A method to measure the resonance transitions between the gravitationally bound quantum states of neutrons in the GRANIT spectrometer
M. Kreuz, V.V. Nesvizhevsky, P. Schmidt-Wellenburg, T. Soldner, M., Thomas, H.G. Boerner, F. Naraghi, G. Pignol, K.V. Protasov, D. Rebreyend, F., Vezzu, R. Flaminio, C. Michel, L. Pinard, A. Remillieux, S. Baessler, A.M., Gagarski, L.A. Grigorieva, T.M. Kuzmina, A.E. Meyerovich

TL;DR
This paper introduces a novel method to measure resonance transitions between gravitationally bound quantum states of neutrons using the GRANIT spectrometer, enhancing precision in quantum state parameter measurements.
Contribution
The paper presents a new technique employing magnetic field gradients to excite and detect resonance transitions in ultracold neutrons within the GRANIT setup.
Findings
Resonance transitions can be excited using periodic magnetic field gradients.
The method allows for high-precision measurements of quantum state parameters.
Potential applications include testing fundamental physics principles.
Abstract
We present a method to measure the resonance transitions between the gravitationally bound quantum states of neutrons in the GRANIT spectrometer. The purpose of GRANIT is to improve the accuracy of measurement of the quantum states parameters by several orders of magnitude, taking advantage of long storage of Ultracold neutrons at specula trajectories. The transitions could be excited using a periodic spatial variation of a magnetic field gradient. If the frequency of such a perturbation (in the frame of a moving neutron) coincides with a resonance frequency defined by the energy difference of two quantum states, the transition probability will sharply increase. The GRANIT experiment is motivated by searches for short-range interactions (in particular spin-dependent interactions), by studying the interaction of a quantum system with a gravitational field, by searches for extensions of…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
