108,293 research outputs found
Unfolding Quantum Computer Readout Noise
In the current era of noisy intermediate-scale quantum (NISQ) computers,
noisy qubits can result in biased results for early quantum algorithm
applications. This is a significant challenge for interpreting results from
quantum computer simulations for quantum chemistry, nuclear physics, high
energy physics, and other emerging scientific applications. An important class
of qubit errors are readout errors. The most basic method to correct readout
errors is matrix inversion, using a response matrix built from simple
operations to probe the rate of transitions from known initial quantum states
to readout outcomes. One challenge with inverting matrices with large
off-diagonal components is that the results are sensitive to statistical
fluctuations. This challenge is familiar to high energy physics, where
prior-independent regularized matrix inversion techniques (`unfolding') have
been developed for years to correct for acceptance and detector effects when
performing differential cross section measurements. We study various unfolding
methods in the context of universal gate-based quantum computers with the goal
of connecting the fields of quantum information science and high energy physics
and providing a reference for future work. The method known as iterative
Bayesian unfolding is shown to avoid pathologies from commonly used matrix
inversion and least squares methods.Comment: 13 pages, 16 figures; v2 has a typo fixed in Eq. 3 and a series of
minor modification
Digital Quantum Simulation of the Statistical Mechanics of a Frustrated Magnet
Many interesting problems in physics, chemistry, and computer science are
equivalent to problems of interacting spins. However, most of these problems
require computational resources that are out of reach by classical computers. A
promising solution to overcome this challenge is to exploit the laws of quantum
mechanics to perform simulation. Several "analog" quantum simulations of
interacting spin systems have been realized experimentally. However, relying on
adiabatic techniques, these simulations are limited to preparing ground states
only. Here we report the first experimental results on a "digital" quantum
simulation on thermal states; we simulated a three-spin frustrated magnet, a
building block of spin ice, with an NMR quantum information processor, and we
are able to explore the phase diagram of the system at any simulated
temperature and external field. These results serve as a guide for identifying
the challenges for performing quantum simulation on physical systems at finite
temperatures, and pave the way towards large scale experimental simulations of
open quantum systems in condensed matter physics and chemistry.Comment: 7 pages for the main text plus 6 pages for the supplementary
material
Quantum Algorithm Animator
The design and development of quantum algorithms present a challenge, especially for inexperienced computer science students. Despite the numerous common concepts with classical computer science, quantum computation is still considered a branch of theoretical physics not commonly used by computer scientists. Experimental research into the development of a quantum computer makes the use of quantum mechanics in organizing computation more attractive, however the physical realization of a working quantum computer may still be decades away.
This study introduces quantum computing to computer science students using a quantum algorithm animator called QuAL. QuAL\u27s design uses features common to classical algorithm animators guided by an exploratory study but refined to animate the esoteric and interesting aspects of quantum algorithms.
In addition, this study investigates the potential for the animation of a quantum sorting algorithm to help novice computer science students understand the formidable concepts of quantum computing. The animations focus on the concepts required to understand enough about quantum algorithms to entice student interest and promote the integration of quantum computational concepts into computer science applications and curricula.
The experimental case study showed no significant improvement in student learning when using QuAL\u27s initial prototype. Possible reasons include the animator\u27s presentation of concepts and the study\u27s pedagogical framework such as choice of algorithm (Wallace and Narayanan\u27s sorting algorithm), design of pre- and post tests, and the study\u27s small size (20 students) and brief duration (2 hours). Nonetheless, the animation system was well received by students. Future work includes enhancing this animation tool for illustrating elusive concepts in quantum computing
QJava: A Monadic Java Library for Quantum Programming
To help the understanding and development of quantum algorithms there is an effort focused on the investigation of new semantic models and programming languages for quantum computing. Researchers in computer science have the challenge of deve loping programming languages to support the creation, analysis, modeling and simulation of high level quantum algorithms. Based on previous works that use monads inside the programming language Haskell to elegantly explain the odd characteristics of quantum computation (like superposition and entanglement), in this work we present a monadic Java library for quantum programming. We use the extension of the programming language Java called BGGA Closure, that allow the manipulation of anonymous functions (closures) inside Java. We exemplify the use of the library with an implementation of the Toffoli quantum circuit
Near-Term Quantum Computing Techniques: Variational Quantum Algorithms, Error Mitigation, Circuit Compilation, Benchmarking and Classical Simulation
Quantum computing is a game-changing technology for global academia, research
centers and industries including computational science, mathematics, finance,
pharmaceutical, materials science, chemistry and cryptography. Although it has
seen a major boost in the last decade, we are still a long way from reaching
the maturity of a full-fledged quantum computer. That said, we will be in the
Noisy-Intermediate Scale Quantum (NISQ) era for a long time, working on dozens
or even thousands of qubits quantum computing systems. An outstanding
challenge, then, is to come up with an application that can reliably carry out
a nontrivial task of interest on the near-term quantum devices with
non-negligible quantum noise. To address this challenge, several near-term
quantum computing techniques, including variational quantum algorithms, error
mitigation, quantum circuit compilation and benchmarking protocols, have been
proposed to characterize and mitigate errors, and to implement algorithms with
a certain resistance to noise, so as to enhance the capabilities of near-term
quantum devices and explore the boundaries of their ability to realize useful
applications. Besides, the development of near-term quantum devices is
inseparable from the efficient classical simulation, which plays a vital role
in quantum algorithm design and verification, error-tolerant verification and
other applications. This review will provide a thorough introduction of these
near-term quantum computing techniques, report on their progress, and finally
discuss the future prospect of these techniques, which we hope will motivate
researchers to undertake additional studies in this field.Comment: Please feel free to email He-Liang Huang with any comments,
questions, suggestions or concern
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Digital Quantum Simulation of the Statistical Mechanics of a Frustrated Magnet
Many problems of interest in physics, chemistry and computer science are equivalent to problems defined on systems of interacting spins. However, most such problems require computational resources that are out of reach with classical computers. A promising solution to overcome this challenge is quantum simulation. Several 'analogue' quantum simulations of interacting spin systems have been realized experimentally, where ground states were prepared using adiabatic techniques. Here we report a 'digital' quantum simulation of thermal states; a three-spin frustrated magnet was simulated using a nuclear magnetic resonance quantum information processor, and we were able to explore the phase diagram of the system at any simulated temperature and external field. These results help to identify the challenges for performing quantum simulations of physical systems at finite temperatures, and suggest methods that may be useful in simulating thermal open quantum systems.Chemistry and Chemical Biolog
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