Quantum.Tech 2022: Next Generation Insights of Technology Innovations
The Quantum International Conference
- Quantum.Tech 2022, in-person (Boston, MA, USA).
- Players in the Industry focusing on quantum computing, quantum communication, and quantum sensing.
- Early use-cases in Quantum Computing, Quantum Sensing, and Quantum Communication (US-based companies: Government agencies, Private sectors).
- There are only a handful innovative quantum startups for investors to select from, expects to have more in coming years.
- NISQ-era, Noisy Intermediate Scale Quantum. FTQC-era, Fault Tolerant Quantum Computer, quantum hardware, quantum development software, quantum development framework.
- Post Quantum Cryptography (PQC), Quantum Key Distribution (QKD), HNDL/SNDL (Harvest/Store Now, Decrypt Later) attack, GPS-free PNT (Positioning, Navigation, and Timing).
Quantum.Tech is back in June 2022!. The annual Quantum Conference was held in 2022 in Boston, Massachusets, USA. This hybrid event was in-person and virtual and took place in early summer in nice sunny, not-so-windy weather averaging 70F (21C). Again, attendees were able to meet the global quantum communities since the in-person event had resumed in 2021 following zoom-only (fully online) in 2020.
Ever since WHO declared Covid-19 a pandemic in March 2020, it has impacted many aspects of most people and industries worldwide, including regular International events such as Quantum.Tech.
After doing events digitally during a few years of the COVID-19 pandemic, Quantum.Tech was back for an in-person event in the heart of Boston — Marriot Copley Place hotel, on June 14–15 2022.
IBM Quantum and ClassicQ were present as the Platinum Sponsors, while Quantinuum and Zapata as the Founding Sponsors. Gold Sponsors included known players in these emerging technologies: AgnostiQ, Atom Computing, AWS, DWave, and Quantropi.
Thanks to the advancements in technologies enabling the availability of COVID-19 vaccines within less than a year. Governments could start deploying vaccines to their people worldwide in early 2021. The expectation has been to achieve herd immunity in the shortest possible time, thus significantly slowing down the spreading of the virus.
While most Governments started to ease the regulations for following strict health protocols, some are still advising people to follow mask-wearing (especially indoors), including practicing social distancing (getting less and less as more business activities get back to normal) and regularly washing hands.
Initially, Quantum.Tech 2022 accepted only WHO-approved Covid-19 vaccinated participants (either fully approved or approved for emergency use authorization by World Health Organization). However, a couple of weeks before the event started, the requirement for mask-wearing had been lifted in the city of Boston. There was also no need for attendees to present proof of COVID-19 vaccination as per the city regulation before. However, if they chose to do so, attendees were free to wear masks. Hand sanitizers were also provided at various locations during the event.
About 400 attendees were registered for the in-person event in the Marriot Copley hotel in Boston. Slightly down from 2021 which was attended by 500 people. Quantum.Tech attempted to start conducting the event in 2018 with just one attendee and increased to 300 attendees in 2019.
Highlights of Quantum.Tech 2022
Quantum technology covers diverse areas such as quantum sensing, quantum communication, and quantum computing. Quantum communication like QKD (Quantum Key Distribution) is seen as the more mature area (TRL 7 — Technical Readiness Level) for many potential implementations compared to quantum sensing and quantum computing. Quantum Computing is at TRL 3.
A few notable key insights for some early adopters of quantum technology in USA government agencies are discussed below.
Early use cases in Government agencies mostly focus on quantum sensing and communication. Quantum communication includes quantum cryptography.
- Department of Homeland Security (DHS) is looking for use cases in quantum sensing e.g. for TSA (Transportation and Security Administration).
- Quantum in Defense (e.g. Department of Defense, DoD) focuses on PNT (Position, Navigation, Timing) in the sensor, computing, and communication area.
- National Aeronautics and Space Administration (NASA) mostly looks for use cases around free-space quantum communication.
- National Science Foundation (NSF) starts to facilitate the transition from Quantum Information Science (QIS) to implementable practical early use cases.
- Airforce Research Laboratory (ARFL) is looking for use cases that leverage distributed quantum entanglement.
As more quantum hardware and simulation tools are increasingly available, although not yet enough for practical applied “useful” applications:
- Fortune-500 companies are trying to identify potential use cases.
- Now, quite many quantum providers are professionally providing access to quantum Infrastructure, even if it’s still in research facilities.
- Invest early in “potential quantum business cases”, and dynamically rearrange priorities as technologies mature.
