5 November 2021

Rigetti Computing, a pioneer in full-stack quantum computing, and Oxford Instruments are gold sponsors of the upcoming City Quantum Summit London 2021 which is taking place on Wednesday 10th November at Mansion House. The Summit will bring together founders and CEOs of quantum computing companies with the aim of clearly demonstrating the need for quantum computing in all sectors and industries, from sustainable development to medical revelations. The event is being hosted by William Russell, Lord Mayor Of The City Of London, in collaboration with Robinson Hambro.

"The City Quantum Summit is a great example of the level of collaboration required to secure ongoing quantum commercialisation here in the UK and we're pleased to be actively participating in the discussions and working closely with other leading players like Rigetti to accelerate real applications in quantum computing today," says Stuart Woods, Managing Director at Oxford Instruments NanoScience. Rigetti and Oxford Instruments are partners in a public-private consortium to deliver the first commercial quantum computer in the U.K.

Woods and Marco Paini, Technology Partnerships Director for Europe at Rigetti, will both be participating in the event as part of a panel discussion focused on financial modelling. The discussion will cover quantum computing applications for the financial sector and a project with Standard Chartered to analyse use cases including, for example, synthetic financial data generation and classification for implied volatility.

"Some of the most promising use cases for quantum computing are based in the financial sector. The ability to develop practical applications, like financial modelling, on real hardware puts us in a strong position to accelerate the commercialisation of quantum computing in the UK. Our Innovate UK consortium brings together industry experts and full-stack quantum expertise to make practical quantum computing a reality."

The Summit will be conducted as a hybrid event with the opportunity to join virtually as well as in person. You can find out more about how to register for the event here

Disclaimer

Oxford Instruments plc published this content on 09 November 2021 and is solely responsible for the information contained therein. Distributed by Public, unedited and unaltered, on 09 November 2021 09:32:06 UTC.

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Rigetti and Oxford Instruments Participate and Sponsor The City - Marketscreener.com

On October 1 of this year, IonQ became the first pure-play quantum computing start-up to go public. At this writing, the stock (NYSE: IONQ) was around $15 and its market capitalization was roughly $2.89 billion. Co-founder and chief scientist Chris Monroe says it was fun to have a few of the companys roughly 100 employees travel to New York to ring the opening bell of the New York Stock Exchange. It will also be interesting to listen to IonQs first scheduled financial results call (Q3) on November 15.

IonQ is in the big leagues now. Wall Street can be brutal as well as rewarding, although these are certainly early days for IonQ as a public company. Founded in 2015 by Monroe and Duke researcher Jungsang Kim who is the company CTO IonQ now finds itself under a new magnifying glass.

How soon quantum computing will become a practical tool is a matter of debate, although theres growing consensus that it will, in fact, become such a tool. There are several competing flavors (qubit modality) of quantum computing being pursued. IonQ has bet that trapped ion technology will be the big winner. So confident is Monroe that he suggests other players with big bets on other approaches think superconducting, for example are waking up to ion traps advantages and are likely to jump into ion trap technology as direct competitors.

In a wide-ranging discussion with HPCwire, Monroe talked about ion technology and IonQs (roughly) three-step plan to scale up quickly; roadblocks facing other approaches (superconducting and photonic); how an IonQ system with about 1,200 physical qubits and home-grown error-correction will be able to tackle some applications; and why IonQ is becoming a software company and thats a good thing.

In ion trap quantum computing, ions are held in position by magnetic forces where they can be manipulated by laser beams. IonQ uses ytterbium (Yb) atoms. Once the atoms are turned into ions by stripping off one valence electron, IonQ use a specialized chip called alinear ion trap to hold the ions precisely in 3D space. Literally, they sort of float above the surface. This small trap features around 100 tiny electrodes precisely designed, lithographed, and controlled to produce electromagnetic forces that hold our ions in place, isolated from the environment to minimize environmental noise and decoherence, as described by IonQ.

It turns out ions have naturally longer coherence times and therefore require somewhat less error correction and are suitable for longer operations. This is the starting point for IonQs advantage. Another plus is that system requirements themselves are less complicated and less intrusive (noise producing) than systems for semiconductor-based, superconducting qubits think of the need to cram control cables into a dilution refrigerator to control superconducting qubits. That said, all of the quantum computing paradigms are plenty complicated.

