arXiv subjects

Yuan Cao

Publications and source records attributed to Yuan Cao.

At least 199 records · Page 11Linked to original sources

arXiv2019

Collective excitations in twisted bilayer graphene close to the magic angle

The electronic properties of twisted bilayer graphene (TBG) can be dramatically different from those of a single graphene layer, in particular when the two layers are rotated relative to each other by a small angle. TBG has recently attracted a great deal of interest, sparked by the discovery of correlated insulating and superconducting states, for twist angle $θ$ close to a so-called 'magic angle' $\approx 1.1°$. In this work, we unveil, via near-field optical microscopy, a collective plasmon mode in charge-neutral TBG near the magic angle, which is dramatically different from the ordinary single-layer graphene intraband plasmon. In selected regions of our samples, we find a gapped collective mode with linear dispersion, akin to the bulk magnetoplasmons of a two-dimensional (2D) electron gas. We interpret these as interband plasmons and associate those with the optical transitions between quasi-localized states originating from the moiré superlattice. Surprisingly, we find a higher plasmon group velocity than expected, which implies an enhanced strength of the corresponding optical transition. This points to a weaker interlayer coupling in the AA regions. These intriguing optical properties offer new insights, complementary to other techniques, on the carrier dynamics in this novel quantum electron system.

cond-mat.str-el↗

arXiv2019

Spaceborne low-noise single-photon detection for satellite-based quantum communications

Single-photon detectors (SPDs) play important roles in highly sensitive detection applications, such as fluorescence spectroscopy, remote sensing and ranging, deep space optical communications, elementary particle detection, and quantum communications. However, the adverse conditions in space, such as the increased radiation flux and thermal vacuum, severely limit their noise performances, reliability, and lifetime. Herein, we present the first example of spaceborne, low-noise, high reliability SPDs, based on commercial off-the-shelf (COTS) silicon avalanche photodiodes (APD). Based on the high noise-radiation sensitivity of silicon APD, we have developed special shielding structures, multistage cooling technologies, and configurable driver electronics that significantly improved the COTS APD reliability and mitigated the SPD noise-radiation sensitivity. This led to a reduction of the expected in-orbit radiation-induced dark count rate (DCR) from ~219 counts per second (cps) per day to ~0.76 cps/day. During a continuous period of continuous operations in orbit which spanned of 1029 days, the SPD DCR was maintained below 1000 cps, i.e., the actual in-orbit radiation-induced DCR increment rate was ~0.54 cps/day, i.e., two orders of magnitude lower than those evoked by previous technologies, while its photon detection efficiency was > 45%. Our spaceborne, low-noise SPDs established a feasible satellite-based up-link quantum communication that was validated on the quantum experiment science satellite platform. Moreover, our SPDs open new windows of opportunities for space research and applications in deep-space optical communications, single-photon laser ranging, as well as for testing the fundamental principles of physics in space.

physics.ins-det↗

arXiv2019

Algorithm-Dependent Generalization Bounds for Overparameterized Deep Residual Networks

The skip-connections used in residual networks have become a standard architecture choice in deep learning due to the increased training stability and generalization performance with this architecture, although there has been limited theoretical understanding for this improvement. In this work, we analyze overparameterized deep residual networks trained by gradient descent following random initialization, and demonstrate that (i) the class of networks learned by gradient descent constitutes a small subset of the entire neural network function class, and (ii) this subclass of networks is sufficiently large to guarantee small training error. By showing (i) we are able to demonstrate that deep residual networks trained with gradient descent have a small generalization gap between training and test error, and together with (ii) this guarantees that the test error will be small. Our optimization and generalization guarantees require overparameterization that is only logarithmic in the depth of the network, while all known generalization bounds for deep non-residual networks have overparameterization requirements that are at least polynomial in the depth. This provides an explanation for why residual networks are preferable to non-residual ones.

cs.LG↗

arXiv2019

On self-duality and hulls of cyclic codes over $\frac{\mathbb{F}_{2^m}[u]}{\langle u^k\rangle}$ with oddly even length

