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Efficient preparation of many-body ground states is key to harnessing the power of quantum computers in studying quantum many-body systems. In this work, we propose a simple method to design exact linear-depth parameterized quantum circuits…

Quantum Physics · Physics 2024-12-12 Yu-Jie Liu , Kirill Shtengel , Frank Pollmann

The problems of quantum state preparation and matrix block-encoding are ubiquitous in quantum computing: they are crucial parts of various quantum algorithms for the purpose for initial state preparation as well as loading problem relevant…

Quantum state discrimination is one of the most fundamental problems studied in quantum information theory. Applications range from channel coding to metrology and cryptography. In this work, we introduce a new variant of this task: Local…

Quantum Physics · Physics 2024-05-20 Christian Majenz , Maris Ozols , Christian Schaffner , Mehrdad Tahmasbi

One of the key considerations in the development of Quantum Machine Learning (QML) protocols is the encoding of classical data onto a quantum device. In this chapter we introduce the Matrix Product State representation of quantum systems…

Quantum Physics · Physics 2026-01-15 Chris Nakhl , Maxwell West , Muhammad Usman

In this paper, we present an efficient quantum compression method for identically prepared states with arbitrary dimentional.

Quantum Physics · Physics 2023-07-25 Zeyu Chen , Chunhe Xiong , Kamil Khadiev , Junde Wu

Effective quantum computation relies upon making good use of the exponential information capacity of a quantum machine. A large barrier to designing quantum algorithms for execution on real quantum machines is that, in general, it is…

Quantum Physics · Physics 2020-05-12 Adam Holmes , A. Y. Matsuura

We propose a variational approach for preparing entangled quantum states on quantum computers. The methodology involves training a unitary operation to match with a target unitary using the Fubini-Study distance as a cost function. We…

Quantum Physics · Physics 2023-07-03 Vu Tuan Hai , Nguyen Tan Viet , Le Bin Ho

In pursuit of enhancing the predication capabilities of the neural network, it has been a longstanding objective to create dataset encompassing a diverse array of samples. The purpose is to broaden the horizons of neural network and…

Quantum Physics · Physics 2024-01-23 Chao-Chao Li , Run-Hong He , Zhao-Ming Wang

One of the major components for realizing quantum computers is the ability to initialize the computer to a known fiducial state, also known as state preparation. We demonstrate a state preparation method via measurement-induced steering on…

Quantum Physics · Physics 2024-04-24 Daniel Volya , Prabhat Mishra

Quantum state tomography is a fundamental tool in quantum information processing. It allows us to estimate the state of a quantum system by measuring different observables on many identically prepared copies of the system. This is, in…

Quantum Physics · Physics 2011-11-28 Carlos A. Riofrío

Many quantum algorithms rely on a quality initial state for optimal performance. Preparing an initial state for specific applications can considerably reduce the cost of probabilistic algorithms such as the well studied quantum phase…

Quantum Physics · Physics 2024-12-10 Alexandre Fleury , James Brown , Erika Lloyd , Maritza Hernandez , Isaac H. Kim

Ideal deterministic quantum communication tasks require maximally entangled channels. The reality is that the maximally entangled channel is inevitably degraded to a non-maximally entangled one because of various decoherence mechanisms,…

Quantum Physics · Physics 2023-05-17 Xuanxuan Xin , Shiwen He , Yongxing Li , Chong Li

Recently, tremendous progress has been made in the field of quantum science and technologies: different platforms for quantum simulation as well as quantum computing, ranging from superconducting qubits to neutral atoms, are starting to…

A discrete-time method for solving problems in optimal quantum control is presented. Controlling the time discretized markovian dynamics of a quantum system can be reduced to a Markov-decision process. We demonstrate this method in this…

Quantum Physics · Physics 2012-06-05 Jon R. Grice , David A. Meyer

Remote state preparation is the variant of quantum state teleportation in which the sender knows the quantum state to be communicated. The original paper introducing teleportation established minimal requirements for classical communication…

Quantum Physics · Physics 2007-05-23 Charles H. Bennett , Patrick Hayden , Debbie W. Leung , Peter W. Shor , Andreas Winter

The initialization of quantum states or Quantum State Preparation (QSP) is a basic subroutine in quantum algorithms. In the worst case, general QSP algorithms are expensive due to the application of multi-controlled gates required to build…

Classical representations of quantum states and operations as vectors and matrices are plagued by an exponential growth in memory and runtime requirements for increasing system sizes. Based on their use in classical computing, an…

Quantum Physics · Physics 2024-06-19 Aaron Sander , Ioan-Albert Florea , Lukas Burgholzer , Robert Wille

Quantum computing promises to solve some important problems faster than conventional computations ever could. Currently available NISQ devices on which first practical applications are already executed demonstrate the potential -- with…

Quantum Physics · Physics 2023-02-10 Robert Wille , Stefan Hillmich , Lukas Burgholzer

Estimation of quantum states and measurements is crucial for the implementation of quantum information protocols. The standard method for each is quantum tomography. However, quantum tomography suffers from systematic errors caused by…

Quantum Physics · Physics 2018-10-19 Adam C. Keith , Charles H. Baldwin , Scott Glancy , E. Knill

Quantum computers promise to solve important problems faster than conventional computers. However, unleashing this power has been challenging. In particular, design automation runs into (1) the probabilistic nature of quantum computation…

Quantum Physics · Physics 2023-11-08 Stefan Hillmich , Richard Kueng , Igor L. Markov , Robert Wille
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