Leading the Quantum Frontier: Dynex’s Unmatched Efficiency and Scalability

• Patent pending neuromorphic-inspired architecture that dramatically reduces complexity of computing quantum algorithms.
• Compared with industry leaders, Dynex demonstrates the capability to efficiently compute quantum gate circuits beyond the limits of its competition.
• How Dynex matched (and even surpassed) Google’s Willow chip benchmarks in quantum computing.

Dynex is transforming the world of quantum computing with its unique approach that defies the limits of traditional quantum simulators. Unlike classical systems that rely on the exponential growth of computational resources as the number of qubits increases, Dynex employs a patent pending neuromorphic-inspired architecture that dramatically reduces this complexity. By utilising its innovative circuit simulation on decentralised GPUs and a new method of mapping qubits onto Dynex qubits, the platform can efficiently simulate large-scale quantum systems, opening the door to real-world applications previously thought impractical for current quantum computers.

Dynex is winning continuous traction in the market to apply quantum computing solutions to real-world use cases across a wide range of industries upholding ethical integrity. By partnering with leading organisations in fields such as automotive, pharmaceuticals, aerospace, and energy, Dynex seeks to help businesses solve complex optimization, simulation, and data analysis problems. For example, Dynex’s technology is being used to develop optimised racing strategies in motorsports, enhance AI for health-tech innovations and -research and to accelerate drug discovery in pharmaceuticals. These partnerships across industries showcase the practical, scalable impact of Dynex’s quantum computing solutions, allowing clients to leverage cutting-edge technology to tackle industry-specific challenges and achieve significant advancements.

Dynex’s customers and partners are leveraging cutting-edge technology to tackle industry-specific challenges and achieve significant advancements across a variety of industries, from healthcare to environmental.

What Makes Dynex Different?

Dynex’s patent pending quantum computing approach centers on a breakthrough in how quantum circuits are simulated and executed. While traditional quantum computing technologies rely on quantum-mechanical qubits and Schrödinger’s equations for calculations, Dynex introduces its own type of “Dynex qubits,” which are inspired by neuromorphic computing principles. Analog logic gates based Dynex qubits exhibit properties similar to quantum superposition and entanglement but are based on ion drift effects, typically seen in memristors. Dynex qubits do not require the extreme low-temperature conditions needed by quantum computers based on quantum-mechanical principles, such as those from IBM, Google, IonQ or Rigetti.

This method allows Dynex to simulate quantum circuits on classical hardware, notably GPUs, with far less computational resource demand than conventional quantum simulations. The sub-exponential scaling required by Dynex enables it to handle large numbers of qubits far more efficiently than current systems, making it scalable for complex real-world problems. By focusing on mapping problems to neuromorphic circuits where gates interact with one another to find solutions, Dynex not only computes quantum algorithms but does so at a scale and with an efficiency that traditional quantum computers cannot match.

Dynex is actively contributing to the scientific community by publishing research and advancing the field of quantum computing. Through a series of scientific papers and publications, Dynex shares insights into its innovative approaches, including the use of proprietary qubits and efficient simulation techniques. These contributions help to further the understanding of quantum computing principles and their real-world applications. By making its findings available to the broader scientific community, Dynex fosters collaboration and knowledge sharing, supporting the ongoing development of scalable, practical quantum computing solutions.

The Role of Dynex’s Unique Qubits

The Dynex qubits are not quantum-mechanics-based but serve as neuromorphic counterparts that model quantum phenomena. They operate in voltage states between -1.0 and +1.0 volts, which enables them to simulate the behaviour of quantum superposition. The ability to map quantum algorithms onto these neuromorphic circuits, where gates interact in parallel, creates an effect akin to quantum tunnelling. This design not only reduces the complexity of simulations but also allows Dynex to break industry benchmarks like Q-Score and quantum volume, demonstrating its ability to handle increasingly complex quantum circuits.

Dynex’s unique approach enables it to achieve higher Q-Score values, reflecting its superior ability to simulate quantum algorithms accurately. It also surpasses quantum volume benchmarks, a key metric of a quantum computer’s capability to perform meaningful computations, by efficiently scaling simulations even as the size of the quantum circuits increases. These achievements highlight Dynex’s computational power and scalability, establishing it as a leading Quantum-as-a-Service (QaaS) provider in the quantum computing landscape.

