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Computer Science > Data Structures and Algorithms

Title: On approximability of the Permanent of PSD matrices

Abstract: We study the complexity of approximating the permanent of a positive semidefinite matrix $A\in \mathbb{C}^{n\times n}$.
1. We design a new approximation algorithm for $\mathrm{per}(A)$ with approximation ratio $e^{(0.9999 + \gamma)n}$, exponentially improving upon the current best bound of $e^{(1+\gamma-o(1))n}$ [AGOS17,YP22]. Here, $\gamma \approx 0.577$ is Euler's constant.
2. We prove that it is NP-hard to approximate $\mathrm{per}(A)$ within a factor $e^{(\gamma-\epsilon)n}$ for any $\epsilon>0$. This is the first exponential hardness of approximation for this problem. Along the way, we prove optimal hardness of approximation results for the $\|\cdot\|_{2\to q}$ ``norm'' problem of a matrix for all $-1 < q < 2$.
Subjects: Data Structures and Algorithms (cs.DS); Computational Complexity (cs.CC)
Cite as: arXiv:2404.10959 [cs.DS]
  (or arXiv:2404.10959v1 [cs.DS] for this version)

Submission history

From: Ansh Nagda [view email]
[v1] Tue, 16 Apr 2024 23:54:55 GMT (33kb)

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