  Polar codes are the first class of structured channel codes that achieve the
symmetric capacity of binary channels with efficient encoding and decoding. In
2019, Arikan proposed a new polar coding scheme referred to as
polarization-adjusted convolutional (PAC)} codes. In contrast to polar codes,
PAC codes precode the information word using a convolutional code prior to
polar encoding. This results in material coding gain over polar code under Fano
sequential decoding as well as successive cancellation list (SCL) decoding.
Given the advantages of SCL decoding over Fano decoding in certain scenarios
such as low-SNR regime or where a constraint on the worst case decoding latency
exists, in this paper, we focus on SCL decoding and present a simplified SCL
(SSCL) decoding algorithm for PAC codes. SSCL decoding of PAC codes reduces the
decoding latency by identifying special nodes in the decoding tree and
processing them at the intermediate stages of the graph. Our simulation results
show that the performance of PAC codes under SSCL decoding is almost similar to
the SCL decoding while having lower decoding latency.
