New control electronics for quantum computers that improve performance, cut costs

Gustavo Cancelo led a team of Fermilab engineers to create a new compact electronics board: It has the capabilities of an entire rack of equipment that is compatible with many designs of superconducting qubits at a fraction of the cost. Credit: Ryan Postel, Fermilab

When designing a next-generation quantum computer, a surprisingly large problem is bridging the communication gap between the classical and quantum worlds. Such computers need a specialized control and readout electronics to translate back and forth between the human operator and the quantum computer’s languages—but existing systems are cumbersome and expensive.

However, a new system of control and readout electronics, known as Quantum Instrumentation Control Kit, or QICK, developed by engineers at the U.S. Department of Energy’s Fermi National Accelerator Laboratory, has proved to drastically improve quantum computer performance while cutting the cost of control equipment.

“The development of the Quantum Instrumentation Control Kit is an excellent example of U.S. investment in joint quantum technology research with partnerships between industry, academia and government to accelerate pre-competitive quantum research and development technologies,” said Harriet Kung, DOE deputy director for science programs for the Office of Science and acting associate director of science for high-energy physics.

The faster and more cost-efficient controls were developed by a team of Fermilab engineers led by senior principal engineer Gustavo Cancelo in collaboration with the University of Chicago whose goal was to create and test a field-programmable gate array-based (FPGA) controller for quantum computing experiments. David Schuster, a physicist at the University of Chicago, led the university’s lab that helped with the specifications and verification on real hardware.

“This is exactly the type of project that combines the strengths of a national laboratory and a university,” said Schuster. “There is a clear need for an open-source control hardware ecosystem, and it is being rapidly adopted by the quantum community.”

Engineers designing quantum computers deal with the challenge of bridging the two seemingly incompatible worlds of quantum and classical computers. Quantum computers are based on the counterintuitive, probabilistic rules of quantum mechanics that govern the microscopic world, which enables them to perform calculations that ordinary computers cannot. Because people live in the macroscopic visible world where classical physics reigns, control and readout electronics act as the interpreter connecting these two worlds.

Control electronics use signals from the classical world as instructions for the computer’s quantum bits, or qubits, while readout electronics measure the states of the qubits and convey that information back to the classical world.

One promising technology for quantum computers uses superconducting circuits as qubits. Currently, most control and readout systems for superconducting quantum computers use off-the-shelf commercial equipment not specialized to the task. As a result, researchers often must string together a dozen or more expensive components. The cost can quickly add up to tens of thousands of dollars per , and the large size of these systems creates more problems.

Despite recent technological advances, qubits still have a relatively short lifetime, generally a fraction of a millisecond, after which they generate errors. “When you work with qubits, time is critical. Classical electronics take time to respond to the qubits, limiting the performance of the computer,” said Cancelo.

Just as the effectiveness of an interpreter depends on rapid communication, the effectiveness of a control and readout system depends on its turnaround time. And a large system made of many modules means long turnaround times.

To address this issue, Cancelo and his team at Fermilab designed a compact control and readout system. The team incorporated the capabilities of an entire rack of equipment in a single electronics board slightly larger than a laptop. The new system is specialized, yet it is versatile enough to be compatible with many designs of superconducting qubits.

“We are designing a general instrument for a large variety of qubits, hoping to cover those that will be designed six months or a year from now,” Cancelo said. “With our control and readout electronics, you can achieve functionality and performance that is hard or impossible to do with commercial equipment.”

Most of the current control and readout systems for superconducting quantum computers use off-the-shelf commercial equipment in which researchers must string together a dozen or more expensive components resulting bulky and expensive control system. Credit: University of Chicago

The control and readout of qubits depend on microwave pulses—radio waves at frequencies similar to the signals that carry mobile phone calls and heat up microwave dinners. The Fermilab team’s (RF) board contains more than 200 elements: mixers to tweak the frequencies; filters to remove undesired frequencies; amplifiers and attenuators to adjust the amplitude of the signals; and switches to turn signals on and off. The board also contains a low-frequency control to tune certain qubit parameters. Together with a commercial field-programmable gate array, or FPGA, board, which serves as the “brains” of the computer, the RF board provides everything scientists need to communicate successfully with the quantum world.

