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Realistic simulation of quantum materials is a central goal of quantum computation. Although quantum processors have advanced rapidly in scale and fidelity, it has remained unclear whether pre-fault-tolerant devices can perform…

We improve the quality of quantum circuits on superconducting quantum computing systems, as measured by the quantum volume, with a combination of dynamical decoupling, compiler optimizations, shorter two-qubit gates, and excited state…

The circuit model of quantum computation is reformulated as a multilayer network theory [3] called a Quantum Multiverse Network (QuMvN). The QuMvN formulation allows us to interpret the quantum wave function as a combination of ergodic…

Quantum Physics · Physics 2019-09-24 Perry Sakkaris , Ryan Sudhakaran

Limited quantum memory is one of the most important constraints for near-term quantum devices. Understanding whether a small quantum computer can simulate a larger quantum system, or execute an algorithm requiring more qubits than…

Quantum Physics · Physics 2020-12-10 Tianyi Peng , Aram Harrow , Maris Ozols , Xiaodi Wu

Parametric quantum circuits play a crucial role in the performance of many variational quantum algorithms. To successfully implement such algorithms, one must design efficient quantum circuits that sufficiently approximate the solution…

Quantum Physics · Physics 2021-05-05 Lena Funcke , Tobias Hartung , Karl Jansen , Stefan Kühn , Paolo Stornati

Variational quantum circuits (VQCs) are a leading approach to quantum machine learning on near-term devices, yet it remains unclear which circuit architecture yields the best accuracy-parameter trade-off on classical tabular data. We…

Quantum Physics · Physics 2026-04-28 Chi-Sheng Chen , En-Jui Kuo

Quantum state tomography is a key process in most quantum experiments. In this work, we employ quantum machine learning for state tomography. Given an unknown quantum state, it can be learned by maximizing the fidelity between the output of…

Quantum computers promise to enhance machine learning for practical applications. Quantum machine learning for real-world data has to handle extensive amounts of high-dimensional data. However, conventional methods for measuring quantum…

Quantum Physics · Physics 2023-02-10 Tobias Haug , Chris N. Self , M. S. Kim

Realizing a conceptual quantum algorithm on an actual physical device necessitates the algorithm's quantum circuit description to undergo certain transformations in order to adhere to all constraints imposed by the hardware. In this regard,…

Quantum Physics · Physics 2023-01-11 Lukas Burgholzer , Rudy Raymond , Robert Wille

Universal fault-tolerant quantum computers will require error-free execution of long sequences of quantum gate operations, which is expected to involve millions of physical qubits. Before the full power of such machines will be available,…

Quantum computers promise to perform computations beyond the reach of modern computers with profound implications for scientific research. Due to remarkable technological advances, small scale devices are now becoming available for use. One…

Strongly Correlated Electrons · Physics 2022-05-20 Adam Smith , Bernhard Jobst , Andrew G. Green , Frank Pollmann

Network verification (NWV), broadly defined as the verification of properties of distributed protocols used in network systems, cannot be efficiently solved on classical hardware via brute force. Prior work has developed a variety of…

Hypergraph partitioning is a central component of distributed quantum computing (DQC) compilers. However, due to the limited size of available quantum benchmark suites, many partitioning studies rely on random quantum circuits as evaluation…

Quantum Physics · Physics 2026-05-12 Maria Gragera Garces

Vector architectures lack tools for research. Consider the gem5 simulator, which is possibly the leading platform for computer-system architecture research. Unfortunately, gem5 does not have an available distribution that includes a…

Linear cross-entropy benchmarking (LXEB) with random quantum circuits is a standard method for evaluating quantum computers. However, LXEB requires classically simulating the ideal output distribution of a given quantum circuit with high…

Quantum Physics · Physics 2025-07-24 Takumi Kaneda , Keisuke Fujii , Hiroshi Ueda

Due to the unreliability and limited capacity of existing quantum computer prototypes, quantum circuit simulation continues to be a vital tool for validating next generation quantum computers and for studying variational quantum algorithms,…

Quantum Physics · Physics 2021-04-01 Yipeng Huang , Steven Holtzen , Todd Millstein , Guy Van den Broeck , Margaret Martonosi

Creating scalable, reliable, and well-motivated benchmarks for quantum computers is challenging: straightforward approaches to benchmarking suffer from exponential scaling, are insensitive to important errors, or use poorly-motivated…

Quantum Physics · Physics 2025-11-05 Noah Siekierski , Stefan Seritan , Neer Patel , Siyuan Niu , Thomas Lubinski , Timothy Proctor

As quantum devices scale up, many-body quantum gates and algorithms begin to surpass what is possible to simulate classically. Validation methods which rely on such classical simulation, such as process tomography and randomized…

We define a class of stochastic processes based on evolutions and measurements of quantum systems, and consider the complexity of predicting their long-term behavior. It is shown that a very general class of decision problems regarding…

Computational Complexity · Computer Science 2007-05-23 John Watrous

Current technological advancements of quantum computers highlight the need for application-driven, practical and well-defined methods of benchmarking their performance. As the existing NISQ device's quality of two-qubit gate errors rate is…

Performance · Computer Science 2023-12-15 Krzysztof Kurowski , Piotr Rydlichowski , Konrad Wojciechowski , Tomasz Pecyna , Mateusz Slysz