Q-Roundup: Diraq’s War Chest, DARPA’s Bet on Topological Qubits, Citi/Classiq Explore Optimization, WEF’s Quantum Blueprint

By John Russell

February 13, 2024

Yesterday, Australian start-up Diraq added $15 million to its war chest (now $120 million) to build a fault tolerant computer based on quantum dots. Last week DARPA’s grant to Azure quantum was a vote of confidence in mysterious topological qubits, while AWS reported joint work with Citi Innovation Labs and Classiq to better understand optimization (think financial portfolios). Late last month the World Economic Forum (WEF) released the Quantum Economy Blueprint.

The WEF, best known for its annual Davos Conference, has an optimistic vision for the potential of quantum information sciences writ large. Here’s the report foreword from Jeremy Jurgens, managing director, WEF:

“Unlocking the promise of quantum technologies and strengthening the efforts in developing real-world quantum applications requires close public-private collaboration in research and development and scaling globally. The Forum’s Quantum Economy Network aims to encourage global collaboration and the sharing of knowledge, increasing the awareness of the potential of the technology and building readiness to mitigate cybersecurity risks. The Forum is committed to working with the ecosystem to advance the responsible innovation and commercialization of quantum technology.”

 “Quantum Economy Blueprint provides a roadmap to build quantum ecosystems in an equitable manner to prevent a widening gap in quantum capabilities and access to quantum hardware and infrastructure, enabling the transition to the quantum economy. Each nation or region may adopt the various building blocks of the blueprint in a modular and phased manner, irrespective of which quantum technology they are involved in, based on the maturity level of their quantum strategy. We hope this blueprint will serve as a valuable starting point to self-assess, participate and harness the benefits of the quantum economy for a better future for humanity.”

Getting from the here to there will be challenging but as the chart below shows, the world is rushing in to carve out pieces of the quantum landscape. (More at the end of this article, link to full WEF blueprint.)

The quantum news flood keeps growing. Let’s start with Dirac’s latest fundraising.

Diraq’s Path to Fault Tolerance

Diraq’s latest funding round – led by Quantonation which touts itself as “the world’s first venture capital fund dedicated to quantum technologies” – will be used to continue development of its quantum dot technology. Its qubits are quantum dots manufactured using CMOS – they are small (~50 nm) and potentially offer tremendous scalability advantages, and possible energy consumption and cooling efficiency. A con is the quantum dots’ small size means they are sensitive to any manufacturing variability.

Part of what’s interesting here is that Australia-based Diraq is one of a growing number of quantum hardware developers that are publicly eschewing NISQ (noisy intermediate scale quantum) claims and setting their sights on full fault tolerant quantum computing (FTQC). Intel, which is using a similar approach, has long said the road to FTQC will be long as has photonics-based QC developer PsiQuantum.

In the official announcement, Diraq’s U.S.-based chairman, William Jeffrey, a former director of the U.S. National Institute of Standards and Technology (NIST) said, “This funding round shows international recognition of our capabilities and potential impact. There is a key advantage to our technology which is based on modified transistors – the same components that are integral to our daily lives. As one of the few global companies pursuing the goal of achieving millions of qubits on a single chip, we can leverage over 50 years and trillions of dollars of investment in the semiconductor industry.”

Diraq emphasizes that existing CMOS manufacturing technology currently allows well over one billion transistors to be packed onto a single silicon chip. Diraq’s patented CMOS qubits are the same size as today’s transistors and use the same manufacturing, according to the company.

“Over the next ten years our Diraq chips will progress from prototypes to working silicon quantum processor chips at nanometer scales that other quantum bit technologies will never achieve,” reports the company, which was founded in 2022 and is located in Sydney, AUS.

Citi Innovation Labs uses Classiq Tools to Test QAOA

Looking for improved quantum-based optimization tools, a Citi Innovation Labs project with Classiq and run on AWS, explored the Quantum Approximate Optimization Algorithm (QAOA) for portfolio optimization – “investigating how adjustments to the algorithm’s penalty factor (when introducing constraints to the problem) impacted the algorithm’s performance.”

If the QAOA algorithm ultimately proves to have a comparative advantage over classical methods the fine-tuning strategies discussed in this exploration could pave the way for improved results in portfolio optimization and potentially other complex financial challenges that Citi faces. AWS has posted a blog describing the work.

“We started by collecting historical stock price data for several assets, including Apple, Walmart, Tesla, GE, Amazon, and Deutsche Bank using the Yahoo Finance API (yfinance). Using this data, we calculate the expected returns and the covariance matrix, setting the stage for optimized portfolio construction,” write the researchers[i].

QAOA is a hybrid algorithm, which means it combines both classical and quantum computation. The algorithm searches through all potential solutions using a mixer layer (which shuffles between alternative solutions) and a cost layer (which favors good ones). The circuit parameters are fine-tuned classically in an iterative manner, converging toward their optimal values with each run of QAOA.

