Archive for the ‘Quantum Computing’ Category

On the quest for qubits: Different types of quantum startups, explained – Sifted

With hundreds of European startups working on quantum and plenty of fresh cash being injected into the sector, the race to build a fully fledged large-scale quantum computer is on.

Unlike classical computers that operate on binary bits (0 or 1), quantum computers use qubits quantum bits which can exist simultaneously in multiple states, allowing for parallel computations. This can allow quantum computers to potentially calculate problems that even supercomputers cant handle.

A conventional computer is closer to an abacus than to a quantum computer, says Chris Ballance, cofounder of quantum computing startup Oxford Ionics.

To build a quantum computer, you can pick anything in principle that obeys quantum mechanics atoms, protons, electrons. This is why you see this zoo of different approaches to building the quantum computers, says John Morton, professor at UCL and CTO of London-based Quantum Motion.

Were currently in the noisy intermediate-scale quantum (NISQ) era which means we have some quantum computing tech, but its not yet advanced enough to solve a problem without errors or perform better than a classical computer. Once we go beyond this era, humanity could unlock applications from finance and drug discovery to finding new materials to stall climate change.

And there are lots of ways to get there. Here are some of the technologies European quantum computing startups are using, and how they work.

The most mature approach used by the likes of IBM and Google is superconducting qubits. At the basic level, asuperconducting qubit is a circuit loop made up of metals that become superconducting (ie. able to conduct current when cooled down) with an electric current travelling around it. They use electric currents flowing through them to store and process information. When Google claimed quantum supremacy in 2019, it used a 53-qubit superconducting device, and in 2022, IBM unveiled Osprey, a 433-qubit superconducting processor.

In the UK, Oxford Quantum Circuits (OQC) has built an eight-qubit superconducting quantum computer named Lucy. Brian Vlastakis, its quantum R&D lead, says because all of its quantum information is encoded into electrical signals, it can use a lot of the same circuits that are used for other electronics.

The startup has been providing quantum-as-a-service since 2019. Lucy, for example, is available on the cloud (Amazon Braket) for customers to try out and learn more about how quantum computers could be useful for the problems that theyre trying to solve.

Vlastakis says one of the reasons hes excited about OQCs technology is that our architecture is incredibly flexible. We can essentially design many different quantum processor variations to function in a way that will work better for customers.

Another method is using trapped ion technology, which consists of trapping single atoms in place using an electromagnetic field. Unlike superconducting qubits, trapped ion qubits are identical to each other.

Ilyas Khan, cofounder and chief product officer of UK-headquartered Quantinuum, says trapped ion devices offer two advantages stability and circuit depth which provide relatively low error rates. However, its not clear how scalable the tech will be and the method is slower than superconducting.

At the moment theres no point to being fast if you cant do anything, says Khan.

While Quantinuum (and others such as IonQ and Alpine Quantum Technologies) rely on complex laser systems to control the trapped ions, Oxford Ionics uses a technology that can be integrated into a standard silicon chip.

Ballance says Oxford Ionics focus is on optimising a lower number of qubits with very low error rates, rather than scaling the number of qubits massively.

Most quantum computers on the market have far more qubits than they can use in useful computation because of the error rate, he says. So for example, IBM have their 433-qubit devices theyve launched, but when you benchmark them they perform less good than a perfect nine-qubit system, he says. Our focus is getting to those few 100 qubit devices as fast as possible.

While superconducting and trapped ion qubits were originally physics experiments in labs, Morton says Quantum Motion has a different approach: silicon-based qubits.

Were ultimately saying that for quantum computers to be useful youre going to need a lot of qubits. What does a lot mean? Well, hundreds of thousands or millions of qubits, he says. There arent many technologies that make millions of anything one example of something that has is the silicon transistor.

If you dont try to correct for errors, then its true maybe you can do something useful with just a hundred or a few hundred qubits, but the problem is you still are going to want to be able to run lots of problems, and run them many times, and so you still, in the end, want lots of qubits.

The startup hopes the silicon approach will be more scalable and cost-efficient, as it can build quantum processors with far less specialist technology, such as lasers or a high vacuum. Quantum Motions approach offers qubit densities that are highly miniaturised and its silicon-based quantum chips are typically a few millimetres across. Morton expects the cooling system required to operate the chip to be similar to a standard 19-inch server rack.

Another approach is photonic qubits,made from particles of light. PsiQuantum, a US company founded in the UK, says photons are the only way to reach a million qubits and a million qubits is the only way for a quantum computer to be useful.

There are many advantages when you decide to use photons, because first of all photons are a quantum particle that have no mass and no charge, so that means that photons are less exposed to disturbance than other kinds of techniques, says Marine Xech-Gaspa, chief of staff to the CEO of Quandela, a French startup also betting on photonics. So to be more concrete they can be manipulated at room temperature, because you dont have to be in a specific environment, also it consumes less energy.

