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Related papers: Wasserstein Complexity of Quantum Circuits

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This paper addresses the problem of finding the depth overhead that will be incurred when running quantum circuits on near-term quantum computers. Specifically, it is envisaged that near-term quantum computers will have low qubit…

Quantum Physics · Physics 2020-07-29 Steven Herbert

The development of quantum computing technologies builds on the unique features of quantum physics while borrowing familiar principles from the design of conventional devices. We introduce the fundamental concepts required for designing and…

The variational quantum eigensolver (VQE) is one of the most promising algorithms to find eigenvalues and eigenvectors of a given Hamiltonian on noisy intermediate-scale quantum (NISQ) devices. A particular application is to obtain ground…

The development of complex circuits for practical applications in the current quantum computing ecosystem is based on basic primitives such as Bell states, which provide superposition, entanglement, and coherence. The range of…

Quantum Physics · Physics 2026-04-07 Hillol Biswas

In quantum chemistry, the price paid by all known efficient model chemistries is either the truncation of the Hilbert space or uncontrolled approximations. Theoretical computer science suggests that these restrictions are not mere…

Chemical Physics · Physics 2017-03-15 James D. Whitfield , Peter J. Love , Alan Aspuru-Guzik

Demonstrating quantum supremacy, a complexity-guaranteed quantum advantage against over the best classical algorithms by using less universal quantum devices, is an important near-term milestone for quantum information processing. Here we…

Quantum Physics · Physics 2016-10-13 Keisuke Fujii

Coherence and correlation are key features of the quantum system. Quantifying these quantities are astounding task in the framework of resource theory of quantum information processing. In this article, we identify an affinity-based metric…

Quantum Physics · Physics 2021-02-11 R. Muthuganesan , V. K. Chandrasekar , R. Sankaranarayanan

The Wasserstein distance is a distance between two probability distributions and has recently gained increasing popularity in statistics and machine learning, owing to its attractive properties. One important approach to extending this…

Methodology · Statistics 2022-02-14 Ryo Okano , Masaaki Imaizumi

Although near-term quantum computing devices are still limited by the quantity and quality of qubits in the so-called NISQ era, quantum computational advantage has been experimentally demonstrated. Moreover, hybrid architectures of quantum…

This thesis presents three different results in quantum information theory. The first result addresses the theoretical foundations of quantum metrology. The Heisenberg limit considered as the ultimate limit in quantum metrology sets a lower…

Quantum Physics · Physics 2015-03-18 Marcin Zwierz

Quantum computers hold unprecedented potentials for machine learning applications. Here, we prove that physical quantum circuits are PAC (probably approximately correct) learnable on a quantum computer via empirical risk minimization: to…

Quantum Physics · Physics 2022-01-04 Haoyuan Cai , Qi Ye , Dong-Ling Deng

Quantifying how far the output of a learning algorithm is from its target is an essential task in machine learning. However, in quantum settings, the loss landscapes of commonly used distance metrics often produce undesirable outcomes such…

Quantum Physics · Physics 2022-07-07 Bobak Toussi Kiani , Giacomo De Palma , Milad Marvian , Zi-Wen Liu , Seth Lloyd

Noise is the greatest obstacle in quantum metrology that limits it achievable precision and sensitivity. There are many techniques to mitigate the effect of noise, but this can never be done completely. One commonly proposed technique is to…

Quantum Physics · Physics 2021-04-27 Nathan Shettell , William J. Munro , Damian Markham , Kae Nemoto

Recent breakthroughs have opened the possibility to intermediate-scale quantum computing with tens to hundreds of qubits, and shown the potential for solving classical challenging problems, such as in chemistry and condensed matter physics.…

Quantum Physics · Physics 2025-10-30 Zhong-Xia Shang , Ming-Cheng Chen , Xiao Yuan , Chao-Yang Lu , Jian-Wei Pan

We expound on some known lower bounds of the quadratic Wasserstein distance between random vectors in $\mathbb{R}^n$ with an emphasis on affine transformations that have been used in manifold learning of data in Wasserstein space. In…

Machine Learning · Statistics 2024-02-09 Keaton Hamm , Andrzej Korzeniowski

We develop circuit implementations for digital-level quantum Hamiltonian dynamics simulation algorithms suitable for implementation on a reconfigurable quantum computer, such as trapped ions. Our focus is on the co-design of a problem, its…

Quantum Physics · Physics 2020-04-09 Yunseong Nam , Dmitri Maslov

We investigate the theoretical limits of the effect of the quantum interaction distance on the speed of exact quantum addition circuits. For this study, we exploit graph embedding for quantum circuit analysis. We study a logical mapping of…

Quantum Physics · Physics 2012-09-17 Byung-Soo Choi , Rodney Van Meter

Classical simulations of quantum circuits are limited in both space and time when the qubit count is above 50, the realm where quantum supremacy reigns. However, recently, for the low depth circuit with more than 50 qubits, there are…

Quantum Physics · Physics 2018-08-15 Zhao-Yun Chen , Qi Zhou , Cheng Xue , Xia Yang , Guang-Can Guo , Guo-Ping Guo

We consider a notion of complexity of quantum channels in relativistic continuum quantum field theory (QFT) defined by the distance to the trivial (identity) channel. Our distance measure is based on a specific divergence between quantum…

Quantum Physics · Physics 2025-08-22 Stefan Hollands , Alessio Ranallo

Query complexity is a model of computation in which we have to compute a function $f(x_1, \ldots, x_N)$ of variables $x_i$ which can be accessed via queries. The complexity of an algorithm is measured by the number of queries that it makes.…

Quantum Physics · Physics 2017-12-19 Andris Ambainis