Relevance of Near-Term Quantum Computing in the Cloud: A Humanities Perspective

Author(s):  
Johanna Barzen ◽  
Frank Leymann ◽  
Michael Falkenthal ◽  
Daniel Vietz ◽  
Benjamin Weder ◽  
...  
Keyword(s):  
2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Dong-Gil Im ◽  
Chung-Hyun Lee ◽  
Yosep Kim ◽  
Hyunchul Nha ◽  
M. S. Kim ◽  
...  

AbstractQuantum teleportation exemplifies how the transmission of quantum information starkly differs from that of classical information and serves as a key protocol for quantum communication and quantum computing. While an ideal teleportation protocol requires noiseless quantum channels to share a pure maximally entangled state, the reality is that shared entanglement is often severely degraded due to various decoherence mechanisms. Although the quantum noise induced by the decoherence is indeed a major obstacle to realizing a near-term quantum network or processor with a limited number of qubits, the methodologies considered thus far to address this issue are resource-intensive. Here, we demonstrate a protocol that allows optimal quantum teleportation via noisy quantum channels without additional qubit resources. By analyzing teleportation in the framework of generalized quantum measurement, we optimize the teleportation protocol for noisy quantum channels. In particular, we experimentally demonstrate that our protocol enables to teleport an unknown qubit even via a single copy of an entangled state under strong decoherence that would otherwise preclude any quantum operation. Our work provides a useful methodology for practically coping with decoherence with a limited number of qubits and paves the way for realizing noisy intermediate-scale quantum computing and quantum communication.


2021 ◽  
Author(s):  
Oliver Barima ◽  

Digital computing and allied communication tools have been phenomenal, but they are fast reaching their technical limits and also their capacity to solve certain extant complex problems. Quantum computing has now emerged with a touted potential to deal with aspects of the latter complex problems and also significantly transform extant computing and communication methods. Yet, little studies exist in the Architectural, Engineering and Construction (AEC) industry related literature on quantum computing to boost awareness and also explore its prospective impact on the AEC industry. This study discusses the underpinning basic concepts, technologies and trends in the quantum computing domain to build awareness to boost Architecture, Engineering and Construction (AEC) industry capacity on the topic. The research dissects the challenges in this novel area. And also examines the near-term practical opportunities and potential impact of quantum computing on the AEC industry. The study concludes with suggestions for practice and future research.


2020 ◽  
pp. 1-5
Author(s):  
Bahman Zohuri ◽  
◽  
Farhang Mossavar Rahmani ◽  

Companies such as Intel as a pioneer in chip design for computing are pushing the edge of computing from its present Classical Computing generation to the next generation of Quantum Computing. Along the side of Intel corporation, companies such as IBM, Microsoft, and Google are also playing in this domain. The race is on to build the world’s first meaningful quantum computer—one that can deliver the technology’s long-promised ability to help scientists do things like develop miraculous new materials, encrypt data with near-perfect security and accurately predict how Earth’s climate will change. Such a machine is likely more than a decade away, but IBM, Microsoft, Google, Intel, and other tech heavyweights breathlessly tout each tiny, incremental step along the way. Most of these milestones involve packing more quantum bits, or qubits—the basic unit of information in a quantum computer—onto a processor chip ever. But the path to quantum computing involves far more than wrangling subatomic particles. Such computing capabilities are opening a new area into dealing with the massive sheer volume of structured and unstructured data in the form of Big Data, is an excellent augmentation to Artificial Intelligence (AI) and would allow it to thrive to its next generation of Super Artificial Intelligence (SAI) in the near-term time frame.


2020 ◽  
Vol 8 ◽  
Author(s):  
Hai-Ping Cheng ◽  
Erik Deumens ◽  
James K. Freericks ◽  
Chenglong Li ◽  
Beverly A. Sanders

Chemistry is considered as one of the more promising applications to science of near-term quantum computing. Recent work in transitioning classical algorithms to a quantum computer has led to great strides in improving quantum algorithms and illustrating their quantum advantage. Because of the limitations of near-term quantum computers, the most effective strategies split the work over classical and quantum computers. There is a proven set of methods in computational chemistry and materials physics that has used this same idea of splitting a complex physical system into parts that are treated at different levels of theory to obtain solutions for the complete physical system for which a brute force solution with a single method is not feasible. These methods are variously known as embedding, multi-scale, and fragment techniques and methods. We review these methods and then propose the embedding approach as a method for describing complex biochemical systems, with the parts not only treated with different levels of theory, but computed with hybrid classical and quantum algorithms. Such strategies are critical if one wants to expand the focus to biochemical molecules that contain active regions that cannot be properly explained with traditional algorithms on classical computers. While we do not solve this problem here, we provide an overview of where the field is going to enable such problems to be tackled in the future.