For the moment, ion traps using lasers to interact with the qubits is one of the most straightforward approaches. It has its own scaling challenge but Monroe contends modular scaling will solve that problem and leverage ion traps other strengths.

Repeatability [in manufacturing superconducting qubits] is wonderful but we dont need atomic scale deposition, like you hear of with five nanometer feature sizes on the latest silicon chips, said Monroe. The atoms themselves are far away from the chips, theyre 100 microns, i.e. a 10th of a millimeter away, which is miles atomically speaking, so they dont really see all the little imperfections in the chip. I dont want to say it doesnt matter. We put a lot of care into the design and the fab of these chips. The glass trap has certain features; [for example] its actually a wonderful material for holding off high voltage compared to silicon.

IonQ started with silicon-based traps and is now moving to evaporated glass traps.

What is interesting is that weve built the trap to have several zones. This is one of our strategies for scale. Right now, at IonQ, we have exactly one chain of atoms, these are the qubits, and we typically have a template of about 32 qubits. Thats as many as we control. You might ask, how come youre not doing 3200 qubits? The reason is, if you have that many qubits, you better be able to perform lots and lots of operations and you need very high quality operations to get there. Right now, the quality of our operation is approaching 99.9%. That is a part per 1000 error, said Monroe.

This is sort of back of the envelope calculations but that would mean that you can do about 1000 ops. Theres an intuition here [that] if you have n qubits, you really want to do about n2 ops. The reason is, you want these pairwise operations, and you want to entangle all possible pairs. So if you have 30 qubits, you should be able to get to about 1000 ops. Thats sort of where we are now. The reason we dont have 3200 yet is that if you have 3200 qubits, you should be able to do 10 million ops and that means your noise should be one part in 107. Were not there yet. We have strategy to get there, said Monroe.

While you could put more ions in a trap, controlling them becomes more difficult. Long chains of ions become soft and squishy. A smaller chain is really stiff [and] much less noisy. So 32 is a good number. 16 might be a good number. 64 is a good number, but its going to be somewhere probably under 100 ions, said Monroe.

The first part of the strategy for scaling is to have multiple chains on a chip that are separated by a millimeter or so which prevents crosstalk and permits local operations. Its sort of like a multi-core classical architecture, like the multi-core Pentium or something like that. This may sound exotic, but we actually physically move the atoms, we bring them together, the multiple chains to connect them. Theres no real wires. This is sort of the first [step] in rolling out a modular scale-up, said Monroe.

In proof of concept work, IonQ announced the ability to arbitrarily move four chains of 16 atoms around in a trap, bringing them together and separating them without losing any of the atoms. It wasnt a surprise we were able to do that, said Monroe. But it does take some design in laying out the electrodes. Its exactly like surfing, you know, the atoms are actually surfing on an electric field wave, and you have to design and implement that wave. That was that was the main result there. In 2022, were going to use that architecture in one of our new systems to actually do quantum computations.

There are two more critical steps in IonQs plan for scaling. Error correction is one. Clustering the chips together into larger systems is the other. Monroe tackled the latter first.

Think about modern datacenters, where you have a bunch of computers that are hooked together by optical fibers. Thats truly modular, because we can kind of plug and play with optical fibers, said Monroe. He envisions something similar for trapped ion quantum computers. Frankly, everyone in the quantum computing community is looking at clustering approaches and how to use them effectively to scale smaller systems into larger ones.

This interface between individual atom qubits and photonic qubits has been done. In fact, my lab at University of Maryland did this for the first time in 2007. That was 14 years ago. We know how to do this, how to move memory quantum bits of an atom onto a propagating photon and actually, you do it twice. If you have a chip over here and a chip over here, you bring two fibers together, and they interfere and you detect the photons. That basically makes these two photons entangled. We know how to do that.

Once we get to that level, then were sort of in manufacturing mode, said Monroe. We can stamp out chips. We imagine having a rack-mounted chips, probably multicore. Maybe well have several 100 atoms on that chip, and a few of the atoms on the chip will be connected to optical conduits, and that allows us to connect to the next rack-mounted system, he said.

