Tag Archives: Sonia Fernandez

The memristor as computing device

An Oct. 27, 2016 news item on Nanowerk both builds on the Richard Feynman legend/myth and announces some new work with memristors,

In 1959 renowned physicist Richard Feynman, in his talk “[There’s] Plenty of Room at the Bottom,” spoke of a future in which tiny machines could perform huge feats. Like many forward-looking concepts, his molecule and atom-sized world remained for years in the realm of science fiction.

And then, scientists and other creative thinkers began to realize Feynman’s nanotechnological visions.

In the spirit of Feynman’s insight, and in response to the challenges he issued as a way to inspire scientific and engineering creativity, electrical and computer engineers at UC Santa Barbara [University of California at Santa Barbara, UCSB] have developed a design for a functional nanoscale computing device. The concept involves a dense, three-dimensional circuit operating on an unconventional type of logic that could, theoretically, be packed into a block no bigger than 50 nanometers on any side.

A figure depicting the structure of stacked memristors with dimensions that could satisfy the Feynman Grand Challenge Photo Credit: Courtesy Image

A figure depicting the structure of stacked memristors with dimensions that could satisfy the Feynman Grand Challenge. Photo Credit: Courtesy Image

An Oct. 27, 2016 UCSB news release (also on EurekAlert) by Sonia Fernandez, which originated the news item, offers a basic explanation of the work (useful for anyone unfamiliar with memristors) along with more detail,

“Novel computing paradigms are needed to keep up with the demand for faster, smaller and more energy-efficient devices,” said Gina Adam, postdoctoral researcher at UCSB’s Department of Computer Science and lead author of the paper “Optimized stateful material implication logic for three dimensional data manipulation,” published in the journal Nano Research. “In a regular computer, data processing and memory storage are separated, which slows down computation. Processing data directly inside a three-dimensional memory structure would allow more data to be stored and processed much faster.”

While efforts to shrink computing devices have been ongoing for decades — in fact, Feynman’s challenges as he presented them in his 1959 talk have been met — scientists and engineers continue to carve out room at the bottom for even more advanced nanotechnology. A nanoscale 8-bit adder operating in 50-by-50-by-50 nanometer dimension, put forth as part of the current Feynman Grand Prize challenge by the Foresight Institute, has not yet been achieved. However, the continuing development and fabrication of progressively smaller components is bringing this virus-sized computing device closer to reality, said Dmitri Strukov, a UCSB professor of computer science.

“Our contribution is that we improved the specific features of that logic and designed it so it could be built in three dimensions,” he said.

Key to this development is the use of a logic system called material implication logic combined with memristors — circuit elements whose resistance depends on the most recent charges and the directions of those currents that have flowed through them. Unlike the conventional computing logic and circuitry found in our present computers and other devices, in this form of computing, logic operation and information storage happen simultaneously and locally. This greatly reduces the need for components and space typically used to perform logic operations and to move data back and forth between operation and memory storage. The result of the computation is immediately stored in a memory element, which prevents data loss in the event of power outages — a critical function in autonomous systems such as robotics.

In addition, the researchers reconfigured the traditionally two-dimensional architecture of the memristor into a three-dimensional block, which could then be stacked and packed into the space required to meet the Feynman Grand Prize Challenge.

“Previous groups show that individual blocks can be scaled to very small dimensions, let’s say 10-by-10 nanometers,” said Strukov, who worked at technology company Hewlett-Packard’s labs when they ramped up development of memristors and material implication logic. By applying those results to his group’s developments, he said, the challenge could easily be met.

The tiny memristors are being heavily researched in academia and in industry for their promising uses in memory storage and neuromorphic computing. While implementations of material implication logic are rather exotic and not yet mainstream, uses for it could pop up any time, particularly in energy scarce systems such as robotics and medical implants.

“Since this technology is still new, more research is needed to increase its reliability and lifetime and to demonstrate large scale three-dimensional circuits tightly packed in tens or hundreds of layers,” Adam said.

HP Labs, mentioned in the news release, announced the ‘discovery’ of memristors and subsequent application of engineering control in two papers in 2008.

Here’s a link to and a citation for the UCSB paper,

Optimized stateful material implication logic for threedimensional data manipulation by Gina C. Adam, Brian D. Hoskins, Mirko Prezioso, &Dmitri B. Strukov. Nano Res. (2016) pp. 1 – 10. doi:10.1007/s12274-016-1260-1 First Online: 29 September 2016

This paper is behind a paywall.

You can find many articles about memristors here by using either ‘memristor’ or ‘memristors’ as your search term.

Connecting chaos and entanglement

Researchers seem to have stumbled across a link between classical and quantum physics. A July 12, 2016 University of California at Santa Barbara (UCSB) news release (also on EurekAlert) by Sonia Fernandez provides a description of both classical and quantum physics, as well as, the research that connects the two,

Using a small quantum system consisting of three superconducting qubits, researchers at UC Santa Barbara and Google have uncovered a link between aspects of classical and quantum physics thought to be unrelated: classical chaos and quantum entanglement. Their findings suggest that it would be possible to use controllable quantum systems to investigate certain fundamental aspects of nature.