Let $\mathbb{F}_{2^m}$ be a finite field of $2^m$ elements, and $R=\mathbb{F}_{2^m}[u]/\langle u^k\rangle=\mathbb{F}_{2^m}+u\mathbb{F}_{2^m}+\ldots+u^{k-1}\mathbb{F}_{2^m}$ ($u^k=0$) where $k$ is an integer satisfying $k\geq 2$. For any odd positive integer $n$, an explicit representation for every self-dual cyclic code over $R$ of length $2n$ and a mass formula to count the number of these codes are given first. Then a generator matrix is provided for the self-dual and $2$-quasi-cyclic code of length $4n$ over $\mathbb{F}_{2^m}$ derived by every self-dual cyclic code of length $2n$ over $\mathbb{F}_{2^m}+u\mathbb{F}_{2^m}$ and a Gray map from $\mathbb{F}_{2^m}+u\mathbb{F}_{2^m}$ onto $\mathbb{F}_{2^m}^2$. Finally, the hull of each cyclic code with length $2n$ over $\mathbb{F}_{2^m}+u\mathbb{F}_{2^m}$ is determined and all distinct self-orthogonal cyclic codes of length $2n$ over $\mathbb{F}_{2^m}+u\mathbb{F}_{2^m}$ are listed.

cs.IT↗

arXiv2019

Universal transfer and stacking technique of van der Waals heterostructures for spintronics

The key to achieving high-quality van der Waals heterostructure devices made from various two-dimensional (2D) materials lies in the control over clean and flexible interfaces. However, existing transfer methods based on different mediators possess insufficiencies including the presence of residues, the unavailability of flexible interface engineering, and the selectivity towards materials and substrates since their adhesions differ considerably with the various preparation conditions, from chemical vapor deposition (CVD) growth to mechanical exfoliation. In this paper, we introduce a more universal method using a prefabricated polyvinyl alcohol (PVA) film to transfer and stack 2D materials, whether they are prepared by CVD or exfoliation. This peel-off and drop-off technique promises an ideal interface of the materials without introducing contamination. In addition, the method exhibits a micron-scale spatial transfer accuracy and meets special experimental conditions such as the preparation of twisted graphene and the 2D/metal heterostructure construction. We illustrate the superiority of this method with a WSe2 vertical spin valve device, whose performance verifies the applicability and advantages of such a method for spintronics. Our PVA-assisted transfer process will promote the development of high-performance 2D-material-based devices.

physics.app-ph↗

arXiv2019

Mapping the twist angle and unconventional Landau levels in magic angle graphene

The emergence of flat electronic bands and of the recently discovered strongly correlated and superconducting phases in twisted bilayer graphene crucially depends on the interlayer twist angle upon approaching the magic angle $θ_M \approx 1.1°$. Although advanced fabrication methods allow alignment of graphene layers with global twist angle control of about 0.1$°$, little information is currently available on the distribution of the local twist angles in actual magic angle twisted bilayer graphene (MATBG) transport devices. Here we map the local $θ$ variations in hBN encapsulated devices with relative precision better than 0.002$°$ and spatial resolution of a few moir$é$ periods. Utilizing a scanning nanoSQUID-on-tip, we attain tomographic imaging of the Landau levels in the quantum Hall state in MATBG, which provides a highly sensitive probe of the charge disorder and of the local band structure determined by the local $θ$. We find that even state-of-the-art devices, exhibiting high-quality global MATBG features including superconductivity, display significant variations in the local $θ$ with a span close to 0.1$°$. Devices may even have substantial areas where no local MATBG behavior is detected, yet still display global MATBG characteristics in transport, highlighting the importance of percolation physics. The derived $θ$ maps reveal substantial gradients and a network of jumps. We show that the twist angle gradients generate large unscreened electric fields that drastically change the quantum Hall state by forming edge states in the bulk of the sample, and may also significantly affect the phase diagram of correlated and superconducting states. The findings call for exploration of band structure engineering utilizing twist-angle gradients and gate-tunable built-in planar electric fields for novel correlated phenomena and applications.