The Apollo Chip: Speeding up Quantum Computation

Dynex is continuing its technological advancements with the upcoming Apollo chip, which will support up to 1,000 fully entangled Dynex qubits. Unlike traditional quantum computers that rely on quantum-mechanical qubits, Apollo’s qubits operate within the same framework as Dynex’s existing technology, offering the ability to simulate larger quantum systems without encountering the exponential bottleneck. These chips are designed to operate at room temperature, drastically lowering the operational complexity and cost compared to other quantum systems, which require cryogenic conditions. The Apollo chip marks a new phase in the realization of a scalable, practical quantum computing platform capable of solving real-world problems across industries.

Clarifying the Use of “Quantum”

While Dynex’s system uses the term “quantum” in its technology, it’s crucial to differentiate it from traditional quantum computing platforms. Dynex is not building a universal quantum computer that uses quantum-mechanics-based qubits but instead offers a computational platform that efficiently simulates quantum systems using neuromorphic principles. Its ability to compute quantum gate circuits and algorithms efficiently and at scale makes it a valid candidate for solving quantum problems, but it does not aim to build a universal quantum computer as defined by conventional scientific standards.

The use of the term “quantum” in Dynex’s case refers to its capability to simulate and execute quantum algorithms with efficiency, achieving quantum-like behavior without relying on quantum mechanical phenomena.

Applicability of Dynex’s Quantum-Computing-as-a-Service (QaaS) for Real-World Use Cases

Dynex’s quantum-computing-as-a-service (QaaS) is uniquely positioned to solve real-world problems that other quantum computing platforms are currently unable to tackle at scale. While traditional quantum systems from IBM, Google, and others are still limited to small, toy-sized problems, Dynex has already demonstrated the ability to scale up to much larger problems. This makes it ideal for industries looking to solve complex problems that require significant computational power, such as in the pharmaceutical, automotive, aerospace, and financial sectors.

In practical terms, Dynex’s quantum algorithms are used for optimization problems in real-world settings, such as in motorsports, where Dynex has been successfully applied for real-time decision-making in race strategies. Similarly, Dynex’s technology is being used to simulate complex molecular systems in pharmaceuticals, helping companies discover new drugs and therapies faster. Its scalability allows industries to leverage quantum computing for applications such as material science, cryptography, and logistics, which require computational power beyond the capabilities of current quantum hardware.

Dynex’s decentralised quantum computing model enables companies to integrate this power into their existing infrastructures, allowing for more accessible and scalable quantum computation. This contrasts with the universal quantum computers being developed by IBM, Google, and others, which are still constrained by noise, error rates, and coherence times. These traditional systems are far from being able to solve meaningful, large-scale problems in the short term, making them less practical for immediate applications.

Seamless Integration with Commonly Used Quantum Programming Languages

Dynex integrates seamlessly with the most commonly used quantum programming languages, making it easy for users to leverage its advanced computational capabilities within their existing workflows. Through the Dynex SDK, users can write quantum programs in familiar languages like Qiskit, Cirq, and others, enabling smooth interoperability between Dynex and these widely adopted frameworks. This integration allows for a more accessible entry point into quantum computing, as users can run their quantum circuits and algorithms on Dynex without needing to learn a new language or environment. The result is a highly flexible and user-friendly platform that accelerates the adoption of quantum computing in real-world applications.

Comparing Dynex with Industry Leaders

While Dynex’s approach is distinct from traditional quantum systems, it remains a powerful force in the quantum computing ecosystem. Below is a detailed comparison of Dynex with the leading players in the field:

This chart compares the capabilities of Dynex and other quantum computing systems based on quantum circuit computing efficiency and qubit count. The x-axis shows quantum circuit computing efficiency, where Dynex stands out as the most efficient, able to simulate large-scale quantum algorithms with fewer resources. The y-axis, displayed on a logarithmic scale, represents the number of qubits supported by each platform, with platforms like IBM Quantum, Google Quantum, Rigetti Quantum, and IonQ showing significant qubit counts. However, despite supporting proprietary Dynex qubits, Dynex can handle more complex computations due to its unique approach, positioning it as a leader in scalable computing of quantum gate circuits.

