Direct detection of dark matter remains an important outstanding problem since abundant astrophysical evidence points towards its existence, but no experiment has succeeded in detecting it. Axions and axion-like-particles are some of the most compelling candidates for dark matter given their appearance in many theories of physics beyond the Standard Model and their relatively unexplored parameter space compared to other candidates. Recently, the Cosmic Axion Spin Precession Experiment-Electric (CASPEr-e) has used nuclear magnetic resonance (NMR) to search for effective magnetic fields created by axionic dark matter. By decreasing technical noise sources, CASPEr-e is projected to reach the standard quantum limit where spin projection noise is the dominant noise source limiting sensitivity. However, some axion models predict axion couplings to normal matter that would be too small for even a quantum limited CASPEr-e experiment to detect. This creates a need for surpassing the spin projection noise limit in NMR dark matter searches.
In this thesis, I explore the prospects for surpassing the quantum limit in NMR by using spin squeezed states, entangled states with variance in one projection reduced below the standard quantum limit. First, I propose an experimental scheme for generating squeezed states by coupling the spins to an off-resonant circuit to create a One-Axis-Twist Hamiltonian. Then, using exact results and numerical simulations, I determine the amount of squeezing that can be achieved given decoherence and noise. Next, I perform modeling to show that squeezing can accelerate dark matter searches despite earlier results that argued squeezing cannot improve experimental sensitivity when subject to decoherence. Finally, I apply these results to the CASPEr-e experiment and show that at axion frequencies near 100MHz, squeezing can speed up the experiment by a factor of up to 30, corresponding to a sensitivity improvement by a factor of over 5.
| Identifer | oai:union.ndltd.org:bu.edu/oai:open.bu.edu:2144/46365 |
| Date | 16 June 2023 |
| Creators | Boyers, Eric |
| Contributors | Sushkov, Alexander O. |
| Source Sets | Boston University |
| Language | en_US |
| Detected Language | English |
| Type | Thesis/Dissertation |
Page generated in 0.0109 seconds