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arXiv:2505.22142 · IEEE Information Theory Workshop (ITW)

Interpolation of Quantum Polar Codes and Quantum Reed-Muller Codes

Keita Hidaka, Dina Abdelhadi, Rudiger L. Urbanke

Published Sep 29, 2025• 0 citations
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Abstract

Good quantum error-correcting codes that fulfill practical considerations, such as simple encoding circuits and efficient decoders, are essential for functional quantum information processing systems. Quantum polar codes satisfy some of these requirements but lack certain critical features, thereby hindering their widespread use. Existing constructions either require entanglement assistance to produce valid quantum codes, suffer from poor finite-size performance, or fail to tailor polar codes to the underlying channel properties. Meanwhile, quantum Reed-Muller (RM) codes demonstrate strong performance, though no known efficient decoding algorithm exists for them. In this work, we propose strategies to interpolate between quantum polar codes and quantum RM codes, thus addressing the challenges of designing valid quantum polar codes without entanglement assistance and improving finite-size code performance.

DOI
10.1109/itw62417.2025.11240456

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We explore the relationship between polar and RM codes and we describe a coding scheme which improves upon the performance of the standard polar code at practical block lengths. Our starting point is the experimental observation that RM codes have a smaller error probability than polar codes under MAP decoding. This motivates us to introduce a family of codes that "interpolates" between RM and polar codes, call this family Cinter={Cα:α∈[0,1]}{\mathcal C}_{\rm inter} = \{C_α : α\in [0, 1]\}Cinter​={Cα​:α∈[0,1]}, where Cα∣α=1C_α \big |_{α= 1}Cα​​α=1​ is the original polar code, and Cα∣α=0C_α \big |_{α= 0}Cα​​α=0​ is an RM code. Based on numerical observations, we remark that the error probability under MAP decoding is an increasing function of ααα. MAP decoding has in general exponential complexity, but empirically the performance of polar codes at finite block lengths is boosted by moving along the family Cinter{\mathcal C}_{\rm inter}Cinter​ even under low-complexity decoding schemes such as, for instance, belief propagation or successive cancellation list decoder. We demonstrate the performance gain via numerical simulations for transmission over the erasure channel as well as the Gaussian channel.
We explore the relationship between polar and RM codes and we describe a coding scheme which improves upon the performance of the standard polar code at practical block lengths. Our starting point is the experimental observation that RM codes have a smaller error probability than polar codes under MAP decoding. This motivates us to introduce a family of codes that “interpolates” between RM and polar codes, call this family Cinter= {Cα: α ∈ [0, 1]}, where Cα|α=1is the original polar code, and Cα|α=0is an RM code. Based on numerical observations, we remark that the error probability under MAP decoding is an increasing function of α. MAP decoding has in general exponential complexity, but empirically the performance of polar codes at finite block lengths is boosted by moving along the family Cintereven under low-complexity decoding schemes such as, for instance, belief propagation or successive cancellation list decoder. We demonstrate the performance gain via numerical simulations for transmission over the erasure channel as well as the Gaussian channel.
We explore the relationship between polar and RM codes and we describe a coding scheme which improves upon the performance of the standard polar code at practical block lengths. Our starting point is the experimental observation that RM codes have a smaller error probability than polar codes under MAP decoding. This motivates us to introduce a family of codes that “interpolates” between RM and polar codes, call this family Cinter= {Cα: α ∈ [0, 1j}, where Cα|α=1is the original polar code, and Cα|α=0is an RM code. Based on numerical observations, we remark that the error probability under MAP decoding is an increasing function of α. MAP decoding has in general exponential complexity, but empirically the performance of polar codes at finite block lengths is boosted by moving along the family Cinter even under low-complexity decoding schemes such as, for instance, belief propagation or successive cancellation list decoder. We demonstrate the performance gain via numerical simulations for transmission over the erasure channel as well as the Gaussian channel.
In this thesis, we start from the theory of classical error-correcting codes. We also introduce classical Reed-Muller codes along with its properties. We discuss the encoding and decoding methods for classical Reed-Muller codes using the majority rule. Then we turn to the topic of quantum error-correcting codes.We talk about stabilizer codes and discuss how classical Reed-Muller codes can be transformed into quantum Reed-Muller codes using Steane's method. Finally, we give a construction of a quantum code with parameter [[8,3,3]], and discuss its encoding and decoding process.
We construct an explicit quantum coding scheme which achieves a communication rate not less than the coherent information when used to transmit the quantum information over a noisy quantum channel. For Pauli and erasure channels, we also present efficient encoding and decoding algorithms for this communication scheme based on polar codes (essentially linear in the blocklength), but which do not require the sender and receiver to share any entanglement before the protocol begins. Due to the existence of degeneracies in the involved error-correcting codes, it is indeed possible that the rate of the scheme exceeds the coherent information. We provide a simple criterion which indicates such performance. Finally, we discuss how the scheme can be used for secret key distillation as well as private channel coding.