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Quantum Computer Hardware component breakthroughs accelerate their scaling and commercialization

Quantum computers promise the potential to tackle problems that conventional computers can’t handle by leveraging a phenomenon of quantum physics that allows qubits to exist in multiple states simultaneously. As a result, qubits can conduct a large number of calculations at the same time — dramatically speeding up complex problem-solving.


In the race to realize the power and potential of quantum computers, researchers have focused extensively on qubit fabrication, building test chips that demonstrate the exponential power of a small number of qubits operating in superposition. While much progress has been made in the development of small-scale quantum computers, a design for a quantum computer that can scale to the size needed to break current cryptography has not been demonstrated, nor can it be achieved by straightforward scaling of any of the current implementations.


Quantum hardware is an active area of research. Numerous academic groups and government-affiliate laboratories worldwide are researching how to design, build, and control qubit systems, and numerous established and start-up companies are now working to commercialize quantum computers built from superconducting and trapped ion qubits.


Quantum Computer Hardware

Apart from the development of qubits and the number of qubits in the current prototypical quantum computing chip, any quantum computer requires an integrated hardware approach using significant conventional hardware to enable qubits to be controlled, programmed, and readout.


A quantum processing unit (QPU) is a computational unit that relies on quantum principles to perform a task. the QPU includes the:

QRAM (register + gates)
Quantum control unit (QCU) which drives the system to the desired state.
Classical controller interface which defines the interaction between the host CPU and the QPU


To assist in conceptualizing the necessary hardware components for an analog or gate-based quantum computer, the hardware can be modeled in four abstract layers: the “quantum data plane,” where the qubits reside; the “control and measurement plane,” responsible for carrying out operations and measurements on the qubits as required; the “control processor plane,” which determines the sequence of operations and measurements that the algorithm requires, potentially using measurement outcomes to inform subsequent quantum operations; and the “host processor,” a classical computer that handles access to networks, large storage arrays, and user interfaces. This host processor runs a conventional operating system/user interface, which facilitates user interactions, and has a high bandwidth connection to the control processor.


The quantum data plane is the “heart” of a QC. It includes the physical qubits and the structures needed to hold them in place. It also must contain any support circuitry needed to measure the qubits’ state and perform gate operations on the physical qubits for a gate-based system or control the Hamiltonian for an analog computer.   The control and measurement plane converts the control processor’s digital signals, which indicates what quantum operations are to be performed, to the analog control signals needed to perform the operations on the qubits in the quantum data plane. Control information for the qubits, which is analog in nature, must be sent to the correct qubit (or qubits). In some systems, this control information is transmitted electrically using wires, so these wires are part of the quantum data plane; in others, it is transmitted with optical or microwave radiation.


The control processor plane identifies and triggers the proper Hamiltonian or sequence of quantum gate operations and measurements (which are subsequently carried out by the control and measurement plane on the quantum data plane). These sequences execute the program, provided by the host processor, for implementing a quantum algorithm. The control processor plane operates at a low level of abstraction: it converts compiled code to commands for the control and measurement layer. As a result, a user will not interact with (or need to understand) the control processor plane directly. Rather, the user will interact with a host computer. This plane will attach to that computer and act to accelerate the execution of some applications. This type of architecture is widely used in today’s computers, with “accelerators” for everything from graphics to machine learning to networking.


The host processor is a classical computer, running a conventional operating system with standard supporting libraries for its own operation. This computing system provides all of the software development tools and services users expect from a computer system. It will run the software development tools necessary to create applications to be run on the control processor, which are different from those used to control today’s classical computers, as well as provide storage and networking services that a quantum application might require while running. Attaching a quantum processor to a classical computer allows it to utilize all of its features without needing to start entirely from scratch.


