Tyler O'Neal, Staff Editor SYSTEMS

Bristol's QETLabs develops ML algo that helps unravel the physics underlying quantum systems

Protocol to reverse engineer Hamiltonian models advances automation of quantum devices

Scientists from the University of Bristol's Quantum Engineering Technology Labs (QETLabs) have developed a machine learning algorithm that provides valuable insights into the physics underlying quantum systems - paving the way for significant advances in quantum computation and sensing and potentially turning a new page in a scientific investigation.

In physics, systems of particles and their evolution are described by mathematical models, requiring the successful interplay of theoretical arguments and experimental verification. Even more complex is the description of systems of particles interacting with each other at the quantum mechanical level, which is often done using a Hamiltonian model. The process of formulating Hamiltonian models from observations is made even harder by the nature of quantum states, which collapse when attempts are made to inspect them. The nitrogen vacancy centre set-up, that was used for the first experimental demonstration of QMLA. CREDIT Gentile et al.

In the paper, Learning models of quantum systems from experiments, quantum mechanics from Bristol's QET Labs describe an algorithm that overcomes these challenges by acting as an autonomous agent, using machine learning to reverse engineer Hamiltonian models.

The team developed a new protocol to formulate and validate approximate models for quantum systems of interest. Their algorithm works autonomously, designing and performing experiments on the targeted quantum system, with the resultant data being fed back into the algorithm. It proposes candidate Hamiltonian models to describe the target system and distinguishes between them using statistical metrics, namely Bayes factors.

Excitingly, the team successfully demonstrated the algorithm's ability on a real-life quantum experiment involving defect centers in a diamond, a well-studied platform for quantum information processing and quantum sensing.

The algorithm could be used to aid automated characterization of new devices, such as quantum sensors. This development, therefore, represents a significant breakthrough in the development of quantum technologies.

"Combining the power of today's supercomputers with machine learning, we were able to automatically discover structure in quantum systems. As new quantum computers/simulators become available, the algorithm becomes more exciting: first, it can help to verify the performance of the device itself, then exploit those devices to understand ever-larger systems," said Brian Flynn from the University of Bristol's QETLabs and Quantum Engineering Centre for Doctoral Training.

"This level of automation makes it possible to entertain myriads of hypothetical models before selecting an optimal one, a task that would be otherwise daunting for systems whose complexity is ever-increasing," said Andreas Gentile, formerly of Bristol's QETLabs, now at Qu & Co.

"Understanding the underlying physics and the models describing quantum systems, help us to advance our knowledge of technologies suitable for quantum computation and quantum sensing," said Sebastian Knauer, also formerly of Bristol's QETLabs and now based at the University of Vienna's Faculty of Physics.

Anthony Laing, co-Director of QETLabs and Associate Professor in Bristol's School of Physics, and an author on the paper praised the team: "In the past, we have relied on the genius and hard work of scientists to uncover new physics. Here the team has potentially turned a new page in the scientific investigation by bestowing machines with the capability to learn from experiments and discover new physics. The consequences could be far-reaching indeed."

The next step for the research is to extend the algorithm to explore larger systems and different quantum models that represent different physical regimes or underlying structures.

UMD engineering employs all-atom molecular dynamics simulations to demonstrate overscreening, flow reversal in nanosystems

Tyler O'Neal, Staff Editor SYSTEMS

Nanochannels have important applications in biomedicine, sensing, and many other fields. Though engineers working in the field of nanotechnology have been fabricating these tiny, tube-like structures for years, much remains unknown about their properties and behavior.

Now, University of Maryland mechanical engineering associate professor Siddhartha Das and a group of his Ph.D. students have published surprising new findings in the journal ACS Nano. Using atomic-level simulations, Das and his team were able to demonstrate that charge properties as well as charge-induced fluid flow within a functionalized nanochannel does not always behave as expected.

"We've discovered a new context for nanochannels functionalized by grafting their inner walls with charged polymer molecules (also known as polyelectrolytes or PEs)," Das said, referring to the process of grafting polymers or other substances onto the nanochannel in order to cause it to function in a certain way. "The functionalization of nanochannels is not new. But we've come up with a paradigm shift in terms of understanding the behavior and properties of such systems in the context of their charge properties and their ability to regulate fluid flow. (left) Schematic of the PE-brush-grafted nanochannel system. (right) Flow reversal with applied electric field strength. CREDIT T. H. Pial et al., ACS Nano, 2021, DOI: 10.1021/acsnano.0c09248

"For example," Das said, "we've discovered a new type of flow behavior in such functionalized nanochannels; by increasing the magnitude of the electric field applied to a nanochannel, the direction of this electric-field-driven flow (often known as electroosmotic flow) can be reversed."

The paper by Das and his students details three specific discoveries. Firstly, they showed that, when polyelectrolytes (PEs) are grafted in the form of a layer on the inner wall of the nanochannel, this PE layer will, under certain conditions, undergo a surprising reversal of electrical charge. Normally, if negative PE molecules have been attached to the nanochannel, the PE layer nearby should have a net negative charge. Das and his students, however, identified situations in which the charge becomes inverted and the net charge within the layer is positive due to the attraction of more number of positive ions (than needed to screen the charge of the PE layer) within the layer--this phenomenon is known as "overscreening."

The team then investigated how this overscreening affects the external electric field driven flow (known as the electroosmotic or EOS flow) within the nanochannel. They found, surprisingly, that in such situations the flow is driven by ions having the same charge as the Pes grafted onto the channel walls; thus, a negatively charged polymer creates a net positive field in its vicinity, but the flow is driven by the negative ions.

