Withstanding Scrutiny
Top Challenges, Willow & Industry Observers
If you’re a quantum technology vendor these days, your team needs not only to be creative but resilient to scrutiny, looking for the gems in the criticisms of industry observers. SpaceX is an example of a company that lives publicly from its very visible failures taking each new piece of data to become a better manufacturer of rocketry.
So when a quantum vendor issues a new release or stated ‘breakthrough’, like that of Google’s Willow, the industry is now, in 2024, at a place where there are a group of highly informed individuals who sift though the announcements for hype versus reality. And often the lens is not merely speed or reliability but practical application. Can the technology work in the relatively world on pressing problems, and can they do it ‘better’ than classical systems?
Image source: Brian Lenahan/Midjourney
The Current Challenges
First, what challenges are we talking about overcoming?
Quantum technology, which leverages quantum mechanics for applications in computing, communication, sensing, and more, faces several complex challenges.
1. Quantum Decoherence
Problem: Quantum systems lose coherence quickly due to interactions with their environment, causing errors in computations or data loss in communication.
Impact: This limits the ability to maintain quantum states for long enough to perform useful computations or secure communications.
Current Efforts: Development of error-correcting codes and noise-resistant quantum materials.
2. Error Correction and Fault Tolerance
Problem: Quantum systems are inherently error-prone due to noise, imperfections in hardware, and quantum uncertainty.
Impact: Building reliable quantum computers requires a massive overhead of physical qubits to create a single logical qubit.
Current Efforts: Researchers are designing advanced error-correcting codes like surface codes and improving qubit fidelity.
3. Scalability of Quantum Systems
Problem: Scaling from small, proof-of-concept systems to large, fault-tolerant quantum computers is immensely challenging.
Impact: Ensuring reliable connectivity and integration between increasing numbers of qubits without significant error rates is a critical bottleneck.
Current Efforts: Exploring modular and distributed quantum architectures, as well as improving fabrication techniques.
4. Material Limitations
Problem: Current materials used for quantum technologies (e.g., superconductors, trapped ions) have limitations in performance and scalability.
Impact: Material imperfections can lead to reduced qubit coherence times and higher error rates.
Current Efforts: Developing novel materials like topological insulators or investigating alternative qubit platforms, such as photonic or silicon-based qubits.
5. Control and Measurement Precision
Problem: Precisely controlling and measuring qubits without disturbing their quantum states is technically difficult.
Impact: Errors in control and readout processes can degrade computation accuracy.
Current Efforts: Refining pulse control techniques, improving single-shot readout accuracy, and developing high-precision instruments.
6. Cryogenic and Energy Requirements
Problem: Many quantum systems require extremely low temperatures (milliKelvin range) to operate, which is energy-intensive and expensive.
Impact: Limits the practicality and scalability of quantum technologies for widespread use.
Current Efforts: Exploring room-temperature quantum platforms like nitrogen-vacancy centers in diamonds or photonic qubits.
7. Quantum Algorithm Development
Problem: Designing algorithms that provide a clear advantage over classical counterparts is difficult and not well-understood for many practical problems.
Impact: Without powerful algorithms, the utility of quantum computers remains limited to niche problems like factoring (Shor’s algorithm) or search (Grover’s algorithm).
Current Efforts: Research into hybrid quantum-classical algorithms, optimization techniques, and new areas of quantum advantage.
8. Integration with Classical Systems
Problem: Quantum systems must interface with classical systems for input/output processing and error correction, creating additional complexity.
Impact: The speed mismatch between quantum and classical components can bottleneck overall performance.
Current Efforts: Developing faster classical controllers and co-optimization frameworks for hybrid systems.
9. Secure Quantum Communication
Problem: Quantum communication relies on entanglement and quantum key distribution, which are challenging to implement over long distances due to signal loss and noise.
Impact: Limits the feasibility of global-scale quantum networks or secure communication.
Current Efforts: Deploying quantum repeaters and exploring satellite-based quantum communication.
10. Standardization and Benchmarking
Problem: There is a lack of standardized methods for comparing quantum hardware, software, and performance metrics.
Impact: Makes it difficult to assess progress and identify the most promising approaches.