Nordic Quantum Computing Group also has the aim of developing a quantum computing platform based on photonic integrated circuits.

Its focus is two-fold, according to Axel Mustad, its founder and CEO. On the hardware side, it will use quantum dot-based single photon sources, and on the software side it will develop algorithms which can be implemented on photonic hardware in particular algorithms to solve hard problems in capital markets and financial services, and in energy management and trading.

Other startups outside of those building hardware are also an important part of the race.

Steve Brierley is founder and CEO of Cambridge-based Riverlane, which is building an error correction layer (using different qubits types) that different hardware companies can use.

We call it an operating system, because operating systems manage complexity for the user, he says. This is like an additional fabric that sits on top of the qubits, really removes errors during the computation and it means it can do much longer and ultimately trillions of operations before failure.

Bristol-based Phasecraft is working on algorithms to provide to hardware companies.

If you want to do something useful you need to have a quantum algorithm to run on that quantum computer, because quantum computers are not just faster computers, you need to think in totally different ways to get the most out of them to do something useful, says Ashley Montanaro, cofounder of Phasecraft.

Were particularly thinking about near-term quantum computers, so the kind of machines that we have now, or that we might have in the next two to five years

Ultimately at this early stage, it would be impossible to claim one technology is better than another.

That would be foolhardy and in fact misleading we are years away from being able to evidence superiority in any given platform, says Khan. If you look at this moment in time and youre able to magically transport yourself to 2030, it would be a bit like measuring a marathon in its first or second mile.

But what he can say with confidence is that the early signs are that different architectures might lend themselves better to certain tasks in the future.

My expectation is that in 10 years, a lot of the dust will have settled, itll become very clear and the market structure will have changed from lots of noise and lots of different approaches sprouting up to consolidation and stabilisation of one or two hardware platforms that cut the mustard and a few other hardware platforms that are specialised, says Ballance.

And while funding and access to talent stay on quantum founders minds, the biggest battle is the sheer scale of the challenge facing quantum computing startups.

Its equivalent to landing on the moon, says Brierley. Its that kind of scale and ambition and so thats going to require bringing together lots of different skills and expertise and ideas. I dont think any one company is going to solve this problem.

Steph Bailey is Sifteds head of content and coproduces Sifteds flagship podcast. She tweets from @steph_hbailey

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On the quest for qubits: Different types of quantum startups, explained - Sifted

Post-Quantum Satellite Protection Rockets Towards Reality – Dark Reading

Developers of post-quantum cryptography have successfully created a trial, data-transmission channel from Earth to satellites in multiple orbits that would be resistant to the hacking of the future.

The idea is to protect data routed via satellite clusters from being harvested and decrypted by quantum computers and to protect the operational technology communications that keep the arrays functioning. The challenge lies in maintaining resource-intensive, post-quantum protection along multiple hops as a signal is beamed around a cluster, with a data transmission rate that's acceptable for military and commercial real-time communications (and other applications).

During the test, carried out by QuSecure and Accenture, a data-transmission channel protected by both classical RSA-2048 and post-quantum encryption was opened to a low-Earth orbit (LEO) satellite and switched to a higher-altitude geosynchronous orbit (GEO) satellite, and then beamed back down to Earth.

"As more organizations are increasingly relying on space technology to provide solutions, resiliency, and more relevant information, security of those systems and the data is paramount," said Paul Thomas, space innovation lead for Technology Innovation at Accenture, in a statement.

Once efficient quantum computing becomes a reality, the expectation is that clusters of them will have enough gas in the tank to break RSA-2048 encryption, something that even the most powerful of today's computers are incapable of achieving.

And presumably, when that happens, there will be legions of cybercriminal types pouring out of the woodwork to decrypt the many classified secrets that organizations, governments, and critical infrastructure (including satellite arrays) use to ward off mass operational disruption.

Granted, the timing on that breakthrough remains a moving target, but the satellite test is a step towards prepping for that doomsday scenario. Also, by employing post-quantum encryption now, it can protect against any "steal now, decrypt later" plans on the part of cyberattackers who might be stockpiling encrypted data in anticipation of a literal quantum leap.

"Outer space is getting more crowded and contested every day and providing reliable space-based security is critical in today's global economy," said Tom Patterson, quantum and space security lead at Accenture.

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Post-Quantum Satellite Protection Rockets Towards Reality - Dark Reading

We Asked GPT Some Tech Questions, Can You Tell Which Answers … – TechSpot

ChatGPT and its wordsmith capabilities are all over the news, and for good reason. The large language model (LLM) at the heart of the chatbot can create impressive results, with some even claiming the era of human writers is nearing its end.