They key enabler, said Monroe, is a nonblocking optical switch. Think of it as an old telephone operator. They have, lets say they have 100 input ports and 100 output ports. And the operator connects, connects with any input to any output. Now, there are a lot of connections, a lot of possibilities there. But these things exist, these automatic operators using mirrors, and so forth. Theyre called n-by-n, nonblocking optical switches and you can reconfigure them, he said.

Whats cool about that is you can imagine having several hundred, rack-mounted, multi-core quantum computers, and you feed them into this optical switch, and you can then connect any multi-core chip to any other multi-core chip. The software can tell you exactly how you want to network. Thats very powerful as an architecture because we have a so-called full connection there. We wont have to move information to nearest neighbor and shuttle it around to swap; we can just do it directly, no matter where you are, said Monroe.

The third leg is error correction, which without question is a daunting challenge throughout quantum computing. The relative unreliability of qubits means you need many redundant physical qubits estimates vary widely on how many to have a single reliable logical qubit. Ions are among the better behaving qubits. For starters, all the ions are literally identical and not subject to manufacturing defects. A slight downside is that Ion qubit switching speed is slower than other modalities, which some observers say may hamper efficient error correction.

Said Monroe, The nice thing about trapped ion qubits is their errors are already pretty good natively. Passively, without any fancy stuff, we can get to three or four nines[i] before we run into problems.

What are those problems? I dont want to say theyre fundamental, but there are brick walls that require a totally different architecture to get around, said Monroe. But we dont need to get better than three or four nines because of error correction. This is sort of a software encoding. The price you pay for error correction, just like in classical error correction encoding, is you need a lot more bits to redundantly encode. The same is true in quantum. Unfortunately, with quantum there are many more ways you can have an error.

Just how many physical qubits are needed for a logical qubit is something of an open question.

It depends what you mean by logical qubit. Theres a difference in philosophy in the way were going forward compared to many other platforms. Some people have this idea of fault tolerant quantum computing, which means that you can compute infinitely long if you want. Its a beautiful theoretical result. If you encode in a certain way, with enough overhead, you can actually you can run gates as long as you want. But to get to that level, the overhead is something like 100,000 to one, [and] in some cases a million to one, but that logical qubit is perfect, and you get to go as far as you want [in terms of number of gate operations], he said.

IonQ is taking a different tack that leverages software more than hardware thanks to ions stability and less noisy overall support system [ion trap]. He likens improving qubit quality to buying a nine in the commonly-used five nines vernacular of reliability. Five nines 99.999 percent (five nines) is used describe availability, or put another way, time between shutdowns because of error.

Were going to gradually leak in error correction only as needed. So were going to buy a nine with an overhead of about 16 physical qubits to one logical qubit. With another overhead of 32 to one, we can buy another nine. By then we will have five nines and several 100 logical qubits. This is where things are going to get interesting, because then we can do algorithms that you cant simulate classically, [such] as some of these financial models were doing now. This is optimizing some function, but its doing better than the classical result. Thats where we think we will be at that point, he said.

Monroe didnt go into detail about exactly how IonQ does this, but he emphasized that software is the big driver now at IonQ. Our whole approach at IonQ is to throw everything up to software as much as we can. Thats because we have these perfectly replicable atomic qubits, and we dont have manufacturing errors, we dont have to worry about a yield or anything like that everything is a control problem.

So how big a system do you need to run practical applications?

Thats a really good question, because I can safely say we dont exactly know the answer to that. What we do know if you get to about 100 qubits, maybe 72, or something like that, and these qubits are good enough, meaning that you can do 10s of 1000s of ops. Remember, with 100 qubits you want to do about 10,000 ops to something you cant simulate classically. This is where you might deploy some machine learning techniques that you would never be able to do classically. Thats probably where the lowest hanging fruit are, said Monroe.

Now for us to get to 100 [good] qubits and say 50,000 Ops, that requires about 1000 physical qubits, maybe 1500 physical qubits. Were looking at 1200 physical qubits, and this might be 16 cores with 64 ions in each core before we have to go to photonic connections. But the photonic connection is the key because [its] where you start to have a truly modular data center. You can stamp these things out. At that point, were just going to be making these things like crazy, and wiring them together. I think well be able to do interesting things before we get to that stage and it will be important if we can show some kind of value (application results/progress) and that we have the recipe for scaling indefinitely, thats a big deal, he said.

