Experiment Shows How Software-Optimized Circuits Run Less Error-Prone Quantum Algorithms

A research partnership at Lawrence Berkeley National Laboratory’s Advanced Quantum Testbed (AQT) (Berkeley Lab) and Chicago-based Tremendous.tech (acquired by ColdQuanta in May 2022), demonstrated how to optimize the execution of the ZZ SWAP network protocol, vital for quantum computing. The team also introduced a novel quantum error mitigation approach that will improve network protocol implementation in quantum processors. The experimental data was published in July in Physical Overview Exploration, adding more near-term avenues for implementing quantum algorithms using gate-based quantum computing.

An intelligent compiler for superconducting quantum hardware

Quantum processors with two- or three-dimensional architectures have limited qubit connectivity where each qubit interacts with only a limited number of other qubits. Additionally, each qubit’s information can only exist so long before noise and errors cause decoherence, limiting the runtime and fidelity of quantum algorithms. Therefore, when designing and executing a quantum circuit, researchers must optimize the translation of the circuit composed of abstract (logical) gates into physical instructions based on the native hardware gates available in a given quantum processor. Efficient circuit decompositions minimize uptime because they take into account the number of gates and operations natively supported by the hardware to perform the desired logic operations.

SWAP gates – which exchange information between qubits – are often introduced into quantum circuits to facilitate interactions between information in non-adjacent qubits. If a quantum device only allows gates between adjacent qubits, permutations are used to move information from one qubit to another non-adjacent qubit.

In hardware Intermediate Scale Quantum Noisy (NISQ), the introduction of swap gates may require significant experimental overhead. The exchange gate must often be decomposed into native gates, such as NON-controlled gates. Therefore, when designing quantum circuits with limited qubit connectivity, it is vital to use a smart compiler that can search, decompose, and cancel redundant quantum gates to improve the runtime of an algorithm or a quantum application.

The research partnership used Tremendous.tech’s SuperstaQ software allowing scientists to fine-tune their purposes and automate circuit compilations for hardware AQT’s superconductor, especially for an indigenous high-fidelity controlled S-gate, which is not available on most hardware systems. This smart compilation approach with four transmon qubits allows SWAP arrays to be decomposed more efficiently than normal decomposition methods.

A ZZ SWAP gate array requires only one minimal linear connectivity between qubits without additional couplings, so it offers practical advantages for the efficient execution of quantum algorithms such as the quantum approximate optimization algorithm (QAOA). QAOA approaches methods to combinatorial optimization problems – finding the optimal answer by giving a set of criteria. The Maximum-Reduce problem, which can be used to organize hubs on a transportation network system, is an example of a famous combinatorial optimization problem that can potentially be solved faster with QAOA using quantum circuits. .

“One of the most difficult challenges in quantum computing is performing discrete logical operations. Because our control signals are analog and continuous, they are always imperfect. As we build more complex quantum circuits, the software infrastructure that optimally compiles gates suitable for AQT’s hardware helps us achieve higher operational fidelity,” Akel Hashim, the Principal Investigator. from AQT on experience and a graduate student at the University of California, Berkeley.

“A distinctive feature of quantum computing is that it allows partial logic gates. This functionality has no equivalent in traditional Boolean logic – for example, your portable computer cannot execute 50 % of an AND gate. AQT’s ability to calibrate these partially controlled gates -S quantum gates has allowed us to develop a wider range of new optimizations to get the most out of the hardware,” said Abundant Rines, formerly of Tremendous.tech and currently an engineer. software at ColdQuanta.

“A key software engineering challenge for this experiment was remote collaboration, so we iteratively developed custom gate-informed quantum circuit optimizations calibrated by the AQT team. We optimized end-to-end by figuring out how to serialize these pulses while considering the hardware. We also figured out how to integrate open source quantum software packages into our compiler, ensuring that our optimizations don’t reinvent the wheel,” said Victory Omole, formerly at Tremendous.tech and software engineer at ColdQuanta.

As part of the experiment, the team also introduced a new approach called Equivalent Circuit Average (ECA), which randomized the different parameters of SWAP networks to generate many logically equivalent circuits . ECA randomizes the decomposition of quantum circuits, mitigating the impact of systematic coherent errors – one of the most serious errors in quantum computers and widely studied at AQT.

“I proposed a way to merge my previous experimental work in random compilation with Quantum Benchmark (acquired by Keysight) using Super.tech’s clever compiler to investigate a new way to reduce the impact of crosstalk errors,” said said Hashim. “I wouldn’t have had the insight to come up with this idea if I hadn’t worked with other researchers through the AQT user program. As someone who is about to enter the job market, networking is key to building up a core of people I know in the field who are gurus in various fields, to whom I can also present research ideas. »

These experimental optimizations have improved the accuracy of QAOA performance by up to 88%. Researchers seek to continue to explore and refine the methods of this work and apply them to other apps.

Supporting industry growth with an open-access research lab

AQT operates an open experimental testbed technology based on superconducting circuits and is funded by the Advanced Scientific Computing Research (ASCR) program of the United States Department of Energy. Technologies developed elsewhere can be deployed and field tested at AQT, providing deep access to the full quantum computing stack at no additional cost.

Since inauguration of its user program in 88, the AQT provided Tremendous.tech, one of the many users in the industry, with low-level access to the material to test his ideas. Few cloud-based quantum platforms offer this form of full access to the entire quantum computing stack and real-time feedback from hardware experts at no cost. Tremendous.tech has collaborated with AQT’s experimental team of experts to learn how to improve performance on this sort of hardware.

“By revealing the hardware’s internal controls quantum computing, AQT’s collaborative approach with users drives innovation across the quantum computing stack. We look forward to continuing our research collaboration with AQT, and we will continue to share these results with the scientific community by publishing our learnings. “, said Pranav Gokhale, vice president of Quantum Application at ColdQuanta and former CEO and co-founder of Tremendous.tech.

Berkeley Lab’s AQT continues to grow as a as a cutting-edge center for quantum information research and development by bringing together expertise and users, including early-stage startups, such as Tremendous.tech, which are now continuing their growth journey as part of ColdQuanta.

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