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Artificial Intelligence breaks quantum physics

Artificial Intelligence (AI) is developing experiments that transcend any human idea and making amazing progress on the frontiers of experimental quantum physics. informs Scientific American.


Behind this feat is the quantum physicist Mario Krenn, which this month started a new research group at the Max Planck Institute for the Science of Light, in Germany, with the aim of using AI algorithms as a source of inspiration in quantum physics.


Those algorithms are geared towards the development of new technologies, including improved quantum microscopes or telescopes, as well as new sources for quantum computers.


New ideas

New ideas The main orientation of this team is to understand new ideas and concepts of artificial intelligence systems, develop new quantum technologies, and gain new insights into quantum physics itself.


The group will apply two different technologies for the design of new quantum experiments and quantum hardware: first, a new and powerful theoretical-graphic artificial intelligence algorithm, which will allow the extraction of the conceptual nuclei of the solutions to arduous scientific problems, informs the aforementioned Institute.


Second, the team will use Deep Learning technologies, which have been successfully applied in other fields, such as materials design, to discover how machine learning models “think” about the most complex scientific problems.


Complex entangled states

Complex entangled states The challenge is considerable and their work promises interesting results. In 2016, long before landing at the German institute, Krenn had solved the problem of creating highly complex entangled states involving multiple photons.


A machine learning algorithm developed by Krenn, and called Melvin, had accomplished the feat on its own, without anyone having provided the instructions necessary to generate such complex states.


What was most striking is that the algorithm had found a way to create complex entangled states without prior knowledge: it had even improved an experimental (human) solution proposed in the 1990s.


This revelation has triggered an escalation of experiments by other teams aimed at testing the conceptual foundations of quantum mechanics in different ways, harnessing the power of Artificial Intelligence.


Powerful algorithm

Powerful algorithm Krenn has also not stopped and has improved Melvin with a new machine learning algorithm called Theseus, which is much more powerful than its predecessor: it will be the star in the developments of the new research team of the German institute.


All this technological advance revolves around quantum entanglement, one of the most puzzling phenomena in quantum mechanics: it involves two particles, each occupying several states at the same time, an experience known as superposition.


When two particles, such as atoms, photons, or electrons, become entangled, they also experience an inexplicable bond that is maintained even if the particles are on opposite sides of the universe. While they are entangled, the behavior of the particles is linked to each other.


Quantum entanglement and state superposition have become more complex with various attempts to explore them not with two, but with more particles, especially photons or light particles.


Quantum escalation

Quantum escalation Krenn is one of those who has scaled the effects of quantum entanglement involving not only more photons, but also increasing the number of superpositions of quantum states thanks to AI.


Quantum superposition occurs when an elementary particle simultaneously possesses two or more states, as happens for example with photons: they can remain in two different places at the same time, something unimaginable in the ordinary physical world.


These overlapping states can be scaled with more photons and promise safer and faster quantum communications: three photons could be in a three-state superposition and achieve qubits in a three-dimensional quantum state.


If a bit is the basic unit of information in classical binary computation (based on 1 and 0), and a qubit is its quantum equivalent (uses superposition to handle simultaneous states of 1 and 0), in the new complex superimposed states speaks of ternary systems (trits) called quantum trits, which involve a superposition of at least three basic states. Quantum escalation has no theoretical limits.


High-dimensional entanglement

High-dimensional entanglement The Melvin algorithm achieved this ternary state complexity and showed that its configuration could be used to generate high-dimensional entangled states.


Theseus outpaces him and promises to reach more complex levels of quantum entanglement, with AI photons, qubits and qutrits thinking for themselves.


These sophisticated algorithms do not wait for human instructions to break the current molds of quantum research, surpassing even the human capacity to devise new experiments, as has already happened.


New technological phase

New technological phase The design of new devices and experiments has historically been based on the intuition of human experts, they explain in this regard Krenn and other authors in Nature Reviews Physics


The new stage is inspired, however, by the design of computers that increasingly increase the capacity of scientists, particularly in the quantum field, they add.


This field is uniquely important because complex computing can solve two major challenges of quantum experiments: that quantum phenomena are not intuitive, and that the number of possible configurations of quantum experiments skyrockets exponentially with AI, the authors of this paper conclude. .


Reference:

Learning Interpretable Representations of Entanglement in Quantum Optics Experiments using Deep Generative Models. Mario Krenn et al. arXiv: 2109.02490v1arXiv: 2109.02490v1

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