Blocks
Blocks are the basic building blocks of a quantum circuit in Yao. It simply means a quantum operator, thus, all the blocks have matrices in principal and one can get its matrix by mat. The basic blocks required to build an arbitrary quantum circuit is defined in the component package YaoBlocks.
Block Tree serves as an intermediate representation for Yao to analysis, optimize the circuit, then it will be lowered to instructions like for simulations, blocks will be lowered to instruct! calls.
The structure of blocks is the same with a small type system, it consists of two basic kinds of blocks: CompositeBlock (like composite types), and PrimitiveBlock (like primitive types). By combining these two kinds of blocks together, we'll be able to construct a quantum circuit and represent it in a tree data structure.
Primitive Blocks
Primitive blocks are subtypes of PrimitiveBlock, they are the leaf nodes in a block tree, thus primitive types do not have subtypes.
We provide the following primitive blocks:
YaoBlocks.GeneralMatrixBlock — Type.GeneralMatrixBlock{M, N, T, MT} <: PrimitiveBlock{N, T}General matrix gate wraps a matrix operator to quantum gates. This is the most general form of a quantum gate. M is the hilbert dimension (first dimension), N is the hilbert dimension (second dimension) of current quantum state. For most quantum gates, we have $M = N$.
YaoBlocks.Measure — Type.Measure{N, K, OT} <: PrimitiveBlock{N, Bool}
Measure(n::Int; operator=ComputationalBasis(), locs=1:n, collapseto=nothing, remove=false)Measure operator.
YaoBlocks.PhaseGate — Type.PhiGateGlobal phase gate.
YaoBlocks.PrimitiveBlock — Type.PrimitiveBlock{N, T} <: AbstractBlock{N, T}Abstract type that all primitive block will subtype from. A primitive block is a concrete block who can not be decomposed into other blocks. All composite block can be decomposed into several primitive blocks.
subtype for primitive block with parameter should implement hash and == method to enable key value cache.
YaoBlocks.ReflectGate — Type.ReflectGate{N, T, Tr} <: PrimitiveBlock{N, T}Reflection operator to target state psi.
Definition
YaoBlocks.ReflectGate — Method.ReflectGate(r::AbstractVector)Create a ReflectGate with a quantum state vector v.
YaoBlocks.ReflectGate — Method.ReflectGate(r::ArrayReg{1})Create a ReflectGate with a quantum register r.
YaoBlocks.RotationGate — Type.RotationGate{N, T, GT <: AbstractBlock{N, Complex{T}}} <: PrimitiveBlock{N, Complex{T}}RotationGate, with GT both hermitian and isreflexive.
YaoBlocks.ShiftGate — Type.ShiftGate <: PrimitiveBlockPhase shift gate.
YaoBlocks.TimeEvolution — Type.TimeEvolution{N, TT, GT} <: PrimitiveBlock{N, ComplexF64}TimeEvolution, where GT is block type. input matrix should be hermitian.
!!!note:     TimeEvolution contructor check hermicity of the input block by default, but sometimes it can be slow. Turn off the check manually by specifying optional parameter check_hermicity = false.
YaoBlocks.TimeEvolution — Method.TimeEvolution(H, dt[; tol::Real=1e-7])Create a TimeEvolution block with Hamiltonian H and time step dt. The TimeEvolution block will use Krylove based expv to calculate time propagation.
Optional keywords are tolerance tol (default is 1e-7) TimeEvolution block can also be used for imaginary time evolution if dt is complex.
Composite Blocks
Composite blocks are subtypes of CompositeBlock, they are the composition of blocks.
We provide the following composite blocks:
YaoBlocks.AbstractContainer — Type.AbstractContainer{BT, N, T} <: CompositeBlock{N, T}Abstract type for container block. Container blocks are blocks contain a single block. Container block should have a
YaoBlocks.CachedBlock — Type.YaoBlocks.ChainBlock — Type.ChainBlock{N, T} <: CompositeBlock{N, T}ChainBlock is a basic construct tool to create user defined blocks horizontically. It is a Vector like composite type.
YaoBlocks.CompositeBlock — Type.CompositeBlock{N, T} <: AbstractBlock{N, T}Abstract supertype which composite blocks will inherit from. Composite blocks are blocks composited from other AbstractBlocks, thus it is a AbstractBlock as well.
