arXiv subjects

M. Hsieh

Publications and source records attributed to M. Hsieh.

3 recordsLinked to original sources

arXiv2026

WAsp: The Wideband (W) Adaptive-Scale Pixel (Asp) Deconvolution Algorithm for Interferometric Imaging

This paper introduces the Wide-band Asp-Clean (\texttt{WAsp}) algorithm, a novel scale-sensitive image reconstruction method tailored for wide-band imaging applications. This algorithm is particularly beneficial for thermal noise-limited imaging with aperture synthesis telescopes, where joint spatio-frequency modeling of the sky brightness distribution is critical. The \texttt{WAsp} algorithm replaces the use of the MS-Clean algorithm in the MS-MFS algorithm with the {\tt Asp} algorithm \citep{Asp_Clean}, which itself has been improved for both imaging and runtime performance. With the high sensitivity of current and next-generation telescopes, spatio-frequency modeling in a scale-sensitive basis becomes crucial for ensuring that residuals align with the noise model across the frequency band. Although existing wide-band scale-sensitive algorithms have demonstrated superior performance over scale-insensitive counterparts, they often suffer from well-documented deficiencies, leading to significant wide-scale residuals in Stokes-I at low levels and consequently significant relative errors in spectral index maps. The \texttt{WAsp} algorithm addresses these limitations while maintaining computational efficiency. The implementation can be configured to support narrow-band and wide-band scale-sensitive imaging, spectral-cube imaging applications and joint single-dish and interferometer imaging. To demonstrate improved imaging performance, we show comparison with existing algorithms via carefully developed simulations for stress-testing the algorithms. We also present results from its application to real-world wide-band data, underscoring its effectiveness in practical imaging scenarios.

astro-ph.IM↗

arXiv2025

An Algorithm Architecture for Radio Interferometric Data Processing

We present a foundational, scalable algorithm architecture for processing data from aperture synthesis radio telescopes. The analysis leading to the architecture is rooted in the theory of aperture synthesis, signal processing and numerical optimization keeping it scalable for variations in computing load, algorithmic complexity, and accommodate the continuing evolution of algorithms. It also adheres to scientific software design principles and use of modern performance engineering techniques providing a stable foundation for long-term scalability, performance, and development cost. We first show that algorithms for both calibration and imaging algorithms share a common mathematical foundation and can be expressed as numerical optimization problems. We then decompose the resulting mathematical framework into fundamental conceptual architectural components, and assemble calibration and imaging algorithms from these foundational components. For a physical architectural view, we used a library of algorithms implemented in the LibRA software for the various architectural components, and used the Kokkos framework in the compute-intensive components for performance portable implementation. This was deployed on hardware ranging from desktop-class computers to multiple super-computer class high-performance computing (HPC) and high-throughput computing (HTC) platforms with a variety of CPU and GPU architectures, and job schedulers (HTCondor and Slurm). As a test, we imaged archival data from the NSF's Karl G. Jansky Very Large Array (VLA) telescope in the A-array configuration for the Hubble Ultra Deep Field. Using over 100 GPUs we achieve a processing rate of ~2 Terabyte per hour to make one of the deepest images in the 2 -- 4 GHz band with an RMS noise of ~1 microJy/beam.

astro-ph.IM↗

arXiv2003

An Explicit Universal Gate-set for Exchange-Only Quantum Computation

A single physical interaction might not be universal for quantum computation in general. It has been shown, however, that in some cases it can generate universal quantum computation over a subspace. For example, by encoding logical qubits into arrays of multiple physical qubits, a single isotropic or anisotropic exchange interaction can generate a universal logical gate-set. Recently, encoded universality for the exchange interaction was explicitly demonstrated on three-qubit arrays, the smallest nontrivial encoding. We now present the exact specification of a discrete universal logical gate-set on four-qubit arrays. We show how to implement the single qubit operations exactly with at most 3 nearest neighbor exchange operations and how to generate the encoded controlled-not with 29 parallel nearest neighbor exchange interactions or 54 serial gates, obtained from extensive numerical optimization using genetic algorithms and Nelder-Mead searches. Our gate-sequences are immediately applicable to implementations of quantum circuits with the exchange interaction.

quant-ph↗