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I have just uploaded to the arXiv my paper “Sharp bounds for multilinear curved Kakeya, restriction and oscillatory integral estimates away from the endpoint“, submitted to Mathematika. In this paper I return (after more than a decade’s absence) to one of my first research interests, namely the Kakeya and restriction family of conjectures. The starting point is the following “multilinear Kakeya estimate” first established in the non-endpoint case by Bennett, Carbery, and myself, and then in the endpoint case by Guth (with further proofs and extensions by Bourgain-Guth and Carbery-Valdimarsson:

Theorem 1 (Multilinear Kakeya estimate) Let {\delta > 0} be a radius. For each {j = 1,\dots,d}, let {\mathbb{T}_j} denote a finite family of infinite tubes {T_j} in {{\bf R}^d} of radius {\delta}. Assume the following axiom:

  • (i) (Transversality) whenever {T_j \in \mathbb{T}_j} is oriented in the direction of a unit vector {n_j} for {j =1,\dots,d}, we have

    \displaystyle  \left|\bigwedge_{j=1}^d n_j\right| \geq A^{-1}

    for some {A>0}, where we use the usual Euclidean norm on the wedge product {\bigwedge^d {\bf R}^d}.

Then, for any {p \geq \frac{1}{d-1}}, one has

\displaystyle  \left\| \prod_{j=1}^d \sum_{T_j \in \mathbb{T}_j} 1_{T_j} \right\|_{L^p({\bf R}^d)} \lesssim_{A,p} \delta^{\frac{d}{p}} \prod_{j \in [d]} \# \mathbb{T}_j. \ \ \ \ \ (1)

where {L^p({\bf R}^d)} are the usual Lebesgue norms with respect to Lebesgue measure, {1_{T_j}} denotes the indicator function of {T_j}, and {\# \mathbb{T}_j} denotes the cardinality of {\mathbb{T}_j}.

The original proof of this proceeded using a heat flow monotonicity method, which in my previous post I reinterpreted using a “virtual integration” concept on a fractional Cartesian product space. It turns out that this machinery is somewhat flexible, and can be used to establish some other estimates of this type. The first result of this paper is to extend the above theorem to the curved setting, in which one localises to a ball of radius {O(1)} (and sets {\delta} to be small), but allows the tubes {T_j} to be curved in a {C^2} fashion. If one runs the heat flow monotonicity argument, one now picks up some additional error terms arising from the curvature, but as the spatial scale approaches zero, the tubes become increasingly linear, and as such the error terms end up being an integrable multiple of the main term, at which point one can conclude by Gronwall’s inequality (actually for technical reasons we use a bootstrap argument instead of Gronwall). A key point in this approach is that one obtains optimal bounds (not losing factors of {\delta^{-\varepsilon}} or {\log^{O(1)} \frac{1}{\delta}}), so long as one stays away from the endpoint case {p=\frac{1}{d-1}} (which does not seem to be easily treatable by the heat flow methods). Previously, the paper of Bennett, Carbery, and myself was able to use an induction on scale argument to obtain a curved multilinear Kakeya estimate losing a factor of {\log^{O(1)} \frac{1}{\delta}} (after optimising the argument); later arguments of Bourgain-Guth and Carbery-Valdimarsson, based on algebraic topology methods, could also obtain a curved multilinear Kakeya estimate without such losses, but only in the algebraic case when the tubes were neighbourhoods of algebraic curves of bounded degree.

Perhaps more interestingly, we are also able to extend the heat flow monotonicity method to apply directly to the multilinear restriction problem, giving the following global multilinear restriction estimate:

Theorem 2 (Multilinear restriction theorem) Let {\frac{1}{d-1} < p \leq \infty} be an exponent, and let {A \geq 2} be a parameter. Let {M} be a sufficiently large natural number, depending only on {d}. For {j \in [d]}, let {U_j} be an open subset of {B^{d-1}(0,A)}, and let {h_j: U_j \rightarrow {\bf R}} be a smooth function obeying the following axioms:

  • (i) (Regularity) For each {j \in [d]} and {\xi \in U_j}, one has

    \displaystyle  |\nabla_\xi^{\otimes m} \otimes h_j(\xi)| \leq A \ \ \ \ \ (2)

    for all {1 \leq m \leq M}.