Current Efforts: Establishing benchmarks like quantum volume and researching cross-platform comparison tools.
11. Economic and Workforce Challenges
Problem: Quantum research and development require significant investment and a skilled workforce, both of which are currently limited.
Impact: Slows the pace of innovation and commercialization.
Current Efforts: Governments and companies are investing in quantum education, training, and funding initiatives.
12. Ethical and Security Concerns
Problem: Potential misuse of quantum technologies (e.g., breaking current encryption standards) and lack of ethical frameworks for their use.
Impact: Creates societal risks and challenges for secure digital infrastructure.
Current Efforts: Developing post-quantum cryptography and engaging in policy discussions on responsible quantum use.
Recent Example - Google Willow
Given the foregoing list of challenges, is every new quantum solution expected to address all the challenges? That would ‘expecting’ too much. Yet when announcements are made it’s difficult for many readers to understand the breadth and depth of the solution in relation to this list.
Fortunately, after many years of announcements, the industry has engendered quantum voices who leverage their academic and practical experience to make objective assessments, each of which should be taken as additional research for quantum consumers.
Case in point: Google stock soared 4% one day after its ‘Willow’ quantum chip announcement:
According to one report “The Willow quantum chip represents a revolutionary step forward, promising to solve problems that even the world’s most advanced supercomputers would take trillions of years to complete. Specifically, Google claims Willow can tackle computations in just five minutes that would otherwise require an incomprehensible ten septillion years—a timeframe so vast it boggles the imagination. This feat is made possible by Willow’s advanced quantum architecture, which boasts 1,000 qubits capable of processing multiple states simultaneously, far surpassing traditional binary computing.”
So as a business person, I look at such a report and ask how is ‘Willow’ practical? And which challenges does it address? So I look to objectives industry observers for thoughts I can then assess on my own.
CNBC’s Arjun Khapal took a look at the announcement and said “Google claims quantum computing milestone — but the tech can’t solve real-world problems yet”.
Observer Sreekuttan L S. Co-founder and CEO at Bloq argues:
New quantum chip is not faster than classical supercomputers for every task!
It performs a very niche problem called Random Circuit Sampling faster than classical. RCS benchmark is specifically a quantum task and has no real world application yet. That is to sample from the probability distributions generated by randomly constructed quantum circuits. Even though this is an important step in the right direction, emphasising too much on the septillion claim would only create unnecessary hype. What I'm really excited about is the error correction capabilities and the scalability of it. - Sreekuttan L S
Others like Jack Krupansky, long time industry monitor, says:
“Here's the latest in quantum computing from Google Quantum AI - the latest in Quantum Smoke and Mirrors. Sure, they have some improvements, some advances, a healthy improvement over Sycamore, but nothing truly useful …
They focus a lot of attention on error correction - but nothing that you can use for practical applications, yet. And they double down on random circuit sampling (cross-entropy benchmarking), possibly the most useless benchmarking metric yet invented for quantum computing. Again, more Quantum Smoke and Mirrors.” - Jack Krupansky
Again the purpose of this substack is to draw out various perspectives for my Quantum’s Business readers given the complexity and nascency of the quantum industry. Drawing attention to many industry observers provides insights in short order for decision makers to help their assessments. Consider other experienced authors, as well, like David Shaw, Olivier Ezratty and Jaime Gomez Garcia when thinking about the value of a new breakthrough in quantum technologies.
Do Your Research
As always, my message is do your research. Quantum vendors have a responsibility to be able to address scrutiny. The Google Willow solution could be exactly what your team has been looking for. Alternatively, it could be a step towards your own objectives. Doing your own research will inform your team’s opinion and augment your potential success towards adopting quantum technologies.
Brian Lenahan is founder and chair of the Quantum Strategy Institute, author of seven Amazon published books on quantum technologies and artificial intelligence. Brian’s focus on the practical side of technology ensures you will get the guidance and inspiration you need to gain value from quantum now and into the future. Brian does not purport to be an expert in each field or subfield for which he provides science communication.
Brian’s books are available on Amazon. Quantum Strategy for Business course is available on the QURECA platform.
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