Quantum Hardware advances

Quantum computers are, by default, hybrid machines that combine the exotic properties of the quantum world with a classical computer that, essentially, manages it. A lot of the focus in the industry has gone into the actual quantum processors, but as those machines get more powerful, the classical part — and the process of converting those digital commands for use in the analog world of quantum computing — is becoming a bottleneck. That’s what Quantum Machines, an Israeli startup that’s coming out of stealth today, is tackling. The company’s Quantum Orchestration Platform is a full hardware and software solution for controlling quantum systems. The company built its own custom pulse processor that can handle multi-qubit manipulation while being independent of the quantum processor with which it interacts (assuming it’s supported, of course).


Intel and QuTech Unveil Details of First Cryogenic Quantum Computing Control Chip, ‘Horse Ridge’

Intel Labs, in collaboration with QuTech ‑ a partnership between TU Delft and TNO (Netherlands Organization for Applied Scientific Research) ‑ outlines key technical features of its new cryogenic quantum control chip “Horse Ridge” in a research paper released at the 2020 International Solid-State Circuits Conference (ISSCC) in San Francisco. The paper unveils key technical capabilities of Horse Ridge that address fundamental challenges in building a quantum system powerful enough to demonstrate quantum practicality: scalability, flexibility and fidelity.


Since a quantum computer must eventually interface with users, data, and networks—tasks that conventional computing excels at—a quantum computer can leverage a conventional computer for these tasks whenever it is most efficient to do so. Furthermore, qubit systems require carefully orchestrated control in order to function in a useful way; this control can be managed using conventional computers.


A lot of research has gone into qubits, which can do simultaneous calculations. But Intel saw that controlling the qubits created another big challenge to developing large-scale commercial quantum systems, said Jim Clarke, director of quantum hardware, at an Intel press event. Intel Labs unveiled a first-of-its-kind cryogenic control chip — code-named Horse Ridge — that will speed up the development of quantum computing systems. Horse Ridge will enable control of multiple quantum bits (qubits) and set a clear path toward scaling larger systems — a major milestone on the path to quantum practicality.


“We’re looking at what it’s going to take to scale quantum systems to a large number of qubits,” said Richard Uhlig, managing director of Intel Labs, in an interview with VentureBeat. “And we need to get there because until you get to thousands or millions of qubits, you’re not really going to be solving the interesting problems. If you want to do that, you have to have a strategy for configuring, reading out the state of qubits in large numbers. And today, those control electronics need to run at higher temperatures than the qubits themselves.”


Horse Ridge greatly simplifies today’s complex control electronics required to operate such a quantum system by using a highly integrated system-on-chip (SoC) for faster setup time, improved qubit performance and efficient scaling to larger qubit counts required for quantum computing to solve practical, real-world applications.  It effectively reduces the complexity of quantum control engineering from hundreds of cables running into and out of a refrigerator to a single unified package operating near the quantum device. Replacing these bulky instruments with a highly integrated system-on-chip (SoC) will simplify system design and allow for sophisticated signal processing techniques to accelerate set-up time, improve qubit performance, and enable the system to efficiently scale to larger qubit counts.


“What we’ve done with Horse Ridge — that’s the code name for this cryo CMOS controller — is that it’s able to run at temperatures that are much closer to the qubits themselves. It runs at about 4 degrees Kelvin. The innovation is that we solved the challenges around getting CMOS to run at that at those temperatures and still have a lot of flexibility in how the qubits are controlled and configured.” “It’s pretty unique in the community, as we’re going to take all these racks of electronics you see in a university lab and miniaturize that with our 22-nanometer technology and put it inside of a fridge,” said Clarke. “And so we’re starting to control our qubits very locally without having a lot of complex wires for cooling.”


Horse Ridge is fabricated using Intel’s 22-nanometer FinFET manufacturing technology. The in-house fabrication of these control chips at Intel will dramatically accelerate the company’s ability to design, test, and optimize a commercially viable quantum computer, the company said. Designed to act as a radio frequency (RF) processor to control the qubits operating in the refrigerator, Horse Ridge is programmed with instructions that correspond to basic qubit operations. It translates those instructions into electromagnetic microwave pulses that can manipulate the state of the qubits.


