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Many quantum algorithms, including recently proposed hybrid classical/quantum algorithms, make use of restricted tomography of the quantum state that measures the reduced density matrices, or marginals, of the full state. The most…

Quantum Physics · Physics 2018-05-16 Nicholas C. Rubin , Ryan Babbush , Jarrod McClean

Quantum metrology explores quantum effects to improve the measurement accuracy of some physical quantities beyond the classical limit. However, due to the interaction between the system and the environment, the decoherence can significantly…

Quantum Physics · Physics 2024-05-07 Cheng-Ge Liu , Cong-Wei Lu , Na-Na Zhang , Qing Ai

We characterize good clocks, which are naturally subject to fluctuations, in statistical terms. We also obtain the master equation that governs the evolution of quantum systems according to these clocks and find its general solution. This…

Quantum Physics · Physics 2009-10-31 Inigo L. Egusquiza , Luis J. Garay , Jose M. Raya

Characterising the time over which quantum coherence survives is critical for any implementation of quantum bits, memories and sensors. The usual method for determining a quantum system's decoherence rate involves a suite of experiments…

Identifying and extracting the past information relevant to the future behaviour of stochastic processes is a central task in the quantitative sciences. Quantum models offer a promising approach to this, allowing for accurate simulation of…

Quantum Physics · Physics 2019-06-26 Qing Liu , Thomas. J. Elliott , Felix. C. Binder , Carlo Di Franco , Mile Gu

We present a quantum algorithm to estimate parameters at the quantum metrology limit using deterministic quantum computation with one bit. When the interactions occurring in a quantum system are described by a Hamiltonian $H= \theta H_0$,…

Quantum Physics · Physics 2008-07-03 Rolando D. Somma , Sergio Boixo

Simulating the time-evolution of quantum mechanical systems is BQP-hard and expected to be one of the foremost applications of quantum computers. We consider classical algorithms for the approximation of Hamiltonian dynamics using…

We discuss the procedure for obtaining measurement-based implementations of quantum algorithms given by quantum circuit diagrams and how to reduce the required resources needed for a given measurement-based computation. This forms the…

Quantum Physics · Physics 2023-07-25 F. K. Marqversen , N. T. Zinner

We present a classical algorithm for simulating universal quantum circuits composed of "free" nearest-neighbour matchgates or equivalently fermionic-linear-optical (FLO) gates, and "resourceful" non-Gaussian gates. We achieve the promotion…

Quantum Physics · Physics 2024-12-11 Oliver Reardon-Smith , Michał Oszmaniec , Kamil Korzekwa

Existing approaches to analogue quantum simulations of time-dependent quantum systems rely on perturbative corrections to quantum simulations of time-independent quantum systems. We overcome this restriction to perturbative treatments with…

Quantum Physics · Physics 2024-02-13 Boyuan Shi , Florian Mintert

We propose a gate-based Quantum Genetic Algorithm (QGA) for real-valued global optimization. In this model, individuals are represented by quantum circuits whose measurement outcomes are decoded into real-valued vectors through binary…

Quantum Physics · Physics 2025-11-10 Leandro C. Souza , Laurent E. Dardenne , Renato Portugal

Simulating dynamics of physical systems is a key application of quantum computing, with potential impact in fields such as condensed matter physics and quantum chemistry. However, current quantum algorithms for Hamiltonian simulation yield…

Calibrating the role of entanglement in quantum algorithms is a crucial task in the development of quantum computing. Most existing studies have primarily focused on how the static properties of entanglement-such as its magnitude and…

Quantum Physics · Physics 2026-04-28 Chunxiao Du , Yang Zhou , Zhichen Huang , Rui Li , Zheng Qin , Shikun Zhang , Zhisong Xiao

Quantum simulation, the simulation of quantum processes on quantum computers, suggests a path forward for the efficient simulation of problems in condensed-matter physics, quantum chemistry, and materials science. While the majority of…

Quantum Physics · Physics 2022-10-03 Paul K. Faehrmann , Mark Steudtner , Richard Kueng , Maria Kieferova , Jens Eisert

The temporal evolution of a quantum system can be characterized by quantum process tomography, a complex task that consumes a number of physical resources scaling exponentially with the number of subsystems. An alternative approach to the…

Iterative phase estimation has long been used in quantum computing to estimate Hamiltonian eigenvalues. This is done by applying many repetitions of the same fundamental simulation circuit to an initial state, and using statistical…

Quantum Physics · Physics 2019-07-25 Ian D. Kivlichan , Christopher E. Granade , Nathan Wiebe

We consider unitary dynamical evolutions on n qubits caused by time dependent pair-interaction Hamiltonians and show that the running time of a parallelized two-qubit gate network simulating the evolution is given by the time integral over…

Quantum Physics · Physics 2009-11-06 Dominik Janzing , Thomas Beth

We propose genetic algorithms, which are robust optimization techniques inspired by natural selection, to enhance the versatility of digital quantum simulations. In this sense, we show that genetic algorithms can be employed to increase the…

Quantum Physics · Physics 2016-06-22 U. Las Heras , U. Alvarez-Rodriguez , E. Solano , M. Sanz

Mid-circuit measurements and measurement-controlled gates are supported by an increasing number of quantum hardware platforms and will become more relevant as an essential building block for quantum error correction. However, mid-circuit…

Quantum Physics · Physics 2025-02-27 Yanbin Chen , Innocenzo Fulginiti , Christian B. Mendl

Quantum control is valuable for various quantum technologies such as high-fidelity gates for universal quantum computing, adaptive quantum-enhanced metrology, and ultra-cold atom manipulation. Although supervised machine learning and…

Machine Learning · Computer Science 2017-09-06 Pantita Palittapongarnpim , Peter Wittek , Ehsan Zahedinejad , Shakib Vedaie , Barry C. Sanders
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