In June 2023, we offered how quantum computing must graduate through three implementation levels (quantum computing implementation levels QCILs) to achieve utility scale: Level 1 Foundational, Level 2 Resilient, Level 3 Scale. All quantum computing technologies today are at Level 1. And while NISQ machines are all around us, they do not offer practical quantum advantage. True utility will only come from orchestrating resilient computation across a sea of logical qubits something that, to the best of our current knowledge, can only be achieved with error correction and fault tolerance. Fault tolerance will be a necessary and essential ingredient in any quantum supercomputer, and for any practical quantum advantage.The first step toward the goal of reaching practical quantum advantage is to demonstrate resilient computation on a logical qubit. However, just one logical qubit will not be enough; ultimately the goal is to show that quantum error correction helps non-trivial computation instead of hindering, and an important element of this non-triviality is the interaction between qubits and their entanglement. Demonstrating an error corrected resilient computation, initially on two logical qubits, that outperforms the same computation on physical qubits, will mark the first demonstration of a resilient computation in our field's history.The race is on to demonstrate a resilient logical qubit but what is a meaningful demonstration? Before our industry can declare a victory on reaching Level 2 for a given quantum computing hardware and claim the demonstration of a resilient logical qubit, it's important to align on what this means.Criteria of Level 2: resilient quantum computation
How should we define a logical qubit? The most meaningful definition of a logical qubit hinges on what one can do with that qubit demonstrating a qubit that can only remain idle, that is, be preserved in a memory, is not meaningful if one cannot demonstrate non-trivial operations as well. Therefore, it makes sense to define a logical qubit such that it allows some non-trivial, encoded computation to be performed on it.Distinct hardware comes with distinct native operations. This presents a significant challenge in formally defining a logical qubit; for example, the definition should not favor one hardware over another. To address this, we propose a set of criteria that mark the entrance into the resilient level of quantum computation. In other words, these are the criteria for calling something a "logical qubit".Entrance criteria to Level 2Exiting Level 1 NISQ computing and entering Level 2 Resilient quantum computing is achieved when fewer errors are observed on the output of a logical circuit using quantum error correction than on the same analogous physical circuit without error correction.We argue that a demonstration of the resilient level of quantum computation must satisfy the following criteria:
involve at least 2 logical qubitsdemonstrate convincingly large separation (ideally 5-10x) of logical error rate < physical error rate on the non-trivial logical circuitcorrect all individual circuit faults ("fault distance" must be at least 3)implement a non-trivial logical operation that generates entanglement between logical qubitsThe justification for these is self-evident being able to correct errors is how resiliency is achieved and demonstrating an improvement over physical error rates is precisely what we mean by resiliency but we feel that it is worth emphasizing the requirement for logical entanglement. Our goal is to achieve advantage with a quantum computer, and an important ingredient to advantage is entanglement across at least 2 logical qubits.The distinction between Resilient Level and the Scale Level is also important to emphasize a proof of principle demonstration of resiliency must be convincing, but it does not require a fully scaled machine. For this reason, we find it important to allow some forms of post-selection, with the following requirements
Post-selection acceptance criteria must be computable in real-time (but may be implemented in post-processing for demonstration);scalable post-selection (rejection rate can be made vanishingly small)if post-selection is not scalable, it must at least correct all low weight errors in the computations (with the exception of state-preparation, since post-selection in state-preparation is scalable);In other words, post-selection must be either fully compatible with scalability, or it must still allow for demonstration of the key ingredients of error correction, not simply error detection.Measuring progress across Level 2Once a quantum computing hardware has entered the Resilient Level, it is important to also be able to measure continued progress toward Level 3. Not every type of quantum computing hardware will achieve Level 3 Scale, as the requirements to reach Scale include achieving upwards of 1000 logical qubits with logical error rates better than 10-12 and mega-rQOPS and more.Progress toward scale may be measured along four axes: universality, scalability, fidelity, composability. We offer the following ideas to the community on how to measure progress across these four axes, such that we as a community can benchmark progress in the resilient level of utility scale quantum computation:
Universality: universality typically splits into two components: Clifford group gates and non-Clifford group gates. Does one have a set of high-fidelity Clifford-complete logical operations? Does one have a set of high-fidelity universal logical operations? A typical strategy employed is to design the former, which can then be used in conjunction with a noisy non-Clifford state to realize a universal set of logical operations. Of course, different hardware may employ different strategies.Scalability: At its core, resource requirement for advantage must be reasonable (i.e., small fraction of Earth's resources or a person's lifetime). More technically, quantum resource overhead required should scale polynomially with target logical error rate of any quantum algorithm. Note also that some systems may achieve very high fidelity but may have limited numbers of physical qubits, so that improving the error correction codes in the most obvious way (increasing distance) may be difficult.Fidelity: Logical error rates of all operations improve with code size (sub-threshold). More strictly, one would like to see logical error rate is better than physical error rate (sub-pseudothreshold). Progress on this axis can be measured with Quantum Characterization Verification & Validation (QCVV) performed at the logical level, or with other operational tasks such as Bell inequality violations and self-testing protocols.Composability: Composable gadgets for all logical operations. Criteria to advance from Level 2 to Level 3, a Quantum SupercomputerThe exit of the resilient level of logical computation, and the achievement of the world's first quantum supercomputer, will be marked by large depth computations on high fidelity circuits involving upwards of hundreds of logical qubits. For example, a logical circuit on ~100+ logical qubits with a universal set of composable logical operations hitting a fidelity of ~10e-8 or better. Ultimately, a quantum supercomputer will be achieved once the machine is able to demonstrate 1000 logical qubits with logical error rate of 10^-12 and a mega-rQOPS. Performance of a quantum supercomputer can then be measured by reliable quantum operations per second (rQOPS).Conclusion
It's no doubt an exciting time to be in quantum computing. Our industry is at the brink of reaching the next implementation level, Level 2, which puts our industry on path to ultimately achieving practical quantum advantage. If you have thoughts on these criteria for a logical qubit, or how to measure progress, we'd love to hear from you.
A research team from the Vienna University of Technology has demonstrated that due to finite energy or entropy generation, no clock can achieve both perfect resolution and precision simultaneously.
This fundamental limitation impacts the potential capabilities of quantum computers.
This discovery implies natural limits for quantum computers, as the achievable resolution and precision in timekeeping restrict the speed and reliability of quantum computations.
UNIVERSITY RESEARCH NEWS — Vienna University of Technology/November 26, 2023 — There are different ideas about how quantum computers could be built. But they all have one thing in common: you use a quantum physical system — for example, individual atoms — and change their state by exposing them to very specific forces for a specific time. However, this means that in order to be able to rely on the quantum computing operation delivering the correct result, you need a clock that is as precise as possible.
But here you run into problems: perfect time measurement is impossible. Every clock has two fundamental properties: a certain precision and a certain time resolution. The time resolution indicates how small the time intervals are that can be measured — i.e., how quickly the clock ticks. Precision tells you how much inaccuracy you have to expect with every single tick.
The research team was able to show that since no clock has an infinite amount of energy available (or generates an infinite amount of entropy), it can never have perfect resolution and perfect precision at the same time. This sets fundamental limits to the possibilities of quantum computers.
Quantum calculation steps are like rotations
In our classical world, perfect arithmetic operations are not a problem. For example, you can use an abacus in which wooden balls are threaded onto a stick and pushed back and forth. The wooden beads have clear states, each one is in a very specific place, if you don’t do anything the bead will stay exactly where it was.
And whether you move the bead quickly or slowly does not affect the result. But in quantum physics it is more complicated.
“Mathematically speaking, changing a quantum state in a quantum computer corresponds to a rotation in higher dimensions,” says Jake Xuereb from the Atomic Institute at the Vienna University of Technology in the team of Marcus Huber and first author of the first paper published in Physical Review Letters. “In order to achieve the desired state in the end, the rotation must be applied for a very specific period of time. Otherwise, you turn the state either too short or too far.”
