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Where we are currently, and where we are headed

Quantum computing is a technology that exploits the laws of quantum mechanics to solve problems too complex for classical computers. The first significant contribution to the development of quantum computing occurred in 1982, when Richard Feynman postulated that to simulate the evolution of quantum systems in an efficient way, we would need to build quantum computers (computational machines that use quantum effects). Nevertheless, it was not until 1994 that the view on quantum computing changed. Peter Shor developed a polynomial time quantum algorithm allowing quantum computers to efficiently factorize large integers exponentially quicker than the best classical algorithm on traditional machines, turning a problem which is computationally intractable into one that can be solved in just a few hours by a large enough quantum computer. So, once practical quantum computers are a reality, it will be possible to crack cryptographic algorithms based on integer factorization, such as RSA, which are fundamental for the operation of internet protocols.

But what do we mean by a large enough quantum computer? How far are we from building it?

Large technology companies have been working for years with the objective of building a large-scale quantum device. As published by the Quantum Insider, the leading players in this field are Google, IBM, Microsoft and AWS (Amazon), although IBM has the longest computing history.

Apart from them, there are other promising companies which are also invested in fabricating quantum hardware and developing software. Some examples are D-Wave, Rigetti Computing, IonQ, PsiQuantum, Quantiuum or Oxford Ionics. It is worth noting that not all of them are working on the same type of quantum computers. Differences among these computers depend on the nature of qubits and how they can be controlled and manipulated. The main types of quantum computers are superconducting, photonic, neutral atoms-based, trapped ions, quantum dots and gate-based quantum computers, the first being the most mature and popular type.

In 2016, IBM put the first quantum computer on the cloud for anyone to run experiments (the IBM Quantum Experience). One year later, they introduced Qiskit, the open-source python-based toolkit for programming these quantum computers (the version 1.0 will be released this year). Then, in subsequent years, the company developed Falcon, a 27-qubit quantum computer (2018) and the 65-qubit Hummingbird (2020). Also, in 2020, IBM released their development roadmap, which had a major update in 2022 and provides a detailed plan to build an error-corrected quantum computer before the end of the decade. According to this roadmap, IBM was planning to build in 2021 the first quantum processor with more than 100 qubits, the 127 qubit Eagle; in 2022, the 433-qubit Osprey; and finally, in 2023, the 1121-qubit Condor processor. All objectives were successfully achieved. Nevertheless, as Jay Gambetta, VP of IBM Quantum, mentioned in his article, we must figure out how to scale up quantum processors since a quantum computer capable of reaching its full potential could require hundreds of thousands, maybe millions of high-quality qubits. For this reason, in the following years and with the ambition of solving the scaling problem, the company is proposing three different approaches for developing ways to link processors together into a modular system capable of scaling without physics limitations.

Scalability refers to the ability to increase the number of qubits in a quantum system, allowing to solve more complex problems.

Another tech giant working on quantum computing is Google, which has the Quantum AI Campus. This company announced in 2018 a 72-qubit quantum processor called Bristlecone and in 2019 presented a 53-qubit quantum computer, Sycamore, and claimed quantum supremacy for the first time, which generated a lot of debate in the community. Lastly, the Quantum AI researchers announced significant advances in quantum error correction by achieving for the first time the experimental milestone of scaling a logical qubit. Quantum error correction is essential for scaling up quantum computers and achieving error rates low enough for useful calculations.

Quantum supremacy describes the ability of a quantum computer for solving a problem that the most powerful conventional computer cannot process in a practical amount of time.

Microsoft decided to focus on quantum computing in the late 1990s and currently is offering Azure Quantum, a cloud quantum computing service which provides an environment to develop quantum algorithms which can be run in simulators of quantum computers. Due to the companys approach of working with partners and academic institutions, Azure Quantum allows us to choose from different quantum hardware solutions created by industry leaders such as Quantinuum, Ionq, Quantum Circuits, Inc., Rigetti or Pasqal.

Microsoft is taking a different approach on the design of quantum computers they are relying on a new type of qubit, a topological qubit. As they explicitly say, Our approach to building a scaled quantum machine is the more challenging path in the near term, but its the most promising one long term. In this regard, in 2022, Microsoft reported an important achievement on the development topological qubit hardware, and later that year they share more data from their experiments.

