SQUARE: Strategic Quantum Ancilla Reuse for Modular Quantum Programs via Cost-Effective Uncomputation

Ding, Yongshan; Wu, Xingfu; Holmes, Adam; Wiseth, Ash; Franklin, Diana; Martonosi, Margaret; Chong, Frederic T.

doi:10.1109/isca45697.2020.00054

Cited by 22 publications

(9 citation statements)

References 53 publications

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“…Tab. 3 omits SQUARE [9] as it does not synthesize uncomputation: SQUARE expects the programmer to manually provide and mark the uncomputation code blocks for each ancilla, and then saves qubits or operations by interleaving those blocks. Silq: Enable Safe Uncomputation.…”

Section: Related Workmentioning

confidence: 99%

Unqomp: synthesizing uncomputation in Quantum circuits

Paradis

Bichsel

Steffen

et al. 2021

Proceedings of the 42nd ACM SIGPLAN International Conference on Programming Language Design and Implementation

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A key challenge when writing quantum programs is the need for uncomputation: temporary values produced during the computation must be reset to zero before they can be safely discarded. Unfortunately, most existing quantum languages require tedious manual uncomputation, often leading to inefficient and error-prone programs.We present Unqomp, the first procedure to automatically synthesize uncomputation in a given quantum circuit. Unqomp can be readily integrated into popular quantum languages, allowing the programmer to allocate and use temporary values analogously to classical computation, knowing they will be uncomputed by Unqomp.Our evaluation shows that programs leveraging Unqomp are not only shorter (-19% on average), but also generate more efficient circuits (-71% gates and -19% qubits on average).

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Section: Related Workmentioning

confidence: 99%

Unqomp: synthesizing uncomputation in Quantum circuits

Paradis

Bichsel

Steffen

et al. 2021

Proceedings of the 42nd ACM SIGPLAN International Conference on Programming Language Design and Implementation

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“…Efficient qubit routing techniques are required to minimize compilation overhead for reliable computation. Different from existing qubit routing algorithms that respect the gate order in the input circuit [20,23,45,46], the routing in 2QAN exploits the operator permutation flexibility in a Hamiltonian. The pseudocode is in Algorithm 1 and an example is shown in Figure 3c.…”

Section: Qubit Routingmentioning

confidence: 99%

2QAN: A quantum compiler for 2-local qubit Hamiltonian simulation algorithms

Lao¹,

Browne²

2021

Preprint

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Simulating quantum systems is one of the most important potential applications of quantum computers to demonstrate its advantages over classical algorithms. The high-level circuit defining the simulation needs to be transformed into one that compiles with hardware limitations such as qubit connectivity and hardware gate set. Many techniques have been developed to efficiently compile quantum circuits while minimizing compilation overhead. However, general-purpose quantum compilers work at the gate level and have little knowledge of the mathematical properties of quantum applications, missing further optimization opportunities. In this work, we exploit one application-level property in Hamiltonian simulation, which is, the flexibility of permuting different operators in the Hamiltonian (no matter whether they commute). Conventional compilation techniques may not be directly adapted to this flexibility because changing the order of anti-commuting gates violates program semantics.We develop a compiler, named 2QAN, to optimize quantum circuits for 2-local qubit Hamiltonian simulation problems, a framework which includes the important quantum approximate optimization algorithm (QAOA). In particular, we propose permutation-aware qubit mapping, qubit routing, gate optimization and scheduling techniques to minimize the compilation overhead. We evaluate 2QAN by compiling three applications (up to 50 qubits) onto three quantum computers that have different qubit topologies and hardware two-qubit gates, namely, Google Sycamore, IBMQ Montreal and Rigetti Aspen. Compared to state-of-the-art quantum compilers, 2QAN can reduce the number of inserted SWAP gates by up to 11.5X, reduce overhead in hardware gate count by up to 30.7X, and reduce overhead in circuit depth by up to 21X. This significant overhead reduction will help improve application performance. Experimental results on the Montreal device demonstrate that benchmarks compiled by 2QAN achieve highest fidelity.

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“…Scratch qubits that are entangled with data qubits alter the state of the data qubits if they are reset or measured. Reclaiming scratch (ancilla) qubits is the process of returning them to their original state for future reuse [28]. This facilitates the reuse of the scratch qubits on subsequent computations, and, at the same time, the modification of the scratch qubits downstream does not affect the output qubits in case they are entangled; 4.…”

Section: Quantum Modulesmentioning

confidence: 99%

On the Definition of Quantum Programming Modules

Sánchez

Alonso

2021

Applied Sciences

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There are no doubts that quantum programming and, in general, quantum computing, is one of the most promising areas within computer science and one of the areas where most expectations are being placed in recent years. Although the days when reliable and affordable quantum computers will be available is still a long way off, the explosion of programming languages for quantum programming has grown exponentially in recent years. The software engineering community has been quick to react to the need to adopt and adapt well-known tools and methods for software development, and for the design of new ones tailored to this new programming paradigm. However, many key aspects for its success depend on the establishment of an appropriate conceptual framework for the conception and design of quantum programs. This article discusses the concept of module, key in the software engineering discipline, and establishes initial criteria for determining the cohesion and coupling levels of a module in the field of quantum programming as a first step towards a sound quantum software engineering. As detailed in the article, the conceptual differences between classical and quantum computing are so pronounced that the translation of classical concepts to the new programming approach is not straightforward.

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SQUARE: Strategic Quantum Ancilla Reuse for Modular Quantum Programs via Cost-Effective Uncomputation

Cited by 22 publications

References 53 publications

Unqomp: synthesizing uncomputation in Quantum circuits

Unqomp: synthesizing uncomputation in Quantum circuits

2QAN: A quantum compiler for 2-local qubit Hamiltonian simulation algorithms

On the Definition of Quantum Programming Modules

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