Searcharxiv⌕ Search

arXiv subjects

Yu Xu

Publications and source records attributed to Yu Xu.

At least 127 records · Page 7Linked to original sources

Experimental exploration of five-qubit quantum error correcting code with superconducting qubits

Quantum error correction is an essential ingredient for universal quantum computing. Despite tremendous experimental efforts in the study of quantum error correction, to date, there has been no demonstration in the realisation of universal quantum error correcting code, with the subsequent verification of all key features including the identification of an arbitrary physical error, the capability for transversal manipulation of the logical state, and state decoding. To address this challenge, we experimentally realise the $[\![5,1,3]\!]$ code, the so-called smallest perfect code that permits corrections of generic single-qubit errors. In the experiment, having optimised the encoding circuit, we employ an array of superconducting qubits to realise the $[\![5,1,3]\!]$ code for several typical logical states including the magic state, an indispensable resource for realising non-Clifford gates. The encoded states are prepared with an average fidelity of $57.1(3)\%$ while with a high fidelity of $98.6(1)\%$ in the code space. Then, the arbitrary single-qubit errors introduced manually are identified by measuring the stabilizers. We further implement logical Pauli operations with a fidelity of $97.2(2)\%$ within the code space. Finally, we realise the decoding circuit and recover the input state with an overall fidelity of $74.5(6)\%$, in total with $92$ gates. Our work demonstrates each key aspect of the $[\![5,1,3]\!]$ code and verifies the viability of experimental realization of quantum error correcting codes with superconducting qubits.

quant-ph↗

Observation of thermalization and information scrambling in a superconducting quantum processor

Understanding various phenomena in non-equilibrium dynamics of closed quantum many-body systems, such as quantum thermalization, information scrambling, and nonergodic dynamics, is a crucial for modern physics. Using a ladder-type superconducting quantum processor, we perform analog quantum simulations of both the $XX$ ladder and one-dimensional (1D) $XX$ model. By measuring the dynamics of local observables, entanglement entropy and tripartite mutual information, we signal quantum thermalization and information scrambling in the $XX$ ladder. In contrast, we show that the $XX$ chain, as free fermions on a 1D lattice, fails to thermalize, and local information does not scramble in the integrable channel. Our experiments reveal ergodicity and scrambling in the controllable qubit ladder, and opens the door to further investigations on the thermodynamics and chaos in quantum many-body systems.

quant-ph↗

Verification of a resetting protocol for an uncontrolled superconducting qubit

Quantum resetting protocols allow a quantum system to be sent to a state in the past by making it interact with quantum probes when neither the free evolution of the system nor the interaction is controlled. We experimentally verify the simplest non-trivial case of a quantum resetting protocol, known as the $\mathcal{W}_4$ protocol, with five superconducting qubits, testing it with different types of free evolutions and target-probe interactions. After projection, we obtained a reset state fidelity as high as $0.951$, and the process fidelity was found to be $0.792$. We also implemented 100 randomly-chosen interactions and demonstrated an average success probability of $0.323$ for $|1\rangle$ and $0.292$ for $|-\rangle$, experimentally confirmed the nonzero probability of success for unknown interactions; the numerical simulated values are about $0.3$. Our experiment shows that the simplest quantum resetting protocol can be implemented with current technologies, making such protocols a valuable tool in the eternal fight against unwanted evolution in quantum systems.

quant-ph↗

Experimental characterization of quantum many-body localization transition

As strength of disorder enhances beyond a threshold value in many-body systems, a fundamental transformation happens through which the entire spectrum localizes, a phenomenon known as many-body localization. This has profound implications as it breaks down fundamental principles of statistical mechanics, such as thermalization and ergodicity. Due to the complexity of the problem, the investigation of the many-body localization transition has remained a big challenge. The experimental exploration of the transition point is even more challenging as most of the proposed quantities for studying such effect are practically infeasible. Here, we experimentally implement a scalable protocol for detecting the many-body localization transition point, using the dynamics of a $N=12$ superconducting qubit array. We show that the sensitivity of the dynamics to random samples becomes maximum at the transition point which leaves its fingerprints in all spatial scales. By exploiting three quantities, each with different spatial resolution, we identify the transition point with excellent match between simulation and experiment. In addition, one can detect the evidence of mobility edge through slight variation of the transition point as the initial state varies. The protocol is easily scalable and can be performed across various physical platforms.