"We call this 'co-ion driven electro-osmosis,' and our paper marks the first time this phenomenon has been identified," Das said.

Finally, the team demonstrated the unexpected results of ramping up the magnitude of the electric field: the PE molecules attached to the nanochannel become deformed, and the ions that caused the instance of overscreening start to escape from the PE layer. This causes the overscreening to stop, and also reverses the direction of flow in the channel: if it was moving left to right, for instance, it switches to right-left. "No one predicted this," Das said.

The findings are significant, Das said, because much of the interest in nanochannels relates from their ability to transport molecules. "Since flow is so important, a new discovery in this area allows us to build on our understanding of how nanochannels work and what we can do with them," Das said. "There are other methods of reversing flow, but until now it was not known that we can accomplish this by increasing field strength."

NASA launches new space tech research institutes to advance electric propulsion, entry systems

Tyler O'Neal, Staff Editor SYSTEMS

Technology drives exploration, and as NASA eyes deep-space human exploration, technology is at the forefront of its plans. Preparing for these missions requires technology development within the agency and research by external experts in various fields.

As part of this effort, NASA will establish two new university-led Space Technology Research Institutes (STRIs), which will join four already active institutes. The new STRIs will bring together researchers from different disciplines and organizations to tackle challenges associated with electric propulsion ground testing and atmospheric entry systems modeling. The new STRIs aim to advance these game-changing technologies for exploring the Moon, Mars, and beyond.

“We started the STRI opportunity as a novel approach to technology research and development,” said Jim Reuter, associate administrator for NASA’s Space Technology Mission Directorate (STMD). “The selected institutes bring together premier researchers from their respective fields to focus on challenges facing future missions. The advancements these new STRI’s make will help NASA to venture farther into space.”

Each STRI will receive as much as $15 million over five years. The selected institutes are:

Joint Advanced Propulsion Institute (JANUS)

NASA is exploring high-power electric propulsion systems for human exploration of the solar system. The JANUS institute will develop strategies and specific methodologies to surmount limitations in ground testing of high-power electric propulsion systems and to improve characterization of the wear and performance of these devices representative of in-space operation. Solar electric propulsion Hall thruster prototype. Credits: NASA

Establishing a sufficient space-like environment is crucial for evaluating and predicting high-power propulsion system behavior and ensuring mission success. JANUS will utilize physics-based modeling, high-power thruster testing, novel diagnostic development, and fundamental experiments to advance mitigation strategies to overcome the limits of current ground testing capabilities. 

Mitchell Walker of the Georgia Institute of Technology in Atlanta is the principal investigator and will lead the JANUS team. Partnering universities include the University of Michigan in Ann Arbor; University of California, Los Angeles; the University of Illinois at Urbana-Champaign; Colorado State University in Fort Collins; Pennsylvania State University in State College; Stanford University in Stanford, California; University of Colorado Boulder; Western Michigan University in Kalamazoo; Clark Atlanta University in Atlanta; and Chicago State University and City Colleges of Chicago, both in Chicago. Other partners include The Aerospace Corporation, Aerojet Rocketdyne, and Busek.

Advanced Computational Center for Entry System Simulation (ACCESS)

Entry, descent, and landing technologies must continue to improve to meet the challenges of placing large payloads on other worlds, such as Mars. Accurate modeling and simulation of atmospheric entry systems are critical for the design and planning of these missions. The Arc Jet Complex at NASA’s Ames Research Center in California’s Silicon Valley conducts heat simulation testing on a conceptual heat shield prototype. Credits: NASA

The ACCESS institute will advance the analysis and design of NASA entry systems by developing a fully integrated, interdisciplinary simulation capability. ACCESS will focus on thermal protection systems, which protect spacecraft from aerodynamic heating, as well as prediction of the extreme environments experienced during entry. It will develop game-changing capabilities through the use of high-fidelity, validated physics models. This advancement will be enabled by innovative numerical algorithms, high-performance computing, and uncertainty quantification methods, with the goal of enabling computational entry system reliability assessments. 

Iain Boyd of the University of Colorado Boulder will serve as the principal investigator and lead the ACCESS team. The institute will be implemented in partnership with the University of Illinois at Urbana-Champaign, the University of Minnesota Twin Cities, the University of Kentucky in Lexington, and the University of New Mexico in Albuquerque.

Active STRIs at Work

In 2017, NASA selected the first-ever STRIs. The Center for the Utilization of Biological Engineering in Space, or CUBES, furthers biomanufacturing technologies that are needed to sustain astronauts on another planet. The institute has successfully grown medicine using lettuce and developed optimized lighting techniques for future extra-terrestrial greenhouses. The Institute for Ultra-Strong Composites by Computational Design, or US-COMP,  matures transformative carbon nanotube composite materials by using modeling and simulation to support their manufacturing and design. The institute has produced samples with more than twice the tensile strength of existing composite materials.

In 2019, NASA funded two more STRIs focused on technologies to enable “smart” habitats. Habitats Optimized for Missions of Exploration, or HOME, is advancing early-stage technologies related to autonomous systems, human-robot teams, data science, machine learning, onboard manufacturing, and more. The Resilient ExtraTerrestrial Habitats institute, or RETHi, is designing a deep-space habitat concept that can adapt, absorb, and rapidly recover from expected and unexpected disruptions. The habitat would operate and thrive in both crewed and uncrewed configurations.

STMD’s Space Technology Research Grants program hosts and funds each STRI. STMD develops the pioneering technologies and capabilities NASA needs to achieve its current and future missions.

For more information about NASA space tech, visit: http://www.nasa.gov/spacetech