In this post, we shall discuss various generalizations of the notion of the spectral radius to a sort of spectral radius for collections of multiple operators, and we shall develop the theory of the -spectral radius
. This post consists of the new mathematical research on spectral radii which I will apply to measure the cryptographic security of block cipher round functions with very small key space and small message space. The results that are about the
-spectral radii
are due to J. Van Name unless otherwise stated while all other results stated are due to others unless otherwise or are standard results in quantum information theory. This post shall be a purely mathematical post, so this post will not contain any cryptography nor will we discuss algorithms that one can use to compute the spectral radii or at least bounds for the spectral radii. I expect for the notion of the
-spectral radius to extend to infinite dimensional Hilbert spaces, but no one has formulated such a generalization yet. Future posts about spectral radii will be about the application of spectral radii to cryptography, algorithms, the results of these computations, and possible an
-spectral radius for infinite dimensional spaces.
This post includes a large amount of linear algebra and quantum information theory. I recommend the book The Theory of Quantum Information by John Watrous (2018) for information about quantum information theory; most of the facts about linear algebra and quantum information theory that I state but do not prove can be found in The Theory of Quantum Information. I intend for this post to be accessible to people who understand linear algebra but who do not necessarily have much knowledge about functional analysis, quantum information theory, quantum computation, or quantum mechanics.
Spectral radius
Suppose that is a complex Banach space that contains an operation
that makes
into a unital ring. Then we say that
is a unital Banach algebra if
whenever
and if
If , then the spectrum
of
is the set of all complex numbers
where
is not invertible. If
is a square complex matrix, then
is simply the set of all eigenvalues of
. The spectrum
is always a compact non-empty subset of
. Define the spectral radius
of
to be
. The following theorem motivates the spectral radius
as a measure of the growth rate of
Theorem: If , then
We have whenever
and this sum converges absolutely. On the other hand,
diverges whenever
. More generally,
is the radius of convergence of the power series
.
We may generalize the notion of the spectral radius to a spectral radius of multiple operators in several different ways. If is a Banach algebra,
, and
, then define the
-spectral radius as
(it is not too hard to show that this limit exists). Observe that when
, this definition of
does not depend on the choice of norm, and this definition still holds even if we drop the requirement that the norm is sub-multiplicative. Define
(this limit exists) . We can also write
in terms of the
norm for
by letting
Here,
denotes the
norm.
If is a ring and
, then we say that
is jointly nilpotent if
for all but finitely many strings
.
Basic observations: Suppose that is a Banach algebra and
. Let
be an invertible element in
. Suppose that
Let
.
whenever
is an invertible element in
.
for each scalar
.
whenever
.
.
if and only if
is jointly nilpotent.
To prove the above fact, we use the fact that if , then
While the spectral radii are distinct important generalizations of the notion of a spectral radius, for this post, we shall be primarily concerned with the spectral radius
. For the rest of this post, we shall assume all vector spaces are finite dimensional inner product spaces.
Let be a finite dimensional complex inner product spaces. Let
denote the space of all linear operators from
to
, and let
. If
, then define a mapping
by letting
Throughout this post, we shall implicitly use the fact that the operator
is similar to
If , then recall that the
-Schatten norm of a complex matrix
is defined by letting
for
and
If
are the singular values of
, then
. If
are real or complex matrices with the same dimensions, then define the Frobenius inner product
. Observe that
. If
then
.
The following proposition was originally proven by Ding-Xuan Zhou in the 1998 paper titled The -norm joint spectral radius for even integers.
Proposition: .
Proof: Let be the collection of all positive semidefinite matrices
with
. Observe that if
is positive semidefinite, then
if and only if
. We will need to use the fact that
.
For this proof, the norm on an operator
from
to
shall be the maximum value of
such that
. We have
=. Q.E.D.
Corollary: If is an even integer, then
.
Proposition: Suppose that are positive real numbers with
. Then
.
Proof: Assume that our matrix norm satisfies the property for all matrices
. By applying Holder’s inequality, we perform the following calculations.
Q.E.D.
The above inequality is sharp when since
.
Example: If are unitary matrices, then
More generally, if
are constants, then
Example: Suppose that are matrices. Then
Example: If are matrices, then
Quantum information theory
A mapping is said to be positive if
is positive semidefinite whenever
is positive semidefinite. The mapping
is said to be completely positive if
is positive whenever
is a finite dimensional complex inner product space. The mapping
is said to be trace preserving if
for each
The mapping
is said to be unital if
A mapping
is said to be a quantum channel if
is completely positive and trace preserving.