quant-ph↗

Origin of the Electronic Structure in Single-Layer FeSe/SrTiO3 Films

The accurate theoretical description of the underlying electronic structures is essential for understanding the superconducting mechanism of iron-based superconductors. Compared to bulk FeSe, the superconducting single-layer FeSe/SrTiO3 films exhibit a distinct electronic structure consisting of only electron Fermi pockets, due to the formation of a new band gap at the Brillouin zone (BZ) corners and an indirect band gap between the BZ center and corners. Although intensive studies have been carried out, the origin of such a distinct electronic structure and its connection to bulk FeSe remain unclear. Here we report a systematic study on the temperature evolution of the electronic structure in single-layer FeSe/SrTiO3 films by angle-resolved photoemission spectroscopy. A temperature-induced electronic phase transition was clearly observed at 200 K, above which the electronic structure of single-layer FeSe/SrTiO3 films restored to that of bulk FeSe, characterized by the closing of the new band gap and the vanishing of the indirect band gap. Moreover, the interfacial charge transfer effect induced band shift of ~ 60 meV was determined for the first time. These observations not only show the first direct evidence that the electronic structure of single-layer FeSe/SrTiO3 films originates from bulk FeSe through a combined effect of an electronic phase transition and an interfacial charge transfer, but also provide a quantitative basis for theoretical models in describing the electronic structure and understanding the superconducting mechanism in single-layer FeSe/SrTiO3 films.

cond-mat.supr-con↗

Emulating quantum teleportation of a Majorana zero mode qubit

Topological quantum computation based on anyons is a promising approach to achieve fault-tolerant quantum computing. The Majorana zero modes in the Kitaev chain are an example of non-Abelian anyons where braiding operations can be used to perform quantum gates. Here we perform a quantum simulation of topological quantum computing, by teleporting a qubit encoded in the Majorana zero modes of a Kitaev chain. The quantum simulation is performed by mapping the Kitaev chain to its equivalent spin version, and realizing the ground states in a superconducting quantum processor. The teleportation transfers the quantum state encoded in the spin-mapped version of the Majorana zero mode states between two Kitaev chains. The teleportation circuit is realized using only braiding operations, and can be achieved despite being restricted to Clifford gates for the Ising anyons. The Majorana encoding is a quantum error detecting code for phase flip errors, which is used to improve the average fidelity of the teleportation for six distinct states from $70.76 \pm 0.35 \% $ to $84.60 \pm 0.11 \%$, well beyond the classical bound in either case.

quant-ph↗

Study of using machine learning for level 1 trigger decision in JUNO experiment

A study on the use of a machine learning algorithm for the level 1 trigger decision in the JUNO experiment ispresented. JUNO is a medium baseline neutrino experiment in construction in China, with the main goal of determining the neutrino mass hierarchy. A large liquid scintillator (LS)volume will detect the electron antineutrinos issued from nuclear reactors. The LS detector is instrumented by around 20000 large photomultiplier tubes. The hit information from each PMT will be collected into a center trigger unit for the level 1 trigger decision. The current trigger algorithm used to select a neutrino signal event is based on a fast vertex reconstruction. We propose to study an alternative level 1 (L1) trigger in order to achieve a similar performance as the vertex fitting trigger but with less logic resources by using firmware implemented machine learning model at the L1 trigger level. We treat the trigger decision as a classification problem and train a Multi-Layer Perceptron (MLP)model to distinguish the signal events with an energy higher than a certain threshold from noise events. We use JUNO software to generate datasets which include 100K physics events with noise and 100K pure noise events coming from PMT dark noise.For events with energy higher than 100 keV, the L1 trigger based on the converged MLP model can achieve an efficiency higher than 99%. After the training performed on simulations,we successfully implemented the trained model into a Kintex 7FPGA. We present the technical details of the neural network development and training, as well as its implementation in the hardware with the FPGA programming. Finally the performance of the L1 trigger MLP implementation is discussed.

physics.ins-det↗

Spectroscopic Evidence of Superconductivity Pairing at 83 K in Single-Layer FeSe/SrTiO3 Films

