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Related papers: AI methods for approximate compiling of unitaries

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Quantum compilation provides a method to translate quantum algorithms at a high level of abstraction into their implementations as quantum circuits on real hardware. One approach to quantum compiling is to design a parameterised circuit and…

Quantum Physics · Physics 2022-10-18 Niall F. Robertson , Albert Akhriev , Jiri Vala , Sergiy Zhuk

A quantum compiling algorithm is an algorithm for decomposing ("compiling") an arbitrary unitary matrix into a sequence of elementary operations (SEO). Suppose $U_{in}$ is an $\nb$-bit unstructured unitary matrix (a unitary matrix with no…

Quantum Physics · Physics 2007-05-23 Robert R. Tucci

Quantum Approximation Optimization Algorithm (QAOA) is a highly advocated variational algorithm for solving the combinatorial optimization problem. One critical feature in the quantum circuit of QAOA algorithm is that it consists of…

Quantum Physics · Physics 2022-07-21 Yuwei Jin , Jason Luo , Lucent Fong , Yanhao Chen , Ari B. Hayes , Chi Zhang , Fei Hua , Eddy Z. Zhang

Quantum computing is a promising paradigm that may overcome the current computational power bottlenecks. The increasing maturity of quantum processors provides more possibilities for the development and implementation of quantum algorithms.…

Quantum Physics · Physics 2025-10-15 Ge Yan , Wenjie Wu , Yuheng Chen , Kaisen Pan , Xudong Lu , Zixiang Zhou , Yuhan Wang , Ruocheng Wang , Junchi Yan

We propose and validate on real quantum computing hardware a new method for extended two-qubit gate set design, replacing iterative, fine calibration with fast characterization of a small number of gate parameters which are then tracked and…

We give three new algorithms for efficient in-place estimation, without using ancilla qubits, of average fidelity of a quantum logic gate acting on a d-dimensional system using much fewer random bits than what was known so far. Previous…

Quantum Physics · Physics 2019-01-23 Aditya Nema , Pranab Sen

Advanced simulations and calculations on quantum computers require high-fidelity implementations of quantum operations. The universal gateset approach builds complex unitaries from a small set of primitive gates, often resulting in a long…

Mixed-precision quantization methods have been proposed to reduce model size while minimizing accuracy degradation. However, existing studies require retraining and do not consider the computational overhead and intermediate representations…

Artificial Intelligence · Computer Science 2025-01-14 Jeongseok Kim , Jemin Lee , Yongin Kwon , Daeyoung Kim

As quantum processors grow in scale and reliability, the need for efficient quantum gate decomposition of circuits to a set of specific available gates, becomes ever more critical. The decomposition of a particular algorithm into a sequence…

Quantum Physics · Physics 2025-01-30 Jonathan Nemirovsky , Maya Chuchem , Yotam Shapira

We discuss the implementation of an iterative quantum phase estimation algorithm, with a single ancillary qubit. We suggest using this algorithm as a benchmark for multi-qubit implementations. Furthermore we describe in detail the smallest…

Quantum Physics · Physics 2010-03-26 M. Dobsicek , G. Johansson , V. S. Shumeiko , G. Wendin

The architecture of circuital quantum computers requires computing layers devoted to compiling high-level quantum algorithms into lower-level circuits of quantum gates. The general problem of quantum compiling is to approximate any unitary…

Quantum Physics · Physics 2021-09-21 Lorenzo Moro , Matteo G. A. Paris , Marcello Restelli , Enrico Prati

This paper overviews the basic principles and recent advances in the emerging field of Quantum Computation (QC), highlighting its potential application to Artificial Intelligence (AI). The paper provides a very brief introduction to basic…

Artificial Intelligence · Computer Science 2007-05-24 Kyriakos N. Sgarbas

Overcoming the influence of noise and imperfections in quantum devices is one of the main challenges for viable quantum applications. In this article, we present different protocols, which we denote as "superposed quantum error mitigation",…

Recent developments in engineering and algorithms have made real-world applications in quantum computing possible in the near future. Existing quantum programming languages and compilers use a quantum assembly language composed of 1- and…

Compiling quantum algorithms for near-term quantum computers (accounting for connectivity and native gate alphabets) is a major challenge that has received significant attention both by industry and academia. Avoiding the exponential…

With improved gate calibrations reducing unitary errors, we achieve a benchmarked single-qubit gate fidelity of 99.95% with superconducting qubits in a circuit quantum electrodynamics system. We present a method for distinguishing between…

Quantum Physics · Physics 2016-01-13 Sarah Sheldon , Lev S. Bishop , Easwar Magesan , Stefan Filipp , Jerry M. Chow , Jay M. Gambetta

There is currently a significant need for robust and efficient methods for characterizing quantum devices. While there has been significant progress in this direction, there remains a crucial need to precisely determine the strength and…

Quantum Physics · Physics 2019-09-04 Arnaud Carignan-Dugas , Joel J. Wallman , Joseph Emerson

Here we present a technique for using machine learning (ML) for single-qubit gate synthesis on field programmable logic for a superconducting transmon-based quantum computer based on simulated studies. Our approach is multi-stage. We first…

Compilation optimizes quantum algorithms performances on real-world quantum computers. To date, it is performed via classical optimization strategies. We introduce a class of quantum algorithms to perform compilation via quantum computers,…

Quantum Physics · Physics 2025-09-25 Davide Rattacaso , Daniel Jaschke , Marco Ballarin , Ilaria Siloi , Simone Montangero

Recently, the demand of low-power deep-learning hardware for industrial applications has been increasing. Most existing artificial intelligence (AI) chips have evolved to rely on new chip technologies rather than on radically new hardware…

Machine Learning · Computer Science 2020-02-14 Byungik Ahn