If are complex vector spaces, then there is a unique linear mapping
where
whenever
. This linear mapping is known as the partial trace.
Observation: Suppose that
, and
. Then
and
If are finite dimensional complex inner product spaces, then
are inner product spaces with the Frobenius norm. In this case, if
is a linear mapping, then the adjoint
of
is the adjoint with respect to the Frobenius norms on
and
.
Let be finite dimensional complex inner product spaces. Every mapping in
is a linear combinational of mappings of the form
where
Therefore, if
, then let
be the mapping defined by letting
whenever
. If
, then let
be the mapping defined by letting
and define
by letting
We shall sometimes write
for
and
for
in order to specify the vector space
. Observe that
and
, and
whenever these equations make sense.
The linear operator is similar to the linear operator
.
Theorem: Let be finite dimensional complex inner product spaces. Let
be a linear mapping. The following are equivalent:
Theorem: Let be finite dimensional complex inner product spaces. Let
be a linear mapping. The following are equivalent:
is completely positive.
is positive.
for some
and
.
for some finite dimensional complex inner product space
and
.
Theorem: Let be finite dimensional complex inner product spaces. Let
be a linear mapping. Then the operator
is trace preserving if and only if its adjoint
is unital.
Theorem
1: Let . Then
i. The following are equivalent:
a. is trace preserving.
b.
c. .
ii. The following are equivalent:
a. is unital.
b. .
c. .
2. Let Then
i. The following are equivalent:
a. is trace preserving.
b. .
c. .
ii. The following are equivalent:
a. is unital.
b. .
c. .
Theorem: Suppose that and
are linear. The mapping
is a quantum channel if and only if
is an isometry. The mapping
is a quantum channel if and only if
.
Example: The completely depolarizing channel is the channel defined by letting
. The completely depolarizing channel is unital. If
, then let
be the
-matrix defined by letting
where
refers to the Kronecker delta function. Then
. We shall write
in order to specify the space
, and we shall write
for
.
Example: Suppose that is a probability vector. Let
be a finite dimensional complex inner product space. Let
be unitary operators. Then let
be the function where
for each
. Then we say that
is mixed unitary. Every mixed unitary operator is a unital channel, but not every unitary channel is mixed unitary. However, John Watrous has shown that there is a neighborhood
of the completely depolarizing channel where if
, then
is mixed unitary if and only if it is unital.
Example: The complete dephasing channel is the channel defined by letting
precisely when
for
and
for
. Suppose that
are the matrices where
for
and where the addition in the subscript is taken modulo
. Then
Example: The shifted complete dephasing channel is the channel defined by letting
precisely when
for
and
for
where the addition in the subscripts is taken modulo
. Suppose now that
are the matrices where
for
and where the addition in the subscript is taken modulo
. Then
Example: The shifted complete dephasing channel is the channel defined by letting
precisely when
for
and
for
where the addition in the subscripts is taken modulo
. Suppose now that
are the matrices where
for
and where the addition in the subscript is taken modulo
. Then
Proposition: If is positive and either trace preserving or unital, then
.
Proof outline: Since is trace preserving if and only if its adjoint
is unital, we only have to prove this result when
is trace preserving.
If is positive and trace preserving, then whenever
is positive semidefinite, we have
. From this fact, one can easily conclude that
. Q.E.D.
Proposition: If is positive and
whenever
is a positive semidefinite matrix with
, then
has a positive semidefinite eigenvector with non-zero eigenvector.
Proof: Let be the collection of all positive semidefinite operators
with
. Define a mapping
by letting
Then by Brouwer’s fixed point theorem, there is some
with
. Therefore,
.
Q.E.D.
Corollary: If is positive and trace preserving, then there is a positive semidefinite
with
and
.
Proposition: If is a positive mapping. If
is a positive definite eigenvector, then
Proof: Suppose that is an eigenvalue with
and
is an eigenvector with
. Then there are positive semidefinite
with
. Therefore, there is some
with
for all
.
For all , we have
This is only possible if
.
Q.E.D.
Tensor products
We will apply the following observations about tensor products and related constructions to the -spectral radius.
