Algorithmiq develops quantum algorithms that integrate classical computers with advanced quantum computers. Their quantum solutions are designed to push the boundaries of scientific discovery at an atomistic-scale resolution to solve life science problems that are currently deemed impossible.
One of the biggest challenges facing scientists and developers working with current quantum computing systems is noise - unwanted disturbances that affect the quality of the quantum computation. Noise mitigation strategies are crucial for improving the utility of near-term quantum devices. While these algorithms can course-correct for a certain period, they’re prone to diminishing returns, particularly as the problem size and number of qubits increase.
Algorithmiq’s Tensor Network Error Mitigation (TEM) method is a hybrid quantum-classical algorithm designed for performing noise mitigation entirely at the classical post-processing stage. TEM is also designed to integrate with error correction techniques to help extend the scale and accuracy of quantum simulations, the combination of which will become increasingly relevant, as quantum processors increasingly become more sophisticated.
Algorithmiq’s error mitigation algorithm, TEM, is now commercially available on IBM’s Qiskit Functions Catalog. Using the Qiskit Functions Catalog, developers can release Qiskit Functions that unlock capabilities for enterprise developers and quantum computational scientists.
Breakthroughs interviewed Algorithmiq CEO Sabrina Maniscalco to discuss the use of quantum computing in life sciences and how IBM is opening up new opportunities for developers of quantum technology and making it easier for users to access quantum computing.
How does the recent expansion of the IBM Quantum Data Center impact global quantum computing capabilities?
Maniscalco: “IBM's expansion of its Quantum Data Center in Poughkeepsie marks a significant leap forward for global quantum computing capabilities. The centre now houses the world's largest concentration of utility-scale quantum computers, offering up to 16 times better performance and 25 times faster than IBM's 2022 quantum systems.”
“This expansion brings tremendous potential to the entire scientific community and enhances Algorithmiq’s ability to refine our algorithms. It also intensifies the competitive landscape, which history has shown is one of the most significant drivers of innovation.”
“As IBM continues to push the boundaries of quantum hardware, it's creating new opportunities for algorithm discovery and practical applications; for example, in healthcare and life sciences, as well as in materials science. This progress is accelerating the global quantum ecosystem's growth, attracting top talent and bringing us closer to achieving quantum advantage in real-world scenarios.”
What role does the IBM Quantum Cloud service play in making quantum computing more accessible to global clients and industries?
Maniscalco: “While there’s been a great deal of promise and progress in quantum computing, we’ve only begun to scratch the surface of unlocking the true potential for scientific discovery. IBM's Quantum Cloud service is a significant moving of the needle, offering clients and industries access to leading-edge quantum hardware. This cloud-based approach eliminates the need for organisations to invest in quantum infrastructure, significantly lowering the barrier to entry.”
“Additionally, when combined with IBM’s Qiskit software stack, the Quantum Cloud service simplifies quantum programming. This accessibility is crucial for nurturing a global quantum software and services ecosystem. It's enabling startups and established companies alike to contribute to the field, accelerating the pace of discovery and innovation.”
What is the significance of operating at utility-scale in quantum computing, and how does it distinguish quantum systems from classical computing?
Maniscalco: “Operating at utility-scale represents a crucial milestone in quantum computing. It means our quantum computers can now simulate certain systems as accurately as best-in-class classical methods, even outperforming brute-force classical simulations. This capability opens up a tremendous potential for computational exploration and algorithm development that was previously out of reach.”
“The differentiator here lies in the quantum computer's ability to harness quantum mechanical phenomena like superposition and entanglement. At utility-scale, these quantum properties allow us to tackle more and more complex problems.”
“For Algorithmiq and the broader industry, utility-scale quantum computing signifies a transition from theoretical potential to practical applicability. Whilst it’s not yet full quantum advantage, it enables us to explore use cases, on today’s computers, which could bring new computational territories, potentially leading to breakthroughs in fields such as molecular simulation for chemistry and materials.”
Algorithmiq has developed tools within the Qiskit Functions Catalog. How are these collaborations helping to address real-world challenges using quantum computing?
Maniscalco: “Algorithmiq's integration into the Qiskit Functions Catalog represents a significant step towards making quantum computing more accessible and applicable to real-world challenges. Our Tensor Network Error Mitigation (TEM) has achieved levels of error mitigation never before witnessed without the need for additional quantum circuits. This optimised error mitigation with minimal use of the quantum hardware enables access to utility-scale quantum experiments.”
“Error mitigation is crucial in quantum computing, especially as we push towards utility-scale applications. Quantum systems are inherently noisy, and managing this noise is key to achieving reliable results. TEM helps address this challenge, enabling users to run more complex quantum algorithms more accurately.”
Could you explain how Qiskit simplifies the process of programming quantum computers?
Maniscalco: “Qiskit has emerged as a leading tool in quantum computing, and it is known for its performance and user-friendly approach, making quantum programming more accessible and intuitive.”
“For newcomers to quantum computing, Qiskit provides a gentle learning curve. Its Python-based interface allows developers familiar with classical programming to transition more easily into the quantum realm. Much like the tools developers use daily, Qiskit offers a host of documentation and tutorials and enables new users to grasp quantum concepts and start coding quickly.”
“For those already familiar with working in and around quantum computing, Qiskit allows for low-level control of quantum circuits while also offering high-level abstractions for complex quantum operations. This versatility enables seasoned developers to fine-tune their algorithms for optimal performance on IBM's quantum hardware."
How can quantum computers be used to solve challenges in life science or healthcare?
Maniscalco: “By simulating molecular interactions at the quantum level, quantum computers can accelerate drug discovery and development, enhance our understanding of diseases like Alzheimer's, and pave the way for more personalised medicine. At Algorithmiq, we are working on integrating multiple approaches like AI and network medicine to reshape the future of healthcare and life sciences by developing quantum algorithms that unlock the power of quantum computers. Instead of the slow trial-and-error methods used in labs today, advanced computer models will rapidly analyse billions of options to discover the best medicines.”
“While many of these applications are still in the early stages, recent advancements in quantum hardware, such as IBM's utility-scale systems, bring us closer to practical implementation.”
Sabrina Maniscalco is CEO and co-founder of Algorithmiq, a Professor of Quantum Information and Logic at the University of Helsinki, and an Adjunct Professor at Aalto University, Finland.
