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Parametrised quantum circuits are a central framework for near term quantum machine learning. However, it remains challenging to determine in advance how architectural choices, such as encoding strategies, gate placement, and entangling…

Quantum Physics · Physics 2026-04-07 Kyle James Stuart Campbell , Luigi Del Debbio , Petros Wallden

We present a general quantum circuit design for finding eigenvalues of non-unitary matrices on quantum computers using the iterative phase estimation algorithm. In particular, we show how the method can be used for the simulation of…

Quantum Physics · Physics 2013-11-01 Anmer Daskin , Ananth Grama , Sabre Kais

Practical success of quantum learning models hinges on having a suitable structure for the parameterized quantum circuit. Such structure is defined both by the types of gates employed and by the correlations of their parameters. While much…

Quantum Physics · Physics 2024-02-29 Frederic Sauvage , Martin Larocca , Patrick J. Coles , M. Cerezo

Two different algorithms are presented for generating a quantum circuit realization of a matrix representing a permutation on $2^n$ letters. All circuits involve $n$ qubits and only use multi--controlled Toffoli gates. The first algorithm…

Quantum Physics · Physics 2025-12-16 Jason Hanson

In this paper, we develop a Lie group theoretic approach for parametric representation of unitary matrices. This leads to develop a quantum neural network framework for quantum circuit approximation of multi-qubit unitary gates. Layers of…

Quantum Physics · Physics 2025-03-26 Rohit Sarma Sarkar , Bibhas Adhikari

In the age of noisy quantum processors, the exploitation of quantum symmetries can be quite beneficial in the efficient preparation of trial states, an important part of the variational quantum eigensolver algorithm. The benefits include…

Quantum Physics · Physics 2023-08-21 Babatunde M. Ayeni

The process of translating a quantum algorithm into a form suitable for implementation on a quantum computing platform is crucial but yet challenging. This entails specifying quantum operations with precision, a typically intricate task. In…

Quantum Physics · Physics 2024-08-26 M. Zomorodi , H. Amini , M. Abbaszadeh , J. Sohrabi , V. Salari , P. Plawiak

Many promising quantum algorithms in economics, medical science, and material science rely on circuits that are parameterized by a large number of angles. To ensure that these algorithms are efficient, these parameterized circuits must be…

Quantum Physics · Physics 2025-07-09 Neil J. Ross , Scott Wesley

We construct quantum circuits which exactly encode the spectra of correlated electron models up to errors from rotation synthesis. By invoking these circuits as oracles within the recently introduced "qubitization" framework, one can use…

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

The variational quantum eigensolver is a prominent hybrid quantum-classical algorithm expected to impact near-term quantum devices. They are usually based on a circuit ansatz consisting of parameterized single-qubit gates and fixed…

Quantum Physics · Physics 2022-10-13 S. E. Rasmussen , N. T. Zinner

In the current noisy intermediate-scale quantum (NISQ) era, quantum machine learning is emerging as a dominant paradigm to program gate-based quantum computers. In quantum machine learning, the gates of a quantum circuit are parametrized,…

Quantum Physics · Physics 2022-06-15 Osvaldo Simeone

Parameterised quantum circuits (PQCs) hold great promise for demonstrating quantum advantages in practical applications of quantum computation. Examples of successful applications include the variational quantum eigensolver, the quantum…

Quantum Physics · Physics 2024-04-30 Xin Hong , Wei-Jia Huang , Wei-Chen Chien , Yuan Feng , Min-Hsiu Hsieh , Sanjiang Li , Mingsheng Ying

Diagrammatic representations of quantum algorithms and circuits offer novel approaches to their design and analysis. In this work, we describe extensions of the ZX-calculus especially suitable for parameterized quantum circuits, in…

Quantum Physics · Physics 2023-11-16 Tobias Stollenwerk , Stuart Hadfield

Constructing general programmable circuits to be able to run any given unitary operator efficiently on a quantum processor is of fundamental importance. We present a new quantum circuit design technique resulting two general programmable…

Quantum Physics · Physics 2012-07-24 Anmer Daskin , Ananth Grama , Giorgos Kollias , Sabre Kais

A key open question in quantum computing is whether quantum algorithms can potentially offer a significant advantage over classical algorithms for tasks of practical interest. Understanding the limits of classical computing in simulating…

Quantum Physics · Physics 2021-06-23 Matija Medvidovic , Giuseppe Carleo

Given an arbitrary $2^w \times 2^w$ unitary matrix $U$, a powerful matrix decomposition can be applied, leading to four different syntheses of a $w$-qubit quantum circuit performing the unitary transformation. The demonstration is based on…

Quantum Physics · Physics 2016-11-18 Alexis De Vos , Stijn De Baerdemacker

In Variational Quantum Simulations, the construction of a suitable parametric quantum circuit is subject to two counteracting effects. The number of parameters should be small for the device noise to be manageable, but also large enough for…

Quantum Physics · Physics 2026-03-13 Lena Funcke , Tobias Hartung , Karl Jansen , Stefan Kühn , Manuel Schneider , Paolo Stornati

An algorithm is proposed to convert arbitrary unitary matrix to a sequence of $X$ gates and fully controlled $R_y, R_z$ and $R_1$ gates. This algorithm is used to generate Q# implementation for arbitrary unitary matrix. Some optimizations…

Quantum Physics · Physics 2025-01-15 Dmytro Fedoriaka

Quantum access to arbitrary classical data encoded in unitary black-box oracles underlies interesting data-intensive quantum algorithms, such as machine learning or electronic structure simulation. The feasibility of these applications…

Quantum Physics · Physics 2025-12-23 Shuchen Zhu , Aarthi Sundaram , Guang Hao Low
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