YaoBlocks.Concentrator — Type.Concentrator{N, T, BT <: AbstractBlock} <: AbstractContainer{BT, N, T}concentrates serveral lines together in the circuit, and expose it to other blocks.
YaoBlocks.Daggered — Type.Daggered{N, T, BT} <: TagBlock{N, T}Wrapper block allowing to execute the inverse of a block of quantum circuit.
YaoBlocks.KronBlock — Type.KronBlock{N, T, MT<:AbstractBlock} <: CompositeBlock{N, T}composite block that combine blocks by kronecker product.
YaoBlocks.PauliString — Method.PauliString(list::Vector)Create a PauliString from a list of Pauli gates.
Example
julia> PauliString([X, Y, Z])
nqubits: 3, datatype: Complex{Float64}
PauliString
├─ X gate
├─ Y gate
└─ Z gateYaoBlocks.PauliString — Method.PauliString(xs::PauliGate...)Create a PauliString from some Pauli gates.
Example
julia> PauliString(X, Y, Z)
nqubits: 3, datatype: Complex{Float64}
PauliString
├─ X gate
├─ Y gate
└─ Z gateYaoBlocks.PutBlock — Type.PutBlock <: AbstractContainerType for putting a block at given locations.
YaoBlocks.RepeatedBlock — Type.RepeatedBlock <: AbstractContainerRepeat the same block on given locations.
YaoBlocks.Roller — Type.Roller{N, T, BT <: Tuple} <: CompositeBlock{N, T}Roller block.
YaoBlocks.TagBlock — Type.TagBlock{BT, N, T} <: AbstractContainer{BT, N, T}TagBlock is a special kind of Container block, it forwards most of the methods but tag the block with some extra information.
APIs
Base.kron — Method.kron(n, blocks::Pair{Int, <:AbstractBlock}...)Return a KronBlock, with total number of qubits n and pairs of blocks.
Example
Use kron to construct a KronBlock, it will put an X gate on the 1st qubit, and a Y gate on the 3rd qubit.
julia> kron(4, 1=>X, 3=>Y)
nqubits: 4, datatype: Complex{Float64}
kron
├─ 1=>X gate
└─ 3=>Y gate
Base.kron — Method.kron(blocks::AbstractBlock...)
kron(n, itr)Return a KronBlock, with total number of qubits n, and blocks should use all the locations on n wires in quantum circuits.
Example
You can use kronecker product to composite small blocks to a large blocks.
julia> kron(X, Y, Z, Z)
nqubits: 4, datatype: Complex{Float64}
kron
├─ 1=>X gate
├─ 2=>Y gate
├─ 3=>Z gate
└─ 4=>Z gate
Base.kron — Method.kron(blocks...) -> f(n)
kron(itr) -> f(n)Return a lambda, which will take the total number of qubits as input.
Example
If you don't know the number of qubit yet, or you are just too lazy, it is fine.
julia> kron(put(1=>X) for _ in 1:2)
(n -> kron(n, (n  ->  put(n, 1 => X gate)), (n  ->  put(n, 1 => X gate))))
julia> kron(X for _ in 1:2)
nqubits: 2, datatype: Complex{Float64}
kron
├─ 1=>X gate
└─ 2=>X gate
julia> kron(1=>X, 3=>Y)
(n -> kron(n, 1 => X gate, 3 => Y gate))Base.repeat — Method.repeat(x::AbstractBlock, locs)Lazy curried version of repeat.
Base.repeat — Method.repeat(n, x::AbstractBlock[, locs]) -> RepeatedBlock{n}Create a RepeatedBlock with total number of qubits n and the block to repeat on given location or on all the locations.
Example
This will create a repeat block which puts 4 X gates on each location.
julia> repeat(4, X)
nqubits: 4, datatype: Complex{Float64}
repeat on (1, 2, 3, 4)
└─ X gateYou can also specify the location
julia> repeat(4, X, (1, 2))
nqubits: 4, datatype: Complex{Float64}
repeat on (1, 2)
└─ X gateBut repeat won't copy the gate, thus, if it is a gate with parameter, e.g a phase(0.1), the parameter will change simultaneously.
julia> g = repeat(4, phase(0.1))
nqubits: 4, datatype: Complex{Float64}
repeat on (1, 2, 3, 4)
└─ phase(0.1)
julia> g.content
phase(0.1)
julia> g.content.theta = 0.2
0.2
julia> g
nqubits: 4, datatype: Complex{Float64}
repeat on (1, 2, 3, 4)
└─ phase(0.2)YaoBlocks.Rx — Method.Rx(theta)Return a RotationGate on X axis.