One of QAOA’s strength’s is its flexible and can solve optimization problems with many constraints. “There are two main options for incorporating constraints into the algorithm. The first is by modifying the mixer layer to only include valid solutions, thus limiting the optimization search space. The second option is to modify the cost layer (indicated in Figure 1 by HC) by adding a penalty factor to the function we are trying to optimize so that invalid solutions are penalized and are less likely to be picked,” they wrote.

“We investigate the second option because it produces considerably shallower circuits with fewer gates than the first, making it more relevant to near-term noisy quantum computers. As a result, we want to know how to implement a penalty factor that will increase the likelihood of selecting an optimal portfolio of assets.”

The Citi researchers used Classiq Software Development Kit (SDK), which they reported allows users to model quantum algorithms without having to navigate the low-level details like qubit assignment and quantum logic operations, “significantly simplifying the process of designing and applying quantum algorithms to solve complex problems.” The blog includes portions of the code used.

“We analyzed the impact on the probability of finding valid solutions when making small changes to the penalty factor while executing both the inequality and equality constraints’ QAOA circuits. Our first focus was to sample a valid solution that satisfies the constraints for the inequality and equality constraints as explained earlier. In the graphs that follow, we see the probability of obtaining such a solution” they write.

“Without any penalty, the graphs show zero probability for both constraints. However, as the penalty is increased, we notice a variation in behavior between the types of constraints. For the inequality constraint, the probability consistently grows with the penalty factor. In contrast, for the equality constraint, there’s a discernible peak or optimal penalty value. Beyond this peak, as we increase the penalty, the likelihood of getting a valid solution diminishes.”

The researcher next sampled the top 1% of all possible valid solutions.

Bottom line: “We discovered that the quality of the results is sensitive to the magnitude of the penalty factor, which has a great impact on the quality of the algorithm. For both types of constraints, the probability to find the best 1% of valid solutions peaks when the penalty is relatively small, while increasing the penalty beyond a certain value reduces the probability of getting a good solution.

“We want to highlight that fine-tuning the penalty factor is just one facet of the broader challenge. Near-term quantum algorithms are usually heuristic in nature. This means they demand considerable experimentation, involving trial and error, to optimize various parameters and settings. This iterative process is crucial to harnessing the full potential of quantum computing in NISQ devices.”

The blog is best read in full.

DARPA Holds Pat on Microsoft/Azure’s Marjorana Bet

The Microsoft/Azure Quantum effort to build a quantum computer based on topological qubits got a boost last week from DARPA’s Underexplored Systems for Utility-Scale Quantum Computing (US2QC) program, “which seeks to determine whether an underexplored approach to quantum computing can achieve utility-scale operation – meaning its computational value exceeds its cost – faster than conventional predictions.”

DARPA awarded Azure a US2QC contract though the details were not disclosed.

Writing in Forbes, analyst Paul Smith-Goodson of Moor Insights & Strategy, noted “DARPA is sponsoring the US2QC program to explore new ways to scale qubit count for larger systems, create additional layers of entanglement connectivity for faster performance and develop a broader set of quantum error correction algorithms for fault tolerance. Specifically, DARPA wants to determine if relatively new quantum technologies such as neutral atom, topological and photonics can be leveraged to develop a fault-tolerant quantum computer within ten years. Although the amount of funding wasn’t specified, I expect it will be enough to significantly move the needle for the corporate teams involved, given the program’s five-year span and DARPA’s $4.1 billion 2023 budget.”

Other companies selected for US2QC include (Forbes excerpt):

  • Atom Computing — Atom is based in Berkeley, California and has an advanced research facility in Boulder, Colorado. In October 2021, Atom unveiled a gate-based 100-qubit quantum computer called Phoenix, which uses an optical array platform based on strontium neutral atom spin qubits. These qubits have an exceptionally long coherence time of about 40 seconds. A second-generation machine with more qubits, higher fidelity and advanced features is expected to be announced soon.
  • PsiQuantum — Based in Palo Alto, California, the company is developing a single photon-based quantum computer. Rather than developing intermediate qubit-sized processors, for its first release PsiQuantum is planning on a million-qubit processor. It is using Global Foundries for fabrication of its CMOS silicon processor.

The Azure effort has long been pursuing a fault tolerant system strategy which depends on the much-debated Marjorana particles, whose existence is frequently challenged. That said the topological states associated with Marjorana and any qubit system based upon it would be inherently more resistant to error and disruption. By way of background, here’s an excerpt from a 2022 Microsoft blog written by Chetan Nayak, Technical Fellow and Distinguished Engineer, Microsoft Azure Quantum hardware team:

“Microsoft is taking a more challenging, but ultimately more promising approach to scaled quantum computing with topological qubits that are theorized to be inherently more stable than qubits produced with existing methods without sacrificing size or speed. We have discovered that we can produce the topological superconducting phase and its concomitant Majorana zero modes, clearing a significant hurdle toward building a scaled quantum machine. The explanation of our work and methods below shows that the underlying physics behind a topological qubit are sound—the observation of a 30 μeV topological gap is a first in this work, and one that lays groundwork for the potential future of topological quantum computing. While engineering challenges remain, this discovery proves out a fundamental building block for our approach to a scaled quantum computer and puts Microsoft on the path to deliver a quantum machine in Azure that will help solve some of the world’s toughest problems.”