Proposition: Suppose that are
-complex matrices. Then
if and only if there is an
-unitary matrix
such that
for
.
Lemma: Suppose that are linear operators. Then
if and only if there is a unitary
such that
.
Lemma: Suppose that are matrices over a field
where
are of the same dimensions and
are of the same dimensions. Let
be
-matrices over the field
. Suppose furthermore that
and
for
. If
, then
.
Lemma: Suppose that are complex matrices where
have the same dimensions, and
have the same dimensions. Let
be complex
-matrices. Suppose that
and
for
and
, then
Lemma: Let be finite dimensional complex inner product spaces. Suppose that
and
are linear mappings. Let
be linear mappings. Suppose that
and
. Then
.
Proposition: Let be finite dimensional complex inner product spaces. Let
be linear. Let
be an orthonormal basis for
. Let
be linear. Suppose that
. Then
.
Observation: Let be finite dimensional complex inner product spaces. Suppose that
is an orthonormal basis for
. Let
be linear operators. Suppose that
are linear operators and
. Let
be linear. Then
Proposition: Let be finite dimensional complex inner product spaces. Suppose that
are linear mappings. Let
be an orthonormal basis for
. Let
be linear maps. Suppose that
. Then
.
-spectral radius.
Let be the collection of all tuples
which are not jointly nilpotent. Suppose that
are complex matrices. Then define the
-spectral radius of
by
By the Cauchy-Schwarz inequality , we know that
whenever
, and since
we know that if
, then
.
Proposition: Suppose that are
complex matrices. Suppose that there is a
unitary matrix
such that
for
. Then
.
Proof: Let Then
is unitary. Suppose now that
. Then there are
with
Now set
for
, then
and
. Therefore,
, so
. We can therefore conclude that
For the reverse inequality, observe that if , then
and
is unitary, so we can conclude that
as well.
Q.E.D.
Corollary: If , then
for all
.
If is a completely positive superoperator, then define
by letting
whenever
. By the above corollary, the quantity
is well-defined. If
is a linear operator, then define
Observation: Let be finite dimensional complex inner product spaces with
. Let
be an orthonormal basis for
. Let
and let
. Let
, and let
Then the following quantities are equivalent:
.
Proof outline: By definition 1-3 are equivalent to each other. The equivalence between 1 and 4 follows from the fact that and
The equivalence between 4 and 5 follows from the fact that if
and
, then
and
The equivalence between 6 and 7 follows from the fact that
. The equivalence between 1 and 7 follows from the fact that
and
Q.E.D.
We shall soon see how in the above result, each of the suprema can actually be reached, so we can replace each supremum with a maximum.
Proposition: Suppose that are
-complex matrices. Suppose furthermore that there is an invertible
-complex matrix
, a complex number
and a
unitary matrix
such that
for
. Then
.
Proof: It is easy to see that . Furthermore, since
, we know that
as well. Q.E.D.
Lemma: Suppose that are linear operators. If
, then
Proof: We have
. Therefore,
is similar to
, so
. We therefore conclude that
. Furthermore, we have
, so
as well.
Q.E.D.
Lemma: Suppose that are linear operators. If
, then
Proof: Observe that
. Therefore,
is similar to
, so
. We conclude that
, and clearly
.
Now, since , we know that
. Q.E.D.
Quantum channels and spectral radii
Here, we give theorems that interpret the spectral radii in terms of quantum channels.
Let be finite dimensional complex Hilbert spaces. Suppose that
is a positive mapping. Suppose that
has a positive definite eigenvector
with non-zero (necessarily positive) eigenvalue
. Then define a positive operator
by
. Then
is unital.
Suppose that is a positive mapping. Suppose that
has a positive definite eigenvector
with non-zero (necessarily positive) eigenvalue
. Then define a mapping
by letting
. Then
is trace preserving and positive. In particular, if
is a completely positive, and
has a positive definite eigenvector
, then
is a quantum channel.
We say that a positive operator is pre-unital if
has a positive definite eigenvector
with non-zero (necessarily positive) eigenvalue
. We say that a positive operator
is pre-trace preserving if
has a positive definite eigenvector
with non-zero (necessarily positive) eigenvalue
.
We say that a tuple is pre-unital (pre-trace preserving) if
is pre-unital (pre-trace preserving). We say that
is pre-unital (pre-trace preserving) if
is pre-unital (pre-trace preserving).
