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Related papers: Adaptive projected variational quantum dynamics

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We introduce a variational hybrid classical-quantum algorithm to simulate the Lindblad master equation and its adjoint for time-evolving Markovian open quantum systems and quantum observables. Our method is based on a direct representation…

Quantum Physics · Physics 2023-05-19 Tasneem Watad , Netanel H. Lindner

Current quantum simulators suffer from multiple limitations such as short coherence time, noisy operations, faulty readout and restricted qubit connectivity in some platforms. Variational quantum algorithms are the most promising approach…

Quantum Physics · Physics 2023-05-31 Chufan Lyu , Xiaoyu Tang , Junning Li , Xusheng Xu , Man-Hong Yung , Abolfazl Bayat

Adaptive variational quantum simulation algorithms use information from the quantum computer to dynamically create optimal trial wavefunctions for a given problem Hamiltonian. A key ingredient in these algorithms is a predefined operator…

Electronic structure simulation is an anticipated application for quantum computers. Due to high-dimensional quantum entanglement in strongly correlated systems, the quantum resources required to perform such simulations are far beyond the…

Quantum Physics · Physics 2022-01-25 Jie Liu , Zhenyu Li , Jinlong Yang

Highly excited states of quantum many-body systems are central objects in the study of quantum dynamics and thermalization that challenge classical computational methods due to their volume-law entanglement content. In this work, we explore…

Quantum Physics · Physics 2022-02-17 Feng Zhang , Niladri Gomes , Yongxin Yao , Peter P. Orth , Thomas Iadecola

The relative power of quantum algorithms, using an adaptive access to quantum devices, versus classical post-processing methods that rely only on an initial quantum data set, remains the subject of active debate. Here, we present evidence…

Quantum Physics · Physics 2025-10-02 Oleksandr Kyriienko , Chukwudubem Umeano , Zoë Holmes

Variational Quantum Algorithms are among the most promising systems to implement quantum computing under the Noisy-Intermediate Scale Quantum (NISQ) technology. In variational quantum algorithm, wavefunction represented by a parametrized…

Quantum Physics · Physics 2023-01-02 H. Davoodi Yeganeh

Classical algorithms for predicting the equilibrium geometry of strongly correlated molecules require expensive wave function methods that become impractical already for few-atom systems. In this work, we introduce a variational quantum…

Variational quantum metrology represents a powerful tool for optimizing generic estimation strategies, combining the principles of variational optimization with the techniques of quantum metrology. Such optimization procedures result…

We present adaptive measurement techniques tailored for variational quantum algorithms on near-term small and noisy devices. In particular, we generalise earlier "learning to measure" strategies in two ways. First, by considering a class of…

The quantum approximate optimisation algorithm was proposed as a heuristic method for solving combinatorial optimisation problems on near-term quantum computers and may be among the first algorithms to perform useful computations in the…

Quantum Physics · Physics 2022-11-10 David Headley , Thorge Müller , Ana Martin , Enrique Solano , Mikel Sanz , Frank K. Wilhelm

Variational quantum algorithms are a class of techniques intended to be used on near-term quantum computers. The goal of these algorithms is to perform large quantum computations by breaking the problem down into a large number of shallow…

Quantum Physics · Physics 2023-03-24 Ryan Shaffer , Lucas Kocia , Mohan Sarovar

Digital quantum simulation (DQS) of continuous-variable quantum systems in the position basis requires efficient implementation of diagonal unitaries approximating the time evolution operator generated by the potential energy function. In…

Quantum Physics · Physics 2022-12-12 Tenzan Araki , James Stokes , Shravan Veerapaneni

Digital quantum simulation relies on Trotterization to discretize time evolution into elementary quantum gates. On current quantum processors with notable gate imperfections, there is a critical tradeoff between improved accuracy for finer…

Quantum Physics · Physics 2024-07-09 Hongzheng Zhao , Marin Bukov , Markus Heyl , Roderich Moessner

Quantum parameter estimation has many applications, from gravitational wave detection to quantum key distribution. We present the first experimental demonstration of the time-symmetric technique of quantum smoothing. We consider both…

Variational quantum algorithms (VQAs), as one of the most promising routes in the noisy intermediate-scale quantum (NISQ) era, offer various potential applications while also confront severe challenges due to near-term quantum hardware…

Quantum Physics · Physics 2024-12-12 Shi-Xin Zhang , Jiaqi Miao , Chang-Yu Hsieh

Adaptive quantum variational algorithms are particularly promising for simulating strongly correlated systems on near-term quantum hardware, but they are not yet viable due, in large part, to the severe coherence time limitations on current…

We present an empirical analysis of the scaling of the minimal quantum circuit depth required for a variational quantum simulation (VQS) method to obtain a solution to the time evolution of a quantum system within a predefined error…

Quantum Physics · Physics 2026-04-14 Mario Ponce , Thomas Cope , Inés de Vega , Martin Leib

Variational quantum algorithms (VQAs) represent a promising approach to utilizing current quantum computing infrastructures. VQAs are based on a parameterized quantum circuit optimized in a closed loop via a classical algorithm. This hybrid…

Quantum Physics · Physics 2024-04-10 David Fitzek , Robert S. Jonsson , Werner Dobrautz , Christian Schäfer

We devise powerful algorithms based on differential evolution for adaptive many-particle quantum metrology. Our new approach delivers adaptive quantum metrology policies for feedback control that are orders-of-magnitude more efficient and…

Quantum Physics · Physics 2013-06-04 Neil B. Lovett , Cécile Crosnier , Martí Perarnau-Llobet , Barry C. Sanders