A Walk From Free Probability to Matrix Discrepancy II: Weaver's Problem and the Kadison-Singer Conjecture

📅 2026-09-16
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🤖 AI Summary
本文通过设计一个在多项式时间内运行的确定性算法,解决了Weaver的不平等问题,并为Kadison-Singer猜想提供了有效解法,算法基于矩阵差异分析。
📝 Abstract
\cite{mss2015} proved Weaver's discrepancy result existentially, resolving the Kadison--Singer conjecture . Finding such signs efficiently for general inputs remained an open algorithmic question. In the real-arithmetic model, we give a deterministic algorithm running in polynomial time with discrepancy at most $35\sqrt\varepsilon$. The algorithm walks from the origin of the hypercube to a vertex, fixing coordinates as they hit a face. Its potential measures a soft spectral edge of the discrepancy matrix perturbed by an operator-valued free semicircular element. The perturbation's covariance vanishes as the coefficients reach their endpoints. Inspired by the free interpolation approach of Bandeira, Boedihardjo, and van Handel \cite{bbvh2023}, we combine Lehner's variational formula \cite{lehner1999} with spectral Tsallis--$1/2$ regularization used in \cite{allenZhuLiaoOrecchia2015} and \cite{pesentivladu2026}. The resulting potential has a finite-dimensional SDP formulation, allowing the discrepancy and remaining covariance to be analyzed together. We analyze the optimizer's stability through the linearized Karush--Kuhn--Tucker (KKT) system of a regularized min--max problem, whose stationarity equations are related to the matrix Dyson equation \cite{erdos2019}. This gives the movement rule: either a coordinate can move toward its nearer endpoint at small spectral cost, or a low-curvature direction orthogonal to the current coefficient vector allows further progress. Choosing the better sign of this direction controls discrepancy while increasing the squared distance from the origin. Upcoming work \cite{kathuria2026higherRank} will address higher-rank Kadison-Singer and spectrally thin trees. Lean formalizations of our main discrepancy theorems have been completed and will be released shortly.
Problem

Research questions and friction points this paper is trying to address.

Weaver's discrepancy
Kadison-Singer conjecture
deterministic algorithm
polynomial time
Innovation

Methods, ideas, or system contributions that make the work stand out.

deterministic algorithm
polynomial time
spectral Tsallis-1/2 regularization
Karush-Kuhn-Tucker (KKT) system
matrix discrepancy
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