Proposition: Let be a finite dimensional complex inner product space. Let
be a positive operator. The following are equivalent:
is pre-unital.
- There is some positive definite
and non-zero
where if
, then
is unital.
- There is some invertible
and non-zero
where if
, then
is unital.
In particular, is the spectral radius of the operator
Proposition: Let be a finite dimensional complex inner product space. Let
be a positive operator. The following are equivalent:
is pre-trace preserving.
- There is some positive definite
and non-zero
where if
, then
is trace preserving.
- There is some invertible
and non-zero
where if
, then
is trace preserving.
Proposition: Let be finite dimensional complex inner product spaces where
is an orthonormal basis for
. Let
and suppose that
. Then the following are equivalent:
is pre unital.
- There exists some invertible
and some
where
is unital.
- There is some positive definite
and some
where
is unital.
- There exists some invertible
and some
where
is unital.
- There exists some positive definite
and some
where
is unital.
Proposition: Let be finite dimensional complex inner product spaces where
has orthonormal basis
. Let
, and suppose that
. Then the following are equivalent:
is pre-trace preserving.
- There exists some invertible
and some
where
is trace preserving.
- There is some positive definite
and some
where
is trace preserving.
- There exists some invertible
and some
where
is trace-preserving.
- There exists some positive definite
and some
where
is trace-preserving.
Observation: Let be finite dimensional complex vector spaces and let
be a subspace of
Let
be linear operators. Let
be a linear operator. Let
be positive semidefinite.
.
.
.
.
.
.
.
.
.
.
.
.
From the following proposition, we can conclude that if , then almost all tuples
are both pre-unital and pre-trace preserving.
Proposition: Let be a finite dimensional complex inner product space. Let
. Suppose that
has no irreducible subspace other than
and
. Then
is both pre-unital and pre-trace preserving.
Theorem: (J. Van Name) Let be finite dimensional complex vector spaces where
has orthonormal basis
and
Let
, and suppose that
. Suppose that
The following quantities are equivalent:
.
.
.
.
.
.
Proof: Observe that is compact, so the maximum
actually exists. By similar arguments, one can show that the maximum exists in 3-9. Furthermore, observe that the quantities in 3-9 are all less than or equal to
Suppose that
. Then there is some
where
. Therefore, there is a pre-trace preserving and pre-unital
with
. Since
is pre-trace preserving, there is some
and invertible
where
is trace preserving. In this case, if
for
, then
Therefore, since
Therefore,
.
Since is pre-unital, there is some
and invertible
where
is unital. Let
for
. In this case, we have
so
Thus as well.
The proofs that are all greater than or equal to
are similar to the proofs that
.
Q.E.D.
Let be finite dimensional complex Hilbert spaces. Suppose that
is a linear operator. Then define the induced trace norm of
as
, and define the completely bounded trace norm of
as
. Both the induced trace norm and the completely bounded trace norm are submultiplicative, so
whenever
.
The proof of following lemma can be found in the 2012 paper ‘Relations for certain symmetric norms and anti-norms before and after partial trace’ by Alexey E. Rastegin.
Lemma: Let be finite dimensional complex inner product spaces. Let
be a linear operator. Suppose that
. Then
. In particular,
.
If is a positive and trace preserving map, then
. If
is a quantum channel, then
Observe that if . Therefore,
.
Observation: (J. Van Name) Let be finite dimensional complex Hilbert spaces with
and where
has orthonormal basis
. Let
and suppose that
is the mapping where
. Then the following quantities are equivalent:
There are other similar formulae for , but for the sake of brevity, we shall leave the task of finding other formulae for
to the reader.
Observation: whenever
are complex matrices,
are isometries, and this product makes sense.
Lemma: Suppose that are isometries. Then
.
Proof: Observe that whenever
is an operator. Therefore,
. Q.E.D.
Lemma: Suppose that are isometries. Then
.
Proof: Suppose that is an eigenvalue for
. Then
for some
. Therefore,
. Now, by the polar decomposition, there is a positive semidefinite
and an isometry
where
. Let
. Now,
.
Suppose that . Then
and
. Therefore,
. This is only possible if
.
Q.E.D.
Theorem: (J. Van Name) Suppose that are finite dimensional complex vector spaces and
. Suppose that
is pre-trace preserving, and
is has no non-trivial invariant subspace. If
, then
has an invariant subspace
and there is a linear bijection
and non-zero
with
for
where
is the restriction of
to the invariant subspace
.
