2022 Billington Cybersecurity Summit
Takeaways from an Important Discussion about the Future of Encryption
By Duncan Jones
In September, nearly 200 senior cybersecurity leaders from around the world convened to discuss the state of U.S. cybersecurity at the. Topics around cybersecurity were varied and included discussions about moral asymmetry of today’s global threat actors, lessons learned from Ukraine and general discussions around all things that “keep us up at night” concerning cyber threats.
As a speaker at the Summit, I wanted to take a moment to share my take-aways from an important discussion that took place during our breakout session, “Future of Encryption: Moving to a Quantum Resistant World.” My esteemed fellow panelists from NSA, NIST, CMU and AWS exchanged insights as to where U.S. government agencies stand in their preparation for current and future threats to encryption, the likely hurdles they face, and the resources that exist to assist in the transition. Those responsible for moving their agency to a quantum-resistant world should find the following insights worth considering.
Getting Out of The Starting Gate
With the prospect of powerful quantum computers breaking known encryption methods on the horizon and with federal mandate now in place, the good news is that quantum-proof encryption is finally being discussed. The not-so-good-news is that it isn’t clear to cybersecurity practitioners what they need to do first. Understanding the threat is not nearly as difficult as understanding the timing, which seems to have left agency personnel at the starting gate of a planning process fraught with challenges – and urgency.
Why is the timeline so difficult to establish? Because there is no way of knowing when a quantum-based attack will take place. The Quantum-safe Security Working Group of the Cloud Security Alliance (CSA) chose the date, April 14, 2030, to represent “Y2Q,” also known as “Q-Day” – the moment secure IT infrastructure becomes vulnerable to the threat of a fault-tolerant quantum computer running Shor’s algorithm. The Biden Administration based its implementation timeline on the day that NIST announced the four winning algorithms for standardization. Then there is the “hack now, decrypt later” timeline which suggests that quantum-related attacks may already be underway.
Regardless of the final timeline or potential drivers, one thing that was clear to the panel attendees was that they need to start the transition now.
The Need to ‘Future-Proof’
I get this question often and was not disappointed when one attendee asked, “How can I convince my agency leadership that migrating to quantum-proof encryption is a priority when they are still trying to tackle basic cyber threats?”
The panelists responded and agreed that the U.S. government’s data storage requirements are unique in that classification dates are typically 20 years. This means that systems in development today, that are typically fielded over the next 10 years, will actually have a storage shelf life of 30 years minimum. Those systems need to be “future-proofed” today, a term that should be effective when trying to convince agency leaders of the priority.
The need to future-proof is driven by a variety of scenarios, such as equipment and software upgrades. In general, it takes a long time (and perhaps even longer for government entities) to upgrade or change equipment, software, etc. It will take an extremely long time to update all of the software that has cryptography in place.
The panelists also agreed that given the extensive supply chain supporting federal systems, vendors are a critical component to the overall success of an agency’s future-proofing for the quantum age. In 10-15 years, there will be some government partner/vendor somewhere who will not have transitioned to quantum-proof encryption. For leaders who have not yet prioritized their agency’s cryptography migration, let them ponder that thought — and start to focus on the need to prepare.
Déjà Vu or Lessons Learned?
The panel shared several past technology migrations that were similar in their minds to the adoption of quantum computing.
Y2K was similar to the looming quantum threat by both the urgency and scale of the government’s need to migrate systems. However, without a deadline assigned to implementing the encryption migration, Y2K is really only similar in scale.
The panelists also recalled when every company had to hash function, but concluded that the amount of time, effort, and energy required to replace current encryption will be way more important than SHA-1 — and way more ubiquitous.
While previous technology migrations help to establish lessons learned for the government’s quantum-proof cryptography migration, the panel concluded that this go-round will have a very unique set of challenges — the likes of which organizations have never had to tackle before.
Where to Start
The consensus among panelists was that agencies need to first understand what data they have today and how vulnerable it is to attack. Data that is particularly sensitive, and vulnerable to the “hack-now, decrypt-later” attacks, should be prioritized above less sensitive data. For some organizations, this is a very challenging endeavor that they’ve never embarked upon before. Now is an opportune time to build inventory data and keep it up to date. From a planning and migration perspective, this is an agency’s chance to do it once and do it well.
It is important to assume from the start that the vast majority of organizations will need to migrate multiple times. Panelists emphasized the need for “crypto agility” that will enable future replacement of algorithms to be made easily. Crypto agility is about how easy it is to transition from one algorithm (or choice of parameters) to another. Organizations that prioritize long-term thinking should already be looking at this.
