arXiv subjects

Yuan-Chi Yang

Publications and source records attributed to Yuan-Chi Yang.

7 recordsLinked to original sources

arXiv2026

Upscaling from ab initio atomistic simulations to electrode scale: The case of manganese hexacyanoferrate, a cathode material for Na-ion batteries

We present a generalizable scale-bridging computational framework that enables predictive modeling of insertion-type electrode materials from atomistic to device scales. Applied to sodium manganese hexacyanoferrate, a promising cathode material for grid-scale sodium-ion batteries, our methodology employs an active-learning strategy to train a Moment Tensor Potential through iterative hybrid grand-canonical Monte Carlo--molecular dynamics sampling, robustly capturing configuration spaces at all sodiation levels. The resulting machine learning interatomic potential accurately reproduces experimental properties including volume expansion, operating voltage, and sodium concentration-dependent structural transformations, while revealing a four-order-of-magnitude difference in sodium diffusivity between the rhombohedral (sodium-rich) and tetragonal (sodium-poor) phases at 300 K. We directly compute all critical parameters -- temperature- and concentration-dependent diffusivities, interfacial and strain energies, and complete free-energy landscapes -- to feed them into pseudo-2D phase-field simulations that predict phase-boundary propagation and rate-dependent performances across electrode length scales. This multiscale workflow establishes a blueprint for rational computational design of next-generation insertion-type materials, such as battery electrode materials, demonstrating how atomistic insights can be systematically translated into continuum-scale predictions.

cond-mat.mtrl-sci↗

arXiv2022

Few-shot learning for medical text: A systematic review

Objective: Few-shot learning (FSL) methods require small numbers of labeled instances for training. As many medical topics have limited annotated textual data in practical settings, FSL-based natural language processing (NLP) methods hold substantial promise. We aimed to conduct a systematic review to explore the state of FSL methods for medical NLP. Materials and Methods: We searched for articles published between January 2016 and August 2021 using PubMed/Medline, Embase, ACL Anthology, and IEEE Xplore Digital Library. To identify the latest relevant methods, we also searched other sources such as preprint servers (eg., medRxiv) via Google Scholar. We included all articles that involved FSL and any type of medical text. We abstracted articles based on data source(s), aim(s), training set size(s), primary method(s)/approach(es), and evaluation method(s). Results: 31 studies met our inclusion criteria-all published after 2018; 22 (71%) since 2020. Concept extraction/named entity recognition was the most frequently addressed task (13/31; 42%), followed by text classification (10/31; 32%). Twenty-one (68%) studies reconstructed existing datasets to create few-shot scenarios synthetically, and MIMIC-III was the most frequently used dataset (7/31; 23%). Common methods included FSL with attention mechanisms (12/31; 39%), prototypical networks (8/31; 26%), and meta-learning (6/31; 19%). Discussion: Despite the potential for FSL in biomedical NLP, progress has been limited compared to domain-independent FSL. This may be due to the paucity of standardized, public datasets, and the relative underperformance of FSL methods on biomedical topics. Creation and release of specialized datasets for biomedical FSL may aid method development by enabling comparative analyses.

cs.CL↗

arXiv2020

High-Fidelity Entangling Gates for Quantum-Dot Hybrid Qubits Based on Exchange Interactions

Quantum dot hybrid qubits exploit an extended charge-noise sweet spot that suppresses dephasing and has enabled the experimental achievement of high-fidelity single-qubit gates. However, current proposals for two-qubit gates require tuning the qubits away from their sweet spots. Here, we propose a two-hybrid-qubit coupling scheme, based on exchange interactions, that allows the qubits to remain at their sweet spots at all times. The interaction is controlled via the inter-qubit tunnel coupling. By simulating such gates in the presence of realistic quasistatic and $1\!/\!f$ charge noise, we show that our scheme should enable controlled-$Z$ gates of length $\sim$5~ns, and Z-CNOT gates of length $\sim$7~ns, both with fidelities $>$99.9\%.

