QUANTIFY: A Framework for Resource Analysis and Design Verification of Quantum Circuits

We present an arithmetic circuit performing constant modular addition having O(n) depth of Toffoli gates and using a total of n + 3 qubits. This is an improvement by a factor of two compared to the width of the stateof-the-art Toffoli-based constant modular adder. The advantage of our adder, compared to the ones operating in the Fourier basis, is that it does not require small-angle rotations and their Clifford + T decomposition. Our circuit uses a recursive adder combined with the modular addition scheme proposed by Vedral et al. The circuit is implemented and verified exhaustively with QUANTIFY, an open-sourced framework. We also report on the Clifford + T cost of the circuit.

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“…The presented modular adder was implemented in QUAN-TIFY [9], which is open-sourced and available from Ref. [10].…”

Section: Results and Resource Analysismentioning

confidence: 99%

“…We implemented the constant modular adder in QUAN-TIFY [9], which is an open-sourced framework. Moreover, using this framework, we compiled the circuits using Toffoli gates and exhaustively verified the correctness.…”

Section: Discussionmentioning

confidence: 99%

Halving the width of Toffoli-based constant modular addition to n+3 qubits

Oumarou

Basmadjian

2022

Phys. Rev. A

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“…number of qubits). We use QUANTIFY [17] to count exactly the gates and determine the depth of the circuits. The work of [16] analyses the role of Toffoli gate decompositions for improving carry-lookahead adder circuits.…”

Section: Methodsmentioning

confidence: 99%

On the realistic worst case analysis of quantum arithmetic circuits

Oumarou¹,

Basmadjian²

2021

Preprint

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We provide evidence that commonly held intuitions when designing quantum circuits can be misleading. In particular we show that: a) reducing the T-count can increase the total depth; b) it may be beneficial to trade CNOTs for measurements in NISQ circuits; c) measurement-based uncomputation of relative phase Toffoli ancillae can make up to 30% of a circuit's depth; d) area and volume cost metrics can misreport the resource analysis. Our findings assume that qubits are and will remain a very scarce resource. The results are applicable for both NISQ and QECC protected circuits. Our method uses multiple ways of decomposing Toffoli gates into Clifford+T gates. We illustrate our method on addition and multiplication circuits using ripple-carry. As a byproduct result we show systematically that for a practically significant range of circuit widths, ripple-carry addition circuits are more resource efficient than the carry-lookahead addition ones. The methods and circuits were implemented in the open-source QUANTIFY software.

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“…We develop our own quantum circuit simulator and include it in QUANTIFY [15]. Our simulator uses the Cirq state vector simulator as a starting point and we exploit the speed of GPUs by replacing NumPy calls with CuPy ones.…”

Section: Methodsmentioning

confidence: 99%

“…We benchmarked the performance of CuPy using two types of circuits: supremacy and arithmetic. We use QUANTIFY [15] to generate quantum arithmetic circuits (e.g. multipliers).…”

Section: Methodsmentioning

confidence: 99%

Fast quantum circuit simulation using hardware accelerated general purpose libraries

Oumarou

Basmadjian

2021

Preprint

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Quantum circuit simulators have a long tradition of exploiting massive hardware parallelism. Most of the times, parallelism has been supported by special purpose libraries tailored specifically for the quantum circuits. Quantum circuit simulators are integral part of quantum software stacks, which are mostly written in Python. Our focus has been on ease of use, implementation and maintainability within the Python ecosystem. We report the performance gains we obtained by using CuPy, a general purpose library (linear algebra) developed specifically for CUDA-based GPUs, to simulate quantum circuits. For supremacy circuits the speedup is around 2x, and for quantum multipliers almost 22x compared to state-of-the-art C++-based simulators.

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QUANTIFY: A Framework for Resource Analysis and Design Verification of Quantum Circuits

Cited by 9 publications

References 14 publications

Halving the width of Toffoli-based constant modular addition to n+3 qubits

Halving the width of Toffoli-based constant modular addition to n+3 qubits

On the realistic worst case analysis of quantum arithmetic circuits

Fast quantum circuit simulation using hardware accelerated general purpose libraries

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