cond-mat.mes-hall↗

arXiv2019

Self-dual binary $[8m, 4m]$-codes constructed by left ideals of the dihedral group algebra $\mathbb{F}_2[D_{8m}]$

Let $m$ be an arbitrary positive integer and $D_{8m}$ be a dihedral group of order $8m$, i.e., $D_{8m}=\langle x,y\mid x^{4m}=1, y^2=1, yxy=x^{-1}\rangle$. Left ideals of the dihedral group algebra $\mathbb{F}_2[D_{8m}]$ are called binary left dihedral codes of length $8m$, and abbreviated as binary left $D_{8m}$-codes. In this paper, we give an explicit representation and enumeration for all distinct self-dual binary left $D_{8m}$-codes. These codes make up an important class of self-dual binary $[8m,4m]$-codes such that the dihedral group $D_{8m}$ is necessary a subgroup of the automorphism group of each code. In particular, we provide recursive algorithms to solve congruence equations over finite chain rings for constructing all distinct self-dual binary left $D_{8m}$-codes and obtain a Mass formula to count the number of all these self-dual codes. As a preliminary application, we obtain the extremal self-dual binary $[48,24,12]$-code and an extremal self-dual binary $[56,28,12]$-code from self-dual binary left $D_{48}$-codes and left $D_{56}$-codes respectively.

cs.IT↗

arXiv2019

An efficient method to construct self-dual cyclic codes of length $p^s$ over $\mathbb{F}_{p^m}+u\mathbb{F}_{p^m}$

Let $p$ be an odd prime number, $\mathbb{F}_{p^m}$ be a finite field of cardinality $p^m$ and $s$ a positive integer. Using some combinatorial identities, we obtain certain properties for Kronecker product of matrices over $\mathbb{F}_p$ with a specific type. On that basis, we give an explicit representation and enumeration for all distinct self-dual cyclic codes of length $p^s$ over the finite chain ring $\mathbb{F}_{p^m}+u\mathbb{F}_{p^m}$ $(u^2=0)$. Moreover, We provide an efficient method to construct every self-dual cyclic code of length $p^s$ over $\mathbb{F}_{p^m}+u\mathbb{F}_{p^m}$ precisely.

cs.IT↗

arXiv2019

Construction and enumeration for self-dual cyclic codes of even length over $\mathbb{F}_{2^m} + u\mathbb{F}_{2^m}$

Let $\mathbb{F}_{2^m}$ be a finite field of cardinality $2^m$, $R=\mathbb{F}_{2^m}+u\mathbb{F}_{2^m}$ $(u^2=0)$ and $s,n$ be positive integers such that $n$ is odd. In this paper, we give an explicit representation for every self-dual cyclic code over the finite chain ring $R$ of length $2^sn$ and provide a calculation method to obtain all distinct codes. Moreover, we obtain a clear formula to count the number of all these self-dual cyclic codes. As an application, self-dual and $2$-quasi-cyclic codes over $\mathbb{F}_{2^m}$ of length $2^{s+1}n$ can be obtained from self-dual cyclic code over $R$ of length $2^sn$ and by a Gray map preserving orthogonality and distances from $R$ onto $\mathbb{F}_{2^m}^2$.

cs.IT↗

arXiv2019

Massively Multilingual Neural Machine Translation in the Wild: Findings and Challenges

We introduce our efforts towards building a universal neural machine translation (NMT) system capable of translating between any language pair. We set a milestone towards this goal by building a single massively multilingual NMT model handling 103 languages trained on over 25 billion examples. Our system demonstrates effective transfer learning ability, significantly improving translation quality of low-resource languages, while keeping high-resource language translation quality on-par with competitive bilingual baselines. We provide in-depth analysis of various aspects of model building that are crucial to achieving quality and practicality in universal NMT. While we prototype a high-quality universal translation system, our extensive empirical analysis exposes issues that need to be further addressed, and we suggest directions for future research.

