Advantage Distillation for Quantum Key Distribution

Enhancing the performance of quantum key distribution is crucial, driving the exploration of various key distillation techniques to increase the key rate and tolerable error rate. It is imperative to develop a comprehensive framework to encapsulate and enhance the existing methods. In this work, we propose an advantage distillation framework for quantum key distribution. Building on the entanglement distillation protocol, our framework integrates all the existing key distillation methods and offers better generalization and performance. Using classical linear codes, our framework can achieve higher key rates, particularly without one-time pad encryption for postprocessing. Our approach provides insights into existing protocols and offers a systematic way for future enhancements of quantum key distribution protocols.Comment: 24 pages, 14 figures, comments are welcom

Optimizing Circuit Reusing and its Application in Randomized Benchmarking

Quantum learning tasks often leverage randomly sampled quantum circuits to characterize unknown systems. An efficient approach known as "circuit reusing," where each circuit is executed multiple times, reduces the cost compared to implementing new circuits. This work investigates the optimal reusing parameter that minimizes the variance of measurement outcomes for a given experimental cost. We establish a theoretical framework connecting the variance of experimental estimators with the reusing parameter R. An optimal R is derived when the implemented circuits and their noise characteristics are known. Additionally, we introduce a near-optimal reusing strategy that is applicable even without prior knowledge of circuits or noise, achieving variances close to the theoretical minimum. To validate our framework, we apply it to randomized benchmarking and analyze the optimal R for various typical noise channels. We further conduct experiments on a superconducting platform, revealing a non-linear relationship between R and the cost, contradicting previous assumptions in the literature. Our theoretical framework successfully incorporates this non-linearity and accurately predicts the experimentally observed optimal R. These findings underscore the broad applicability of our approach to experimental realizations of quantum learning protocols.Comment: 19 pages, 12 figures. Comments are welcomed

Realizing Non-Physical Actions through Hermitian-Preserving Map Exponentiation

Quantum mechanics features a variety of distinct properties such as coherence and entanglement, which could be explored to showcase potential advantages over classical counterparts in information processing. In general, legitimate quantum operations must adhere to principles of quantum mechanics, particularly the requirements of complete positivity and trace preservation. Nonetheless, non-physical maps, especially Hermitian-preserving maps, play a crucial role in quantum information science. To date, there exists no effective method for implementing these non-physical maps with quantum devices. In this work, we introduce the Hermitian-preserving map exponentiation algorithm, which can effectively realize the action of an arbitrary Hermitian-preserving map by encoding its output into a quantum process. We analyze the performances of this algorithm, including its sample complexity and robustness, and prove its optimality in certain cases. When combined with algorithms such as the Hadamard test and quantum phase estimation, it allows for the extraction of information and generation of states from outputs of Hermitian-preserving maps, enabling various applications. Utilizing positive but not completely positive maps, this algorithm provides exponential advantages in entanglement detection and quantification compared to protocols based on single-copy operations. In addition, it facilitates the recovery of noiseless quantum states from multiple copies of noisy states by implementing the inverse map of the corresponding noise channel, offering an intriguing approach to handling quantum errors. Our findings present a pathway for systematically and efficiently implementing non-physical actions with quantum devices, thereby boosting the exploration of potential quantum advantages across a wide range of information processing tasks.Comment: 34 pages, 10 figures, comments are welcom

Optimizing Circuit Reusing and its Application in Randomized Benchmarking

Quantum learning tasks often leverage randomly sampled quantum circuits to characterize unknown systems. An efficient approach known as ``circuit reusing,'' where each circuit is executed multiple times, reduces the cost compared to implementing new circuits. This work investigates the optimal reusing times that minimizes the variance of measurement outcomes for a given experimental cost. We establish a theoretical framework connecting the variance of experimental estimators with the reusing times $R$. An optimal $R$ is derived when the implemented circuits and their noise characteristics are known. Additionally, we introduce a near-optimal reusing strategy that is applicable even without prior knowledge of circuits or noise, achieving variances close to the theoretical minimum. To validate our framework, we apply it to randomized benchmarking and analyze the optimal $R$ for various typical noise channels. We further conduct experiments on a superconducting platform, revealing a non-linear relationship between $R$ and the cost, contradicting previous assumptions in the literature. Our theoretical framework successfully incorporates this non-linearity and accurately predicts the experimentally observed optimal $R$. These findings underscore the broad applicability of our approach to experimental realizations of quantum learning protocols

Plasmodium falciparum transcription factor AP2-06B is mutated at high frequency in Southeast Asia but does not associate with drug resistance