Proof: Since are both pre-trace preserving, there are matrices
and non-zero complex numbers
such that if
for
, then
are quantum channels. Suppose now that
. Then
Suppose now that are the same as in the above lemma, and suppose that
. Then
.
This is only possible if whenever
. This happens precisely when
. Therefore, we have
. We therefore, conclude that
. The positive definite matrix
is positive definite, so
.
Suppose that . Then
. Therefore,
whenever
.
Now, let
be the restrictions of
.
The mapping is unitary. Here,
. Therefore,
, so
. Therefore,
, so
Q.E.D.
Theorem: (J. Van Name) Let be finite dimensional complex inner product spaces. Suppose that
are linear operators. Then we can assign the vector spaces
bases such that for
, we can write the operators
as block matrices to get
and
where
i. whenever
,
ii. is square whenever
,
iii. has no non-trivial irreducible subspace whenever
,
iv. whenever
v. is square whenever
, and
vi. has no non-trivial irreducible subspace whenever
.
Given such a decomposition of into block matrices, the following are equivalent:
- There exists
, a complex number
and an invertible
where
and
and where
for
.
Corollary: (J. Van Name) If has no non-trivial invariant subspace, then
whenever
.
Proof: By the above result, we can choose such that
, but by the above result, we know that
Q.E.D.
Statement 1 in the following theorem was originally proven by Fedja from MathOverflow, but the proof given is by Joseph Van Name (I was only able to see how quantum channels were related to after reading Fedja’s proof).
Theorem: (J. Van Name) Let be positive integers. Suppose that
is a
-matrix with real entries whenever
. Let
be the
matrix that can be written as the block matrix
Then
2. For all , the matrices
can be chosen such that
3. If and
, then
for each
.
4. Let denote the complete depolarizing channel. Then
.
Proof:
If is an
-complex matrix, then let
be the system of submatrices so that
Let be the collection of all systems
where
is not nilpotent. Let
be the collection of all systems
which are pre-trace preserving. Let
(resp
) be the collection of all
where
(resp
).
Suppose that is an
-matrix where
is a quantum channel. Then
Therefore, . Furthermore, if
, then
, and this is only possible if
.
- Suppose now that
Then there is a complex number
and an invertible
where
is a quantum channel. Suppose now that
is the
matrix with
for each
. In this case,
. Furthermore, if
and
, then
, so
as well. Since
is dense in
, we conclude that
whenever
.
2. Let if
or
, and if
and
, then let
be the
matrix where the
-th entry is
but every other entry is
. In this case, we have
.
3. We shall now define functions and
. Let
whenever
and
where
are the eigenvalues of
ordered so that
Observe that if
, then
precisely when
.
Now suppose that . Then let
. Then there is some
where if
and
, then
Now select a matrix
with
. Then
. Therefore, there is some
and
where if
is the
matrix with
for each
, then
is a quantum channel. Therefore, we have
.
Thus, Let
be the eigenvalues of
ordered such that
. Then
. Therefore,
, so
.
We conclude that . Therefore,
as
, so
which means that
.
4. Let be the
-matrix where all entries in
are zero except for the
-th entry, and where the
-th entry in
is
. Observe that
and if
is a
-matrix, then
. Therefore,
, so
Q.E.D.
Let be an inner product space. Then
is said to be a frame if there are
with
for all
If
, then we say that the frame
is a tight frame. In other words,
is a tight frame if
for all
. We observe that
is a tight frame precisely when
. An equal-norm tight frame is a tight frame
where
for all
.
Lemma: Suppose that is either the field of real or complex numbers. There exists an equal-norm tight frame
for the inner product space
.
See Corollary 7.1 in the book An Introduction to Finite Tight Frames by Shayne F. D. Waldron for a proof of the above lemma.
Lemma: (Weyl’s inequality) Suppose that is a
-matrix with eigenvalues
and singular values
ordered such that
and
. Then
whenever
.
Let be a natural number. Let
be the matrices where
such that
refers to the Kronecker delta function and where the addition is taken modulo
. Then
Therefore,
is the maximum value of
where
.
Theorem: (J. Van Name) Suppose that
whenever
.
2. If are matrices such that
, then
for
.