While the reality is most likely less catastrophic for us human writers, we must admit that the question of whether AI will end up taking our jobs did pass through our minds once or thrice. So, let's check out whether our readers can spot the difference between a human writer and an AI.

Instead of writing an entire essay and then letting ChatGPT come up with its own version of the same topic, we've decided to compare humans and ChatGPT based on short-form answers to various tech-related questions. We took some answers from TechSpot explainer articles and wrote some additional ones that are less "conceptual" to see what GPT 4.0 came up with.

Each question below features two answers: one made by a human and the other provided by ChatGPT. They're listed randomly on the left and on the right, and it's up to you to spot the difference. Can you tell which is which? You can click the poll below each answer and see how you do.

Before we start, a couple of additional disclaimers: first, this piece is not meant to be a formal experiment, just a fun take on the human vs. AI discussion. Second, if you've used ChatGPT before, then you know the bot is known to spew paragraphs and paragraphs of text, even when you ask basic questions. This is why we had to include an 80-word limit in our prompts; otherwise, the answers generated by ChatGPT would be considerably longer, unnecessarily ballooning this piece.

Let's get started.

Manufacturing processes: Which is the human answer?

The human answer is on the left. GPT's answer isn't completely accurate.

Throttling: Which is the human answer?

The human answer is on the left.

OLED and LCD: Which is the human answer?

The human answer is on the right.

PCIe lanes: Which is the human answer?

The human answer is on the right. GPT's answer is only partially correct.

Chip binning: Which is the human answer?

The human answer is on the right.

SATA SSD fit: Which is the human answer?

The human answer is on the right. GPT's answer is unaware of SATA-to-M.2 adapters even though they are a niche solution.

M.2 SSD to SATA: Which is the human answer?

The human answer is on the left.

Cryptography: Which is the human answer?

The human answer is on the right.

Quantum computing: Which is the human answer?

The human answer is on the left.

Path tracing: Which is the human answer?

The human answer is on the left. Also, GPT got it wrong this time.

SSD trimming: Which is the human answer?

The human answer is on the right.

So, how did you do? How many answers did you get right (out of 11)?

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We Asked GPT Some Tech Questions, Can You Tell Which Answers ... - TechSpot

A robust quantum memory that stores information in a trapped-ion quantum network – Phys.org

This article has been reviewed according to ScienceX's editorial process and policies. Editors have highlighted the following attributes while ensuring the content's credibility:

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by Ingrid Fadelli , Phys.org

Researchers at University of Oxford have recently created a quantum memory within a trapped-ion quantum network node. Their unique memory design, introduced in a paper in Physical Review Letters, has been found to be extremely robust, meaning that it could store information for long periods of time despite ongoing network activity.

"We are building a network of quantum computers, which use trapped ions to store and process quantum information," Peter Drmota, one of the researchers who carried out the study, told Phys.org. "To connect quantum processing devices, we use single photons emitted from a single atomic ion and utilize quantum entanglement between this ion and the photons."

Trapped ions, charged atomic particles that are confined in space using electromagnetic fields, are a commonly used platform for realizing quantum computations. Photons (i.e., the particles of light), on the other hand, are generally used to transmit quantum information between distant nodes. Drmota and his colleagues have been exploring the possibility of combining trapped ions with photons, to create more powerful quantum technologies.

"Until now, we have implemented a reliable way of interfacing strontium ions and photons, and used this to generate high-quality remote entanglement between two distant network nodes," Drmota said. "On the other hand, high-fidelity quantum logic and long-lasting memories have been developed for calcium ions. In this experiment, we combine these capabilities for the first time, and show that it is possible to create high-quality entanglement between a strontium ion and a photon and thereafter store this entanglement in a nearby calcium ion."

Integrating a quantum memory into a network node is a challenging task, as the criteria that need to be fulfilled for such a system to work are higher than those required for the creation of a standalone quantum processor. Most notably, the developed memory would need to be robust against concurrent network activity.

"This means that the quantum information stored in the memory must not degrade while a network link is established," Drmota explained. "This requires extreme isolation between the memory and the network, but at the same time, there also needs to be a fast and reliable mechanism that couples the memory to the network when needed." View inside the vacuum chamber, where we trap strontium and calcium ions using electric fields and lasers. Credits: David Nadlinger.

To create their quantum memory, Drmota and his colleagues used two different atomic species, namely strontium and calcium, as this allowed them to minimize crosstalk while establishing a network link. The limited crosstalk in this mixed-species architecture also allowed them to detect errors in real-time and to utilize what is known as in-sequence cooling. Mixed-species entangling gates provided the missing connection between the network and the memory.