The panelists added that communicating with vendors early on in the planning process is vital. As one panelist explained, “A lot of our service providers, vendors, etc. will be flipping switches for us, but a lot won’t. Understanding what your priorities are for flipping the switch and communicating it to your vendors is important.”
Help Is on Its Way
Matt Scholl of NIST shared about the is doing to provide guidance, tips, and to answer questions such as what are discovery tools and how do I budget? The project, announced in July 2022, is working to develop white papers, playbooks, demonstrations, tools that can help other organizations implement their conversions to post-quantum cryptography. Other resources that offer good guidance, according to Scholl, include recent , DHS’and the .
One additional resource that has been extremely helpful for our CISO customers is ԹϺ’s The guide outlines what CISOs from any organization should be doing now and provides a basic transition roadmap to follow.
Conclusion
The discussion wrapped up with the acknowledgement that quantum has finally become part of the mainstream cybersecurity discussion and that the future benefit of quantum computing far outweighs the challenges of transitioning to new cryptography. As a parting thought, I emphasized the wonderful opportunity that agencies have to rethink how they do things and encouraged attendees to secure management commitment and funding for this much-needed modernization.
I want to give a special thanks to my fellow panelists for the engaging discussion: Margaret Salter, Director, Applied Cryptography, AWS, Dr. Mark Sherman, Director, Cybersecurity Foundations, CMU, Matthew Scholl, Chief of the Computer Security Division, ITL, NIST, and Dr. Adrian Stanger, Cybersecurity Directorate Senior Cryptographic Authority NSA.
About ԹϺ
ԹϺ,the world’s largest integrated quantum company, pioneers powerful quantum computers and advanced software solutions. ԹϺ’s technology drives breakthroughs in materials discovery, cybersecurity, and next-gen quantum AI. With over 500 employees, including 370+ scientists and engineers, ԹϺ leads the quantum computing revolution across continents.
Every year, APS Global Physics Summit brings together scientific community members from around the world across all disciplines of physics.
Join ԹϺ at this year’s conference, taking place in our backyard, Denver, Colorado, from March 15th – 20th, where we will showcase how our quantum hardware, software, and partnerships are helping define the next era of high-performance and quantum computing.
Find our team at booth #1020 and join our sessions below to discover how we’re advancing quantum technologies and building the bridge between HPC and quantum.
Monday, March 16th
Speaker: Andrew Potter
Time: 10:12 – 10:48 am
Speaker: Charles Baldwin
Time: 12:36 – 12:48 pm
High-Fidelity Quantum operations in the Helios Barium-Ion Processor
Speaker: Anthony Ransford
Time: 4:18 – 4:30 pm
Speaker: Jem Guhit
Time: 4:42 – 4:54 pm
Speaker: Enrico Rinaldi
Time: 5:54 – 6:30 pm
Tuesday, March 17th
Speaker: Caroline Figgatt
Time: 8:00 – 8:12 am
Speaker: Adam Reed
Time: 8:12 – 8:24 am
Speaker: Konstantinos Meichanetzidis
Time: 8:48 – 9:00 am
Speaker: Colin Kennedy
Time: 9:00 - 9:12 am
Speaker: David Stephen
Time: 9:12 - 9:24 am
Speaker: Matthew DeCross
Time: 9:36 - 9:48 am
Speaker: Leigh Norris
Time: 10:00 - 10:12 am
Speaker: Andrew Guo
Time: 12:00 - 12:12 pm
Speaker: Carlo Alberto Gaggioli
Time: 3:30 - 3:42 pm
Wednesday, March 18th
Speaker: Michael Foss-Feig
Time: 8:36 - 9:12 am
Speaker: Michelle Wynne Sze
Time: 9:24 - 9:36 am
Speaker: Juan Pedersen
Time: 9:48 - 10:00 am
Speaker: Noah Berthusen
Time: 12:48 - 1:00 pm
When is enough enough? Efficient estimation of quantum properties by stopping early
Speaker: Oliver Hart
Time: 12:48 - 1:00 pm
Speaker: John Campora
Time: 1:48 - 2:24 pm
Speaker: Eli Chertkov
Time: 4:42 - 4:54 pm
Thursday, March 19th
Speaker: Shival Dasu
Time: 8:00 - 8:36 am
Speaker: Ross Hutson
Time: 8:36 - 8:48 am
Speaker: Victor Colussi
Time: 10:00 am
Speaker: Maxwell Urmey
Time: 12:00 - 12:36 pm
Speaker: Matteo Puviani
Time: 5:54 - 6:06 pm
Friday, March 20th
Speaker: Reza Haghshenas
Time: 8:36 - 8:48 am
Speaker: Imran Bashir
Time: 10:36 - 10:48 am
Speaker: Fabian Finger
Time: 12:36 - 12:48 pm
Speaker: Elijah Durso-Sabina
Time: 12:48 - 1:00 pm
Speaker: Natalie Brown
Time: 1:12 - 1:48 pm
Speaker: Anthony Ransford
Time: 2:24 - 3:00 pm
*All times in MT
In our latest paper, we’ve taken a big step toward large scale fault-tolerant quantum computing, squeezing up to 94 error-detected qubits (and 48 error-corrected qubits) out of just 98 physical qubits, a low-fat encoding that cuts overhead to the bone. With 64 of our logical qubits, we were able to simulate quantum magnetism at a scale that can be exceedingly difficult for classical computers.
