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PropertyT.jl/SL3Z.jl

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using JLD
using JuMP
import Primes: isprime
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import SCS: SCSSolver
import Mosek: MosekSolver
using Mods
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using Groups
using ProgressMeter
function SL_generatingset(n::Int)
indexing = [(i,j) for i in 1:n for j in 1:n if i≠j]
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S = [E(i,j,N=n) for (i,j) in indexing];
S = vcat(S, [convert(Array{Int,2},x') for x in S]);
S = vcat(S, [convert(Array{Int,2},inv(x)) for x in S]);
return unique(S)
end
function E(i::Int, j::Int; val=1, N::Int=3, mod=Inf)
@assert i≠j
m = eye(Int, N)
m[i,j] = val
if mod == Inf
return m
else
return [Mod(x,mod) for x in m]
end
end
function cofactor(i,j,M)
z1 = ones(Bool,size(M,1))
z1[i] = false
z2 = ones(Bool,size(M,2))
z2[j] = false
return M[z1,z2]
end
import Base.LinAlg.det
function det(M::Array{Mod,2})
if size(M,1) size(M,2)
d = Mod(0,M[1,1].mod)
elseif size(M,1) == 2
d = M[1,1]*M[2,2] - M[1,2]*M[2,1]
else
d = zero(eltype(M))
for i in 1:size(M,1)
d += (-1)^(i+1)*M[i,1]*det(cofactor(i,1,M))
end
end
# @show (M, d)
return d
end
function adjugate(M)
K = similar(M)
for i in 1:size(M,1), j in 1:size(M,2)
K[j,i] = (-1)^(i+j)*det(cofactor(i,j,M))
end
return K
end
import Base: inv, one, zero, *
one(::Type{Mod}) = 1
zero(::Type{Mod}) = 0
zero(x::Mod) = Mod(x.mod)
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function inv(M::Array{Mod,2})
d = det(M)
d 0*d || thow(ArgumentError("Matrix is not invertible!"))
return inv(det(M))*adjugate(M)
return adjugate(M)
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end
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function prepare_Δ_sdp_constraints(identity, S)
@show length(S)
B₁ = vcat([identity], S)
B₂ = products(B₁, B₁);
B₃ = products(B₁, B₂);
B₄ = products(B₁, B₃);
@assert B₄[1:length(B₂)] == B₂
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product_matrix = create_product_matrix(B₄,length(B₂));
sdp_constraints = constraints_from_pm(product_matrix, length(B₄))
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L_coeff = splaplacian_coeff(S, B₂, length(B₄));
Δ = GroupAlgebraElement(L_coeff, product_matrix)
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return Δ, sdp_constraints
end
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function load_Δ_sdp_constraints(name::String;cached=true)
pm_filename = "$name.product_matrix.jld"
Δ_coeff_filename = "$name.delta.coefficients.jld"
f₁ = isfile(pm_filename)
f₂ = isfile(Δ_coeff_filename)
if cached && f₁ && f₂
println("Loading precomputed pm, Δ, sdp_constraints...")
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product_matrix = load(pm_filename, "pm")
L = load(Δ_coeff_filename, "Δ")[:, 1]
Δ = GroupAlgebraElement(L, Array{Int,2}(product_matrix))
sdp_constraints = constraints_from_pm(product_matrix)
else
println("Computing pm, Δ, sdp_constraints...")
ID = eye(Int, 3)
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S = SL₃_generatingset()
Δ, sdp_constraints = prepare_Δ_sdp_constraints(ID, S)
save(pm_filename, "pm", Δ.product_matrix)
save(Δ_coeff_filename, "Δ", Δ.coefficients)
end
return Δ, sdp_constraints
end
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function compute_κ_A(name::String, Δ, sdp_constraints;
cached = true,
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tol = 1e-7,
verbose = false,
# solver = MosekSolver(INTPNT_CO_TOL_REL_GAP=tol, QUIET=!verbose))
solver = SCSSolver(eps=tol, max_iters=20000, cg_rate=3, verbose=verbose))
f₁ = isfile("$name.kappa")
f₂ = isfile("$name.SDPmatrixA")
if cached && f₁ && f₂
println("Loading precomputed κ, A...")
A = readdlm("$name.SDPmatrixA")
κ = readdlm("$name.kappa")[1]
else
println("Solving SDP problem maximizing κ...")
κ, A = solve_SDP(sdp_constraints, Δ, solver, verbose=verbose)
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# writedlm("$name.kappa", kappa)
# writedlm("$name.SDPmatrixA", A)
end
return κ, A
end
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function main()
const NAME = "SL3Z"
const VERBOSE = true
const TOL=1e-7
const Δ, sdp_constraints = load_Δ_sdp_constraints(NAME)
const κ, A = compute_κ_A(NAME, Δ, sdp_constraints, cached=false, verbose=VERBOSE)
if maximum(A) < 1e-2
warn("Solver might not solved the problem successfully and the positive solution is due to floating-point error, proceeding anyway...")
end
if κ > 0
@assert A == Symmetric(A)
const A_sqrt = real(sqrtm(A))
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T = _distance_to_positive_cone(Δ, κ, A, tol=TOL, verbose=VERBOSE)
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if T < 0
println("$NAME HAS property (T)!")
else
println("$NAME may NOT HAVE property (T)!")
end
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else
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println(" < 0: $NAME may NOT HAVE property (T)!")
end
end
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@everywhere push!(LOAD_PATH, "./")
using GroupAlgebras
include("property(T).jl")
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main()