{-# LANGUAGE FlexibleInstances #-} {-# LANGUAGE MultiParamTypeClasses #-} {-# LANGUAGE FunctionalDependencies #-} {-# LANGUAGE UndecidableInstances #-} {-# LANGUAGE TypeSynonymInstances #-} {-# LANGUAGE ScopedTypeVariables #-} {-# LANGUAGE FlexibleContexts #-} {-# LANGUAGE TypeFamilies #-} {-# LANGUAGE Rank2Types #-} -- | This module provides functions for simulating circuits, -- for testing and debugging purposes. -- It borrows ideas from the implementation of the Quantum IO Monad. -- -- This module provides the internal implementation of the library, -- and can be imported by other libraries. The public interface to -- simulation is "Quipper.Libraries.Simulation". module Quipper.Libraries.Simulation.QuantumSimulation where import Quipper import Quipper.Internal -- The following is a bunch of stuff we need to import because, -- temporarily, QuantumSimulation.hs uses low-level interfaces. It -- should be re-implemented using only high-level interfaces, or in -- some cases, more stuff should be exported from Quipper.hs. import Quipper.Internal.Circuit import Quipper.Internal.Transformer import Quipper.Internal.Monad (qubit_of_wire) import Quipper.Internal.Generic (encapsulate_dynamic, qc_unbind) import Quipper.Utils.Auxiliary -- we use the state monad to hold our \"quantum\" state import Control.Monad.State -- we use complex numbers as our probability amplitudes import Quantum.Synthesis.Ring (Cplx (..), i) -- we use a random number generator to simulate \"quantum randomness\" import System.Random hiding (split) -- we store \"basis\" states as a map, import Data.Map (Map) import qualified Data.Map as Map import Data.List (partition) import Control.Applicative (Applicative(..)) import Control.Monad (liftM, ap) import qualified Debug.Trace -- used in tracing the simulation of quipper computations -- | We define our own trace function that only calls trace if the boolean -- argument is true. trace :: Bool -> String -> a -> a trace False _ a = a trace True message a = Debug.Trace.trace message a -- ====================================================================== -- * Simulation as a Transformer -- $ The quantum simulator takes a Quipper circuit producing function, -- and uses a transformer to simulate the resulting circuit, one gate at a time. -- This allows the simulation to progress in a lazy manner, allowing dynamic -- lifting results to be passed back to the circuit producing function as -- and when they are required (to generate further gates in the circuit). -- $ The implementation of the quantum simulator makes use of a /State/ monad -- to carry an underlying quantum state throughout the computation. This /State/ -- is updated by each quantum operation within the circuit. A quantum -- state is a vector of basis states, along with complex amplitudes. -- | Gates that act on a single qubit can be defined by essentially a 2-by-2 matrix. -- A GateR is written by rows, such that a matrix: -- -- \[image GateR.png] -- -- would be written as (m00,m01,m10,m11). type GateR r = (Cplx r,Cplx r, Cplx r, Cplx r) -- | Scalar multiplication of a 2-by-2 matrix by a given scalar. scale :: (Floating r) => Cplx r -> GateR r -> GateR r scale e (a,b,c,d) = (e*a,e*b,e*c,e*d) -- | The inverse of a 'GateR' is its conjugate transpose. reverseR :: (Floating r) => GateR r -> GateR r reverseR (m00,m01,m10,m11) = (conjugate m00, conjugate m10, conjugate m01, conjugate m11) where conjugate (Cplx a b) = Cplx a (-b) -- | A simple pattern matching function that gives each \"gate name\" -- a /GateR/ representation. Adding (single qubit) quantum gates to -- this function will give them an implementation in the -- simulator. Any single qubit named quantum gate that needs to be -- simulated must have a clause in this function, along with a given -- /GateR/ that is its matrix representation. Note that unitarity is -- not enforced, so defined gates must be checked manually to be -- unitary operators. -- -- > Example Gates: -- > gateQ "x" = (0,1,1,0) -- > gateQ "hadamard" = (h, h, h,-h) where h = (1/sqrt 2) gateQ :: (Floating r) => String -> GateR r gateQ "x" = (0,1,1,0) gateQ "hadamard" = (h, h, h,-h) where h = Cplx (1/sqrt 2) 0 gateQ "X" = (0,1,1,0) gateQ "Y" = (0,-i,i,0) gateQ "Z" = (1,0,0,-1) gateQ "S" = (1,0,0,i) gateQ "E" = ((-1+i)/2, (1+i)/2, (-1+i)/2, (-1-i)/2) gateQ "YY" = (h,i*h,i*h,h) where h = Cplx (1/sqrt 2) 0 gateQ "T" = (1,0,0,omega) where omega = (Cplx (1 / sqrt 2) (1 / sqrt 2)) gateQ "V" = scale 0.5 (a,b,b,a) where a = Cplx 1 (-1) b = Cplx 1 1 gateQ "omega" = (omega,0,0,omega) where omega = (Cplx (1 / sqrt 2) (1 / sqrt 