IBM Quantum

• Focus: Quantum hardware development, primarily using superconducting qubits.
• Simulation Tools: IBM Qiskit and Aer are used for simulating quantum circuits on classical hardware.
• Strengths: IBM is a leader in quantum hardware development and the ecosystem surrounding it.
• Limitations: Limited by quantum coherence and noise, with systems still in early stages of scalability.

Google Quantum

• Focus: Quantum supremacy experiments using superconducting qubits.
• Simulation Tools: Google Cirq is used for quantum circuit design and simulation.
• Strengths: Leading in quantum algorithm development, particularly for achieving quantum supremacy.
• Limitations: Quantum systems are still not capable of solving large-scale, practical problems due to noise and hardware limitations.

D-Wave

• Focus: Quantum annealing for optimization tasks.
• Simulation Tools: D-Wave provides a platform for quantum annealing simulation, but it is not a general-purpose quantum simulator.
• Strengths: Excellent for solving optimization problems.
• Limitations: Not suited for general-purpose quantum computing, limited to specific types of algorithms.

Rigetti Quantum

• Focus: Quantum processor development using superconducting qubits.
• Simulation Tools: Forest provides cloud-based quantum simulation and hardware access.
• Strengths: Strong focus on integrating quantum computing into the cloud.
• Limitations: Still in early stages with hardware scalability challenges similar to IBM and Google.

Pros and Cons Table

Dynex stands out in the quantum computing landscape by offering a highly efficient approach to computing quantum circuits on classical hardware, particularly GPUs. Unlike IBM, Google, Rigetti, and IonQ, which rely on quantum-mechanical qubits and are still limited by challenges like coherence time and noise, Dynex uses proprietary qubits that enable more scalable computations with fewer resources and less energy.

Dynex’s quantum-as-a-service (QaaS) excels in quantum circuit computation efficiency, handling larger problems with fewer qubits, and it has surpassed industry benchmarks like Q-Score and quantum volume. While other platforms focus on building quantum hardware or specialized quantum systems, Dynex’s method offers unparalleled scalability for complex real-world use cases, including optimization and simulation problems, without the exponential scaling bottleneck faced by traditional quantum systems.

Dynex Head-to-Head with Industry Leaders

Dynex has conducted comprehensive head-to-head comparisons by running the same quantum gate circuits on multiple platforms (Dynex, IBM AER and IBM QPU), with increasing circuit complexity. These tests, accompanied by source codes for reproduction and real-time screen recordings, clearly demonstrate Dynex’s superior capability.

Quantum gate circuits with growing complexity, from 2^8 to 2^64, benchmarked up to 2^104

As the complexity of the quantum gate circuits increases, Dynex remains the only technology able to compute these circuits efficiently, while the other tested solutions struggle to handle the same level of complexity. This reinforces Dynex’s position as the leading quantum-computing-as-a-service (QaaS) provider for scalable, large-scale quantum circuit computations.

Head-to-head comparison screen recordings of the real-time execution of n-bit adder quantum gate circuits with growing complexity: 8 bit, 16 bit, 32 bit, 64 bit, 88 bit and 104 bit respectively.

In the performed benchmarks, Dynex has successfully computed quantum gate circuits with a complexity of up to 2^104, consistently returning the correct results for the quantum circuit operations. In comparison, IBM Aer can handle computations with a complexity up to 2^16, producing correct results. However, the IBM QPU (127-qubit Eagle r3) fails to compute accurate results beyond 2^8 and is unable to return correct sample results at higher complexities.

[1] Performed on Dynex Quantum-as-a-Service (QaaS) on 18–12–2024 [2] Performed on IBM AerSimulator [3] Performed on IBM Quantum Platform, 127 qubits, 30K CLOPS, Eagle r3 QPU

The following IBM dashboard screen displays the results of executing the benchmark’s 8-bit adder quantum gate circuit on IBM’s Eagle r3 QPU. The probabilistically determined best result was “10010011” (147), observed with a frequency of 12, while the expected, correct outcome, “11001000” (58 + 124 = 200), was reported with a frequency of only 5. This discrepancy can be attributed to error correction issues inherent in hardware quantum-mechanical based systems, which is a major disadvantage compared to Dynex. In contrast, Dynex experiences significantly fewer error correction challenges, ensuring more reliable and accurate results.