  • (ii) (Transversality) One has

    \displaystyle  \left| \bigwedge_{j \in [d]} (-\nabla_\xi h_j(\xi_j),1) \right| \geq A^{-1}

    whenever {\xi_j \in U_j} for {j \in [d]}.

Let {U_{j,1/A} \subset U_j} be the sets

\displaystyle  U_{j,1/A} := \{ \xi \in U_j: B^{d-1}(\xi,1/A) \subset U_j \}. \ \ \ \ \ (3)

Then one has

\displaystyle  \left\| \prod_{j \in [d]} {\mathcal E}_j f_j \right\|_{L^{2p}({\bf R}^d)} \leq A^{O(1)} \left(d-1-\frac{1}{p}\right)^{-O(1)} \prod_{j \in [d]} \|f_j \|_{L^2(U_{j,1/A})}

for any {f_j \in L^2(U_{j,1/A} \rightarrow {\bf C})}, {j \in [d]}, extended by zero outside of {U_{j,1/A}}, and {{\mathcal E}_j} denotes the extension operator

\displaystyle  {\mathcal E}_j f_j( x', x_d ) := \int_{U_j} e^{2\pi i (x' \xi^T + x_d h_j(\xi))} f_j(\xi)\ d\xi.

Local versions of such estimate, in which {L^{2p}({\bf R}^d)} is replaced with {L^{2p}(B^d(0,R))} for some {R \geq 2}, and one accepts a loss of the form {\log^{O(1)} R}, were already established by Bennett, Carbery, and myself using an induction on scale argument. In a later paper of Bourgain-Guth these losses were removed by “epsilon removal lemmas” to recover Theorme 2, but only in the case when all the hypersurfaces involved had curvatures bounded away from zero.

There are two main new ingredients in the proof of Theorem 2. The first is to replace the usual induction on scales scheme to establish multilinear restriction by a “ball inflation” induction on scales scheme that more closely resembles the proof of decoupling theorems. In particular, we actually prove the more general family of estimates

\displaystyle  \left\| \prod_{j \in [d]} E_{r}[{\mathcal E}_j f_j] \right\|_{L^{p}({\bf R}^d)} \leq A^{O(1)} \left(d-1 - \frac{1}{p}\right)^{O(1)} r^{\frac{d}{p}} \prod_{j \in [d]} \| f_j \|_{L^2(U_{j,1/A})}^2

where {E_r} denotes the local energies

\displaystyle  E_{r}[f](x',x_d) := \int_{B^{d-1}(x',r)} |f(y',x_d)|^2\ dy'

(actually for technical reasons it is more convenient to use a smoother weight than the strict cutoff to the disk {B^{d-1}(x',r)}). With logarithmic losses, it is not difficult to establish this estimate by an upward induction on {r}. To avoid such losses we use the heat flow monotonicity method. Here we run into the issue that the extension operators {{\mathcal E}_j f_j} are complex-valued rather than non-negative, and thus would not be expected to obey many good montonicity properties. However, the local energies {E_r[{\mathcal E}_j f_j]} can be expressed in terms of the magnitude squared of what is essentially the Gabor transform of {{\mathcal E}_j f_j}, and these are non-negative; furthermore, the dispersion relation associated to the extension operators {{\mathcal E}_j f_j} implies that these Gabor transforms propagate along tubes, so that the situation becomes quite similar (up to several additional lower order error terms) to that in the multilinear Kakeya problem. (This can be viewed as a continuous version of the usual wave packet decomposition method used to relate restriction and Kakeya problems, which when combined with the heat flow monotonicity method allows for one to use a continuous version of induction on scales methods that do not concede any logarithmic factors.)

Finally, one can combine the curved multilinear Kakeya result with the multilinear restriction result to obtain estimates for multilinear oscillatory integrals away from the endpoint. Again, this sort of implication was already established in the previous paper of Bennett, Carbery, and myself, but the arguments there had some epsilon losses in the exponents; here we were able to run the argument more carefully and avoid these losses.

Earlier this month, Hao Huang (who, incidentally, was a graduate student here at UCLA) gave a remarkably short proof of a long-standing problem in theoretical computer science known as the sensitivity conjecture. See for instance this blog post of Gil Kalai for further discussion and links to many other online discussions of this result. One formulation of the theorem proved is as follows. Define the {n}-dimensional hypercube graph {Q_n} to be the graph with vertex set {({\bf Z}/2{\bf Z})^n}, and with every vertex {v \in ({\bf Z}/2{\bf Z})^n} joined to the {n} vertices {v + e_1,\dots,v+e_n}, where {e_1,\dots,e_n} is the standard basis of {({\bf Z}/2{\bf Z})^n}.