3. Suppose are matrices. Then the following are equivalent:
i. is a quantum channel with
.
ii. there is an equal-norm tight frame with
for
and
with
for
where if
, then
for
.
4. There are real -matrices
such that
is a quantum channel and
.
5. Let be the matrices in the above example. Then
Proof:
- Suppose that
and
is a quantum channel. Then
.
Therefore, by the arithmetic-geometric mean inequality, we have
Therefore, if is a complex number,
is a complex matrix, and
for
, then
. Therefore,
whenever
is pre-trace preserving. We conclude that
for all
by continuity since the pre-trace preserving maps are dense in
whenever
.
2. If , and
is a quantum channel with
, then
for all
which implies that
for
. By applying continuity, we shall show that if
, and
, then
for
.
Let be the collection of all tuples
which are pre-trace preserving. Let
be the mapping defined by
Let be the mapping where
where
are the eigenvalues of
ordered in such a way so that
. Let
be the mapping defined by letting
Suppose now that and suppose that
. Then for each
, there is a neighborhood
of
where if
, then
Therefore, select a
. Then there is some
and invertible
where if we set
, then
is a quantum channel. Now, for
, let
be the eigenvalues of
and suppose that these eigenvalues are ordered in a way so that
. Then
Therefore, we conclude that and
. We conclude that
Therefore,
so
for
.
3. Suppose that
is a quantum channel and
Then since
, there are vectors
with
for
. In this case,
Therefore,
.
Thus,
Since , we have
This means that there are non-zero constants where
for
.
Now set, . Then
Observe that
is an equal-norm tight frame with
for all
. In this case, if we set
so that
, then
Therefore, we have
.
Now suppose that
is an equal-norm tight frame with
for
and
with
for
where if
, then
for
.
Then
Q.E.D.
Miscellaneous examples
Here are a few examples of where we give bounds for .
Example: (J. Van Name). Suppose that is completely positive. Then
.
Proof: Suppose that are matrices with
whenever
. Let
be
-matrices where
is a quantum channel and
.
In this case, , so
is a quantum channel. However, we have
.
Therefore, . Therefore,
.
Q.E.D.
For the next example, observe that tensor products behave well with regards to the Frobenius norm. Here, whenever
are complex matrices where the formula makes sense. In particular, if
are orthogonal, then
are also orthogonal.
Example: (J. Van Name) Suppose that are
-complex matrices. Then
.
Proof: Suppose that are
-complex matrices where
is a quantum channel and
has
as an eigenvalue with
.
Suppose now that . Then
is a quantum channel, and
, and
has
as an eigenvalue.
is maximized subject to
when
In this case, we have
. Therefore,
. Q.E.D.
We conjecture that .
Proposition: (J. Van Name) Suppose that is a linear operator. Then
Proof: The mapping is a positive semidefinite sesquilinear form. Therefore, there is a positive semidefinite
such that
. Since
is positive semidefinite, there is a basis
for
and non-negative
with
. Now set
for
. In this case, we have
. Now,
whenever
. Furthermore,
.
Suppose now that is a quantum channel. Then
. Therefore,
We conclude that Q.E.D.
Conclusions
We have seen that there are many different sensible notions of a spectral radius of multiple operators, but in many regards, the -spectral radius seems to be the correct way to generalize the spectral radius to multiple operators, and the
-spectral radius seems to be a sensible approximation to the
-spectral radius.
While we have produced a few basic results that initially develop the theory of the -spectral radius, computer calculations indicate that the pure mathematical theory of the
-spectral radius can be developed much further. In particular, if
with
, and
, then our computer calculations suggest that the linear operator
seems to be unique up to simultaneous similarity in most cases, and
seems to inherit at least to some extent many of the properties that
has including rank, realness, symmetry, self-adjointness, positivity, unitarity, etc. One should therefore consider the operator
as an operator obtained by reducing the dimension of the space
to obtain the space
while preserving the properties of
in the best possible way.
The -spectral radius is a mathematical function that should therefore be of interest to pure mathematicians for purely mathematical and aesthetic reasons, but we will apply the
-spectral radius to measure the cryptographic security of block ciphers. The pure mathematical nature of the
-spectral radius should make the
-spectral radius a more appealing measure of security of block ciphers. In a future post, we shall see that the
-spectral radius can be used to measure aspects of cryptographic security of block ciphers.