### Quantum-computing related developments

On this page we post about interesting quantum-computing related research and news which we are following.

On this page we post about interesting quantum-computing related research and news which we are following.

March 14, 2019

- Source: arXiv

Currently, the latest state-of-the-art quantum computers are so-called NISQ (noisy intermediate-scale quantum) devices, meaning they have a number of qubits which approaches competition with classical simulation of the output of such systems, yet the systems are noisy and no fault-tolerance can be achieved yet. The question is: are there methods which can sufficiently compensate for their noisy nature, enabling the emergence of quantum advantage on these devices? In recent years, many error correction and mitigation schemes have been developed: from Richardson extrapolation techniques to extend results down to `zero noise’, to parity check measurements and more. But typically, those techniques require additional complicated circuitry, ancillary qubits, pulse modifications, or calibration/tuning steps. In this paper, an alternative strategy based on the general principle of a class of methods called Quantum Subspace Expansion (QSE) is proposed. In this strategy, one performs clever post-processing of classical data with or without additional measurements with (at most) simple additional operations in the circuit and no (scaling) ancillary qubits. This paper generalizes the application of QSE error mitigation to any quantum computation, not restricting itself necessarily to problem-specifics like chemistry. Another interesting idea presented here is to use NISQ devices to experimentally study small quantum codes for later use in larger-scale quantum computers implementing error correcting code, such as in future FTQC (fault-tolerant quantum computing).

January 15, 2019

- Source: ArXiv

Thus far, quantum chemistry quantum algorithms have been experimentally demonstrated only on gate-based quantum computers. Efforts have been made to also map the chemistry problem Fermionic Hamiltonian to an Ising Hamiltonian in order to solve it on a quantum annealer. However, the number of qubits required still scales exponentially with the problem size (the number of orbitals considered in the electronic structure problem). As an alternative, this paper presents a different approach exploiting the efficiency at which quantum annealers can solve discrete optimization problems, and mapping a qubit coupled cluster method to this form. They simulate their method on an ideal Ising machine and on a D-Wave 2000Q system, and find promising success rates for smaller molecules. However, further investigation would be necessary to investigate the usability for larger or more complex systems, as the scaling of their folding technique with the number of local minima is unknown. In addition, it is unclear from the experimental data whether the limitations of the D-Wave system as compared to a perfect Ising machine could hinder expected performance gains for more complex systems.

December 17, 2018

- Source: Fact Based Insight

In this online market and technology outlook, Fact Based Insight, a quantum-technology consultancy, provides their predictions for the developments in the quantum-sector in 2019 and beyond. The report covers developments in qubit technologies and quantum-processors, quantum-software, quantum safe cryptography and quantum-imaging, -sensing and -timing technologies.

December 15, 2018

- Source: The National Academies Press

With this report, the National Academy of Sciences, a US based non-profit, and more specifically its Committee on technical assessment of the feasibility and implications of quantum computing chaired by Mark Horowitz, aims to help bring clarity about the current state of the art, likely progress toward, and ramifications of, a general-purpose quantum computer and to clarify the theoretical characteristics and limitations of quantum computing and to correct some common public misperceptions about the field. Specifically, the committee focused on understanding the current state of quantum computing hardware, software, and algorithms, and what advances would be needed to create a scalable, gate-based quantum computer capable of deploying Shor’s algorithm. Early in this process, it became clear that the current engineering approaches could not directly scale to the size needed to create this scalable, fully error corrected quantum computer. As a result, the group focused on finding intermediate milestones and metrics to track the progress toward this goal.

December 1, 2018

- Source: Deloitte

In the last chapter (from page 96) of the 2019 version of its annual report Technology, Media, and Telecommunications Predictions, Deloitte, a business consultancy, provides their five key predictions for the development of quantum-computing in 2019 and beyond. These are: 1) Quantum computers will not replace clas- sical computers for decades, if ever. 2) The quantum computer market of the future will be about the size of today’s supercomputer market—around US$50 billion. 3) The first commercial general-purpose quantum computers will appear in the 2030s at earliest. 4) The Noisy Intermediate Scale Quantum (NISQ) computing market—using what could be considered early-stage QCs—will be worth hundreds of millions of dollars per year in the 2020s. 5) The quantum-safe security industry is also likely to be worth hundreds of mil- lions of dollars per year in the 2020s.

