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K. Sung

Publications and source records attributed to K. Sung.

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The HITRAN2024 methane update

Spectroscopic parameters of methane from many different studies were gathered to improve the HITRAN database towards its 2024 version. After a validation process using high-resolution FTS and CRDS spectra, about 80,000 lines of the four most abundant isotopologues were replaced from the dyad to the triacontad regions. These changes amount to 51,000 transition wavenumbers, 18,000 line intensities, 33,000 pressure-broadening half-widths, and 3300 assignments. 44,000 new lines were added with 16,000 old lines removed, extending the database from 12,000 cm$^{-1}$ up to 14,000 cm$^{-1}$, and covering some gaps. A greater focus was brought on the pentad, octad, and tetradecad regions, targeted by several remote sensing instruments. In these regions, comparisons of spectral fits from multiple line lists were performed, taking only the parameters that provide best fit for each line. In the $\nu _3$ band, in addition to replacing the previous values, speed-independent pressure broadening parameters of $^{12}$CH$_4$ were gathered and used to fit Pad\'e-approximant functions. These functions then replaced any outdated experimental data in $\nu _3$, missing data in the new lines, as well as the values that were determined to be outside their physical boundaries. The CH$_3$D broadening parameters were replaced in the same manner, for missing and low or high values, using a semi-empirical formula instead.

astro-ph.EP

FPGA-based tracking for the CMS Level-1 trigger using the tracklet algorithm

The high instantaneous luminosities expected following the upgrade of the Large Hadron Collider (LHC) to the High Luminosity LHC (HL-LHC) pose major experimental challenges for the CMS experiment. A central component to allow efficient operation under these conditions is the reconstruction of charged particle trajectories and their inclusion in the hardware-based trigger system. There are many challenges involved in achieving this: a large input data rate of about 20--40 Tb/s; processing a new batch of input data every 25 ns, each consisting of about 15,000 precise position measurements and rough transverse momentum measurements of particles ("stubs''); performing the pattern recognition on these stubs to find the trajectories; and producing the list of trajectory parameters within 4 $μ\,$s. This paper describes a proposed solution to this problem, specifically, it presents a novel approach to pattern recognition and charged particle trajectory reconstruction using an all-FPGA solution. The results of an end-to-end demonstrator system, based on Xilinx Virtex-7 FPGAs, that meets timing and performance requirements are presented along with a further improved, optimized version of the algorithm together with its corresponding expected performance.

physics.ins-det