Zurich Instruments Newsletter - Edition Q1/2020

Overview

Welcome to the Q1/2020 newsletter!

New year, new website – we hope you enjoy the fresh look of our pages, which we re-designed entirely to offer a clearer and more efficient navigation. Browse and get inspired!

For this edition of the newsletter, our application scientists wrote about a variety of topics including multiplexed readout of superconducting qubits, data acquisition for imaging applications, and impedance spectroscopy of tap water.

News: Zurich Instruments joins IBM Q Network

Zurich Instruments has joined the IBM Q Network™, which now counts over 100 members from different industry sectors as well as research laboratories and startups. With access to IBM's quantum resources such as the Qiskit software and developer tools, this membership will enable us to work with IBM on the integration of their quantum technology with our products. The goal? Ensure reliable control and measurement of a quantum device with a clean software interface to the next level in the quantum stack.

Read about the news on our website

Paper: Repeated quantum error detection in a surface code

Thumb of Repeated quantum error detection in a surface code

Would you like to see what is possible when the Zurich Instruments Quantum Computing Control System (QCCS) is in the hands of an ambitious research team? Take a look at the preprint by the Quantum Device Lab at ETH Zurich reporting the first realization of the surface code. Christian Andersen and colleagues built a setup with 3 HDAWGs and 2 UHFQAs to perform successful error detection using 7 superconducting qubits. Congratulations on this result!

Read the full preprint

Blog Post: How to use the UHFQA for multiplexed readout of superconducting qubits

Multiplexed readout

Frequency-multiplexed readout of qubits is at the core of superconducting quantum processors. The Zurich Instruments UHFQA Quantum Analyzer was specifically designed for this task. In this blog post, Max Ruckriegel discusses how to use the advanced features of the UHFQA in a tabletop realization. The demonstration includes the generation of multiplexed readout signals, weighted integration, crosstalk suppression, and state discrimination – all based on the high-level Python API.

Read the full post by Max Ruckriegel

Video and Blog Post:
Choose the right tool to acquire lock-in data

Zurich Instruments' Lock-in Amplifiers come with a variety of tools to record data. In our latest video and related blog post, Kivanç Esat discusses how to pick the best acquisition tool for an efficient workflow in four typical use cases: acquiring an individual data point, observing the temporal evolution of a signal, capturing several data points after a trigger, and acquiring an entire image simultaneously on multiple channels.

Read the full post by Kivanç Esat

Blog Post: DFRT revisited – from feedback optimization to full data acquisition

DFRT Revisited

Leave no room for guessing and tame any type of linear system response. In this blog post, Romain Stomp provides a practical step-by-step guide for the dual frequency resonance tracking (DFRT) technique. Watch the data as they are acquired line by line with any third-party scan generator: this is image acquisition from raw input signal to well-behaved tip trajectory.

Read the full post by Romain Stomp

Interview: Dr. Natalia Ares, University of Oxford

Group of DR. Natalia Ares, University of Oxford
Dr. Natalia Ares (standing in the center) is a Royal Society University Research Fellow in the Materials Department at the University of Oxford. She leads a group researching quantum behaviour in nanoscale devices.

Hi Natalia, we found your work on characterizing quantum dots with machine learning fascinating. Tell us why and how you started using this approach in your measurements.

We started using machine learning (ML) techniques in our laboratory because we realized that a bottleneck to the scalability of quantum devices, common to all implementations, is that each device has to be characterized and tuned, requiring the exploration of a large parameter space. Even for an experienced researcher, to manually characterize and tune a quantum device is time-consuming; for a large array of quantum devices the task quickly becomes intractable. Our work tackles this challenge through automation, which I believe will be key in the race to scale from today’s few-qubit devices to a technologically useful number.

