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The integration of quantum machine learning with classical deep learning offers promising avenues for medical image analysis by mapping data into high-dimensional Hilbert spaces. However, effectively unifying these distinct paradigms…
Entanglement is one of the most fundamental properties of quantum mechanics, and is the key resource for quantum information processing. Bipartite entangled states of identical particles have been generated and studied in several…
Image fusion aims to integrate complementary information from multiple input images acquired through various sources to synthesize a new fused image. Existing methods usually employ distinct constraint designs tailored to specific scenes,…
Even when starting with a very poor initial guess, the iterative configuration interaction (iCI) approach can converge from above to full CI very quickly by constructing and diagonalizing a small Hamiltonian matrix at each…
The quasi-neutral hybrid model with kinetic ions and fluid electrons is a promising approach for bridging the inherent multi-scale nature of many problems in space and laboratory plasmas. Here, a novel, implicit, particle-in-cell based…
Magnetized Liner Inertial Fusion (MagLIF) is a magneto-inertial-fusion (MIF) concept, which is presently being studied on the Z Pulsed Power Facility. The MagLIF platform has achieved interesting plasma conditions at stagnation and produced…
We describe a method to automatically generate an ion implantation recipe, a set of energies and fluences, to produce a desired defect density profile in a solid using the fewest required energies. We simulate defect density profiles for a…
Multimodal learning aims to enhance perceptual and decision-making capabilities by integrating information from diverse sources. However, classical deep learning approaches face a critical trade-off between the high accuracy of black-box…
Iron phosphate glasses (IPG) have been proposed as futuristic glass material for nuclear waste immobilization, anode material for lithium batteries and also as bioactive glass. In the last decade, there have been attempts to propose…
To fully leverage the power of image simulation to corroborate and explain patterns and structures in atomic resolution microscopy (e.g., electron and scanning probe), an initial correspondence between the simulation and experimental image…
There are two main methods of nulcear fusion: inertial confinement fusion (ICF) and magnetic confinement fusion (MCF). Existing thermonuclear reactors are very complex, expensive, large, and heavy. They cannot achieve the Lawson creterion.…
In recent years, numerous vision and learning tasks have been (re)formulated as nonconvex and nonsmooth programmings(NNPs). Although some algorithms have been proposed for particular problems, designing fast and flexible optimization…
Understanding and designing inertial confinement fusion (ICF) implosions through radiation-hydrodynamics simulations rely on the accurate knowledge of the equation of state (EOS) of the deuterium and tritium fuels. To minimize the drive…
The heavy-ion fusion reactions induced by neutron-rich nuclei are investigated with the improved quantum molecular dynamics (ImQMD) model. With a subtle consideration of the neutron skin thickness of nuclei and the symmetry potential, the…
We present a framework to simulate the dynamics of hard probes such as heavy quarks or jets in a hot, strongly-coupled quark-gluon plasma (QGP) on a quantum computer. Hard probes in the QGP can be treated as open quantum systems governed in…
The issues of energy and environment are the main constraint of sustainable development in worldwide. Nuclear energy source is one important optional choice for long term sustainable development. The nuclear energy consists of fusion energy…
The existence of efficient ion acceleration regimes in collective laser-plasma interactions opens up the possibility to develop high-energy physics facilities in conjunction with projects for inertial confinement nuclear fusion (ICF) and…
Designing the next generation colliders and detectors involves solving optimization problems in high-dimensional spaces where the optimal solutions may nest in regions that even a team of expert humans would not explore. Resorting to…
We propose Adaptive Deep Kernel Fitting with Implicit Function Theorem (ADKF-IFT), a novel framework for learning deep kernel Gaussian processes (GPs) by interpolating between meta-learning and conventional deep kernel learning. Our…
Intraatomic orbital hybridization and interatomic bond formation are the two fundamental processes when real atoms are condensed to form matter. Artificial atoms mimic real atoms by demonstrating discrete energy levels attributable to…