Shifted Anticoncentration for Real Gram Hafnians and Symmetric Gaussian Hafnians

• URL: http://arxiv.org/abs/2609.06526v1
• Date: Sun, 06 Sep 2026 10:47:33 GMT
• Title: Shifted Anticoncentration for Real Gram Hafnians and Symmetric Gaussian Hafnians
• Abstract summary: We prove a uniform shifted anticoncentration theorem for the hafnian of a real Gaussian Gram matrix under an explicit condition on the row dimension.<n>At fixed hafnian order, a rescaled limit as the row dimension grows yields bounds for the hafnian of a real symmetric symmetric matrix with independent entries above the diagonal.
• Score: 2.8224889996383395
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: We prove a uniform shifted anticoncentration theorem for the hafnian of a real Gaussian Gram matrix under an explicit condition on the row dimension. After normalization by its root mean square, the law has a bounded continuous density, maximal at zero, and every interval has probability bounded by an explicit coefficient times its radius. Under suitable growth conditions on the row dimension, this coefficient grows at most polynomially in the hafnian order, meaning half the dimension of the Gram matrix. We also compute the exact second moment. The proof exploits the perfect matching structure, combining conditional Gaussian representations, row suspension, and bilinear interpolation to control an inverse moment of the conditional variance. At fixed hafnian order, a rescaled limit as the row dimension grows yields corresponding bounds for the hafnian of a real symmetric Gaussian matrix with independent entries above the diagonal.

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