Insider Brief
- Algorithmiq has launched its Tensor Network Error Mitigation (TEM) solution, available through IBM’s Qiskit Functions Catalog.
- TEM enables noise mitigation in quantum computing, optimizing performance with fewer quantum hardware resources.
- Collaborating with IBM and Trinity College, Algorithmiq has achieved groundbreaking error mitigation in large-scale quantum simulations.
PRESS RELEASE — Algorithmiq, a team pioneering the integration of quantum computing, artificial intelligence (AI), and Network Science to solve complex problems in the Healthcare and Life Sciences, has today announced the commercial availability of its revolutionary Tensor Network Error Mitigation (TEM) solution, via IBM’s newly launched Qiskit Functions Catalog.
Leveraging the properties of tensor networks, Algorithmiq’s TEM is now available to the 250+ Fortune 500 companies, universities, laboratories, and startups in the IBM Quantum Network. TEM allows developers, researchers, and computational and data scientists to manage noise in software post-processing while lowering quantum processing unit (QPU) usage. This combination allows for the programming of quantum computers with greater ease and simplicity, ultimately reducing the time needed to build and execute new workflows.
Noisy and Far From Perfect
One of the biggest challenges facing scientists and developers working with current quantum computing systems is noise, i.e., any unwanted disturbances that affect the quality of the quantum computation, e.g., a stray photon or physical vibration.
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.
Greater Accuracy with Fewer Resources
Since its establishment in 2020 by co-founders Sabrina Maniscalco, Guillermo García-Pérez, Matteo Rossi, and Boris Sokolov, Algorithmiq has aimed to push the boundaries of what is possible in error mitigation for quantum computing. The company’s approach to scalable error mitigation continues to pave the way toward true quantum value.
With the application of tensor networks in the post-processing stage of quantum computing execution, Algorithmiq’s Tensor Network Error Mitigation (TEM) has achieved levels of error mitigation never before witnessed without the need for additional quantum circuits. This optimized error cancellation with minimal use of the quantum hardware enables access to utility-scale quantum experiments.
Pushing the Boundaries of Science
Late last year, in collaboration with Trinity College Dublin and IBM, Algorithmiq demonstrated the utility of TEM by successfully running one of the largest scale error mitigation experiments to date on IBM’s hardware, achieving 2,402 entangling gates. Six months later, detailed in a paper soon to be published on the arXiv, the Algorithmiq team has now pushed the boundaries even further, successfully conducting an experiment that sees the use of 91 active qubits x 91 layers of entangling gates, resulting in a total of 4,095 entangling gates.
This marks the largest-scale digital simulation of ‘quantum chaos,’ which refers to the study of complex and unpredictable behaviors of particles at the quantum level. By understanding this chaotic behavior, we can advance research and push the boundaries of science in areas like material science, medicine, and technology.
This progress and heightened level of dependability and precision in digital quantum simulations is critical in discovering new physics and pushing the boundaries of what current quantum technology can achieve. With TEM, the door opens to more efficient utility-scale experiments.
Professor Sabrina Maniscalco, Co-Founder and CEO of Algorithmiq
“Being one of the first third-party services offered within IBM’s Qiskit Functions Catalog is an important moment, not only for Algorithmiq’s pivotal role in the quantum ecosystem but for the wider quantum community, providing IBM Quantum Network clients with access to utility-scale solutions for a class of increasingly complex problems.
“Our error mitigation algorithm, via the TEM solution in Qiskit Functions, is designed to improve computation results for the IBM Quantum Network users looking to experiment on deeper circuit depths and can enable quantum value in complex scenarios. This capability marks an important milestone, allowing quantum simulations and computations previously unattainable due to noise limitations.
“The immediate future of quantum computing relies heavily on effective error mitigation techniques. Through the power of TEM running on IBM quantum hardware, we can push the boundaries of what near-term quantum devices can achieve, bringing us closer to practical and advantageous quantum computations.”
Jay Gambetta, IBM Fellow, VP of IBM Quantum
“As we move along the IBM Quantum roadmap towards ever larger quantum systems, Qiskit Functions incorporating error mitigation services such as Algorithmiq’s TEM will help extend the boundaries of what today’s systems can explore. Together with our partners, we look forward to using techniques such as TEM to discover quantum algorithms that will unlock new computational territory and push towards quantum advantage.”
IBM Quantum Network members with an agreement authorized by Algorithmiq can access TEM through the Qiskit Functions Catalog on the IBM Quantum Platform.”