The "holy grail" of quantum computing is universal fault-tolerance: the ability to correct errors faster than they occur during any computation. To realize this, we aim to create “logical qubits,” which are groups of entangled physical qubits that share quantum information in a way that protects it. Better protection leads to lower “logical” error rate and greater ability to solve complex problems.
However, it’s never that easy. An unofficial law of physics is “there’s no such thing as a free lunch”. Creating high quality, low error-rate logical qubits often costs many physical qubits, thus reducing the size of calculations you can run, despite your new, lower-than-ever error rates.
With our , we are thrilled to announce that we have hit a key milestone on the ԹϺ roadmap: an ultra-efficient method for creating logical qubits, extracting a whopping 48 error-corrected and 64 error-detected logical qubits out of just 98 physical qubits. Our logical qubits boasted better than “break-even” fidelity, beating their physical counterparts with lower error rates on several different fronts. And still that isn’t the end of the story: we used our 64 error-detected logical qubits in a large-scale quantum magnetism simulation, laying the groundwork for future studies of exotic interactions in materials.
Stacking Wins
To get this world-leading result, we employed a neat trick: ‘nesting’ super efficient quantum error-detecting codes together to make a new, ultra-efficient error-correcting code. Dr. DeCross, a primary author on the paper, said this nesting is like “braiding together ropes made out of ropes made out of ropes”. Physicists call this ‘code concatenation’, and you can think of it as adding layers of protection on top of each other.
To begin, we took the now-famous ‘iceberg code’, a quantum error detection code that gives an almost 1:1 ratio of physical qubits to logical qubits. The iceberg code only detects errors, however, which means that instead of actually correcting errors it lets you throw out bits where errors were detected. To make a code that could both detect and correct errors, we concatenated two iceberg codes together, giving a code that can correct small errors while still boasting a world-record 2:1 physical:logical ratio (physicists call this a “high encoding rate”).
The team then benchmarked the logical qubits, checking large system-scale operations and comparing them to their physical counterparts. This introduces a crucial hurdle to clear: oftentimes, researchers end up with logical qubits that perform *worse* than their physical counterparts. It’s critical that logical qubits actually beat physical ones, after all – that is the whole point!
Thanks to some clever circuit design and our natively high fidelities, the new logical qubits outperformed their physical counterparts in every test we performed, sometimes by a factor of 10 to 100.
Computing Logically
Of course, the whole point is to use our logical qubits for something useful, the ultimate measure of functionality. With 64 error-detected qubits, we performed a simulation of quantum magnetism; a crucial milestone that validates our roadmap.
The team took extra care to perform their simulation in 3 dimensions to best reflect the real-world (often, studies like this will only be in 1D or 2D to make them easier). Problems like this are both incredibly important for expanding our understanding of materials, but are also incredibly hard, as their complexity scales quickly. To make qubits interact as if they are in a 3D material when they are trapped in 2D inside the computer, we used our all-to-all connectivity, a feature that results from our movable qubits.
Maximizing Entanglement
Breaking the encoding rate record and performing a world-leading logical simulation wasn’t enough for the team. For their final feat, the team generated 94 error-detected logical qubits, and entangled them all in a special state called a “GHZ” state (also known as a ‘cat’ state, alluding to Schrödinger’s cat). GHZ states are often used by experts as a simple benchmark for showcasing quantum computing’s unique capacity to use entanglement across many qubits. Our best 94-logical qubit GHZ state boasted a fidelity of 94.9%, crushing its un-encoded counterpart.
