Rotational Abstractions for Verification of Quantum Fourier Transform Circuits

• URL: http://arxiv.org/abs/2301.00737v1
• Date: Mon, 2 Jan 2023 16:13:39 GMT
• Title: Rotational Abstractions for Verification of Quantum Fourier Transform Circuits
• Authors: Arun Govindankutty, Sudarshan K. Srinivasan, and Nimish Mathure
• Abstract summary: We propose a novel formal verification method that is targeted at Quantum Fourier Transform (QFT) circuits. QFT is a fundamental quantum algorithm that forms the basis of many quantum computing applications. Our method is able to scale up to the verification of QFT circuits with 10,000 qubits and 50 million quantum gates.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: With the race to build large-scale quantum computers and efforts to exploit quantum algorithms for efficient problem solving in science and engineering disciplines, the requirement to have efficient and scalable verification methods are of vital importance. We propose a novel formal verification method that is targeted at Quantum Fourier Transform (QFT) circuits. QFT is a fundamental quantum algorithm that forms the basis of many quantum computing applications. The verification method employs abstractions of quantum gates used in QFT that leads to a reduction of the verification problem from Hilbert space to the quantifier free logic of bit-vectors. Very efficient decision procedures are available to reason about bit-vectors. Therefore, our method is able to scale up to the verification of QFT circuits with 10,000 qubits and 50 million quantum gates, providing a meteoric advance in the size of QFT circuits thus far verified using formal verification methods.

Related papers

• QuantumSEA: In-Time Sparse Exploration for Noise Adaptive Quantum Circuits [82.50620782471485]
  QuantumSEA is an in-time sparse exploration for noise-adaptive quantum circuits. It aims to achieve two key objectives: (1) implicit circuits capacity during training and (2) noise robustness. Our method establishes state-of-the-art results with only half the number of quantum gates and 2x time saving of circuit executions.
  arXiv  Detail & Related papers  (2024-01-10T22:33:00Z)
• Enhancing variational quantum state diagonalization using reinforcement learning techniques [1.583327010995414]
  We tackle the problem of designing a very shallow quantum circuit, required in the quantum state diagonalization task. We use a novel encoding method for the RL-state, a dense reward function, and an $epsilon$-greedy policy to achieve this. We demonstrate that the circuits proposed by the reinforcement learning methods are shallower than the standard variational quantum state diagonalization algorithm.
  arXiv  Detail & Related papers  (2023-06-19T17:59:04Z)
• Quantum process tomography of continuous-variable gates using coherent states [49.299443295581064]
  We demonstrate the use of coherent-state quantum process tomography (csQPT) for a bosonic-mode superconducting circuit. We show results for this method by characterizing a logical quantum gate constructed using displacement and SNAP operations on an encoded qubit.
  arXiv  Detail & Related papers  (2023-03-02T18:08:08Z)
• GASP -- A Genetic Algorithm for State Preparation [0.0]
  We present a genetic algorithm for state preparation (GASP) which generates relatively low-depth quantum circuits for initialising a quantum computer in a specified quantum state. GASP can produce more efficient circuits of a given accuracy with lower depth and gate counts than other methods.
  arXiv  Detail & Related papers  (2023-02-22T04:41:01Z)
• Efficient estimation of trainability for variational quantum circuits [43.028111013960206]
  We find an efficient method to compute the cost function and its variance for a wide class of variational quantum circuits. This method can be used to certify trainability for variational quantum circuits and explore design strategies that can overcome the barren plateau problem.
  arXiv  Detail & Related papers  (2023-02-09T14:05:18Z)
• A quantum Fourier transform (QFT) based note detection algorithm [0.0]
  In quantum information processing, the quantum transform (QFT) has a plethora of applications. We create a quantum music note detection algorithm both on a simulated and a real quantum computer.
  arXiv  Detail & Related papers  (2022-04-25T16:45:56Z)
• Quantum circuit debugging and sensitivity analysis via local inversions [62.997667081978825]
  We present a technique that pinpoints the sections of a quantum circuit that affect the circuit output the most. We demonstrate the practicality and efficacy of the proposed technique by applying it to example algorithmic circuits implemented on IBM quantum machines.
  arXiv  Detail & Related papers  (2022-04-12T19:39:31Z)
• Circuit Symmetry Verification Mitigates Quantum-Domain Impairments [69.33243249411113]
  We propose circuit-oriented symmetry verification that are capable of verifying the commutativity of quantum circuits without the knowledge of the quantum state. In particular, we propose the Fourier-temporal stabilizer (STS) technique, which generalizes the conventional quantum-domain formalism to circuit-oriented stabilizers.
  arXiv  Detail & Related papers  (2021-12-27T21:15:35Z)
• Proof-of-principle experimental demonstration of quantum gate verification [1.9852463786440127]
  Recently, a scheme called quantum gate verification (QGV) has been proposed, which can verifies quantum gates with near-optimal efficiency. We show that for a single-qubit quantum gate, only $sim300$ samples are needed to confirm the fidelity of the quantum gate to be at least $97%$ with a $99%$ confidence level. The QGV method has the potential to be widely used for the evaluation of quantum devices in various quantum information applications.
  arXiv  Detail & Related papers  (2021-07-28T16:20:27Z)
• QUANTIFY: A framework for resource analysis and design verification of quantum circuits [69.43216268165402]
  QUANTIFY is an open-source framework for the quantitative analysis of quantum circuits. It is based on Google Cirq and is developed with Clifford+T circuits in mind. For benchmarking purposes QUANTIFY includes quantum memory and quantum arithmetic circuits.
  arXiv  Detail & Related papers  (2020-07-21T15:36:25Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.