By Amrita Manzari, QSI Head of AI & Quantum Machine Learning
The world of subatomic particles is weird and, at its heart, lies the bizarre world of quantum mechanics. Remembering the memorable words of Richard Feynman, “Nature isn’t classical, dammit, and if you want to make a simulation of nature, you’d better make it quantum mechanical”, but simulating a quantum system and trying to extract the utility out of that model has not been easy. However, the advances in the past decade in isolating, manipulating, and detecting quantum systems has impacted not just science but engineering as well. The curiosity to find utilization out of an actual quantum System has led to the rise of a new domain, namely quantum engineering.
Quantum engineering is a deeply integrated subject that holds tremendous potential, possibly revolutionizing all aspects of science, technology, and business. Originating from the intersection of interdisciplinary areas like quantum physics, computer science, electronics, electrical engineering, materials science, along with social and soft skills, this new discipline is a difficult subject in terms of implementation and communication to the layperson.
The emergence of quantum engineering requires exposure to many overlapping disciplines. As a computer engineering graduate with a passion to pursue quantum while employed as a software engineer, I always had the following question in my mind. Can a software engineer or a business professional transition to quantum engineering? Fortunately, the answer I discovered was “Yes”.
Over the past month, I spent a great deal of time talking to industry experts about what that transition looks like for typical software and machine learning engineers into the quantum computing (QC) world. One of the experts I spoke to was Paul Lipman, President of Quantum Computing at ColdQuanta, which develops cold atom technology that is used in a broad spectrum of quantum applications. “It is the same as how traditional software engineers, do not have to think about gates like ‘AND Gate’ and ‘OR Gate’ or the structure of the CPU, the same occurs with quantum. If you think about today’s quantum computing, you know you could write a circuit based on a gate program for a 5-qubits, 10 qubits QC, but you are not going to do that for 100 qubit or as much as 1000 qubit QC. There is this kind of abstraction layer that will abstract you from underlying physics, so that engineering is much focused towards algorithm, workflows, which is not there yet but it’s completely critical to make full blown thought of the computing landscape”, says Paul.
Quantum engineers may or may not require a background in quantum science depending upon the area of engineering we focus on. But for software engineers, bringing the quantum engineering mindset to project execution and development of enterprise programs is important. “As the layers of abstraction increases, and we are agreed upon the standards in community, it’s going to make less and less necessary for engineers to know what quantum Hamiltonian, unitary transformations, superposition, and entanglement concepts is, because the functionalities are quite tough to understand and it’s going to be packaged and you know software modules and application layer that are easier to plug and play into existing application” argues Denny Dahl, Director of Quantum Applications at Cold Quanta. “I think that will evolve over time, but right now it’s still necessary to have a pretty good understanding of those basic concepts.”
What does it take to become a successful Quantum Engineer?
The important aspect for a person who is new to quantum physics or a mathematics background is to develop intuition for key quantum computing concepts and how that intuition can be leveraged with engineering skills.
The wheel graphic below illustrates the primary skills that are required in the areas of educational background, technical background, business, and soft skills:
Image Source: Quantum Strategy Institute, 2021 based on ARTIBA AI Wheel
The role of Quantum Engineer is a complex one, involving deep education, technical, business, and soft skills. The following describes each area in more detail.
STEM – Any discipline within Science, Technology, Engineering, Mathematics, Computer Science, and Information technology. Masters and PhD. in Science is preferred, however Bachelor’s in Engineering with Computer Science or Electronics is a requirement.
Quantum Mechanics/Physics/ Chemistry – Quantum mechanics is a desired skillset. Quantum mechanics is the fundamental theory of physics that provides the description of nature at atomic and subatomic level. Quantum computing leverages the underlying complex laws of quantum mechanics like entanglement, superposition, teleportation etc.
- Quantum Engineers do not require PhD, however a strong grasp of programming languages like Python, R and Quantum SDKs like Qiskit (IBM), Pennylane (Xanadu), Cirq (Google), and/or TensorFlow (Google) is important.
