Quantum Materials for Energy Efficient Neuromorphic Computing (Q-MEEN-C)—a nationwide consortium led by the University of California San Diego—has been at the forefront of research to create brain-like computers with minimal energy requirements would revolutionize nearly every aspect of modern life.  Quantum News Briefs summarizes August 8 article in Phys.org.
UC San Diego Assistant Professor of Physics Alex Frañó is co-director of Q-MEEN-C and thinks of the center’s work in phases. In the first phase, teams were successful in finding ways to create or mimic the properties of a single brain element (such as a neuron or synapse) in a quantum material. New research from Q-MEEN-C, published in Nano Letters, shows that electrical stimuli passed between neighboring electrodes can also affect non-neighboring electrodes. Known as non-locality, this discovery is a crucial milestone in the journey toward new types of devices that mimic brain functions known as neuromorphic computing.
“In the brain it’s understood that these non-local interactions are nominal—they happen frequently and with minimal exertion,” said Frañó. “It’s a crucial part of how the brain operates, but similar behaviors replicated in synthetic materials are scarce.
To date, recognition tasks that the brain executes so beautifully,can only be simulated through computer software. AI programs like ChatGPT and Bard use complex algorithms to mimic brain-based activities like thinking and writing. And they do it really well. But without correspondingly advanced hardware to support it, at some point software will reach its limit.
Frañó is eager for a hardware revolution to parallel the one currently happening with software, and showing that it’s possible to reproduce non-local behavior in a synthetic material inches scientists one step closer. The next step will involve creating more complex arrays with more electrodes in more elaborate configurations.
“It’s widely understood that in order for this technology to really explode, we need to find ways to improve the hardware—a physical machine that can perform the task in conjunction with the software,” Frañó stated. “The next phase will be one in which we create efficient machines whose physical properties are the ones that are doing the learning. That will give us a new paradigm in the world of artificial intelligence. Click here to read complete article in Phys.org.

Are quantum computers the future of genome analysis?

DNA sequencing technology, i.e., determining the order of nucleotide bases in a DNA molecule, is central to personalized medicine and disease diagnostics, yet even the fastest technologies require hours, or days, to read a complete sequence. Now, a multi-institutional research team led by The Institute of Scientific and Industrial Research (SANKEN) at Osaka University, has developed a technique that could lead to a new paradigm for genomic analysis. Quantum News Briefs summarizes.
In a study recently published in the Journal of Physical Chemistry B, the researchers aimed to use a quantum computer to distinguish adenosine from the other three nucleotide molecules. Using quantum encoding to identify single nucleotide molecules is a necessary first step toward the ultimate goal of DNA sequencing, and it’s this problem that the researchers sought to address.
“Using a quantum circuit, we show how to detect a nucleotide from only the measurement data of a single molecule,” explains Masateru Taniguchi, lead author of the study. “This is the first time a quantum computer has been connected to measurement data for a single molecule, and demonstrates the feasibility of using quantum computers in genome analysis.”
The researchers used electrodes with a nanoscale gap between them to detect single nucleotides. The output of current versus time for the adenosine monophosphate nucleotide differed from that of the other three nucleotides. This is because the conduction path of electrons between the nucleotide and the electrodes depends on the chemical architecture of the nucleotide. This is the basis for designing a quantum gate, which that serves as a molecular fingerprint for each nucleotide.
This work has broad and exciting potential applications: advances in drug discovery, cancer diagnosis, and infectious disease research are a few examples of what is expected with the advent of ultra-fast genome analysis.  Click here to read the July 31 Eureka Alert announcement in-entirety.

Sandra K. Helsel, Ph.D. has been researching and reporting on frontier technologies since 1990.  She has her Ph.D. from the University of Arizona.