Entropy: Time makes everything more and more messy
Marcus Huber and his team investigated in general which laws must always apply to every conceivable clock. “Time measurement always has to do with entropy,” explains Marcus Huber. In every closed physical system, entropy increases and it becomes more and more disordered. It is precisely this development that determines the direction of time: the future is where the entropy is higher, and the past is where the entropy is even lower.
As can be shown, every measurement of time is inevitably associated with an increase in entropy: a clock, for example, needs a battery, the energy of which is ultimately converted into frictional heat and audible ticking via the clock’s mechanics — a process in which a fairly ordered state occurs the battery is converted into a rather disordered state of heat radiation and sound.
On this basis, the research team was able to create a mathematical model that basically every conceivable clock must obey. “For a given increase in entropy, there is a tradeoff between time resolution and precision,” says Florian Meier, first author of the second paper, now posted to the arXiv preprint server. “That means: Either the clock works quickly or it works precisely — both are not possible at the same time.”
Limits for quantum computers
This realization now brings with it a natural limit for quantum computers: the resolution and precision that can be achieved with clocks limits the speed and reliability that can be achieved with quantum computers. “It’s not a problem at the moment,” says Huber.
“Currently, the accuracy of quantum computers is still limited by other factors, for example, the precision of the components used or electromagnetic fields. But our calculations also show that today we are not far from the regime in which the fundamental limits of time measurement play the decisive role.”
Therefore, if the technology of quantum information processing is further improved, one will inevitably have to contend with the problem of non-optimal time measurement. But who knows: Maybe this is exactly how we can learn something interesting about the quantum world.
Featured image: The oversampling regime of an exemplary clock — a pendulum in a weakly lit environment. The two sources of entropy production for this clock are: the friction within the clockwork itself, and the matter–light interaction necessary to track the position of the pendulum. The plot shows the elementary ticking events of this clock as a function of time, i.e., the photons reflected off the pendulum when it is close to its maximum deflection. In the oversampling regime, the average time between two such ticks is much shorter than that of the period of the TPC (continuous line), which in the case of this pendulum is 2 s. Due to technical limitations, one does not count photons, but rather the TPC cycles through the averaged light intensity. Credit: arXiv (2023). DOI: 10.48550/arxiv.2301.05173
Riverlane has been chosen for Phase 2 of the Quantum Benchmarking programme funded by the Defense Advanced Research Projects Agency (DARPA). The programme aims to develop key quantum computing metrics for practical problems. Riverlane's CEO, Steve Brierley, stated that the programme aligns with their mission to make quantum computing useful sooner. The company is working with universities such as the University of Southern California and the University of Sydney to identify benchmarks for practical problems in various fields. Principal Quantum Scientist at Riverlane, Hari Krovi, highlighted the importance of fault tolerance in quantum computing.
BosonQ Psi’s Quantum-Inspired Design Optimization (QIDO) Solver has been validated as an effective solution for topology optimization in the aerospace and automotive industries, overcoming challenges faced by classical topology optimization methods in large-scale design problems. The study involved using the QIDO Solver to optimize airfoil structures, demonstrating its ability to efficiently handle complex design problems, such as weight minimization.
QIDO’s quantum-inspired approach, utilizing principles like superposition and entanglement, allows for simultaneous searching of larger solution spaces, resulting in better optimization than classical methods. This technology reduces the number of iterations and computing resources needed for topology optimization, offering more accurate and cost-effective solutions for airfoil structures in aircraft and automobiles.
The research highlighted the potential of QIDO Solver to dramatically improve aircraft and automobile performance and safety. Traditional topology optimization problems are typically solved using finite element analysis, but the QIDO Solver can handle complex design problems, such as minimization of the total weight of the structure, and finds global minima for obtaining optimal airfoil designs. This has implications for reducing manufacturing costs and enhancing efficiency in advanced aircraft and automobile airfoil structures.
