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We propose new signals for the direct detection of ultralight dark matter such as the axion. Axion or axion like particle (ALP) dark matter may be thought of as a background, classical field. We consider couplings for this field which give…

High Energy Physics - Phenomenology · Physics 2013-09-11 Peter W. Graham , Surjeet Rajendran

Magnetic field inhomogeneity estimation is important in some types of magnetic resonance imaging (MRI), including field-corrected reconstruction for fast MRI with long readout times, and chemical shift based water-fat imaging. Regularized…

Image and Video Processing · Electrical Eng. & Systems 2020-10-13 Claire Yilin Lin , Jeffrey A. Fessler

In the search for axion dark matter, the cavity-based haloscope offers the most sensitive approach to the theoretically interesting models in the microwave region. However, experimental searches have been limited to relatively low masses up…

High Energy Physics - Experiment · Physics 2023-01-25 Sungjae Bae , SungWoo Youn , Junu Jeong

We analyze the prospects of employing a distributed global network of precision measurement devices as a dark matter and exotic physics observatory. In particular, we consider the atomic clocks of the Global Positioning System (GPS),…

Instrumentation and Methods for Astrophysics · Physics 2018-04-25 B. M. Roberts , G. Blewitt , C. Dailey , A. Derevianko

Bayesian optimization is a powerful global optimization technique for expensive black-box functions. One of its shortcomings is that it requires auxiliary optimization of an acquisition function at each iteration. This auxiliary…

Machine Learning · Statistics 2014-02-28 Ziyu Wang , Babak Shakibi , Lin Jin , Nando de Freitas

The optimal instant of observation of astrophysical phenomena for objects that vary on human time-sales is an important problem, as it bears on the cost-effective use of usually scarce observational facilities. In this paper we address this…

Solar and Stellar Astrophysics · Physics 2023-02-15 Miguel Videla , Rene A. Mendez , Jorge F. Silva , Marcos E. Orchard

Particle accelerators are invaluable discovery engines in the chemical, biological and physical sciences. Characterization of the accelerated beam response to accelerator input parameters is of-ten the first step when conducting…

Axions and axion-like particles are compelling candidates for ultralight bosonic dark matter, forming coherent oscillating fields that can be probed by experiments known as haloscopes. A broad range of haloscope concepts has been developed,…

We present Bayesian Binary Search (BBS), a novel probabilistic variant of the classical binary search/bisection algorithm. BBS leverages machine learning/statistical techniques to estimate the probability density of the search space and…

Machine Learning · Computer Science 2024-10-03 Vikash Singh , Matthew Khanzadeh , Vincent Davis , Harrison Rush , Emanuele Rossi , Jesse Shrader , Pietro Lio

Bayesian optimization techniques have been successfully applied to robotics, planning, sensor placement, recommendation, advertising, intelligent user interfaces and automatic algorithm configuration. Despite these successes, the approach…

Machine Learning · Statistics 2016-01-12 Ziyu Wang , Frank Hutter , Masrour Zoghi , David Matheson , Nando de Freitas

An algorithm is devised for solving minimization problems with equality constraints. The algorithm uses first-order derivatives of both the objective function and the constraints. The step is computed as a sum between a steepest-descent…

Numerical Analysis · Mathematics 2017-11-15 Cristian Barbarosie , Sérgio Lopes , Anca-Maria Toader

One of the most important magnetic spin structure is the topologically stabilised skyrmion quasi-particle. Its interesting physical properties make them candidates for memory and efficient neuromorphic computation schemes. For the device…

Machine Learning · Computer Science 2023-03-31 Isaac Labrie-Boulay , Thomas Brian Winkler , Daniel Franzen , Alena Romanova , Hans Fangohr , Mathias Kläui

Computational exploration of the compositional spaces of materials can provide guidance for synthetic research and thus accelerate the discovery of novel materials. Most approaches employ high-throughput sampling and focus on reducing the…

For the first time, we determine the properties of the optimal single-moded, linear, passive search for electromagnetic coupling to axion and hidden-photon dark matter, subject to the Standard Quantum Limit on phase-insensitive…

High Energy Physics - Phenomenology · Physics 2021-05-11 Saptarshi Chaudhuri , Kent Irwin , Peter W. Graham , Jeremy Mardon

In this thesis, I explore the possibilities of conducting Bayesian optimization techniques in high dimensional domains. Although high dimensional domains can be defined to be between hundreds and thousands of dimensions, we will primarily…

Machine Learning · Computer Science 2020-10-09 David Yenicelik

Efficient parameter identification of electrochemical models is crucial for accurate monitoring and control of lithium-ion cells. This process becomes challenging when applied to complex models that rely on a considerable number of…

Systems and Control · Electrical Eng. & Systems 2024-05-20 Jianzong Pi , Samuel Filgueira da Silva , Mehmet Fatih Ozkan , Abhishek Gupta , Marcello Canova

Ultra-low-mass axions are a viable dark matter candidate and may form a coherently oscillating classical field. Nuclear spins in experiments on Earth might couple to this oscillating axion dark-matter field, when propagating on Earth's…

A new search strategy for the detection of the elusive dark matter (DM) axion is proposed. The idea is based on streaming DM axions, whose flux might get temporally enormously enhanced due to gravitational lensing. This can happen if the…

Numerical homogenization, i.e. the finite-dimensional approximation of solution spaces of PDEs with arbitrary rough coefficients, requires the identification of accurate basis elements. These basis elements are oftentimes found after a…

Numerical Analysis · Mathematics 2015-05-12 Houman Owhadi

A wide variety of optimization techniques, both exact and heuristic, tend to be biased samplers. This means that when attempting to find multiple uncorrelated solutions of a degenerate Boolean optimization problem a subset of the solution…

Disordered Systems and Neural Networks · Physics 2019-05-14 Andrew J. Ochoa , Darryl C. Jacob , Salvatore Mandrà , Helmut G. Katzgraber