### 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.

April 7, 2020

- Source: Wall Street Journal

At Qu&Co we always restrained ourselves from reacting to exaggerated claims about the short-term potential of quantum-computing. Rather we focused on our scientifically rigorous work to advance the field of quantum as we strongly believe in its long-term potential. However, we draw the line at quantum being pushed as a short-term solution for researchers working on COVID, like this WSJ article in which a quantum hardware manufacturer offers free hardware access to researchers studying COVID, stating ‘we have a fairly unique system that could add value’. Although this offer could be a misplaced April-fools joke, we want to stress that, although quantum has strong long-term potential, there is zero chance it will provide any short-term value for COVID research. Therefore, no serious researchers working on the current pandemic should be distracted by this offer. If you are determined to use novel methods to solve today’s combinatorial optimisation problems, perhaps try simulated annealing on a purpose-built classical processor. And of course, if your time horizon is >2 years and you want to work on collaborative quantum-algorithm R&D, without distracting scarce COVID R&D staff, we are here to help. Stay safe and focused!

January 31, 2020

- Source: arXiv

In this arXiv submission by Qu & Co and Covestro, a well-known approximation in classical computational methods for quantum chemistry is applied to a quantum computing scheme for simulating molecular chemistry efficiently on near-term quantum devices. The restricted mapping allows for a polynomial reduction in both the quantum circuit depth and the total number of measurements required, as compared to the conventional variational approaches based on near-term quantum simulation of molecular chemistry, such as UCCSD. This enables faster runtime convergence of the variational algorithm to a potentially higher accuracy by using a larger basis set allowed by the restricted mapping. The latter is shown via an example simulation of the disassociation curve of lithium hydride. These results open up a new direction for efficient near-term quantum chemistry simulation, as well as decreasing the effective quantum resource requirements for future fault-tolerant quantum computing schemes.

September 21, 2019

- Source: Scott Aaronson

Recently some contributors to a paper describing a quantum-supremacy experiment inadvertently posted an older version of this paper online, which was quickly picked-up by the popular press resulting in a flurry of (in many cases) unfounded claims about the progress of quantum-computing. We believe that it is important for people interested in this topic to inform themselves through reading a balanced opinion from someone who is an expert in this field. Therefore we kindly refer to Scott Aaronson's excellent blogpost on this matter.

July 12, 2019

- Source: McKinsey & Co

In this article by McKinsey & Co, a strategy consulting firm, Florian Budde and Daniel Volz state that the chemical companies must act now to capture the benefits of quantum computing. Of course we at Qu & Co are a bit biased on this topic, but we do agree with the authors that the chemical sector is likely to be an early beneficiary of the vastly expanded modeling and computational capabilities, which is promised to be unlocked by quantum computing.

May 13, 2019

- Source: The Boston Consulting Group

In this market outlook, The Boston Consulting group assesses how and where quantum computing will create business value, the likely progression, and what steps executives should take now to put their firms in the best position to capture that value. The report is based on interviews and workshops involving more than 100 experts, a review of some 150 peer-reviewed publications, and analysis of more than 35 potential use cases.

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.

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