Automated Quantum Algorithm Synthesis

• URL: http://arxiv.org/abs/2503.08449v2
• Date: Wed, 12 Mar 2025 08:25:14 GMT
• Title: Automated Quantum Algorithm Synthesis
• Authors: Amy Rouillard, Matt Lourens, Francesco Petruccione,
• Abstract summary: We present a method to automatically design the n-qubit realisations of quantum algorithms.<n>We learn the algorithm structure rather than a specific unitary implementation.<n>Our method proves robust, as it maintains performance across increasingly large search spaces.
• Score: 0.0
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: We present a computational method to automatically design the n-qubit realisations of quantum algorithms. Our approach leverages a domain-specific language (DSL) that enables the construction of quantum circuits via modular building blocks, making it well-suited for evolutionary search. In this DSL quantum circuits are abstracted beyond the usual gate-sequence description and scale automatically to any problem size. This enables us to learn the algorithm structure rather than a specific unitary implementation. We demonstrate our method by automatically designing three known quantum algorithms--the Quantum Fourier Transform, the Deutsch-Jozsa algorithm, and Grover's search. Remarkably, we were able to learn the general implementation of each algorithm by considering examples of circuits containing at most 5-qubits. Our method proves robust, as it maintains performance across increasingly large search spaces. Convergence to the relevant algorithm is achieved with high probability and with moderate computational resources.

Related papers

• Connectivity-aware Synthesis of Quantum Algorithms [0.0]
  We present a general method for the implementation of quantum algorithms that optimize both gate count and circuit depth.<n>Our approach introduces connectivity-adapted CNOT-based building blocks called Parity Twine chains.
  arXiv  Detail & Related papers  (2025-01-23T19:00:01Z)
• Quantum Subroutine for Variance Estimation: Algorithmic Design and Applications [80.04533958880862]
  Quantum computing sets the foundation for new ways of designing algorithms. New challenges arise concerning which field quantum speedup can be achieved. Looking for the design of quantum subroutines that are more efficient than their classical counterpart poses solid pillars to new powerful quantum algorithms.
  arXiv  Detail & Related papers  (2024-02-26T09:32:07Z)
• Quantum Circuit Optimization with AlphaTensor [47.9303833600197]
  We develop AlphaTensor-Quantum, a method to minimize the number of T gates that are needed to implement a given circuit. Unlike existing methods for T-count optimization, AlphaTensor-Quantum can incorporate domain-specific knowledge about quantum computation and leverage gadgets. Remarkably, it discovers an efficient algorithm akin to Karatsuba's method for multiplication in finite fields.
  arXiv  Detail & Related papers  (2024-02-22T09:20:54Z)
• Generalized quantum Arimoto-Blahut algorithm and its application to quantum information bottleneck [55.22418739014892]
  We generalize the quantum Arimoto-Blahut algorithm by Ramakrishnan et al. We apply our algorithm to the quantum information bottleneck with three quantum systems. Our numerical analysis shows that our algorithm is better than their algorithm.
  arXiv  Detail & Related papers  (2023-11-19T00:06:11Z)
• QArchSearch: A Scalable Quantum Architecture Search Package [1.725192300740999]
  We present textttQArchSearch, an AI based quantum architecture search package with the textttQTensor library as a backend. We show that the search package is able to efficiently scale the search to large quantum circuits and enables the exploration of more complex models for different quantum applications.
  arXiv  Detail & Related papers  (2023-10-11T20:00:33Z)
• Riemannian quantum circuit optimization for Hamiltonian simulation [2.1227079314039057]
  Hamiltonian simulation is a natural application of quantum computing. For translation invariant systems, the gates in such circuit topologies can be further optimized on classical computers. For the Ising and Heisenberg models on a one-dimensional lattice, we achieve orders of magnitude accuracy improvements.
  arXiv  Detail & Related papers  (2022-12-15T00:00:17Z)
• Quantum Clustering with k-Means: a Hybrid Approach [117.4705494502186]
  We design, implement, and evaluate three hybrid quantum k-Means algorithms. We exploit quantum phenomena to speed up the computation of distances. We show that our hybrid quantum k-Means algorithms can be more efficient than the classical version.
  arXiv  Detail & Related papers  (2022-12-13T16:04:16Z)
• Entanglement and coherence in Bernstein-Vazirani algorithm [58.720142291102135]
  Bernstein-Vazirani algorithm allows one to determine a bit string encoded into an oracle. We analyze in detail the quantum resources in the Bernstein-Vazirani algorithm. We show that in the absence of entanglement, the performance of the algorithm is directly related to the amount of quantum coherence in the initial state.
  arXiv  Detail & Related papers  (2022-05-26T20:32:36Z)
• Synthesis of Quantum Circuits with an Island Genetic Algorithm [44.99833362998488]
  Given a unitary matrix that performs certain operation, obtaining the equivalent quantum circuit is a non-trivial task. Three problems are explored: the coin for the quantum walker, the Toffoli gate and the Fredkin gate. The algorithm proposed proved to be efficient in decomposition of quantum circuits, and as a generic approach, it is limited only by the available computational power.
  arXiv  Detail & Related papers  (2021-06-06T13:15:25Z)
• ACSS-q: Algorithmic complexity for short strings via quantum accelerated approach [1.4873907857806357]
  We present a quantum circuit for estimating algorithmic complexity using the coding theorem method. As a use-case, an application framework for protein-protein interaction based on algorithmic complexity is proposed.
  arXiv  Detail & Related papers  (2020-09-18T14:41:41Z)
• Improving the Performance of Deep Quantum Optimization Algorithms with Continuous Gate Sets [47.00474212574662]
  Variational quantum algorithms are believed to be promising for solving computationally hard problems. In this paper, we experimentally investigate the circuit-depth-dependent performance of QAOA applied to exact-cover problem instances. Our results demonstrate that the use of continuous gate sets may be a key component in extending the impact of near-term quantum computers.
  arXiv  Detail & Related papers  (2020-05-11T17:20:51Z)
• Topological Quantum Compiling with Reinforcement Learning [7.741584909637626]
  We introduce an efficient algorithm that compiles an arbitrary single-qubit gate into a sequence of elementary gates from a finite universal set. Our algorithm may carry over to other challenging quantum discrete problems, thus opening up a new avenue for intriguing applications of deep learning in quantum physics.
  arXiv  Detail & Related papers  (2020-04-09T18:00:01Z)

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.