arXiv subjects

Yu Cai

Publications and source records attributed to Yu Cai.

At least 37 records · Page 2Linked to original sources

arXiv2021

Genuine network quantum nonlocality and self-testing

The network structure offers in principle the possibility for novel forms of quantum nonlocal correlations, that are proper to networks and cannot be traced back to standard quantum Bell nonlocality. Here we define a notion of genuine network quantum nonlocality. Our approach is operational and views standard quantum nonlocality as a resource for producing correlations in networks. We show several examples of correlations that are genuine network nonlocal, considering the so-called bilocality network of entanglement swapping. In particular, we present an example of quantum self-testing which relies on the network structure; the considered correlations are non-bilocal, but are local according to the usual definition of Bell locality.

quant-ph↗

arXiv2021

Parameterization of nearshore wave breaker index

The performances of phase-averaged parametric nearshore wave transformation models depend significantly on a reliable estimate of the wave breaker index r (the breaker height-to-depth ratio), a free model parameter that essentially controls the amount of breaking energy dissipation. While the previous studies have suggested separate relationships between r and the offshore wave steepness (s0) or the normalized local water depth (kh), the parameterization of r still requires further investigation considering a wider variety of conditions and a sounder physical basis. In this study, we use the field datasets of wave height and the inverse modelling approach to reveal a composite dependence of r on both s0 and kh. Specifically, the results show a positive dependence of r on kh for larger s0, and a negative dependence of r on kh for smaller s0. Based on such composite relationships, a new r formula is proposed, and its performance is verified against the available datasets of wave height in three coasts and 14 laboratory tests. Implementation of this new formula in a parametric wave model leads to the error reduction of wave height prediction by 10~24% (mean = 19%) relative to seven widely used models in literatures. In particular, a remarkably higher model accuracy is obtained under wave conditions with small offshore wave steepness, which is important for studying onshore sediment transport and beach recovery. Two counteractive physical mechanisms for wave nonlinearity effects, namely the breaking intensification mechanism and the breaking resistance mechanism, are suggested to explain the opposite r-kh relationships within different ranges of s0.

physics.ao-ph↗

arXiv2021

A flapping feathered wing-powered aerial vehicle

An aerial vehicle powered by flapping feathered wings was designed, developed and fabricated. Different from legacy flapping-wing aerial vehicles with membrane wings, the new design uses authentic bird feathers to fabricate wings. In field tests, a radio-controlled electric-powered aerial vehicle with flapping feathered wings successfully took off, flew up to 63.88 s and landed safely. It was found that flapping feathered wings can generate sufficient thrust and lift to make a man-made aerial vehicle accomplish takeoff, sustainable flight and a safe landing.

eess.SY↗

arXiv2020

Experimental high-dimensional quantum teleportation

Quantum teleportation provides a way to transmit unknown quantum states from one location to another. In the quantum world, multilevel systems which enable high-dimensional systems are more prevalent. Therefore, to completely rebuild the quantum states of a single particle remotely, one needs to teleport multilevel (high-dimensional) states. Here, we demonstrate the teleportation of high-dimensional states in a three-dimensional six-photon system. We exploit the spatial mode of a single photon as the high-dimensional system, use two auxiliary entangled photons to realize a deterministic three-dimensional Bell state measurement. The fidelity of teleportation process matrix is F=0.596\pm0.037. Through this process matrix, we can prove that our teleportation is both nonclassical and genuine three dimensional. Our work paves the way to rebuild complex quantum systems remotely and to construct complex quantum networks.

quant-ph↗

arXiv2020

Fast semidefinite programming with feedforward neural networks

Semidefinite programming is an important optimization task, often used in time-sensitive applications. Though they are solvable in polynomial time, in practice they can be too slow to be used in online, i.e. real-time applications. Here we propose to solve feasibility semidefinite programs using artificial neural networks. Given the optimization constraints as an input, a neural network outputs values for the optimization parameters such that the constraints are satisfied, both for the primal and the dual formulations of the task. We train the network without having to exactly solve the semidefinite program even once, thus avoiding the possibly time-consuming task of having to generate many training samples with conventional solvers. The neural network method is only inconclusive if both the primal and dual models fail to provide feasible solutions. Otherwise we always obtain a certificate, which guarantees false positives to be excluded. We examine the performance of the method on a hierarchy of quantum information tasks, the Navascués-Pironio-Acín hierarchy applied to the Bell scenario. We demonstrate that the trained neural network gives decent accuracy, while showing orders of magnitude increase in speed compared to a traditional solver.

