Enhancing the Harrow-Hassidim-Lloyd (HHL) algorithm in systems with large condition numbers

Although the Harrow-Hassidim-Lloyd (HHL) algorithm offers an exponential speedup in system size for treating linear equations of the form Ax[over ⃗]=b[over ⃗] on quantum computers when compared to their traditional counterparts, it faces a challenge related to the condition number (κ) scaling of the...

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Bibliographic Details
Main Authors: Peniel Bertrand Tsemo, Akshaya Jayashankar, K. Sugisaki, Nishanth Baskaran, Sayan Chakraborty, V. S. Prasannaa
Format: Article
Language:English
Published: American Physical Society 2025-06-01
Series:Physical Review Research
Online Access:http://doi.org/10.1103/msvx-1drx
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Summary:Although the Harrow-Hassidim-Lloyd (HHL) algorithm offers an exponential speedup in system size for treating linear equations of the form Ax[over ⃗]=b[over ⃗] on quantum computers when compared to their traditional counterparts, it faces a challenge related to the condition number (κ) scaling of the A matrix. In this work, we address the issue by introducing the postselection-improved HHL (Psi-HHL) framework that operates on a simple yet effective premise: subtracting mixed and wrong signals to extract correct signals while providing the benefit of optimal scaling in the condition number of A (denoted as κ) for large κ scenarios. This approach, which leads to minimal increase in circuit depth, has the important practical implication of having to use substantially fewer shots relative to the traditional HHL algorithm. The term “signal” refers to a feature of |x〉. We design circuits for overlap and expectation value estimation in the Psi-HHL framework. We demonstrate performance of Psi-HHL via numerical simulations. We carry out two sets of computations, where we go up to 26-qubit calculations, to demonstrate the ability of Psi-HHL to handle situations involving large-κ matrices via (a) a set of toy matrices, for which we go up to size 64×64 and κ values of up to ≈1×10^{6}, and (b) application to quantum chemistry, where we consider matrices up to size 256×256 that reach κ of about 393. The molecular systems that we consider are Li_{2}, KH, RbH, and CsH.
ISSN:2643-1564