An improved upper limit on the direct 3α decay of the Hoyle state

Bishop, J.; Smith, Robin; Kokalova, Tzany; Wheldon, C.; Curtis, N.; Freer, M.; Parker, David J.

doi:10.1063/1.5078854

Cited by 3 publications

(1 citation statement)

References 27 publications

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“…From there, the relative energies of the three break-up α-particles were examined in the 12 C centre-of-mass frame using Dalitz plots. The construction of Dalitz plots is discussed in detail in the references [14,19]. In short, the symmetric Dalitz plot provides a way to draw three quantities on a two-dimensional plot, provided that the three quantities sum to a known value.…”

Section: Charged-particle Spectroscopy With Silicon-strip Detectorsmentioning

confidence: 99%

A Fast Universal Kinematic Fitting Code for Low-Energy Nuclear Physics: FUNKI_FIT

Smith

Bishop

2019

Physics

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We present an open source kinematic fitting routine designed for low-energy nuclear physics applications. Although kinematic fitting is commonly used in high-energy particle physics, it is rarely used in low-energy nuclear physics, despite its effectiveness. A FORTRAN and ROOT C++ version of the FUNKI_FIT kinematic fitting code have been developed and published open access. The FUNKI_FIT code is universal in the sense that the constraint equations can be easily modified to suit different experimental set-ups and reactions. Two case studies for the use of this code, utilising experimental and Monte-Carlo data, are presented: (1) charged-particle spectroscopy using silicon-strip detectors; (2) charged-particle spectroscopy using active target detectors. The kinematic fitting routine provides an improvement in resolution in both cases, demonstrating, for the first time, the applicability of kinematic fitting across a range of nuclear physics applications. The ROOT macro has been developed in order to easily apply this technique in standard data analysis routines used by the nuclear physics community.

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Section: Charged-particle Spectroscopy With Silicon-strip Detectorsmentioning

confidence: 99%