- To better adopt any new technology such as quantum, we need to ensure that it can fit in and improve the Enterprise workflow. If not, the technology can not be useful for businesses (does not contribute to the bottom line).
The following lists some of the early adopters of quantum technology in the private sector.
- Airbus, which has delivered 14,000 aircraft so far, is focusing on quantum sensing, searching for an alternative to dependency on GPS for PNT. Including quantum secure connectivity and quantum computational fluid dynamics (Quantum CFD) for aircraft design. GPS-free PNT is expected to have many potential applications in many areas enabled by quantum communication.
- BP (British Petroleum) is exploring many areas of potential quantum application by having a separate R&D group focusing on quantum and developing several partnerships with external parties.
- Wells Fargo discusses HNDL (Harvest Now Decrypt Later) or SNDL (Store Now Decrypt Later). The potential for an attacker to attack data at rest or data in motion by storing (or ‘stealing’) the data now, then decrypting later (many years later) when the capable quantum computer is available. Wells Fargo prefers to be “quantum-resistance rather than quantum-safe” or more difficult to hack than the competitors rather than hackproof. The reason is “we don’t know what we don’t know.” The future has so many good or bad potentials that are unknown at the present time before millions of qubits of the actual quantum computer are available. Target quantum resilience on cyber security, get a free demo from solution providers whenever possible, and expect quantum error correction to be improved soon.
- Boeing — Explores new technologies like quantum within the approved budget and real outcomes within three years to get more funding for future research. Looking more into quantum sensing. Standardization for interfacing is very important. Actively invests in multiple emerging technologies. Deploy and reallocate more budget for projects that potentially lead to maximum ROI.
- Mastercard — focuses on quantum cryptography, mitigating future risks of quantum attacks in the future. Actively searching for potential risks in the future. The main challenge is more on utilizing big data.
SandboxAQ (a spinoff of Google’s parent company: Alphabet) develops products and services to assist customers in assessing and developing a migration plan to Post Quantum Cryptography (PQC), considering SNDL. SanboxAQ also develops products in quantum sensing as well as simulation and optimization.
An interesting approach shared by a startup: Bleximo, developing an application-specific full-stack quantum solution in coordination with UC Berkeley. The hardware and software will be custom developed (grouped by problem category) based on the type of problems to solve. Bleximo is developing the tools to build the custom full-stack quantum solution.
Qureca, a startup in quantum education provides a range of quantum resources and professional services for both individuals and businesses (Qureca, 2022). As quantum technology is still in the early stage of industrialization, there are more needs for Ph.D. and Postdoc in quantum mechanics for advanced state-of-the-art research. However, as technology evolves, more multidisciplinary resources with bachelor's, master's, and Ph.D. degrees will be needed as we develop more applicable uses-cases for industries.
A panel discussion on “International, global use cases” covered various topics such as:
- The need for standardization in quantum computing, sensing, and cryptography.
- Innovation should be based on the “right benchmark” and bring diverse multi-disciplinary people, not just quantum scientists.
- It is important that end-users can see the potential as they are the influencer to adopt new tech such as quantum technology.
- International collaboration is important to move things forward faster and reduce duplicating work or research.
“We are still in NISQ-era (Noisy Intermediate Scale Quantum), at least for some more years,” a conclusion stated in the closing remark by a group of panelists on the readiness of enterprises to welcome the 1,000 noisy qubits for quantum computing in the near future. Some more years could be towards sometime around the year 2030.
A few more closing remarks:
- Hybrid classical-quantum will be more in practical applications rather than mostly or purely quantum computing. Quantum computing will be part of the business process.
- Business Executives do not care about quantum computing or anything quantum. It is similar to what’s happened with AI. They care “what the new technology can do for my business.” If the technologists can not articulate the benefit of new technologies such as quantum (quantum computing, quantum sensing, or quantum communication), it will have many challenges to get board approval (e.g. for funding).
- For enterprises that do not have or not planning to have quantum expertise in the near future, it would be best to develop partnerships with startups or technology vendors for example to get early awareness of the development of quantum technology and do initial explorations in searching for potential use-cases.
- Talent for quantum computing experts is scarce (especially at the Ph.D. level). It would be tough to find resources to implement a novel idea e.g. for innovative startups. venture capital (VC) is playing an important role here. Seed investment range typically between USD 150K to 5M. The investments to startups that are more than USD 5M fall into the category of growth investment. Good timing to market is also an important metric to consider for both the investor and founder.
- From the VC’s point of view (seed investor), having the patient for such a long time (10 years or so before being ready to IPO) is really challenging i.e. regretting the initial investment by doing an early exit due to not seeing the potentially much larger ROI in the longer future.
