Quantum Computing - skill creation is a key factor. Report of informal conversations with students and professors

Introduction

We are at a tipping point in the evolution of information technology.

We will summarize below some aspects that happened to discuss in a recent informal meeting with some freshmen of an important European University about the skills needed to face Quantum Computer rapid expansion in research and industry.

Quantum mechanics is making continuous progress in understanding the potential of the world around us and the link with advances in technology makes the evolution an interesting ride throughout vast unexplored spaces from both a scientific and technological point of view.

Quantum mechanics fascinates, a world still with a lot to discover, that every day reveals wonders that in the coming decades will radically change not only the understanding of the world around us but also the way of living and communicating in everyday life. An invitation to those who love the physics and mathematical aspects not to be intimidated by the initial abstruseness, once inside, it reserves exciting surprises.

For example, already in traditional computer architecture, future transistors will exploit techniques learned from quantum mechanics; Purdue University researchers recently achieved a breakthrough in the design of next-generation transistors, which could allow for an extension of the life of silicon-based semiconductors. The new design (Cascade Field Effect Transistor - CasFET ) is a further step on the road to miniaturization. It allows for lower switching voltages and lower power consumption. Large multinationals companies already have CasFEt in their plans. (Fig 1)

Fig 1 CasFET design as shared by Purdue University. The Superlattice layers are the new design breakthrough that could improve transistor miniaturization.?(Image credit: Purdue University)

Therefore basic competence in quantum mechanics remains a starting point for understanding the future of hardware in IT, independently from Quantum computing.

For the computational aspect it should be remembered that Quantum computing was first thought of by Richard Feynman when he stated that by using the effects of quantum mechanics, it is possible to obtain an exponentially faster computation.

Instead of miniaturizing, the paradigm is changed. We try to exploit the conditions of atomic particles to characterize every single state with a greater amount of information.

With the transistor system at each "clock" rate, the state of a unitary entity, the bit, can only be either 0 or 1 (binary system).

Without going into a detailed description now, the advantage of Quantum Computing is to exploit two typical conditions of quantum physics, "entanglement" and "superposition". These phenomena make it possible to use quantum particles and define with a single state a vast variety of information that is equivalent to more or less long series of "traditional bits". If with a microprocessor with N bits I can represent 2 * N states (linear trend) at each clock beat, with N "qubits" (the basic entity of the Quantum Computer) the possibilities are 2 raised to N, exponentially increasing power and speed also for extremely complex calculations, effectively reducing processing times from years for a traditional computer to minutes for a quantum computer.

What are the research and development areas around the quantum computer?

We can divide the areas of development into the areas of hardware, system software, applications, and consequently the ancillary services. (Fig 2)

A big role will be played by the technology for the creation of computational units (qubits) on which the major universities are continuously developing new projects in connection with hardware manufacturers. At the moment, different development strategies are in the roadmap, we are not yet in a standardised phase.

Specific skills will be needed on the basic technology of the quantum computer and in the techniques of access and control to the “core” together with error correction and simulation techniques.

Disconnected from the basic level are then all the activities for evaluating the convenience of using the quantum computer and the development of related applications and services.

Fig 2 summarizes the scenarios in which it will be necessary to create specific skills in the IT world in a harmonized way to minimize the reaction of skills shortages (Image Credit ORSi Consilium Ltd)

Hardware

The structure of quantum computers splits into two large families at the moment. Quantum Computers based on superconductor processors such as those of IBM (Hummingbird successor to Falcon), UST of China (Zuchongzhi) and Google (Sycamore), which require a working environment of practically 0oK and a more recent family of processors based on “silicon photonic chips” that can work at temperatures closer to ambient such as those used by Xanadu and PSIQuantum.

Using superconductor based qubits, from the millions of transistors emitting zeros and ones, the core of the quantum computer contains a few qubits, increasing though rapidly. (IBM recently announced to use 65 (named Hummingbird) and UST of China 66 (on Zuchongzhi in August 2021)

Qubits are made of the element niobium or equivalent and pressed into a silicon chip, the material that ordinary computer chips are made of.

In superconducting quantum computers, separating two niobium electrodes with a thin layer of aluminum oxide creates a so-called Josephson contact, through which an overlap typical of quantum mechanics can occur. A Josephson contact is only possible if the material is superconducting, which means it has no electrical resistance.

