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Complexity of mixed Schatten norms of quantum maps

Jan Kochanowski, Omar Fawzi, Cambyse Rouzé

TL;DR

This work maps the computational landscape of mixed Schatten norms and their cb variants for quantum maps, revealing a sharp contrast between regimes: non-hypercontractive regions admit efficient algorithms (via convex optimization and quantum Boyd-type methods), while key CP and EB-difference settings become NP-hard. Central to the hardness results is a 2-Out-of-4-SAT reduction that encodes SAT solutions into optimal pure-state outputs of carefully crafted channels. In the cb framework, the paper derives convex-optimization reformulations that render $cb,1\to p$ norms tractable for arbitrary maps, including non-CP ones, and shows non-hypercontractive cb norms of CP maps collapse to their non-cb counterparts. Overall, the results delineate when quantum norm computations are feasible and when they inherit classical NP-hardness, with practical implications for channel distinguishability and open-system dynamics.

Abstract

We study the complexity of computing the mixed Schatten $\|Φ\|_{q\to p}$ norms of linear maps $Φ$ between matrix spaces. When $Φ$ is completely positive, we show that $\| Φ\|_{q \to p}$ can be computed efficiently when $q \geq p$. The regime $q \geq p$ is known as the non-hypercontractive regime and is also known to be easy for the mixed vector norms $\ell_{q} \to \ell_{p}$ [Boyd, 1974]. However, even for entanglement-breaking completely-positive trace-preserving maps $Φ$, we show that computing $\| Φ\|_{1 \to p}$ is $\mathsf{NP}$-complete when $p>1$. Moving beyond the completely-positive case and considering $Φ$ to be difference of entanglement breaking completely-positive trace-preserving maps, we prove that computing $\| Φ\|^+_{1 \to 1}$ is $\mathsf{NP}$-complete. In contrast, for the completely-bounded (cb) case, we describe a polynomial-time algorithm to compute $\|Φ\|_{cb,1\to p}$ and $\|Φ\|^+_{cb,1\to p}$ for any linear map $Φ$ and $p\geq1$.

Complexity of mixed Schatten norms of quantum maps

TL;DR

This work maps the computational landscape of mixed Schatten norms and their cb variants for quantum maps, revealing a sharp contrast between regimes: non-hypercontractive regions admit efficient algorithms (via convex optimization and quantum Boyd-type methods), while key CP and EB-difference settings become NP-hard. Central to the hardness results is a 2-Out-of-4-SAT reduction that encodes SAT solutions into optimal pure-state outputs of carefully crafted channels. In the cb framework, the paper derives convex-optimization reformulations that render norms tractable for arbitrary maps, including non-CP ones, and shows non-hypercontractive cb norms of CP maps collapse to their non-cb counterparts. Overall, the results delineate when quantum norm computations are feasible and when they inherit classical NP-hardness, with practical implications for channel distinguishability and open-system dynamics.

Abstract

We study the complexity of computing the mixed Schatten norms of linear maps between matrix spaces. When is completely positive, we show that can be computed efficiently when . The regime is known as the non-hypercontractive regime and is also known to be easy for the mixed vector norms [Boyd, 1974]. However, even for entanglement-breaking completely-positive trace-preserving maps , we show that computing is -complete when . Moving beyond the completely-positive case and considering to be difference of entanglement breaking completely-positive trace-preserving maps, we prove that computing is -complete. In contrast, for the completely-bounded (cb) case, we describe a polynomial-time algorithm to compute and for any linear map and .

Paper Structure

This paper contains 25 sections, 36 theorems, 159 equations, 2 figures.

Key Result

Theorem 1.1

Computing $\|\Phi-\Psi\|_{1\to 1}^+$ is $\mathsf{NP}$-complete for quantum channels $\Phi, \Psi$. In addition the channels may be assumed to be entanglement-breaking, see equ:def.eb.

Figures (2)

  • Figure 1: (a) known complexity results on approximating mixed $q\to p$ matrix norms of any matrix on top and of a positivity preserving one on bottom, see \ref{['sec:classicalComplexities']} for details Bhattiprolu.2019Bhattiprolu.2023Bhaskara.2011Barak.2012Daureen.2007Brandao.2015. In (b) and (c) our new complexity results for computing, respectively, the mixed Schatten (\ref{['sec:mixed.Schatten']}), and mixed completely bounded Schatten norms (\ref{['sec:mixed.cb.Schatten']}) of a linear map $\Phi:\mathop{\mathrm{\mathbb{C}}}\nolimits^{n\times n}\to \mathop{\mathrm{\mathbb{C}}}\nolimits^{m\times m}$ on top and on bottom when the map is promised to be completely positive (CP). Included the references to our results in \ref{['sec:summary.of.results']}Red hereby signifies $\mathsf{NP}$-hardness and green the existence of an efficient algorithm. The white areas represent unknown complexities. The orange dot represents hardness for the positive version of the problem, i.e. the $\|\cdot\|^+_{1\to 1}$.
  • Figure 2: A diagram visualizing mixed $q\to p$ norms, with $1\leq q\leq\infty$ on the horizontal and $1\leq p\leq \infty$ on the vertical axese. The region $\infty>p>q>1$, (the upper left triangle without borders) is called the hypercontractive region. Its complement is the non-hypercontractive region, i.e., the lower right triangle with borders. By Hölder duality computing the $q\to p$ norm of some linear map is equivalent to computing the $q^\prime \to p^\prime$ of its adjoint map.

Theorems & Definitions (93)

  • Theorem 1.1: $\mathsf{NP}$-completeness of $\|\cdot\|^+_{1\to 1}$, informal, \ref{['thm:thm1to1']}
  • Theorem 1.2: $\mathsf{NP}$-completeness of CP $\|\cdot\|_{1\to p}$, $p>1$, informal, \ref{['thm:1top.hardness']}
  • Proposition 1.3: $\mathsf{NP}$-hardness of mixed Schatten norms, informal, \ref{['cor:generic.Schatten.hardness']}
  • Lemma 1.4: Efficient algorithm for CP $q\geq p$, informal, \ref{['thm:ellipsoid.result']}, \ref{['lem:cb.equals.non.cb']}
  • Theorem 1.5: Quantum Boyd's algorithm, informal, \ref{['thm:Quantum.Boyds']} and \ref{['thm:strict.positive.q.Boyds']}
  • Theorem 1.6: Efficient algorithm for ${cb,1\to p}$, informal, \ref{['thm:efficient.cb.1top']}
  • Definition : 2-Out-of-4-SAT
  • Lemma 1.7: Hölder duality simplification
  • proof
  • Definition 2.1
  • ...and 83 more