2)) gateQ "iX" = (0,i,i,0) gateQ name = error ("quantum gate: " ++ name ++ " not implemented") -- | Like 'gateQ', but also conditionally invert the gate depending -- on InverseFlag. gateQinv :: (Floating r) => String -> InverseFlag -> GateR r gateQinv name False = gateQ name gateQinv name True = reverseR (gateQ name) -- | The exponential function for 'Cplx' numbers. expC :: (Floating r) => Cplx r -> Cplx r expC (Cplx a b) = Cplx (exp a * cos b) (exp a * sin b) -- | The constant π, as a complex number. piC :: (Floating r) => Cplx r piC = Cplx pi 0 -- | Like 'gateQ', but takes the name of a rotation and a real parameter. rotQ :: (Floating r) => String -> Timestep -> GateR r rotQ "exp(-i%Z)" theta = expZtR t where t = fromRational (toRational theta) rotQ "exp(% pi i)" theta = gPhase t where t = fromRational (toRational theta) rotQ "R(2pi/%)" theta = (1,0,0,expC (2*piC*i/t)) where t = fromRational (toRational theta) rotQ "T(%)" theta = (1,0,0,expC (-i*t)) where t = fromRational (toRational theta) rotQ "G(%)" theta = (expC (-i*t),0,0,expC (-i*t)) where t = fromRational (toRational theta) rotQ "Rz(%)" theta = (expC (-i*t/2),0,0,expC (i*t/2)) where t = fromRational (toRational theta) rotQ name theta = error ("quantum rotation: " ++ name ++ " not implemented") -- | Like 'rotQ', but also conditionally invert the gate depending on -- InverseFlag. rotQinv :: (Floating r) => String -> InverseFlag -> Timestep -> GateR r rotQinv name False theta = rotQ name theta rotQinv name True theta = reverseR (rotQ name theta) -- | Return the matrix for the 'expZt' gate. expZtR :: (Floating r) => r -> GateR r expZtR t = (expC (Cplx 0 (-t)),0,0,expC (Cplx 0 t)) -- | Return the matrix for the 'GPhase' gate. gPhase :: (Floating r) => r -> GateR r gPhase t = (expC (Cplx 0 (t * pi)),0,0,expC (Cplx 0 (t * pi))) -- | Translate a classical gate name into a boolean function. -- Adding classical gates to this function will give them an implementation in -- the simulator. -- -- > Example Gate: -- > gateC "if" [a,b,c] = if a then b else c gateC :: String -> ([Bool] -> Bool) gateC "if" [a,b,c] = if a then b else c gateC name inputs = error ("classical gate: " ++ name ++ ", not implemented (at least for inputs: " ++ show inputs ++ " )") -- | The type of vectors with scalars in /n/ over the basis /a/. A -- vector is simply a list of pairs. data Vector n a = Vector [(a,n)] -- | An amplitude distribution gives each classical basis state an amplitude. type Amplitudes r = Vector (Cplx r) (Map Qubit Bool) -- | A probability distribution gives each element a probability. type ProbabilityDistribution r a = Vector r a -- | A QuantumTrace is essentially a probability distribution for the current state -- of the qubits that have been traced. We can represent this using a Vector. The -- list of Booleans is in the same order as the list of Qubits that was being -- traced. type QuantumTrace r = ProbabilityDistribution r [Bool] -- | Normalizing is used to make sure the probabilities add up to 1. normalize :: (Floating r) => QuantumTrace r -> QuantumTrace r normalize (Vector xs) = Vector xs' where p' = Prelude.foldr (\(_,p) accum -> accum + p) 0.0 xs xs' = map (\(bs,p) -> (bs,p / p')) xs -- | A 'QuantumState' is the data structure containing the state that we update -- throughout the simulation. We need to keep track of the next available wire, -- and a quantum state in the form of a distribution of basis states. We also -- track a list of quantum traces, so that we have a \"tracing\" mechanism during -- the execution of quantum circuits. data QuantumState r = QState { next_wire :: Wire, quantum_state :: Amplitudes r, traces :: [QuantumTrace r], -- this will be stored in the reverse order in which -- the traces occured in the circuit. namespace :: Namespace, -- we need a namespace to keep track of subroutines trace_flag :: Bool -- whether or not we trace comments during the simulation } -- | When we start a simulation, we need an empty starting state. empty_quantum_state :: (Floating r) => Bool -> r -> QuantumState r empty_quantum_state tf _ = QState { next_wire = 0, quantum_state = Vector [(Map.empty,1)], traces = [], namespace = namespace_empty, trace_flag = tf} -- | It doesn't make sense having a quantum control on a classical gate, so -- we can throw an error if that is the case, and just collect the boolean -- result otherwise. classical_control :: Signed (B_Endpoint Qubit Bool) -> Bool classical_control (Signed bep val) = case bep of (Endpoint_Bit val') -> val == val' (Endpoint_Qubit _) -> error "CNot: Quantum Control on Classical Gate" -- | Map the 