YaoBlocks.Ry — Method.Ry(theta)Return a RotationGate on Y axis.
YaoBlocks.Rz — Method.Rz(theta)Return a RotationGate on Z axis.
YaoBlocks.apply! — Method.apply!(register, block)Apply a block (of quantum circuit) to a quantum register.
YaoBlocks.applymatrix — Method.applymatrix(g::AbstractBlock) -> MatrixTransform the apply! function of specific block to dense matrix.
YaoBlocks.cache_key — Method.cache_key(block)Returns the key that identify the matrix cache of this block. By default, we use the returns of parameters as its key.
YaoBlocks.cache_type — Method.cache_type(::Type) -> DataTypeReturn the element type that a CacheFragment will use.
YaoBlocks.chain — Method.chain([T=ComplexF64], n)Return an empty ChainBlock which can be used like a list of blocks.
YaoBlocks.chain — Method.chain()Return an lambda n->chain(n).
YaoBlocks.chain — Method.chain(blocks...)Return a ChainBlock which chains a list of blocks with same nqubits and datatype. If there is lazy evaluated block in blocks, chain can infer the number of qubits and create an instance itself.
YaoBlocks.chcontent — Method.chcontent(x, blk)Create a similar block of x and change its content to blk.
YaoBlocks.chsubblocks — Method.chsubblocks(composite_block, itr)Change the sub-blocks of a CompositeBlock with given iterator itr.
YaoBlocks.cnot — Method.cnot(n, ctrl_locs, location)Return a speical ControlBlock, aka CNOT gate with number of active qubits n and locs of control qubits ctrl_locs, and location of X gate.
Example
julia> cnot(3, (2, 3), 1)
nqubits: 3, datatype: Complex{Float64}
control(2, 3)
└─ (1,) X gate
julia> cnot(2, 1)
(n -> cnot(n, 2, 1))YaoBlocks.collect_blocks — Method.collect_blocks(block_type, root)Return a ChainBlock with all block of block_type in root.
YaoBlocks.concentrate — Method.concentrate(block, locs) -> f(n)Lazy curried version of concentrate.
YaoBlocks.concentrate — Method.concentrate(n, block, locs)Create a Concentrator block with total number of current active qubits n, which concentrates given wire location together to length(locs) active qubits, and relax the concentration afterwards.
Example
Concentrator is equivalent to put a block on given position mathematically, but more efficient and convenient for large blocks.
julia> r = rand_state(3)
ArrayReg{1, Complex{Float64}, Array...}
    active qubits: 3/3
julia> apply!(copy(r), concentrate(X, 1)) ≈ apply!(copy(r), put(1=>X))
trueIt works for in-contigious locations as well
julia> r = rand_state(4)
ArrayReg{1, Complex{Float64}, Array...}
    active qubits: 4/4
julia> cc = concentrate(4, kron(X, Y), (1, 3))
nqubits: 4, datatype: Complex{Float64}
Concentrator: (1, 3)
└─ kron
   ├─ 1=>X gate
   └─ 2=>Y gate
julia> pp = chain(4, put(1=>X), put(3=>Y))
nqubits: 4, datatype: Complex{Float64}
chain
├─ put on (1)
│  └─ X gate
└─ put on (3)
   └─ Y gate
julia> apply!(copy(r), cc) ≈ apply!(copy(r), pp)
trueYaoBlocks.content — Method.content(x)Returns the content of x.
YaoBlocks.control — Method.control(ctrl_locs, target) -> f(n)Return a lambda that takes the number of total active qubits as input. See also control.
Example
julia> control((2, 3), 1=>X)
(n -> control(n, (2, 3), 1 => X gate))
julia> control(2, 1=>X)
(n -> control(n, 2, 1 => X gate))YaoBlocks.control — Method.control(n, ctrl_locs, target)Return a ControlBlock with number of active qubits n and control locs ctrl_locs, and control target in Pair.
