FLOYao no support for nbatch

[p-luo]

In Yao, the zero_state function supports an optional parameter nbatch, whereas FLOYao.zero_state does not (see example below).

using Yao
using FLOYao

nbatch = 10
yao_reg = zero_state(4; nbatch)
floyao_reg = FLOYao.zero_state(4; nbatch)

Is there a way to implement the nbatch in FLOYao?

[jlbosse]

So far FLOYao doesn't support batch simulation of many states in parallel, but evolves a single state by doing (clever) matrix-matrix multiplication. In principle this could be changed to make the content of a MajoranaReg a Array{3,T} instead of Matrix{T}, but that would be a fair bit of work.

What do you want the feature for? Maybe it is easier to just have a vector of MajoranaRegs and use julia's dot-syntax to pipe them through circuits?

[p-luo]

I honestly just wanted the feature so that my code could be cleaner. Unless batch simulation of many states in parallel is significantly faster than evolving each state through the circuit one-by-one, it's fine for now. For what it's worth, I implemented your suggestion and it worked; see the below MWE:

using FLOYao, Yao

nq = 2
circuit = chain(nq)
push!(circuit, put(nq, 1=>Rz(0.5)))

regs = []
nbatch = 5
for _ in 1:nbatch
    push!(regs, FLOYao.rand_state(nq))
end

new_states = regs .|> circuit

#output
3-element Vector{MajoranaReg{Float64}}:
 MajoranaReg{Float64}(2)
 MajoranaReg{Float64}(2)
 MajoranaReg{Float64}(2)

for i in 1:nbatch
    new_states[i] |> state |> println
end

#output
[-0.7668885487411203 0.312456896719723 0.2159993916117787 0.5172976941040434; -0.6042237042763625 -0.6248313051834304 -0.29995352644237966 -0.3930997802442814; 0.005546676980823645 0.308319100949791 -0.9279220768907074 0.20944972089458433; -0.2162519442103582 0.6456747321558772 0.04829869581011839 -0.7307574651440231]
[0.9775710401337321 -0.07730360405978609 -0.14973051030739953 0.12633205679599258; -0.07786574402059304 -0.9969375126230046 0.00717706654973211 0.0010057578817703541; -0.15023378588627606 0.00461038358366843 -0.988619170362541 -0.006378866135073871; 0.12538579256936722 -0.010885453028505474 -0.012704329596938261 -0.9919669903497839]
[0.3629279470486389 -0.5994061555507496 0.5902654723349837 0.40072713672534027; 0.7927757785381314 -0.20217245318898594 -0.5001642303064363 -0.2836698906418825; -0.4530544103416353 -0.6882784776092233 -0.5389757055116502 0.17469867600569364; -0.18582672435447523 -0.35512152443825207 0.333057958558788 -0.8534808302691927]