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A Meet-in-the-Middle Algorithm for Fast Synthesis of Depth-Optimal Quantum Circuits

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TLDR
An algorithm for computing depth-optimal decompositions of logical operations, leveraging a meet-in-the-middle technique to provide a significant speedup over simple brute force algorithms is presented.
Abstract
We present an algorithm for computing depth-optimal decompositions of logical operations, leveraging a meet-in-the-middle technique to provide a significant speedup over simple brute force algorithms. As an illustration of our method, we implemented this algorithm and found factorizations of commonly used quantum logical operations into elementary gates in the Clifford+T set. In particular, we report a decomposition of the Toffoli gate over the set of Clifford and T gates. Our decomposition achieves a total T-depth of 3, thereby providing a 40% reduction over the previously best known decomposition for the Toffoli gate. Due to the size of the search space, the algorithm is only practical for small parameters, such as the number of qubits, and the number of gates in an optimal implementation.

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Experimental Comparison of Two Quantum Computing Architectures

TL;DR: It is shown that quantum algorithms and circuits that use more connectivity clearly benefit from a better-connected system of qubits, and suggested that codesigning particular quantum applications with the hardware itself will be paramount in successfully using quantum computers in the future.
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Roads towards fault-tolerant universal quantum computation

TL;DR: In this article, the authors proposed a fault-tolerant logical qubit architecture for quantum computers, which uses high-dimensional quantum codes in a modular architecture, but need to be explored further.
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Toward the first quantum simulation with quantum speedup.

TL;DR: It is argued that simulating the time evolution of spin systems is a classically hard problem of practical interest that is among the easiest to address with early quantum devices, and develops optimized implementations and performs detailed resource analyses for several leading quantum algorithms for this problem.
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Noisy intermediate-scale quantum algorithms

TL;DR: In this article , the authors discuss what is possible in this ''noisy intermediate scale'' quantum (NISQ) era, including simulation of many-body physics and chemistry, combinatorial optimization, and machine learning.
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Polynomial-Time T-Depth Optimization of Clifford+T Circuits Via Matroid Partitioning

TL;DR: A polynomial-time algorithm for optimizing quantum circuits that takes the actual implementation of fault-tolerant logical gates into consideration, allowing space-time trade-offs to be easily explored.
References
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Book

Quantum Computation and Quantum Information

TL;DR: In this article, the quantum Fourier transform and its application in quantum information theory is discussed, and distance measures for quantum information are defined. And quantum error-correction and entropy and information are discussed.
Journal ArticleDOI

Quantum computation and quantum information

TL;DR: This special issue of Mathematical Structures in Computer Science contains several contributions related to the modern field of Quantum Information and Quantum Computing, with a focus on entanglement.
Journal ArticleDOI

Quantum Mechanical Computers

TL;DR: The physical limitations due to quantum mechanics on the functioning of computers are analyzed in this paper, where the physical limitations of quantum mechanics are discussed and the physical limits of quantum computing are analyzed.
Journal ArticleDOI

Improved simulation of stabilizer circuits

TL;DR: The Gottesman-Knill theorem, which says that a stabilizer circuit, a quantum circuit consisting solely of controlled-NOT, Hadamard, and phase gates can be simulated efficiently on a classical computer, is improved in several directions.
Proceedings ArticleDOI

Exponential algorithmic speedup by a quantum walk

TL;DR: A black box graph traversal problem that can be solved exponentially faster on a quantum computer than on a classical computer is constructed and it is proved that no classical algorithm can solve the problem in subexponential time.
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