For most of us who are not physicists by formal education, it is really challenging to explore and learn about quantum — whether quantum computing, quantum sensing, or quantum communication. It is expected that quantum technology will eventually come to be implemented in practical applications to solve some of the world’s most challenging problems that are tough to solve within a reasonable time, even with the most sophisticated classical supercomputers.
Becoming exposed to and having an early hands-on practical experience in emerging technologies such as quantum computing would be invaluable in being relevant in the future.
In addition to understanding fundamental quantum computing concepts like superposition, entanglement, and interference, having a good awareness of the availability of related hardware and software stacks from different providers would be invaluable.
We typically access the quantum computer in the cloud from a classical computer, such as laptops or smartphones. Quantum Computing as a Service (QCaaS) is the cloud-accessible Quantum Computing service. Thus, the term Hybrid Classical-Quantum Computing.
IBM quantum experience as QCaaS can be accessed from the cloud since May 2016. When announced, the IBM quantum experience platform was still based on QASM, the Quantum Assembly language. The higher-level quantum library, Qiskit, was developed based on Python programming language.
Most if not all, existing quantum services (quantum computing, quantum communication) from various providers nowadays are accessible through the cloud as QCaaS to some extent. Be it full-stack (hardware, software, applications, and services) or just a certain part of the stack. In addition to IBM (IBM Qiskit), there are Amazon Braket, D-Wave, Zapata Computing, Google cirq, Honeywell quantum, Quantropi QiSpace, QCWare Forge, ColdQuanta, Pasqal, QuEra, agnostic, Quantinuum, Atom Computing, Terra Quantum, and many more.
On the hardware side, scalable quantum computers’ construction towards thousands and millions of qubits is still in active research either in Universities or Industries. We expect to see innovations and substantial advancements with the racing for a million qubits towards 2030. We are now in the “Early Industrial Era for Quantum Computing, NISQ” according to Prof. John Preskill, an American theoretical physicist and the Richard P. Feynman Professor of Theoretical Physics at the California Institute of Technology.
In NISQ-era — IBM, with its 1,000+ logical qubits plan, expects that 2023 could be the inflection point for having practical applications of quantum computing. And plan to scale to 10,000–100,000 qubits beyond 2026. Google, Xanadu, IonQ, and a few others have also been racing towards FTQC. The big challenge now is that a logical qubit needs to be built from many physical qubits to be fault-tolerant. As many as 1,000 physical qubits are needed to build one logical qubit.
One of the two most adopted approaches in developing quantum computer hardware is the gate-based model being pursued by IBM, Google, Honeywell, and Intel. Another method is an analog-based approach, like the one implemented by D-Wave with its quantum annealer model.
The quantum gate model expresses problems in a series of quantum gates. In quantum annealing, the user expressed the problem as an optimization problem. The quantum annealer computer then seeks to find the best solution.
As of mid-2022, Qiskit, the IBM quantum development framework, has supported other hardware service providers: IonQ and Azure Quantum.
IBM, Google, Alibaba, and Intel have been experimenting with Superconducting qubits, aiming to build universal quantum computers in the near future. Likewise, Xanadu with Photonic qubits.
D-Wave with its latest achievement of 5000+ qubits (D-Wave 5th generation, Advantage quantum computer) has been continuously focusing on the quantum annealer approach, targeting specific areas around optimization and simulation problems. Recently, D-Wave also developed gate-based quantum computers (D-Wave, 2021).
AWS does not have quantum computer hardware yet. As of June 2022, AWS has partnered with several quantum computer providers such as D-Wave, IonQ, Rigetti, OQC, Xanadu, and QuEra.
In collaboration with QuTech, Intel has created the first qubits for another promising modality: the Spin qubit (Intel, 2022).
By relying on topological quantum qubits, Microsoft has not shown any significant results so far in the last 15 years. Recent news (Matt Swayne, 2021) could be a huge setback for Microsoft (or an opportunity for a new challenge?) as the underlying quantum hardware technology that it depends on may not be visible for practical implementation.
As we are now in the era of Noisy Intermediate-Scale Quantum (NISQ), we do expect to see Fault-Tolerant-Quantum Computer (FTQC) closed by the year 2035 (Antonio Manzalini, 2020).
In the future, there may be a time when a material science breakthrough will enable the creation of a high-fidelity logical qubit without much effort to build it from hundreds of physical qubits, compensating for quantum error correction. When that time comes, the business impact of creating millions of logical qubits may accelerate many developments in commercial applications.