RESEARCH NEWS— Buffalo, NY/November 15, 2023 — Design optimization finds the optimal material layout of a given structure by rearranging the material within the domain. It is classified into size, shape, and topology optimization based on the problem’s complexity. Topology optimization plays a significant role in achieving safer and more efficient designs for the aerospace and automotive industries. Different aircraft and automobile wing structures can be obtained with next-generation additive manufacturing technologies, departing from traditional rib-spar wing constructions. However, traditional topology optimization methods need to be revised when applied to aerospace structures due to their large-scale design problems.
This article will discuss the topology optimization capabilities of the Quantum-Inspired Design Optimization (QIDO) Solver, its advantages over classical methods, and the future roadmap for maximizing efficiency in advanced aircraft and automobile airfoil structures.
Figure 1: Schematic Airfoil section internal domain as design space, the outer skin as non-design space, and the wing supports are fixed.
Current Bottlenecks with the classical topology optimization techniques in Engineering Optimization:
The shape and weight of an airfoil plays a significant role in aircraft performance and safety. Topology optimization has become a priority within the aerospace and automotive industries to achieve safer and more efficient designs while reducing weight. However, computational challenges arise when dealing with high aspect-ratio wings, which require conventional density-based topology optimization methods to discretize the problem domain uniformly.
Figure 1 shows design space in blue, which is required to be discretized in the above optimization method. The complex geometry and boundary conditions turn the problem into a large-scale design optimization problem. Similarly, high aspect ratio domains of wings in aircraft or automobiles create more complex and harder-to-model design spaces [1, 2]. This limits the effectiveness of traditional classical optimization algorithms and classical computers that need an advanced solution.
Another limitation of the classical approach is that it reaches local minima instead of global minima, indicating that more efficient designs could be explored and exploited within the design process [3]. Additionally, classical optimization methods require more iterations to get optimal results for a given airfoil design, which demands more computing resources, such as GPUs and CPUs. Classical algorithms on classical computers demand more efficiency regarding the computing resources required while still delivering accuracy in topology optimization tasks.
Figure 2: The figure illustrates how, in the real world, the origin of aerodynamic forces on an airfoil section arises from the combined effects of pressure distributions and shear stress on the boundary layer.
Quantum-Inspired Approach in Design Optimization:
The Quantum-Inspired approach utilizes the principles of quantum computing, such as interference, superposition, and entanglement, to process information. By emulating these principles, the Quantum-Inspired approach allows for simultaneous searching of a larger solution space, leading to better-optimized results over classical solutions, faster convergence speed, and minimizing the usage of computing resources.
BosonQ Psi’s QIDO Solver is a Quantum-Inspired Design Optimization solver that maximizes efficiency in design engineering. QIDO’s ability to search the global optima sets it apart from traditional optimization techniques, resulting in better airfoil designs with higher performance and efficiency. The QIDO solver also significantly reduces the number of iterations required to converge to the optimal design, saving substantial simulation time. Moreover, by harnessing the power of quantum algorithms, the QIDO Solver optimizes the design using fewer computing resources, enhancing the cost-effectiveness of the design optimization process.
In the context of volume minimization of airfoil structures, the QIDO solver brings a different optimization landscape than classical methods. The low volume fraction of aerospace and automobile structures and the considerations of slenderness, buckling, and strength contribute to the complexity of optimizing low-weight, high-performance airfoil designs. By focusing on topology optimization methods, QIDO removes materials from unintended structures, meeting the demands for low-volume fraction aerospace structures, which increases the efficiency of the component.
Traditional topology optimization problems are typically solved using finite element (FE) analysis, treating each element’s presence as a design variable and aiming to find the optimal distribution of elements in the design domain [4]. This approach formulates the problem with continuous design variables, where design variables take values from 0 to 1. They produce optimal designs with fictitious elements and no clear boundary for fabricating them [4, 5].
Previous research has demonstrated that efficient topology optimization techniques can significantly enhance aircraft performance and safety. For example, Airbus’s method successfully reduced the weight of A380 components such as wingbox ribs by 10%, leading to increased stability, safety, and a 42% reduction in drag. These advancements in topology optimization have also led to cost reductions for aircraft manufacturing companies. However, for a middle-sized topology optimization problem on flexible wing structures, the number of design variables can reach up to approximately 70,000 to 100,000, making these problems incredibly complex for traditional optimization methods [2, 6].