“A topological superconducting phase and its concomitant Majorana zero modes, clearing a significant hurdle toward building a scaled quantum machine. The explanation of our work and methods below shows that the underlying physics behind a topological qubit are sound—the observation of a 30 μeV topological gap is a first in this work, and one that lays groundwork for the potential future of topological quantum computing. While engineering challenges remain, this discovery proves out a fundamental building block for our approach to a scaled quantum computer and puts Microsoft on the path to deliver a quantum machine in Azure that will help solve some of the world’s toughest problems.”

The Azure effort has hit a few bumps along the way but evidence for the existence of Marjorana has been steadily building and Azure Quantum has been at the vanguard of engineering efforts to turn the concept into practical use. It’s noteworthy that others are also exploring topological qubits, including, for example the Quantum Science Center, based at Oak Ridge National Laboratory, one of five U.S. National QIS Research Centers.

In an Azure blog announcing the DARPA award, David Bohn, Microsoft hardware partner, wrote, “Microsoft expects that a computer built with topological qubits will scale to the level at which it can solve commercially significant problems far too complex for classical computers, such as those in chemistry and materials science. This ability to reach utility scale is possible because topological qubits can process information much faster than other types of qubits can. Furthermore, a topological quantum computer could control over one million physical qubits on a single chip, which is enough to perform extremely complex computations in a practical timeframe, yet the computer itself would be small enough to fit in a closet.”

Nayak is quoted saying, “We are looking forward to extending our collaboration with DARPA as we continue to make progress in the design and validation of a scalable quantum computer. Having successfully completed the first phase, which involved providing a detailed explanation of Microsoft Azure Quantum’s technology to DARPA, we will now focus our efforts on designing a prototype of a topological quantum computer.”

WEF Issues 2024 Quantum Economy Blueprint

Perhaps a tempering note is warranted as IBM and SandBoxAQ –  who both have horses in the quantum sweepstakes race – collaborated in creating the WEF report. In their forewords they say:

  • Joseph Broz, VP, Quantum Growth and Market Development, IBM, noted, “As of December 2023, 24 countries have some form of national initiative or strategy to support quantum technology development. Many of these governments explicitly acknowledge a need to guide the ethical, social, legal and economic implications of quantum technologies, including the impact on cybersecurity and the global financial system, blunt the potential for monopolization or militarization by certain countries or multinationals, and promote the active discussion of data privacy and equity.”
  • Jack Hidary, CEO, SandboxAQ, wrote, “It will take an orchestrated, global initiative to ensure that the benefits of AI and quantum technology are distributed equitably among nations to avoid the growing quantum divide. The World Economic Forum’s vision for and approach to the democratization and globalization of quantum technologies will have a broad and long-lasting impact on the future of society.”

It is a grand vision. Market development is rarely orderly and it will be interesting to see how international guidelines around quantum information systems (computers, sensors, etc.) emerge.

WEF says the report is designed to be relevant irrespective of the stage of one’s regional or national quantum strategy: “Each country may adopt the building blocks in a modular manner, irrespective of which quantum technology they are involved in, based on the maturity level of their quantum strategy or quantum activities.”

The following five phases are differentiated:

  • Discovery: The country is in the discovery phase, with early quantum activity either in academia or industry.
  • Initial strategic considerations: Policy-makers and industry leaders are reflecting on a national or regional quantum strategy, but there is no structured responsibility yet.
  • Initial priorities defined: Policy-makers have defined the initial quantum priorities, and responsibilities have been allocated across ministries, federal departments or industry.
  • Strategy defined: There is a defined national or regional strategy that includes a funding plan but no implementation plan.
  • Strategy and implementation plan: This is the final stage where strategy, funding and the implementation plan are defined, detailed and in the process of execution.

Link to Dirac announcement, https://www.hpcwire.com/off-the-wire/diraq-secures-15m-in-series-a-2-funding-to-advance-fault-tolerant-quantum-computing-development/

Link to AWS, Citi, Classiq blog, https://aws.amazon.com/blogs/quantum-computing/citi-and-classiq-advance-quantum-solutions-for-portfolio-optimization/

Link to Azure blog, https://cloudblogs.microsoft.com/quantum/2024/02/08/darpa-selects-microsoft-to-continue-the-development-of-a-utility-scale-quantum-computer/

Link to World Economic Forum report, https://www.weforum.org/publications/quantum-economy-blueprint/

[i] AWS blog written by Yoram Avidan, Iftach Yakar, and Zachar Borsutsky from Citi, Adam Goldfeld and Tamuz Danzig from Classiq, and Perminder Singh from AWS

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