The algorithm represents a first step in the automated learning of quantum information networks
Quantum-based communication and computation technologies promise unprecedented applications, such as unconditionally secure communications, ultra-precise sensors, and quantum computers capable of solving specific problems with a level of efficiency impossible to reach by classical computers.
In recent times, quantum computers are also envisioned as nodes in a network of quantum devices, where connections are established via quantum channels and data are quantum systems that flow through the network, thus setting the bases for a future "quantum internet".
With the design of these quantum information networks come new theoretical challenges, given that it is necessary to establish optimised automated information treatment protocols to work with quantum data, in the same way as current communcation networks automatically manage information.
UAB researchers have had to deal with one of these challenges for the first time: the problem with sorting data from a quantum systems network according to the state in which they were prepared. The researchers have devised an optimal procedure that can identify clusters of identically prepared quantum systems.
The protocol developed by researchers at the UAB shows a natural connection to an archetypical use case of classical machine learning: clustering data samples according to whether they share a common underlying probability distribution.
The problem is similar to how a classical computer discerns the origin of different sounds captured simultaneously by a microphone placed on the street. The computer can recognise patterns and discern a conversation, traffic, and a street musician. However, unlike soundwaves, identifying patterns in quantum data is much more challenging, since a mere observation only provides partial information and irretrievably degrades the data in the process.
Physicists at the UAB were also able to compare the performances of classical and quantum protocols. According to the researchers, the new protocol by far outperforms classical strategies, particularly for large dimensional data.
This proposal represents a new step towards quantum information networks, since it sets a solid theoretical framework on what is physically possible in the field of automated classification and distribution of quantum information.
The research was published today in the journal Physical Review X and is signed by researchers from the Quantum Phenomena and Information Unit at the UAB Department of Physics Gael Sentís, Àlex Monràs, Ramon Muñoz-Tàpia, Jon Calsamiglia and Emilio Bagan.
Gael Sentís | EurekAlert!
Spintronics: Faster data processing through ultrashort electric pulses
02.07.2020 | Martin-Luther-Universität Halle-Wittenberg
Multi-sensor system for the precise and efficient inspection of roads, railways and similar assets
01.07.2020 | Fraunhofer IPM
Solar cells based on perovskite compounds could soon make electricity generation from sunlight even more efficient and cheaper. The laboratory efficiency of these perovskite solar cells already exceeds that of the well-known silicon solar cells. An international team led by Stefan Weber from the Max Planck Institute for Polymer Research (MPI-P) in Mainz has found microscopic structures in perovskite crystals that can guide the charge transport in the solar cell. Clever alignment of these "electron highways" could make perovskite solar cells even more powerful.
Solar cells convert sunlight into electricity. During this process, the electrons of the material inside the cell absorb the energy of the light....
Empa researchers have succeeded in applying aerogels to microelectronics: Aerogels based on cellulose nanofibers can effectively shield electromagnetic radiation over a wide frequency range – and they are unrivalled in terms of weight.
Electric motors and electronic devices generate electromagnetic fields that sometimes have to be shielded in order not to affect neighboring electronic...
A promising operating mode for the plasma of a future power plant has been developed at the ASDEX Upgrade fusion device at Max Planck Institute for Plasma...
Live event – July 1, 2020 - 11:00 to 11:45 (CET)
"Automation in Aerospace Industry @ Fraunhofer IFAM"
The Fraunhofer Institute for Manufacturing Technology and Advanced Materials IFAM l Stade is presenting its forward-looking R&D portfolio for the first time at...
With an X-ray experiment at the European Synchrotron ESRF in Grenoble (France), Empa researchers were able to demonstrate how well their real-time acoustic monitoring of laser weld seams works. With almost 90 percent reliability, they detected the formation of unwanted pores that impair the quality of weld seams. Thanks to a special evaluation method based on artificial intelligence (AI), the detection process is completed in just 70 milliseconds.
Laser welding is a process suitable for joining metals and thermoplastics. It has become particularly well established in highly automated production, for...
02.07.2020 | Event News
19.05.2020 | Event News
07.04.2020 | Event News
03.07.2020 | Life Sciences
03.07.2020 | Studies and Analyses
03.07.2020 | Power and Electrical Engineering