With the QIDO (Quantum-Inspired Design Optimization) Solver from BosonQ Psi, topology optimization achieves highly optimized results for internal aircraft wing structures, improving efficiency and reducing manufacturing costs. The solver can handle complex design problems, such as minimization of the total weight of the structure, and finds global minima for obtaining optimal airfoil designs.
Figure 3: Optimal design of airfoil obtained using BQPhy’s QIDO solver
BQPhy’s topology optimization results for airfoil wings using QIDO have demonstrated remarkable outcomes. By considering the outer skin as a non-design domain, the weight of the airfoil structure can be reduced to 60% [refer to Figure 3] of its initial solid volume while maintaining its structural integrity.
Conclusion:
The QIDO presents a revolutionary approach to weight minimization in the design of airfoil structures. QIDO harnesses the principles of quantum computing and integrates them into the optimization process. This nascent methodology enables engineers to reach global minima, significantly reduces the number of iterations required, and optimizes designs using fewer computing resources. These advancements improve efficiency, reduce manufacturing costs, and the possibility of pushing the boundaries of performance and innovation in advanced aircraft and automobile airfoil structures. With QIDO, the goal of achieving safer, more efficient, and lighter designs becomes within reach for companies in the aerospace and automotive industries.
List of references:
1. Zhu, Ji-Hong, Wei-Hong Zhang, and Liang Xia. “Topology optimization in aircraft and aerospace structures design.” Archives of computational methods in engineering 23 (2016): 595–622.
2. Luis Félix, Alexandra A. Gomes2, and Afzal Suleman. “Wing Topology Optimization with Self-Weight Loading” iWorld Congress on Structural and Multidisciplinary Optimization May19, -24, 2013, Orlando,Florida, USA.
3. Stanford, Bret, and Peter Ifju. “Multi-objective topology optimization of wing skeletons for aeroelastic membrane structures.” International Journal of Micro Air Vehicles 1.1 (2009): 51–69.
4. Høghøj, Lukas C., et al. “Simultaneous shape and topology optimization of wings.” Structural and Multidisciplinary Optimization 66.5 (2023): 116.
5. Gomes, Pedro, and Rafael Palacios. “Aerodynamic-driven topology optimization of compliant airfoils.” Structural and Multidisciplinary Optimization 62 (2020): 2117–2130.
6. James, Kai. Aerostructural shape and topology optimization of aircraft wings. University of Toronto (Canada), 2012.
There is vast opportunity for nanoscale innovation to transform the world in positive ways — expressed MIT.nano Director Vladimir Bulović as he posed two questions to attendees at the start of the inaugural Nano Summit: “Where are we heading? And what is the next big thing we can develop?”
“The answer to that puts into perspective our main purpose — and that is to change the world,” Bulović, the Fariborz Maseeh Professor of Emerging Technologies, told an audience of more than 325 in-person and 150 virtual participants gathered for an exploration of nano-related research at MIT and a celebration of MIT.nano’s fifth anniversary.
Over a decade ago, MIT embarked on a massive project for the ultra-small — building an advanced facility to support research at the nanoscale. Construction of MIT.nano in the heart of MIT’s campus, a process compared to assembling a ship in a bottle, began in 2015, and the facility launched in October 2018.
Fast forward five years: MIT.nano now contains nearly 170 tools and instruments serving more than 1,200 trained researchers. These individuals come from over 300 principal investigator labs, representing more than 50 MIT departments, labs, and centers. The facility also serves external users from industry, other academic institutions, and over 130 startup and multinational companies.
A cross section of these faculty and researchers joined industry partners and MIT community members to kick off the first Nano Summit, which is expected to become an annual flagship event for MIT.nano and its industry consortium. Held on Oct. 24, the inaugural conference was co-hosted by the MIT Industrial Liaison Program.
Six topical sessions highlighted recent developments in quantum science and engineering, materials, advanced electronics, energy, biology, and immersive data technology. The Nano Summit also featured startup ventures and an art exhibition.
