HOPPS: Hardware-Aware Optimal Phase Polynomial Synthesis with Blockwise Optimization for Quantum Circuits

• URL: http://arxiv.org/abs/2511.18770v1
• Date: Mon, 24 Nov 2025 05:07:32 GMT
• Title: HOPPS: Hardware-Aware Optimal Phase Polynomial Synthesis with Blockwise Optimization for Quantum Circuits
• Authors: Xinpeng Li, Ji Liu, Shuai Xu, Paul Hovland, Vipin Chaudhary,
• Abstract summary: We introduce HOPPS: a hardware-aware optimal phase synthesis algorithm.<n>CNOT, Rz blocks with CNOT count or depth optimality could be generated.<n>For large QAOA circuit, after mapping by Qiskit, circuit can be reduced CNOT count and depth by up to 44.4% and 42.4%.
• Score: 14.068472784717294
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Blocks composed of {CNOT, Rz} are ubiquitous in modern quantum applications, notably in circuits such as QAOA ansatzes and quantum adders. After compilation, many of them exhibit large CNOT counts or depths, which lowers fidelity. Therefore, we introduce HOPPS: a SAT-based hardware-aware optimal phase polynomial synthesis algorithm that could generate {CNOT, Rz} blocks with CNOT count or depth optimality. Sometime {CNOT, Rz} blocks are large, such as in QAOA ansatzes, HOPPS's pursuit of optimality limits its scalability. To address this issue, we introduce an iterative blockwise optimization strategy: large circuits are partitioned into smaller blocks, each block is optimally refined, and the process is repeated for several iterations. Empirical results show that HOPPS is more efficient comparing with existing near optimal synthesis tools. Used as a peephole optimizer, HOPPS reduces the CNOT count by up to 50.0% and the CNOT depth by up to 57.1% under OLSQ. For large QAOA circuit, after mapping by Qiskit, circuit can be reduced CNOT count and depth by up to 44.4% and 42.4% by our iterative blockwise optimization. Index Terms-Phase Polynomial, Quantum Circuit Synthesis, Quantum Circuit Optimization.

Related papers

• Optimization and Synthesis of Quantum Circuits with Global Gates [41.99844472131922]
  We use global interactions, such as the Global Molmer-Sorensen gate present in ion trap hardware, to optimize and synthesize quantum circuits.<n>The algorithm is based on the ZX-calculus and uses a specialized circuit extraction routine that groups entangling gates into Global MolmerSorensen gates.<n>We benchmark the algorithm in a variety of circuits, and show how it improves their performance under state-of-the-art hardware considerations.
  arXiv  Detail & Related papers  (2025-07-28T10:25:31Z)
• PhasePoly: An Optimization Framework forPhase Polynomials in Quantum Circuits [10.451992404984217]
  This paper focuses on a critical type of quantum circuit optimization -- phase-polynomial circuit optimization.<n>We show improvements of up to 50%-with an average total gate reduction of 34.92%-and reductions in the CNOT gate count of up to 48.57%, averaging 28.53%, for logical circuits.
  arXiv  Detail & Related papers  (2025-06-25T17:13:16Z)
• Optimization by Decoded Quantum Interferometry [38.063836468778895]
  We introduce Decoded Quantum Interferometry (DQI), a quantum algorithm that uses the quantum Fourier transform to reduce optimization problems to decoding problems.<n>For approximating optimal fits over finite fields, DQI achieves a superpolynomial speedup over known classical algorithms.
  arXiv  Detail & Related papers  (2024-08-15T17:47:42Z)
• Optimal Layout-Aware CNOT Circuit Synthesis with Qubit Permutation [0.0]
  CNOT optimization plays a significant role in noise reduction for Quantum Circuits. We provide optimization for both CNOT gate count and circuit depth. We show that allowing qubit permutations can further reduce up to 56% in CNOT count and 46% in circuit depth.
  arXiv  Detail & Related papers  (2024-08-08T10:20:13Z)
• Linear Circuit Synthesis using Weighted Steiner Trees [45.11082946405984]
  CNOT circuits are a common building block of general quantum circuits. This article presents state-of-the-art algorithms for optimizing the number of CNOT gates. A simulated evaluation shows that the suggested is almost always beneficial and reduces the number of CNOT gates by up to 10%.
  arXiv  Detail & Related papers  (2024-08-07T19:51:22Z)
• 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)
• Efficient DCQO Algorithm within the Impulse Regime for Portfolio Optimization [41.94295877935867]
  We propose a faster digital quantum algorithm for portfolio optimization using the digitized-counterdiabatic quantum optimization (DCQO) paradigm. Our approach notably reduces the circuit depth requirement of the algorithm and enhances the solution accuracy, making it suitable for current quantum processors. We experimentally demonstrate the advantages of our protocol using up to 20 qubits on an IonQ trapped-ion quantum computer.
  arXiv  Detail & Related papers  (2023-08-29T17:53:08Z)
• 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)
• Scaling Quantum Approximate Optimization on Near-term Hardware [49.94954584453379]
  We quantify scaling of the expected resource requirements by optimized circuits for hardware architectures with varying levels of connectivity. We show the number of measurements, and hence total time to synthesizing solution, grows exponentially in problem size and problem graph degree. These problems may be alleviated by increasing hardware connectivity or by recently proposed modifications to the QAOA that achieve higher performance with fewer circuit layers.
  arXiv  Detail & Related papers  (2022-01-06T21:02:30Z)
• Variational Quantum Optimization with Multi-Basis Encodings [62.72309460291971]
  We introduce a new variational quantum algorithm that benefits from two innovations: multi-basis graph complexity and nonlinear activation functions. Our results in increased optimization performance, two increase in effective landscapes and a reduction in measurement progress.
  arXiv  Detail & Related papers  (2021-06-24T20:16:02Z)
• 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)
• QGo: Scalable Quantum Circuit Optimization Using Automated Synthesis [3.284627771501259]
  On NISQ devices, two-qubit gates such as CNOTs are much noisier than single-qubit gates. Quantum circuit synthesis is a process of decomposing an arbitrary unitary into a sequence of quantum gates. We propose a hierarchical, block-by-block optimization framework, QGo, for quantum circuit optimization.
  arXiv  Detail & Related papers  (2020-12-17T18:54:38Z)
• Adaptive pruning-based optimization of parameterized quantum circuits [62.997667081978825]
  Variisy hybrid quantum-classical algorithms are powerful tools to maximize the use of Noisy Intermediate Scale Quantum devices. We propose a strategy for such ansatze used in variational quantum algorithms, which we call "Efficient Circuit Training" (PECT) Instead of optimizing all of the ansatz parameters at once, PECT launches a sequence of variational algorithms.
  arXiv  Detail & Related papers  (2020-10-01T18:14:11Z)

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.