Theorem 1 (Lower bound on maximum degree of induced subgraphs of hypercube) Let {E} be a set of at least {2^{n-1}+1} vertices in {Q_n}. Then there is a vertex in {E} that is adjacent (in {Q_n}) to at least {\sqrt{n}} other vertices in {E}.

The bound {\sqrt{n}} (or more precisely, {\lceil \sqrt{n} \rceil}) is completely sharp, as shown by Chung, Furedi, Graham, and Seymour; we describe this example below the fold. When combined with earlier reductions of Gotsman-Linial and Nisan-Szegedy; we give these below the fold also.

Let {A = (a_{vw})_{v,w \in ({\bf Z}/2{\bf Z})^n}} be the adjacency matrix of {Q_n} (where we index the rows and columns directly by the vertices in {({\bf Z}/2{\bf Z})^n}, rather than selecting some enumeration {1,\dots,2^n}), thus {a_{vw}=1} when {w = v+e_i} for some {i=1,\dots,n}, and {a_{vw}=0} otherwise. The above theorem then asserts that if {E} is a set of at least {2^{n-1}+1} vertices, then the {E \times E} minor {(a_{vw})_{v,w \in E}} of {A} has a row (or column) that contains at least {\sqrt{n}} non-zero entries.

The key step to prove this theorem is the construction of rather curious variant {\tilde A} of the adjacency matrix {A}:

Proposition 2 There exists a {({\bf Z}/2{\bf Z})^n \times ({\bf Z}/2{\bf Z})^n} matrix {\tilde A = (\tilde a_{vw})_{v,w \in ({\bf Z}/2{\bf Z})^n}} which is entrywise dominated by {A} in the sense that

\displaystyle  |\tilde a_{vw}| \leq a_{vw} \hbox{ for all } v,w \in ({\bf Z}/2{\bf Z})^n \ \ \ \ \ (1)

and such that {\tilde A} has {\sqrt{n}} as an eigenvalue with multiplicity {2^{n-1}}.

Assuming this proposition, the proof of Theorem 1 can now be quickly concluded. If we view {\tilde A} as a linear operator on the {2^n}-dimensional space {\ell^2(({\bf Z}/2{\bf Z})^n)} of functions of {({\bf Z}/2{\bf Z})^n}, then by hypothesis this space has a {2^{n-1}}-dimensional subspace {V} on which {\tilde A} acts by multiplication by {\sqrt{n}}. If {E} is a set of at least {2^{n-1}+1} vertices in {Q_n}, then the space {\ell^2(E)} of functions on {E} has codimension at most {2^{n-1}-1} in {\ell^2(({\bf Z}/2{\bf Z})^n)}, and hence intersects {V} non-trivially. Thus the {E \times E} minor {\tilde A_E} of {\tilde A} also has {\sqrt{n}} as an eigenvalue (this can also be derived from the Cauchy interlacing inequalities), and in particular this minor has operator norm at least {\sqrt{n}}. By Schur’s test, this implies that one of the rows or columns of this matrix has absolute values summing to at least {\sqrt{n}}, giving the claim.

Remark 3 The argument actually gives a strengthening of Theorem 1: there exists a vertex {v_0} of {E} with the property that for every natural number {k}, there are at least {n^{k/2}} paths of length {k} in the restriction {Q_n|_E} of {Q_n} to {E} that start from {v_0}. Indeed, if we let {(u_v)_{v \in E}} be an eigenfunction of {\tilde A} on {\ell^2(E)}, and let {v_0} be a vertex in {E} that maximises the value of {|u_{v_0}|}, then for any {k} we have that the {v_0} component of {\tilde A_E^k (u_v)_{v \in E}} is equal to {n^{k/2} |u_{v_0}|}; on the other hand, by the triangle inequality, this component is at most {|u_{v_0}|} times the number of length {k} paths in {Q_n|_E} starting from {v_0}, giving the claim.

