arXiv subjects

Yan Xia

Publications and source records attributed to Yan Xia.

At least 181 records · Page 10Linked to original sources

arXiv2022

Robust population inversion in three-level systems by composite pulses

In this work, we exploit the idea of composite pulses to achieve robust population inversion in a three-level quantum system. The scheme is based on the modulation of the coupling strength, while the other physical parameters remain unchanged. The composite pulses sequence is designed by vanishing high-order error terms, and can compensate the systematic errors to any desired order. In particular, this scheme keeps a good performance under the disturbance of waveform deformations. This trait ensures that population inversion can be nearly obtained even when the pulse sequence has a short jump delay. As an example, we employ the designed composite pulse sequence to prepare the W state in a robust manner in the superconducting circuits. The numerical results show that the fidelity can still maintain a high level in a decoherence environment.

quant-ph↗

arXiv2022

Nonadiabatic geometric quantum computation with cat qubits via invariant-based reverse engineering

We propose a protocol to realize nonadiabatic geometric quantum computation of small-amplitude Schrödinger cat qubits via invariant-based reverse engineering. We consider a system with a two-photon driven Kerr nonlinearity, which provides a pair of dressed even and odd coherent states, i.e., Schrödinger cat states for fault-tolerant quantum computations. An additional coherent field is applied to linearly drive a cavity mode, to induce oscillations between dressed cat states. By designing this linear drive with invariant-based reverse engineering, nonadiabatic geometric quantum computation with cat qubits can be implemented. The performance of the protocol is estimated by taking into account the influence of systematic errors, additive white Gaussian noise, and decoherence including photon loss and dephasing. Numerical results demonstrate that our protocol is robust against these negative factors. Therefore, this protocol may provide a feasible method for nonadiabatic geometric quantum computation in bosonic systems.

quant-ph↗

arXiv2022

An Approach to Mispronunciation Detection and Diagnosis with Acoustic, Phonetic and Linguistic (APL) Embeddings

Many mispronunciation detection and diagnosis (MD&D) research approaches try to exploit both the acoustic and linguistic features as input. Yet the improvement of the performance is limited, partially due to the shortage of large amount annotated training data at the phoneme level. Phonetic embeddings, extracted from ASR models trained with huge amount of word level annotations, can serve as a good representation of the content of input speech, in a noise-robust and speaker-independent manner. These embeddings, when used as implicit phonetic supplementary information, can alleviate the data shortage of explicit phoneme annotations. We propose to utilize Acoustic, Phonetic and Linguistic (APL) embedding features jointly for building a more powerful MD&D system. Experimental results obtained on the L2-ARCTIC database show the proposed approach outperforms the baseline by 9.93%, 10.13% and 6.17% on the detection accuracy, diagnosis error rate and the F-measure, respectively.

cs.CL↗

arXiv2022

Noise assisted quantum coherence protection in hierarchical environment

In this paper, we investigate coherence protection of a quantum system coupled to a hierarchical environment by utilizing noise. As an example, we solve the Jaynes-Cummings (J-C) model in presence of both a classical and a quantized noise. The master equation is derived beyond the Markov approximation, where the influence of memory effects from both noises is taken into account. More importantly, we find that the performance of the coherence protection sensitively depends on the non-Markovian properties of both noises. By analyzing the mathematical mechanism of the coherence protection, we show the decoherence caused by a non-Markovian noise with longer memory time can be suppressed by another Markovian noise with shorter memory time. Last but not least, as an outlook, we try to analyze the connection between the atom-cavity entanglement and the atomic coherence, then discuss the possible clue to search for the required noise. The results presented in this paper show the possibility of protecting coherence by utilizing noise and may open a new path to design noise-assisted coherence protection schemes.

