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If ker ${\cal M}^{T} $ is one-dimensional, there are two possibilities:

Case 1: $(\mathbf{u},\mathbf{v},M\mathbf{u})$ are linearly dependent; then $M\mathbf{v} $ is linearly independent of the other three, and we can construct the vector $\mathbf{w} $ orthogonal to all four vectors via $\mathbf{w}_{i} = \epsilon_{ijkl} \mathbf{u}_{j} \mathbf{v}_{k} (M\mathbf{v} )_{l} $.

Case 2: $(\mathbf{u},\mathbf{v},M\mathbf{u})$ are linearly independent; then $M\mathbf{v} $ is linearly dependent on the other three, and we can construct the vector $\mathbf{w} $ orthogonal to all four vectors via $\mathbf{w}_{i} = \epsilon_{ijkl} \mathbf{u}_{j} \mathbf{v}_{k} (M\mathbf{u} )_{l} $, and we can also add arbitrary multiples of $\epsilon_{ijkl} \mathbf{u}_{j} \mathbf{v}_{k} (M\mathbf{v} )_{l} $, as long as the result doesn't cancel.

We can furthermore consolidate the two cases into the expression

   $$ \mathbf{w}_{i} = \epsilon_{ijkl} \mathbf{u}_{j} \mathbf{v}_{k} [(M\mathbf{u} )_{l} + (M\mathbf{v} )_{l} +\mbox{sgn}(\epsilon_{mnop} \mathbf{u}_{n} \mathbf{v}_{o} (M\mathbf{u} )_{p} \epsilon_{mqrs} \mathbf{u}_{q} \mathbf{v}_{r} (M\mathbf{v} )_{s})(M\mathbf{v} )_{l}] $$

  because in either case, it reduces to the form specific to that case already given. Here, the last term in the square brackets is a kludge to take into account the loophole pointed out by Willie Wong in comments, that the $M\mathbf{u} $ and $M\mathbf{v} $ components orthogonal to both $\mathbf{u} $ and $\mathbf{v} $ may cancel; this last term eliminates such a cancellation. Maybe one can make this less ugly and completely symmetric in $\mathbf{u} $, $\mathbf{v} $ again.

If ker ${\cal M}^{T} $ is one-dimensional, there are two possibilities:

Case 1: $(\mathbf{u},\mathbf{v},M\mathbf{u})$ are linearly dependent; then $M\mathbf{v} $ is linearly independent of the other three, and we can construct the vector $\mathbf{w} $ orthogonal to all four vectors via $\mathbf{w}_{i} = \epsilon_{ijkl} \mathbf{u}_{j} \mathbf{v}_{k} (M\mathbf{v} )_{l} $.

Case 2: $(\mathbf{u},\mathbf{v},M\mathbf{u})$ are linearly independent; then $M\mathbf{v} $ is linearly dependent on the other three, and we can construct the vector $\mathbf{w} $ orthogonal to all four vectors via $\mathbf{w}_{i} = \epsilon_{ijkl} \mathbf{u}_{j} \mathbf{v}_{k} (M\mathbf{u} )_{l} $.

We can furthermore consolidate the two cases into the expression

 $$ \mathbf{w}_{i} = \epsilon_{ijkl} \mathbf{u}_{j} \mathbf{v}_{k} [(M\mathbf{u} )_{l} + (M\mathbf{v} )_{l} +\mbox{sgn}(\epsilon_{mnop} \mathbf{u}_{n} \mathbf{v}_{o} (M\mathbf{u} )_{p} \epsilon_{mqrs} \mathbf{u}_{q} \mathbf{v}_{r} (M\mathbf{v} )_{s})(M\mathbf{v} )_{l}] $$

  Here, the last term in the square brackets is a kludge to take into account the loophole pointed out by Willie Wong in comments, that the $M\mathbf{u} $ and $M\mathbf{v} $ components orthogonal to both $\mathbf{u} $ and $\mathbf{v} $ may cancel; this last term eliminates such a cancellation. Maybe one can make this less ugly and completely symmetric in $\mathbf{u} $, $\mathbf{v} $ again.

