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Efficient Quantum Control via Automatic Control Skips
Authors:
Peleg Emanuel,
Eyal Cornfeld,
Ravid Alon,
Shmuel Ur,
Israel Reichental
Abstract:
Control of quantum operations is a crucial yet expensive construct for quantum computation. Efficient implementations of controlled operations often avoid applying control to certain subcircuits, which can significantly reduce the number of gates and overall circuit depth. However, these methods are specialized and circuits frequently need to be implemented manually. This paper presents a generic…
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Control of quantum operations is a crucial yet expensive construct for quantum computation. Efficient implementations of controlled operations often avoid applying control to certain subcircuits, which can significantly reduce the number of gates and overall circuit depth. However, these methods are specialized and circuits frequently need to be implemented manually. This paper presents a generic method for finding "skippable" patterns without having to tailor implementations for each algorithm. We prove that finding the optimal operations to be skipped is generally NP-hard. Nevertheless, sub-optimal, polynomial approximation algorithms that find skippable subcircuits can lead to over $50\%$ improvement in circuit metrics for real-world applications.
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Submitted 23 May, 2025;
originally announced May 2025.
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Scalable Memory Recycling for Large Quantum Programs
Authors:
Israel Reichental,
Ravid Alon,
Lior Preminger,
Matan Vax,
Amir Naveh
Abstract:
As quantum computing technology advances, the complexity of quantum algorithms increases, necessitating a shift from low-level circuit descriptions to high-level programming paradigms. This paper addresses the challenges of developing a compilation algorithm that optimizes memory management and scales well for bigger, more complex circuits. Our approach models the high-level quantum code as a cont…
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As quantum computing technology advances, the complexity of quantum algorithms increases, necessitating a shift from low-level circuit descriptions to high-level programming paradigms. This paper addresses the challenges of developing a compilation algorithm that optimizes memory management and scales well for bigger, more complex circuits. Our approach models the high-level quantum code as a control flow graph and presents a workflow that searches for a topological sort that maximizes opportunities for qubit reuse. Various heuristics for qubit reuse strategies handle the trade-off between circuit width and depth. We also explore scalability issues in large circuits, suggesting methods to mitigate compilation bottlenecks. By analyzing the structure of the circuit, we are able to identify sub-problems that can be solved separately, without a significant effect on circuit quality, while reducing runtime significantly. This method lays the groundwork for future advancements in quantum programming and compiler optimization by incorporating scalability into quantum memory management.
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Submitted 2 March, 2025;
originally announced March 2025.
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Design and synthesis of scalable quantum programs
Authors:
Tomer Goldfriend,
Israel Reichental,
Amir Naveh,
Lior Gazit,
Nadav Yoran,
Ravid Alon,
Shmuel Ur,
Shahak Lahav,
Eyal Cornfeld,
Avi Elazari,
Peleg Emanuel,
Dor Harpaz,
Tal Michaeli,
Nati Erez,
Lior Preminger,
Roman Shapira,
Erik Michael Garcell,
Or Samimi,
Sara Kisch,
Gil Hallel,
Gilad Kishony,
Vincent van Wingerden,
Nathaniel A. Rosenbloom,
Ori Opher,
Matan Vax
, et al. (20 additional authors not shown)
Abstract:
We present a scalable, robust approach to creating quantum programs of arbitrary size and complexity. The approach is based on the true abstraction of the problem. The quantum program is expressed in terms of a high-level model together with constraints and objectives on the final program. Advanced synthesis algorithms transform the model into a low-level quantum program that meets the user's spec…
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We present a scalable, robust approach to creating quantum programs of arbitrary size and complexity. The approach is based on the true abstraction of the problem. The quantum program is expressed in terms of a high-level model together with constraints and objectives on the final program. Advanced synthesis algorithms transform the model into a low-level quantum program that meets the user's specification and is directed at a stipulated hardware. This separation of description from implementation is essential for scale. The technology adapts electronic design automation methods to quantum computing, finding feasible implementations in a virtually unlimited functional space. The results show clear superiority over the compilation and transpilation methods used today. We expect that this technological approach will take over and prevail as quantum software become more demanding, complex, and essential.
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Submitted 22 January, 2025; v1 submitted 10 December, 2024;
originally announced December 2024.