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Related papers: Defects in Quantum Computers

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We analyze the problem of optimal adiabatic passage through a quantum critical point. We show that to minimize the number of defects the tuning parameter should be changed as a power-law in time. The optimal power is proportional to the…

Other Condensed Matter · Physics 2008-08-15 Roman Barankov , Anatoli Polkovnikov

We lay the foundation for a benchmarking methodology for assessing current and future quantum computers. We pose and begin addressing fundamental questions about how to fairly compare computational devices at vastly different stages of…

Quantum Physics · Physics 2016-04-04 Ojas Parekh , Jeremy Wendt , Luke Shulenburger , Andrew Landahl , Jonathan Moussa , John Aidun

The presence of noise in quantum computers hinders their effective operation. Even though quantum error correction can theoretically remedy this problem, its practical realization is still a challenge. Testing and benchmarking noisy,…

Quantum Physics · Physics 2023-02-15 Adrian Ortega , Orsolya Kálmán , Tamás Kiss

Quantum annealing is a promising method for solving combinational optimization problems and performing quantum chemical calculations. The main sources of errors in quantum annealing are the effects of decoherence and non-adiabatic…

Quantum Physics · Physics 2022-11-23 Takashi Imoto , Yuya Seki , Yuichiro Matsuzaki and , Shiro Kawabata

Fault tolerant quantum computers will require efficient co-processors for real-time decoding of their adopted quantum error correction protocols. In this work we examine the possibility of using specialised Ising model hardware to perform…

Quantum Physics · Physics 2019-03-26 Joschka Roffe , Stefan Zohren , Dominic Horsman , Nicholas Chancellor

The recent emergence of novel computational devices, such as adiabatic quantum computers, CMOS annealers, and optical parametric oscillators, present new opportunities for hybrid-optimization algorithms that are hardware accelerated by…

Optimization and Control · Mathematics 2019-06-20 Carleton Coffrin , Harsha Nagarajan , Russell Bent

A quantum system will stay near its instantaneous ground state if the Hamiltonian that governs its evolution varies slowly enough. This quantum adiabatic behavior is the basis of a new class of algorithms for quantum computing. We test one…

Quantum Physics · Physics 2009-11-07 Edward Farhi , Jeffrey Goldstone , Sam Gutmann , Joshua Lapan , Andrew Lundgren , Daniel Preda

Analog models of quantum information processing, such as adiabatic quantum computation and analog quantum simulation, require the ability to subject a system to precisely specified Hamiltonians. Unfortunately, the hardware used to implement…

Quantum Physics · Physics 2014-02-25 Kevin C. Young , Robin Blume-Kohout , Daniel A. Lidar

We illustrate the adiabatic quantum computing solution of the knapsack problem with both integer profits and weights. For problems with $n$ objects (or items) and integer capacity $c$, we give specific examples using both an Ising class…

Quantum Physics · Physics 2017-01-23 Mark W. Coffey

By analyzing the characteristics of hardware-native Ising Models and their performance on current and next generation quantum annealers, we provide a framework for determining the prospect of advantage utilizing adiabatic evolution compared…

Quantum Physics · Physics 2024-06-25 Salvatore Certo , Georgios Korpas , Andrew Vlasic , Philip Intallura

Adiabatic quantum computing (AQC) started as an approach to solving optimization problems, and has evolved into an important universal alternative to the standard circuit model of quantum computing, with deep connections to both classical…

Quantum Physics · Physics 2018-02-05 Tameem Albash , Daniel A. Lidar

Quantum information processing offers dramatic speedups, yet is famously susceptible to decoherence, the process whereby quantum superpositions decay into mutually exclusive classical alternatives, thus robbing quantum computers of their…

Quantum Physics · Physics 2014-08-21 Kristen L. Pudenz , Tameem Albash , Daniel A. Lidar

Adiabatic quantum computation has recently attracted attention in the physics and computer science communities, but its computational power was unknown. We describe an efficient adiabatic simulation of any given quantum algorithm, which…

Quantum Physics · Physics 2007-11-22 Dorit Aharonov , Wim van Dam , Julia Kempe , Zeph Landau , Seth Lloyd , Oded Regev

A large class of optimisation problems can be mapped to the Ising model where all details are encoded in the coupling of spins. The task of the original mathematical optimisation is then equivalent to finding the ground state of the…

The goal of this paper is to introduce building blocks for adiabatic quantum algorithms. Adiabatic quantum computing uses the principle of quantum annealing, which implies that a carefully controlled energy solution is optimal and…

Quantum Physics · Physics 2014-08-27 Richard H. Warren

Entangled many-body states are a key resource for quantum technologies. Yet their preparation through analog control of interacting quantum systems is often hindered by experimental imperfections. Here, we introduce the adiabatic echo…

A central challenge in the successful implementation of adiabatic quantum algorithms is to maintain the quantum adiabaticity during the entire evolution. However, the energy gap between the ground and the excited states of interacting…

Quantum Physics · Physics 2018-02-08 Lin Tian

Adiabatic control is a fundamental technique for manipulating quantum systems, guided by the quantum adiabatic theorem, which ensures suppressed nonadiabatic transitions under slow parameter variations. Quantum annealing, a heuristic…

Quantum Physics · Physics 2025-01-22 Yuta Shingu , Takuya Hatomura

Quantum annealing is a continuous-time heuristic quantum algorithm for solving or approximately solving classical optimization problems. The algorithm uses a schedule to interpolate between a driver Hamiltonian with an easy-to-prepare…

The ability to efficiently prepare ground states of quantum Hamiltonians via adiabatic protocols is typically limited by the smallest energy gap encountered during the quantum evolution. This presents a key obstacle for quantum simulation…