quant-ph↗

arXiv2022

Detecting a single atom in a cavity using the $χ^{(2)}$ nonlinear medium

We propose a protocol for detecting a single atom in a cavity with the help of the $χ^{(2)}$ nonlinear medium. When the $χ^{(2)}$ nonlinear medium is driven by an external laser field, the cavity mode will be squeezed, and thus one can obtain an exponentially enhanced light-matter coupling. Such a strong coupling between the atom and the cavity field can significantly change the output photon flux, the quantum fluctuations, the quantum statistical property, and the photon number distributions of the cavity field. This provides practical strategies to determine the presence or absence of an atom in a cavity. The proposed protocol exhibits some advantages, such as controllable squeezing strength and exponential increase of atom-cavity coupling strength, which make the experimental phenomenon more obvious. We hope that this protocol can supplement the existing intracavity single-atom detection protocols and provide a promise for quantum sensing in different quantum systems.

quant-ph↗

arXiv2022

Composite pulses for high fidelity population transfer in three-level systems

In this work, we propose a composite pulses scheme by modulating phases to achieve high fidelity population transfer in three-level systems. To circumvent the obstacle that not enough variables are exploited to eliminate the systematic errors in the transition probability, we put forward a cost function to find the optimal value. The cost function is independently constructed either in ensuring an accurate population of the target state, or in suppressing the population of the leakage state, or both of them. The results demonstrate that population transfer is implemented with high fidelity even when existing the deviations in the coupling coefficients. Furthermore, our composite pulses scheme can be extensible to arbitrarily long pulse sequences. As an example, we employ the composite pulses sequence for achieving the three-atom singlet state in an atom-cavity system with ultrahigh fidelity. The final singlet state shows robustness against deviations and is not seriously affected by waveform distortions. Also, the singlet state maintains a high fidelity under the decoherence environment.

quant-ph↗

arXiv2021

Enhanced phonon blockade in a weakly-coupled hybrid system via mechanical parametric amplification

We propose how to achieve strong phonon blockade (PB) in a hybrid spin-mechanical system in the weak-coupling regime. We demonstrate the implementation of magnetically-induced two-phonon interactions between a mechanical cantilever resonator and an embedded nitrogen-vacancy (NV) center, which, combined with parametric amplification of the mechanical motion, produces significantly enlarged anharmonicity in the eigenenergy spectrum. In the weak-driving regime, we show that strong PB appears in the hybrid system along with a large mean phonon number, even in the presence of strong mechanical dissipation. We also show flexible tunability of phonon statistics by controlling the strength of mechanical parametric amplification. Our work opens up prospects for the implementation of an efficient single-phonon source, with potential applications in quantum phononics and phononic quantum networks.

quant-ph↗

arXiv2021

Systematic error tolerant multiqubit holonomic entangling gates

Quantum holonomic gates hold built-in resilience to local noises and provide a promising approach for implementing fault-tolerant quantum computation. We propose to realize high-fidelity holonomic $(N+1)$-qubit controlled gates using Rydberg atoms confined in optical arrays or superconducting circuits. We identify the scheme, deduce the effective multi-body Hamiltonian, and determine the working condition of the multiqubit gate. Uniquely, the multiqubit gate is immune to systematic errors, i.e., laser parameter fluctuations and motional dephasing, as the $N$ control atoms largely remain in the much stable qubit space during the operation. We show that $C_N$-NOT gates can reach same level of fidelity at a given gate time for $N\leq5$ under a suitable choice of parameters, and the gate tolerance against errors in systematic parameters can be further enhanced through optimal pulse engineering. In case of Rydberg atoms, the proposed protocol is intrinsically different from typical schemes based on Rydberg blockade or antiblockade. Our study paves a new route to build robust multiqubit gates with Rydberg atoms trapped in optical arrays or with superconducting circuits. It contributes to current efforts in developing scalable quantum computation with trapped atoms and fabricable superconducting devices.

quant-ph↗

arXiv2021

Unidirectional acoustic metamaterials based on nonadiabatic holonomic quantum transformations

Nonadiabatic holonomic quantum transformations (NHQTs) have attracted wide attention and have been applied in many aspects of quantum computation, whereas related research is usually limited to the field of quantum physics. Here we bring NHQTs into constructing a unidirectional acoustic metamaterial (UDAM) for shaping classical beams. The UDAM is made up of an array of three-waveguide couplers, where the propagation of acoustic waves mimics the evolution of NHQTs. The excellent agreement among analytical predictions, numerical simulations, and experimental measurements confirms the great applicability of NHQTs in acoustic metamaterial engineering. The present work extends research on NHQTs from quantum physics to the field of classical waves for designing metamaterials with simple structures and may pave a new way to design UDAMs that would be of potential applications in acoustic isolation, communication, and stealth.