quant-ph↗

arXiv2020

Entanglement for any definition of two subsystems

The notion of entanglement of quantum states is usually defined with respect to a fixed bipartition. Indeed, a global basis change can always map an entangled state to a separable one. The situation is however different when considering a set of states. In this work we define the notion of an "absolutely entangled set" of quantum states: for any possible choice of global basis, at least one of the states in the set is entangled. Hence, for all bipartitions, i.e. any possible definition of the subsystems, the set features entanglement. We present a minimum example of this phenomenon, with a set of four states in $\mathbb{C}^4 = \mathbb{C}^2 \otimes \mathbb{C}^2$. Moreover, we propose a quantitative measure for absolute set entanglement. To lower-bound this quantity, we develop a method based on polynomial optimization to perform convex optimization over unitaries, which is of independent interest.

quant-ph↗

arXiv2020

A neural network oracle for quantum nonlocality problems in networks

Characterizing quantum nonlocality in networks is a challenging, but important problem. Using quantum sources one can achieve distributions which are unattainable classically. A key point in investigations is to decide whether an observed probability distribution can be reproduced using only classical resources. This causal inference task is challenging even for simple networks, both analytically and using standard numerical techniques. We propose to use neural networks as numerical tools to overcome these challenges, by learning the classical strategies required to reproduce a distribution. As such, the neural network acts as an oracle, demonstrating that a behavior is classical if it can be learned. We apply our method to several examples in the triangle configuration. After demonstrating that the method is consistent with previously known results, we give solid evidence that the distribution presented in [N. Gisin, Entropy 21(3), 325 (2019)] is indeed nonlocal as conjectured. Finally we examine the genuinely nonlocal distribution presented in [M.-O. Renou et al., PRL 123, 140401 (2019)], and, guided by the findings of the neural network, conjecture nonlocality in a new range of parameters in these distributions. The method allows us to get an estimate on the noise robustness of all examined distributions.

quant-ph↗

arXiv2020

Constraints on nonlocality in networks from no-signaling and independence

Generalising the concept of Bell nonlocality to networks leads to novel forms of correlations, the characterization of which is however challenging. Here we investigate constraints on correlations in networks under the two natural assumptions of no-signaling and independence of the sources. We consider the ``triangle network'', and derive strong constraints on correlations even though the parties receive no input, i.e. each party performs a fixed measurement. We show that some of these constraints are tight, by constructing explicit local models (i.e. where sources distribute classical variables) that can saturate them. However, we also observe that other constraints can apparently not be saturated by local models, which opens the possibility of having nonlocal (but non-signaling) correlations in the triangle network.

quant-ph↗

arXiv2020

MNN: A Universal and Efficient Inference Engine

Deploying deep learning models on mobile devices draws more and more attention recently. However, designing an efficient inference engine on devices is under the great challenges of model compatibility, device diversity, and resource limitation. To deal with these challenges, we propose Mobile Neural Network (MNN), a universal and efficient inference engine tailored to mobile applications. In this paper, the contributions of MNN include: (1) presenting a mechanism called pre-inference that manages to conduct runtime optimization; (2)deliveringthorough kernel optimization on operators to achieve optimal computation performance; (3) introducing backend abstraction module which enables hybrid scheduling and keeps the engine lightweight. Extensive benchmark experiments demonstrate that MNN performs favorably against other popular lightweight deep learning frameworks. MNN is available to public at: https://github.com/alibaba/MNN.

cs.CV↗

arXiv2019

Semi-device-independent characterization of quantum measurements under a minimum overlap assumption

Recently, a novel framework for semi-device-independent quantum prepare-and-measure protocols has been proposed, based on the assumption of a limited distinguishability between the prepared quantum states. Here, we discuss the problem of characterizing an unknown quantum measurement device in this setting. We present several methods to attack this problem. Considering the simplest scenario of two preparations with lower bounded overlap, we show that genuine 3-outcome POVMs can be certified, even in the presence of noise. Moreover, we show that the optimal POVM for performing unambiguous state discrimination can be self-tested.