November 15, 2018

- Source: The Boston Consulting Group

This report by The Boston Consulting Group, a strategy consulting firm, targets business executives and other people looking for a broader market overview on quantum computing. The authors (Philipp Gerbert et al.) provide some insight in where the technology currently stands, who is who in the emerging ecosystem, and the potentially interesting applications. The report also analyzes some of the leading indicators of investments, patents, and publications, which countries and entities are most active and the status and prospects for the main categories of quantum hardware technologies. Additionally, the report aims to provide a simple framework for understanding quantum algorithms and assessing their applicability and potential. Finally, the authors provide their view of what can be expected in the next five to ten years, and what corporates should be doing, or getting ready for, in response.

August 27, 2018

- Source: ArXiv

Ever since the publication of Shor’s algorithm in 1994, efficient integer factorization has been a key application area envisioned for quantum-computers, with important implications for the security of some of the most used cryptosystems. Because Shor’s algorithm requires a large-scale fault-tolerant quantum-processor, RSA-3072 encryption was so-far believed to remain safe until 2030. However, in recent years hybrid (classical-quantum) alternatives have been developed for many important quantum-algorithms. Such hybrid algorithms can be run on current-day noisy and small-scale quantum-processors. In this paper Eric Anschuetz et al. describe such a hybrid alternative for Shor’s algorithm, which they call variational quantum factoring (VQF). If some pre-processing is applied VQF scales with O(n), n being the number of bits of the integer being factored. If VQF can be optimized to scale well up to 3000+ qubits, which is very challenging, but not completely unthinkable, and if we assume the number of physical qubits in quantum-processors doubles every year, quantum-processors could have sufficiently high qubit count to break RSA-3072 as early as 2025. However, as VQF relies on a quantum-optimization algorithm (QAOA) it seems unlikely that the speed-up of VQF could be more than quadratic, which means that the runtime for breaking RSA-3072 could very well be prohibitively long and that doubling the RSA-6144 (double the key-length) would again be just as safe as RSA-3072 is currently.

July 11, 2018

- Source: Arxiv

Many financial services players are experimenting with quantum-computing so that they can be the first to start exploiting its benefits in speed-up and tractability. Algorithms have been developed for a wide range of finance related topics e.g. Monte Carlo simulation, portfolio optimization, anomaly (fraud) detection, market forecasting and reduction of slippage. In this paper Orus et al. provide a nice overview of most of these applications. Although the paper puts much emphasis on what has been done with quantum-annealers, applying the Quantum Approximate Optimization Algorithm (QAOA) lets us map all of them to universal-gate devices, which ensures that these applications stay relevant even when annealers become obsolete.

May 16, 2018

- Source: The Boston Consulting Group

This report by The Boston Consulting Group, a strategy consulting firm, provides both an introductory status overview of current and near-term qubit technologies and of practical quantum-computing applications as well as a longer-term outlook of the quantum-computing market, which the authors (Massimo Russo et al.) estimate could be as large as $50bln by 2030. The report also provides some advice to corporates on how to prepare for the arrival of practical quantum-computing applications

April 19, 2018

- Source: Arxiv

Recently, promising experimental results have been shown for quantum-chemistry calculations using small, noisy quantum processors. As full scale fault-tolerant error correction is still many years away, near-term quantum computers will have a limited number of qubits, and each qubit will be noisy. Methods that reduce noise and correct errors without doing full error correction on every qubit will help extend the range of interesting problems that can be solved in the near-term. In this paper Otten et al. present a scheme for accounting (and removal) of errors in observables determined from quantum algorithms and apply this scheme to the variational quantum eigensolver algorithm, simulating the calculation of the ground state energy of equilibrium H2 and LiH in the presence of several noise sources, including amplitude damping, dephasing, thermal noise, and correlated noise. They show that their scheme provides a decrease in the needed quality of the qubits by up to two orders of magnitude.

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