The two compact boards cost about 10 times less to produce than conventional systems. In their simplest configuration, they can control eight qubits. Integrating all the RF components into one board allows for faster, more precise operation as well as real-time feedback and error correction.

“You need to inject signals that are very, very fast and very, very short,” said Fermilab engineer Leandro Stefanazzi, a member of the team. “If you don’t control both the frequency and duration of these signals very precisely, then your qubit won’t behave the way you want.”

Designing the RF board and layout took about six months and presented substantial challenges: adjacent circuit elements had to match precisely so that signals would travel smoothly without bouncing and interfering with each other. Plus, the engineers had to carefully avoid layouts that would pick up stray from sources like cell phones and WiFi. Along the way, they ran simulations to verify that they were on the right track.

The design is now ready for fabrication and assembly, with the goal of having working RF boards this summer.

Throughout the process, the Fermilab engineers tested their ideas with the University of Chicago. The new RF board is ideal for researchers like Schuster who seek to make fundamental advances in quantum computing using a wide variety of quantum computer architectures and devices.

“I often joke that this one board is going to potentially replace almost all of the test equipment that I have in my lab,” said Schuster. “Getting to team up with people who can make electronics work at that level is incredibly rewarding for us.”

The new system is easily scalable. Frequency multiplexing qubit controls, analogous to sending multiple phone conversations over the same cable, would allow a single RF board to control up to 80 qubits. Thanks to their small size, several dozen boards could be linked together and synchronized to the same clock as part of larger quantum computers. Cancelo and his colleagues described their new system in a paper recently published in the AIP Review of Scientific Instruments.

The Fermilab engineering team has taken advantage of a new commercial FPGA chip, the first to integrate digital-to-analog and analog-to-digital converters directly into the board. It substantially speeds up the process of creating the interface between the FPGA and RF boards, which would have taken months without it. To improve future versions of its control and readout system, the team has started designing its own FPGA hardware.

The development of QICK was supported by QuantISED, the Quantum Science Center (QSC) and later by the Fermilab-hosted Superconducting Quantum Materials and Systems Center (SQMS). The QICK electronics is important for research at the SQMS, where scientists are developing superconducting qubits with long lifetimes. It is also of interest to a second national quantum center where Fermilab plays a key role, the QSC hosted by Oak Ridge National Laboratory.

A low-cost version of the hardware is now available only for universities for educational purposes. “Due to its low cost, it allows smaller institutions to have powerful quantum control without spending hundreds of thousands of dollars,” said Cancelo.

“From a scientific point of view, we are working on one of the hottest topics in physics of the decade as an opportunity,” he added. “From an engineering point of view, what I enjoy is that many areas of electronic engineering need to come together to be able to successfully execute this project.”

More information:
Leandro Stefanazzi et al, The QICK (Quantum Instrumentation Control Kit): Readout and control for qubits and detectors, Review of Scientific Instruments (2022). DOI: 10.1063/5.0076249

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Hexbyte Glen Cove A remote control for functional materials

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An intense mid-infrared laser pulse hits a ferroelectric LiNbO3 crystal and kicks atomic vibrations only in a short depth below the surface, emphasized by the bright tetrahedra. Through anharmonic coupling, this strong vibration launches a polarization wave, also called polariton, which propagates throughout the remaining depth of the crystal to modulate the ferroelectric polarization. Credit: Joerg M. Harms / MPSD

Intense mid-infrared excitation has been demonstrated as a powerful tool for controlling the magnetic, ferroelectric and superconducting properties of complex materials. Nonlinear phononics is key to this end, as it displaces specific atoms away from their equilibrium positions to manipulate microscopic interactions. So far, this effect has been thought to occur only within the optically excited volume. Now researchers in Hamburg discovered that the polarization reversal in ferroelectric lithium niobate (LiNbO3) even occurs in areas well away from the direct light ‘hit’. The hitherto unknown phenomenon—called nonlocal nonlinear phononics—has been published in Nature Physics.