Although Amazon has not announced that it is developing quantum hardware and/or software, they launched in 2019 Amazon Braket, a quantum computing service which makes it possible to build quantum algorithms, test them in a simulator, run them on different quantum computers and analyze the results. Customers can access hardware from leaders such as Rigetti, Ion-Q and D-Wave Systems, which means that they can experiment with systems based on three different qubit technologies.

In addition, Amazon also launched the Amazon Quantum Solutions Lab which helps companies to be ready for quantum computing by offering them the possibility to work with leading experts in quantum computing, machine learning, optimization, and high-performance computing.

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The State of the Art in Quantum Computing - Medium

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Computing is on the cusp of a revolution, not with faster clock speeds, but with a whole new way of thinking: quantum computing. Buckle up, because its not just about processing information its about unlocking secrets once deemed impossible. Think teleporting data (okay, not literally!), designing unbreakable codes, and creating revolutionary materials all in the realm of quantum possibilities

But what exactly is this mind-bending tech? Imagine a computer that doesnt rely on 0s and 1s, but on qubits, which can be 0, 1, or both at the same time (thanks, quantum weirdness!). This superposition allows them to explore multiple possibilities simultaneously, making them exponentially faster for certain problems. Think solving global climate challenges or uncovering new medicines problems that would take classical computers centuries

So, whats the hype? Here are some mind-blowing advancements:

But hold on, its not all sunshine and rainbows:

So, when can we expect quantum computers in our homes? Dont ditch your laptop just yet. While significant progress is happening, widespread adoption is still years away. Think of it like the early days of the internet exciting potential, but limited accessibility

But the future is bright! Research is booming, and companies like Google, IBM, and Microsoft are pouring resources into this revolutionary technology. Think of it like a race to the moon full of challenges, but with the potential to change the world.

So, buckle up, tech enthusiasts! The quantum age is dawning, and it promises to be a wild ride. Get ready to witness computing like youve never seen before!

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Quantum Leap: Unveiling the Mysteries of Quantum Computing - Medium

The scientific renaissance of the 20th century saw the rise of quantum mechanics and information theory. In 1982, physicist Richard Feynman famously stated that it was not feasible to model a quantum phenomenon using classical computation; an alternative was required to accurately simulate such phenomena. Whilst Feynmans statement didnt garner much attention at the time, 12 years later, mathematician Peter Shor developed an algorithm that was too sophisticated for classical computers facilitating the idea and possibility of quantum computing.

Quantum and classical computing both manipulate data to solve problems, but three fundamental principles distinguish quantum computing. While classical computers encode information in binary form of 0s and 1s, quantum computers are capable of surveying all the probable states of a quantum bit (qubit) simultaneously. This property of a quantum object is known as superposition. Two quantum entities are said to be entangled when neither can be described without referencing the other, as they lose their individual identities. The phenomena of interference, which occurs when two or more quantum states combine to produce an entirely new state, can be used to enhance the process of error-correction and the probability of measuring the correct output.

The way that quantum computers leverage probabilities and entanglement allows information to be encoded with increased precision across a large number of states simultaneously. Quantum computers show huge promise in terms of industrial and commercial applications in fields of chemical and biological engineering, drug discovery, cybersecurity, artificial intelligence, machine learning, complex manufacturing, and financial services. From being used to simulate complex chemical reactions to being used in aeronautical navigation, it is clear that quantum computers have huge unexploited potential that still needs to be explored.

Despite their huge potential, scientists building quantum computers tend to run into two major hurdles. First, qubits need to be protected in near-zero temperatures from the surrounding environment. The longer the qubit lasts the longer its coherence time, therefore isolation is essential. Secondly, qubits need to be in an entangled state and should be controllable on demand for algorithm execution. Thus, finding the right balance between the states of isolation and interaction is difficult.

With the ability to revolutionise computation, there are multiple players involved in the corporate league of attaining quantum advantage. Leading this race of developing the most refined form of quantum computer are IBM, Google Quantum AI, and Microsoft.

Quantum computers show huge promise in terms of industrial and commercial fields.

In October 2019, Google confirmed that it had attained quantum supremacy, using their fully programmable 54-qubit processor Sycamore to solve a sampling problem in 200 seconds. This was surpassed earlier last year using an updated version of Sycamore with 70 qubits.

