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Window glass, at the microscopic level, shows a strange mix of properties. Like a liquid, its atoms are disordered, but like a solid, its atom are rigid, so a force applied to one atom causes all of them to move.

It's an analogy physicists use to describe a quantum state called a "quantum spin-glass," in which quantum mechanical bits (qubits) in a quantum computer demonstrate both disorder (taking on seemingly random values) and rigidity (when one qubit flips, so do all the others). A team of Cornell researchers unexpectedly discovered the presence of this quantum state while conducting a research project designed to learn more about quantum algorithms and, relatedly, new strategies for error correction in quantum computing.

"Measuring the position of a quantum particle changes its momentum and vice versa. Similarly, for qubits there are quantities which change one another when they are measured. We find that certain random sequences of these incompatible measurements lead to the formation of a quantum spin-glass," said Erich Mueller, professor of physics in the College of Arts and Sciences (A&S). "One implication of our work is that some types of information are automatically protected in quantum algorithms which share the features of our model."

"Subsystem Symmetry, Spin-glass Order, and Criticality From Random Measurements in a Two-dimensional Bacon-Shor Circuit" published on July 31 in Physical Review B. The lead author is Vaibhav Sharma, a doctoral student in physics.

Assistant professor of physics Chao-Ming Jian (A&S) is a co-author along with Mueller. All three conduct their research at Cornell's Laboratory of Atomic and Solid State Physics (LASSP).

"We are trying to understand generic features of quantum algorithmsfeatures which transcend any particular algorithm," Sharma said. "Our strategy for revealing these universal features was to study random algorithms. We discovered that certain classes of algorithms lead to hidden 'spin-glass' order. We are now searching for other forms of hidden order and think that this will lead us to a new taxonomy of quantum states."

Random algorithms are those that incorporate a degree of randomness as part of the algorithme.g., random numbers to decide what to do next.

Mueller's proposal for the 2021 New Frontier Grant "Autonomous Quantum Subsystem Error Correction" aimed to simplify quantum computer architectures by developing a new strategy to correct for quantum processor errors caused by environmental noisethat is, any factor, such as cosmic rays or magnetic fields, that would interfere with a quantum computer's qubits, corrupting information.

The bits of classical computer systems are protected by error-correcting codes, Mueller said; information is replicated so that if one bit "flips," you can detect it and fix the error. "For quantum computing to be workable now and in the future, we need to come up with ways to protect qubits in the same way."

"The key to error correction is redundancy," Mueller said. "If I send three copies of a bit, you can tell if there is an error by comparing the bits with one another. We borrow language from cryptography for talking about such strategies and refer to the repeated set of bits as a 'codeword.'"

When they made their discovery about spin-glass order, Mueller and his team were looking into a generalization, where multiple codewords are used to represent the same information. For example, in a subsystem code, the bit "1" might be stored in 4 different ways: 111; 100; 101; and 001.

"The extra freedom that one has in quantum subsystem codes simplifies the process of detecting and correcting errors," Mueller said.

The researchers emphasized that they weren't simply trying to generate a better error protection scheme when they began this research. Rather, they were studying random algorithms to learn general properties of all such algorithms.

"Interestingly, we found nontrivial structure," Mueller said. "The most dramatic was the existence of this spin-glass order, which points toward there being some extra hidden information floating around, which should be useable in some way for computing, though we don't know how yet."

More information: Vaibhav Sharma et al, Subsystem symmetry, spin-glass order, and criticality from random measurements in a two-dimensional Bacon-Shor circuit, Physical Review B (2023). DOI: 10.1103/PhysRevB.108.024205

Journal information: Physical Review B

Here is the original post:
Promising quantum state found during error correction research - Phys.org

Dublin, Sept. 07, 2023 (GLOBE NEWSWIRE) -- The "Global Quantum Computing in Healthcare Market Size, Share & Industry Trends Analysis Report By Deployment, By Component (Hardware, Software, and Services), By Technology, By Application, By End User, By Regional Outlook and Forecast, 2023 - 2030" report has been added to ResearchAndMarkets.com's offering.

The global Quantum Computing in Healthcare market is on a trajectory for substantial growth, with a projected market size of $1 billion by 2030. The market is expected to experience a remarkable Compound Annual Growth Rate (CAGR) of 45.4% during the forecast period.

Radiotherapy Segment to Drive Significant Revenue

In 2022, the Radiotherapy segment emerged as a major revenue contributor in the Quantum Computing in Healthcare market, generating $5,335.2 million. Radiotherapy involves the use of radiation to eliminate malignant cells or halt their proliferation, frequently used in cancer treatment. Developing a radiation plan that minimizes harm to healthy tissues and body parts is crucial. This process entails complex optimization challenges with numerous variables. Quantum computing can assist in simulating a wide range of possibilities between each iteration, enabling healthcare professionals to concurrently run multiple simulations and formulate an optimal radiation strategy.