It is probably going too far to say that Monroe believes scaling up IonQs quantum computer is now just a straightforward engineering task, but it sometimes sounds that way. The biggest technical challenges, he suggests, are largely solved. Presumably, IonQ will successfully demonstrate its modular architecture in 2022. He said competing approaches superconducting and all-photonics, for example wont be able to scale. They are stuck, he said.

I think they will see atomic systems as being less exotic than they once thought. I mean, we think of computers as built from silicon and as solid state. For better for worse you have companies that that forgot that they supposed to build computers, not silicon or superconductors. I think were going to see a lot more fierce competition on our own turf, said Monroe. There are ion trap rivals. Honeywell is one such rival (Honeywell has announced plans to merge with Cambridge Quantum), said Monroe.

His view of the long-term is interesting. As science and hardware issues are solved, software will become the driver. IonQ already has a substantial software team. The company uses machine learning now to program its control system elements such as the laser pulses and connectivity. Were going to be a software company in the long haul, and Im pretty happy with that, said Monroe.

IonQ has already integrated with the three big cloud providers (AWS, Google, Microsoft) quantum offerings and embraced the growing ecosystem of software and tools providers and has APIs for use with a variety of tools. Monroe, like many in the quantum community, is optimistic but not especially precise about when practical applications will appear. Sometime in the next three years is a good guess, he suggests. As for which application area will be first, it may not matter in the sense that he thinks as soon as one domain shows benefit (e.g. finance or ML) other domains will rush in.

These are heady times at IonQ, as they are throughout quantum computing. Stay tuned.

[i] He likens improving qubit quality to buying a nine in the commonly-used five nines vernacular of reliability. Five nines 99.999 percent (five nines) is used describe availability, or put another way, time between shutdowns because of error.

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IonQ Is First Quantum Startup to Go Public; Will It be First to Deliver Profits? - HPCwire

PARIS, Nov. 4, 2021 Pasqal, developers of neutral atom-based quantum technology, today announced it was named Startup of the Year by LUsine Nouvelle, a leading French business news site covering economic and industrial news across industries. LUsine Nouvelles awards programs honor innovations, individuals and projects that aim to solve societys biggest challenges.

Founded in 2019 as a spin-off from Institut dOptique, Pasqal was the first startup dedicated to quantum computing in France. The company is on an accelerated growth track and expects to grow from 40 employees to 100 by the end of 2022. Pasqal raised a 25 M Series A funding round in June 2021, one of the largest series A rounds in Europe for a deep tech startup. This award comes on the heels of a momentous year for Pasqal. In 2021, the company grew its employee base by 300%, adding 30 new team members from eight different regions.

This award recognizes Pasqals tremendous contributions to the quantum ecosystem. Pasqals initiatives are aligned with the French quantum national plan and the France 2030 investment plan which identified deep tech and quantum computing as critical industries for Frances success. Pasqal aims to solve real-word challenges through quantum technology and believes it will deliver a 1000-qubit quantum processor to the market in 2023, faster than the quantum development roadmaps of the tech giants in the field. Capable of operating at room temperature, Pasqals full-stack, software-agnostic quantum processing units have the potential to address complex problems in medicine, finance and sustainability more efficiently than classical computers. Pasqals open-source library, Pulser enablesthecontrolof neutralatoms-basedprocessors at the level of laser pulses.

Pasqal is already exploring specific use cases across industries. The company is working with a leading French utility company, EDF, to optimize charging schedules for electric vehicles to combat climate change. Pasqal is also working with Crdit Agricole CIB and Multiverse Computing to design and implement new approaches running on classical and quantum computers to outperform state-of-the-art algorithms for capital markets and risk management. In addition, the company is working with Qubit Pharmaceuticals to accelerate drug discovery through quantum technology. Pasqal hopes these initial use cases will open the door to additional applications in carbon capture, energy and sustainability.

With the companys recent funding, Pasqal plans to continue innovating and developing new solutions. By the end of 2022, Pasqal plans to provide cloud access to its quantum computing services and hopes to deliver a full quantum computing device operating on the cloud by 2023.