In December, IBM unveiled Condor, a new chip with 1,121 superconducting qubits, surpassing the 433-qubit capacity of their Osprey processor released in November 2022. Turning their focus towards the development of modular quantum processors with low error rate, the company also announced the Heron processor with 133 qubits and a record low error rate.

Despite the excitement surrounding the possible applications of quantum computers, its not time to celebrate just yet. Shors algorithm remains unsolved, and we are still a considerable distance away from having a system sophisticated enough for commercial use. However the rapid innovation and research within this field, along with the long-term advantage and potential of quantum computing, hints at a new and prosperous computing age.

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Quantum Computing: The Future of Tech? The Badger - The Badger

China has been heavily investing in quantum computing technology and is now closely matched with the US in terms of its capabilities, according to a new report.

GlobalDatas new Quantum Computing 2024 states: China has made enormous strides in catching up with the US, with the countries now standing neck and neck despite pursuing differing strategies.

In the US, private companies are leading development, while in China it is being driven by state institutions.

Despite progress in both countries a so-called quantum winter is being predicted, with the industry facing daunting engineering and macroeconomic hurdles.

Quantum computers are machines that use the quantum states of subatomic particles to store information. Using the counterintuitive behaviour of sub-atomic particles, the machines have vastly greater computational capabilities than todays computers.

They can simulate complicated systems such as financial markets, chemical reactions, molecules and neurons in the brain. A core difference between classic computers and computational computers is in the computational unit.

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While classical computers compute with transistors representing either 0 or 1, quantum computers compute with qubits, which can be both 0 and 1 simultaneously. This means that, where a classical binary computer would solve the possible escape routes of a complex maze one by one, a quantum computer could test all possible escape routes simultaneously.

Quantum computers have applications not just in financial markets or escaping mazes but also in the military and cybersecurity space which explains why they are so sought after in the geopolitical landscape.

The US and China are both developing quantum computing technology. The US has over $4bn quantum computing projects planned, while China has committed at least $15bn over the next five years.

Within China there has been a concerted shift away from private sector development of the technology, with both Baidu and Alibaba withdrawing from the market and donating equipment to the Beijing Academy of Quantum Information Sciences and Zhejiang University, respectively.

Chinas recent quantum achievements have been recognised in the report as a key macroeconomic trend. This is due to China being the first nation to achieve quantum supremacy on more than one type of quantum device and to do so on a programmable device.

Aside from the US and China, the UK, EU, Canada, India, Russia, Japan and Australia all have either government-funded programmes and institutes or private-sector ecosystems specialising in creating and applying quantum technologies.

Quantum computing remains nascent both in its industry and technology, and it is too early to make accurate predictions about market size or know when engineering issues will be solved.

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US and China neck and neck in quantum computing - Verdict

Quantum computing firm D-Wave has announced the general availability of its 1,200 qubit Advantage2 (Adv2) prototype.

First unveiled in 2022, the new Adv2 prototype features more than 1,200 qubits and 10,000 couplers and apparently demonstrates a 20x faster time-to-solution on hard optimization problems.

Compared to D-Waves previously released Advantage2 prototype, the machine has increased qubit connectivity from 15 to 20-way; scaled energy usage by more than 40 percent; and doubled qubit coherence time.

The Adv2 prototype is now available to customers who have the companys Leap quantum cloud service subscription. New customers can sign up to the Leap service and receive up to one minute of free use of D-Waves quantum processing units (QPUs) and quantum hybrid solvers.

Today marks an important milestone in our product delivery roadmap, as we open up access to the newest Advantage2 prototype for businesses, developers, and researchers across the globe, said Mark W. Johnson, senior vice president of quantum technologies and systems products at D-Wave. What were seeing with the Advantage2 prototype in terms of performance gains is remarkable, and were thrilled to make it available today to help customers start applying it to their complex problems now.

D-Wave was the first commercial supplier of quantum computers and offers machines that utilize quantum annealing.

The company went public in August 2022 after a SPAC merger with DPCM Capital. However, in October 2023 the company faced a second potential delisting from the New York Stock Exchange (NYSE) over its low stock price. The company was given six months to bring its share price back above a $1 average closing share price over a 30-day period.

D-Waves stock price hit $1 on February 9, 2024, and sits at $1.35 at the time of publishing.

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D-Wave announces general availability of its Advantage2 prototype - DatacenterDynamics