'classical_control' function to all the controls, and take the -- 'and' of the result classical_controls :: Ctrls Qubit Bool -> Bool classical_controls cs = and (map classical_control cs) -- | When we want a quantum control, we will be working with one \"basis state\" at -- a time, and can look up the qubit's value in that basis state to see whether -- the control firs. qc_control :: Map Qubit Bool -> Signed (B_Endpoint Qubit Bool) -> Bool qc_control mqb (Signed bep val) = case bep of (Endpoint_Bit val') -> val == val' (Endpoint_Qubit q) -> val == val' where val' = mqb Map.! q -- | Map the 'qc_control' function to all the controls (under the given basis -- state), and take the 'and' of the result. qc_controls :: Map Qubit Bool -> Ctrls Qubit Bool -> Bool qc_controls mqb cs = and (map (qc_control mqb) cs) -- | We can calculate the magnitude of a complex number magnitude :: (Floating r) => Cplx r -> r magnitude (Cplx a b) = sqrt (a^2 + b^2) -- | The 'split' function splits a Amplitude distribution, by -- partitioning it around the state of the given qubit within each basis state. It -- also returns the probability of the qubit being True within the given -- Amplitudes. This function is used when we want to measure a qubit. split :: (Floating r, Eq r, Ord r) => Amplitudes r -> Qubit -> (r,Amplitudes r,Amplitudes r) split (Vector pas) q = if p < 0 || p > 1 then error "p < 0 or > 1" else (p,Vector ift,Vector iff) where amp x = foldr (\(_,pa) p -> p + ((magnitude pa)*(magnitude pa))) 0 x apas = amp pas (ift,iff) = partition (\(mqb,_) -> (mqb Map.! q)) pas p = if apas == 0 then 0 else (amp ift)/apas -- | A PMonad is a Monad enriched with a 'merge' function that takes a probability, -- and two results, and returns a merged version of these results under the given -- monad. This idea is taken directly from QIO. class (Floating r, Monad m) => PMonad r m where merge :: r -> a -> a -> m a -- | We can merge two measurement outcomes, and explicitly keep the first outcome -- as the True result, and the second as the False result. merge_with_result :: PMonad r m => r -> a -> a -> m (Bool,a) merge_with_result p ift iff = merge p (True,ift) (False,iff) -- | IO forms a PMonad, where results are merged by choosing one probabilistically -- using a random number. instance (Floating r, Random r, Ord r) => PMonad r IO where merge p ift iff = do pp <- randomRIO (0,1) let res = if p > pp then ift else iff return res -- | A State Monad holding a 'RandomGen' forms a 'PMonad', where results are -- merged by choosing one probabilistically using a random number from the -- 'RandomGen'. instance (Floating r, Random r, Ord r, RandomGen g) => PMonad r (State g) where merge p ift iff = do gen <- get let (pp,gen') = randomR (0,1) gen put gen' let res = if p > pp then ift else iff return res -- | Any numeric indexed vector forms a 'Monad'. instance (Num n) => Monad (Vector n) where return a = Vector [(a,1)] (Vector ps) >>= f = Vector [(b,i*j) | (a,i) <- ps, (b,j) <- removeVector (f a)] where removeVector (Vector as) = as instance (Num n) => Applicative (Vector n) where pure = return (<*>) = ap instance (Num n) => Functor (Vector n) where fmap = liftM -- | We can show certain vectors, ignoring any 0 probabilities, and -- combining equal terms. instance (Show a,Eq a,Num n,Eq n,Show n) => Show (Vector n a) where show (Vector ps) = show (combine (filter (\ (a,p) -> p /= 0) ps) []) where combine [] as = as combine (x:xs) as = combine xs (combine' x as) combine' (a,p) [] = [(a,p)] combine' (a,p) ((a',p'):xs) = if a == a' then (a,p+p'):xs else (a',p'):(combine' (a,p) xs) -- | 'ProbabilityDistribution' forms a 'PMonad' such that probabilistic results are -- \"merged\" by extending the probability distribution by the possible results. instance (Floating r, Eq r) => PMonad r (Vector r) where merge 1 ift iff = Vector [(ift,1)] merge 0 ift iff = Vector [(iff,1)] merge p ift iff = Vector [(ift,p),(iff,1-p)] -- | The 'get_trace' function returns a probability distribution of -- the state of a list of qubits within a given amplitude -- distribution. get_trace :: (Floating r) => [Qubit] -> Amplitudes r -> QuantumTrace r get_trace qs (Vector amps) = Vector ps where ps = map (tracing qs) amps tracing qs (mqb,cd) = (map (\q -> mqb Map.! q) qs,(magnitude cd)*(magnitude cd)) -- | Add an amplitude to an amplitude distribution, combining (adding) the amplitudes for equal states in the distribution. add :: (Floating r) => ((Map Qubit Bool),Cplx r) -> Amplitudes r -> Amplitudes r add (a,x) (Vector axs) = Vector (add' axs) where add' [] = [(a,x)] add' ((by @ (b,y)):bys) | a == b = (b,x+y):bys | otherwise = by:(add' bys) -- | The apply' function is used to apply a function on \"basis states\" to an -- entire amplitude distribution. apply :: (Floating r, Eq r) => (Map Qubit Bool -> Amplitudes r) -> Amplitudes r -> Amplitudes r apply f (Vector []) = Vector [] apply f (Vector ((a,0):[])) = Vector [] apply f (Vector ((a,x):[])) = Vector (map (\(b,k) -> (b,x*k)) (fa)) where Vector fa = f a apply f (Vector ((a,0):vas)) = apply f (Vector vas) apply f (Vector ((a,x):vas)) = foldr add (apply f (Vector vas)) (map (\(b,k) -> (b,x*k)) (fa)) where Vector fa = f a -- | Lift a function that returns a single basis state, to a function that -- returns an amplitude distribution (containing a singleton). vector :: (Floating r) => (Map Qubit Bool -> Map Qubit Bool) -> Map Qubit Bool -> Amplitudes r vector f a = Vector [(f a,1)] -- | apply the given function only if the controls fire. if_controls :: (Floating r) => Ctrls Qubit Bool -> (Map Qubit Bool -> Amplitudes r) -> Map Qubit Bool -> Amplitudes r if_controls c f mqb = if (qc_controls mqb c) then f mqb else Vector [(mqb,1)] -- | 'performGateQ' defines how a single qubit gate is applied to a -- quantum state. The application of a /GateR/ to a qubit in a single -- basis state can split the state into a pair of basis states with -- corresponding amplitudes. performGateQ :: (Floating r) => GateR r -> Qubit -> Map Qubit Bool -> Amplitudes r performGateQ (m00,m01,m10,m11) q mqb = if (mqb Map.! q) then (Vector [(Map.insert q False mqb,m01),(mqb,m11)]) else (Vector [(mqb,m00),(Map.insert q True mqb,m10)]) -- | The 'simulation_transformer' is the actual transformer that does the -- simulation. The type of the 'simulation_transformer' shows that Qubits are -- kept as qubits, but Bits are turned into Boolean values, i.e., the results of -- the computation. We use a StateT Monad, acting over the IO Monad, to store a -- QuantumState throughout the simulation. This means we carry a state, but also -- have access to the IO Monad's random number generator (for probabilistic -- measurement). simulation_transformer :: (PMonad r m, Ord r) => Transformer (StateT (QuantumState r) m) Qubit Bool -- Translation of classical gates: simulation_transformer (T_CNot ncf f) = f $ \val c -> do let ctrl = classical_controls c let val' = if ctrl then not val else val return (val',c) simulation_transformer (T_CInit val ncf f) = f $ return val simulation_transformer (T_CTerm b ncf f) = f $ \val -> if val == b then return () else error "CTerm: Assertion Incorrect" simulation_transformer (T_CDiscard f) = f $ \val -> return () simulation_transformer (T_DTerm b f) = f $ \val -> return () simulation_transformer (T_CGate name ncf f) = f $ \list -> do let result = gateC name list return (result,list) simulation_transformer g@(T_CGateInv name ncf f) = f $ \result list -> do let result' = gateC name list if result == result' then return list else error "CGateInv: Uncomputation error" -- Translation of quantum gates: simulation_transformer (T_QGate "not" 1 0 _ ncf f) = f $ \[q] [] cs -> do let gate = gateQ "x" state <- get let amps = quantum_state state let amps' = apply (if_controls cs (performGateQ gate q)) amps put (state {quantum_state = amps'}) return ([q], [], cs) simulation_transformer (T_QGate "multinot" _ 0 _ ncf f) = f $ \qs [] cs -> do let gate = gateQ "x" state <- get let amps = quantum_state state let amps' = foldr (\q a -> apply (if_controls cs (performGateQ gate q)) a) amps qs put (state {quantum_state = amps'}) return (qs, [], cs) simulation_transformer (T_QGate "H" 1 0 _ ncf f) = f $ \[q] [] cs -> do let gate = gateQ "hadamard" state <- get let amps = quantum_state state let amps' = apply (if_controls cs (performGateQ gate q)) amps put (state {quantum_state = amps'}) return ([q], [], cs) simulation_transformer (T_QGate "swap" 2 0 _ ncf f) = f $ \[w, v] [] cs -> do let gate = gateQ "x" state <- get let amps = quantum_state state let amps' = apply (if_controls ((Signed (Endpoint_Qubit w) True):cs) (performGateQ gate v)) amps let amps'' = apply (if_controls ((Signed (Endpoint_Qubit v) True):cs) (performGateQ gate w)) amps' let amps''' = apply (if_controls ((Signed (Endpoint_Qubit w) True):cs) (performGateQ gate v)) amps'' put (state {quantum_state = amps'''}) return ([w, v], [], cs) simulation_transformer (T_QGate "W" 2 0 _ ncf f) = f $ \[w, v] [] cs -> do let gateX = gateQ "x" let gateH = gateQ "hadamard" state <- get let amps = quantum_state state let amps' = apply (if_controls ((Signed (Endpoint_Qubit w) True):cs) (performGateQ gateX v)) amps let amps'' = apply (if_controls ((Signed (Endpoint_Qubit v) True):cs) (performGateQ gateH w)) amps' let amps''' = apply (if_controls ((Signed (Endpoint_Qubit w) True):cs) (performGateQ gateX v)) amps'' put (state {quantum_state = amps'''}) return ([w, v], [], cs) simulation_transformer (T_QGate "trace" _ _ False ncf f) = f $ \qs gc c -> do -- a \"trace\" gate adds the current probability distribution for the given qubits -- to the list of previous quantum traces state <- get let current_traces = traces state let amps = quantum_state state let new_trace = get_trace qs amps put (state {traces = new_trace:current_traces}) return (qs,gc,c) simulation_transformer (T_QGate "trace" _ _ True ncf f) = f $ \qs gc c -> return (qs,gc,c) -- we don't do anything for the inverse \"trace\" gate simulation_transformer (T_QGate name 1 0 inv ncf f) = f $ \[q] [] c -> do let gate = gateQinv name inv state <- get let amps = quantum_state state let amps' = apply (if_controls c (performGateQ gate q)) amps put (state {quantum_state = amps'}) return ([q],[],c) simulation_transformer (T_QRot name 1 0 inv theta ncf f) = f $ \[q] [] c -> do let gate = rotQinv name inv theta state <- get let amps = quantum_state state let amps' = apply (if_controls c (performGateQ gate q)) amps put (state {quantum_state = amps'}) return ([q],[],c) simulation_transformer (T_GPhase t ncf f) = f $ \w c -> do state <- get let gate = rotQ "exp(% pi i)" t let wire = next_wire state let q = qubit_of_wire wire let amps = quantum_state state let amps' = apply (vector (Map.insert q False)) amps let amps'' = apply (if_controls c (performGateQ gate q)) amps' let (p,ift,iff) = split amps'' q (val,ampsf) <- lift $ merge_with_result p ift iff case val of False -> do let ampsf' = apply (vector (Map.delete q)) ampsf put (state {quantum_state = ampsf'}) return c _ -> error "GPhase" simulation_transformer (T_QInit val ncf f) = f $ do state <- get let wire = next_wire state let q = qubit_of_wire wire let wire' = wire + 1 let amps = quantum_state state let amps' = apply (vector (Map.insert q val)) amps put (state {quantum_state = amps', next_wire = wire'}) return q simulation_transformer (T_QMeas f) = f $ \q -> do state <- get let amps = quantum_state state let (p,ift,iff) = split amps q (val,amps') <- lift $ merge_with_result p ift iff let amps'' = apply (vector (Map.delete q)) amps' put (state {quantum_state = amps''}) return val simulation_transformer (T_QDiscard f) = f $ \q -> do -- a discard is essentially a measurement, with the result thrown away, so we -- do that here, as it will reduce the size of the quantum state we are -- simulating over. state <- get let (p,ift,iff) = split (quantum_state state) q (_,amps) <- lift $ merge_with_result p ift iff let amps' = apply (vector (Map.delete q)) amps put (state {quantum_state = amps'}) return () simulation_transformer (T_QTerm b ncf f) = f $ \q -> do -- with a real quantum computer, when we terminate a qubit with an -- assertion we have no way of actually checking the assertion. The -- best we can do is measure the qubit and then throw an error if -- the assertion is incorrect, which may only occur with a small -- probability. Here, we could split the quantum state and see if -- the qubit exists in the incorrect state with any non-zero -- probability, and throw an error. However, we don't do this -- because an error would sometimes be thrown due to rounding. state <- get let amps = quantum_state state let (p,ift,iff) = split amps q (val,amps') <- lift $ merge_with_result p ift iff if val == b then put (state {quantum_state = amps'}) else error "QTerm: Assertion doesn't hold" simulation_transformer (T_Comment "" inv f) = f $ \_ -> return () -- e.g. a comment can be (the) empty (string) if it only contains labels simulation_transformer (T_Comment name inv f) = f $ \_ -> do state <- get -- we don't need to do anything with a comment, but they can be useful -- to know where we are in the circuit, so we shall output a trace of -- the (non-empty) comments during a simulation. trace (trace_flag state) name $ return () -- The remaining gates are not yet implemented: simulation_transformer g@(T_QGate _ _ _ _ _ _) = error ("simulation_transformer: unimplemented gate: " ++ show g) simulation_transformer g@(T_QRot _ _ _ _ _ _ _) = error ("simulation_transformer: unimplemented gate: " ++ show g) simulation_transformer g@(T_CSwap _ _) = error ("simulation_transformer: unimplemented gate: " ++ show g) simulation_transformer g@(T_QPrep ncf f) = f $ \val -> do state <- get let wire = next_wire state let q = qubit_of_wire wire let wire' = wire + 1 let