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We propose a method for constructing $\texttt{PREPARE}$ circuits for quantum phase estimation of a molecular Hamiltonian in quantum chemistry by using variational optimization of quantum circuits solely on classical computers. The…

Quantum Physics · Physics 2025-05-02 Hayata Morisaki , Kosuke Mitarai , Keisuke Fujii , Yuya O. Nakagawa

Quantum computing has long promised transformative advances in data analysis, yet practical quantum machine learning has remained elusive due to fundamental obstacles such as a steep quantum cost for the loading of classical data and poor…

Hamiltonian learning is an important procedure in quantum system identification, calibration, and successful operation of quantum computers. Through queries to the quantum system, this procedure seeks to obtain the parameters of a given…

Quantum Physics · Physics 2023-08-25 Arkopal Dutt , Edwin Pednault , Chai Wah Wu , Sarah Sheldon , John Smolin , Lev Bishop , Isaac L. Chuang

The preparation of the ground state of a Hamiltonian $H$ with a large spectral radius has applications in many areas such as electronic structure theory and quantum field theory. Given an initial state with a constant overlap with the…

Quantum Physics · Physics 2024-06-05 Yulong Dong , Lin Lin

We study the problems of state preparation, ground state preparation and quantum state preparation. We propose an analytic approach to a stochastic quantum algorithm which prepares the ground state for $n$-qubit Hamiltonian that is…

Quantum Physics · Physics 2025-12-02 Taehee Ko , Sungbin Lim

Quantum state preparation (QSP) for a general $n$-qubit state requires $O(2^n)$ CNOT gates and circuit depth, making exact amplitude encoding (EAE) impractical for near-term quantum hardware. We introduce an ancilla-free hybrid…

Quantum Physics · Physics 2025-12-02 Emad Rezaei Fard Boosari , Maryam Afsary

Quantum algorithms for probing ground-state properties of quantum systems require good initial states. Projection-based methods such as eigenvalue filtering rely on inputs that have a significant overlap with the low-energy subspace, which…

Quantum Physics · Physics 2024-04-10 Danial Motlagh , Modjtaba Shokrian Zini , Juan Miguel Arrazola , Nathan Wiebe

Efficiently characterising quantum systems, verifying operations of quantum devices and validating underpinning physical models, are central challenges for the development of quantum technologies and for our continued understanding of…

Many-body ground state preparation is an important subroutine used in the simulation of physical systems. In this paper, we introduce a flexible and efficient framework for obtaining a state preparation circuit for a large class of…

Quantum Physics · Physics 2024-11-05 Hyun-Soo Kim , Isaac H. Kim , Daniel Ranard

Based on the linearity of quantum unitary operations, we propose a method that runs the parameterized quantum circuits before encoding the input data. This enables a dataset owner to train machine learning models on quantum cloud…

Quantum Physics · Physics 2024-10-10 Guang Ping He

We present a method that outputs a sequence of simple unitary operations to prepare a given quantum state that is a generalized coherent state. Our method takes as inputs the expectation values of some relevant observables on the state to…

Quantum Physics · Physics 2020-01-08 Rolando D. Somma

Quantum algorithms on the noisy intermediate-scale quantum (NISQ) devices are expected to simulate quantum systems that are classically intractable to demonstrate quantum advantages. However, the non-negligible gate error on the NISQ…

Quantum Physics · Physics 2021-12-06 Joseph C. Aulicino , Trevor Keen , Bo Peng

With the fast development of quantum technology, the sizes of both digital and analog quantum systems increase drastically. In order to have better control and understanding of the quantum hardware, an important task is to characterize the…

Quantum Physics · Physics 2023-07-05 Wenjun Yu , Jinzhao Sun , Zeyao Han , Xiao Yuan

A computation in adiabatic quantum computing is implemented by traversing a path of nondegenerate eigenstates of a continuous family of Hamiltonians. We introduce a method that traverses a discretized form of the path: At each step we apply…

Quantum Physics · Physics 2009-08-14 S. Boixo , E. Knill , R. D. Somma

Over the last century, a large number of physical and mathematical developments paired with rapidly advancing technology have allowed the field of quantum chemistry to advance dramatically. However, the lack of computationally efficient…

Quantum Physics · Physics 2011-03-08 James D. Whitfield , Jacob Biamonte , Alán Aspuru-Guzik

Ubiquitous in quantum computing is the step to encode data into a quantum state. This process is called quantum state preparation, and its complexity for non-structured data is exponential on the number of qubits. Several works address this…

Quantum Physics · Physics 2023-07-28 Israel F. Araujo , Carsten Blank , Ismael C. S. Araújo , Adenilton J. da Silva

Quantum process characterization is a fundamental task in quantum information processing, yet conventional methods, such as quantum process tomography, require prohibitive resources and lack scalability. Here, we introduce an efficient…

Quantum Physics · Physics 2025-04-11 Yusen Wu , Yukun Zhang , Chuan Wang , Xiao Yuan

Selecting a set of basis states is a common task in quantum computing, in order to increase and/or evaluate their probabilities. This is similar to designing WHERE clauses in classical database queries. Even though one can find heuristic…

Quantum Physics · Physics 2021-06-16 Austin Gilliam , Marco Pistoia , Constantin Gonciulea

Finding the ground state of a Hamiltonian system is of great significance in many-body quantum physics and quantum chemistry. We propose an improved iterative quantum algorithm to prepare the ground state of a Hamiltonian. The crucial point…

Quantum Physics · Physics 2022-10-25 Jin-Min Liang , Qiao-Qiao Lv , Shu-Qian Shen , Ming Li , Zhi-Xi Wang , Shao-Ming Fei

The theory of quantum algorithms promises unprecedented benefits of harnessing the laws of quantum mechanics for solving certain computational problems. A persistent obstacle to using such algorithms for solving a wide range of real-world…

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