If ker ${\cal M}^{T} $ is one-dimensional, there are two possibilities:

Case 1: $(\mathbf{u},\mathbf{v},M\mathbf{u})$ are linearly dependent; then $M\mathbf{v} $ is linearly independent of the other three, and we can construct the vector $\mathbf{w} $ orthogonal to all four vectors via $\mathbf{w}_{i} = \epsilon_{ijkl} \mathbf{u}_{j} \mathbf{v}_{k} (M\mathbf{v} )_{l} $.

Case 2: $(\mathbf{u},\mathbf{v},M\mathbf{u})$ are linearly independent; then $M\mathbf{v} $ is linearly dependent on the other three, and we can construct the vector $\mathbf{w} $ orthogonal to all four vectors via $\mathbf{w}_{i} = \epsilon_{ijkl} \mathbf{u}_{j} \mathbf{v}_{k} (M\mathbf{u} )_{l} $, and we can also add arbitrary multiples of $\epsilon_{ijkl} \mathbf{u}_{j} \mathbf{v}_{k} (M\mathbf{v} )_{l} $, as long as the result doesn't cancel.

We can furthermore consolidate the two cases into the expression  $$ \mathbf{w}_{i} = \epsilon_{ijkl} \mathbf{u}_{j} \mathbf{v}_{k} [(M\mathbf{u} )_{l} + (M\mathbf{v} )_{l} +\mbox{sgn}(\epsilon_{mnop} \mathbf{u}_{n} \mathbf{v}_{o} (M\mathbf{u} )_{p} \epsilon_{mqrs} \mathbf{u}_{q} \mathbf{v}_{r} (M\mathbf{v} )_{s})(M\mathbf{v} )_{l}] $$ because in either case, it reduces to the form specific to that case already given. Here, the last term in the square brackets is a kludge to take into account the loophole pointed out by Willie Wong in comments, that the $M\mathbf{u} $ and $M\mathbf{v} $ components orthogonal to both $\mathbf{u} $ and $\mathbf{v} $ may cancel; this last term eliminates such a cancellation. Maybe one can make this less ugly and completely symmetric in $\mathbf{u} $, $\mathbf{v} $ again.

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If ker ${\cal M}^{T} $ is one-dimensional, there are two possibilities:

Case 1: $(\mathbf{u},\mathbf{v},M\mathbf{u})$ are linearly dependent; then $M\mathbf{v} $ is linearly independent of the other three, and we can construct the vector $\mathbf{w} $ orthogonal to all four vectors via $\mathbf{w}_{i} = \epsilon_{ijkl} \mathbf{u}_{j} \mathbf{v}_{k} (M\mathbf{v} )_{l} $.

Case 2: $(\mathbf{u},\mathbf{v},M\mathbf{u})$ are linearly independent; then $M\mathbf{v} $ is linearly dependent on the other three, and we can construct the vector $\mathbf{w} $ orthogonal to all four vectors via $\mathbf{w}_{i} = \epsilon_{ijkl} \mathbf{u}_{j} \mathbf{v}_{k} (M\mathbf{u} )_{l} $.

% We can furthermore consolidate the two cases into the expression

$$ % \mathbf{w}_{i} = \epsilon_{ijkl} \mathbf{u}_{j} \mathbf{v}_{k} % [(M\mathbf{u} )_{l} + (M\mathbf{v} )_{l} ] % $$$$ \mathbf{w}_{i} = \epsilon_{ijkl} \mathbf{u}_{j} \mathbf{v}_{k} [(M\mathbf{u} )_{l} + (M\mathbf{v} )_{l} +\mbox{sgn}(\epsilon_{mnop} \mathbf{u}_{n} \mathbf{v}_{o} (M\mathbf{u} )_{p} \epsilon_{mqrs} \mathbf{u}_{q} \mathbf{v}_{r} (M\mathbf{v} )_{s})(M\mathbf{v} )_{l}] $$

because in either caseHere, it reduces to the expression specificlast term in the square brackets is a kludge to take into account the loophole pointed out by Willie Wong in comments, that case already giventhe $M\mathbf{u} $ and $M\mathbf{v} $ components orthogonal to both $\mathbf{u} $ and $\mathbf{v} $ may cancel; this last term eliminates such a cancellation.