amps = quantum_state state let amps' = apply (vector (Map.insert q val)) amps put (state {quantum_state = amps', next_wire = wire'}) return q simulation_transformer g@(T_QUnprep ncf f) = f $ \q -> do state <- get let amps = quantum_state state let (p,ift,iff) = split amps q (val,amps') <- lift $ merge_with_result p ift iff put (state {quantum_state = amps'}) return val simulation_transformer g@(T_Subroutine sub inv ncf scf ws_pat a1_pat vs_pat a2_pat rep f) = f $ \ns in_values c -> do case Map.lookup sub ns of Just (TypedSubroutine sub_ocirc _ _ _) -> do let OCircuit (in_wires, sub_circ, out_wires) = if inv then reverse_ocircuit sub_ocirc else sub_ocirc let in_bindings = bind_list in_wires in_values bindings_empty let sub_bcirc = (sub_circ,ns) out_bind <- transform_bcircuit_rec simulation_transformer sub_bcirc in_bindings return (unbind_list out_bind out_wires, c) Nothing -> error $ "simulation_transformer: subroutine " ++ show sub ++ " not found (in " ++ showNames ns ++ ")" -- | The simulation_transformer is also Dynamic, as the simulated wire states -- can simply be used to perform dynamic liftings. simulation_dynamic_transformer :: (PMonad r m, Ord r) => DynamicTransformer (StateT (QuantumState r) m) Qubit Bool simulation_dynamic_transformer = DT { transformer = simulation_transformer, define_subroutine = \name subroutine -> return (), lifting_function = return } -- | Apply the 'simulation_dynamic_transformer' to a (unary) circuit -- generating function. simulate_transform_unary :: (PMonad r m, Ord r) => (QCData qa, QCData qb, QCData (QCType Bit Bit qb), QCType Bool Bool qb ~ QCType Bool Bool (QCType Bit Bit qb)) => (qa -> Circ qb) -> BType qa -> StateT (QuantumState r) m (QCType Qubit Bool (QCType Bit Bit qb)) simulate_transform_unary (f :: qa -> Circ qb) input = do let ((), circuit) = encapsulate_dynamic (\() -> qc_init input >>= \qi -> f qi >>= \qi' -> qc_measure qi') () (cb,out_bind) <- transform_dbcircuit simulation_dynamic_transformer circuit bindings_empty let output = qc_unbind out_bind cb return output -- | In order to simulate a circuit using an input basis vector, we need to supply -- each quantum leaf, with a concrete (i.e., not a dummy) qubit. qdata_concrete_shape :: (QData qa) => BType qa -> qa qdata_concrete_shape ba = evalState mqa 0 where shape = shapetype_b ba mqa = qdata_mapM shape f ba f :: Bool -> State Wire Qubit f _ = do w <- get put (w+1) return (qubit_of_wire w) -- | In order to simulate a circuit using an input basis vector, we need to supply -- the transformer with a concrete set of qubit bindings. qdata_concrete_bindings :: (QData qa) => BType qa -> Bindings Qubit Bool qdata_concrete_bindings ba = snd $ execState mqa (0,bindings_empty) where shape = shapetype_b ba mqa = qdata_mapM shape f ba f :: Bool -> State (Wire,Bindings Qubit Bool) () f b = do (w,bindings) <- get put (w+1,bind_qubit_wire w (qubit_of_wire w) bindings) return () -- | As a helper function, in order to simulate a circuit using an input basis vector, -- we need to be able to convert each basis into a map from concrete qubits to their -- value in the given basis. qdata_to_basis :: (QData qa) => BType qa -> Map Qubit Bool qdata_to_basis ba = snd $ execState mqa (0,Map.empty) where shape = shapetype_b ba mqa = qdata_mapM shape f ba f :: Bool -> State (Wire,Map Qubit Bool) () f b = do (w,m) <- get put (w+1,Map.insert (qubit_of_wire w) b m) return () -- | In order to simulate a circuit using an input basis vector, we need to be able -- to convert the basis vector into a quantum state suitable for use by the simulator -- i.e. of type Amplitudes. qdata_vector_to_amplitudes :: (QData qa, Floating r) => Vector (Cplx r) (BType qa) -> Amplitudes r qdata_vector_to_amplitudes (Vector das) = (Vector (map (\(a,d) -> (qdata_to_basis a,d)) das)) -- | As a helper function, in order to simulate a circuit using an input basis vector, -- we need to be able to convert a map from concrete qubits to their value into a basis -- of the given concrete shape. basis_to_qdata :: (QData qa) => qa -> Map Qubit Bool -> BType qa basis_to_qdata qa m = getId $ qdata_mapM qa f qa where f :: Qubit -> Id Bool f q = case Map.lookup q m of Just res -> return res _ -> error "basis_to_qdata: qubit not in scope" -- | In order to simulate a circuit using an input basis vector, we need to be able -- to convert the quantum state (i.e. of type Amplitudes) into a basis vector. amplitudes_to_qdata_vector :: (QData qa, Floating r) => qa -> Amplitudes r -> Vector (Cplx r) (BType qa) amplitudes_to_qdata_vector qa (Vector das) = Vector (map (\(a,d) -> (basis_to_qdata