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arXiv:2210.15210

The signaling dimension of physical systems

Michele Dall’Arno

Published Aug 25, 2022• 2 citations
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Abstract

The signaling dimension of a physical system is the minimum dimension of a classical channel that can reproduce the set of input-output correlations attainable by the given system. Here we put the signaling dimension into perspective by reviewing some of the main known results on the topic, starting from Frenkel and Weiner's 2015 breakthrough showing that the signaling dimension of any quantum system is equal to its Hilbert space dimension.

DOI
10.22331/qv-2022-08-25-66

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The signaling dimension of a physical system is the minimum dimension of a classical channel that can reproduce the set of input-output correlations attainable by the given system. Here we put the signaling dimension into perspective by reviewing some of the main known results on the topic, starting from Frenkel and Weiner's 2015 breakthrough showing that the signaling dimension of any quantum system is equal to its Hilbert space dimension.
The signaling dimension of a given physical system quantifies the minimum dimension of a classical system required to reproduce all input/output correlations of the given system. Thus, unlike other dimension measures - such as the dimension of the linear space or the maximum number of (jointly or pairwise) perfectly discriminable states - which examine the correlation space only along a single direction, the signaling dimension does not depend on the arbitrary choice of a specific operational task. In this sense, the signaling dimension summarizes the structure of the entire set of input/output correlations consistent with a given system in a single scalar quantity. For quantum theory, it was recently proved by Frenkel and Weiner in a seminal result that the signaling dimension coincides with the Hilbert space dimension. Here, we derive analytical and algorithmic techniques to compute the signaling dimension for any given system of any given generalized probabilistic theory. We prove that it suffices to consider extremal measurements with ray-extremal effects, and we bound the number of elements of any such measurement in terms of the linear dimension. For systems with a finite number of extremal effects, we recast the problem of characterizing the extremal measurements with ray-extremal effects as the problem of deriving the vertex description of a polytope given its face description, which can be conveniently solved by standard techniques such as the double description algorithm. For each such measurement, we recast the computation of the signaling dimension as a linear program, and we propose a combinatorial branch and bound algorithm to reduce its size. We apply our results to derive the extremal measurements with ray-extremal effects of a composition of two square bits (or squits) and prove that their signaling dimension is five, even though each squit has a signaling dimension equal to two.
The signaling dimension of any given physical system represents its classical simulation cost, that is, the minimum dimension of a classical system capable of reproducing all the input/output correlations of the given system. The signaling dimension landscape is vastly unexplored; the only non-trivial systems whose signaling dimension is known -- other than quantum systems -- are the octahedron and the composition of two squares.}{Building on previous results by Matsumoto, Kimura, and Frenkel, our first result consists of deriving bounds on the signaling dimension of any system as a function of its Minkowski measure of asymmetry. We use such bounds to prove that the signaling dimension of any two-dimensional system (i.e. with two-dimensional set of admissible states, such as polygons and the real qubit) is two if and only if such a set is centrally symmetric, and three otherwise, thus conclusively settling the problem of the signaling dimension for such systems.} {Guided by the relevance of symmetries in the two dimensional case, we propose a branch and bound division-free algorithm for the exact computation of the symmetries of any given polytope, in polynomial time in the number of vertices and in factorial time in the dimension of the space. Our second result then consist of providing an algorithm for the exact computation of the signaling dimension of any given system, that outperforms previous proposals by exploiting the aforementioned bounds to improve its pruning techniques and incorporating as a subroutine the aforementioned symmetries-finding algorithm. We apply our algorithm to compute the exact value of the signaling dimension for all rational Platonic, Archimedean, and Catalan solids, and for the class of hyper-octahedral systems up to dimension five.
A fundamental objective in quantum information science is to determine the cost in classical resources of simulating a particular quantum system. The classical simulation cost is quantified by the signaling dimension which specifies the minimum amount of classical communication needed to perfectly simulate a channel's input-output correlations when unlimited shared randomness is held between encoder and decoder. This paper provides a collection of device-independent tests that place lower and upper bounds on the signaling dimension of a channel. Among them, a single family of tests is shown to determine when a noisy classical channel can be simulated using an amount of communication strictly less than either its input or its output alphabet size. In addition, a family of eight signaling dimension witnesses is presented that completely characterize when any four-outcome measurement channel, such as a Bell measurement, can be simulated using one communication bit and shared randomness. Finally, we bound the signaling dimension for all partial replacer channels in ddd dimensions. The bounds are found to be tight for the special case of the erasure channel.
The signaling dimension of a probabilistic system is the minimum number of classical states required to reproduce, with shared randomness, every finite prepare-and-measure input-output correlation generated by the system. Frenkel and Weiner proved the complex-quantum simulation result that is equivalently expressed as signaling dimension n for an n-level system. Building on Frenkel’s later positive-multilinear-form/supply-demand formulation, we show that hyperbolic polarizations provide a general source of the multilinear structure required by that simulation mechanism, extending the resulting bound to arbitrary proper hyperbolicity cones. If the effect cone of an ordered probabilistic model is the hyperbolicity cone of a homogeneous polynomial p of degree d, then its signaling dimension is at most d. The proof uses the non-negativity of the polar form of p on the hyperbolicity cone and an order-theoretic identity relating the smallest hyperbolic eigenvalue of an effect to its minimum value over normalized dual states. As a corollary, every canonical Euclidean Jordan model has signaling dimension exactly equal to its Jordan rank. This simultaneously covers classical systems, real, complex and quaternionic matrix Jordan models, spin factors, the exceptional Albert algebra, and direct sums. For symmetric cones this yields a numerical identity between signaling dimension, Jordan rank, the cone Carathéodory number, and the optimal self-concordant barrier parameter. The general hyperbolic bound need not be tight; the ℓ1-cone/square-bit example of Ito and Lourenço provides a strict gap when viewed through signaling dimension. The result separates exact classical prepare-and-measure simulation dimension from internal state-space geometry at fixed signaling dimension and motivates the study of which operational invariants resolve the structure that signaling dimension alone does not capture.
In the general probabilistic model of information theory, the signaling dimension of a given communication protocol (or, equivalently, of its state space) is the smallest possible complexity of a classical communication protocol capable of perfectly simulating the given one in terms of input-output correlations. The signaling dimensions of three-, four-, and five-dimensional cross-polytopes have been known to be 3. We give logarithmic lower and upper bounds for the signaling dimensions of higher dimensional cross-polytopes, pinning down the value up to an additive gap of 2. The lower bound shows that the signaling dimension goes to infinity, in contrast to the case of balls and hypercubes.