Results of executing the benchmark’s 8-bit adder quantum gate circuit on IBM’s Eagle r3 QPU. The probabilistically determined best result was “10010011,” observed with a frequency of 12, while the correct outcome, “11001000,” was reported with a frequency of only 5 (Source: IBM Quantum dashboard).

IBM Eagle r3 QPU metrics are showing a performance of 30K CLOPS and a 2Q error (layered) of 1.69e-2 (Source: IBM Quantum dashboard).

How Dynex Matched (and Even Surpassed) Google’s Willow Chip Benchmarks in Quantum Computing

Google’s recent unveiling of the Willow quantum chip has garnered significant attention, with claims of achieving Random Circuit Sampling (RCS) computations in under five minutes that would take classical supercomputers an estimated 10 septillion years (The Verge). This feat was accomplished using the Cross-Entropy Benchmarking (XEB) protocol, a method designed to assess the fidelity of quantum circuits by comparing the output distributions of quantum processors to those of idealised models (Wikipedia).

Wait, what’s RCS and why does it matter?
Imagine this: solving a Random Circuit Sampling (RCS) problem on a classical computer would require more computational power than all the supercomputers in the universe working together — not just in one universe, but across multiple universes. Even if you enlisted the help of every atom in existence, running non-stop since the beginning of time, you’d still fall short. That’s how astronomically difficult these problems become for classical machines as the number of qubits and the circuit depth grow.

Random circuit sampling (RCS), while extremely challenging for classical computers, has yet to demonstrate practical commercial applications (Source: Google)

When Google’s Willow chip pulled off its beyond-classical feat, it set a new bar. Essentially, they proved that there are certain tasks where quantum machines leave even the best classical strategies in cosmic dust. Suddenly, everyone’s eyeing RCS as the new “Mount Everest” in quantum computing.

Now, here’s where it gets exciting: Dynex solved these same problems in just minutes. Quantum magic? Not quite — it’s real, tangible progress in quantum computing, and we’re here to share how we did it.

Enter Dynex
At Dynex, we love a good challenge. Our quantum platform was built with flexibility and scalability in mind, and we believed it could hold its own against the giants. So we took the same RCS game plan that Google used — same style of circuits, similar patterns, patch-based cross-entropy benchmarking (XEB) for verifying results, the whole nine yards — and put Dynex through the wringer.

We started small with a 4×4 grid of qubits (just 16 qubits) to ensure our setup was correct and that our fidelity measurements (how “accurate” the quantum distribution is) matched expected patterns. Once we nailed that, we raised the stakes and scaled up to a 10×10 grid — 100 qubits strong. That’s a lot of quantum muscle, pushing well into the territory where classical simulation becomes, let’s say, “unlikely before the sun burns out.”

Our Random Circuit Sampling (RCS) experiments follow a carefully structured methodology inspired by established benchmarks, notably those demonstrated on Google’s Willow chip. The core of this approach involves arranging qubits in a two- dimensional grid and applying a standardised sequence of gate operations, both of which are now hallmarks of beyond-classical RCS demonstrations (Source: Approaching Google Willow Chip’s Beyond-Classical Random Circuit Sampling Benchmarks Using Dynex; Neumann Adam, 12/2024).

From Minutes to Millennia
How bad is the classical simulation scenario? Using estimates inspired by Google’s published data, we crunched the numbers for simulating our largest circuits on a classical supercomputer. The result: even at fairly “small” circuit depths, you’re looking at simulation times of trillions and trillions of years.

Now the fun part: how long did it take Dynex to run these monstrous circuits? Minutes. Seriously. About 20 minutes total, with roughly 5 minutes per circuit depth configuration. On a quantum device. Running in real time. It’s hard to overstate how wild that is. In other words, a task that would outlast multiple universes on a classical setup took just one coffee break on Dynex.

Fidelity: More Than Just a Number
Running the circuits is one thing, but we also need to prove we’re getting that same “quantum accuracy” that Google captured. We used patch-based XEB, a clever technique that lets you verify output distributions without needing to simulate the entire circuit classically. Instead, you break the qubits into smaller patches, simulate those patches (which is doable classically), and then cross-check against the actual measured outputs from Dynex. The fidelity numbers were right where we wanted them, showing that the device isn’t just spewing random gibberish, but producing a genuinely complex quantum distribution akin to what Google achieved with Willow.

