Can a handful of atoms outperform a much larger digital neural network on a real-world task? The answer may be yes. In a ...
The quantum layer will will not be exhausted by one hardware modality, one algorithmic framework or one vendor’s roadmap.
The study of coherent states and quantum dynamics occupies a pivotal role in modern quantum physics, offering a bridge between quantum theory and classical intuition. Coherent states, which represent ...
Imagine zooming into matter at the quantum scale, where tiny particles can interact in more than a trillion configurations at once. If that sounds complicated, it is: Physicists often rely on ...
An international group of researchers have investigated the role of memory in quantum systems and dynamics. Their findings show that a quantum process can appear memoryless from one perspective while ...
(a) The two matrices of the shifted functional connectivity between seven manifold networks reflect different interactions in wakefulness (top) and deep sleep (bottom). Importantly, there are ...
The field of non-equilibrium quantum dynamics has rapidly progressed in recent years due to a confluence of interdisciplinary advances. These include developments in the theory of random quantum ...
The study of quantum dynamics in conjunction with nonlinear Schrödinger equations (NLS) sits at the confluence of mathematical physics, quantum mechanics and nonlinear analysis. This field ...
Quantum wavepacket dynamics depicting the collective motion of an ensemble of identical spins subject to periodic modulation in their interaction strength. Panels (b) and (c) indicate the generation ...
The quantum tangent kernel method is a mathematical approach used to understand how fast and how well quantum neural networks can learn. A quantum neural network is a machine learning model that runs ...
We’ve long marveled at how efficiently plants convert sunlight into energy—but no one guessed they were using quantum mechanics to do it. In this episode, we speak with Greg Engel, a pioneering ...
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