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The development of new-generation permanent magnets is based on experimental efforts and innovative theoretical tools for modeling magnetic properties. Magnetocrystalline anisotropy energy (MAE) - one of the main intrinsic properties of…

Molecular dynamics simulations have become essential in many areas of atomistic modelling from drug discovery to materials science. They provide critical atomic-level insights into key dynamical events experiments cannot easily capture.…

Biological Physics · Physics 2024-06-14 Tiejun Wei , Balint Dudas , Edina Rosta

Fast quantum spin manipulation is needed to design spin-based quantum logic gates and other quantum applications. Here, we construct exact evolution operator of the nitrogen-vacancy-center (NV) spin in diamond under external magnetic fields…

Mesoscale and Nanoscale Physics · Physics 2017-08-25 Wen-Qi Fang , Bang-Gui Liu

Estimation of permutation entropy (PE) using Bayesian statistical methods is presented for systems where the ordinal pattern sampling follows an independent, multinomial distribution. It is demonstrated that the PE posterior distribution is…

Data Analysis, Statistics and Probability · Physics 2022-02-09 Douglas J. Little , Joshua P. Toomey , Deb M. Kane

The spatial resolution of imaging magnetometers has benefited from scanning probe techniques. The requirement that the sample perturbs the scanning probe through a magnetic field external to its volume limits magnetometry to samples with…

Quantum Physics · Physics 2017-04-05 J. van Bree , M. E. Flatté

Recent progress in the application of color centers to nanoscale spin sensing makes the combined use of noise spectroscopy and scanning probe imaging an attractive route for the characterization of arbitrary material systems. Unfortunately,…

Dynamic state and parameter estimation (DSE) plays a key role for reliably monitoring and operating future, power-electronics-dominated power systems. While DSE is a very active research field, experimental applications of proposed…

Systems and Control · Electrical Eng. & Systems 2022-03-29 Nicolai Lorenz-Meyer , René Suchantke , Johannes Schiffer

Quantum sensors based on solid-state spins provide tremendous opportunities in a wide range of fields from basic physics and chemistry to biomedical imaging. However, integrating them into a scanning probe microscope to enable practical,…

Mesoscale and Nanoscale Physics · Physics 2016-01-19 Jean-Philippe Tetienne , Alain Lombard , David A. Simpson , Cameron Ritchie , Jianing Lu , Paul Mulvaney , Lloyd C. L. Hollenberg

For decades, searches for exotic spin interactions have used increasingly-precise laboratory measurements to test various theoretical models of particle physics. However, most searches have focused on interaction length scales greater than…

Quantum Physics · Physics 2022-07-04 P. -H. Chu , N. Ristoff , J. Smits , N. Jackson , Y. J. Kim , I. Savukov , V. M. Acosta

The sensing capability of a single optically bright electronic spin in diamond can be enhanced by making use of proximal dark nuclei as ancillary spins. Such systems, so far only realized in bulk diamond, provide orders of magnitude higher…

Quantum Physics · Physics 2017-10-04 Helena S. Knowles , Dhiren M. Kara , Mete Atatüre

The Bayesian Optimisation Algorithm (BOA) is an Estimation of Distribution Algorithm (EDA) that uses a Bayesian network as probabilistic graphical model (PGM). Determining the optimal Bayesian network structure given a solution sample is an…

Top-k maximum inner product search (MIPS) is a central task in many machine learning applications. This paper extends top-k MIPS with a budgeted setting, that asks for the best approximate top-k MIPS given a limit of B computational…

Databases · Computer Science 2020-09-15 Stephan S. Lorenzen , Ninh Pham

Nanodiamonds have a wide range of applications including catalysis, sensing, tribology and biomedicine. To leverage nanodiamond design via machine learning, we introduce the new dataset ND5k, consisting of 5,089 diamondoid and nanodiamond…

Chemical Physics · Physics 2024-04-23 Thorren Kirschbaum , Börries von Seggern , Joachim Dzubiella , Annika Bande , Frank Noé

Quantum parameter estimation holds the promise of quantum technologies, in which physical parameters can be measured with much greater precision than what is achieved with classical technologies. However, how to obtain a best precision when…

Quantum Physics · Physics 2024-03-05 Jianning Li , Dianzhen Cui , X. X. Yi

Block-encodings have become one of the most common oracle assumptions in the circuit model. I present an algorithm that uses von Neumann's measurement procedure to measure a phase, using time evolution on a block-encoded Hamiltonian as a…

Quantum Physics · Physics 2025-09-05 S. E. Skelton

Magnetic Detection Electrical Impedance Tomography is a novel technique that could enable non-invasive imaging of fast neural activity in the brain. However, commercial magnetometers are not suited to its technical requirements.…

Medical Physics · Physics 2024-12-19 Kai Mason , Florencia Maurino-Alperovich , Kirill Aristovich , David Holder

Quantum metrology and sensing seek advantage in estimating an unknown parameter of some quantum state or channel, using entanglement such as spin squeezing produced by one-axis twists or other quantum resources. In particular, qubit phase…

Quantum Physics · Physics 2024-05-29 Tyler G. Thurtell , Akimasa Miyake

We present an optimized scheme for nanoscale measurements of temperature in a complex environment using the nitrogen-vacancy center in nanodiamonds. To this end we combine a Ramsey measurement utilized to temperature determination with…

Quantum metrology enables estimation of optical phase shifts with precision beyond the shot-noise limit. One way to exceed this limit is to use squeezed states, where the quantum noise of one observable is reduced at the expense of…

We propose a framework for optimization of the chemical composition of multinary compounds with the aid of machine learning. The scheme is based on first-principles calculation using the Korringa-Kohn-Rostoker method and the coherent…

Materials Science · Physics 2019-06-05 Taro Fukazawa , Yosuke Harashima , Zhufeng Hou , Takashi Miyake