Research ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-11 ◽  
Author(s):  
Shijie Wei ◽  
Hang Li ◽  
GuiLu Long

Quantum simulation of quantum chemistry is one of the most compelling applications of quantum computing. It is of particular importance in areas ranging from materials science, biochemistry, and condensed matter physics. Here, we propose a full quantum eigensolver (FQE) algorithm to calculate the molecular ground energies and electronic structures using quantum gradient descent. Compared to existing classical-quantum hybrid methods such as variational quantum eigensolver (VQE), our method removes the classical optimizer and performs all the calculations on a quantum computer with faster convergence. The gradient descent iteration depth has a favorable complexity that is logarithmically dependent on the system size and inverse of the precision. Moreover, the FQE can be further simplified by exploiting a perturbation theory for the calculations of intermediate matrix elements and obtaining results with a precision that satisfies the requirement of chemistry application. The full quantum eigensolver can be implemented on a near-term quantum computer. With the rapid development of quantum computing hardware, the FQE provides an efficient and powerful tool to solve quantum chemistry problems.


Quantum ◽  
2020 ◽  
Vol 4 ◽  
pp. 303
Author(s):  
Madhav Krishnan Vijayan ◽  
Austin P. Lund ◽  
Peter P. Rohde

Error-detection and correction are necessary prerequisites for any scalable quantum computing architecture. Given the inevitability of unwanted physical noise in quantum systems and the propensity for errors to spread as computations proceed, computational outcomes can become substantially corrupted. This observation applies regardless of the choice of physical implementation. In the context of photonic quantum information processing, there has recently been much interest in passive linear optics quantum computing, which includes boson-sampling, as this model eliminates the highly-challenging requirements for feed-forward via fast, active control. That is, these systems are passive by definition. In usual scenarios, error detection and correction techniques are inherently active, making them incompatible with this model, arousing suspicion that physical error processes may be an insurmountable obstacle. Here we explore a photonic error-detection technique, based on W-state encoding of photonic qubits, which is entirely passive, based on post-selection, and compatible with these near-term photonic architectures of interest. We show that this W-state redundant encoding techniques enables the suppression of dephasing noise on photonic qubits via simple fan-out style operations, implemented by optical Fourier transform networks, which can be readily realised today. The protocol effectively maps dephasing noise into heralding failures, with zero failure probability in the ideal no-noise limit. We present our scheme in the context of a single photonic qubit passing through a noisy communication or quantum memory channel, which has not been generalised to the more general context of full quantum computation.


2020 ◽  
Author(s):  
Oliver Barima

<p>ABSTRACT</p><p></p><p>Digital computing and allied communication tools have been phenomenal, but they are fast reaching their technical limits and also their capacity to solve certain extant complex problems. Quantum computing has now emerged with a touted potential to deal with aspects of the latter complex problems and also significantly transform extant computing and communication methods. Yet, little studies exist in the AEC industry related literature on quantum computing to boost awareness and also explore its prospective impact on the AEC industry. </p> <p><br></p><p>This paper discusses the underpinning basic concepts, technologies and trends in the quantum computing domain to build awareness to boost Architecture, Engineering and Construction (AEC) industry capacity on the topic. The paper dissects the challenges in this novel area. And also examines the near term practical opportunities and potential impact of quantum computing on the AEC industry. The paper concludes with suggestions for practice and future research.</p><br><p></p>


2020 ◽  
Vol 108 (8) ◽  
pp. 1338-1352 ◽  
Author(s):  
Antonio D. Corcoles ◽  
Abhinav Kandala ◽  
Ali Javadi-Abhari ◽  
Douglas T. McClure ◽  
Andrew W. Cross ◽  
...  

Quantum ◽  
2020 ◽  
Vol 4 ◽  
pp. 263 ◽  
Author(s):  
Jonas M. Kübler ◽  
Andrew Arrasmith ◽  
Lukasz Cincio ◽  
Patrick J. Coles

Variational hybrid quantum-classical algorithms (VHQCAs) have the potential to be useful in the era of near-term quantum computing. However, recently there has been concern regarding the number of measurements needed for convergence of VHQCAs. Here, we address this concern by investigating the classical optimizer in VHQCAs. We introduce a novel optimizer called individual Coupled Adaptive Number of Shots (iCANS). This adaptive optimizer frugally selects the number of measurements (i.e., number of shots) both for a given iteration and for a given partial derivative in a stochastic gradient descent. We numerically simulate the performance of iCANS for the variational quantum eigensolver and for variational quantum compiling, with and without noise. In all cases, and especially in the noisy case, iCANS tends to out-perform state-of-the-art optimizers for VHQCAs. We therefore believe this adaptive optimizer will be useful for realistic VHQCA implementations, where the number of measurements is limited.


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