Example
julia> control(4, (1, 2), 3=>X)
nqubits: 4, datatype: Complex{Float64}
control(1, 2)
└─ (3,) X gate
julia> control(4, 1, 3=>X)
nqubits: 4, datatype: Complex{Float64}
control(1)
└─ (3,) X gateYaoBlocks.control — Method.control(target) -> f(ctrl_locs)Return a lambda that takes a Tuple of control qubits locs as input. See also control.
Example
julia> control(1=>X)
(ctrl_locs -> control(ctrl_locs, 1 => X gate))
julia> control((2, 3) => ConstGate.CNOT)
(ctrl_locs -> control(ctrl_locs, (2, 3) => CNOT gate))YaoBlocks.control — Method.control(ctrl_locs::Int...) -> f(target)Return a lambda that takes a Pair of control target as input. See also control.
Example
julia> control(1, 2)
(target -> control((1, 2), target))YaoBlocks.dispatch! — Method.dispatch!(x::AbstractBlock, collection)Dispatch parameters in collection to block tree x.
it will try to dispatch the parameters in collection first.
YaoBlocks.expect — Method.expect(op::AbstractBlock, reg::AbstractRegister{B}) -> Vector
expect(op::AbstractBlock, dm::DensityMatrix{B}) -> Vectorexpectation value of an operator.
YaoBlocks.getiparams — Method.getiparams(block)Returns the intrinsic parameters of node block, default is an empty tuple.
YaoBlocks.iparams_eltype — Method.iparams_eltype(block)Return the element type of getiparams.
YaoBlocks.mat — Method.mat(blk)Returns the matrix form of given block.
YaoBlocks.matblock — Method.YaoBlocks.matblock — Method.matblock(m::AbstractMatrix)Create a GeneralMatrixBlock with a matrix m.
YaoBlocks.mathgate — Method.mathgate(f; nbits[, bview=BitBasis.bint])Create a MathGate with a math function f and number of bits. You can select different kinds of view which this MathGate will be applied on. Possible values are BitBasis.bint, BitBasis.bint_r, BitBasis.bfloat, BitBasis.bfloat_r.
mathgate(f; bview=BitBasis.bint) -> f(n)Lazy curried version of mathgate.
Example
We can make a classical toffoli gate on quantum register.
julia> r = ArrayReg(bit"110")
ArrayReg{1, Complex{Float64}, Array...}
    active qubits: 3/3
julia> function toffli(b::BitStr)
           t = @inbounds b[1] ⊻ (b[3] & b[2])
           return @inbounds bit_literal(t, b[2], b[3])
       end
toffli (generic function with 1 method)
julia> g = mathgate(toffli; nbits=3)
mathgate(toffli; nbits=3, bview=bint)
julia> apply!(r, g) == ArrayReg(bit"111")
true
YaoBlocks.niparams — Method.nparameters(block) -> IntReturn number of parameters in block. See also nparameters.
YaoBlocks.occupied_locs — Method.occupied_locs(x)Return an iterator of occupied locations of x.
YaoBlocks.parameters! — Method.parameters!(out, block)Append all the parameters contained in block tree with given root block to out.
YaoBlocks.parameters — Method.parameters(block)Returns all the parameters contained in block tree with given root block.
YaoBlocks.parameters_eltype — Method.parameters_eltype(x)Return the element type of parameters.
YaoBlocks.phase — Method.phase(theta)Returns a global phase gate.
YaoBlocks.popdispatch! — Method.popdispatch!(block, list)Pop the first nparameters parameters of list, then dispatch them to the block tree block. See also dispatch!.
YaoBlocks.popdispatch! — Method.popdispatch!(f, block, list)Pop the first nparameters parameters of list, map them with a function f, then dispatch them to the block tree block. See also dispatch!.
YaoBlocks.postwalk — Method.postwalk(f, src::AbstractBlock)Walk the tree and call f after the children are visited.
YaoBlocks.prewalk — Method.prewalk(f, src::AbstractBlock)Walk the tree and call f once the node is visited.
YaoBlocks.print_tree — Function.print_tree(io, root, node[, depth=1, active_levels=()]; kwargs...)Print the block tree.
Keywords
- maxdepth: max tree depth to print
- charset: default is ('├','└','│','─'). See also- BlockTreeCharSet.
- title: control whether to print the title,- trueor- false, default is- true
YaoBlocks.print_tree — Method.print_tree([io=stdout], root)Print the block tree.