qa a,d)) das) -- | Apply the 'simulation_dynamic_transformer' to a (unary) circuit generating -- function, starting with the quantum state set to the given vector of base states -- and returning the resulting vector of base states. simulate_amplitudes_unary :: (PMonad r m, Eq r, Ord r, QData qa, QData qb, qb ~ QCType Qubit Bool qb) => (qa -> Circ qb) -> Vector (Cplx r) (BType qa) -> m (Vector (Cplx r) (BType qb)) simulate_amplitudes_unary f input@(Vector is) = do (out_shape,state) <- runStateT circ input_state let out_amps = quantum_state state return (amplitudes_to_qdata_vector out_shape (apply (vector id) out_amps)) where amps = qdata_vector_to_amplitudes input specimen = case is of [] -> error "simulate_amplitudes_unary: can't use empty vector" ((b,_):_) -> b shape = qdata_concrete_shape specimen bindings = qdata_concrete_bindings specimen max_wire = case wires_of_bindings bindings of [] -> 0 ws -> maximum ws input_state = (empty_quantum_state False undefined) {quantum_state = amps, next_wire = max_wire + 1} (_,circuit) = encapsulate_dynamic f shape circ = do (cb,out_bind) <- transform_dbcircuit simulation_dynamic_transformer circuit bindings let output = qc_unbind out_bind cb return output -- | Input a source of randomness, a quantum circuit, and an initial -- state (represented as a map from basis vectors to amplitudes). -- Simulate the circuit and return the final state. If the circuit -- includes measurements, the simulation will be probabilistic. -- -- The type of this heavily overloaded function is difficult to -- read. It has, for example, the following types: -- -- > sim_amps :: StdGen -> (Qubit -> Circ Qubit) -> Map Bool (Cplx Double) -> Map Bool (Cplx Double) -- > sim_amps :: StdGen -> ((Qubit,Qubit) -> Circ Qubit) -> Map (Bool,Bool) (Cplx Double) -> Map Bool (Cplx Double) -- -- and so forth. Note that instead of 'Double', another real number -- type, such as 'Data.Number.FixedPrec.FixedPrec' /e/, can be used. sim_amps :: (RandomGen g, Floating r, Random r, Ord r, QData qa, QData qb, qb ~ QCType Qubit Bool qb, Ord (BType qb)) => g -> (qa -> Circ qb) -> Map (BType qa) (Cplx r) -> Map (BType qb) (Cplx r) sim_amps gen f input_map = output_map where input_vec = Vector (Map.toList input_map) circ = simulate_amplitudes_unary f input_vec Vector output = evalState circ gen output_map = Map.fromList output -- | Input a source of randomness, a real number, a circuit, and a -- basis state. Then simulate the circuit probabilistically. Measure -- the final state and return the resulting basis vector. -- -- The real number argument is a dummy and is never evaluated; its -- only purpose is to specify the /type/ of real numbers that will be -- used during the simulation. run_unary :: (Floating r, Random r, Ord r, RandomGen g, QCData qa, QCData qb, QCData (QCType Bit Bit qb), QCType Bool Bool qb ~ QCType Bool Bool (QCType Bit Bit qb)) => g -> r -> (qa -> Circ qb) -> BType qa -> QCType Qubit Bool (QCType Bit Bit qb) run_unary g r f input = evalState comp g where comp = evalStateT f' (empty_quantum_state False r) f' = simulate_transform_unary f input -- | Like 'run_unary', but return the list of 'QuantumTrace' elements -- that were generated during the computation. This is useful for -- checking the intermediary state of qubits within a computation. run_unary_trace :: (Floating r, Random r, Ord r, RandomGen g, QCData qa, QCData qb, QCData (QCType Bit Bit qb), QCType Bool Bool qb ~ QCType Bool Bool (QCType Bit Bit qb)) => g -> r -> (qa -> Circ qb) -> BType qa -> [QuantumTrace r] run_unary_trace g r f input = evalState comp g where comp = do state <- execStateT f' (empty_quantum_state True r) let qts = traces state return (reverse qts) f' = simulate_transform_unary f input -- | Like 'run_unary', but run in the 'IO' monad instead of passing an -- explicit source of randomness. run_unary_io :: (Floating r, Random r, Ord r, QCData qa, QCData qb, QCData (QCType Bit Bit qb), QCType Bool Bool qb ~ QCType Bool Bool (QCType Bit Bit qb)) => r -> (qa -> Circ qb) -> BType qa -> IO (QCType Qubit Bool (QCType Bit Bit qb)) run_unary_io r f input = do g <- newStdGen return (run_unary g r f input) -- | Like 'run_unary_trace', but run in the 'IO' monad instead of -- passing an explicit source of randomness. run_unary_trace_io :: (Floating r, Random r, Ord r, QCData qa, QCData qb, QCData (QCType Bit Bit qb), QCType Bool Bool qb ~ QCType Bool Bool (QCType Bit Bit qb)) => r -> (qa -> Circ qb) -> BType qa -> IO [QuantumTrace r] run_unary_trace_io r f input = do g <- newStdGen return (run_unary_trace g r f input) -- | Apply