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

Research on Kill Chain Analysis Method of Cooperative Combat Based on System of Systems Framework

With the development of information technology and the innovation of combat concepts, the future air combat will show the trend of coordination, intelligence and fierce confrontation. The coordinated confrontation between equipment that constitutes the kill chain will increase the complexity of the killing chain, and bring difficulties to the design optimization of the kill chain and tactical decision-making. This paper studies the kill chain analysis method of cooperative combat based on system of systems framework, summarizes the idea of kill chain modeling based on system of systems framework, sorts out the modeling steps of kill chain analysis, puts forward the kill chain analysis and evaluation model. Combining manned/unmanned cooperative combat, it designs the different kill chain configurations, and makes instance measurement to verify the effectiveness of the proposed method, so as to lay the foundation for kill chain design, combat planning and development decision-making, and promoting coordinated development of equipment systems

The Parameter-Optimized Recursive Sliding Variational Mode Decomposition Algorithm and Its Application in Sensor Signal Processing

In industrial polishing, the sensor on the polishing motor needs to extract accurate signals in real time. Due to the insufficient real-time performance of Variational Mode Decomposition (VMD) for signal extraction, some studies have proposed the Recursive Sliding Variational Mode Decomposition (RSVMD) algorithm to address this limitation. However, RSVMD can exhibit unstable performance in strong-interference scenarios. To suppress this phenomenon, a Parameter-Optimized Recursive Sliding Variational Mode Decomposition (PO-RSVMD) algorithm is proposed. The PO-RSVMD algorithm optimizes RSVMD in the following two ways: First, an iterative termination condition based on modal component error mutation judgment is introduced to prevent over-decomposition. Second, a rate learning factor is introduced to automatically adjust the initial center frequency of the current window to reduce errors. Through simulation experiments with signals with different signal-to-noise ratios (SNR), it is found that as the SNR increases from 0 dB to 17 dB, the PO-RSVMD algorithm accelerates the iteration time by at least 53% compared to VMD and RSVMD; the number of iterations decreases by at least 57%; and the RMSE is reduced by 35% compared to the other two algorithms. Furthermore, when applying the PO-RSVMD algorithm and the RSVMD algorithm to the Inertial Measurement Unit (IMU) for measuring signal extraction performance under strong interference conditions after the polishing motor starts, the average iteration time and number of iterations of PO-RSVMD are significantly lower than those of RSVMD, demonstrating its capability for rapid signal extraction. Moreover, the average RMSE values of the two algorithms are very close, verifying the high real-time performance and stability of PO-RSVMD in practical applications

Discovery of Novel Potential Aphid Repellents: Geranic Acid Esters Containing Substituted Aromatic Rings

Aphids are one of the most damaging agricultural pests. For the sake of novel eco-friendly compounds with good activity for aphid control, a series of novel geranic acid esters containing substituted aromatic rings were designed by inverting ester groups of lead compounds. All compounds were characterized by HRMS, 1H-NMR, and 13C-NMR. In order to identify the effect of inversion ester groups on activity, a bioassay was conducted. The results showed that the repellent activity against Acyrthosiphon pisum (A. pisum) and the binding affinity with the odorant-binding protein 9 from A. pisum (ApisOBP9) of the compounds were increased after inversion of the ester groups. Particularly, 5f showed the best repellent activity (repellency proportion: 55.6%) and binding affinity (1/Ki: 0.49 µM). Meanwhile, the structure–activity relationships revealed that the introduction of meta-substitution of the benzene ring and halogen atoms, such as Cl and Br, facilitated the biological activity. The further molecular docking results demonstrated that hydrogen bonding interactions and hydrophobic interactions were vital for the binding affinity with ApisOBP9. Additionally, all compounds were predicted to be eco-friendly and their volatile physicochemical properties have been enhanced compared to the leads. The present results provide valuable clues for the further rational design of aphids’ behavioral control agents

Experimental realization of quantum algorithm for solving linear systems of equations

National Key Basic Research Program of China [2013CB921800, 2014CB848700]; National Natural Science Foundation of China [11227901, 91021005, 11375167, 11004181, 11161160553]; Strategic Priority Research Program (B) of the CAS [XDB01030400]; NSF Center for Quantum Information and Computation for Chemistry [CHE-1037992]Many important problems in science and engineering can be reduced to the problem of solving linear equations. The quantum algorithm discovered recently indicates that one can solve an N-dimensional linear equation in O(log N) time, which provides an exponential speedup over the classical counterpart. Here we report an experimental demonstration of the quantum algorithm when the scale of the linear equation is 2 x 2 using a nuclear magnetic resonance quantum information processor. For all sets of experiments, the fidelities of the final four-qubit states are all above 96%. This experiment gives the possibility of solving a series of practical problems related to linear systems of equations and can serve as the basis to realize many potential quantum algorithms