Seeing and manipulating at the nanoscale — and beyond
“We need to develop new ways of building the next generation of materials,” said Frances Ross, the TDK Professor in Materials Science and Engineering (DMSE). “We need to use electron microscopy to help us understand not only what the structure is after it’s built, but how it came to be. I think the next few years in this piece of the nano realm are going to be really amazing.”
Speakers in the session “The Next Materials Revolution,” chaired by MIT.nano co-director for Characterization.nano and associate professor in DMSE James LeBeau, highlighted areas in which cutting-edge microscopy provides insights into the behavior of functional materials at the nanoscale, from anti-ferroelectrics to thin-film photovoltaics and 2D materials. They shared images and videos collected using the instruments in MIT.nano’s characterization suites, which were specifically designed and constructed to minimize mechanical-vibrational and electro-magnetic interference.
Later, in the “Biology and Human Health” session chaired by Boris Magasanik Professor of Biology Thomas Schwartz, biologists echoed the materials scientists, stressing the importance of the ultra-quiet, low-vibration environment in Characterization.nano to obtain high-resolution images of biological structures.
“Why is MIT.nano important for us?” asked Schwartz. “An important element of biology is to understand the structure of biology macromolecules. We want to get to an atomic resolution of these structures. CryoEM (cryo-electron microscopy) is an excellent method for this. In order to enable the resolution revolution, we had to get these instruments to MIT. For that, MIT.nano was fantastic.”
Seychelle Vos, the Robert A. Swanson (1969) Career Development Professor of Life Sciences, shared CryoEM images from her lab’s work, followed by biology Associate Professor Joey Davis who spoke about image processing. When asked about the next stage for CryoEM, Davis said he’s most excited about in-situ tomography, noting that there are new instruments being designed that will improve the current labor-intensive process.
To chart the future of energy, chemistry associate professor Yogi Surendranath is also using MIT.nano to see what is happening at the nanoscale in his research to use renewable electricity to change carbon dioxide into fuel.
“MIT.nano has played an immense role, not only in facilitating our ability to make nanostructures, but also to understand nanostructures through advanced imaging capabilities,” said Surendranath. “I see a lot of the future of MIT.nano around the question of how nanostructures evolve and change under the conditions that are relevant to their function. The tools at MIT.nano can help us sort that out.”
Tech transfer and quantum computing
The “Advanced Electronics” session chaired by Jesús del Alamo, the Donner Professor of Science in the Department of Electrical Engineering and Computer Science (EECS), brought together industry partners and MIT faculty for a panel discussion on the future of semiconductors and microelectronics. “Excellence in innovation is not enough, we also need to be excellent in transferring these to the marketplace,” said del Alamo. On this point, panelists spoke about strengthening the industry-university connection, as well as the importance of collaborative research environments and of access to advanced facilities, such as MIT.nano, for these environments to thrive.
The session came on the heels of a startup exhibit in which eleven START.nano companies presented their technologies in health, energy, climate, and virtual reality, among other topics. START.nano, MIT.nano’s hard-tech accelerator, provides participants use of MIT.nano’s facilities at a discounted rate and access to MIT’s startup ecosystem. The program aims to ease hard-tech startups’ transition from the lab to the marketplace, surviving common “valleys of death” as they move from idea to prototype to scaling up.
When asked about the state of quantum computing in the “Quantum Science and Engineering” session, physics professor Aram Harrow related his response to these startup challenges. “There are quite a few valleys to cross — there are the technical valleys, and then also the commercial valleys.” He spoke about scaling superconducting qubits and qubits made of suspended trapped ions, and the need for more scalable architectures, which we have the ingredients for, he said, but putting everything together is quite challenging.
Throughout the session, William Oliver, professor of physics and the Henry Ellis Warren (1894) Professor of Electrical Engineering and Computer Science, asked the panelists how MIT.nano can address challenges in assembly and scalability in quantum science.