“It’s kind of surprising because chaos is this totally classical concept — there’s no idea of chaos in a quantum system,” Charles Neill, a researcher in the UCSB Department of Physics and lead author of a paper that appears in Nature Physics. “Similarly, there’s no concept of entanglement within classical systems. And yet it turns out that chaos and entanglement are really very strongly and clearly related.”

Initiated in the 15th century, classical physics generally examines and describes systems larger than atoms and molecules. It consists of hundreds of years’ worth of study including Newton’s laws of motion, electrodynamics, relativity, thermodynamics as well as chaos theory — the field that studies the behavior of highly sensitive and unpredictable systems. One classic example of chaos theory is the weather, in which a relatively small change in one part of the system is enough to foil predictions — and vacation plans — anywhere on the globe.

At smaller size and length scales in nature, however, such as those involving atoms and photons and their behaviors, classical physics falls short. In the early 20th century quantum physics emerged, with its seemingly counterintuitive and sometimes controversial science, including the notions of superposition (the theory that a particle can be located in several places at once) and entanglement (particles that are deeply linked behave as such despite physical distance from one another).

And so began the continuing search for connections between the two fields.

All systems are fundamentally quantum systems, according [to] Neill, but the means of describing in a quantum sense the chaotic behavior of, say, air molecules in an evacuated room, remains limited.

Imagine taking a balloon full of air molecules, somehow tagging them so you could see them and then releasing them into a room with no air molecules, noted co-author and UCSB/Google researcher Pedram Roushan. One possible outcome is that the air molecules remain clumped together in a little cloud following the same trajectory around the room. And yet, he continued, as we can probably intuit, the molecules will more likely take off in a variety of velocities and directions, bouncing off walls and interacting with each other, resting after the room is sufficiently saturated with them.

“The underlying physics is chaos, essentially,” he said. The molecules coming to rest — at least on the macroscopic level — is the result of thermalization, or of reaching equilibrium after they have achieved uniform saturation within the system. But in the infinitesimal world of quantum physics, there is still little to describe that behavior. The mathematics of quantum mechanics, Roushan said, do not allow for the chaos described by Newtonian laws of motion.

To investigate, the researchers devised an experiment using three quantum bits, the basic computational units of the quantum computer. Unlike classical computer bits, which utilize a binary system of two possible states (e.g., zero/one), a qubit can also use a superposition of both states (zero and one) as a single state. Additionally, multiple qubits can entangle, or link so closely that their measurements will automatically correlate. By manipulating these qubits with electronic pulses, Neill caused them to interact, rotate and evolve in the quantum analog of a highly sensitive classical system.

The result is a map of entanglement entropy of a qubit that, over time, comes to strongly resemble that of classical dynamics — the regions of entanglement in the quantum map resemble the regions of chaos on the classical map. The islands of low entanglement in the quantum map are located in the places of low chaos on the classical map.

“There’s a very clear connection between entanglement and chaos in these two pictures,” said Neill. “And, it turns out that thermalization is the thing that connects chaos and entanglement. It turns out that they are actually the driving forces behind thermalization.

“What we realize is that in almost any quantum system, including on quantum computers, if you just let it evolve and you start to study what happens as a function of time, it’s going to thermalize,” added Neill, referring to the quantum-level equilibration. “And this really ties together the intuition between classical thermalization and chaos and how it occurs in quantum systems that entangle.”

The study’s findings have fundamental implications for quantum computing. At the level of three qubits, the computation is relatively simple, said Roushan, but as researchers push to build increasingly sophisticated and powerful quantum computers that incorporate more qubits to study highly complex problems that are beyond the ability of classical computing — such as those in the realms of machine learning, artificial intelligence, fluid dynamics or chemistry — a quantum processor optimized for such calculations will be a very powerful tool.

“It means we can study things that are completely impossible to study right now, once we get to bigger systems,” said Neill.

Experimental link between quantum entanglement (left) and classical chaos (right) found using a small quantum computer. Photo Credit: Courtesy Image (Courtesy: UCSB)

Experimental link between quantum entanglement (left) and classical chaos (right) found using a small quantum computer. Photo Credit: Courtesy Image (Courtesy: UCSB)

Here’s a link to and a citation for the paper,

Ergodic dynamics and thermalization in an isolated quantum system by C. Neill, P. Roushan, M. Fang, Y. Chen, M. Kolodrubetz, Z. Chen, A. Megrant, R. Barends, B. Campbell, B. Chiaro, A. Dunsworth, E. Jeffrey, J. Kelly, J. Mutus, P. J. J. O’Malley, C. Quintana, D. Sank, A. Vainsencher, J. Wenner, T. C. White, A. Polkovnikov, & J. M. Martinis. Nature Physics (2016)  doi:10.1038/nphys3830 Published online 11 July 2016

This paper is behind a paywall.