_vector(v)
+        for i in range(2): 
+            self[f'p{i}'] =  _MCMInstrumentOp(self.noise_map, i, self.right_isometry, self.left_isometry, 'pp')
+        self.dirty = dirty_value 
+
+    def submembers(self):
+        """
+        Get the ModelMember-derived objects contained in this one.
+
+        Returns
+        -------
+        list
+        """
+        return list(self.values())
+
+    @property
+    def num_params(self):
+        """
+        Get the number of independent parameters which specify this Instrument.
+
+        Returns
+        -------
+        int
+            the number of independent parameters.
+        """
+        return self.noise_map.num_params
+
+    def simplify_operations(self, prefix=""):
+        """
+        Creates a dictionary of simplified instrument operations.
+
+        Returns a dictionary of operations that belong to the Instrument's parent
+        `Model` - that is, whose `gpindices` are set to all or a subset of
+        this instruments's gpindices.  These are used internally within
+        computations involving the parent `Model`.
+
+        Parameters
+        ----------
+        prefix : str
+            A string, usually identitying this instrument, which may be used
+            to prefix the simplified gate keys.
+
+        Returns
+        -------
+        OrderedDict of Gates
+        """
+        #Create a "simplified" (Model-referencing) set of element gates
+        simplified = _collections.OrderedDict()
+        if isinstance(prefix, _Label):  # Deal with case when prefix isn't just a string
+            for k, g in self.items():
+                simplified[_Label(prefix.name + "_" + k, prefix.sslbls)] = g
+        else:
+            if prefix: prefix += "_"
+            for k, g in self.items():
+                simplified[prefix + k] = g
+        return simplified
+
+    @property
+    def parameter_labels(self): 
+        """
+        Get the labels of the independent parameters which specify this instrument. 
+    
+        Returns
+        -------
+        array
+            array of parameter labels 
+        """
+        return self.noise_map.parameter_labels
+
+    @property
+    def num_elements(self):
+        """
+        Return the number of total gate elements in this instrument.
+
+        This is in general different from the number of *parameters*,
+        which are the number of free variables used to generate all of
+        the matrix *elements*.
+
+        Returns
+        -------
+        int
+        """
+        return sum([g.size for g in self.values()])
+
+    def transform_inplace(self,s): 
+        """
+        Update each Instrument element matrix `O` with `inv(s) * O * s`
+        and update the error generator/noise map appropriately.  
+
+        Parameters
+        ----------
+        s : GaugeGroupElement
+            A gauge group element which specifies the "s" matrix
+            (and it's inverse) used in the above similarity transform.
+
+        Returns
+        -------
+        None
+        """
+        Smx = s.transform_matrix
+        Si = s.transform_matrix_inverse
+        self.noise_map = _op.FullTPOp(_np.kron(Si, _np.eye(4)) @ self.noise_map.to_dense() @ self.aux_GATES @ _np.kron(Smx, _np.eye(4))  @ self.aux_GATES)
+        for i in range(2): 
+            self[f'p{i}'] = _MCMInstrumentOp(self.noise_map, i, self.right_isometry, self.left_isometry, 'pp')
+        self.dirty = True
+
+    def __str__(self):
+            s = f'MCMInstrument representing a MCM with elements:\n'
+            for lbl, element in self.items():
+                s += "%s:\n%s\n" % (lbl, _mt.mx_to_string(element.to_dense(), width=4, prec=3))
+            return s