This argument can be viewed as an instance of a more general “interlacing method” to try to control the behaviour of a graph {G} on all large subsets {E} by first generating a matrix {\tilde A} on {G} with very good spectral properties, which are then partially inherited by the {E \times E} minor of {\tilde A} by interlacing inequalities. In previous literature using this method (see e.g., this survey of Haemers, or this paper of Wilson), either the original adjacency matrix {A}, or some non-negatively weighted version of that matrix, was used as the controlling matrix {\tilde A}; the novelty here is the use of signed controlling matrices. It will be interesting to see what further variants and applications of this method emerge in the near future. (Thanks to Anurag Bishoi in the comments for these references.)

The “magic” step in the above argument is constructing {\tilde A}. In Huang’s paper, {\tilde A} is constructed recursively in the dimension {n} in a rather simple but mysterious fashion. Very recently, Roman Karasev gave an interpretation of this matrix in terms of the exterior algebra on {{\bf R}^n}. In this post I would like to give an alternate interpretation in terms of the operation of twisted convolution, which originated in the theory of the Heisenberg group in quantum mechanics.

Firstly note that the original adjacency matrix {A}, when viewed as a linear operator on {\ell^2(({\bf Z}/2{\bf Z})^n)}, is a convolution operator

\displaystyle  A f = f * \mu


\displaystyle \mu(x) := \sum_{i=1}^n 1_{x=e_i}

is the counting measure on the standard basis {e_1,\dots,e_n}, and {*} denotes the ordinary convolution operation

\displaystyle  f * g(x) := \sum_{y \in ({\bf Z}/2{\bf Z})^n} f(y) g(x-y) = \sum_{y_1+y_2 = x} f(y_1) g(y_2).

As is well known, this operation is commutative and associative. Thus for instance the square {A^2} of the adjacency operator {A} is also a convolution operator

\displaystyle  A^2 f = f * (\mu * \mu)(x)

where the convolution kernel {\mu * \mu} is moderately complicated:

\displaystyle  \mu*\mu(x) = n \times 1_{x=0} + \sum_{1 \leq i < j \leq n} 2 \times 1_{x = e_i + e_j}.

The factor {2} in this expansion comes from combining the two terms {1_{x=e_i} * 1_{x=e_j}} and {1_{x=e_j} * 1_{x=e_i}}, which both evaluate to {1_{x=e_i+e_j}}.

More generally, given any bilinear form {B: ({\bf Z}/2{\bf Z})^n \times ({\bf Z}/2{\bf Z})^n \rightarrow {\bf Z}/2{\bf Z}}, one can define the twisted convolution

\displaystyle  f *_B g(x) := \sum_{y \in ({\bf Z}/2{\bf Z})^n} (-1)^{B(y,x-y)} f(y) g(x-y)

\displaystyle  = \sum_{y_1+y_2=x} (-1)^{B(y_1,y_2)} f(y_1) g(y_2)

of two functions {f,g \in \ell^2(({\bf Z}/2{\bf Z})^n)}. This operation is no longer commutative (unless {B} is symmetric). However, it remains associative; indeed, one can easily compute that

\displaystyle  (f *_B g) *_B h(x) = f *_B (g *_B h)(x)

\displaystyle = \sum_{y_1+y_2+y_3=x} (-1)^{B(y_1,y_2)+B(y_1,y_3)+B(y_2,y_3)} f(y_1) g(y_2) h(y_3).

In particular, if we define the twisted convolution operator

\displaystyle  A_B f(x) := f *_B \mu(x)

then the square {A_B^2} is also a twisted convolution operator

\displaystyle  A_B^2 f = f *_B (\mu *_B \mu)

and the twisted convolution kernel {\mu *_B \mu} can be computed as

\displaystyle  \mu *_B \mu(x) = (\sum_{i=1}^n (-1)^{B(e_i,e_i)}) 1_{x=0}

\displaystyle + \sum_{1 \leq i < j \leq n} ((-1)^{B(e_i,e_j)} + (-1)^{B(e_j,e_i)}) 1_{x=e_i+e_j}.

For general bilinear forms {B}, this twisted convolution is just as messy as {\mu * \mu} is. But if we take the specific bilinear form

\displaystyle  B(x,y) := \sum_{1 \leq i < j \leq n} x_i y_j \ \ \ \ \ (2)

then {B(e_i,e_i)=0} for {1 \leq i \leq n} and {B(e_i,e_j)=1, B(e_j,e_i)=0} for {1 \leq i < j \leq n}, and the above twisted convolution simplifies to

\displaystyle  \mu *_B \mu(x) = n 1_{x=0}

and now {A_B^2} is very simple:

\displaystyle  A_B^2 f = n f.