the 'simulation_transformer' to a (unary) circuit, and then evaluate -- the resulting stateful computation to get a probability distribution of possible -- results sim_unary :: (Floating r, Ord r, QCData qa, QCData qb, QCData (QCType Bit Bit qb), QCType Bool Bool qb ~ QCType Bool Bool (QCType Bit Bit qb)) => r -> (qa -> Circ qb) -> BType qa -> ProbabilityDistribution r (QCType Qubit Bool (QCType Bit Bit qb)) sim_unary r f input = evalStateT f' (empty_quantum_state False r) where f' = simulate_transform_unary f input -- ====================================================================== -- * Generic functions -- ** Generic run function -- $ Generic functions to run Quipper circuits, using 'Random' to -- simulate quantum states. -- | Quantum simulation of a circuit, for testing and debugging -- purposes. Input a source of randomness, a real number, and a -- quantum circuit. Output a corresponding probabilistic boolean -- function. -- -- The inputs to the quantum circuit are initialized according to the -- given boolean arguments. The outputs of the quantum circuit are -- measured, and the boolean measurement outcomes are -- returned. -- -- The real number argument is a dummy and is never evaluated; its -- only purpose is to specify the /type/ of real numbers that will be -- used during the simulation. -- -- The type of this heavily overloaded function is difficult to -- read. In more readable form, it has all of the following types (for -- example): -- -- > run_generic :: (Floating r, Random r, Ord r, RandomGen g, QCData qa) => g -> r -> Circ qa -> BType qa -- > run_generic :: (Floating r, Random r, Ord r, RandomGen g, QCData qa, QCData qb) => g -> r -> (qa -> Circ qb) -> BType qa -> BType qb -- > run_generic :: (Floating r, Random r, Ord r, RandomGen g, QCData qa, QCData qb, QCData qc) => g -> r -> (qa -> qb -> Circ qc) -> BType qa -> BType qb -> BType qc -- -- and so forth. run_generic :: (Floating r, Random r, Ord r, RandomGen g, QCData qa, QCDataPlus qb, QCurry qfun qa qb, Curry qfun' (QCType Bool Bool qa) (QCType Qubit Bool (QCType Bit Bit qb))) => g -> r -> qfun -> qfun' run_generic gen r f = g where f1 = quncurry f g1 = run_unary gen r f1 g = mcurry g1 -- | Like 'run_generic', but also output a trace of the states of the -- given list of qubits at each step during the evaluation. run_generic_trace :: (Floating r, Random r, Ord r, RandomGen g, QCData qa, QCDataPlus qb, QCurry qfun qa qb, Curry qfun' (QCType Bool Bool qa) [QuantumTrace r]) => g -> r -> qfun -> qfun' run_generic_trace gen r f = g where f1 = quncurry f g1 = run_unary_trace gen r f1 g = mcurry g1 -- | Like 'run_generic', but run in the 'IO' monad instead of passing -- an explicit source of randomness. run_generic_io :: (Floating r, Random r, Ord r, QCData qa, QCDataPlus qb, QCurry qfun qa qb, Curry qfun' (QCType Bool Bool qa) (IO (QCType Qubit Bool (QCType Bit Bit qb)))) => r -> qfun -> qfun' run_generic_io r f = g where f1 = quncurry f g1 = run_unary_io r f1 g = mcurry g1 -- | Like 'run_generic_trace', but run in the 'IO' monad instead of -- passing an explicit source of randomness. run_generic_trace_io :: (Floating r, Random r, Ord r, QCData qa, QCDataPlus qb, QCurry qfun qa qb, Curry qfun' (QCType Bool Bool qa) (IO [QuantumTrace r])) => r -> qfun -> qfun' run_generic_trace_io r f = g where f1 = quncurry f g1 = run_unary_trace_io r f1 g = mcurry g1 -- ---------------------------------------------------------------------- -- ** Generic sim function -- $ A generic function to simulate Quipper circuits, returning a -- probability distribution of the possible results. -- | A generic function to simulate Quipper circuits, returning a -- probability distribution of the possible results. -- -- The type of this heavily overloaded function is difficult to -- read. In more readable form, it has all of the following types (for -- example): -- -- > sim_generic :: (Floating r, Ord r, QCData qa) => r -> Circ qa -> ProbabilityDistribution r (BType qa) -- > sim_generic :: (Floating r, Ord r, QCData qa, QCData qb) => r -> (qa -> Circ qb) -> BType qa -> ProbabilityDistribution r (BType qb) -- > sim_generic :: (Floating r, Ord r, QCData qa, QCData qb, QCData qc) => r -> (qa -> qb -> Circ qc) -> BType qa -> BType qb -> ProbabilityDistribution r (BType qc) -- -- and so forth. sim_generic :: (Floating r, Ord r, QCData qa, QCDataPlus qb, QCurry qfun qa qb, Curry qfun' (QCType Bool Bool qa) (ProbabilityDistribution r (QCType Qubit Bool (QCType Bit Bit qb)))) => r -> qfun -> qfun' sim_generic r f = g where f1 = quncurry f g1 = sim_unary r f1 g = mcurry g1