physics.class-ph↗

arXiv2021

Two-level systems with periodic $N$-step driving fields: Exact dynamics and quantum state manipulations

In this work, we derive exact solutions of a dynamical equation, which can represent all two-level Hermitian systems driven by periodic $N$-step driving fields. For different physical parameters, this dynamical equation displays various phenomena for periodic $N$-step driven systems. The time-dependent transition probability can be expressed by a general formula that consists of cosine functions with discrete frequencies, and, remarkably, this formula is suitable for arbitrary parameter regimes. Moreover, only a few cosine functions (i.e., one to three main frequencies) are sufficient to describe the actual dynamics of the periodic $N$-step driven system. {Furthermore}, we find that a beating in the transition probability emerges when two (or three) main frequencies are similar. Some applications are also demonstrated in quantum state manipulations by periodic $N$-step driving fields.

quant-ph↗

arXiv2021

Rapid Assessments of Light-Duty Gasoline Vehicle Emissions Using On-Road Remote Sensing and Machine Learning

In-time and accurate assessments of on-road vehicle emissions play a central role in urban air quality and health policymaking. However, official insight is hampered by the Inspection/Maintenance (I/M) procedure conducted in the laboratory annually. It not only has a large gap to real-world situations (e.g., meteorological conditions) but also is incapable of regular supervision. Here we build a unique dataset including 103831 light-duty gasoline vehicles, in which on-road remote sensing (ORRS) measurements are linked to the I/M records based on the vehicle identification numbers and license plates. On this basis, we develop an ensemble model framework that integrates three machining learning algorithms, including neural network (NN), extreme gradient boosting (XGBoost), and random forest (RF). We demonstrate that this ensemble model could rapidly assess the vehicle-specific emissions (i.e., CO, HC, and NO). In particular, the model performs quite well for the passing vehicles under normal conditions (i.e., lower VSP (< 18 kw/t), temperature (6 ~ 32 °C), relative humidity (< 80%), and wind speed (< 5m/s)). Together with the current emission standard, we identify a large number of the dirty (2.33%) or clean (74.92%) vehicles in the real world. Our results show that the ORRS measurements, assisted by the machine-learning-based ensemble model developed here, can realize day-to-day supervision of on-road vehicle-specific emissions. This approach framework provides a valuable opportunity to reform the I/M procedures globally and mitigate urban air pollution deeply.

cs.LG↗

arXiv2021

Demonstration of dynamical control of three-level open systems with a superconducting qutrit

We propose a method for the dynamical control in three-level open systems and realize it in the experiment with a superconducting qutrit. Our work demonstrates that in the Markovian environment for a relatively long time (3 us), the systemic populations or coherence can still strictly follow the preset evolution paths. This is the first experiment for precisely controlling the Markovian dynamics of three-level open systems, providing a solid foundation for the future realization of dynamical control in multiple open systems. An instant application of the techniques demonstrated in this experiment is to stabilize the energy of quantum batteries.

quant-ph↗

arXiv2021

Spread of Tweets in Climate Discussions

Characterising the spreading of ideas within echo chambers is essential for understanding polarisation. In this paper, we explore the characteristics of popular and viral content in climate change discussions on Twitter around the 2019 announcement of the Nobel Peace Prize, where we find the retweet network of users to be polarised into two well-separated groups of activists and sceptics. Operationalising popularity as the number of retweets and virality as the spreading probability inferred using an independent cascade model, we find that the viral themes echo and differ from the popular themes in interesting ways. Most importantly, we find that the most viral themes in the two groups reflect different types of bonds that tie the community together, yet both function to enhance ingroup connections while repulsing outgroup engagement. With this, our study sheds light, from an information spreading perspective, on the formation and upkeep of echo chambers in climate discussions.

