This paper proposes a method of quantum Monte Carlo integration that retains the full quadratic quantum advantage, without requiring any arithmetic or quantum phase estimation to be performed on the quantum computer. No previous proposal for quantum Monte Carlo integration has achieved all of these at once. The heart of the proposed method is a Fourier series decomposition of the sum that approximates the expectation in Monte Carlo integration, with each component then estimated individually using quantum amplitude estimation. The main result is presented as theoretical statement of asymptotic advantage, and numerical results are also included to illustrate the practical benefits of the proposed method. The method presented in this paper is...
Recently, a variety of quantum algorithms have been devised to estimate thermal averages on a genuin...
We present efficient methods to interpolate data with a quantum computer that complement uploading t...
We reexamine some fundamental Quantum Monte Carlo (QMC) algorithms with the goal of making QMC more ...
Monte Carlo integration is a widely used numerical method for approximating integrals, which is ofte...
Quantum computing and quantum Monte Carlo (QMC) are respectively the state-of-the-art quantum and cl...
Quantum computing is a promising way to systematically solve the longstanding computational problem,...
Quantum computing was so far mainly concerned with discrete problems. Recently, E. Novak and the aut...
A quantum implementation of the Stochastic Series Expansion (SSE) Monte Carlo method is proposed, an...
Present-day, noisy, small or intermediate-scale quantum processors-although far from fault tolerant-...
We introduce a variant of Quantum Amplitude Estimation (QAE), called Iterative QAE (IQAE), which doe...
Quantum computers are actively competing to surpass classical supercomputers, but quantum errors rem...
Outcome probability estimation via classical methods is an important task for validating quantum com...
Amplitude estimation algorithms are based on Grover's algorithm: alternating reflections about the i...
We apply quantum integration to elementary particle-physics processes. In particular, we look at sca...
The paper presents an introductory and general discussion on the quantum Monte Carlo methods, some f...
Recently, a variety of quantum algorithms have been devised to estimate thermal averages on a genuin...
We present efficient methods to interpolate data with a quantum computer that complement uploading t...
We reexamine some fundamental Quantum Monte Carlo (QMC) algorithms with the goal of making QMC more ...
Monte Carlo integration is a widely used numerical method for approximating integrals, which is ofte...
Quantum computing and quantum Monte Carlo (QMC) are respectively the state-of-the-art quantum and cl...
Quantum computing is a promising way to systematically solve the longstanding computational problem,...
Quantum computing was so far mainly concerned with discrete problems. Recently, E. Novak and the aut...
A quantum implementation of the Stochastic Series Expansion (SSE) Monte Carlo method is proposed, an...
Present-day, noisy, small or intermediate-scale quantum processors-although far from fault tolerant-...
We introduce a variant of Quantum Amplitude Estimation (QAE), called Iterative QAE (IQAE), which doe...
Quantum computers are actively competing to surpass classical supercomputers, but quantum errors rem...
Outcome probability estimation via classical methods is an important task for validating quantum com...
Amplitude estimation algorithms are based on Grover's algorithm: alternating reflections about the i...
We apply quantum integration to elementary particle-physics processes. In particular, we look at sca...
The paper presents an introductory and general discussion on the quantum Monte Carlo methods, some f...
Recently, a variety of quantum algorithms have been devised to estimate thermal averages on a genuin...
We present efficient methods to interpolate data with a quantum computer that complement uploading t...
We reexamine some fundamental Quantum Monte Carlo (QMC) algorithms with the goal of making QMC more ...