Results 41 to 50 of about 96,436 (259)
Quantum-assisted Monte Carlo algorithms for fermions [PDF]
Quantum, 2023 Quantum computing is a promising way to systematically solve the longstanding computational problem, the ground state of a many-body fermion system. Many efforts have been made to realise certain forms of quantum advantage in this problem, for instance ...
Xiaosi Xu, Ying Li
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PRX Quantum, 2022 Under suitable assumptions, some recently developed quantum algorithms can estimate the ground-state energy and prepare the ground state of a quantum Hamiltonian with near-optimal query complexities. However, this is based on a block-encoding input model
Yulong Dong, Lin Lin, Yu Tong
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Quantum integration of elementary particle processes
Physics Letters B, 2022 We apply quantum integration to elementary particle-physics processes. In particular, we look at scattering processes such as e+e−→qq¯ and e+e−→qq¯′W.
Gabriele Agliardi +3 more
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Adaptive Algorithm for Quantum Amplitude Estimation
, 2022 Quantum amplitude estimation is a key sub-routine of a number of quantum algorithms with various applications. We propose an adaptive algorithm for interval estimation of amplitudes. The quantum part of the algorithm is based only on Grover's algorithm.
Zhao, Yunpeng +5 more
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Quantum advantage of Monte Carlo option pricing
Journal of Physics Communications, 2023 Quantum computers have the potential to provide quadratic speedup for Monte Carlo methods currently used in various classical applications. In this work, we examine the advantage of quantum computers for financial option pricing with the Monte Carlo ...
Zoltán Udvarnoki +2 more
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Joint quantum estimation of loss and nonlinearity in driven-dissipative Kerr resonators
Physical Review Research, 2023 We address multiparameter quantum estimation for coherently driven nonlinear Kerr resonators in the presence of loss. In particular, we consider the realistic situation in which the parameters of interest are the loss rate and the nonlinear coupling ...
Muhammad Asjad +2 more
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Optimal polynomial based quantum eigenstate filtering with application to solving quantum linear systems [PDF]
Quantum, 2020 We present a quantum eigenstate filtering algorithm based on quantum signal processing (QSP) and minimax polynomials. The algorithm allows us to efficiently prepare a target eigenstate of a given Hamiltonian, if we have access to an initial state with ...
Lin Lin, Yu Tong
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Recovery With Incomplete Knowledge: Fundamental Bounds on Real-Time Quantum Memories [PDF]
Quantum, 2023 The recovery of fragile quantum states from decoherence is the basis of building a quantum memory, with applications ranging from quantum communications to quantum computing.
Arshag Danageozian
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Quantum Amplitude Estimation in the Presence of Noise
, 2020 Quantum Amplitude Estimation (QAE) -- a technique by which the amplitude of a given quantum state can be estimated with quadratically fewer queries than by standard sampling -- is a key sub-routine in several important quantum algorithms, including Grover search and Quantum Monte-Carlo methods.
Brown, Eric G. +2 more
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Grand Unification of Quantum Algorithms
PRX Quantum, 2021 Quantum algorithms offer significant speed-ups over their classical counterparts for a variety of problems. The strongest arguments for this advantage are borne by algorithms for quantum search, quantum phase estimation, and Hamiltonian simulation, which
John M. Martyn +3 more
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