Reducing sequencing complexity in dynamical quantum error suppression by Walsh modulation

We study dynamical error suppression from the perspective of reducing sequencing complexity, in order to facilitate efficient semi-autonomous quantum-coherent systems. With this aim, we focus on digital sequences where all interpulse time periods are integer multiples of a minimum clock period and compatibility with simple digital classical control circuitry is intrinsic, using so-called em Walsh functions as a general mathematical framework. The Walsh functions are an orthonormal set of basis functions which may be associated directly with the control propagator for a digital modulation scheme, and dynamical decoupling (DD) sequences can be derived from the locations of digital transitions therein. We characterize the suite of the resulting Walsh dynamical decoupling (WDD) sequences, and identify the number of periodic square-wave (Rademacher) functions required to generate a Walsh function as the key determinant of the error-suppressing features of the relevant WDD sequence. WDD forms a unifying theoretical framework as it includes a large variety of well-known and novel DD sequences, providing significant flexibility and performance benefits relative to basic quasi-periodic design. We also show how Walsh modulation may be employed for the protection of certain nontrivial logic gates, providing an implementation of a dynamically corrected gate. Based on these insights we identify Walsh modulation as a digital-efficient approach for physical-layer error suppression.Comment: 15 pages, 3 figure

Predicting Bevirimat resistance of HIV-1 from genotype

<p>Abstract</p> <p>Background</p> <p>Maturation inhibitors are a new class of antiretroviral drugs. Bevirimat (BVM) was the first substance in this class of inhibitors entering clinical trials. While the inhibitory function of BVM is well established, the molecular mechanisms of action and resistance are not well understood. It is known that mutations in the regions CS p24/p2 and p2 can cause phenotypic resistance to BVM. We have investigated a set of p24/p2 sequences of HIV-1 of known phenotypic resistance to BVM to test whether BVM resistance can be predicted from sequence, and to identify possible molecular mechanisms of BVM resistance in HIV-1.</p> <p>Results</p> <p>We used artificial neural networks and random forests with different descriptors for the prediction of BVM resistance. Random forests with hydrophobicity as descriptor performed best and classified the sequences with an area under the Receiver Operating Characteristics (ROC) curve of 0.93 ± 0.001. For the collected data we find that p2 sequence positions 369 to 376 have the highest impact on resistance, with positions 370 and 372 being particularly important. These findings are in partial agreement with other recent studies. Apart from the complex machine learning models we derived a number of simple rules that predict BVM resistance from sequence with surprising accuracy. According to computational predictions based on the data set used, cleavage sites are usually not shifted by resistance mutations. However, we found that resistance mutations could shorten and weaken the <it>α</it>-helix in p2, which hints at a possible resistance mechanism.</p> <p>Conclusions</p> <p>We found that BVM resistance of HIV-1 can be predicted well from the sequence of the p2 peptide, which may prove useful for personalized therapy if maturation inhibitors reach clinical practice. Results of secondary structure analysis are compatible with a possible route to BVM resistance in which mutations weaken a six-helix bundle discovered in recent experiments, and thus ease Gag cleavage by the retroviral protease.</p