Logical Qubits Are the New Normal
Taken together, these results show that we can suppress errors more effectively than ever before, proving that Helios is capable of delivering complex, high-fidelity operations that were previously thought to be years away. While the magnetism simulation was only error-detected, it showcases our ability to protect universal computations with partially fault-tolerant methods. On top of that, the team also demonstrated key error-corrected primitives on Helios at scale.
All of this has real-world implications for the quantum ecosystem: we are working to package these iceberg codes into QCorrect, an upcoming tool that will help developers automatically improve the performance of their own applications.
This is just the beginning: we are officially entering the era of large-scale logical computing. The path to fault-tolerance is no longer just theoretical—it is being built, gate by gate, on Helios.
Japan has made bold, strategic investments in both high-performance computing (HPC) and quantum technologies. As these capabilities mature, an important question arises for policymakers and research leaders: how do we move from building advanced machines to demonstrating meaningful, integrated use?
Last year, ԹϺ installed its Reimei quantum computer at a world-class facility in Japan operated by RIKEN, the country’s largest comprehensive research institution. The system was integrated with Japan’s famed supercomputer Fugaku, one of the most powerful in the world, as part of an ambitious national project commissioned by the New Energy and Industrial Technology Development Organization (NEDO), the national research and development entity under the Ministry of Economy, Trade and Industry.
Now, for the first time, a full scientific workflow has been executed across Fugaku, one of the world’s most powerful supercomputers, and Reimei, our trapped-ion quantum computer. This marks a transition from infrastructure development to practical deployment.
Quantum Biology
In this first foray into hybrid HPC-quantum computation, the team explored chemical reactions that occur inside biomolecules such as proteins. Reactions of this type are found throughout biology, from enzyme functions to drug interactions.
Simulating such reactions accurately is extremely challenging. The region where the chemical reaction occurs—the “active site”—requires very high precision, because subtle electronic effects determine the outcome. At the same time, this active site is embedded within a much larger molecular environment that must also be represented, though typically at a lower level of detail.
To address this complexity, computational chemistry has long relied on layered approaches, in which different parts of a system are treated with different methods. In our work, we extended this concept into the hybrid computing era by combining classical supercomputing with quantum computing.
Shifting the Paradigm
While the long-term goal of quantum computing is to outperform classical approaches alone, the purpose of this project was to demonstrate a fully functional hybrid system working as an end-to-end platform for real scientific applications. We believe it is not enough to develop hardware in isolation – we must also build workflows where classical and quantum resources create a whole that is greater than the parts. We believe this is a crucial step for our industry; large-scale national investments in quantum computing must ultimately show how the technology can be embedded within existing research infrastructure.
In this work, the supercomputer Fugaku handled geometry optimization and baseline electronic structure calculations. The quantum computer Reimei was used to enhance the treatment of the most difficult electronic interactions in the active site, those that are known to challenge conventional approximate methods. The entire process was coordinated through ԹϺ’s workflow system , which allows jobs to move efficiently between machines.
Hybrid Computation is Now an Operational Reality
With this infrastructure in place, we are now poised to truly leverage the power of quantum computing. In this instance, the researchers designed the algorithm to specifically exploit the strengths of both the quantum and the classical hardware.
First, the classical computer constructs an approximate description of the molecular system. Then, the quantum computer is used to model the detailed quantum mechanics that the classical computer can’t handle. Together, this improves accuracy, extending the utility of the classical system.
A Path to Hybrid Advantage
Accurate simulation of biomolecular reactions remains one of the major challenges in biochemistry. Although the present study uses simplified systems to focus on methodology, it lays the groundwork for future applications in drug design, enzyme engineering, and photoactive biological systems.
While fully fault-tolerant, large-scale quantum computers are still under development, hybrid approaches allow today’s quantum hardware to augment powerful classical systems, such as Fugaku, to explore meaningful applications. As quantum technology matures, the same workflows can scale accordingly.
High-performance computing centers worldwide are actively exploring how quantum devices might integrate into their ecosystems. By demonstrating coordinated job scheduling, direct hardware access, and workflow orchestration across heterogeneous architectures, this work offers a concrete example of how such integration can be achieved.
As quantum hardware matures, we believe the algorithms and workflows developed here can be extended to increasingly realistic and industrially relevant problems. For Japan’s research ecosystem, this first application milestone signals that hybrid quantum–supercomputing is moving from ambition to implementation.