“To harness the power of students to innovate, you really need to allow them to get their hands dirty, try new things, try all their crazy ideas, before this goes into a foundry-level process,” responded Kevin O’Brien, associate professor in EECS. “That’s what my group has been working on at MIT.nano, building these superconducting quantum processors using the state-of-the art fabrication techniques in MIT.nano.”
Connecting the digital to the physical
In his reflections on the semiconductor industry, Douglas Carlson, senior vice president for technology at MACOM, stressed connecting the digital world to real-world application. Later, in the “Immersive Data Technology” session, MIT.nano associate director Brian Anthony explained how, at the MIT.nano Immersion Lab, researchers are doing just that.
“We think about and facilitate work that has the human immersed between hardware, data, and experience,” said Anthony, principal research scientist in mechanical engineering. He spoke about using the capabilities of the Immersion Lab to apply immersive technologies to different areas — health, sports, performance, manufacturing, and education, among others. Speakers in this session gave specific examples in hardware, pediatric health, and opera.
Anthony connected this third pillar of MIT.nano to the fab and characterization facilities, highlighting how the Immersion Lab supports work conducted in other parts of the building. The Immersion Lab’s strength, he said, is taking novel work being developed inside MIT.nano and bringing it up to the human scale to think about applications and uses.
Artworks that are scientifically inspired
The Nano Summit closed with a reception at MIT.nano where guests could explore the facility and gaze through the cleanroom windows, where users were actively conducting research. Attendees were encouraged to visit an exhibition on MIT.nano’s first- and second-floor galleries featuring work by students from the MIT Program in Art, Culture, and Technology (ACT) who were invited to utilize MIT.nano’s tool sets and environments as inspiration for art.
In his closing remarks, Bulović reflected on the community of people who keep MIT.nano running and who are using the tools to advance their research. “Today we are celebrating the facility and all the work that has been done over the last five years to bring it to where it is today. It is there to function not just as a space, but as an essential part of MIT’s mission in research, innovation, and education. I hope that all of us here today take away a deep appreciation and admiration for those who are leading the journey into the nano age.”
MIT faculty and researchers participate in a panel discussion on quantum science and engineering. Left to right: Professor Aram Harrow, Professor Paola Cappellaro, Associate Professor Kevin O'Brien, Research Scientist Jeff Grover, and session chair Professor William Oliver.
The University of Tokyo (UTokyo) and IBM have launched Japan's first IBM Quantum System One, featuring a 127-qubit IBM Quantum Eagle processor. This is the first utility-scale processor in the region, defined by IBM as a quantum computer capable of exploring new scales of problems. The Quantum Innovation Initiative (QII) Consortium will use the system for quantum research in various fields including bioinformatics, high energy physics, materials science, and finance. UTokyo's Executive Vice President, Hiroaki Aihara, highlighted the potential of quantum computers to perform complex calculations beyond the capabilities of supercomputers.
In a recent speech, U.S. House Representative Jay Obernolte from California discussed the transformative potential of quantum computing (QC) in both the industrial and governmental sectors. He said that QC is not merely about faster processing but also about its unique capabilities to enhance various workflows and missions, especially within federal agencies.
Obernolte’s business career in technology began with the founding of FarSight Studios, a video game development company, in 1988. He established this company while still a student, and it has since become known for developing well-regarded games for various platforms. Obernolte’s role at FarSight demonstrates his entrepreneurial spirit and expertise in the tech industry, showcasing his ability to lead and innovate in a dynamic and competitive field. His success in the video game industry provided a strong foundation for his later efforts in public service and politics and is a clear reason — it seems — why he advocates a future that includes QC.
“Quantum Computing is going to be a revolutionary game changer in many areas of industry and also in government.”
— Jay Obernolte
Obernolte emphasized the significance of an amendment that instructs the National Science Technology Council Subcommittee on Quantum Information Science to initiate an outreach program for federal agencies. This program aims to help these agencies identify practical applications of quantum computing that can significantly enhance their operations. He clarified that this amendment does not entail additional funding or expand government mandates. Instead, it focuses on guiding federal agencies to recognize and utilize quantum computing’s potential based on the council’s recommendations.
