Using Macaulay2, we may compute the maximum likelihood degree (“ML degree”) of a scaled Segre variety where
The Macaulay2 commands for six distinct scaling arrays
ML degree 1: when
R = QQ[s,t_11,t_12,t_21,t_22];
sT = transpose matrix{{
1*s*t_11*t_21,
1*s*t_11*t_22,
1*s*t_11,
1*s*t_12*t_21,
1*s*t_12*t_22,
1*s*t_12,
1*s*t_21,
1*s*t_22,
1*s}};
As = matrix{
{1,1,1,1,1,1,1,1,1},
{1,1,1,0,0,0,0,0,0},
{0,0,0,1,1,1,0,0,0},
{1,0,0,1,0,0,1,0,0},
{0,1,0,0,1,0,0,1,0}};
U = transpose matrix{{
random(0,999),random(0,999),random(0,999),
random(0,999),random(0,999),random(0,999),
random(0,999),random(0,999),random(0,999)}};
As = substitute(As,R);
U = substitute(U,R);
Usum = (sum(flatten(entries U)));
rels = As*U-Usum*As*sT;
I = ideal rels
degree I
ML degree 2: when
R = QQ[s,t_11,t_12,t_21,t_22];
sT = transpose matrix{{
1*s*t_11*t_21,
2*s*t_11*t_22,
1*s*t_11,
1*s*t_12*t_21,
1*s*t_12*t_22,
1*s*t_12,
1*s*t_21,
1*s*t_22,
1*s}};
As = matrix{
{1,1,1,1,1,1,1,1,1},
{1,1,1,0,0,0,0,0,0},
{0,0,0,1,1,1,0,0,0},
{1,0,0,1,0,0,1,0,0},
{0,1,0,0,1,0,0,1,0}};
U = transpose matrix{{
random(0,999),random(0,999),random(0,999),
random(0,999),random(0,999),random(0,999),
random(0,999),random(0,999),random(0,999)}};
As = substitute(As,R);
U = substitute(U,R);
Usum = (sum(flatten(entries U)));
rels = As*U-Usum*As*sT;
I = ideal rels
degree I
ML degree 3: when
R = QQ[s,t_11,t_12,t_21,t_22];
sT = transpose matrix{{
1*s*t_11*t_21,
2*s*t_11*t_22,
3*s*t_11,
1*s*t_12*t_21,
1*s*t_12*t_22,
1*s*t_12,
1*s*t_21,
1*s*t_22,
1*s}};
As = matrix{
{1,1,1,1,1,1,1,1,1},
{1,1,1,0,0,0,0,0,0},
{0,0,0,1,1,1,0,0,0},
{1,0,0,1,0,0,1,0,0},
{0,1,0,0,1,0,0,1,0}};
U = transpose matrix{{
random(0,999),random(0,999),random(0,999),
random(0,999),random(0,999),random(0,999),
random(0,999),random(0,999),random(0,999)}};
As = substitute(As,R);
U = substitute(U,R);
Usum = (sum(flatten(entries U)));
rels = As*U-Usum*As*sT;
I = ideal rels
degree I
ML degree 4: when
R = QQ[s,t_11,t_12,t_21,t_22];
sT = transpose matrix{{
1*s*t_11*t_21,
2*s*t_11*t_22,
3*s*t_11,
1*s*t_12*t_21,
2*s*t_12*t_22,
1*s*t_12,
1*s*t_21,
1*s*t_22,
1*s}};
As = matrix{
{1,1,1,1,1,1,1,1,1},
{1,1,1,0,0,0,0,0,0},
{0,0,0,1,1,1,0,0,0},
{1,0,0,1,0,0,1,0,0},
{0,1,0,0,1,0,0,1,0}};
U = transpose matrix{{
random(0,999),random(0,999),random(0,999),
random(0,999),random(0,999),random(0,999),
random(0,999),random(0,999),random(0,999)}};
As = substitute(As,R);
U = substitute(U,R);
Usum = (sum(flatten(entries U)));
rels = As*U-Usum*As*sT;
I = ideal rels
degree I
ML degree 5: when
R = QQ[s,t_11,t_12,t_21,t_22];
sT = transpose matrix{{
1*s*t_11*t_21,
2*s*t_11*t_22,
3*s*t_11,
2*s*t_12*t_21,
1*s*t_12*t_22,
1*s*t_12,
1*s*t_21,
1*s*t_22,
1*s}};
As = matrix{
{1,1,1,1,1,1,1,1,1},
{1,1,1,0,0,0,0,0,0},
{0,0,0,1,1,1,0,0,0},
{1,0,0,1,0,0,1,0,0},
{0,1,0,0,1,0,0,1,0}};
U = transpose matrix{{
random(0,999),random(0,999),random(0,999),
random(0,999),random(0,999),random(0,999),
random(0,999),random(0,999),random(0,999)}};
As = substitute(As,R);
U = substitute(U,R);
Usum = (sum(flatten(entries U)));
rels = As*U-Usum*As*sT;
I = ideal rels
degree I
ML degree 6: when
R = QQ[s,t_11,t_12,t_21,t_22];
sT = transpose matrix{{
1*s*t_11*t_21,
2*s*t_11*t_22,
3*s*t_11,
2*s*t_12*t_21,
3*s*t_12*t_22,
1*s*t_12,
1*s*t_21,
1*s*t_22,
1*s}};
As = matrix{
{1,1,1,1,1,1,1,1,1},
{1,1,1,0,0,0,0,0,0},
{0,0,0,1,1,1,0,0,0},
{1,0,0,1,0,0,1,0,0},
{0,1,0,0,1,0,0,1,0}};
U = transpose matrix{{
random(0,999),random(0,999),random(0,999),
random(0,999),random(0,999),random(0,999),
random(0,999),random(0,999),random(0,999)}};
As = substitute(As,R);
U = substitute(U,R);
Usum = (sum(flatten(entries U)));
rels = As*U-Usum*As*sT;
I = ideal rels
degree I