Submitted:
21 August 2026
Posted:
25 August 2026
Read the latest preprint version here
Abstract
We give a proof of the finite-dimensional scalar form of Crouzeix's conjecture: for every complex matrix A and every rational function r whose poles lie off the numerical range W(A), ||r(A)||_2 <= 2 max_{z in W(A)} |r(z)|. The argument first treats real-analytic strictly convex outer domains. It combines a positive normalized operator-valued double-layer kernel, conjugate Cauchy companions for all powers of finite Blaschke products, Fourier cancellation, and a bounded-sequence recurrence that excludes a singular value larger than 2. Schur approximation and a convex outer approximation then yield the polynomial and rational statements.
Keywords:
Crouzeix conjecture
; numerical range
; spectral set
; finite Blaschke product
; double-layer potential
The theorem below is the sharp constant-2 assertion conjectured by Crouzeix [1]. Crouzeix later obtained the dimension-free bound [2], and the previously published general bound is , due to Crouzeix and Palencia [5]. Two contemporaneous preprints also claim the sharp bound, by Jin [14] and by Lorist and Schwenninger [15]. The present proof is stated only for scalar-valued functions and finite-dimensional matrices.
Theorem 1.
Let , and let
Then every complex polynomial p satisfies
The same inequality holds for every rational function whose poles lie off . Thus , which is compact in finite dimensions, is a 2-spectral set for A.
Proof.
We first prove the inequality with replaced by a particularly regular convex neighborhood. Let be a bounded convex domain with real-analytic strictly convex boundary, and assume that . We shall prove
The conjugate-Cauchy and positive double-layer framework used below originates in Delyon and Delyon [3] and was developed for convex spectral sets and numerical-range functional calculus in [2,4,5]. For a clarification of the symmetrized mechanism and a recent systematic treatment of the double-layer potential, see [6,7]. The finite-fiber kernel and the all-powers recurrence below are the forms used in the present argument.
We use counterclockwise orientation on . At , let be the outward unit normal, regarded as a complex number, and let denote arclength. Thus
For a function u analytic on a neighborhood of , define its conjugate Cauchy transform by
We next establish the boundary kernel that drives the proof. Let be a conformal map. Real-analyticity of the boundary and Schwarz reflection imply that extends conformally across [8]. Let
where B is a nonconstant finite Blaschke product. Thus f is analytic on a neighborhood of and on . If is an arclength parametrization and , then
Indeed, a finite Blaschke product restricts to an orientation-preserving covering of the unit circle. In particular, all boundary solutions of , , are simple.
For , put
This kernel has positive real part at A. In fact, convexity gives
because . If T is strictly accretive, then
Since
we obtain
Let be normalized arclength measure on . The change of variables and (5) give on every sheet of the boundary covering. Hence, for ,
and, for ,
where . These identities may be evaluated at A, since all functions involved are analytic on a neighborhood of . If and , they yield
To see this directly, for unit vectors use positivity first in the pointwise inequality , and then use Cauchy–Schwarz in to obtain
The same scalar argument, with A replaced by any , gives
We need one more consequence of the same kernel. Define
The principal part of at a boundary solution is
by (5). Thus the apparent boundary poles cancel and is analytic across . Furthermore,
Only these Fourier-coefficient identities will be used; therefore no pointwise convergence of a Fourier series is required.
Since , we have . Here is invertible: the spectral mapping theorem and the maximum principle give . A direct multiplication shows
Using , we therefore obtain the exact decomposition
Choose unit singular vectors such that
For every function h analytic on , put
Indeed,
and the second equality follows from .
For , define the real numbers
They are bounded uniformly in m. To make this completely explicit, choose a positively oriented contour of winding number one around . The holomorphic functional calculus gives
Consequently, by (13),
Thus
Fix an integer and, for , set
The sum telescopes after multiplication by :
Fourier orthogonality also gives the exact identity
For completeness, the mean of is
whereas the mean of is
Their difference is precisely .