WORKING ON EDIT TO TAKE INTO ACCOUNT REMARK BY W Maybe one can make this less ugly and completely symmetric in $\mathbf{u} $, $\mathbf{v} $ again. WONG

If ker ${\cal M}^{T} $ is one-dimensional, there are two possibilities:

Case 1: $(\mathbf{u},\mathbf{v},M\mathbf{u})$ are linearly dependent; then $M\mathbf{v} $ is linearly independent of the other three, and we can construct the vector $\mathbf{w} $ orthogonal to all four vectors via $\mathbf{w}_{i} = \epsilon_{ijkl} \mathbf{u}_{j} \mathbf{v}_{k} (M\mathbf{v} )_{l} $.

Case 2: $(\mathbf{u},\mathbf{v},M\mathbf{u})$ are linearly independent; then $M\mathbf{v} $ is linearly dependent on the other three, and we can construct the vector $\mathbf{w} $ orthogonal to all four vectors via $\mathbf{w}_{i} = \epsilon_{ijkl} \mathbf{u}_{j} \mathbf{v}_{k} (M\mathbf{u} )_{l} $.

% We can furthermore consolidate the two cases into the expression

$$ % \mathbf{w}_{i} = \epsilon_{ijkl} \mathbf{u}_{j} \mathbf{v}_{k} % [(M\mathbf{u} )_{l} + (M\mathbf{v} )_{l} ] % $$

because in either case, it reduces to the expression specific to that case already given.

WORKING ON EDIT TO TAKE INTO ACCOUNT REMARK BY W. WONG

If ker ${\cal M}^{T} $ is one-dimensional, there are two possibilities:

Case 1: $(\mathbf{u},\mathbf{v},M\mathbf{u})$ are linearly dependent; then $M\mathbf{v} $ is linearly independent of the other three, and we can construct the vector $\mathbf{w} $ orthogonal to all four vectors via $\mathbf{w}_{i} = \epsilon_{ijkl} \mathbf{u}_{j} \mathbf{v}_{k} (M\mathbf{v} )_{l} $.

Case 2: $(\mathbf{u},\mathbf{v},M\mathbf{u})$ are linearly independent; then $M\mathbf{v} $ is linearly dependent on the other three, and we can construct the vector $\mathbf{w} $ orthogonal to all four vectors via $\mathbf{w}_{i} = \epsilon_{ijkl} \mathbf{u}_{j} \mathbf{v}_{k} (M\mathbf{u} )_{l} $.

We can furthermore consolidate the two cases into the expression

$$ \mathbf{w}_{i} = \epsilon_{ijkl} \mathbf{u}_{j} \mathbf{v}_{k} [(M\mathbf{u} )_{l} + (M\mathbf{v} )_{l} +\mbox{sgn}(\epsilon_{mnop} \mathbf{u}_{n} \mathbf{v}_{o} (M\mathbf{u} )_{p} \epsilon_{mqrs} \mathbf{u}_{q} \mathbf{v}_{r} (M\mathbf{v} )_{s})(M\mathbf{v} )_{l}] $$

Here, the last term in the square brackets is a kludge to take into account the loophole pointed out by Willie Wong in comments, that the $M\mathbf{u} $ and $M\mathbf{v} $ components orthogonal to both $\mathbf{u} $ and $\mathbf{v} $ may cancel; this last term eliminates such a cancellation. Maybe one can make this less ugly and completely symmetric in $\mathbf{u} $, $\mathbf{v} $ again.