In our first paper on this topic, we showed how a machine learning algorithm can efficiently measure quantum devices in real time, reducing measurement times up to a factor of 4. More recently, we reported on automatic tuning of quantum devices faster than human experts without human input. The parameters vary non-monotonically and not always predictably with the control signals, making device tuning an extremely complex task to automate: scientists from DeepMind and my group at Oxford found an algorithm that can dynamically tune a 'virgin' double quantum dot device to operation conditions. We believe this technology is a promising route towards tuning large quantum circuits.

To what other measurement scenarios could ML be applied? What are the benefits and potential pitfalls?

I see a great potential in ML techniques for optimal measurement and control, especially as the complexity of quantum circuits increases. The major benefit can be seen in tasks such as the exploration of a multi-dimensional parameter space. I think the main pitfall is to believe that off-the-shelf machine learning algorithms are ready to solve the characterization and tuning challenges that quantum devices present. We realized we had to innovate the ML techniques to make a significant contribution.

Can you tell us about your journey as a scientist?

I studied physics at the University of Buenos Aires, Argentina, where I am from. My master's thesis was on quantum chaos, a theoretical project focused on the effect of perturbations on quantum systems. When I graduated, I wanted to work on experimental realizations of quantum devices and moved to France for postgraduate education. I developed SiGe quantum devices for the implementation of long-lived qubits that build on integrated circuit technology. I arrived in Oxford more than six years ago as a postdoc, and shortly after that was awarded a Marie Skłodowska Curie Fellowship. Since then, I have been awarded a Templeton Independent Research Fellowship and am currently a Royal Society University Research Fellow. At the University of Oxford I first worked on radio-frequency reflectometry for spin-qubit readout and carbon nanotube electromechanics. My group now focuses on machine learning for qubit scalability and on developing quantum devices to study quantum thermodynamics.

This has been a great journey so far, and I was lucky enough to benefit from the support of amazing people. I realized that mentors and role models are essential. Especially for women in science, I think we all have to work harder at creating mechanisms for inspiration and guidance and, most important, mechanisms that counterbalance the biases and extra challenges that women face.

What are the fundamental concepts you tackle in the area of quantum thermodynamics?

I aim at studying the laws of thermodynamics in quantum devices, for which fluctuations are important and quantum effects arise. Quantum thermodynamics is a rapidly advancing field of physics, but its theoretical development is presently far ahead of experimental implementations. I want to develop an experimental platform with the necessary ingredients to explore questions such as: what is the efficiency of a quantum engine? Understanding thermodynamics in the quantum arena will be key for the construction of nanomachines and for energy harvesting. It will also improve the engineering basis of quantum technologies by facilitating fully informed choices on device design and optimization, and it may reveal entirely novel technologies.

How do the Zurich Instruments UHFLI Lock-in Amplifiers help you in your work?

We use our UHFLIs for radio-frequency reflectometry readout of semiconductor devices. We achieved a record sensitivity to the change in quantum capacitance associated with qubit states, which is key for fast and accurate qubit readout. Thanks to the UHFLI, the experiment was faster and simpler.

We also used our UHFLIs to detect coherent nanomechanical oscillations driven by single-electron tunneling in a suspended carbon nanotube. These oscillations have not been observed before because their detection required a challenging combination of coupling strength and measurement speed. Our experiment achieved both requirements, allowing us to connect the physics of back-action with that of lasers. For this experiment, we used the PID Controller option to generate a correction voltage for stabilizing the mechanics.

How big is your group, and what other quantum-information-related efforts are ongoing in Oxford?

I lead a group of 3 master students, 7 PhD students and 4 postdocs. The University of Oxford is part of the Networked Quantum Information Technologies Hub, which has now entered its second phase. There are efforts on superconducting qubits, trapped ions, NV centers, and the theory of quantum algorithms and quantum architectures to cite a few.

What do you do when you don't work?

I used to do artistic skating, but a few years ago I took up ballet. I didn't do any classical dance as a child, so it is a real challenge! I also go back to Argentina every year to have 'mate' (a traditional drink similar to tea) with my family and friends.

