Quantum Random Access Codes (QRACs) embody the fundamental trade-off between the compressibility of information into limited quantum resources and the accessibility of that information, serving as a cornerstone of quantum communication and computation. In particular, the $(n,n-1)$-QRACs, which encode $n$ bits of classical information into $n-1$ qubits, provides an ideal theoretical model for verifying quantum advantage in high-dimensional spaces; however, the analytical derivation of codes saturating the conjectured bound for general $n$ has remained an open problem. In this paper, we establish an analytical construction method for $(n,n-1)$-QRACs by using an explicit operator formalism. We prove that this construction strictly achieves the numerically conjectured upper bound of the average success probability, $\mathcal{P}=1/2+\sqrt{(n-1)/n}/2$, for all $n$. Furthermore, we present a systematic algorithm to decompose the derived positive-operator-valued measure saturating this bound into standard quantum gates. Since the resulting decoding circuit consists solely of interactions between adjacent qubits, it can be implemented with a circuit depth of $O\left(n\right)$ even under linear connectivity constraints. Additionally, we analyze the high-dimensional limit $n\to \infty$ and demonstrate that while the noncommutativity of measurements is weakened, an information-theoretic gap of $O\left({log}_{2}n\right)$ from the mutual-information bound inevitably arises for symmetric encoding. This study not only provides a scalable implementation method for high-dimensional quantum information processing but also offers new insights into the mathematical structure at the quantum-classical boundary.

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• Quantum circuits
• Quantum communication
• Quantum computation
• Quantum information theory