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Exact simulations of quantum circuits (QCs) are currently limited to $\sim$50 qubits because the memory and computational cost required to store the QC wave function scale exponentially with qubit number. Therefore, developing efficient…

Quantum Physics · Physics 2025-02-18 Marco Bernardi

We prove that quantum computation is polynomially equivalent to classical probabilistic computation with an oracle for estimating the value of simple sums, quadratically signed weight enumerators. The problem of estimating these sums can be…

Quantum Physics · Physics 2007-05-23 E. Knill , R. Laflamme

Quantum simulations are designed to model quantum systems, and many compilation frameworks have been developed for executing such simulations on quantum computers. Most compilers leverage the capabilities of digital and analog quantum…

Quantum Physics · Physics 2025-09-26 Liyi Li , Federico Zahariev , Chandeepa Dissanayake , Jae Swanepoel , Amr Sabry , Mark S. Gordon

We show that the computational power of the non-causal circuit model, i.e., the circuit model where the assumption of a global causal order is replaced by the assumption of logical consistency, is completely characterized by the complexity…

Quantum Physics · Physics 2018-01-15 Ämin Baumeler , Stefan Wolf

Many-electron problems pose some of the greatest challenges in computational science, with important applications across many fields of modern science. Fermionic quantum Monte Carlo (QMC) methods are among the most powerful approaches to…

Deep learning has been shown to be able to recognize data patterns better than humans in specific circumstances or contexts. In parallel, quantum computing has demonstrated to be able to output complex wave functions with a few number of…

Quantum Physics · Physics 2021-08-05 Junhua Liu , Kwan Hui Lim , Kristin L. Wood , Wei Huang , Chu Guo , He-Liang Huang

The neural network and quantum computing are both significant and appealing fields, with their interactive disciplines promising for large-scale computing tasks that are untackled by conventional computers. However, both developments are…

Quantum Physics · Physics 2021-06-22 Feihong Shen , Jun Liu

We use the benefits and components of classical computers every day. However, there are many types of problems which, as they grow in size, their computational complexity grows larger than classical computers will ever be able to solve.…

We show that the time evolution of the wave function of a quantum mechanical many particle system can be implemented very efficiently on a quantum computer. The computational cost of such a simulation is comparable to the cost of a…

Quantum Physics · Physics 2009-10-30 Christof Zalka

Quantum Parametric Circuits are constructed as an alternative to reduce the size of quantum circuits, meaning to decrease the number of quantum gates and, consequently, the depth of these circuits. However, determining the optimal circuit…

Machine Learning · Computer Science 2025-02-24 Fernando M de Paula Neto

Generative modeling has seen a rising interest in both classical and quantum machine learning, and it represents a promising candidate to obtain a practical quantum advantage in the near term. In this study, we build over a proposed…

Quantum Physics · Physics 2025-07-31 Mohamed Hibat-Allah , Marta Mauri , Juan Carrasquilla , Alejandro Perdomo-Ortiz

Unlike fixed designs, programmable circuit designs support an infinite number of operators. The functionality of a programmable circuit can be altered by simply changing the angle values of the rotation gates in the circuit. Here, we…

Quantum Physics · Physics 2012-12-27 Anmer Daskin , Ananth Grama , Giorgos Kollias , Sabre Kais

Variational quantum algorithms have been introduced as a promising class of quantum-classical hybrid algorithms that can already be used with the noisy quantum computing hardware available today by employing parameterized quantum circuits.…

Quantum Physics · Physics 2023-02-10 Tom Peham , Lukas Burgholzer , Robert Wille

Quantum machine learning (QML) holds promise for accelerating pattern recognition, optimization, and data analysis, but the conditions under which it can truly outperform classical approaches remain unclear. Existing research often…

Quantum Physics · Physics 2025-09-23 Christophe Pere

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

Tensor networks and quantum computation are two of the most powerful tools for the simulation of quantum many-body systems. Rather than viewing them as competing approaches, here we consider how these two methods can work in tandem. We…

We present an architecture of QCPU(Quantum Central Processing Unit), based on the discrete quantum gate set, that can be programmed to approximate any n-qubit computation in a deterministic fashion. It can be built efficiently to implement…

Quantum Physics · Physics 2009-11-07 Fei Xue , Zeng-Bing Chen , Mingjun Shi , Xianyi Zhou , Jiangfeng Du , Rongdian Han

We present a class of hybrid classical systems using quantum co-processors and point out that unlike purely quantum computers, such hybrids can be both universal and Turing complete; we introduce such quantum-classical hybrids as…

Quantum Physics · Physics 2018-08-15 Edward H. "Ned" Allen , Cristian S. Calude

Quantum message authentication codes are families of keyed encoding and decoding maps that enable the detection of tampering on encoded quantum data. Here, we study a new class of simulators for quantum message authentication schemes, and…

Quantum Physics · Physics 2016-12-08 Anne Broadbent , Evelyn Wainewright

Quantum algorithms for simulating electronic ground states are slower than popular classical mean-field algorithms such as Hartree-Fock and density functional theory, but offer higher accuracy. Accordingly, quantum computers have been…

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