This is the biggest challenge to overcome when developing quantum computers since the properties of quantum mechanics only occur at the atomic level, the slightest disturbance in the calculations is enough to render them ineffective. Even an atom of air or light particle can cause vulnerable qubits to deviate, causing them to lose the superposition.

That's why the quantum chip in the labs of IBM, UST, and Google sits at the bottom of a freezer in a large cabinet with gold and copper components, which cool the chip down to near absolute zero of -273.15 oC. This construction is called a cryostat and is the only thing that allows researchers to perform calculations on a quantum chip.

This also explains why quantum computers have not contained more qubits until now. The more qubits they have, the harder it is to keep them overlapping for the time needed for detection because the risk of electrical interference from the outside increases exponentially with the number of qubits. Furthermore, it must be considered that the detection itself changes the state

Fig 3 The structure of a Quantum Computer (Image credit IBM Corporation)

The Xanadu Silicon Photonic quantum qubits, on the other hand, work at room temperature and use a completely different approach to create the "superposition" and "entanglement" necessary for the computation. The optical inputs to be processed are handled by "squeezers", microdevices that create "resonance rings" that generate "squeezed states". It is in fact the creation of a superposition of photons. Downstream an interferometer is created, which acts as the programming input of the "core", creating the condition of entanglement in a sequence of quantum "gates". (Fig 4) At the end of the operation, the gates are ready for readout. The reading is done by a photonic detector that Xanadu calls the “transition edge sensor”. It checks the photons present at each output, creating a data matrix that is reported to the user in the form of statistics.

Fig 4 The overall structure of a Xanadu qubit (image credit Xanadu inc)

From what has been very briefly summarized so far the research space on Quantum Mechanics for computational utilisation is very wide. Many of the European universities are developing important studies in the field of materials and techniques for detecting quantum effects in cooperation with private institutes. China and the USA are making huge investments in the research and application of quantum mechanics in the computational and communications fields. In Europe, the so-called Quantum Flagship, one of the largest and most ambitious research initiatives in the European Union, was launched in 2018. With a budget of at least € 1 billion and a 10-year lifespan, the lighthouse brings together research institutes, universities, industry, business and policymakers, in a joint and collaborative initiative on an unprecedented scale. From a specific skills point of view, the UK, Denmark, France, Germany, Sweden and Italy have recently seen a lot of progress. There is also close collaboration between university researchers and system engineers, software developers and consultants from commercial companies.

The next steps

In a recent study McKinsey confirms that for any emerging technology, the concentration of assets and investments around it says a lot about its maturity and what lies ahead. The vast majority of investments in quantum computing to date, over 80%, are in the hardware or its components, which are needed to unlock the opportunity. The next phase will focus more on software and applications. This area is currently receiving interest from startups, but not at the same level of broad hardware support.

The technical path to bring quantum computing to the market is still not fully defined, although the statement by the CEO of IBM is in recent days that foresees a rapid expansion of the use of quantum computers over the current decade

In fact, several large technology companies and start-ups have set the goal of creating a quantum computer functional for industrial and commercial applications in the coming years. As early as July 2020, Google established a road map to arrive at an error-corrected quantum computer by end of the decade. At the same time, the Chinese group proposed a very similar road map as did IBM.

Fig 5 IBM's roadmap for scaling quantum technology (Image credit IBM Corporation)

Although there are already solutions to overcome the two key obstacles to the production of an industrial quantum computer: the scalability and reliability (noise reduction) of qubits, there is much room for improvement.

Scalability refers to the challenge of producing interconnected qubits in large quantities. The way to the solution is standardization, which does not yet exist, which favours the industrialization of the production of quantum computers. This area is all to be defined at an international level.

Reliability, or noise reduction, has been a challenge since the beginning of quantum computing because quantum states must remain entangled long enough for them to be detected and the quantum computer to function reliably. Error correction methods are an important area of study with various possible solutions.

Among the key skills, apart from the evident knowledge of Quantum mechanics and microelectronics competencies, we should highlight the electronic measurement techniques, in an environment where the measurement can modify the qubit status itself, and complex statistical modelling, considering that the work involves atomic particles.

The lack of expertise globally should be emphasized which can be an inhibitor of rapid progress. Truly competent people are disputed between research centres, start-ups and large companies. It is necessary to define a plan for creating skills in the various areas.