Quantum Software and Development Frameworks
A software development framework encapsulates many lower-level hardware details so we can focus on the higher-level problems to solve. Some startups are building software frameworks to work with any underlying hardware when they become available in the future. Zapata Computing for quantum workflow (Orquestra) and Xanadu for quantum artificial intelligence (Pennylane.ai).
Qiskit Open Source by IBM consists of rich quantum libraries for building various quantum applications. Including Qiskit aqua which provides higher-level quantum libraries to enable developers to focus more on building vertical applications, capitalizing on the underlying quantum hardware platform.
The framework for Quantum Machine Learning or QML, like the one provided by Xanadu’s Pennylane.ai, combines Artificial Intelligence with Quantum Computer capability for developing a Hybrid Classical-Quantum Deep Learning model. See an example of image classification using quantum transfer learning (Andi Sama, 2020).
Another framework by Zapata Computing called Orquestra provides an orchestrated integrated workflow to work in a hybrid classical-quantum environment.
Algorithms and Tools
Generic tools to master include programming languages such as Python and C++. Programming languages are indispensable in working with quantum algorithms such as the two famous Grover’s and Shor’s algorithms. Grover’s quantum algorithm is used for searching unsorted data with quadratic speedup. Shor’s quantum algorithm is used for factoring large prime numbers with polynomial speedup.
More inventions of novel quantum algorithms with polynomial or exponential speedup would be something we may see in the coming years.
The commercialization of quantum use cases can be broadly categorized into three areas (Andi Sama, 2021b): Machine Learning, Simulation, and Optimization.
Machine Learning creates models to predict the outcome, given sufficient historical data. Quantum Machine Learning comes in the form of a generic neural network model trained on the ImageNet dataset for example and is used as the base for Transfer Learning on the Image Classification task (based on ResNet18). This pre-trained model’s last layer is modified by quantum means through a quantum machine learning framework such as Pennylane.ai.
Quantum chemistry simulation that performs quantum simulation on finding the right catalyst (that does not require high temperature) for chemical reactions can significantly improve new material discovery in material science (Cem Dilmegani, 2021). Likewise, molecular biology and healthcare research (e.g., drug-discovery) include a process similar to chemistry research. In this case, quantum simulations can replace laboratory experiments.
Optimization aims to minimize or maximize a given objective function, given constraints. This can minimize travel distance in a logistic network or maximize capacity and system throughput to avoid conflicts and backlogs.
The commercial application potentials of quantum computers.
Quantum Chemistry (e.g., for drug discovery) stays in the first rank in the survey, followed by Security (TheQuantumDaily, 2020). A Quantum Internet, for example, relies mostly on Quantum Security.
In addition to quantum computing applications, other potential use cases like quantum sensing (e.g., for medical imaging and GPS-free navigation starting in 2025) and quantum communication (e.g., quantum internet towards 2035).
- Alpha Events, 2022, “Quantum.Tech: Driving Quantum Adoption Across Global Enterprise” June, Boston, MA, USA.
- AWS, 2022, “Amazon Braket Quantum Computing Service.”
- Andi Sama, 2022, “My First 2022 Business Travel in Covid-19 Pandemic — Is it worth it?.”
- Andi Sama, 2021a, “Embarking on a Journey to Quantum Computing — Without Physics Degree.”
- Andi Sama, 2021b, “Quantum Computing, Challenges & Opportunities.”
- Andi Sama, 2020, “Hello Tomorrow — I am a Hybrid QML.”
- Antonio Manzalini, 2020, “The Second Quantum Revolution is underway.”
- Cem Dilmegani, 2021, “Top 20+ Quantum Computing Applications / Use Cases in 2021.”
- D-Wave, 2021, “A Practical Approach to Quantum Computing.”
- Elijah Pelofske, Andreas Bärtschi, Stephan Eidenbenz, 2022, “Quantum Volume in Practice: What Users Can Expect from NISQ Devices,” March, Cornell University.
- IBM, 2022, “IBM Unveils New Roadmap to Practical Quantum Computing Era; Plans to Deliver 4,000+ Qubit System,” May.
- Intel, 2022, “Intel and QuTech Collaborate to Produce Silicon Qubits at Scale,” April.
- Matt Swayne, 2021, “Paper Backing Microsoft’s Quantum Technology to be Retracted, Quantum Hardware Field Narrows.”
- Qureca, 2022, “Quantum Resources & Professional Services” https://qureca.com/
- TheQuantumDaily, 2020, “The Quantum Technology Survey,” September 2020.
- Zapata, 2022, “Build and deploy quantum-ready applications® on Orquestra.”