Single-layer FeSe films grown on the SrTiO3 substrate (FeSe/STO) have attracted much attention because of their possible record-high superconducting critical temperature Tc and distinct electronic structures in iron-based superconductors. However, it has been under debate on how high its Tc can really reach due to the inconsistency of the results obtained from the transport, magnetic and spectroscopic measurements. Here we report spectroscopic evidence of superconductivity pairing at 83 K in single-layer FeSe/STO films. By preparing high-quality single-layer FeSe/STO films, we observe for the first time strong superconductivity-induced Bogoliubov back-bending bands that extend to rather high binding energy ~100 meV by high-resolution angle-resolved photoemission measurements. The Bogoliubov back-bending band provides a new definitive benchmark of superconductivity pairing that is directly observed up to 83 K in the single-layer FeSe/STO films. Moreover, we find that the superconductivity pairing state can be further divided into two temperature regions of 64-83 K and below 64 K. We propose the 64-83 K region may be attributed to superconductivity fluctuation while the region below 64 K corresponds to the realization of long-range superconducting phase coherence. These results indicate that either Tc as high as 83 K is achievable in iron-based superconductors, or there is a pseudogap formation from superconductivity fluctuation in single-layer FeSe/STO films.

cond-mat.supr-con↗

AutoADR: Automatic Model Design for Ad Relevance

Large-scale pre-trained models have attracted extensive attention in the research community and shown promising results on various tasks of natural language processing. However, these pre-trained models are memory and computation intensive, hindering their deployment into industrial online systems like Ad Relevance. Meanwhile, how to design an effective yet efficient model architecture is another challenging problem in online Ad Relevance. Recently, AutoML shed new lights on architecture design, but how to integrate it with pre-trained language models remains unsettled. In this paper, we propose AutoADR (Automatic model design for AD Relevance) -- a novel end-to-end framework to address this challenge, and share our experience to ship these cutting-edge techniques into online Ad Relevance system at Microsoft Bing. Specifically, AutoADR leverages a one-shot neural architecture search algorithm to find a tailored network architecture for Ad Relevance. The search process is simultaneously guided by knowledge distillation from a large pre-trained teacher model (e.g. BERT), while taking the online serving constraints (e.g. memory and latency) into consideration. We add the model designed by AutoADR as a sub-model into the production Ad Relevance model. This additional sub-model improves the Precision-Recall AUC (PR AUC) on top of the original Ad Relevance model by 2.65X of the normalized shipping bar. More importantly, adding this automatically designed sub-model leads to a statistically significant 4.6% Bad-Ad ratio reduction in online A/B testing. This model has been shipped into Microsoft Bing Ad Relevance Production model.

cs.CL↗

Particle Identification at MeV Energies in JUNO

JUNO is a multi-purpose neutrino experiment currently under construction in Jiangmen, China. It is primary aiming to determine the neutrino mass ordering. Moreover, its 20\,kt target mass makes it an ideal detector to study neutrinos from various sources, including nuclear reactors, the Earth and its atmosphere, the Sun, and even supernovae. Due to the small cross section of neutrino interactions, the event rate of neutrino experiments is limited. In order to maximize the signal-to-noise ratio, it is extremely important to control the background levels. In this paper we discuss the potential of particle identification in JUNO, its underlying principles and possible areas of application in the experiment. While the presented concepts can be transferred to any large liquid scintillator detector, our methods are evaluated specifically for JUNO and the results are mainly driven by its high optical photon yield of 1,200 photo electrons per MeV of deposited energy. In order to investigate the potential of event discrimination, several event pairings are analysed, i.e. $α/β$, $p/β$, $e^+/e^-$, and $e^-/γ$. We compare the discrimination performance of advanced analytical techniques based on neural networks and on the topological event reconstruction keeping the standard Gatti filter as a reference. We use the Monte Carlo samples generated in the physically motivated energy intervals. We study the dependence of our cuts on energy, radial position, PMT time resolution, and dark noise. The results show an excellent performance for $α/β$ and $p/β$ with the Gatti method and the neural network. Furthermore, $e^+/e^-$ and $e^-/γ$ can partly be distinguished by means of neural network and topological reconstruction on a statistical basis. Especially in the latter case, the topological method proved very successful.

