EPOC: A Novel Pulse Generation Framework Incorporating Advanced Synthesis Techniques for Quantum Circuits

In this paper we propose EPOC, an efficient pulse generation framework for quantum circuits that combines ZX-Calculus, circuit partitioning, and circuit synthesis to accelerate pulse generation. Unlike previous works that focus on generating pulses from unitary matrices without exploring equivalent representations, EPOC employs a finer granularity approach by grouping quantum gates and decomposing the resulting unitary matrices into smaller ones using synthesis techniques. This enables increased parallelism and decreased latency in quantum pulses. EPOC also continuously optimizes the circuit by identifying equivalent representations, leading to further reductions in circuit latency while minimizing the computational overhead associated with quantum optimal control. We introduce circuit synthesis into the workflow of quantum optimal control for the first time and achieve a 31.74% reduction in latency compared to previous work and a 76.80% reduction compared to the gate-based method for creating pulses. The approach demonstrates the potential for significant performance improvements in quantum circuits while minimizing computational overhead

Calibration Transfer of Near-Infrared Spectroscopic Model for Soluble Solid Content Predication of Apples by the Combined Use of Direct Standardization and Piecewise Direct Standardization

To achieve the transfer of a near-infrared (NIR) calibration model for determining the soluble solid content (SSC) in apples, this study employed the spectral data and SSC values of 89 apple samples measured with two portable NIR spectrometers. After outlier removal and preprocessing, the calibration set from the master instrument was used to establish the NIR model by partial least-squares regression (PLSR). Subsequently, the transfer of the NIR model between the master and slave instruments was accomplished by the combined use of direct standardization (DS) and piecewise direct standardization (PDS). The results indicated that compared with DS and PDS, the combined algorithm not only significantly improved the prediction performance of the model for the slave instrument, but also mitigated the artifacts caused by PDS. After calibration transfer, the ratio of standard deviation of the validation set to standard error of prediction (RPD) increased from 1.585 3 to 3.264 5, while the root mean square error of prediction (RMSEP) decreased from 1.093 2 to 0.530 9. Therefore, the proposed DS-PDS algorithm leverages the advantages of DS and PDS, allowing successful transfer of the calibration model between the two portable spectrometers

BvSP: Broad-view Soft Prompting for Few-Shot Aspect Sentiment Quad Prediction

Aspect sentiment quad prediction (ASQP) aims to predict four aspect-based elements, including aspect term, opinion term, aspect category, and sentiment polarity. In practice, unseen aspects, due to distinct data distribution, impose many challenges for a trained neural model. Motivated by this, this work formulates ASQP into the few-shot scenario, which aims for fast adaptation in real applications. Therefore, we first construct a few-shot ASQP dataset (FSQP) that contains richer categories and is more balanced for the few-shot study. Moreover, recent methods extract quads through a generation paradigm, which involves converting the input sentence into a templated target sequence. However, they primarily focus on the utilization of a single template or the consideration of different template orders, thereby overlooking the correlations among various templates. To tackle this issue, we further propose a Broadview Soft Prompting (BvSP) method that aggregates multiple templates with a broader view by taking into account the correlation between the different templates. Specifically, BvSP uses the pre-trained language model to select the most relevant k templates with Jensen-Shannon divergence. BvSP further introduces soft prompts to guide the pre-trained language model using the selected templates. Then, we aggregate the results of multi-templates by voting mechanism. Empirical results demonstrate that BvSP significantly outperforms the stateof-the-art methods under four few-shot settings and other public datasets. Our code and dataset are available at https://github.com/byinhao/BvSP.Comment: Accepted to ACL 2024 Main Conferenc

Myocardial Stunning-Induced Left Ventricular Dyssynchrony On Gated Single-Photon Emission Computed Tomography Myocardial Perfusion Imaging