Partnerships Driving Market Development

Key market participants are embracing partnerships as a strategic approach to meet evolving end-user demands:

Market Competition Analysis

Google LLC leads the market, notably partnering with Bayer AG for drug discovery. Additionally, companies such as Accenture PLC, IBM Corporation, and Protiviti Inc. are playing crucial roles in driving innovation in the Quantum Computing in Healthcare market.

Factors Driving Market Growth

Two key factors are propelling the growth of the Quantum Computing in Healthcare market:

Factors Restraining Market Growth

Several challenges hinder the quantum computing healthcare market's growth:

Market Segmentation

The Quantum Computing in Healthcare market is segmented based on components, technology, applications, end-users, and deployment:

Component:

Technology:

Application:

End-user:

Deployment:

Regional Outlook

As of 2022, North America leads the Quantum Computing in Healthcare market, with strong investments and collaborations driving quantum computing advancements. The development of quantum computing is particularly significant in the pharmaceutical and biopharmaceutical sectors.

Key Players

Key market players, including IBM Corporation, RIGETTI COMPUTING, INC., ID Quantique SA, D-Wave Systems Inc., Google LLC (Alphabet Inc.), Protiviti Inc. (ROBERT HALF INTERNATIONAL INC.), Deloitte Touche Tohmatsu Limited, Accenture PLC, and Atos Group, are actively contributing to the growth and innovation of the Quantum Computing in Healthcare market.

For more information about this report visit https://www.researchandmarkets.com/r/xrt3tc

About ResearchAndMarkets.comResearchAndMarkets.com is the world's leading source for international market research reports and market data. We provide you with the latest data on international and regional markets, key industries, the top companies, new products and the latest trends.

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Quantum Computing in Healthcare: A Billion-Dollar Revolution by ... - GlobeNewswire

During the AWS annual Re:Invent conference in 2019, the public cloud provider announced Braket, a service and hardware initiative for quantum computing.

The service was introduced in 2020 with support for three machines: a superconducting gate-based machine from Rigetti; a trapped-ion machine and a quantum annealing device from D-Wave. The latest update is claimed to offer a 10x improvement in the performance of hybrid workloads.

Discussing how the companys quantum computing strategy began, Richard Moulds, general manager at AWS Braket, says: We launched a hardware effort, which is actually co-located at the Caltech campus in California to provide a superconducting quantum computer. This, he adds, was accessed via Braket services.

The companys quantum computing strategy is focused on being hardware agnostic, offering its customer access to quantum computing technology through Braket. Since quantum computing technology is evolving, no one knows for certain which quantum technology will emerge as the winner.

Organisations wishing to use quantum computing need to understand the difference between the various architectural approaches, weigh up the pros and cons, and learn how to take advantage of each type of quantum computer when developing use cases.

By 2020, Moulds says AWS had three quantum computing devices available: Our goal was to make a wide variety of machines available to customers so they could see what was real, so they could see what claims made sense and could get a sense of the trajectory in terms of how quickly these machines are evolving. This, he says, helps customers pan and enables them to understand if quantum computing is going to be in their business.

Moulds points out that there is no one perfect architecture for a quantum computer. Businesses need to understand the different technical approaches each architecture offers, so customers want to experiment across different devices. Nobody wants to be locked into a single technology these days. Its just way too early, he adds.

The thing that customers can do right now is experiment with todays quantum hardware. Theres lots of different ways you can build a quantum computer. You know you can use ions, electrons or photons. But they all have really different trade-offs in terms of quality, the error rates, speed of operation, the number of qubits, the type of gates they can deliver and the connectivity between those gates. All vary enormously.

Among the areas of quantum computing AWS has tried to address is to make it easier for customers to access a quantum computing machine to see how they are operated. According to Moulds, the companies developing quantum computing may often only have a few machines that are operational: These things are in labs and oftentimes you only have private access and you need to know the scientists involved.

Its not like they have racks of servers. These are early stage devices. In some cases you might even describe them as prototype machines. So, they need some care and feeding and might require calibrating every day. The technology is not mature enough right now, unfortunately, to build quantum computers in an Amazon datacentre.

Nobody wants to be locked into a single technology these days. Its just way too early

Richard Moulds, AWS Braket

What this means is that the programs that customers want to run need to run on quantum machines that are not inside the AWS physical boundary. Mould says: We have to do a lot of work in terms of securing that connection and we work very closely with the quantum computing hardware providers to make sure that their security infrastructure is appropriate for running our customers data.