Ferroelectric materials such as LiNbO3 possess a static electric polarization generated by lines of positive and negative charge that can be switched with an electric field. This unique property makes these materials the basic building block of many modern electronic components in smartphones, laptops and ultrasound imaging devices. Using to change the ferroelectric polarization is a new approach that allows for extremely fast processes which would be a key step in the development of highly efficient ultrafast optical switches for new devices.

The researchers in Andrea Cavalleri’s group at the Max Planck Institute for the Structure and Dynamics (MPSD) used mid-infrared pulses to excite the surface of a LiNbO3 crystal, launching a strong vibration throughout a region that spans a depth of 3 micrometers from the crystal surface. Then, they used a technique called femtosecond stimulated Raman scattering to measure ultrafast changes of the ferroelectric polarization throughout the complete 50 micrometer crystal thickness. The measurements revealed that light pulses with a very high energy density cause the ferroelectric polarization to reverse throughout the entire crystal. By using to simulate the effects of nonlinear phononics in LiNbO3, the authors found that strong polarization waves called polaritons emerge from the small volume traversed by the light pulse and move throughout the remaining depth of the crystal. These polariton waves are believed to play a significant role in altering the ferroelectric polarization throughout the sections of the crystal that are untouched by the light pulse.

The results reported by Henstridge et al. add an exciting new piece to the elusive puzzle of ultrafast ferroelectricity, the understanding of which can lead to new device components such as sustainable optical switches. More broadly, this work opens an enormous question concerning whether past and future systems driven by nonlinear phononics can exhibit a similar type of nonlocal character. The ability to manipulate functional properties at a distance could expand the realm of possibilities for incorporating nonlinear phononics into integrated devices and other complex materials, opening new avenues for controlling systems with light.

More information:
M. Henstridge et al, Nonlocal nonlinear phononics, Nature Physics (2022). DOI: 10.1038/s41567-022-01512-3

A remote control for functional materials (2022, March 9)
retrieved 10 March 2022

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Hexbyte Glen Cove EPFL and DeepMind use AI to control plasmas for nuclear fusion

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Plasma inside the TCV tokamak. Credit: Curdin Wüthrich /SPC/EPFL

EPFL’s Swiss Plasma Center (SPC) has decades of experience in plasma physics and plasma control methods. DeepMind is a scientific discovery company acquired by Google in 2014 that’s committed to “solving intelligence to advance science and humanity.” Together, they have developed a new magnetic control method for plasmas based on deep reinforcement learning, and applied it to a real-world plasma for the first time in the SPC’s tokamak research facility, TCV. Their study has just been published in Nature.

Tokamaks are donut-shaped devices for conducting research on , and the SPC is one of the few research centers in the world that has one in operation. These devices use a powerful magnetic field to confine plasma at extremely high temperatures—hundreds of millions of degrees Celsius, even hotter than the sun’s core—so that nuclear fusion can occur between hydrogen atoms. The energy released from fusion is being studied for use in generating electricity.

What makes the SPC’s tokamak unique is that it allows for a variety of plasma configurations, hence its name: variable-configuration tokamak (TCV). That means scientists can use it to investigate new approaches for confining and controlling plasmas. A plasma’s configuration relates to its shape and position in the device.

Controlling a substance as hot as the sun

Tokamaks form and maintain plasmas through a series of magnetic coils whose settings, especially voltage, must be controlled carefully. Otherwise, the plasma could collide with the vessel walls and deteriorate. To prevent this from happening, researchers at the SPC first test their control systems configurations on a simulator before using them in the TCV tokamak.

“Our simulator is based on more than 20 years of research and is updated continuously,” says Federico Felici, an SPC scientist and co-author of the study. “But even so, lengthy calculations are still needed to determine the right value for each variable in the control system. That’s where our joint research project with DeepMind comes in.”