Thus the only eigenvalues of {A_B} are {+\sqrt{n}} and {-\sqrt{n}}. The matrix {A_B} is entrywise dominated by {A} in the sense of (1), and in particular has trace zero; thus the {+\sqrt{n}} and {-\sqrt{n}} eigenvalues must occur with equal multiplicity, so in particular the {+\sqrt{n}} eigenvalue occurs with multiplicity {2^{n-1}} since the matrix has dimensions {2^n \times 2^n}. This establishes Proposition 2.

Remark 4 Twisted convolution {*_B} is actually just a component of ordinary convolution, but not on the original group {({\bf Z}/2{\bf Z})^n}; instead it relates to convolution on a Heisenberg group extension of this group. More specifically, define the Heisenberg group {H} to be the set of pairs {(x, t) \in ({\bf Z}/2{\bf Z})^n \times ({\bf Z}/2{\bf Z})} with group law

\displaystyle  (x,t) \cdot (y,s) := (x+y, t+s+B(x,y))

and inverse operation

\displaystyle  (x,t)^{-1} = (-x, -t+B(x,x))

(one can dispense with the negative signs here if desired, since we are in characteristic two). Convolution on {H} is defined in the usual manner: one has

\displaystyle  F*G( (x,t) ) := \sum_{(y,s) \in H} F(y,s) G( (y,s)^{-1} (x,t) )

for any {F,G \in \ell^2(H)}. Now if {f \in \ell^2(({\bf Z}/2{\bf Z})^n)} is a function on the original group {({\bf Z}/2{\bf Z})^n}, we can define the lift {\tilde f \in \ell^2(H)} by the formula

\displaystyle  \tilde f(x,t) := (-1)^t f(x)

and then by chasing all the definitions one soon verifies that

\displaystyle  \tilde f * \tilde g = 2 \widetilde{f *_B g}

for any {f,g \in \ell^2(({\bf Z}/2{\bf Z})^n)}, thus relating twisted convolution {*_B} to Heisenberg group convolution {*}.

Remark 5 With the twisting by the specific bilinear form {B} given by (2), convolution by {1_{x=e_i}} and {1_{x=e_j}} now anticommute rather than commute. This makes the twisted convolution algebra {(\ell^2(({\bf Z}/2{\bf Z})^n), *_B)} isomorphic to a Clifford algebra {Cl({\bf R}^n,I_n)} (the real or complex algebra generated by formal generators {v_1,\dots,v_n} subject to the relations {(v_iv_j+v_jv_i)/2 = 1_{i=j}} for {i,j=1,\dots,n}) rather than the commutative algebra more familiar to abelian Fourier analysis. This connection to Clifford algebra (also observed independently by Tom Mrowka and by Daniel Matthews) may be linked to the exterior algebra interpretation of the argument in the recent preprint of Karasev mentioned above.

Remark 6 One could replace the form (2) in this argument by any other bilinear form {B'} that obeyed the relations {B'(e_i,e_i)=0} and {B'(e_i,e_j) + B'(e_j,e_i)=1} for {i \neq j}. However, this additional level of generality does not add much; any such {B'} will differ from {B} by an antisymmetric form {C} (so that {C(x,x) = 0} for all {x}, which in characteristic two implied that {C(x,y) = C(y,x)} for all {x,y}), and such forms can always be decomposed as {C(x,y) = C'(x,y) + C'(y,x)}, where {C'(x,y) := \sum_{i<j} C(e_i,e_j) x_i y_j}. As such, the matrices {A_B} and {A_{B'}} are conjugate, with the conjugation operator being the diagonal matrix with entries {(-1)^{C'(x,x)}} at each vertex {x}.