cs.CL↗

arXiv2019

Neural Decipherment via Minimum-Cost Flow: from Ugaritic to Linear B

In this paper we propose a novel neural approach for automatic decipherment of lost languages. To compensate for the lack of strong supervision signal, our model design is informed by patterns in language change documented in historical linguistics. The model utilizes an expressive sequence-to-sequence model to capture character-level correspondences between cognates. To effectively train the model in an unsupervised manner, we innovate the training procedure by formalizing it as a minimum-cost flow problem. When applied to the decipherment of Ugaritic, we achieve a 5.5% absolute improvement over state-of-the-art results. We also report the first automatic results in deciphering Linear B, a syllabic language related to ancient Greek, where our model correctly translates 67.3% of cognates.

cs.CL↗

arXiv2019

Gmail Smart Compose: Real-Time Assisted Writing

In this paper, we present Smart Compose, a novel system for generating interactive, real-time suggestions in Gmail that assists users in writing mails by reducing repetitive typing. In the design and deployment of such a large-scale and complicated system, we faced several challenges including model selection, performance evaluation, serving and other practical issues. At the core of Smart Compose is a large-scale neural language model. We leveraged state-of-the-art machine learning techniques for language model training which enabled high-quality suggestion prediction, and constructed novel serving infrastructure for high-throughput and real-time inference. Experimental results show the effectiveness of our proposed system design and deployment approach. This system is currently being served in Gmail.

cs.CL↗

arXiv2019

Explicit representation for a class of Type 2 constacyclic codes over the ring $\mathbb{F}_{2^m}[u]/\langle u^{2λ}\rangle$ with even length

Let $\mathbb{F}_{2^m}$ be a finite field of cardinality $2^m$, $λ$ and $k$ be integers satisfying $λ,k\geq 2$ and denote $R=\mathbb{F}_{2^m}[u]/\langle u^{2λ}\rangle$. Let $δ,α\in \mathbb{F}_{2^m}^{\times}$. For any odd positive integer $n$, we give an explicit representation and enumeration for all distinct $(δ+αu^2)$-constacyclic codes over $R$ of length $2^kn$, and provide a clear formula to count the number of all these codes. As a corollary, we conclude that every $(δ+αu^2)$-constacyclic code over $R$ of length $2^kn$ is an ideal generated by at most $2$ polynomials in the residue class ring $R[x]/\langle x^{2^kn}-(δ+αu^2)\rangle$.

cs.IT↗

arXiv2019

Single-photon computational 3D imaging at 45 km

Long-range active imaging has a variety of applications in remote sensing and target recognition. Single-photon LiDAR (light detection and ranging) offers single-photon sensitivity and picosecond timing resolution, which is desirable for high-precision three-dimensional (3D) imaging over long distances. Despite important progress, further extending the imaging range presents enormous challenges because only weak echo photons return and are mixed with strong noise. Herein, we tackled these challenges by constructing a high-efficiency, low-noise confocal single-photon LiDAR system, and developing a long-range-tailored computational algorithm that provides high photon efficiency and super-resolution in the transverse domain. Using this technique, we experimentally demonstrated active single-photon 3D-imaging at a distance of up to 45 km in an urban environment, with a low return-signal level of $\sim$1 photon per pixel. Our system is feasible for imaging at a few hundreds of kilometers by refining the setup, and thus represents a significant milestone towards rapid, low-power, and high-resolution LiDAR over extra-long ranges.

eess.IV↗

arXiv2019

Umbrella: Enabling ISPs to Offer Readily Deployable and Privacy-Preserving DDoS Prevention Services

Defending against distributed denial of service (DDoS) attacks in the Internet is a fundamental problem. However, recent industrial interviews with over 100 security experts from more than ten industry segments indicate that DDoS problems have not been fully addressed. The reasons are twofold. On one hand, many academic proposals that are provably secure witness little real-world deployment. On the other hand, the operation model for existing DDoS-prevention service providers (e.g., Cloudflare, Akamai) is privacy invasive for large organizations (e.g., government). In this paper, we present Umbrella, a new DDoS defense mechanism enabling Internet Service Providers (ISPs) to offer readily deployable and privacy-preserving DDoS prevention services to their customers. At its core, Umbrella develops a multi-layered defense architecture to defend against a wide spectrum of DDoS attacks. In particular, the flood throttling layer stops amplification-based DDoS attacks; the congestion resolving layer, aiming to prevent sophisticated attacks that cannot be easily filtered, enforces congestion accountability to ensure that legitimate flows are guaranteed to receive their fair shares regardless of attackers' strategies; and finally the userspecific layer allows DDoS victims to enforce self-desired traffic control policies that best satisfy their business requirements. Based on Linux implementation, we demonstrate that Umbrella is capable to deal with large scale attacks involving millions of attack flows, meanwhile imposing negligible packet processing overhead. Further, our physical testbed experiments and large scale simulations prove that Umbrella is effective to mitigate various DDoS attacks.