The Software

The power of Quantum computing requires a dedicated software management approach on two levels: the development of software and technology to make the most of quantum computers (access and control of the quantum system and development of appropriate simulators, calculation and correction of intrinsic errors etc, what are generally called quantum circuits) (see fig 2) and the development of software and services that allow the best exploitation of the potential for research or commercial applications (quantum programming).

In the first level, programming languages at the "quantum machine" level are essential for translating ideas into instructions that can be executed. They are crucial for large-scale programming and can facilitate the identification of algorithms even before there is hardware capable of executing them. Quantum programming languages are used to control existing physical devices, estimate the costs of running quantum algorithms on future devices, teach quantum computing concepts, or verify quantum algorithms and their implementations. They are used by newbies and experienced professionals, researchers and developers. This variety of purposes and target audience is reflected in the design and ecosystem of existing quantum programming languages, depending on what factors a language takes priority.

Over a period of just under a year, the algorithms reduced the number of iterations two to ten times to receive a confirmed final answer. At the system software level, the improved processor performance reduced the number of repetitive cycles required by each iteration of the algorithm by 10 times. The control systems, with better reading and error recovery performance of qubits. they reduced the amount of time to run the job (that is, running each batch of a few dozen circuits) from 1,000 microseconds to 70 microseconds. In this area, algorithms are based on stochastic processes and some concepts of linear algebra.

IBM then, for example, improved times with the introduction of Qiskit Runtime, a containerized service for quantum computers. Instead of accumulating latencies as code passes between a user's device and the cloud-based quantum computer, developers can run their program in the Qiskit Runtime execution environment, where the IBM hybrid cloud handles the work for them. New software architectures and OpenShift operators allow us to maximize the time spent on processing and minimize waiting time.

Algorithms and applications that use quantum-mechanical resources can thus be written in a simple and efficient way. A quantum circuit is a computational routine consisting of coherent quantum operations on quantum data, such as those contained in qubits, and simultaneous classical computations in real-time. In the following figure, each horizontal line or wire in a circuit represents a qubit, with the left end of the wire representing the initial quantum data and the right the final quantum data generated by the quantum circuit calculation. Operations on qubits can be placed on these wires and are represented by boxes.

Fig 6 IBM Qiskit state teleportation circuit revisited

Without going into too much detail in figure 6, it can be guessed that quantum circuits allow a quantum computer to acquire classical information and produce a classical solution, using quantum principles such as interference and entanglement to perform the computation.

The quantum gates in figure 6 represent primitive operations on the data. They are reversible transformations that preserve information about the data stored in the qubits. (In the case in the figure there are 3 qubits) These "unitary" transformations are the core of the operations of a quantum circuit.

The field of quantum languages and compilers is still in an early stage and current research and implementation efforts are focused on optimizing circuits at the "machine level" by focusing on the "quantum hardware" (quantum circuits) rather than on optimizations that act on the entire program structure.

The emulation and acceleration of a similar progression to that followed by conventional computing over the past 50 years require a collaborative effort between the different disciplines to take full advantage of the knowledge that is acquired at an almost daily rate.

This represents an exciting area of study and development for those with an interest in the semantics of languages and their use. In addition to the already illustrated Qskit we can include the Q # of Microsoft, SILQ of the ETH of Zurich and others.

Computational availability

Starting from 2016, IBM has made available the possibility of using Quantum computing through Cloud services. Still free, if for learning purposes,

On the same path to make available its quantum computational capacity through QCaaS (Quantum Computing as a Service) we find Xanadu, Google, Rigetti, the European OQC, DiWave.

Microsoft's Azure and AWS have instead opted to activate partner networks to be made available to users.

Fig 7 Microsoft azure networking to provide Quantum Computing via Azure (Image Credit Microsoft Corporation)

Amazon has a similar approach through the Amazon Braket linking to IonQ, Rigetti and D-Wave.

This makes a big difference with the other great computer revolutions of the past, just think how only 30 years ago it was very difficult for a student or even a researcher in the computational field to have access to a university computer, an option for a few.

The relative ease of access to quantum computers creates the opportunity to develop software applications for research or commercial needs in a reasonable soon, in the meantime, the hardware technology stabilised and standardise.

This represents the second major area of study for students, perhaps less attracted to the aspects of quantum physics, if not at an informative level.