Georges-Olivier Reymond, CEO and founder of Pasqal, accepted the award at LUsine Nouvelles Foundations of the Industry event today in Paris. The event was attended by more than 150 industry leaders and decision-makers, uniting various industry sectors in France and Europe.

Were honored to be named Startup of the Year among the many French technology startups aiming to solve the worlds biggest challenges, said Reymond. Were proud to be part of Frances hub for technology innovation, supported by the French government, and we look forward to putting our quantum technology to real-world use throughout the region.

To learn more about Pasqal and its award-winning solutions, please visit: http://www.pasqal.io.

About Pasqal

Pasqalis building quantum processors out of neutral atoms atoms possessing an equal number of electrons and protons through the use of optical tweezers using laser light, enabling the engineering of full-stack processors with high connectivity and scalability.

The company is dedicated to delivering a 1000-qubit quantum processor by 2023 to help customers achieve quantum advantage in the fields of quantum simulation and optimization across several vertical sectors, including finance, energy and supercomputing.

For more information, please contact the company:contact@pasqal.io

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Disclaimer: AAAS and EurekAlert! are not responsible for the accuracy of news releases posted to EurekAlert! by contributing institutions or for the use of any information through the EurekAlert system.

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Pasqal named startup of the year by L'Usine Nouvelle - EurekAlert

Early internal calculations show a final chip that could perform 24% quicker than current best available ASIC

OVERVIEW

The goal of the Company is to develop disruptive Bitcoin mining technology, to mine both faster and with less overall energy consumption than current practices. A number of advanced technologies are being used by QBT to achieve this goal; namely, quantum computing, AI Neural Networks - Deep Learning, Algebraic-Boolean reductions, Very Big Data, Cryptography and custom chip programming and design - using GPU, FPGA and ASIC chips.

The current technique used by producers of Bitcoin mining technology on dedicated computers to achieve the fastest performance, is by manufacturing single purpose, customised ASIC chips, which can perform only one wired function, i.e, the computation of the double hashing; the SHA26 cryptographic algorithm used to extract Bitcoins. The simple reality is that the faster the algorithms are computed and the more ASIC chips deployed, the more chances a miner has to extract Bitcoins.

Before manufacturing an ASIC chip, which is an expensive operation, there are usually two initial steps; firstly, to develop the logic gates architecture which will be used by the final ASIC chip this is performed on a cheaper but slower chip, called an FPGA, which already contains some pre-defined functions - and secondly, by customising the design to take advantage of the greater freedom offered by ASIC technology, initially by manufacturing a prototype in a small batch, to keep costs low. The final stage, manufacturing the completed ASIC chip, is an expensive process, but the end result is a very small scale (currently up to 5nm) processing chip, which is significantly quicker, leading to greater results when mining Bitcoin.

QBT has now completed the FPGA development phase and is moving to develop its ASIC protype.

Initial estimates derived from the FPGA performance obtained from our internal testing, would indicate that when the final industrial ASIC prototype design is completed it could outperform the fastest ASIC chip, currently being used to mine Bitcoin by at least 24%.

Moreover, early experimental evidence, using AI techniques to multiply by several factors the speed of an FGPA for computing the Bitcoin mining algorithm, would make even an FPGA a competitive Bitcoin mining tool. This same principal would apply to ASIC and other existing commercial mining tools. Tests on this innovative approach, will continue over the next three months.

DETAILED VIEW

Following testing of a variety of design options, an unrolled SHA-256 architecture has now been implemented, with a number of existing optimisations coded, for QBTs FPGA chip prototype.

The Companys patented ASIC ULTRA Boost improvements (patent under application) will be added in the next few weeks, as a result of the close cooperation between the in-house cryptography expert and the Companys FPGA designer.

Current performance of the Bitcoin mining architecture developed by QBT on the FPGA (based on 16nm technology, at 600MHz basic cycle and the average general purpose available coding area) is 2.8 Giga Hash per second (GH/s) with an estimated 50W energy consumption. The ASIC ULTRA Boost optimisation should improve the above performance by 7% as previously reported.