quant-ph↗

arXiv2019

Almost thermal operations: inhomogeneous reservoirs

The resource theory of thermal operations explains the state transformations that are possible in a very specific thermodynamic setting: there is only one thermal bath, auxiliary systems can only be in corresponding thermal state (free states), and the interaction must commute with the free Hamiltonian (free operation). In this paper we study the mildest deviation: the reservoir particles are subject to inhomogeneities, either in the local temperature (introducing resource states) or in the local Hamiltonian (generating a resource operation). For small inhomogeneities, the two models generate the same channel and thus the same state transformations. However, their thermodynamics is significantly different when it comes to work generation or to the interpretation of the "second laws of thermal operations".

quant-ph↗

arXiv2018

Self-testing using only marginal information

The partial states of a multipartite quantum state may carry a lot of information: in some cases, they determine the global state uniquely. This result is known for tomographic information, that is for fully characterized measurements. We extend it to the device-independent framework by exhibiting sets of two-party correlations that self-test pure three-qubit states.

quant-ph↗

arXiv2018

Improving 3D NAND Flash Memory Lifetime by Tolerating Early Retention Loss and Process Variation

Compared to planar (i.e., two-dimensional) NAND flash memory, 3D NAND flash memory uses a new flash cell design, and vertically stacks dozens of silicon layers in a single chip. This allows 3D NAND flash memory to increase storage density using a much less aggressive manufacturing process technology than planar NAND flash memory. The circuit-level and structural changes in 3D NAND flash memory significantly alter how different error sources affect the reliability of the memory. In this paper, through experimental characterization of real, state-of-the-art 3D NAND flash memory chips, we find that 3D NAND flash memory exhibits three new error sources that were not previously observed in planar NAND flash memory: (1) layer-to-layer process variation, where the average error rate of each 3D-stacked layer in a chip is significantly different; (2) early retention loss, a new phenomenon where the number of errors due to charge leakage increases quickly within several hours after programming; and (3) retention interference, a new phenomenon where the rate at which charge leaks from a flash cell is dependent on the data value stored in the neighboring cell. Based on our experimental results, we develop new analytical models of layer-to-layer process variation and retention loss in 3D NAND flash memory. Motivated by our new findings and models, we develop four new techniques to mitigate process variation and early retention loss in 3D NAND flash memory. These four techniques are complementary, and can be combined together to significantly improve flash memory reliability. Compared to a state-of-the-art baseline, our techniques, when combined, improve flash memory lifetime by 1.85x. Alternatively, if a NAND flash vendor wants to keep the lifetime of the 3D NAND flash memory device constant, our techniques reduce the storage overhead required to hold error correction information by 78.9%.

cs.AR↗

arXiv2018

Structure of the set of quantum correlators via semidefinite programming

Quantum information leverages properties of quantum behaviors in order to perform useful tasks such as secure communication and randomness certification. Nevertheless, not much is known about the intricate geometric features of the set quantum behaviors. In this paper we study the structure of the set of quantum correlators using semidefinite programming. Our main results are (i) a generalization of the analytic description by Tsirelson-Landau-Masanes, (ii) necessary and sufficient conditions for extremality and exposedness, and (iii) an operational interpretation of extremality in the case of two dichotomic measurements, in terms of self-testing. We illustrate the usefulness of our theoretical findings with many examples and extensive computational work.

quant-ph↗

arXiv2018

Violation of all the second laws of thermal operations by inhomogeneous reservoirs

In the resource theory of thermodynamics, the decrease of the free energy based on von Neumann entropy is not a sufficient condition to determine free evolution. Rather, a whole family of generalised free energies $F_α$ must be monotonically decreasing. We study the resilience of this result to relaxations of the framework. We use a toy collisional model, in which the deviations from the ideal situation can be described as arising from inhomogeneities of local fields or temperatures. For any small amount of perturbation, we find that there exist initial states such that both single-shot and averaged values of $F_α$ do not decrease monotonically for all $α>0$. A geometric representation accounts for the observed behavior in a graphic way.

quant-ph↗

arXiv2018

Experimental Characterization, Optimization, and Recovery of Data Retention Errors in MLC NAND Flash Memory