Objectives Myocardial stunning provides additional nonperfusion markers of coronary artery disease (CAD), especially for severe multivessel CAD. The purpose of this study is to assess the influence of myocardial stunning to the changes of left ventricular mechanical dyssynchrony (LVMD) parameters between stress and rest gated single-photon emission computed tomography (SPECT) myocardial perfusion imaging (MPI). Patients and methods A total of 113 consecutive patients (88 males and 25 females) who had undergone both stress and rest 99mTc-sestamibi gated SPECT MPI were retrospectively enrolled. Suspected or known patients with CAD were included if they had exercise stress MPI and moderate to severe myocardial ischemia. Segmental scores were summed for the three main coronary arteries according to standard myocardial perfusion territories, and then regional perfusion, wall motion, and wall thickening scores were measured. Myocardial stunning was defined as both ischemia and wall dysfunction within the same coronary artery territory. Patients were divided into the stunning group (n=58) and nonstunning group (n=55). Results There was no significant difference of LVMD parameters between stress and rest in the nonstunning group. In the stunning group, phase SD and phase histogram bandwidth of contraction were significantly larger during stress than during rest (15.05±10.70 vs. 13.23±9.01 and 46.07±34.29 vs. 41.02±32.16, PP\u3c0.05). Conclusion Both systolic and diastolic LVMD parameters deteriorate with myocardial stunning. This kind of change may have incremental values to diagnose CAD

SpacePulse: Combining Parameterized Pulses and Contextual Subspace for More Practical VQE

In this paper, we explore the integration of parameterized quantum pulses with the contextual subspace method. The advent of parameterized quantum pulses marks a transition from traditional quantum gates to a more flexible and efficient approach to quantum computing. Working with pulses allows us to potentially access areas of the Hilbert space that are inaccessible with a CNOT-based circuit decomposition. Compared to solving the complete Hamiltonian via the traditional Variational Quantum Eigensolver (VQE), the computation of the contextual correction generally requires fewer qubits and measurements, thus improving computational efficiency. Plus a Pauli grouping strategy, our framework, SpacePulse, can minimize the quantum resource cost for the VQE and enhance the potential for processing larger molecular structures

Comparison of left ventricular mechanical dyssynchrony parameters between exercise and adenosine triphosphate stress tests using gated single-photon emission computed tomography myocardial perfusion imaging

Background Left ventricular mechanical dyssynchrony (LVMD) can be induced after stress test. However, no studies have compared the influence of different stress-inducing methods on LVMD parameters. aims The aim of the study was to determine whether there is a difference between exercise and adenosine triphosphate (ATP) stress tests in terms of changes in LVMD parameters assessed using gated single-photon emission computed tomography myocardial perfusion imaging (GSPECT MPI). methods A total of 190 patients who underwent 99mTc-sestamibi GSPECT MPI were consecutively enrolled. Treadmill exercise and ATP stress tests were performed in 95 patients each. Normal myocardial perfusion was defined as the summed stress score (SSS) ≤3 and summed rest score (SRS) ≤3, myocardial ischemia as SSS \u3e3 and SRS ≤3, and myocardial infarction as SSS \u3e3 and SRS \u3e3. Parameters of LVMD, including phase standard deviation (PSD), phase bandwidth (PBW), skewness, and kurtosis were compared. Subtraction was made between values during stress and rest phases to acquire ∆PSD, ∆PBW, ∆skewness, and ∆kurtosis. results There were no differences in LVMD parameters between the exercise and ATP groups. The same results were obtained in the normal perfusion, ischemia, and infarction subgroups. Furthermore, no differences were observed in ∆PSD (median [interquartile range, IQR], 0.25 [-2.3 to 3.1] vs 0.42 (-1.7 to 3.1]; P = 0.73), ∆PBW (median [IQR], 1 [-7 to 11] vs 1 [-6 to 11]; P = 0.95), ∆skewness (mean [SD], -0.06 [0.63] vs 0 [0.81]; P= 0.53), and ∆kurtosis (median [IQR], -0.47 [-4.2 to 4.3] vs -0.42 [-4.8 to 5.2]; P= 0.73) between the exercise and ATP stress-inducing methods. conclusions There are no differences between the exercise and ATP stress tests in terms of changes in LVMD parameters. Thus, the 2 methods can be used alternatively

Adaptive Radio Frequency Interference Mitigation for Passive Bistatic Radar Using OFDM Waveform

High frequency passive bistatic radar (HFPBR) is a novel and promising technique in development. DRM broadcast exploiting orthogonal frequency division multiplexing (OFDM) technique supplies a good choice for the illuminator of HFPBR. HFPBR works in crowded short wave band. It faces severe radio frequency interference (RFI) problem. In this paper, a theoretical analysis of the range-domain correlation of RFI in OFDM-based HF radar is presented. A RFI mitigation method in the range domain is introduced. After the direct-path wave rejection, the interference subspace is constructed using the echo signals at the reserved range bins. Then RFI in the effective range bins is mitigated by the subspace projection, using the correlation among different range bins. The introduced algorithm is easy to perform in practice and the RFI mitigation performance is evaluated using the experimental data of DRM-based HFPBR