IntroductionA continuing challenge for malaria control is the ability of Plasmodium falciparum to develop resistance to antimalarial drugs. Members within the Plasmodium transcription factor family AP2 regulate the growth and development of the parasite, and are also thought to be involved in unclear aspects of drug resistance. Here we screened for single nucleotide polymorphisms (SNPs) within the AP2 family and identified 6 non-synonymous mutations within AP2-06B (PF3D7_0613800), with allele frequencies greater than 0.05. One mutation, K3124R, was located in a PfAP2-06B AP2 domain.MethodsTo investigate transcriptional regulation by PfAP2-06B, ChIP-seq assays were performed on 3D7/PfAP2-06B-GFP schizonts using antibodies against GFP. The DNA sequences of the artemisinin-resistant CWX and the quinoline-resistant strains PfDd2 and Pf7G8 were analyzed for the genetic diversity of AP2-06B, compared with the Pf3D7 strain as a reference sequence. To determine whether AP2-06B can alter the expression of pfk13 and pfcrt, as well as cause artemisinin and quinoline resistance in Plasmodium, we generated both a K3124R mutation and conditional knockdown of AP2-06B in Pf3D7 using CRISPR/Cas9-mediated genome editing.ResultsChIP-Seq analysis showed that AP2-06B can bind to the loci of the Plasmodium genes pfk13 and pfcrt. The AP2-06B K3124R mutation was also found in the artemisinin-resistant parasite strain CWX and the chloroquine-resistant strains Dd2 and 7G8. Contrary to expectation, Pf3D7 Plasmodium lines modified by either K3124R mutation of AP2-06B or conditional knockdown of AP2-06B did not have altered sensitivity to artemisinin or quinolines by modulating pfk13 or pfcrt expression.DiscussionAP2-06B was predicted to be associated with artemisinin and quinoline resistance, but no change in resistance was observed after mutation or conditional knockdown. Given the multigenic nature of resistance, it might be difficult to recreate a resistance phenotype. In conclusion, whether AP2-06B regulates the development of artemisinin or quinoline resistance remains to be studied

Diagenesis of Paleogene sandstones and its response to tectonics in Kuqa Foreland Basin, western China

&amp;lt;p&amp;gt;We used the textures and chemical composition of authigenic cements in Paleogene sandstones from DN2 Gas Field of Kuqa Foreland Basin (KFB) and evidence of associated fluids from fluid inclusions and formation water measurements to infer timing of fluid migration and discuss link between fluids and tectonics. Eodiagenesis occurred with the participation of meteoric waters and connate waters. Mesodiagenesis operated in the context of high salinity fluids, which were interpreted to originate from overlying Neogene evaporite. Halite, anhydrite, glauberite, carnallite and thenardite are major minerals for the evaporite. Homogenization temperatures measured in this study and K-Ar dating performed on authigenetic illites by previous study indicate that initial migration of high salinity fluid occurred during the late Miocene (12.4&amp;amp;#8211;9.2 Ma). The period is consistent with the crucial phase (13&amp;amp;#8211;10 Ma) witnessing the rapid development of southern Tianshan and the stage when calcite and anhydrite veins formed in the studied strata. These results suggest that diagenesis related to high salinity fluids probably occurred as a response to Tianshan&amp;amp;#8217;s rapid uplift and related tectonic processes. The flow of high salinity fluids was probably driven by density gradient and channeled and focused by fractures formed contemporaneously.&amp;lt;/p&amp;gt;</jats:p

Unconditional quantum magic advantage in shallow circuit computation

Abstract Quantum theory promises computational speed-ups over classical approaches. The celebrated Gottesman-Knill Theorem implies that the full power of quantum computation resides in the specific resource of “magic” states—the secret sauce to establish universal quantum computation. However, it is still questionable whether magic indeed brings the believed quantum advantage, ridding unproven complexity assumptions or black-box oracles. In this work, we demonstrate the first unconditional magic advantage: a separation between the power of generic constant-depth or shallow quantum circuits and magic-free counterparts. For this purpose, we link the shallow circuit computation with the strongest form of quantum nonlocality—quantum pseudo-telepathy, where distant non-communicating observers generate perfectly synchronous statistics. We prove quantum magic is indispensable for such correlated statistics in a specific nonlocal game inspired by the linear binary constraint system. Then, we translate generating quantum pseudo-telepathy into computational tasks, where magic is necessary for a shallow circuit to meet the target. As a by-product, we provide an efficient algorithm to solve a general linear binary constraint system over the Pauli group, in contrast to the broad undecidability in constraint systems. We anticipate our results will enlighten the final establishment of the unconditional advantage of universal quantum computation

Computational Complexity Scalable ME Algorithm and Architecture

A computational complexity scalable block-matching algorithm (CCS-BMA) is presented in this paper for the motion estimation of video encoding. The CCS-BMA shares the feature of fast convergence in TSS and the advantage of center bias searching in FSS and DS. With the uniform shape of searching pattern, the VLSI implementation of the CCS-BMA is more convenient than that of other fast motion estimation algorithms. The scalability of computational payload can be achieved through searching steps adjustment and block pixel subsampled. The proposed algorithm and architecture are suitable for low power implementation of video encoding that needs flexible scalable capability. ? 2006 IEEE.EI