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If ker ${\cal M}^{T} $ is one-dimensional, there are two possibilities:

Case 1: $(\mathbf{u},\mathbf{v},M\mathbf{u})$ are linearly dependent; then $M\mathbf{v} $ is linearly independent of the other three, and we can construct the vector $\mathbf{w} $ orthogonal to all four vectors via $\mathbf{w}_{i} = \epsilon_{ijkl} \mathbf{u}_{j} \mathbf{v}_{k} (M\mathbf{v} )_{l} $.

Case 2: $(\mathbf{u},\mathbf{v},M\mathbf{u})$ are linearly independent; then $M\mathbf{v} $ is linearly dependent on the other three, and we can construct the vector $\mathbf{w} $ orthogonal to all four vectors via $\mathbf{w}_{i} = \epsilon_{ijkl} \mathbf{u}_{j} \mathbf{v}_{k} (M\mathbf{u} )_{l} $.

% We can furthermore consolidate the two cases into the expression $$ \mathbf{w}_{i} = \epsilon_{ijkl} \mathbf{u}_{j} \mathbf{v}_{k} [(M\mathbf{u} )_{l} + (M\mathbf{v} )_{l} ] $$ because

$$ % \mathbf{w}_{i} = \epsilon_{ijkl} \mathbf{u}_{j} \mathbf{v}_{k} % [(M\mathbf{u} )_{l} + (M\mathbf{v} )_{l} ] % $$

because in either case, it reduces to the expression specific to that case already given.

WORKING ON EDIT TO TAKE INTO ACCOUNT REMARK BY W. WONG

If ker ${\cal M}^{T} $ is one-dimensional, there are two possibilities:

Case 1: $(\mathbf{u},\mathbf{v},M\mathbf{u})$ are linearly dependent; then $M\mathbf{v} $ is linearly independent of the other three, and we can construct the vector $\mathbf{w} $ orthogonal to all four vectors via $\mathbf{w}_{i} = \epsilon_{ijkl} \mathbf{u}_{j} \mathbf{v}_{k} (M\mathbf{v} )_{l} $.

Case 2: $(\mathbf{u},\mathbf{v},M\mathbf{u})$ are linearly independent; then $M\mathbf{v} $ is linearly dependent on the other three, and we can construct the vector $\mathbf{w} $ orthogonal to all four vectors via $\mathbf{w}_{i} = \epsilon_{ijkl} \mathbf{u}_{j} \mathbf{v}_{k} (M\mathbf{u} )_{l} $.

We can furthermore consolidate the two cases into the expression $$ \mathbf{w}_{i} = \epsilon_{ijkl} \mathbf{u}_{j} \mathbf{v}_{k} [(M\mathbf{u} )_{l} + (M\mathbf{v} )_{l} ] $$ because in either case, it reduces to the expression specific to that case already given.

If ker ${\cal M}^{T} $ is one-dimensional, there are two possibilities:

Case 1: $(\mathbf{u},\mathbf{v},M\mathbf{u})$ are linearly dependent; then $M\mathbf{v} $ is linearly independent of the other three, and we can construct the vector $\mathbf{w} $ orthogonal to all four vectors via $\mathbf{w}_{i} = \epsilon_{ijkl} \mathbf{u}_{j} \mathbf{v}_{k} (M\mathbf{v} )_{l} $.

Case 2: $(\mathbf{u},\mathbf{v},M\mathbf{u})$ are linearly independent; then $M\mathbf{v} $ is linearly dependent on the other three, and we can construct the vector $\mathbf{w} $ orthogonal to all four vectors via $\mathbf{w}_{i} = \epsilon_{ijkl} \mathbf{u}_{j} \mathbf{v}_{k} (M\mathbf{u} )_{l} $.

% We can furthermore consolidate the two cases into the expression

$$ % \mathbf{w}_{i} = \epsilon_{ijkl} \mathbf{u}_{j} \mathbf{v}_{k} % [(M\mathbf{u} )_{l} + (M\mathbf{v} )_{l} ] % $$

because in either case, it reduces to the expression specific to that case already given.

WORKING ON EDIT TO TAKE INTO ACCOUNT REMARK BY W. WONG

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