quant-ph↗

arXiv2019

High-fidelity single-qubit gates in a strongly driven quantum dot hybrid qubit with $1/f$ charge noise

Semiconductor double quantum dot hybrid qubits are promising candidates for high-fidelity quantum computing. However, their performance is limited by charge noise, which is ubiquitous in solid-state devices, and phonon-induced dephasing. Here we explore methods for improving the quantum operations of a hybrid qubit, using strong microwave driving to enable gate operations that are much faster than decoherence processes. Using numerical simulations and a theoretical method based on a cumulant expansion, we analyze qubit dynamics in the presence of $1/f$ charge noise, which forms the dominant decoherence mechanism in many solid-state devices. We show that, while strong-driving effects and charge noise both reduce the quantum gate fidelity, simple pulse-shaping techniques effectively suppress the strong-driving effects. Moreover, a broad AC sweet spot emerges when the detuning parameter and the tunneling coupling are driven simultaneously. Taking into account phonon-mediated noise, we find that it should be possible to achieve $X_π$ gates with fidelities higher than $99.9\%$.

cond-mat.mes-hall↗

arXiv2019

Achieving High-Fidelity Single-Qubit Gates in a Strongly Driven Charge Qubit with $1\!/\!f$ Charge Noise

Charge qubits formed in double quantum dots represent quintessential two-level systems that enjoy both ease of control and efficient readout. Unfortunately, charge noise can cause rapid decoherence, with typical single-qubit gate fidelities falling below $90\%$. Here, we develop analytical methods to study the evolution of strongly driven charge qubits, for general and $1\!/\!f$ charge-noise spectra. We show that special pulsing techniques can simultaneously suppress errors due to strong driving and charge noise, yielding single-qubit gates with fidelities above $99.9\%$. These results demonstrate that quantum dot charge qubits provide a potential route to high-fidelity quantum computation.

cond-mat.mes-hall↗

arXiv2017

Achieving High Fidelity Single Qubit Gates in a Strongly Driven Silicon Quantum Dot Hybrid Qubit

Performing qubit gate operations as quickly as possible can be important to minimize the effects of decoherence. For resonant gates, this requires applying a strong ac drive. However, strong driving can present control challenges by causing leakage to levels that lie outside the qubit subspace. Strong driving can also present theoretical challenges because preferred tools such as the rotating wave approximation can break down, resulting in complex dynamics that are difficult to control. Here we analyze resonant $X$ rotations of a silicon quantum double dot hybrid qubit within a dressed-state formalism, obtaining results beyond the rotating wave approximation. We obtain analytic formulas for the optimum driving frequency and the Rabi frequency, which both are affected by strong driving. While the qubit states exhibit fast oscillations due to counter-rotating terms and leakage, we show that they can be suppressed to the point that gate fidelities above $99.99\%$ are possible, in the absence of decoherence. Hence decoherence mechanisms, rather than strong-driving effects, should represent the limiting factor for resonant-gate fidelities in quantum dot hybrid qubits.

cond-mat.mes-hall↗

arXiv2017

Extending the coherence of a quantum dot hybrid qubit

Identifying and ameliorating dominant sources of decoherence are important steps in understanding and improving quantum systems. Here we show that the free induction decay time ($T_{2}^{*}$) and the Rabi decay rate ($Γ_{\mathrm{Rabi}}$) of the quantum dot hybrid qubit can be increased by more than an order of magnitude by appropriate tuning of the qubit parameters and operating points. By operating in the spin-like regime of this qubit, and choosing parameters that increase the qubit's resilience to charge noise (which we show is presently the limiting noise source for this qubit), we achieve a Ramsey decay time $T_{2}^{*}$ of $177~\mathrm{ns}$ and a Rabi decay time, $1/Γ_{\mathrm{Rabi}}$, exceeding $1~\mathrm{μs}$. We find that the slowest $Γ_{\mathrm{Rabi}}$ is limited by fluctuations in the Rabi frequency induced by charge noise and not by fluctuations in the qubit energy itself.

cond-mat.mes-hall↗