Applications

Until now, we have mainly focused on executing quantum circuits, or sequences of quantum operations.

However, the real applications of Quantum Computing require in the vast majority of cases the support of classical processing as well. The term quantum program describes this combination of quantum circuits and classical processing. Some quantum programs have thousands or even millions of interactions between quantum and classical. Therefore, it is essential to build systems that natively accelerate the execution of quantum programs and not just quantum circuits. Systems built to run quantum programs must have significantly greater effective capabilities and require improvements across the stack, including cloud service design, system software, control hardware, and even quantum hardware.

All this paves the way for research and development for applications such as Cybersecurity, Drug Development, Financial Modeling, Better Batteries, Cleaner Fertilization, Traffic Optimization, Weather Forecasting and Climate Change, Artificial Intelligence and so on.

The programming languages that are appearing are all evolutions of Python, a popular programming language that emphasizes code readability with its use of significant indentation. And assure code readability.

In the area of application development, the quantum development roadmap envisions a quantum future that doesn't require learning a new language and running code separately on a new device. Here following in Fig 8 the IBM roadmap for a complete ecosystem, linked to the hardware roadmap already presented in Fig 5

Fig 8 IBM’s roadmap for building an open quantum software ecosystem (Image credit IBM Corporation)

Other major companies already mentioned above have all similar roadmap for the next years, for the sake of the discussion is important just that they exist. Comparison among the different strategies will be part of a different article.

On this application/service layer the Quantum Computing competencies should cope with industry knowledge, basics of data analysis, cryptography, artificial intelligence development and so on, all applied to a specific industry environment, expanding exponentially the need for new expertise

We need to rethink the skill development

In the chats with students and professors, we arrived at the conclusion that fundamental changes will be needed in education, supply chains, and national policies to create a balanced presence of researchers and professionals in condition to govern appropriately the Quantum Computing evolution.

Probably it is worth preparing people to think about computation in a different way,

We have just mentioned that the major centres of research, multinationals and also start ups are building qubits with different modalities and technology. The main issue is to build fault-tolerant machines that can run super-fast calculations exploiting qubit behaviour and correcting errors introduced from the environment. Specific education on those aspects is required. Several researchers are deeply involved already but the areas of investigation are vast.

Starting now, education needs to improve for involved people to take advantage of the quantum processing breakthroughs as the hardware journey matures. Problem solving and algorithms may be very different in areas like finance, science, and logistic.

At the moment the language of quantum algorithms is based on probabilities and some concepts of linear algebra. This area of education is not very popular in secondary schools and may influence the educational path for students in colleges and inside the companies. Also, Quantum mechanics still remains in a very limited circle of expertise, when instead its application is probably going to change several aspects of our life, for sure IT and communications systems.

Education entities and also governments will need to rethink how to drive it being quantum computing becoming rapidly a matter of national interest and therefore inducing a public need that goes behind the pure commercial interest of the IT companies and start-ups.

The European Quantum Flagship has the goal to facilitate collaboration and bridge a gap between educators, developers, and scientists involved in algorithms and developing hardware, but that should be received in a harmonised way by the public institutions in the countries, otherwise the progress toward a harmonised creation of the necessary skills stalls.

For that reason, several companies are fostering skill development with free initiatives like contests (IBM) and certifications (IBM and Microsoft), and free available education paths (practically all).

Summary

Quantum computing represents a new paradigm in computation and will probably radically change the IT environment during the current decade. In the open discussions reported above, we have analysed several different aspects and types of skills needed. Colleges and Universities have the challenge to prepare the next generation of researchers and professionals to sustain the need for skills. That should be part of a harmonised plan at the European and countries levels to facilitate collaboration and bridge a gap between educators, developers, and scientists. ?