To put things into context, our in-house expert has calculated that, as of today, a top of the range FPGA (using QBTs architecture of the implementation of the algorithm, to make it run at approximately 15 times faster than the standard FPGA), is still approximately 23.4 times slower than the best-in-class existing 7nm ASIC Bitcoin mining chip and much less energy efficient.

It was never the Companys intention to compete on speed and energy efficiency against an ASIC chip, using an FPGA chip but, in order to keep testing costs significantly lower, it has been a necessary step for QBT to take in this phase of its development. As a result, the Company is now in a much better position to assess the performance projection of its SHA256 Bitcoin mining architecture, and therefore the team is confident that it can now transfer this solution over to an ASIC chip.

Preliminary approximate calculations indicate that on a 12nm ASIC chip, extrapolated by comparing it to a commercial mid-range 16nm ASIC Bitcoin mining chip (with circa 300 million gates), our ASIC could achieve a double hash rate of 392 GH/s, with the ASIC ULTRA Boost optimisation adding an extra 7% as previously announced, reaching 419 GH/s, which would still be 2.26 times slower than the fastest ASIC commercially available.

However, the Company strongly believes that when compared with the best commercial 7nm ASIC chip for Bitcoin mining available on the market today, an industrial production of QBTs ASIC at 7nm, would indicate a double hash rate of 1.19TH/s, hence 24% faster.

This performance of QBTs architecture on the 7nm ASIC, doesnt yet include the 7% efficiency achieved by the optimisation of the patent application filed in September, which is still to be implemented. The current work on a second patent by the Companys cryptography expert will hopefully lead to further material optimisations.

Detailed simulations on energy consumption will be run as soon as our ASIC gate design layout is completed.

ASIC programming will start this month, and we estimate that by the end of Q1 2022 we will be able to announce when the first batch of prototype chips will be available for in-house testing. Following the completion of testing, the Company envisages that chip production, for QBTs own use, will commence by the end of 2022.

Concurrently, QBTs R&D team is also considering an alternative SHA256 computing approach (which is categorised as the basic Bitcoin mining algorithm), and this will be tested within the next three months. The joint effort by the members of our AI team and the Companys FPGA expert, could improve the current FPGA hash rate of 2.8GH/s by a highly material multiple factor, making mining by the slower FPGA chip potentially competitive against the best-in-class ASIC chip. Should this route be successful, mining via this method could commence as early as Q2 2022.

These AI techniques, if successful, could also improve the performance of current commercial ASIC Bitcoin miners.

The Companys new R&D IT infrastructure, which will also allow for Bitcoin mining tests to be carried out, will be operational in five weeks time. The wait has been due to the serious worldwide shortage of silicon chips, which is delaying the expected delivery of the hardware. However, the Company has adopted the heavy use of cloud resources in order to avoid any interruption in the R&D activities to the various groups.

The Company remains very confident on the R&D strategy it has adopted which it believes could result in disruptive Bitcoin mining. It is worth noting that the Companys R&D programme is fully funded until the end of 2022.

Francesco Gardin, CEO and Chairman of QBT, commented, Our R&D has delivered some very impressive results in a very short time: In only four months since the programme commenced, we have filed a patent application where we believe the ASIC ULTRA Boost has improved the standard mining algorithm, after five years of little or no progress following the publication in 2016 of the ASIC Boost paper.

We will soon be ready to start the design of our ASIC Bitcoin mining chip which, on paper, already outperforms, in speed, the current best in class ASIC Bitcoin mining commercial solution. This significant improvement is before the implementation of the new optimisation from ASIC ULTRA Boost and we are confident that our second patent application, which is under development by our cryptography expert, will add a further radical improvement to the process, including also a reduction in energy consumption.

All our other teams are working extremely hard on the other R&D fronts: Quantum computing and AI Neural Networks-Deep Learning and algebraic-Boolean optimisation. Meanwhile an AI accelerator will be tested within the next three months, which we believe could radically improve the performance of existing commercial miners, as well as our GPU, FPGA and, in the near future, our AISC chip. We consider that the R&D activity undertaken by our group of 15 experts is unbelievably exciting and, if successful, could potentially be radically innovative for the industry.

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Quantum Blockchain Technologies Plc - Update on FPGA and ASIC Development - Yahoo Finance UK