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Related papers: Spectra of noisy parameterized quantum circuits: S…

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We investigate the effects of noise on parameterised quantum circuits using spectral analysis and classical signal processing tools. For different noise models, we quantify the additional, higher frequency modes in the output signal caused…

Quantum Physics · Physics 2022-11-11 Enrico Fontana , Ivan Rungger , Ross Duncan , Cristina Cîrstoiu

In this paper, we introduce an efficient algorithm for the quantum amplitude estimation task which works in noisy intermediate-scale quantum(NISQ) devices. The quantum amplitude estimation is an important problem which has various…

Quantum Physics · Physics 2021-11-29 Kouhei Nakaji

Two main obstacles for observing quantum advantage in noisy intermediate-scale quantum computers (NISQ) are the finite precision effects due to control errors, or disorders, and decoherence effects due to thermal fluctuations. It has been…

Quantum Physics · Physics 2018-08-14 Leonardo Novo , Shantanav Chakraborty , Masoud Mohseni , Yasser Omar

This work presents an optimization-based scalable quantum neural network framework for approximating $n$-qubit unitaries through generic parametric representation of unitaries, which are obtained as product of exponential of basis elements…

Quantum Physics · Physics 2024-01-17 Rohit Sarma Sarkar , Bibhas Adhikari

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

Quantum many-core processors are envisioned as the ultimate solution for the scalability of quantum computers. Based upon Noisy Intermediate-Scale Quantum (NISQ) chips interconnected in a sort of quantum intranet, they enable large…

Quantum machine learning is often motivated by the idea that quantum systems can expose useful high-dimensional structure that is difficult to access with classical models. We isolate one central component of this claim: the fixed…

Quantum Physics · Physics 2026-05-26 Toheeb Ogunade , Taofeek Kassim , Etinosa Osaro

The emergence of noisy intermediate-scale quantum (NISQ) computers has important consequences for cryptographic algorithms. It is theoretically well-established that key algorithms used in cybersecurity are vulnerable to quantum computers…

Cryptography and Security · Computer Science 2023-06-06 Sahay Harshvardhan , Sanil Jain , James E. McClure , Caleb McIrvin , Ngoc Quy Tran

Quantum field theory (QFT) simulations are a potentially important application for noisy intermediate scale quantum (NISQ) computers. The ability of a quantum computer to emulate a QFT, therefore, constitutes a natural application-centric…

Understanding the computational power of noisy intermediate-scale quantum (NISQ) devices is of both fundamental and practical importance to quantum information science. Here, we address the question of whether error-uncorrected noisy…

Quantum Physics · Physics 2020-09-16 Kyungjoo Noh , Liang Jiang , Bill Fefferman

We propose to use neural networks to estimate the rates of coherent and incoherent processes in quantum systems from continuous measurement records. In particular, we adapt an image recognition algorithm to recognize the patterns in…

Quantum Physics · Physics 2017-11-15 Eliska Greplova , Christian Kraglund Andersen , Klaus Mølmer

Quantum neuromorphic computing physically implements neural networks in brain-inspired quantum hardware to speed up their computation. In this perspective article, we show that this emerging paradigm could make the best use of the existing…

Quantum Physics · Physics 2020-10-28 Danijela Marković , Julie Grollier

The topic area of this paper parameterized quantum circuits (quantum neural networks) which are trained to estimate a given function, specifically the type of circuits proposed by Mitarai et al. (Phys. Rev. A, 2018). The input is encoded…

Quantum Physics · Physics 2020-06-25 Javier Gil Vidal , Dirk Oliver Theis

Quantum machine learning has shown promise for high-dimensional data analysis, yet many existing approaches rely on linear unitary operations and shared trainable parameters across outputs. These constraints limit expressivity and…

Quantum Physics · Physics 2026-02-17 Viktoria Patapovich , Maniraman Periyasamy , Mo Kordzanganeh , Alexey Melnikov

The execution of quantum circuits on real systems has largely been limited to those which are simply time-ordered sequences of unitary operations followed by a projective measurement. As hardware platforms for quantum computing continue to…

Quantum computing has been moving from a theoretical phase to practical one, presenting daunting challenges in implementing physical qubits, which are subjected to noises from the surrounding environment. These quantum noises are ubiquitous…

Noisy intermediate-scale quantum (NISQ) computers have gate errors and decoherence, limiting the depth of circuits that can be implemented on them. A strategy for NISQ algorithms is to reduce the circuit depth at the expense of increasing…

Quantum Physics · Physics 2019-01-09 Yigit Subasi , Lukasz Cincio , Patrick J. Coles

Quantum computing promises advantages over classical computing. The manufacturing of quantum hardware is in the infancy stage, called the Noisy Intermediate-Scale Quantum (NISQ) era. A major challenge is automated quantum circuit design…

Quantum circuits generating probability distributions has applications in several areas. Areas like finance require quantum circuits that can generate distributions that mimic some given data pattern. Hamiltonian simulations require…

Quantum Physics · Physics 2022-08-30 Kalyan Dasgupta , Binoy Paine

Band crossings in electronic band structures play an important role in determining the electronic, topological, and transport properties in solid-state systems, making them central to both condensed matter physics and materials science. The…

Quantum Physics · Physics 2026-01-01 Shaobo Zhang , Akib Karim , Harry M. Quiney , Muhammad Usman
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