There are many approaches when it comes to exploring the potential of the random access code (RAC) communication protocol. Given its versatility, the RAC is particularly useful when the communication between parties is restricted. In previous works, it has been proven that ${2}^{(d)}\ensuremath{\rightarrow}1$ quantum random access codes (QRAC), in the absence of noise, outperform their classical counterpart (the ${2}^{(d)}\ensuremath{\rightarrow}1$ CRAC) for any dimension $d$. Here, building upon these works, we showed that noisy channels can significantly decrease the performance of ${2}^{(d)}\ensuremath{\rightarrow}1$ QRAC. In order to mitigate noise-driven efficiency losses, we employed the see-saw optimization algorithm with semidefinite programming (SDP) to find the best quantum encoding and decoding strategies for the QRAC given a known quantum channel.
There are many approaches when it comes to exploring the potential of the random access code (RAC) communication protocol. Given its versatility, the RAC is particularly useful when the communication between parties is restricted. In previous works, it has been proven that 2(d)\ensuremath→1 quantum random access codes (QRAC), in the absence of noise, outperform their classical counterpart (the 2(d)\ensuremath→1 CRAC) for any dimension d. Here, building upon these works, we showed that noisy channels can significantly decrease the performance of 2(d)\ensuremath→1 QRAC. In order to mitigate noise-driven efficiency losses, we employed the see-saw optimization algorithm with semidefinite programming (SDP) to find the best quantum encoding and decoding strategies for the QRAC given a known quantum channel.
A ${n}^{d}\stackrel{p}{\ensuremath{\rightarrow}}1$ quantum random access code (QRAC) is a communication task where Alice encodes n classical bits into quantum states of dimension d and transmits them to Bob, who performs appropriate measurements to recover the required bit with probability p. In the presence of a noisy environment, the performance of a QRAC is degraded, losing the advantage over classical strategies. We propose a practical technique that enables noise tolerance in such scenarios, recovering the quantum advantage in retrieving the required bit. We perform a photonic implementation of a ${2}^{2}\stackrel{\text{p}}{\ensuremath{\rightarrow}}1$ QRAC using polarization-encoded qubits under an amplitude-damping channel, where simple operations allow for noise robustness showing the revival of the quantum advantage when the noisy channel degrades the performance of the QRAC. This revival can be observed by violating a suitable dimension witness, which is closely related to the average success probability of the QRAC. This technique can be extended to other applications in the so-called prepare-and-measure scenario, enhancing the semi-device-independent protocol implementations.
A random access code (RAC) encodes an L-bit string into a k-bit message, L>k, so that any requested bit can be recovered with high probability; a quantum RAC (QRAC) uses k qubits instead. We give a geometric characterization of optimal classical (L,k)-RACs under average and worst-case decoding criteria. The average criterion is reduced to choosing 2k representatives in {0,1}L, while the worst-case criterion is reduced to a minimax problem over 2k points in [0,1]L with a distance-like objective. This framework proves optimality for several parameter families, with many optimal constructions arising from standard infinite families of binary linear codes. It also yields two explicit classical--quantum separations. First, for every L>1, we construct a (L,1)-QRAC whose average decoding success probability strictly exceeds the optimal classical value. Second, for the family (2k−1,k), we prove worst-case optimality of a classical RAC and construct a QRAC with strictly larger worst-case success probability. For the family (L,L−1), the framework identifies a classical RAC that is average-case optimal and, under a stated conjecture, also worst-case optimal. The same viewpoint further recovers explicit (L,L−1)-QRACs attaining a previously conjectured upper-bound value.
A (quantum) random access code ((Q)RAC) is a scheme that encodes n bits into m (qu)bits such that any of the n bits can be recovered with a worst case probability p>21. We generalize (Q)RACs to a scheme encoding nd-levels into m (quantum) d-levels such that any d-level can be recovered with the probability for every wrong outcome value being less than d1. We construct explicit solutions for all $n\ensuremath{\le}\frac{{d}^{2m}\ensuremath{-}1}{d\ensuremath{-}1}$. For d=2, the constructions coincide with those previously known. We show that the (Q)RACs are d-parity oblivious, generalizing ordinary parity obliviousness. We further investigate optimization of the success probabilities. For d=2, we use the measure operators of the previously best-known solutions, but improve the encoding states to give a higher success probability. We conjecture that for maximal $(n={4}^{m}\ensuremath{-}1,m,p)$ QRACs, $p=\frac{1}{2}{1+{[{(\sqrt{3}+1)}^{m}\ensuremath{-}1]}^{\ensuremath{-}1}}$ is possible, and show that it is an upper bound for the measure operators that we use. We then compare (n,m,pq) QRACs with classical (n,2m,pc) RACs. We can always find ${p}_{q}\ensuremath{\ge}{p}_{c}$, but the classical code gives information about every input bit simultaneously, while the QRAC only gives information about a subset. For several different (n,2,p) QRACs, we see the same trade-off, as the best p values are obtained when the number of bits that can be obtained simultaneously is as small as possible. The trade-off is connected to parity obliviousness, since high certainty information about several bits can be used to calculate probabilities for parities of subsets.