3D model of the TCV vacuum vessel containing the plasma, surrounded by various magnetic coils to keep the plasma in place and to affect its shape. Credit: DeepMind & SPC/EPFL

DeepMind’s experts developed an AI algorithm that can create and maintain specific plasma configurations and trained it on the SPC’s simulator. This involved first having the algorithm try many different control strategies in simulation and gathering experience. Based on the collected experience, the algorithm generated a control strategy to produce the requested plasma configuration. This involved first having the algorithm run through a number of different settings and analyze the plasma configurations that resulted from each one. Then the algorithm was called on to work the other way—to produce a specific plasma configuration by identifying the right settings.

After being trained, the AI-based system was able to create and maintain a wide range of plasma shapes and advanced configurations, including one where two separate plasmas are maintained simultaneously in the vessel. Finally, the research team tested their new system directly on the tokamak to see how it would perform under real-world conditions.

The SPC’s collaboration with DeepMind dates back to 2018 when Felici first met DeepMind scientists at a hackathon at the company’s London headquarters. There he explained his research group’s tokamak magnetic-control problem. “DeepMind was immediately interested in the prospect of testing their AI technology in a field such as nuclear fusion, and especially on a real-world system like a tokamak,” says Felici.

Martin Riedmiller, control team lead at DeepMind and co-author of the study, adds that “our team’s mission is to research a new generation of AI systems—closed-loop controllers—that can learn in complex dynamic environments completely from scratch. Controlling a fusion in the real world offers fantastic, albeit extremely challenging and complex, opportunities.”

Range of different plasma shapes generated with the reinforcement learning controller Credit: DeepMind & SPC/EPFL

A win-win collaboration

After speaking with Felici, DeepMind offered to work with the SPC to develop an AI-based control system for its . “We agreed to the idea right away, because we saw the huge potential for innovation,” says Ambrogio Fasoli, the director of the SPC and a co-author of the study. “All the DeepMind scientists we worked with were highly enthusiastic and knew a lot about implementing AI in control systems.” For his part, Felici was impressed with the amazing things DeepMind can do in a short time when it focuses its efforts on a given project.

DeepMind also got a lot out of the joint research project, illustrating the benefits to both parties of taking a multidisciplinary approach. Brendan Tracey, a senior research engineer at DeepMind and co-author of the study, says: “The collaboration with the SPC pushes us to improve our reinforcement learning algorithms, and as a result can accelerate research on fusing plasmas.”

This project should pave the way for EPFL to seek out other joint R&D opportunities with outside organizations. “We’re always open to innovative win-win collaborations where we can share ideas and explore new perspectives, thereby speeding the pace of technological development,” says Fasoli.

More information:
Jonas Degrave et al, Magnetic control of tokamak plasmas through deep reinforcement learning, Nature (2022). DOI: 10.1038/s41586-021-04301-9

EPFL and DeepMind use AI to control plasmas for nuclear fusion (2022, February 16)
retrieved 17 February 2022

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part may be reproduced without the written permission. The content is provided for information purposes only.

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Hexbyte Glen Cove Transcriptional control of mycobacterial DNA damage response by sigma adaptation

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Credit: ETH Zurich

A recent study by the Weber-Ban and Ban groups (IMBB) published in Science Advances uncovers that the master regulator of the DNA damage response in mycobacteria, PafBC, leverages a unique mechanism of transcriptional activation to allow promoter recognition at promoters lacking the canonical -35 motif.

At the transcriptional level, mycobacteria, such as the human pathogen M. tuberculosis, respond to DNA damage via two intertwined regulatory pathways. One pathway constitutes the canonical SOS response, which is regulated by RecA and repressor LexA. The other, recently discovered pathway under control of regulator PafBC controls a large number of genes by transcription activation, including recA. While the derepression mechanism of the SOS response is well understood, PafBC’s mechanism of transcription activation remained unknown.