This paper summarizes our work on experimentally characterizing, mitigating, and recovering data retention errors in multi-level cell (MLC) NAND flash memory, which was published in HPCA 2015, and examines the work's significance and future potential. Retention errors, caused by charge leakage over time, are the dominant source of flash memory errors. Understanding, characterizing, and reducing retention errors can significantly improve NAND flash memory reliability and endurance. In this work, we first characterize, with real 2Y-nm MLC NAND flash chips, how the threshold voltage distribution of flash memory changes with different retention ages -- the length of time since a flash cell was programmed. We observe from our characterization results that 1) the optimal read reference voltage of a flash cell, using which the data can be read with the lowest raw bit error rate (RBER), systematically changes with its retention age, and 2) different regions of flash memory can have different retention ages, and hence different optimal read reference voltages. Based on our findings, we propose two new techniques. First, Retention Optimized Reading (ROR) adaptively learns and applies the optimal read reference voltage for each flash memory block online. The key idea of ROR is to periodically learn a tight upper bound of the optimal read reference voltage, and from there approach the optimal read reference voltage. Our evaluations show that ROR can extend flash memory lifetime by 64% and reduce average error correction latency by 10.1%. Second, Retention Failure Recovery (RFR) recovers data with uncorrectable errors offline by identifying and probabilistically correcting flash cells with retention errors. Our evaluation shows that RFR essentially doubles the error correction capability.

cs.AR↗

arXiv2018

Read Disturb Errors in MLC NAND Flash Memory

This paper summarizes our work on experimentally characterizing, mitigating, and recovering read disturb errors in multi-level cell (MLC) NAND flash memory, which was published in DSN 2015, and examines the work's significance and future potential. NAND flash memory reliability continues to degrade as the memory is scaled down and more bits are programmed per cell. A key contributor to this reduced reliability is read disturb, where a read to one row of cells impacts the threshold voltages of unread flash cells in different rows of the same block. For the first time in open literature, this work experimentally characterizes read disturb errors on state-of-the-art 2Y-nm (i.e., 20-24 nm) MLC NAND flash memory chips. Our findings (1) correlate the magnitude of threshold voltage shifts with read operation counts, (2) demonstrate how program/erase cycle count and retention age affect the read-disturb-induced error rate, and (3) identify that lowering pass-through voltage levels reduces the impact of read disturb and extend flash lifetime. Particularly, we find that the probability of read disturb errors increases with both higher wear-out and higher pass-through voltage levels. We leverage these findings to develop two new techniques. The first technique mitigates read disturb errors by dynamically tuning the pass-through voltage on a per-block basis. Using real workload traces, our evaluations show that this technique increases flash memory endurance by an average of 21%. The second technique recovers from previously-uncorrectable flash errors by identifying and probabilistically correcting cells susceptible to read disturb errors. Our evaluations show that this recovery technique reduces the raw bit error rate by 36%.

cs.AR↗

arXiv2018

Characterizing, Exploiting, and Mitigating Vulnerabilities in MLC NAND Flash Memory Programming

This paper summarizes our work on experimentally analyzing, exploiting, and addressing vulnerabilities in multi-level cell NAND flash memory programming, which was published in the industrial session of HPCA 2017, and examines the work's significance and future potential. Modern NAND flash memory chips use multi-level cells (MLC), which store two bits of data in each cell, to improve chip density. As MLC NAND flash memory scaled down to smaller manufacturing process technologies, manufacturers adopted a two-step programming method to improve reliability. In two-step programming, the two bits of a multi-level cell are programmed using two separate steps, in order to minimize the amount of cell-to-cell program interference induced on neighboring flash cells. In this work, we demonstrate that two-step programming exposes new reliability and security vulnerabilities in state-of-the-art MLC NAND flash memory. We experimentally characterize contemporary 1X-nm (i.e., 15--19nm) flash memory chips, and find that a partially-programmed flash cell (i.e., a cell where the second programming step has not yet been performed) is much more vulnerable to cell-to-cell interference and read disturb than a fully-programmed cell. We show that it is possible to exploit these vulnerabilities on solid-state drives (SSDs) to alter the partially-programmed data, causing (potentially malicious) data corruption. Based on our observations, we propose several new mechanisms that eliminate or mitigate these vulnerabilities in partially-programmed cells, and at the same time increase flash memory lifetime by 16%.

cs.AR↗