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Hybrid Tensor Networks (hTN) offer a promising solution for encoding variational quantum states beyond the capabilities of efficient classical methods or noisy quantum computers alone. However, their practical usefulness and many…

The analysis of noisy quantum states prepared on current quantum computers is getting beyond the capabilities of classical computing. Quantum neural networks based on parametrized quantum circuits, measurements and feed-forward can process…

Quantum Physics · Physics 2024-09-19 Petr Zapletal , Nathan A. McMahon , Michael J. Hartmann

Quantum simulation is a foundational application for quantum computers, projected to offer insights into complex quantum systems beyond the reach of classical computation. However, with the exception of Trotter-based methods, which suffer…

Quantum Physics · Physics 2026-02-10 Amir Kalev , Itay Hen

Current experimental quantum computing devices are limited by noise, mainly originating from entangling gates. If an efficient gate sequence for an operation is unknown, one often employs layered parameterized quantum circuits, especially…

Quantum Physics · Physics 2025-11-12 Tom R. Rieckmann , Stefan Scheel , A. Douglas K. Plato

We investigate the boundary between classical and quantum computational power. This work consists of two parts. First we develop new classical simulation algorithms that are centered on sampling methods. Using these techniques we generate…

Quantum Physics · Physics 2012-02-20 M. Van den Nest

Fault tolerant quantum simulation via the phase estimation algorithm and qubitization has a T-gate count that scales proportionally to the 1-norm of the Hamiltonian, the cost of block encoding the Hamiltonian, and inversely proportionally…

Quantum Physics · Physics 2025-04-14 Hirsh Kamakari , Emil Zak

Quantum simulation of the electronic structure problem is one of the most researched applications of quantum computing. The majority of quantum algorithms for this problem encode the wavefunction using $N$ Gaussian orbitals, leading to…

Simulating quantum systems is one of the most promising avenues to harness the computational power of quantum computers. However, hardware errors in noisy near-term devices remain a major obstacle for applications. Ideas based on the…

Quantum Physics · Physics 2023-07-26 W. Gong , Yaroslav Kharkov , Minh C. Tran , Przemyslaw Bienias , Alexey V. Gorshkov

Circuit knitting offers a promising path to the scalable execution of large quantum circuits by breaking them into smaller sub-circuits whose output is recombined through classical postprocessing. However, current techniques face excessive…

Quantum Physics · Physics 2024-10-22 Nathaniel Tornow , Christian B. Mendl , Pramod Bhatotia

Tensor Networks (TN) are approximations of high-dimensional tensors designed to represent locally entangled quantum many-body systems efficiently. This study provides a comprehensive comparison between classical TNs and TN-inspired quantum…

Quantum Physics · Physics 2022-12-20 Jack Y. Araz , Michael Spannowsky

Simulating open quantum systems on quantum computers presents a fundamental challenge: open quantum dynamics are intrinsically nonunitary, whereas quantum computers operate through unitary evolution. Conventional approaches overcome this…

Quantum Physics · Physics 2025-10-27 Sameer Dambal , Akira Sone , Yu Zhang

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

Quantum computers have the potential to efficiently simulate large-scale quantum systems for which classical approaches are bound to fail. Even though several existing quantum devices now feature total qubit numbers of more than one…

Quantum Physics · Physics 2023-03-29 Hongye Yu , Yusheng Zhao , Tzu-Chieh Wei

Simulation of quantum chemistry is expected to be a principal application of quantum computing. In quantum simulation, a complicated Hamiltonian describing the dynamics of a quantum system is decomposed into its constituent terms, where the…

Quantum Physics · Physics 2020-03-04 Yingkai Ouyang , David R. White , Earl T. Campbell

The exploration of hybrid quantum-classical algorithms and programming models on noisy near-term quantum hardware has begun. As hybrid programs scale towards classical intractability, validation and benchmarking are critical to…

Quantum Physics · Physics 2019-03-06 Alexander McCaskey , Eugene Dumitrescu , Mengsu Chen , Dmitry Lyakh , Travis S. Humble

In this work we investigate methods to improve the efficiency and scalability of quantum algorithms for quantum chemistry applications. We propose a transformation of the electronic structure Hamiltonian in the second quantization framework…

In recent times, Variational Quantum Circuits (VQC) have been widely adopted to different tasks in machine learning such as Combinatorial Optimization and Supervised Learning. With the growing interest, it is pertinent to study the…

Quantum Physics · Physics 2022-12-13 Dheeraj Peddireddy , Vipul Bansal , Vaneet Aggarwal

In quantum computation every unitary operation can be decomposed into quantum circuits-a series of single-qubit rotations and a single type entangling two-qubit gates, such as controlled-NOT (CNOT) gates. Two measures are important when…

Quantum Physics · Physics 2011-03-07 Martin Plesch , Časlav Brukner

Quantum algorithm design usually assumes access to a perfect quantum computer with ideal properties like full connectivity, noise-freedom and arbitrarily long coherence time. In Noisy Intermediate-Scale Quantum (NISQ) devices, however, the…

Quantum Physics · Physics 2020-09-11 Xiangzhen Zhou , Sanjiang Li , Yuan Feng

The task of learning a probability distribution from samples is ubiquitous across the natural sciences. The output distributions of local quantum circuits form a particularly interesting class of distributions, of key importance both to…