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Related papers: Machine Learning Catalysis of Quantum Tunneling

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Classical optimization algorithms in machine learning often take a long time to compute when applied to a multi-dimensional problem and require a huge amount of CPU and GPU resource. Quantum parallelism has a potential to speed up machine…

Quantum Physics · Physics 2019-11-21 Venkat R. Dasari , Mee Seong Im , Lubjana Beshaj

Machine learning techniques have been successfully applied to classifying an extensive range of phenomena in quantum theory. From detecting quantum phase transitions to identifying Bell non-locality, it has been established that classical…

Quantum Physics · Physics 2022-09-28 Thaís M. Acácio , Cristhiano Duarte

Quantum tunneling in a many-body system is much more non-trivial than that in a one-body system. The most characteristic phenomenon is the mixed tunneling, which has been studied in many fields for decades. For instance, let us consider a…

High Energy Physics - Theory · Physics 2023-05-11 Yutaro Shoji

Quantum entanglement is usually revealed via a well aligned, carefully chosen set of measurements. Yet, under a number of experimental conditions, for example in communication within multiparty quantum networks, noise along the channels or…

The optimally designed control of quantum systems is playing an increasingly important role to engineer novel and more efficient quantum technologies. Here, in the scenario represented by controlling an arbitrary quantum system via the…

We study the quantum synchronization between a pair of two-level systems inside two coupled cavities. By using a digital-analog decomposition of the master equation that rules the system dynamics, we show that this approach leads to quantum…

Quantum Physics · Physics 2019-01-17 F. A. Cárdenas-López , M. Sanz , J. C. Retamal , E. Solano

Coherent information quantifies the achievable rate of the reliable quantum information transmission through a communication channel. Use of the correlated quantum states instead of the factorized ones may result in an increase in the…

Quantum Physics · Physics 2022-06-28 Sergey N. Filippov

Quantum annealing is typically regarded as a tool for combinatorial optimization, but its coherent dynamics also offer potential for machine learning. We present a model that encodes classical data into an Ising Hamiltonian, evolves it on a…

We demonstrate how machine learning is able to model experiments in quantum physics. Quantum entanglement is a cornerstone for upcoming quantum technologies such as quantum computation and quantum cryptography. Of particular interest are…

Machine Learning · Computer Science 2022-07-04 Thomas Adler , Manuel Erhard , Mario Krenn , Johannes Brandstetter , Johannes Kofler , Sepp Hochreiter

In the rapidly evolving field of quantum computing, optimizing quantum circuits for specific tasks is crucial for enhancing performance and efficiency. More recently, quantum sensing has become a distinct and rapidly growing branch of…

Quantum Physics · Physics 2025-09-01 Laxmisha Ashok Attisara , Sathish Kumar

The tunneling probability for a system modelling macroscopic quantum tunneling is computed. We consider an open quantum system with one degree of freedom consisting of a particle trapped in a cubic potential interacting with an environment…

Quantum Physics · Physics 2007-05-23 Esteban Calzetta , Enric Verdaguer

We describe several different methods for generating the entangled ancilla states that are required for linear optics quantum computing. We show that post-selection can be used in combination with linear optical elements to generate the…

Quantum Physics · Physics 2009-11-10 J. D. Franson , M. M. Donegan , B. C. Jacobs

We theoretically and experimentally investigate conditional enhancement of overall coherence of quantum states by probabilistic quantum operations that apply to the input state a quantum filter diagonal in the basis of incoherent states. We…

Quantum Physics · Physics 2021-08-03 Robert Stárek , Michal Mičuda , Michal Kolář , Radim Filip , Jaromír Fiurášek

Quantum Machine Learning(QML) is developed by combining quantum mechanics principles with classical machine learning techniques in a hybrid framework that can give faster, exponential, more efficient power of quantum computing with the data…

Quantum Physics · Physics 2026-01-27 Pallab Biswas , Tamal Maity

Optimizing the training of a machine learning pipeline helps in reducing training costs and improving model performance. One such optimizing strategy is quantum annealing, which is an emerging computing paradigm that has shown potential in…

Quantum Physics · Physics 2021-06-08 Rajdeep Kumar Nath , Himanshu Thapliyal , Travis S. Humble

Quantum mechanics dictates the band-structure of materials that is essential for functional electronic components. With increased miniaturization of devices, it becomes possible to exploit the full potential of quantum mechanics through the…

Quantum Physics · Physics 2022-05-26 Kasper Poulsen , Alan C. Santos , Lasse B. Kristensen , Nikolaj T. Zinner

Quantum-state engineering, i.e., active manipulation over the coherent dynamics of suitable quantum-mechanical systems, has become a fascinating prospect of modern physics. Here we discuss the dynamics of two interacting electrons in a…

Mesoscale and Nanoscale Physics · Physics 2009-11-07 Ping Zhang , Xian-Geng Zhao

Quantum technologies exploit entanglement to enhance various tasks beyond their classical limits including computation, communication and measurements. Quantum metrology aims to increase the precision of a measured quantity that is…

Quantum Physics · Physics 2020-08-25 Bálint Koczor , Suguru Endo , Tyson Jones , Yuichiro Matsuzaki , Simon C. Benjamin

The quantum internet aims to interconnect distant devices and enable large-scale computation through distributed quantum algorithms. One of the key obstacles is communication latency during computation. Even separations of a few hundred…

Quantum Physics · Physics 2026-05-06 Yerim Kim , Kiwmann Hwang , Hyukjoon Kwon , Yosep Kim

Solving electronic structure problems represents a promising field of application for quantum computers. Currently, much effort has been spent in devising and optimizing quantum algorithms for quantum chemistry problems featuring up to…