physics.ins-det↗

Microwave diagnostics of magnetic field strengths in solar flaring loops

We have performed microwave diagnostics of the magnetic field strengths in solar flare loops based on the theory of gyrosynchrotron emission. From Nobeyama Radioheliograph observations of three flare events at 17 and 34 GHz, we obtained the degree of circular polarization and the spectral index of microwave flux density, which were then used to map the magnetic field strengths in post-flare loops. Our results show that the magnetic field strength typically decreases from ~800 G near the loop footpoints to ~100 G at a height of 10--25 Mm. Comparison of our results with magnetic field modeling using a flux rope insertion method is also discussed. Our study demonstrates the potential of microwave imaging observations, even at only two frequencies, in diagnosing the coronal magnetic field of flaring regions.

astro-ph.SR↗

GIANT: Scalable Creation of a Web-scale Ontology

Understanding what online users may pay attention to is key to content recommendation and search services. These services will benefit from a highly structured and web-scale ontology of entities, concepts, events, topics and categories. While existing knowledge bases and taxonomies embody a large volume of entities and categories, we argue that they fail to discover properly grained concepts, events and topics in the language style of online population. Neither is a logically structured ontology maintained among these notions. In this paper, we present GIANT, a mechanism to construct a user-centered, web-scale, structured ontology, containing a large number of natural language phrases conforming to user attentions at various granularities, mined from a vast volume of web documents and search click graphs. Various types of edges are also constructed to maintain a hierarchy in the ontology. We present our graph-neural-network-based techniques used in GIANT, and evaluate the proposed methods as compared to a variety of baselines. GIANT has produced the Attention Ontology, which has been deployed in various Tencent applications involving over a billion users. Online A/B testing performed on Tencent QQ Browser shows that Attention Ontology can significantly improve click-through rates in news recommendation.

cs.CL↗

Ergodic-localized junctions in a periodically-driven spin chain

We report the analogue simulation of an ergodiclocalized junction by using an array of 12 coupled superconducting qubits. To perform the simulation, we fabricated a superconducting quantum processor that is divided into two domains: a driven domain representing an ergodic system, while the second is localized under the effect of disorder. Due to the overlap between localized and delocalized states, for small disorder there is a proximity effect and localization is destroyed. To experimentally investigate this, we prepare a microwave excitation in the driven domain and explore how deep it can penetrate the disordered region by probing its dynamics. Furthermore, we performed an ensemble average over 50 realizations of disorder, which clearly shows the proximity effect. Our work opens a new avenue to build quantum simulators of driven-disordered systems with applications in condensed matter physics and material science

quant-ph↗

Estimation of $Υ$(1S) production in ep process near threshold

The near-threshold photo-productions of heavy quarkonia are important ways to test the QCD-inspired models and to constrain the gluon distribution of nucleon in the large x region. Investigating the various models, we choose a photon-gluon fusion model and a pomeron exchange model for J/$Ψ$ photo-production near threshold, emphasising on the explanation of the recent experimental measurement by GlueX at JLab. We find that these two models are not only valid in a wide range of the center-of-mass energy of $γ$ and proton, but also can be generalized to describe the $Υ$(1S) photo-production. Using these two models, we predict the electro-production cross-sections of $Υ$(1S) at EicC to be 48 fb to 85 fb at the center-of-mass energy of 16.75 GeV.

hep-ph↗

Direct Measurement of the Electronic Structure and band gap nature of atomic-layer-thick 2H-MoTe2

The millimeter sized monolayer and bilayer 2H-MoTe2 single crystal samples are prepared by a new mechanical exfoliation method. Based on such high-quality samples, we report the first direct electronic structure study on them, using standard high resolution angle-resolved photoemission spectroscopy (ARPES). A direct band gap of 0.924eV is found at K in the rubidium-doped monolayer MoTe2. Similar valence band alignment is also observed in bilayer MoTe2,supporting an assumption of a analogous direct gap semiconductor on it. Our measurements indicate a rather large band splitting of 212meV at the valence band maximum (VBM) in monolayer MoTe2, and the splitting is systematically enlarged with layer stacking, from monolayer to bilayer and to bulk. Meanwhile, our PBE band calculation on these materials show excellent agreement with ARPES results. Some fundamental electronic parameters are derived from the experimental and calculated electronic structures. Our findings lay a foundation for further application-related study on monolayer and bilayer MoTe2.