Scalability: The integrated SoC design, implemented using Intel’s 22nm FFL (FinFET Low Power) CMOS technology, integrates four radio frequency (RF) channels into a single device. Each channel is able to control up to 32 qubits leveraging “frequency multiplexing” – a technique that divides the total bandwidth available into a series of non-overlapping frequency bands, each of which is used to carry a separate signal. Leveraging these four channels, Horse Ridge can potentially control up to 128 qubits with a single device, substantially reducing the number of cables and rack instrumentations previously required.


Fidelity: Increases in qubit count trigger other issues that challenge the capacity and operation of the quantum system. One such potential impact is a decline in qubit fidelity and performance. In developing Horse Ridge, Intel optimized the multiplexing technology that enables the system to scale and reduce errors from “phase shift” – a phenomenon that can occur when controlling many qubits at different frequencies, resulting in crosstalk among qubits. The various frequencies leveraged with Horse Ridge can be “tuned” with high levels of precision, enabling the quantum system to adapt and automatically correct for phase shift when controlling multiple qubits with the same RF line, improving qubit gate fidelity. Flexibility: Horse Ridge can cover a wide frequency range, enabling control of both superconducting qubits (known as transmons) and spin qubits. Transmons typically operate around 6 to 7 GHz, while spin qubits operate around 13 to 20 GHz.


Intel said this feat is particularly exciting as Intel progresses its research into silicon spin qubits, which have the potential to operate at slightly higher temperatures than current quantum systems require. Today, a quantum computer operates at in the millikelvin range — just a fraction of a degree above absolute zero. But silicon spin qubits have properties that could allow them to operate at 1 degree Kelvin or higher temperatures, which would dramatically reduce the challenges of refrigerating the quantum system. As research progresses, Intel aims to have cryogenic controls and silicon spin qubits operate at the same temperature level. This will enable the company to create a solution with the qubits and controls in one streamlined package. “It’s a fully working controller, one that we’ve demonstrated at at at those temperatures,” Uhlig said. “And, you know, we’ve been able to show that it works successfully, with full flexibility on the waveforms that you can even send down to the qubits for the purpose of control and readout.”


Cryogenic electro-optical interconnects

Scientists from the Swiss Federal Institute of Technology Lausanne (EPFL) and the Indian Institute of Science Education and Research have demonstrated that commercially available devices known as electro-optical modulators can be used to read the output of superconducting quantum computers at extremely low temperatures. Using an optical signal instead of an all-electrical approach addresses the high heat-load contribution of electrical components, which is known to reduce the overall efficiency of devices. By demonstrating that an optical system can operate at a fraction of a degree above absolute zero, the result could open a new route to scaling up quantum computers.


Optical fibres transmit light via the highly efficient process of total internal reflection and are widely employed in the telecommunications industry. Because fibre networks carry a great deal of information with low signal losses, they are well suited to transferring data over long distances. As fibre technology improves, these benefits are increasingly being applied to data transfer over shorter distances as well, such as the connections between homes and optical fibre networks and optical connections in chip-scale devices.


Optical components are smaller and lighter than bulky, thermally conductive electrical cables, and their low heat loads make them especially attractive to developers of quantum computers that use superconducting quantum bits (qubits) to store information. At present, these devices require extremely low temperatures to operate, which poses questions about how to add more qubits while managing the thermal contributions of additional components.


To tackle this problem, Tobias Kippenberg and colleagues developed an integrated optical solution that eliminates the noise associated with the heat-load of electrical components by replacing these components with less thermally conductive optical devices. Currently, electrical amplifiers based on so-called high-electron-mobility transistors are used to read the microwave signal produced by superconducting devices. The new optical approach replaces these amplifiers with off-the-shelf electro-optical modulators, which use an electrical signal to control the phase of light. This means that the microwave signal produced by the superconducting device can be converted to the optical domain to be read at the output.


Crucially, this change enabled the researchers to use optical fibre connections instead of electrical coaxial cables, which were a source of heat in the original system. To realize this benefit, however, the researchers needed to demonstrate that the modulators could operate at the very low temperatures required by the superconducting device. After testing the performance of the modulator down to 800 mK, they showed that the device was indeed suitable as an interconnect between the microwave signal of the superconducting device and an optical detection scheme.