cs.CR↗

arXiv2019

Electric Field Tunable Correlated States and Magnetic Phase Transitions in Twisted Bilayer-Bilayer Graphene

The recent discovery of correlated insulator states and superconductivity in magic-angle twisted bilayer graphene has paved the way to the experimental investigation of electronic correlations in tunable flat band systems realized in twisted van der Waals heterostructures. This novel twist angle degree of freedom and control should be generalizable to other 2D systems, which may exhibit similar correlated physics behavior while at the same time enabling new techniques to tune and control the strength of electron-electron interactions. Here, we report on a new highly tunable correlated system based on small-angle twisted bilayer-bilayer graphene (TBBG), consisting of two rotated sheets of Bernal-stacked bilayer graphene. We find that TBBG exhibits a rich phase diagram, with tunable correlated insulators states that are highly sensitive to both twist angle and to the application of an electric displacement field, the latter reflecting the inherent polarizability of Bernal-stacked bilayer graphene. We find correlated insulator states that can be switched on and off by the displacement field at all integer electron fillings of the moiré unit cell. The response of these correlated states to magnetic fields points towards evidence of electrically switchable magnetism. Moreover, the strong dependence of the resistance at low temperature and near the correlated insulator states indicates possible proximity to a superconducting phase. Furthermore, in the regime of lower twist angles, TBBG shows multiple sets of flat bands near charge neutrality, resulting in numerous correlated states corresponding to half-filling of each of these flat bands. Our results pave the way to the exploration of novel twist-angle and electric-field controlled correlated phases of matter in novel multi-flat band twisted superlattices.

cond-mat.str-el↗

arXiv2019

An explicit representation and enumeration for negacyclic codes of length $2^kn$ over $\mathbb{Z}_4+u\mathbb{Z}_4$

In this paper, an explicit representation and enumeration for negacyclic codes of length $2^kn$ over the local non-principal ideal ring $R=\mathbb{Z}_4+u\mathbb{Z}_4$ $(u^2=0)$ is provided, where $k, n$ are any positive integers and $n$ is odd. As a corollary, all distinct negacyclic codes of length $2^k$ over $R$ are listed precisely. Moreover, a mass formula for the number of negacyclic codes of length $2^kn$ over $R$ is given and a mistake in [Cryptogr. Commun. (2017) 9: 241--272] is corrected.

cs.IT↗

arXiv2019

AccFlow: Defending Against the Low-Rate TCP DoS Attack in Wireless Sensor Networks

Because of the open nature of the Wireless Sensor Networks (WSN), the Denial of the Service (DoS) becomes one of the most serious threats to the stability of the resourceconstrained sensor nodes. In this paper, we develop AccFlow which is an incrementally deployable Software-Defined Networking based protocol that is able to serve as a countermeasure against the low-rate TCP DoS attack. The main idea of AccFlow is to make the attacking flows accountable for the congestion by dropping their packets according to their loss rates. The larger their loss rates, the more aggressively AccFlow drops their packets. Through extensive simulations, we demonstrate that AccFlow can effectively defend against the low-rate TCP DoS attack even if attackers vary their strategies by attacking at different scales and data rates. Furthermore, while AccFlow is designed to solve the low-rate TCP DoS attack, we demonstrate that AccFlow can also effectively defend against general DoS attacks which do not rely on the TCP retransmission timeout mechanism but cause denial of service to legitimate users by consistently exhausting the network resources. Finally, we consider the scalability of AccFlow and its deployment in real networks.

cs.CR↗