Researchers at IMBB discovered a unique mechanism of promoter recognition employed by PafBC. In bacteria, promoter recognition usually involves two canonical sequence motifs located at positions -35 and -10 from the transcription start site. However, PafBC-dependent promoters can be considered “hybrid,” since they include the canonical -10 region but lack the -35 motif and instead feature a PafBC-specific sequence motif at position -26. Using cryo- and biochemical experiments, the researchers visualized a PafBC-containing transcription initiation complex. They show that PafBC functions as an adaptor by inserting between the sigma subunit and the DNA so that the RNA polymerase holoenzyme recognizes a hybrid -26/-10 promoter, hence this mechanism is referred to as “sigma adaptation.”

Genome-wide studies found that many promoters in mycobacteria lack a canonical -35 motif. The mechanism of PafBC-dependent “sigma adaptation” could therefore represent an example of a widespread, alternative mode of bacterial promoter recognition employed also by other transcription factors.

More information:
Andreas U. Müller et al, Transcriptional control of mycobacterial DNA damage response by sigma adaptation, Science Advances (2021). DOI: 10.1126/sciadv.abl4064

Transcriptional control of mycobacterial DNA damage response by sigma adaptation (2021, December 6)
retrieved 7 December 2021


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Hexbyte Glen Cove Remote control for plants thumbnail

Hexbyte Glen Cove Remote control for plants

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Credit: CC0 Public Domain

Plants have microscopically small pores on the surface of their leaves called stomata. These help plants regulate the influx of carbon dioxide for photosynthesis. They also prevent the loss of too much water and withering away during drought.

The stomatal pores are surrounded by two guard cells. If the internal pressure of these cells drops, they slacken and close the pore. If the pressure rises, the cells move apart and the pore widens.

The stomatal movements are thus regulated by the guard cells. Signaling pathways in these cells are so complex that it is difficult for humans to intervene with them directly. However, researchers of the Julius-Maximilians-Universität (JMU) Würzburg in Bavaria, Germany, nevertheless found a way to control the movements of stomata remotely—using .

Light-sensitive protein from algae used

The researchers succeeded in doing this by introducing a light-sensitive switch into the guard cells of tobacco . This technology was adopted from optogenetics. It has been successfully exploited in animal cells, but the application in plant cells it is still in its infancy.

The team led by JMU biophysicist and guard cell expert Professor Rainer Hedrich describes their approach in the journal Science Advances. JMU researchers Shouguang Huang (first author), Kai Konrad and Rob Roelfsema were significantly involved.

The group used a from the alga Guillardia theta as a light switch, namely the anion channel ACR1 from the group of channelrhodopsins. In response to light pulses, the switch ensures that chloride flows out of the guard cells and potassium follows. The guard cells lose internal pressure, slacken and the pore closes within 15 minutes. “The light pulse is like a for the movement of the stomata,” says Hedrich.

Anion channel hypothesis confirmed

“By exposing ACR1 to light, we have bridged the cell’s own signaling chain, thus proving the hypothesis that the opening of anion channels is essential and sufficient for stomatal closure,” Hedrich says. The exposure to light had almost completely prevented the transpiration of the plants.

With this knowledge, it is now possible to cultivate plants with an increased number of anion channels in the guard . Plants equipped in this way should close their stomata more quickly in response to approaching heat waves and thus be better able to cope with periods of drought.

“Plant anion channels are activated during stress; this process is dependent on calcium. In a follow up optogenetics project, we want to use calcium-conducting channelrhodopsins to specifically allow calcium to flow into the cell through exposure to and to understand the mechanism of anion channel activation in detail,” Hedrich says.

Basic scientific research can also benefit from the results from Würzburg: “Our new optogenetic tool has for research,” says the JMU professor. “With it, we can gain new insights into how plants regulate their water consumption and how carbon dioxide fixation and stomatal movements are coupled.”

More information:
Optogenetic control of the guard cell membrane potential and stomatal movement by the light-gated anion channel GtACR1, Science Advances (2021). DOI: 10.1126/sciadv.abg4619

Remote control for plants (2021, July 9)
retrieved 10 July 2021

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