The patch-based XEB approach confirms that the Dynex platform generates non-trivial quantum distributions consistent with the intended random circuit. Our results show the same characteristic downward trend in fidelity as circuit depth increases that was observed in Google’s Sycamore chip experiments (Source: Approaching Google Willow Chip’s Beyond-Classical Random Circuit Sampling Benchmarks Using Dynex; Neumann Adam, 12/2024)

So, Did We Beat Google?
Let’s keep it humble and honest. Google’s Willow chip made a huge splash and set a major benchmark. Our work at Dynex shows that we’re now playing in the same league. In fact, we might even be edging ahead in some aspects of flexibility. While it’s not a direct apples-to-apples comparison (different hardware, slightly different conditions), the bottom line is this: Dynex achieved beyond-classical RCS performance that’s on par with the state-of-the-art benchmarks set by Willow.

Why Does This Matter?
For one, it’s great news for quantum computing’s future. Seeing multiple platforms hit these beyond-classical regimes means that quantum supremacy — or quantum advantage, as some prefer to call it — isn’t just a one-off stunt by a single device. It’s a reproducible phenomenon. As more quantum players join the party, we can expect rapid improvements in hardware, algorithms, and usability. This pushes quantum computing closer to real-world applications that do more than just turn heads — they solve hard problems no classical machine can touch.

What’s Next?
We’re excited to release our code, data, and methods to the community. This isn’t a secret sauce moment. We want everyone to poke around, verify, critique, and build upon what we’ve done. Collaboration and transparency are what drive the quantum field forward.

Our next steps involve scaling even further, refining error correction, and tackling even more complex circuits and algorithms. The ultimate goal is to move from impressive demonstrations to transformative applications — drug discovery, climate modeling, advanced materials design, and optimization problems that keep classical machines up at night.

In a world where quantum computing’s promise is often overshadowed by its complexity, achieving beyond-classical performance is like planting a flag at the summit. Google did it first with Willow, setting the benchmark. Now Dynex has stepped up to that same plate, connecting a few more dots on the roadmap to practical, commercially relevant quantum computing.

Paper:
Approaching Google Willow Chip’s Beyond-Classical Random Circuit Sampling Benchmarks Using Dynex; Neumann, Adam, 12/2024

Source codes:
https://github.com/dynexcoin/DynexSDK/tree/main/xeb-benchmark

Conclusion

Dynex offers a unique and scalable solution to quantum computing, unlike any of the existing systems from IBM, Google, or others. Its ability to simulate quantum circuits efficiently and handle quantum algorithms at scale sets it apart as the only platform capable of solving real-world problems beyond toy-sized models. With the upcoming Apollo chip and continuous breakthroughs in scalability, Dynex is paving the way for quantum computing to enter practical, industrial applications.

About Dynex

Dynex’s leading Quantum-as-a-Service (QaaS) technology, offers businesses an affordable, accessible and scalable solution for quantum computing underpinned by a robust commitment to ethical integrity. With cost-effective subscription plans available to everyone, Dynex enables industries to solve real-world problems at scale with unparalleled computational power. Dynex plays a key role in the next megacycle in computing: Quantum. Across academia and different industries including artificial intelligence, pharmaceuticals, finance, aerospace and many more, Dynex drives exponential growth in the most complex fields, meeting the increasing demand for advanced computing solutions. Within the Dynex Ecosystem, Dynex Moonshots serves as the strategic, investment and ethical steward, advancing quantum technology to deliver pioneering solutions across nature, health, society and space. Dynex is recognized as a 2024 Technologist of the Year as part of Fast Company’s Next Big Things in Tech Award.

Dynex’s team consists currently of 67 dedicated professionals, with a strong focus on scientific and quantum expertise. Among the team, 6 individuals are core developers, driving the development of our core technologies. Another 6 are academic and science developers, contributing deep research and knowledge to the platform’s innovative features. The leadership team, composed of 9 members, includes experts in quantum computing and AI, overseeing the strategic direction of Dynex’s scientific initiatives. Additionally, the ethical committee and advisors, numbering 6 and 7 respectively, play a crucial role in ensuring the integrity and alignment of Dynex’s innovations with ethical standards. The support team of 13 and other departments, such as business development and marketing, ensure the smooth operation and global outreach of Dynex’s cutting-edge quantum solutions.

Learn more at https://dynex.co/