相关论文: Fast shimming algorithm based on Bayesian optimiza…
One of the prime tools to search for new light bosons interacting very weakly with photons -- prominent examples are axions, axion-like particles and extra ``hidden'' U(1) gauge bosons -- are light-shining-through-a-wall (LSW) experiments.…
Optimization strategies driven by machine learning, such as Bayesian optimization, are being explored across experimental sciences as an efficient alternative to traditional design of experiment. When combined with automated laboratory…
Recent advances in tabletop quantum sensor technology have enabled searches for nongravitational interactions of dark matter (DM). Traditional axion DM experiments rely on sharp resonance, resulting in extensive scanning time to cover a…
Finding optimal parameter configurations for tunable GPU kernels is a non-trivial exercise for large search spaces, even when automated. This poses an optimization task on a non-convex search space, using an expensive to evaluate function…
Machine learning methods usually depend on internal parameters -- so called hyperparameters -- that need to be optimized for best performance. Such optimization poses a burden on machine learning practitioners, requiring expert knowledge,…
One of the goals of computer-aided surgery is to match intraoperative data to preoperative images of the anatomy and add complementary information that can facilitate the task of surgical navigation. In this context, mechanical palpation…
We introduce Bayesian optimization, a technique developed for optimizing time-consuming engineering simulations and for fitting machine learning models on large datasets. Bayesian optimization guides the choice of experiments during…
The standard model axion seesaw Higgs portal inflation (SMASH) model is a well motivated, self-contained description of particle physics over a range of energy scales that predicts axion dark matter particles to exist within the mass range…
We propose an experiment to search for QCD axion and axion-like-particle (ALP) dark matter. Nuclei that are interacting with the background axion dark matter acquire time-varying CP-odd nuclear moments such as an electric dipole moment. In…
In dark matter axion searches, quantum uncertainty manifests as a fundamental noise source, limiting the measurement of the quadrature observables used for detection. We use vacuum squeezing to circumvent the quantum limit in a search for a…
The investigation of magnetic energy landscapes and the search for ground states of magnetic materials using ab initio methods like density functional theory (DFT) is a challenging task. Complex interactions, such as superexchange and…
An overview of our experimental program to search for axion and axion-like-particle (ALP) dark matter using nuclear magnetic resonance (NMR) techniques is presented. An oscillating axion field can exert a time-varying torque on nuclear…
Existence of dark matter indicates the presence of unknown fundamental laws of nature. Ultralight axion-like particles are well-motivated dark matter candidates, emerging naturally from theories of physics at ultrahigh energies. We report…
We propose an algorithm for Bayesian functional optimisation - that is, finding the function to optimise a process - guided by experimenter beliefs and intuitions regarding the expected characteristics (length-scale, smoothness, cyclicity…
A ferromagnetic axion haloscope searches for Dark Matter in the form of axions by exploiting their interaction with electronic spins. It is composed of an axion-to-electromagnetic field transducer coupled to a sensitive rf detector. The…
The Linac Coherent Light Source changes configurations multiple times per day, necessitating fast tuning strategies to reduce setup time for successive experiments. To this end, we employ a Bayesian approach to transport optics tuning to…
Applying Bayesian optimization in problems wherein the search space is unknown is challenging. To address this problem, we propose a systematic volume expansion strategy for the Bayesian optimization. We devise a strategy to guarantee that…
We search for dark matter in the form of axionlike particles (ALPs) in the mass range $5.576741 \,\mathrm{neV/c^2}$ - $5.577733\,\mathrm{neV/c^2}$ by probing their possible coupling to fermion spins through the ALP field gradient. This is…
The Global Network of Optical Magnetometers for Exotic physics searches (GNOME) conducts an experimental search for certain forms of dark matter based on their spatiotemporal signatures imprinted on a global array of synchronized atomic…
Bayesian optimization (BO) is a powerful approach to sample-efficient optimization of black-box functions. However, in settings with very few function evaluations, a successful application of BO may require transferring information from…