Estimating quantum circuit probabilities and Hamiltonian properties using amplitude estimation

泰大 近藤, Kondo, Yasuhiro, 立平 森 +2 more

Pooja Rao, Sua Choi, Kwangmin Yu

A variant of QAE algorithm by Suzuki et al. called maximum likelihood amplitude estimation (MLAE) achieves the amplitude estimation by varying depths of Grover operators and post-processing for maximum likelihood estimation without the additional controlled operations and QFT. However, MLAE requires running multiple circuits of different depths of Grover operators. On the other hand, quantum multi-programming (QMP) is a computing method that executes multiple quantum circuits concurrently on a quantum computer. The quantum circuits executed concurrently can be different and even have different circuit depths. The main motivation of the QMP is that the number of qubits of NISQ computers is much greater than their quantum volume. In this work, using QMP in conjunction with MLAE makes it possible to run MLAE using a single circuit, thus requiring sampling much fewer times. We validate this algorithm for a numerical integration problem using NVIDIA’s open-source platform CUDA Quantum (simulator), Qiskit (simulator) and Quantinuum H2 device.

Joran van Apeldoorn

We give a multidimensional version of amplitude estimation. Let p be an n-dimensional probability distribution which can be sampled from using a quantum circuit U_p. We show that all coordinates of p can be estimated up to error ε per coordinate using Õ(1/(ε)) applications of U_p and its inverse. This generalizes the normal amplitude estimation algorithm, which solves the problem for n = 2. Our results also imply a Õ(n/ε) query algorithm for 𝓁₁-norm (the total variation distance) estimation and a Õ(√n/ε) query algorithm for 𝓁₂-norm. We also show that these results are optimal up to logarithmic factors.

Sima Esfandiarpour Borujeni, Saideep Nannapaneni, Nam H. Nguyen +2 more

Vadim Smelyanskiy, Sergio Boixo, Hrant Gharibyan +6 more

Hayata Morisaki, Kosuke Mitarai, Keisuke Fujii +1 more

We propose a method for constructing circuits for quantum phase estimation of a molecular Hamiltonian in quantum chemistry by using variational optimization of quantum circuits solely on classical computers. The circuit generates a quantum state which encodes the coefficients of the terms in the Hamiltonian as probability amplitudes and plays a crucial role in the state-of-the-art efficient implementations of quantum phase estimation. We employ the automatic quantum circuit encoding algorithm [Shirakawa , ] to construct circuits, which requires classical simulations of quantum circuits of O ( log N ) qubits with N being the number of qubits of the Hamiltonian. The generated circuits do not need any ancillary qubit. We demonstrate our method by investigating the number of T -gates of the obtained circuits for quantum chemistry Hamiltonians of various molecules, which shows a constant-factor reduction compared to previous approaches that do not use ancillary qubits. Since the number of available logical qubits and T gates will be limited at the early stage of the fault-tolerant quantum computing, the proposed method is particularly of use for performing the quantum phase estimation with such limited capability. Published by the American Physical Society 2024