A (Quantum) Random Access Code ((Q)RAC) is a scheme that encodes n bits into m (qu)bits such that any of the n bits can be recovered with a worst case probability p>21. Such a code is denoted by the triple (n,m,p). It is known that n<4m for all QRACs and n<2m for classical RACs. These bounds are also known to be tight, as explicit constructions exist for n=4m−1 and n=2m−1 for quantum and classical codes respectively. We generalize (Q)RACs to a scheme encoding nd-levels into m (qu)-d-levels such that any d-level can be recovered with the probability for every wrong outcome value being less than d1. We construct explicit solutions for all n≤d−1d2m−1. For d=2, the constructions coincide with those previously known. We show that the (Q)RACs are d-parity-oblivious, generalizing ordinary parity-obliviousness. We further investigate optimization of the success probabilities. For d=2, we use the measure operators of the previously best known solutions, but improve the encoding states to give a higher success probability. We conjecture that for maximal (n=4m−1,m,p) QRACs, p=21+(3+1)m−11 is possible and show that it is an upper bound for the measure operators that we use. When we compare (n,m,pq) QRACs with classical (n,2m,pc) RACs, we can always find pq≥pc, but the classical code gives information about every input bit simultaneously, while the QRAC only gives information about a subset. For several different (n,2,p) QRACs, we see the same trade-off, as the best p values are obtained when the number of bits that can be obtained simultaneously is as small as possible. The trade-off is connected to parity-obliviousness, since high certainty information about several bits can be used to calculate probabilities for parities of subsets.
Abstract We consider two classes of quantum generalisations of random access code (RAC) and study the bounds for probabilities of success for such tasks. It provides a useful framework for the study of certain information processing tasks with constrained resources. The first class is based on a RAC with quantum inputs and output known as the no-signalling quantum RAC (NS-QRAC) box (Grudka et al 2015 Phys. Rev. A 92 052312), where unbounded entanglement and constrained classical communication are allowed. We show that it can be seen as quantum teleportation with constrained classical communication and provide a lower quantum bound for the success probability. We consider two modifications to the NS-QRAC scenario: the first, where unbounded entanglement and constrained quantum communication is allowed and the second, where bounded entanglement and unconstrained classical communication is allowed. We find a monogamy relation for the transmission fidelities, which—in contrast to the usual communication schemes—involves multiple senders and a single receiver. We provide an upper bounds for the latter and a lower one for the former. The second class is based on a RAC with a quantum channel and shared entanglement (Tavakoli et al 2021 PRX Quantum 2 040357). We study the set of tasks where two inputs made of two digits of d-base are encoded over a qudit and a maximally entangled state. We show that such tasks can be seen as quantum dense-coding with constrained quantum communication and explicit protocols, which give lower quantum bounds for the tasks’ efficiency, in dimensions d = 2 , 3 , 4 . The employed encoding utilises Gray codes.
A random access code (RAC) is a communication task in which the sender encodes a random message into a shorter one to be decoded by the receiver so that a randomly chosen character of the original message is recovered with some probability. Both the message and the character to be recovered are assumed to be uniformly distributed. In this paper, we extend this protocol by allowing more general distributions of these inputs, which alters the encoding and decoding strategies optimizing the protocol performance, with either classical or quantum resources. We approach the problem of optimizing the performance of these biased RACs with both numerical and analytical tools. On the numerical front, we present algorithms that allow a numerical evaluation of the optimal performance over both classical and quantum strategies and provide a Python package designed to implement them, called RAC-tools. We then use this numerical tool to investigate single-parameter families of biased RACs in the ${n}^{2}\ensuremath{\mapsto}1$ and ${2}^{d}\ensuremath{\mapsto}1$ scenarios. For RACs in the ${n}^{2}\ensuremath{\mapsto}1$ scenario, we derive a general upper bound for the cases in which the inputs are not correlated, which coincides with the quantum value for n=2 and in some cases for n=3. Moreover, it is shown that attaining this upper bound self-tests pairs or triples of rank-1 projective measurements, respectively. An analogous upper bound is derived for the value of RACs in the ${2}^{d}\ensuremath{\mapsto}1$ scenario, which is shown to be always attainable using mutually unbiased measurements if the distribution of input strings is unbiased.