"One of the technical error sources that we face with trapped-ion qubits is dephasing due to magnetic field noise," Drmota said. "Nevertheless, calcium-43 features transitions that are insensitive to magnetic fields, eliminating this error, hence boosting their coherence time. While strontium-88 is perfectly suited for generating photons for networking, it is sensitive to magnetic field noise."

Although strontium-88 is known to be sensitive to magnetic field noise, the researchers were able to preserve entanglement between their memory ion and a photon for a longer time, by transferring quantum information from the strontium to calcium in the system. Specifically, they could preserve this entanglement for over 10s, which is at least 1000 times longer than they observed between a bare strontium ion and a photon.

"Furthermore, the strontium ion can be reused to generate further entangled photons, and we show that this process does not affect the fidelity of entanglement between the memory and the previous photon, hence achieving robustness to network activity," Drmota said. "Notably, we managed to integrate the complexity associated with multiple challenging techniques, which have been developed in isolation in different setups over many years, in a single experiment."

In initial tests, the quantum memory created by Drmota and his colleagues achieved very promising results, as it was found to be highly robust, preserving entanglement between a trapped ion and photon for at least 10s. The team's demonstration of this quantum memory could be an important milestone on the ongoing quest to realize distributed quantum information processing.

Using their design, individual quantum computational nodes can be loaded with a given number of processing qubits (i.e., calcium), while the network qubit (i.e., strontium) can then be used to create quantum links between distant modules. Ultimately, this promising quantum memory could pave the way towards the creation of scalable quantum computing systems, as using small modules that can process quantum information and interconnecting them with other modules circumvents the need for large and complex ion traps.

"The robust quantum memory could be used in quantum repeaters, for private (blind) quantum computation, and is key for new developments in quantum communications, metrology and time keeping," Drmota added. "For example, for the nascent field of entangled atomic clocks, the long entanglement storage durations achieved in our experiments will lead to an order-of-magnitude improvement in the precision of frequency comparison between distant clocks."

More information: P. Drmota et al, Robust Quantum Memory in a Trapped-Ion Quantum Network Node, Physical Review Letters (2023). DOI: 10.1103/PhysRevLett.130.090803.

Journal information: Physical Review Letters

2023 Science X Network

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A robust quantum memory that stores information in a trapped-ion quantum network - Phys.org

House Bill Aims to Apply Quantum Tech to Agriculture – MeriTalk

Reps. Randy Feenstra, R-Iowa, and Haley Stevens, D-Mich., have introduced new legislation that aims to apply the power of quantum computing to assist the agriculture industry and streamline fertilizer production.

The Quantum in Practice Act would introduce quantum molecular simulations and modeling to allow experts to study fertilizer chemical elements and reactions with accuracy.

From fertilizer production to materials manufacturing, quantum computing has the untapped potential to lower input costs for our farmers, improve energy storage, and produce more effective medications for patients, Rep. Feenstra said in a press release.

Im proud to introduce the Quantum in Practice Act to ensure that our main streets, farmers, and small businesses can realize the real benefits of quantum computing, not just in theory, but in practice, he added. Thanks to scientific ingenuity, there is boundless opportunity for our rural communities to harness the power of quantum computing to strengthen our agricultural sector, streamline fertilizer production, and enhance our way of life in the 4th District.

Rep. Feenstra originally introduced a version of this bill in 2022. According to the press release, quantum computing can model the nitrogen fixation process utilized by bacteria, which could be used to develop cheaper, next-generation synthetic fertilizers.

In addition to assisting the agriculture industry with streamlining fertilizer production, the members of Congress said potential scientific discoveries could also help produce safer medicines, energy storage, new metals, protective gear, and superconductors.

Original cosponsors of the legislation include: House Science, Space, and Technology Chairman Frank Lucas, R-Okla., and Ranking Member Zoe Lofgren, D-Calif., and Reps. Young Kim, R-Calif., Jake Ellzey, R-Texas, Rick Crawford, R-Ark., Byron Donalds, R-Fla., Nancy Mace, R-S.C., Brian Fitzpatrick, R-Pa., Rudy Yakym, R-Ind., Brandon Williams, R-N.Y., Tom Kean, R-N.J., Joseph Neguse, D-Colo., and Jeff Jackson, D-N.C.

Sens. Todd Young, R-Ind., and Raphael Warnock, D-Ga., have introduced companion legislation in the Senate.

Quantum simulations are able to model interactions at the sub-molecular level and create a cost-effective alternative to the expensive development of new fertilizers, medications, protective equipment, and more, said Sen. Young.

As we secure our competitive advantage in the 21st?century, we must support the cutting-edge research that will revolutionize Indianas agriculture and pharmaceutical industries, he added. The Quantum in Practice Act would help ensure that American researchers and industries can pursue practical applications to advance quantum technologies.

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House Bill Aims to Apply Quantum Tech to Agriculture - MeriTalk