cs.SI↗

arXiv2021

ASFM-Net: Asymmetrical Siamese Feature Matching Network for Point Completion

We tackle the problem of object completion from point clouds and propose a novel point cloud completion network employing an Asymmetrical Siamese Feature Matching strategy, termed as ASFM-Net. Specifically, the Siamese auto-encoder neural network is adopted to map the partial and complete input point cloud into a shared latent space, which can capture detailed shape prior. Then we design an iterative refinement unit to generate complete shapes with fine-grained details by integrating prior information. Experiments are conducted on the PCN dataset and the Completion3D benchmark, demonstrating the state-of-the-art performance of the proposed ASFM-Net. Our method achieves the 1st place in the leaderboard of Completion3D and outperforms existing methods with a large margin, about 12%. The codes and trained models are released publicly at https://github.com/Yan-Xia/ASFM-Net.

cs.CV↗

arXiv2021

Optimized nonadiabatic holonomic quantum computation based on Förster resonance in Rydberg atoms

In this paper, we propose a scheme for implementing the nonadiabatic holonomic quantum computation (NHQC+) of two Rydberg atoms by using invariant-based reverse engineering (IBRE). The scheme is based on Förster resonance induced by strong dipole-dipole interaction between two Rydberg atoms, which provides a selective coupling mechanism to simply the dynamics of system. Moreover, for improving the fidelity of the scheme, the optimal control method is introduced to enhance the gate robustness against systematic errors. Numerical simulations show the scheme is robust against the random noise in control fields, the deviation of dipole-dipole interaction, the Förster defect, and the spontaneous emission of atoms. Therefore, the scheme may provide some useful perspectives for the realization of quantum computation with Rydberg atoms.

quant-ph↗

arXiv2021

Unselective ground-state blockade of Rydberg atoms for implementing quantum gates

A dynamics regime of Rydberg atoms, unselective ground-state blockade (UGSB), is proposed in the context of Rydberg antiblockade (RAB), where the evolution of two atoms is suppressed when they populate in an identical ground state. UGSB is used to implement a SWAP gate in one step without individual addressing of atoms. Aiming at circumventing common issues in RAB-based gates including atomic decay, Doppler dephasing, and fluctuations in the interatomic coupling strength, we modify the RAB condition to achieve a dynamical SWAP gate whose robustness is much greater than that of the nonadiabatic holonomic one in the conventional RAB regime. In addition, on the basis of the proposed SWAP gates, we further investigate the implementation of a three-atom Fredkin gate by combining Rydberg blockade and RAB. The present work may facilitate to implement the RAB-based gates of strongly coupled atoms in experiment.

quant-ph↗

arXiv2021

A Deep Discontinuity-Preserving Image Registration Network

Image registration aims to establish spatial correspondence across pairs, or groups of images, and is a cornerstone of medical image computing and computer-assisted-interventions. Currently, most deep learning-based registration methods assume that the desired deformation fields are globally smooth and continuous, which is not always valid for real-world scenarios, especially in medical image registration (e.g. cardiac imaging and abdominal imaging). Such a global constraint can lead to artefacts and increased errors at discontinuous tissue interfaces. To tackle this issue, we propose a weakly-supervised Deep Discontinuity-preserving Image Registration network (DDIR), to obtain better registration performance and realistic deformation fields. We demonstrate that our method achieves significant improvements in registration accuracy and predicts more realistic deformations, in registration experiments on cardiac magnetic resonance (MR) images from UK Biobank Imaging Study (UKBB), than state-of-the-art approaches.

eess.IV↗

arXiv2021

CAR-Net: Unsupervised Co-Attention Guided Registration Network for Joint Registration and Structure Learning

Image registration is a fundamental building block for various applications in medical image analysis. To better explore the correlation between the fixed and moving images and improve registration performance, we propose a novel deep learning network, Co-Attention guided Registration Network (CAR-Net). CAR-Net employs a co-attention block to learn a new representation of the inputs, which drives the registration of the fixed and moving images. Experiments on UK Biobank cardiac cine-magnetic resonance image data demonstrate that CAR-Net obtains higher registration accuracy and smoother deformation fields than state-of-the-art unsupervised registration methods, while achieving comparable or better registration performance than corresponding weakly-supervised variants. In addition, our approach can provide critical structural information of the input fixed and moving images simultaneously in a completely unsupervised manner.

eess.IV↗