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The last decade has witnessed remarkable progress in the development of quantum technologies. Although fault-tolerant devices likely remain years away, the noisy intermediate-scale quantum devices of today may be leveraged for other…

One of the main challenges in building a quantum processor is to characterize the environmental noise. Noise characterization can be achieved by exploiting different techniques, such as randomization where several sequences of random…

Quantum Physics · Physics 2020-11-04 Elena Ferraro , Marco De Michielis

The rapid development of machine learning and quantum computing has placed quantum machine learning at the forefront of research. However, existing quantum machine learning algorithms based on quantum variational algorithms face challenges…

Quantum Physics · Physics 2025-08-22 Da Zhang , Xin Li , Yibin Guo , Haifeng Yu , Yirong Jin , Zhang-Qi Yin

Quantum annealing is a method to solve optimization problems that leverages quantum tunneling in a coupled qubit system. We present a detailed study of the coherence of a tunable capacitively-shunted flux qubit, designed for coherent…

Quantum simulation is a potentially powerful application of quantum computing, holding the promise to be able to emulate interesting quantum systems beyond the reach of classical computing methods. Despite such promising applications, and…

Quantum Physics · Physics 2022-10-07 Kaelyn J. Ferris , A. J. Rasmusson , Nicholas T. Bronn , Olivia Lanes

Unwanted interaction between a quantum system and its fluctuating environment leads to decoherence and is the primary obstacle to establishing a scalable quantum information processing architecture. Strategies such as environmental and…

We present experimental measurements on a model quantum system that demonstrate our ability to dramatically suppress qubit error rates by the application of optimized dynamical decoupling pulse sequences in a variety of experimentally…

Advancements in quantum computing have spurred significant interest in harnessing its potential for speedups over classical systems. However, noise remains a major obstacle to achieving reliable quantum algorithms. In this work, we present…

Quantum Physics · Physics 2025-05-29 Lucas Tecot , Di Luo , Cho-Jui Hsieh

We describe a method for improving coherent control through the use of detailed knowledge of the system's Hamiltonian. Precise unitary transformations were obtained by strongly modulating the system's dynamics to average out unwanted…

Quantum computers are poised to radically outperform their classical counterparts by manipulating coherent quantum systems. A realistic quantum computer will experience errors due to the environment and imperfect control. When these errors…

Quantum Physics · Physics 2016-11-21 Joel J. Wallman , Joseph Emerson

One of the greatest challenges for current quantum computing hardware is how to obtain reliable results from noisy devices. A recent paper [A. Kandala et al., Nature 567, 491 (2019)] described a method for injecting noise by stretching gate…

Quantum Physics · Physics 2022-07-22 Sam Tomkins , Rogério de Sousa

To realize the full potential of quantum computers, we must mitigate qubit errors by developing noise-aware algorithms, compilers, and architectures. Thus, simulating quantum programs on high-performance computing (HPC) systems with…

Quantum Physics · Physics 2025-05-20 Meng Wang , Swamit Tannu , Prashant J. Nair

The potential advantage of machine learning in quantum computers is a topic of intense discussion in the literature. Theoretical, numerical and experimental explorations will most likely be required to understand its power. There has been…

Quantum Physics · Physics 2021-04-05 Abhinav Anand , Jonathan Romero , Matthias Degroote , Alán Aspuru-Guzik

Noise and errors are inevitable parts of any practical implementation of a quantum computer. As a result, large-scale quantum computation will require ways to detect and correct errors on quantum information. Here, we present such a quantum…

Several important models of machine learning algorithms have been successfully generalized to the quantum world, with potential speedup to training classical classifiers and applications to data analytics in quantum physics that can be…

Quantum Physics · Physics 2021-10-01 Ji Guan , Wang Fang , Mingsheng Ying

The current quantum reinforcement learning control models often assume that the quantum states are known a priori for control optimization. However, full observation of quantum state is experimentally infeasible due to the exponential…

Quantum Physics · Physics 2022-06-30 Chen Jiang , Yu Pan , Zheng-Guang Wu , Qing Gao , Daoyi Dong

A long-standing problem in quantum optimal control is finding an optimal pulse structure that leads to an efficient exploration of the unitary space with a minimal number of optimization parameters. We solve this problem by constructing…

Successful implementations of quantum technologies require protocols and algorithms that use as few quantum resources as possible. However, many important quantum operations, such as continuous rotation gates in quantum computing or…

Quantum Physics · Physics 2025-01-09 Bálint Koczor

Dynamical decoupling pulse sequences have been used to extend coherence times in quantum systems ever since the discovery of the spin-echo effect. Here we introduce a method of recursively concatenated dynamical decoupling pulses, designed…

Quantum Physics · Physics 2007-05-23 K. Khodjasteh , D. A. Lidar

Quantum Computing has been evolving in the last years. Although nowadays quantum algorithms performance has shown superior to their classical counterparts, quantum decoherence and additional auxiliary qubits needed for error tolerance…

Quantum Physics · Physics 2021-05-06 O. M. Pires , E. I. Duzzioni , J. Marchi , R. Santiago