Quantum Computing News

Quantum Leap in Circuit Optimisation: Path Integral Quantum Control Adapts for Electronic Structure Problems.

Researchers have successfully adopted Path Integral Quantum Control (PiQC) for optimizing parametrized quantum circuits, marking a significant breakthrough in quantum algorithm optimisation. This new adaptation, called Gate-based PiQC (GB-PiQC), shows strong advantages over well-known optimization methods like the Simultaneous Perturbation Stochastic Approximation (SPSA) method, especially in terms of accuracy and robustness. It holds the potential to increase reliability in intricate quantum chemistry simulations.

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Path Integral Quantum Control: Averaging Over Trajectories

It’s still quite difficult to optimize quantum circuits for intricate computations. Initially presented as a new method for calculating optimal controls in both closed and open quantum systems, Path Integral Quantum Control (PiQC) was mainly intended for pulse-based control. PiQC estimates optimal controls by averaging over a large number of potential quantum paths, in contrast to conventional approaches that rely on iterative optimisation algorithms.

This approach effectively explores a variety of control schemes by utilizing the route integral formalism, a potent tool borrowed from quantum physics. Path Integral Quantum Control PiQC efficiently smoothes the control landscape by averaging across all possible quantum routes, which makes it possible to find reliable control solutions that are less vulnerable to errors and noise. When working with complex quantum systems, where traditional optimization strategies typically fail, this skill is extremely helpful.

Framing the deterministic open-loop quantum control problem as a stochastic optimum control (SOC) problem is the fundamental mechanism of PiQC. The Stochastic Schrödinger Equation (SSE) is used to simulate the open dynamics, and iterative averages over continuous quantum trajectories are used to approximate the best controls. The approach defines an update rule for iteratively improving the controls using Adaptive Importance Sampling (AIS). PiQC has an annealing schedule for closed quantum systems that progressively lowers the ambient coupling strengths (noise) during the optimisation procedure. PiQC is categorized as a noise-assisted quantum control method for closed systems because of the annealing process, which allows the algorithm to use noise as a resource.

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Gate-Based PiQC: A Robust Alternative for VQEs

In their latest work, Peyman Najafi, Aarón Villanueva, and Hilbert Kappen from Radboud University effectively used PiQC to optimize hybrid quantum-classical techniques for ground state energy estimates of molecular Hamiltonians, known as Variational Quantum Eigensolvers (VQEs).

Gate-based PiQC (GB-PiQC) is an adaption that combines the advantages of gate-based and pulse-based quantum control. This is accomplished by showing that a randomised version of the VQE can be reformulated as a Wiener-noise-driven continuous stochastic dynamics that is appropriate for the PiQC formulation. The controls that PiQC optimises in this arrangement are the circuit parameters themselves.

PiQC’s efficiency is a key practical benefit; unlike standard methods that necessitate calculating gradients, like the parameter-shift rule, the computational cost of calculating the expected energy at each optimisation step is tied to the number of quantum trajectories sampled and does not scale with the number of circuit parameters. Additionally, the great variation of random circuit paths that results from large noise parameters during the early stages of optimisation makes it easier to explore the control landscape. Compared to utilising a small, fixed sample, this diversified sampling speeds up the optimisation process by enabling accurate parameter estimate with fewer trajectories.

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Benchmarking Reveals Superior Robustness

Both the pulse-based (PB-PiQC) and gate-based (GB-PiQC) variants were thoroughly benchmarked against the VQE method improved using SPSA, a popular stochastic optimisation methodology. A variety of common molecular Hamiltonians were compared, including those that were mapped to qubit systems.

The findings showed that both PiQC algorithms are more resilient than SPSA to changes in the target Hamiltonian brought on by shifting molecular bond lengths. Because molecular systems frequently display both weakly and strongly coupled ground states across a range of interatomic distances, this robustness is essential.

The results specifically point to a number of crucial areas where PiQC excels:

• General Performance: In the majority of cases, Path Integral Quantum Control PiQC consistently performed better than SPSA.
• Complex Regimes: At stretched bond lengths, when the Hartree-Fock solution loses accuracy, PiQC’s higher performance was especially noticeable.
• Complex Regimes: For lithium hydride and beryllium hydride, GB-PiQC consistently outperformed SPSA and produced fewer median errors across all bond lengths.
• Chemical Accuracy: Both PiQC variants kept errors below the chemical accuracy threshold over the tested range of bond distances, whereas SPSA’s accuracy decreased as bond lengths increased, leading to worst-case errors exceeding the chemical accuracy threshold in at least one instance for each molecule.

Overall, the study demonstrates that PiQC both pulse-based and gate-based represents a reliable and precise method for preparing ground states, providing a strong substitute for variationally approaches in applications involving quantum chemistry.

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