QFAST: Conflating Search and Numerical Optimization for Scalable Quantum Circuit Synthesis

• URL: http://arxiv.org/abs/2103.07093v1
• Date: Fri, 12 Mar 2021 05:20:12 GMT
• Title: QFAST: Conflating Search and Numerical Optimization for Scalable Quantum Circuit Synthesis
• Authors: Ed Younis, Koushik Sen, Katherine Yelick, Costin Iancu
• Abstract summary: We present a quantum synthesis algorithm designed to produce short circuits and to scale well in practice. Main contribution is a novel representation of circuits able to encode placement and topology using generic "gates" When compared against optimal depth, search based state-of-the-art techniques, QFAST produces comparable results.
• Score: 5.406226763868874
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: We present a quantum synthesis algorithm designed to produce short circuits and to scale well in practice. The main contribution is a novel representation of circuits able to encode placement and topology using generic "gates", which allows the QFAST algorithm to replace expensive searches over circuit structures with few steps of numerical optimization. When compared against optimal depth, search based state-of-the-art techniques, QFAST produces comparable results: 1.19x longer circuits up to four qubits, with an increase in compilation speed of 3.6x. In addition, QFAST scales up to seven qubits. When compared with the state-of-the-art "rule" based decomposition techniques in Qiskit, QFAST produces circuits shorter by up to two orders of magnitude (331x), albeit 5.6x slower. We also demonstrate the composability with other techniques and the tunability of our formulation in terms of circuit depth and running time.

Related papers

• Quantum Compiling with Reinforcement Learning on a Superconducting Processor [55.135709564322624]
  We develop a reinforcement learning-based quantum compiler for a superconducting processor. We demonstrate its capability of discovering novel and hardware-amenable circuits with short lengths. Our study exemplifies the codesign of the software with hardware for efficient quantum compilation.
  arXiv  Detail & Related papers  (2024-06-18T01:49:48Z)
• 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)
• Tractable Bounding of Counterfactual Queries by Knowledge Compilation [51.47174989680976]
  We discuss the problem of bounding partially identifiable queries, such as counterfactuals, in Pearlian structural causal models. A recently proposed iterated EM scheme yields an inner approximation of those bounds by sampling the initialisation parameters. We show how a single symbolic knowledge compilation allows us to obtain the circuit structure with symbolic parameters to be replaced by their actual values.
  arXiv  Detail & Related papers  (2023-10-05T07:10:40Z)
• A SAT Encoding for Optimal Clifford Circuit Synthesis [3.610459670994051]
  We consider the optimal synthesis of Clifford circuits -- an important subclass of quantum circuits. We propose an optimal synthesis method for Clifford circuits based on encoding the task as a satisfiability problem. The resulting tool is demonstrated to synthesize optimal circuits for up to $26$ qubits.
  arXiv  Detail & Related papers  (2022-08-24T18:00:03Z)
• Wide Quantum Circuit Optimization with Topology Aware Synthesis [0.8469686352132708]
  Unitary synthesis is an optimization technique that can achieve optimal multi-qubit gate counts while mapping quantum circuits to restrictive qubit topologies. We present TopAS, a topology aware synthesis tool built with the emphBQSKit framework that preconditions quantum circuits before mapping.
  arXiv  Detail & Related papers  (2022-06-27T21:59:30Z)
• A Structured Method for Compilation of QAOA Circuits in Quantum Computing [5.560410979877026]
  The flexibility in reordering the two-qubit gates allows compiler optimizations to generate circuits with better depths, gate count, and fidelity. We propose a structured method that ensures linear depth for any compiled QAOA circuit on multi-dimensional quantum architectures. Overall, we can compile a circuit with up to 1024 qubits in 10 seconds with a 3.8X speedup in depth, 17% reduction in gate count, and 18X improvement for circuit ESP.
  arXiv  Detail & Related papers  (2021-12-12T04:00:45Z)
• Fast Swapping in a Quantum Multiplier Modelled as a Queuing Network [64.1951227380212]
  We propose that quantum circuits can be modeled as queuing networks. Our method is scalable and has the potential speed and precision necessary for large scale quantum circuit compilation.
  arXiv  Detail & Related papers  (2021-06-26T10:55:52Z)
• LEAP: Scaling Numerical Optimization Based Synthesis Using an Incremental Approach [0.9297355862757838]
  The LEAP algorithm improves scaling across dimensions using iterative circuit synthesis, incremental re-optimization, dimensionality reduction, and improved numerical optimization. LEAP was evaluated with known quantum circuits such as QFT and physical simulation circuits like the VQE, TFIM, and QITE.
  arXiv  Detail & Related papers  (2021-06-21T16:44:53Z)
• Machine Learning Optimization of Quantum Circuit Layouts [63.55764634492974]
  We introduce a quantum circuit mapping, QXX, and its machine learning version, QXX-MLP. The latter infers automatically the optimal QXX parameter values such that the layed out circuit has a reduced depth. We present empiric evidence for the feasibility of learning the layout method using approximation.
  arXiv  Detail & Related papers  (2020-07-29T05:26:19Z)
• 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)
• QFAST: Quantum Synthesis Using a Hierarchical Continuous Circuit Space [5.406226763868874]
  We present QFAST, a quantum synthesis tool designed to produce short circuits. We show how to generate shorter circuits by plugging in the best available third party synthesis algorithm at a given hierarchy level.
  arXiv  Detail & Related papers  (2020-03-09T23:55:43Z)

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.