The author

Roberto Magnani

Sr Consultant, for decades in the IT industry always managing and leading teams on projects on the leading-edge technology of the moment. Sharing above the results of conversations with students and professors regarding the skill needed for a balanced evolution of Quantum computing linkedin.com/in/robertomagnani

References

1. Wan-Su Bao,4 Sirui Cao,1 et altri. “Strong quantum computational advantage using a superconducting quantum processor”. Different Science Institutes of China?
2. Jay Gambetta, “IBM’s road map for scaling quantum technology,” IBM, September 15, 2020, ibm.com.
3. Keith Kirkpatrick and Clint Wheelock, “Tractica report: Quantum computing for enterprise markets,” ITPro Today, November 26, 2018, itprotoday.com; McKinsey research.
4. Francesco Bova, Avi Goldfarb, Roger Melko?“Quantum Computing Is Coming. What Can It Do”.?Hardware Business Review July 2021
5. Vigliar, C., Paesani, S., Ding, Y. et al. Error-protected qubits in a silicon photonic chip. Nat. Phys. (2021). https://doi.org/10.1038/s41567-021-01333-w
6. R. Magnani "ll “Quantum Computing” un’occasione anche per l’Italia" https://www.dhirubhai.net/pulse/ll-quantum-computing-unoccasione-anche-per-litalia-roberto-magnani/?June 2021
7. Steve Martin, Tillmann Kubis “Purdue technology for downscaling transistors could advance semiconductor design”. https://www.purdue.edu/newsroom/releases/2021/Q3/purdue-technology-for-downscaling-transistors-could-advance-semiconductor-design.html
8. Heim, B., Soeken, M., Marshall, S. et al. Quantum programming languages. Nat Rev Phys 2, 709–722 (2020). https://doi.org/10.1038/s42254-020-00245-7
9. IBM Quantum Experience; https://quantum-computing.ibm.com/
10. Qiskit documentation; https://qiskit.org/documentation/
11. Microsoft Quantum Documentation; https://docs.microsoft.com/quantum
12. Amazon Quantum Documentation; https://aws.amazon.com/blogs/aws/amazon-braket-get-started-with-quantum-computing/
13. J. M. Arrazola et al. Quantum circuits with many photons on a programmable nanophotonic chip, Nature (2021). DOI: 10.1038/s41586-021-03202-1
14. Anthony Escalona “Comparison of IBM and Xanadu Quantum Computing Simulators Using Quantum Teleportation Code”. Seidenberg School of CSIS, Pace University, Pleasantville, New York 10570
15. Feynman, R. 1982. Simulating physics with computers. Int. J. Theor. Phys. 21: 467.?
16. Shor, P.W. (1994). "Algorithms for quantum computation: discrete logarithms and factoring". Proceedings 35th Annual Symposium on Foundations of Computer Science. IEEE Comput. Soc. Press: 124–134.
17. EU Commission, “Quantum Flagship”,?https://qt.eu?, accessed 2021
18. Elsevier Scopus ?, 2021 “ Quantum computing research trends report”?https://www.elsevier.com/solutions/scopus/who-uses/research-and-development/quantum-computing-report”?accessed June 2021
19. IDQ. 2018.?China’s growing investment in quantum computing. Accessed March 2021.
20. Morgan Stanley, 2021,?“Counterpoint Global Insights on Quantum Computing”?https://www.morganstanley.com/im/publication/insights/articles/article_quantumcomputing_a4.pdf, accessed March 2021
21. Martin-Lopez, E. et al. 2012. Experimental realization of Shor’s quantum factoring algorithm using qubit recycling. Nature Photonics 6: 773.
22. D-Wave Systems. 2017.?Temporal Defense Systems purchases the first D-Wave 2000Q quantum computer. Accessed February 2021.
23. Google AI Quantum and Collaborators. 2020. Hartree-Fock on a superconducting qubit quantum computer. Science 369: 1084.
24. W. Zhurek, Decoherence and the Transition from Quantum to Classical”Physics”;?https://doi.org/10.1063/1.881293, accessed May 2021
25. Alvarez-Rodriguez, U. et al. (2918) Quantum artificial life in an IBM quantum computer. Scientific Reports 8: 1479
26. Adrian Cho.?IBM promises 1000-qubit quantum computer—a milestone—by 2023, Science, Sep. 15, By Adrian ChoSep. 15, 2020.
27. ETSI White Paper No. 8?Quantum Safe Cryptography and Security An introduction, benefits, enablers and challenges?June 2015 ISBN No. 979-10-92620-03-0.
28. The word qubit coined in 1995 by B. Shumacher and W.K. Wooters,see?https://quantumfrontiers.com/2015/06/09/who-named-the-qubit/, accessed February 2021?
29. J. von Neumann, "Mathematische Grundlagen der Quantenmechanik", Springer‐Verlag, Berlin (1932)?