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Quantum circuits for loading probability distributions into quantum states are essential subroutines in quantum algorithms used in physics, finance engineering, and machine learning. The ability to implement these with high accuracy in…

Quantum Physics · Physics 2025-10-07 Yuichi Sano , Ikko Hamamura

We give a rigorous and self-contained analysis of the Grover--Rudolph quantum state-preparation algorithm, which encodes a probability distribution $\{p_k\}$ as an $n$-qubit amplitude state $\sum_k\sqrt{p_k}\ket{k}$ via a hierarchy of…

Quantum Physics · Physics 2026-05-26 Antonio Falco , Daniela Falco-Pomares , Hermann G. Matthies

Quantum state preparation involving a uniform superposition over a non-empty subset of $n$-qubit computational basis states is an important and challenging step in many quantum computation algorithms and applications. In this work, we…

Quantum Physics · Physics 2024-09-20 Alok Shukla , Prakash Vedula

Numerous quantum algorithms operate under the assumption that classical data has already been converted into quantum states, a process termed Quantum State Preparation (QSP). However, achieving precise QSP requires a circuit depth that…

Quantum Physics · Physics 2024-08-13 Yilun Zhao , Bingmeng Wang , Wenle Jiang , Xiwei Pan , Bing Li , Yinhe Han , Ying Wang

Upsampling of time series data is often associated with classical fast Fourier transform analysis, but it also can be employed in the preparation of a quantum state vector. The quantum circuit of preparation derived from functional data…

Quantum Physics · Physics 2025-04-28 R. P. Erickson

Qudit Dicke states are higher-dimensional analogues of an important class of highly-entangled completely symmetric quantum states known as (qubit) Dicke states. A circuit for preparing arbitrary qudit Dicke states deterministically is…

Quantum Physics · Physics 2024-12-30 Rafael I. Nepomechie , David Raveh

We propose efficient algorithms with logarithmic step complexities for the generation of entangled $GHZ_N$ and $W_N$ states useful for quantum networks, and we demonstrate an implementation on the IBM quantum computer up to $N=16$. Improved…

The Quantum State Preparation problem aims to prepare an $n$-qubit quantum state $|\psi_v\rangle =\sum_{k=0}^{2^n-1}v_k|k\rangle$ from the initial state $|0\rangle^{\otimes n}$, for a given unit vector $v=(v_0,v_1,v_2,\ldots,v_{2^n-1})^T\in…

Quantum Physics · Physics 2023-02-23 Xiaoming Sun , Guojing Tian , Shuai Yang , Pei Yuan , Shengyu Zhang

We propose applying the adiabatic algorithm to prepare high-energy eigenstates of integrable models on a quantum computer. We first review the standard adiabatic algorithm to prepare ground states in each magnetization sector of the…

Quantum Physics · Physics 2026-03-18 Maximilian Lutz , Lorenzo Piroli , Georgios Styliaris , J. Ignacio Cirac

Efficiently uploading data into quantum states is essential for many quantum algorithms to achieve advantage across various applications. In this paper, we address this challenge by developing a method to upload a polynomial function $f(x)$…

Quantum Physics · Physics 2026-01-06 Nikita Guseynov , Nana Liu

Ground state preparation is a central application for quantum computers but remains challenging in practice. In this work, we quantitatively investigate the performance and gate counts of double-bracket quantum algorithms (DBQAs) for ground…

Quantum state preparation plays an equally important role with quantum operations and measurements in quantum information processing. The previous methods of preparing initial state for bulk quantum computation all have inevitable…

Quantum Physics · Physics 2017-06-27 Tao Xin , Liang Hao , Shi-Yao Hou , Guan-Ru Feng , Gui-Lu Long

Quantum state preparation is a fundamental task in quantum computing and quantum information processing. With the rapid advancement of quantum technologies, efficient quantum state preparation has become increasingly important. This paper…

Quantum Physics · Physics 2025-07-22 Xin Hong , Chenjian Li , Aochu Dai , Sanjiang Li , Shenggang Ying , Mingsheng Ying

We introduce a quantum algorithm to efficiently prepare states with a small energy variance at the target energy. We achieve it by filtering a product state at the given energy with a Lorentzian filter of width $\delta$. Given a local…

Quantum Physics · Physics 2024-07-03 Reinis Irmejs , Mari Carmen Bañuls , J. Ignacio Cirac

We give a polynomial time algorithm that, given copies of an unknown quantum state $\vert\psi\rangle=U\vert 0^n\rangle$ that is prepared by an unknown constant depth circuit $U$ on a finite-dimensional lattice, learns a constant depth…

Quantum Physics · Physics 2025-06-18 Zeph Landau , Yunchao Liu

The preparation of quantum Gibbs state is an essential part of quantum computation and has wide-ranging applications in various areas, including quantum simulation, quantum optimization, and quantum machine learning. In this paper, we…

Quantum Physics · Physics 2021-11-23 Youle Wang , Guangxi Li , Xin Wang

The ground state properties of quantum many-body systems are a subject of interest across chemistry, materials science, and physics. Thus, algorithms for finding ground states can have broad impacts. Variational quantum algorithms are one…

Quantum Physics · Physics 2023-09-28 James B. Larsen , Matthew D. Grace , Andrew D. Baczewski , Alicia B. Magann

We propose a novel deterministic method for preparing arbitrary quantum states. When our protocol is compiled into CNOT and arbitrary single-qubit gates, it prepares an $N$-dimensional state in depth $O(\log(N))$ and spacetime allocation (a…

Dicke states are permutation-invariant superpositions of qubit computational basis states, which play a prominent role in quantum information science. We consider here two higher-dimensional generalizations of these states: $SU(2)$ spin-$s$…

Quantum Physics · Physics 2026-03-16 Noah B. Kerzner , Federico Galeazzi , Rafael I. Nepomechie

The variational quantum eigensolver is one of the most promising approaches for performing chemistry simulations using noisy intermediate-scale quantum (NISQ) processors. The efficiency of this algorithm depends crucially on the ability to…

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