The researchers then compared their new optical design, which they describe in Nature Electronics, with the existing electrical version in two important tests. In the first test, they used coherent microwave spectroscopy, where a laser acts as a mechanical pump to produce a microwave signal in the superconducting device, to confirm that the modulator was able to convert the signal into an optical readout. In the second test, they used the optical modulator to link the superconducting device, which operates at 15 mK, to a room temperature detector. This made it possible to measure the microwave signal produced by the superconducting device directly.


The authors compared the output of the optical device with that of a traditional transistor to show that, whilst there are still improvements to be made in reducing optical noise, the new system nevertheless performs the function of the transistor amplifiers with a vast reduction in heat loss. This result highlights the promise of the optical approach for achieving efficient devices that can provide scalability in superconducting quantum technologies.


Quantum Machines Quantum Orchestration Platform to Powers the Global Quantum Computing Race

Quantum Machines, creator of the first complete hardware and software solution for the control and operation of quantum computers, announced that it has secured $17.5M in funding to accelerate the already rapid adoption of the company’s Quantum Orchestration Platform, which is driving the development of tomorrow’s quantum breakthroughs. The Series A round was led by Avigdor Willenz and Harel with the participation of previous backers TLV Partners and Battery Ventures.


“The classical layers of the quantum computer are the real unmet need. They are the bottleneck,” Quantum Machines co-founder Itamar Sivan told me. “We were really looking into what is holding the industry back. What are the things that we can do today to drive this industry forward, but that will also enable faster progress in the future. Since most of the focus in the last years has been devoted to quantum processors, it was only natural that you know we take on this challenge.”


The problem, he explained, is that in order to run complex algorithms on quantum processors, you also need extremely powerful classical computers. But with Moore’s Law at its end, it takes specialized hardware to do that effectively. And Quantum Machines’ hardware also offers very fast calibration, which in turn yields better, more precise results from the quantum processors it controls. What the company isn’t sharing, of course, is how exactly it is solving this problem. That is, after all, the secret sauce the team developed.


In the race to bring general-purpose quantum computers to fruition, Quantum Machines (QM) announced a major breakthrough earlier this year with the launch of its Quantum Orchestration Platform and its adoption by major players. Its complete set of features works with all quantum technologies, giving researchers and development teams everything they need to run the most complex quantum algorithms and experiments. Looking to the future, Quantum Orchestration lays the ground for tackling some of the most challenging hurdles facing quantum computing, such as complex multi-qubit calibrations, quantum-error-correction, and scaling up to many hundreds of qubits.


Israeli entrepreneur Avigdor Willenz, who recently sold Habana Labs to Intel for $2 billion, is backing QM after the massive enthusiasm he’s witnessed from across the quantum computing industry. “The race to commercial quantum computers is one of the most exciting technological challenges of our generation,” said Willenz, who has also sold companies to Intel, Marvell, Amazon, and Cisco. “Our goal at QM is to make this happen faster than anticipated, and establish ourselves as an essential player in this emerging industry.”


QM was founded in 2018 by Drs. Itamar Sivan, Yonatan Cohen and Nissim Ofek, three physics Ph.Ds. They met at Israel’s Weizmann Institute after each had studied at the world’s top universities, including Yale University, University of Washington, Oxford University and the Ecole Normale Superieure. The QM team has since grown to nearly 30 — more than half of them physicists.


QM’s Orchestration Platform has already been adopted by multinational corporations and startups at the forefront of quantum computing, with many new paying customers joining us every month. “We have been fortunate to assemble a team of all-star researchers and scientists working on the greatest challenges of quantum computing,” said Dr. Itamar Sivan, co-founder and CEO of QM. “Their prowess is evident in the lead that QM has taken as the only company to develop Quantum Orchestration. Quantum technology will decisively shape our future and this new investment will ensure that QM remains at the center of these exciting advancements.”


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