Blog Post: Electrochemical impedance spectroscopy of tap water with the MFIA

Tap Water Measurement

Tap water is often taken for granted, but how can electrochemical impedance spectroscopy (EIS) ensure high water quality standards? In this blog post, Meng Li measures the EIS of tap water over a wide frequency range using the MFIA and a capacitive sensing probe. The conductivity of tap water is found to be 0.03 mS/m at an optimized measurement frequency of 1.4 kHz. The gradual uptake of CO₂ in the water causes a shift in the resistive impedance; the subsequent addition of salt (NaCl) grains to the water sample induces a step change in the impedance. This post shows that the MFIA is ideally suited to the EIS study of electrolytes. EIS can also be used in microfluidics and to characterize supercapacitors or batteries.

Read the full post by Meng Li

Interview: Dr. George Nelson, RIT

Dr. George Nelson, RIT

Dr. George Nelson is a postdoctoral fellow at the Rochester Institute of Technology (RIT). His work focusses on III-V solar cells for the satellite industry.

Hi George, can you introduce yourself and tell us about your research?

I am a postdoctoral fellow at RIT working under Prof. Seth Hubbard at NanoPower Research Labs. I completed my PhD in 2019 within the same group, and my postdoc is a continuation of my PhD research. Our group specializes in III-V solar cells for the satellite industry. A significant aspect of designing cells for space has to do with the effects of the space environment on cell performance. Over the course of a satellite's mission, high-energy particles continually bombard the cell's crystal structure and displace atoms, and the cell's power output degrades as these lattice defects accumulate. The particular defects that drive the performance loss are of interest to us, and a technique that I frequently use to study these defects is deep level transient spectroscopy (DLTS).

What is the principle of DLTS, and what are its potential applications?

DLTS is a non-destructive technique used to detect certain crystalline defects in semiconductor devices and characterize electronic properties of those defects such as the energy level within the bandgap and their concentration. Where applicable, it is a powerful tool to identify both well-known and never-seen-before defects present in a semiconductor material. Conventionally, it requires a device where an internal electric field can be modulated by an applied bias, such as p-n junction or Schottky diodes. The defects are typically small and numerous, with densities of at least 10⁸ cm^-3 and usually higher; they must also be electrically active.

Perhaps the most well-known historical DLTS results are those for gold-contaminated silicon or for the donor-complex in n-type AlGaAs, where DLTS helped explain the poor performance of devices made from these materials. In 2019, a group claimed that their DLTS results explain the cause of light-induced degradation in silicon solar cells, a problem that has vexed the industry for four decades.

What is the role of the Zurich Instruments MFIA Impedance Analyzer in your DLTS system?

Our DLTS system consists of a temperature controller, one of a variety of cryostats designed specifically for DLTS, a PC or laptop, and the MFIA. The MFIA replaces three of the components found in a traditional DLTS system, as it acts primarily as the capacitance meter but is also the pulse generator and the data acquisition system. It's a very economical system.

The MFIA allows for fine tuning of parameters (such as modulation frequency and amplitude) that are generally fixed in other meters. This is useful because there are many edge cases in DLTS where one-size-fits-all parameters are not ideal. Another aspect that proved useful is the small size of the unit. Because it handles so many responsibilities, our DLTS system with a laptop is surprisingly compact and portable, which helps when we need to take it to particle accelerator facilities with limited space.

Our older commercial DLTS system was driven by dozens of physical knobs and switches, and it was easy to make mistakes. It also required someone to be present to start or stop experiments. With our new system and the MFIA, everything is controlled by my own MATLAB^® software; experiments can be run remotely or queued up. Writing my own software to control the MFIA was easy thanks to its documented API. By now, my efficiency must have improved by an order of magnitude over our older commercial DLTS system in terms of the amount of useful data I can collect over time.

What motivated you to upgrade your DLTS system?