This also means that applications on AWS that want to make use of quantum computing resources through Braket require optimisation to reduce the network communications to the target quantum computing site.

Theres always a real important interplay between classical computers and quantum computers they work hand in hand. So, whatever you can do to make that connection efficient, will ultimately speed up the application, says Moulds.

Along with access to the hardware, Moulds says that another problem in quantum computing is that the industry is fragmented. Each machine basically has its own developer environment, its own developer toolkits. We want to get away from that and try to make it possible for customers to design quantum algorithms then run those algorithms on as many different types of [quantum computing] machine as possible.

According to Moulds, today a quantum computer cannot outperform a classical machine. He says: People have come up with some synthetic problems and synthetic examples, which generally is referred to as quantum supremacy, but these are not useful problems. No one is using these devices for running production workloads right now. No ones saving money.

He says many businesses want to find out if there are any useful problems that can be solved by quantum computing faster or cheaper than a classical machine.

There is, however, a lot of work being done in research, where scientists try to understand how they build a better machine and investigate how to identify better algorithms for quantum computing.

Moulds says people are looking how to use classical computing techniques combined with machine learning to make quantum algorithms run better, adding:Today, its all about experimentation.

Moulds says scientists are also looking at the potential to use quantum computing for molecular simulation. He believes this may be the first quantum computing use case that has the potential to succeed. It sort of makes sense, he says. When you think about it, youre using a quantum machine to basically simulate a quantum system.

A chemical reaction involves atoms and molecules interacting at the quantum level electrons and protons. The quantum computer effectively runs a digital twin of the experiment. The results from the real-world, wet lab experiment are then used to adjust parameters in the digital twin, until it produces the same results as the real chemical reaction.

But, as Moulds points out, digital twins that run on a classical computer are unable to model chemical reactions accurately: You cant model this stuff perfectly using a classical machine. Its just too complicated.

Petrochemicals, drugs and plastics are based on huge molecules, which simply cannot be modelled. With classical computing, he says that there are lots of compromises and lots of simplifications. A quantum computer offers scientists a potential way to run the digital twin without simplification and compromises.

From the conversation with Moulds, it seems that quantum computing devices are a long way off. Certainly, it will take some time before the technology has matured to a point where they can be deployed in the same way as datacentres infrastructure in public clouds. Nevertheless, this should not stop organisations from experimenting with the different types of quantum computing architecture to investigate potential use cases.

However, the fact that it is still early days for quantum computing means that applications that target quantum computers can be verified using classic computing architectures. In the future, as and when quantum supremacy is achieved, it will no longer be possible to run these simulations to verify the results.

Link:
Executive interview: Richard Moulds, AWS Braket - ComputerWeekly.com

September 6, 2023 10:20 AM | 4 min read

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Stakeholders in the biopharmaceutical industry are currently exploring the implementation of quantum computing in order to expedite the drug discovery process and cut down the overall R&D capital investment

LONDON , Sept. 6, 2023 /PRNewswire/ --Roots Analysishas announced the addition of "Quantum Computing Marketin Drug Discovery, 2023-2035" report to its list of offerings.

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Owing to the various benefits of quantum computing, such as big data processing and complex molecular modeling for minimizing cost and time investment, the adoption rate of quantum computing in pharmaceutical industry is expected to increase rapidly during the forecast period. Additionally, various partnerships have been inked for application of quantum computing in drug discovery. Majority of these partnerships are research and development agreements, followed by platform utilization agreements. Drug developers require support from both quantum computing software and hardware developers. In July 2021, Riverlane and Astex Pharmaceuticals announced their collaboration with Rigetti Computing to utilize their quantum systems along with Riverlane's algorithm expertise to develop molecular models of chemical compounds and study their interaction with proteins in the human body.

To order this 170+ slide report, which features 30+ figures and 75+ tables, please visit our Quantum Computing Market Report

Key Market Insights

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The financial opportunity within the quantum computing in drug discovery services market has been analysed across the following segments:

The research also includes detailed profiles of the key players (listed below) engaged in the quantum computing in drug discovery services market; each profile features an overview of the company, its financial information (if available), details related to its service portfolio, and recent developments and an informed future outlook.

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Key Questions Answered

Table of Contents

For additional details, please visit https://www.rootsanalysis.com/reports/quantum-computing-in-drug-discovery.html or email sales@rootsanalysis.com

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The quantum computing in drug discovery services market is anticipated to grow at 14% CAGR by 2035, accor - Benzinga