- Primarily Classical Computing Languages such as Python, C, C++ is required and is supported by SDKs like Qiskit and Cirq for programming.
- However, Quantum Programming Languages are broadly classified into:
- Imperative Quantum Programming Language
- Functional Quantum Programming Language
- Multi-Paradigm Languages
Refer to image below for detailed visualization:
Image Source: Quantum Strategy Institute, 2021 based on ARTIBA AI Wheel
Quantum Software Development Kits are required to run Quantum Circuits on Simulators or prototype Quantum Devices.
The below figure illustrates Quantum Software Development Kits from different organizations:
Image Source: Quantum Strategy Institute, 2021
Mathematical Concepts Linear Algebra, Complex Numbers and Probability Theory is a desired skillset.
Quantum Information and Computation including Quantum Algorithms, Quantum Communication, Quantum Cryptography, and Information Processing is applicable in all the areas of quantum technology like Ion Traps, Cavity QED, NMR, photonics quantum computers and solid-state systems. QIC covers all the concepts from Quantum Mechanics to Physical realizations and Quantum Information Theory.
Noisy Intermediate-Scale Quantum (NISQ) marks the ‘NISQ’ era of Quantum Computing with 50- 100 qubits able to perform complex operations and surpass the capabilities of classical computing. Quantum engineers and quantum hardware manufacturers strive for the implementation of more accurate and less-noisy fault- tolerant quantum systems.
Artificial Intelligence and Machine learning plays a significant role in building hybrid environments of classical and quantum computing algorithms. The evolving quantum technology requires more AI Engineers transforming themselves into Quantum Engineers to build and implement Enterprise AI-Quantum Strategy.
The Below figure illustrates the difference between AI and Quantum Engineer Skillset in terms of educational background, technical skills, and business skills:
Source: Quantum Strategy Institute, 2021 based on ARTIBA AI Wheel (image on the right).
Quantum Engineers must be able to convince others of the benefits and alignment with organizational goals of their solutions.
- Communication: Strong communication skills both written and verbal
- Collaboration: Ability to work with diverse team of Engineers, scientists, and Business stakeholders.
- Analytical and Logical Thinking
- Research Papers: Contribution to research papers and experience working in R&D environment
- Contribution to Scientific Community: Transforming from a Software Engineer to Quantum Engineer requires active communication, collaboration, contribution to communities (such as GitHub, Qiskit Community etc.), and publishing and reviewing research papers.
Soft skills are an abstract skillset that is critical for an individual and an organization to evolve and grow. The ability and motivation to learn, to be curious to discover, to be determined, to have growth mindset, to be able to work in a team, to be able to express and communicate, are major factors for transitioning to successful Quantum Engineering.
Networking is a key factor; you need to know people who can point you to the right people.
Quantum Engineering is intense form of science, and there is no substitute for learning. There are tremendous number of resources available on the internet today in comparison to what it was 5 years back and its increasing. The Quantum Strategy Institute (https://quantumstrategyinstitute.com) is one of those sources.
A very important lesson that I understood is focusing and learning, as it has no substitute, and having connection with maybe a small group of brilliant people who can help in getting what is a real fit to your quantum journey.
The power of nature has always been there, but only a pioneer mindset can unfold those mysteries.
I hope this helps you on your journey to become a quantum engineer.
The Quantum Strategy Institute’s purpose is to demystify quantum technology and encourage the development of a pragmatic quantum mindset within the global business community, sharing practical applications and offering strategies for its successful adoption.
Amrita Manzari is Head of Artificial Intelligence and Quantum Machine Learning at the Quantum Strategy Institute. She is also Associate Manager Software Engineering at United Health Group and a Quantum Enthusiast. Amrita is based in India.
A special mention to the Cold Quanta Group:
- Paul Lipman, President, Quantum Computing Cold Quanta
- Denny Dahl, Director of Quantum Applications at Cold Quanta
- Josh Cherek, Product Manager at Cold Quanta
Copyright 2021 Amrita Manzari