I learned how to perform DLTS on an older commercial system. The hardware was completely analog, and the transient processing took place in this analog hardware. That greatly limited the type of analysis I could perform, because to make any changes to the signal processing I had to modify the circuitry. With the MFIA, the transient data is digitized: I can process the decay components within the software. I am free to perform any type of processing or fitting that I wish, and I continually update my software with new techniques.

Can you tell us a little more about the software you wrote to control your DLTS system?

At first, I was intimidated by the idea of writing my own DLTS software suite. Once I committed to it though, I found it to be a lot less difficult than expected. I already understood the physics and many of the practical considerations such as wiring. Coding for the MFIA was straightforward thanks to its documented API and example scripts. Something that was invaluable was the command log on the LabOne^® Web Server, which told me the code-equivalent of whatever I clicked on in the LabOne user interface allowing me to quickly translate LabOne interactions into my own software. As far as I'm aware, my code is the most complete open-source implementation of DLTS software available. It is presently a collection of MATLAB^® scripts that acquire and process capacitance transients. Unofficially, it also has functionality for impedance or admittance spectroscopy. I'm doing my best with documentation and how-to guides to make it more user-friendly, but DLTS is complicated. I'm about to release v1.0, and my plans for v2.0 are to move everything to Python and to improve the user interface. I hope this code is useful to the DLTS community, and perhaps I will receive feedback that will benefit my own experiments too.

You have developed state-of-the-art solar cells: what role can they play in reducing our carbon footprint?

III-V solar cells are indisputably the most efficient, and they can be made with much smaller mass and greater mechanical flexibility than silicon cells. One of my favorite aspects of III-V cells is that they can be designed to absorb high-energy visible and UV light while reflecting infrared light, thus preventing unnecessary heating. One could imagine these lightweight, highly efficient cells built into cars, planes, or buildings. Unfortunately, III-V cells cost ten to a hundred times more than silicon cells that perform almost as well. This led to a crash of the III-V terrestrial market; right now the satellite industry is the only one willing to pay for the extra performance. The cost problem is mostly due to the substrates and could be eliminated if someone found a way to make great virtual substrates. Many groups are working on this aspect, including ours.

What are your interests outside of the lab?

When I don't spend family time with my wife and son, I go to the gym and lift weights, run, or play tennis. I'm a weekend handyman and like fixing things such as old electronics, cars, and houses. I'm also turning into a history buff, especially the history of science and philosophy.

Zurich Instruments Student Travel Grants 2020

Travel Grants 2020 Header

Every new scientific advance made by our customers gives us an extra boost in motivation, and we are passionate to celebrate and support the scientific community. For the sixth year in a row, we are happy to announce the Zurich Instruments Student Travel Grants. As in previous years, the prize allows three young researchers to attend a scientific conference.

The ground rules are simple: are you a PhD student or a postdoctoral researcher? Did you publish a paper mentioning one of Zurich Instruments' products? If so, apply by 30 June 2020. For more details, click here.

Zurich Instruments SPM User Meeting 2020

User Meeting Header

The 4th edition of our SPM User Meeting is approaching. Hosted in France at the Bibliothèque Marie Curie of INSA Lyon, this 2020 event is an opportunity to broaden your knowledge in the field of scanning probe microscopy – with a focus on the measurement of electrical modes at the nanoscale – and expand the community of Zurich Instruments super-users.

Join us to exchange ideas and learn more about our products. Follow this link for additional information and register today! Registration closes on 1 April.

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Recent publications featuring the HDAWG and the MFLI

Rol, M.A. et al. Time-domain characterization and correction of on-chip distortion of control pulses in a quantum processor, Appl. Phys. Lett. 116, 054001 (2020).
Mart, C. et al. Piezoelectric response of polycrystalline silicon-doped hafnium oxide thin films determined by rapid temperature changes, Adv. Electron. Mater. 1901015 (2020) – DOI: 10.1002/aelm.201901015 (Early View).

MFLI and HDAWG