Abstract
Frequency combs and cavity-enhanced optical techniques have revolutionized molecular spectroscopy: their combination allows recording saturated Doppler-free lines with ultrahigh precision. Network theory, based on the generalized Ritz principle, offers a powerful tool for the intelligent design and validation of such precision-spectroscopy experiments and the subsequent derivation of accurate energy differences. As a proof of concept, 156 carefully-selected near-infrared transitions are detected for H2 16O, a benchmark system of molecular spectroscopy, at kHz accuracy. These measurements, augmented with 28 extremely-accurate literature lines to ensure overall connectivity, allow the precise determination of the lowest ortho-H2 16O energy, now set at 23.794 361 22(25) cm−1, and 160 energy levels with similarly high accuracy. Based on the limited number of observed transitions, 1219 calibration-quality lines are obtained in a wide wavenumber interval, which can be used to improve spectroscopic databases and applied to frequency metrology, astrophysics, atmospheric sensing, and combustion chemistry.
Original language | English |
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Article number | 1708 |
Pages (from-to) | 12 |
Number of pages | 1 |
Journal | Nature Communications |
Volume | 11 |
Issue number | 1 |
Early online date | 6 Apr 2020 |
DOIs | |
Publication status | Published - 6 Apr 2020 |
Funding
This research received funding from LASERLAB-EUROPE (Grant No. 654148, European Union’s Horizon 2020 research and innovation program). The work performed in Budapest received support from NKFIH (Grant No. K119658), from the grant VEKOP-2.3.2-16-2017-000, and from the ELTE Excellence Program (1783-3/2018/FEKUT-STRAT) of the Hungarian Ministry of Human Capacities (EMMI). W.U. acknowledges the European Research Council for an ERC Advanced Grant (Grant No. 670168). Further support was obtained from a NWO-FOM program (16MYSTP) and from the NWO Dutch Astrochemistry Network. The authors are grateful to Prof. Jonathan Tennyson for providing PES subroutines, as well as to Dr. Patrick Dupré, Dr. Csaba Fábri, and Dr. Tamás Szidarovszky for useful discussions.
Funders | Funder number |
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ELTE Excellence Program | 1783-3/2018/FEKUT-STRAT |
Hungarian Ministry of Human Capacities | |
Horizon 2020 Framework Programme | 654148 |
Laserlab-Europe | |
European Research Council | 670168 |
Emberi Eroforrások Minisztériuma | |
Nemzeti Kutatási Fejlesztési és Innovációs Hivatal | VEKOP-2.3.2-16-2017-000, K119658 |