YaoBlocks.projector — Method.projector(x)Return projector on 0 or projector on 1.
YaoBlocks.put — Method.YaoBlocks.put — Method.put(total::Int, pair)Create a PutBlock with total number of active qubits, and a pair of location and block to put on.
Example
julia> put(4, 1=>X)
nqubits: 4, datatype: Complex{Float64}
put on (1)
└─ X gateIf you want to put a multi-qubit gate on specific locations, you need to write down all possible locations.
julia> put(4, (1, 3)=>kron(X, Y))
nqubits: 4, datatype: Complex{Float64}
put on (1, 3)
└─ kron
   ├─ 1=>X gate
   └─ 2=>Y gateThe outter locations creates a scope which make it seems to be a contiguous two qubits for the block inside PutBlock.
It is better to use concentrate instead of put for large blocks, since put will use the matrix of its contents directly instead of making use of what's in it. put is more efficient for small blocks.
YaoBlocks.reflect — Method.reflect(v::AbstractVector{<:Complex})Create a ReflectGate with an quantum state vector v.
YaoBlocks.reflect — Method.reflect(r::ArrayReg)Create a ReflectGate with an ArrayReg.
YaoBlocks.roll — Method.roll(n, blocks...)Return a Roller with total number of active qubits.
YaoBlocks.rot — Method.rot(U, theta)Return a RotationGate on U axis.
YaoBlocks.setiparams! — Method.setiparams!(block, itr)
setiparams!(block, params...)Set the parameters of block.
YaoBlocks.setiparams! — Method.setiparams(f, block, collection)Set parameters of block to the value in collection mapped by f.
YaoBlocks.setiparams! — Method.setiparams(f, block, symbol)Set the parameters to a given symbol, which can be :zero, :random.
YaoBlocks.shift — Method.shift(θ)Returns a shift gate.
YaoBlocks.simplify — Method.simplify(block[; rules=__default_simplification_rules__])Simplify a block tree accroding to given rules, default to use __default_simplification_rules__.
YaoBlocks.subblocks — Method.subblocks(x)Returns an iterator of the sub-blocks of a composite block. Default is empty.
YaoBlocks.swap — Method.swap([T=ComplexF64], n, loc1, loc2)Return a n-qubit Swap gate which swap loc1 and loc2.
YaoBlocks.swap — Method.YaoBlocks.@mathgate — Macro.Base.:|> — Method.|>(register, blk)Pipe operator for quantum circuits.
Example
julia> ArrayReg(bit"0") |> X |> Y|> is equivalent to apply!, which means it has side effects. You need to copy original register, if you do not want to change it in-place.
LinearAlgebra.opnorm — Function.opnorm(A::BlockMap, p::Real=2)opnorm for quantum circuit blocks.
YaoBlocks.cunmat — Function.cunmat(nbit::Int, cbits::NTuple{C, Int}, cvals::NTuple{C, Int}, U0::AbstractMatrix, locs::NTuple{M, Int}) where {C, M} -> AbstractMatrixcontrol-unitary matrix
YaoBlocks.decode_sign — Method.decode_sign(ctrls...)Decode signs into control sequence on control or inversed control.
YaoBlocks.getcol — Method.getcol(csc::SDparseMatrixCSC, icol::Int) -> (View, View)get specific col of a CSC matrix, returns a slice of (rowval, nzval)
YaoBlocks.print_annotation — Method.print_annotation(io, root, node, child, k)Print the annotation of k-th child of node, aka the k-th element of subblocks(node).
YaoBlocks.print_prefix — Method.print_prefix(io, depth, charset, active_levels)print prefix of a tree node in a single line.
YaoBlocks.print_title — Method.print_title(io, block)Print the title of given block of an AbstractBlock.
YaoBlocks.setcol! — Method.setcol!(csc::SparseMatrixCSC, icol::Int, rowval::AbstractVector, nzval) -> SparseMatrixCSCset specific col of a CSC matrix
YaoBlocks.u1ij! — Function.u1ij!(target, i, j, a, b, c, d)single u1 matrix into a target matrix.
For coo, we take an additional parameter * ptr: starting position to store new data.
YaoBlocks.unmat — Method.unmat(nbit::Int, U::AbstractMatrix, locs::NTuple) -> AbstractMatrixReturn the matrix representation of putting matrix at locs.