Remark 7 (Added later) This remark combines the two previous remarks. One can view any of the matrices {A_{B'}} in Remark 6 as components of a single canonical matrix {A_{Cl}} that is still of dimensions {({\bf Z}/2{\bf Z})^n \times ({\bf Z}/2{\bf Z})^n}, but takes values in the Clifford algebra {Cl({\bf R}^n,I_n)} from Remark 5; with this “universal algebra” perspective, one no longer needs to make any arbitrary choices of form {B}. More precisely, let {\ell^2( ({\bf Z}/2{\bf Z})^n \rightarrow Cl({\bf R}^n,I_n))} denote the vector space of functions {f: ({\bf Z}/2{\bf Z})^n \rightarrow Cl({\bf R}^n,I_n)} from the hypercube to the Clifford algebra; as a real vector space, this is a {2^{2n}} dimensional space, isomorphic to the direct sum of {2^n} copies of {\ell^2(({\bf Z}/2{\bf Z})^n)}, as the Clifford algebra is itself {2^n} dimensional. One can then define a canonical Clifford adjacency operator {A_{Cl}} on this space by

\displaystyle  A_{Cl} f(x) := \sum_{i=1}^n f(x+e_i) v_i

where {v_1,\dots,v_n} are the generators of {Cl({\bf R}^n,I_n)}. This operator can either be identified with a Clifford-valued {2^n \times 2^n} matrix or as a real-valued {2^{2n} \times 2^{2n}} matrix. In either case one still has the key algebraic relations {A_{Cl}^2 = n} and {\mathrm{tr} A_{Cl} = 0}, ensuring that when viewed as a real {2^{2n} \times 2^{2n}} matrix, half of the eigenvalues are equal to {+\sqrt{n}} and half equal to {-\sqrt{n}}. One can then use this matrix in place of any of the {A_{B'}} to establish Theorem 1 (noting that Schur’s test continues to work for Clifford-valued matrices because of the norm structure on {Cl({\bf R}^n,I_n)}).

To relate {A_{Cl}} to the real {2^n \times 2^n} matrices {A_{B'}}, first observe that each point {x} in the hypercube {({\bf Z}/2{\bf Z})^n} can be associated with a one-dimensional real subspace {\ell_x} (i.e., a line) in the Clifford algebra {Cl({\bf R}^n,I_n)} by the formula

\displaystyle  \ell_{e_{i_1} + \dots + e_{i_k}} := \mathrm{span}_{\bf R}( v_{i_1} \dots v_{i_k} )

for any {i_1,\dots,i_k \in \{1,\dots,n\}} (note that this definition is well-defined even if the {i_1,\dots,i_k} are out of order or contain repetitions). This can be viewed as a discrete line bundle over the hypercube. Since {\ell_{x+e_i} = \ell_x e_i} for any {i}, we see that the {2^n}-dimensional real linear subspace {V} of {\ell^2( ({\bf Z}/2{\bf Z})^n \rightarrow Cl({\bf R}^n,I_n))} of sections of this bundle, that is to say the space of functions {f: ({\bf Z}/2{\bf Z})^n \rightarrow Cl({\bf R}^n,I_n)} such that {f(x) \in \ell_x} for all {x \in ({\bf Z}/2{\bf Z})^n}, is an invariant subspace of {A_{Cl}}. (Indeed, using the left-action of the Clifford algebra on {\ell^2( ({\bf Z}/2{\bf Z})^n \rightarrow Cl({\bf R}^n,I_n))}, which commutes with {A_{Cl}}, one can naturally identify {\ell^2( ({\bf Z}/2{\bf Z})^n \rightarrow Cl({\bf R}^n,I_n))} with {Cl({\bf R}^n,I_n) \otimes V}, with the left action of {Cl({\bf R}^n,I_n)} acting purely on the first factor and {A_{Cl}} acting purely on the second factor.) Any trivialisation of this line bundle lets us interpret the restriction {A_{Cl}|_V} of {A_{Cl}} to {V} as a real {2^n \times 2^n} matrix. In particular, given one of the bilinear forms {B'} from Remark 6, we can identify {V} with {\ell^2(({\bf Z}/2{\bf Z})^n)} by identifying any real function {f \in \ell^2( ({\bf Z}/2{\bf Z})^n)} with the lift {\tilde f \in V} defined by

\displaystyle  \tilde f(e_{i_1} + \dots + e_{i_k}) := (-1)^{\sum_{1 \leq j < j' \leq k} B'(e_{i_j}, e_{i_{j'}})}

\displaystyle f(e_{i_1} + \dots + e_{i_k}) v_{i_1} \dots v_{i_k}

whenever {1 \leq i_1 < \dots < i_k \leq n}. A somewhat tedious computation using the properties of {B'} then eventually gives the intertwining identity

\displaystyle  A_{Cl} \tilde f = \widetilde{A_{B'} f}

and so {A_{B'}} is conjugate to {A_{Cl}|_V}.

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