Put . The three Fourier exponents occurring in are . Expanding the right-hand side and using (15)–() shows that the only nonzero pairings are
It follows from (30) that
This recurrence contradicts the uniform bound (24). Indeed, set
and define and . Induction in (33) gives . If
is the fixed point of this affine recurrence, then
by (19) and (26). Therefore
For large N this gives , contradicting (24). The contradiction proves
for every finite Blaschke product B. The assertion is immediate for a constant unimodular B.
We now pass from finite Blaschke products to all bounded analytic functions. We record the elementary approximation argument. If is analytic, apply the Schur algorithm [9]
As long as , Schwarz’s lemma shows that is again a Schur function. At a chosen level N, replace by a unimodular constant and reverse the recursion by
The resulting is a finite Blaschke product. Each reverse step in (36) raises by one the order of vanishing of the difference from the original Schur iterate. Hence . Since , the generalized Schwarz lemma even gives
If a Schur parameter is unimodular, the algorithm has already terminated in a finite Blaschke product. We have thus proved that finite Blaschke products are locally uniformly dense in the Schur class.
Given with , apply this approximation to . If locally uniformly on , then locally uniformly on . A Cauchy integral over a fixed contour surrounding gives
It remains to let the regular convex domains approach . By the Toeplitz–Hausdorff theorem [10,11], is convex. The standard compression proof recalls that, in dimension at most two, the numerical range is a (possibly degenerate) elliptical disk [12]; it therefore contains the segment joining any two prescribed points of . Compactness follows from continuity on the unit sphere. We briefly justify the needed geometric approximation. For the support-function and curvature-measure facts used below, see [13]. For any compact convex set , its support function
is continuous and the distribution is a nonnegative measure. Convolve with a periodic Poisson kernel, add its uniform approximation error, and then add a positive constant tending to zero. The resulting real-analytic support functions satisfy
The curves
bound real-analytic strictly convex domains with , and in Hausdorff distance.
Apply this construction to . From (1),
Because p is continuous and in Hausdorff distance, the right-hand side tends to . This proves the theorem.
Finally, if r is rational and has no pole on , choose the domains above sufficiently close to that they contain no pole of r. Applying (1) directly to r on each and then taking the same Hausdorff limit gives
This proves the stated spectral-set formulation as well. □
Sharpness.
The constant cannot be reduced. For
the numerical range is the closed disk of radius centered at the origin, whereas . Thus the ratio in the theorem is exactly 2.
Author Contributions
Qinyu Luo: conceptualization, methodology, formal analysis, writing—original draft, writing—review and editing, validation, supervision, and project administration. The author approved the final manuscript and accepts full responsibility for all of its contents.
Funding
The author received no external funding for this work.
Acknowledgments
The author acknowledges the substantial research assistance provided by OpenAI Codex using GPT-5.6 Sol with the Ultra reasoning setting. All AI-assisted output was reviewed and edited by the author.
AI Assistance and Contribution Statement
GPT-5.6 Sol Ultra (OpenAI), accessed through Codex, served as an AI research collaborator. It made substantial non-author contributions through adversarial line-by-line proof auditing; algebraic, Fourier-sign, boundary, and extremal-case checks; design and execution of three-route numerical cross-checks; literature and provenance verification; and English-language editing and release preparation. In accordance with current publication ethics rules, the AI system is not entered in the formal author metadata: it cannot approve the submitted version, hold copyright, or assume legal and scholarly accountability. Qinyu Luo reviewed the outputs, made the final decisions, and assumes complete responsibility for the manuscript.
Data and Code Availability
The manuscript source, compiled PDF, complete Lean 4 formalization, numerical cross-check scripts, machine-readable results, licenses, and citation metadata are available in the public GitHub repository. The immutable v0.1.0 release is permanently archived under the Zenodo version DOI 10.5281/zenodo.22052523; the concept DOI 10.5281/zenodo.22052522 identifies all versions. The GitHub tag archive and Zenodo deposit are byte-identical. The Lean project provides kernel-checked formal verification of the stated finite-dimensional scalar endpoint. The numerical computations are finite-precision falsification tests and are not proofs.
Conflicts of Interest
The author declares no conflict of interest. The views expressed are those of the author and do not necessarily represent ByteDance.
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