cond-mat.mtrl-sci↗

Spectroscopic Evidence of Bilayer Splitting and Interlayer Pairing in an Iron Based Superconductor

In high temperature cuprate superconductors, the interlayer coupling between the CuO$_2$ planes plays an important role in dictating superconductivity, as indicated by the sensitive dependence of the critical temperature (T$_C$) on the number of CuO$_2$ planes in one structural unit. In Bi$_2$Sr$_2$CaCu$_2$O$_{8+δ}$ superconductor with two CuO$_2$ planes in one structural unit, the interaction between the two CuO$_2$ planes gives rise to band splitting into two Fermi surface sheets (bilayer splitting) that have distinct superconducting gap. The iron based superconductors are composed of stacking of the FeAs/FeSe layers; whether the interlayer coupling can cause similar band splitting and its effect on superconductivity remain unclear. Here we report high resolution laser-based angle-resolved photoemission spectroscopy (ARPES) measurements on a newly discovered iron based superconductor, KCa$_2$Fe$_4$As$_4$F$_2$ (T$_C$=33.5\,K) which consists of stacking FeAs blocks with two FeAs layers separated by insulating Ca$_2$F$_2$ blocks. Bilayer splitting effect is observed for the first time that gives rise to totally five hole-like Fermi surface sheets around the Brilliouin zone center. Band structure calculations reproduce the observed bilayer splitting by identifying interlayer interorbital interaction between the two FeAs layers within one FeAs block. All the hole-like pockets around the zone center exhibit Fermi surface-dependent and nodeless superconducting gap. The gap functions with short-range antiferromagetic fluctuations are proposed and the gap symmetry can be well understood when the interlayer pairing is considered. The particularly strong interlayer pairing is observed for one of the bands. Our observations provide key information on the interlayer coupling and interlayer pairing in understanding superconductivity in iron based superconductors.

cond-mat.supr-con↗

Electronic Structure of Exfoliated Millimeter-Sized Monolayer WSe2 on Silicon Wafer

The monolayer WSe2 is interesting and important for future application in nanoelectronics, spintronics and valleytronics devices, because it has the largest spin splitting and longest valley coherence time among all the known monolayer transition-metal dichalcogenides (TMDs). To obtain the large-area monolayer TMDs' crystal is the first step to manufacture scalable and high-performance electronic devices. In this letter, we have successfully fabricated millimeter-sized monolayer WSe2 single crystals with very high quality, based on our improved mechanical exfoliation method. With such superior samples, using standard high resolution angle-resolved photoemission spectroscopy, we did comprehensive electronic band structure measurements on our monolayer WSe2. The overall band features point it to be a 1.2eV direct band gap semiconductor. Its spin-splitting of the valence band at K point is found as 460 meV, which is 30 meV less than the corresponding band splitting in its bulk counterpart. The effective hole masses of valence bands are determined as 2.344 me at Gamma, and 0.529 me as well as 0.532 me at K for the upper and lower branch of splitting bands, respectively. And screening effect from substrate is shown to substantially impact on the electronic properties. Our results provide important insights into band structure engineering in monolayer TMDs. Our monolayer WSe2 crystals may constitute a valuable device platform.

cond-mat.mes-hall↗

Joint Computation and Communication Design for UAV-Assisted Mobile Edge Computing in IoT

Unmanned aerial vehicle (UAV)-assisted mobile edge computing (MEC) system is a prominent concept, where a UAV equipped with a MEC server is deployed to serve a number of terminal devices (TDs) of Internet of Things (IoT) in a finite period. In this paper, each TD has a certain latency-critical computation task in each time slot to complete. Three computation strategies can be available to each TD. First, each TD can operate local computing by itself. Second, each TD can partially offload task bits to the UAV for computing. Third, each TD can choose to offload task bits to access point (AP) via UAV relaying. We propose a new optimization problem formulation that aims to minimize the total energy consumption including communication-related energy, computation-related energy and UAV's flight energy by optimizing the bits allocation, time slot scheduling and power allocation as well as UAV trajectory design. As the formulated problem is non-convex and difficult to find the optimal solution, we solve the problem by two parts, and obtain the near optimal solution with within a dozen of iterations. Finally, numerical results are given to validate the proposed algorithm, which is verified to be efficient and superior to the other benchmark cases.

eess.SP↗