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Since the pioneering discovery, half a century ago, of 12C+12C molecular resonances, a great deal of research work has been undertaken in theSince the pioneering discovery, half a century ago, of 12C+12C molecular resonances, a great deal…
Quantum probes using $N$ uncorrelated particles give a limit on the measurement sensitivity referred to as the standard quantum limit (SQL). The SQL, however, can be overcome by exploiting quantum entangled states, such as spin squeezed…
${}^{12}{\rm C}$ and ${}^{16}{\rm O}$ nuclei represent essential elements for life on Earth. The study of their formation plays a key role in understanding heavy element nucleosynthesis and stellar evolution. In this paper we present the…
3$\alpha$-cluster structures and monopole transitions of $0^+$ states in $^{12}$C and $^{14}$C were investigated with $3\alpha$- and $^{10}$Be+$\alpha$-cluster models. A gas-like $3\alpha$ state and a bending-chain $3\alpha$ state were…
We have performed cough detection based on measurements from an accelerometer attached to the patient's bed. This form of monitoring is less intrusive than body-attached accelerometer sensors, and sidesteps privacy concerns encountered when…
Current quantum simulation experiments are starting to explore non-equilibrium many-body dynamics in previously inaccessible regimes in terms of system sizes and time scales. Therefore, the question emerges which observables are best suited…
The existence of the $0_3^+$ and $0_4^+$ states around 10 MeV excitation energy in ${^{12}{\rm C}}$ is confirmed by a fully microscopic 3$\alpha$ cluster model. Firstly, a GCM (generator coordinate method) calculation is performed by…
As quantum control approaches hardware-imposed performance limits, weak effects omitted by reduced models become consequential. Assumptions required for analytic tractability then cease to guide control design and instead constrain further…
The exploration of large-scale many-body phenomena in quantum materials has produced many important experimental discoveries, including novel states of entanglement, topology and quantum order as found for example in quantum spin ices,…
We describe a measurement-and-feedback technique to deterministically prepare low-entropy states of atomic spin ensembles. Using quantum non-demolition measurement and incoherent optical feedback, we drive arbitrary states in the…
In this work we present a system identification procedure based on Convolutional Neural Networks (CNN) for human posture control models. A usual approach to the study of human posture control consists in the identification of parameters for…
Emerging wireless technologies, such as 5G and beyond, are bringing new use cases to the forefront, one of the most prominent being machine learning empowered health care. One of the notable modern medical concerns that impose an immense…
Obtaining an accurate ground state wave function is one of the great challenges in the quantum many-body problem. In this paper, we propose a new class of wave functions, neural network backflow (NNB). The backflow approach, pioneered…
Artificial intelligence and deep learning are increasingly applied in the clinical domain, particularly for early and accurate disease detection using medical imaging and sound. Due to limited trained personnel, there is a growing demand…
Pulse shaping is a common technique for optimizing signal-to-noise ratio (SNR) in particle detectors. Although analog or digital linear shapers are typically used for this purpose, there are nonlinear approaches, such as neural networks…
The phenomenon of quantum entanglement underlies several important protocols that enable emerging quantum technologies. Entangled states, however, are extremely delicate and often get perturbed by tiny fluctuations in their external…
The carbon atom provides the backbone for the complex organic chemistry composing the building blocks of life. The physics of the carbon nucleus in its predominant isotope, $^{12}$C, is similarly full of multifaceted complexity. Some…
This work presents a quantum convolutional neural network (QCNN) for the classification of high energy physics events. The proposed model is tested using a simulated dataset from the Deep Underground Neutrino Experiment. The proposed…
We aim to optimize the binary detection of Chronic Obstructive Pulmonary Disease (COPD) based on emphysema presence in the lung with convolutional neural networks (CNN) by exploring manually adjusted versus automated window-setting…
The so-called contemporary AI revolution has reached every corner of the social, human and natural sciences -- physics included. In the context of quantum many-body physics, its intersection with machine learning has configured a…