Additionally, Obernolte expressed his support for a crucial part of the bill related to the development of quantum testbeds. He noted that the amendment introduces important changes to the grant program’s eligibility criteria. It limits the number of awardees to five, ensuring a minimum of $10 million available for each, which is crucial for the program’s efficacy. The amendment also encourages applications that include substantial cost-sharing, aligning with the principles of good governance and resource optimization. Lastly, he mentioned the establishment of a one-year timeframe to set up and operate the grant program, emphasizing efficiency and prompt implementation.
“[…] quantum computers are much more than just computers that run faster than traditional computers and it’s often not obvious to industry or particularly to federal agencies how quantum computing can be integrated into their workflows, and how it can be used to improve their missions. So, that’s why this amendment is so important. It requires the National Science Technology Council Subcommittee on Quantum Information Science to establish a programme of outreach to federal agencies to help them identify the use cases that quantum can help to solve meaningfully.”
Nov. 27, 2023 — French quantum computing company PASQAL announced it is part of the inauguration of Espace Quantique 1, a $90 million quantum initiative, in the center of the DistriQ Quantum Innovation Zone in Sherbrooke, Quebec, showcasing its approach to developing neutral atom quantum computers. The project aims to conduct manufacturing and commercialization activities […]
This edition of our weekly HPC News Bytes podcast, Shahin and Doug offer a quick (5:18) fly-over of recent news in the world of HPC-AI, including: NVIDIA's Ethernet offering, AWS's Research & Engineering Studio, an update on exascale in China, Riken's HPC+Quantum integration
OQC, a global leader in quantum compute-as-a-service, has announced the public availability of OQC Toshiko, the world's first enterprise-ready quantum computing platform. The 32-qubit platform is deployed to commercial data centres, allowing businesses worldwide to access the technology. SBI Investment, Japan's leading venture capital fund, is leading OQC's $100m funding round. The platform is named after Toshiko Yuasa, the first female Japanese physicist. OQC is collaborating with global companies including Equinix, NVIDIA, AWS and McKinsey to bring quantum computing out of the lab and into the enterprise.
The Quantum Application Lab (QAL) in Amsterdam has received a 1.2 million euro grant from the Amsterdam municipality. This funding will allow QAL to expand its operations and increase its activity in quantum computing application development. The grant follows a recent one from Quantum Delta NL, supported by the National Growth Fund. QAL will use the funds to hire new quantum innovation officers, a role crucial in translating academic knowledge into practical benefits. The QAL consortium includes the University of Amsterdam, Centrum Wiskunde & Informatica, SURF, the Netherlands eScience Centre, The Netherlands Organization for Applied Scientific Research, and Quantum Inspire.
Media and insiders report that Alibaba’s quantum laboratory has closed down.
Some reports suggest more than two dozen employees have been fired.
Many experts are speculating whether this move is a reaction to the company’s underlying financial woes, or a sign of weakness in the quantum industry as a whole.
Chinese media and anonymour industry insiders with connections to China are reporting that Alibaba’s quantum laboratory, which began with considerable fanfare about three years ago, has been closed down.
DoNews reported this week that Alibaba’s DAMO Academy –Academy for Discovery, Adventure, Momentum and Outlook — has closed down its quantum laboratory due to budget and profitability reasons. The budget ax claimed more than 30 people — possible among China’s brightest quantum researchers — lost their positions, according to the news outlet’s internal sources. For further claims of proof, DoNews reports that the official website of DAMO Academy has also removed the introduction page of the quantum laboratory.
According to the story, translated into English: “Insiders claimed that Alibaba’s DAMO Academy Quantum Laboratory had undergone significant layoffs, but it was not clear at that time whether the entire quantum computing team had been disbanded.”
Media further suggest that many of the DAMO Academy quantum team members who were laid off have begun to send their resumes to other companies.
According to The Quantum Insider’s China’s Quantum Computing Market brief, Alibaba is a diverse tech conglomerate that has been active in quantum since 2015. The company’s Quantum Lab Academy teaching employees and students about the prospects of quantum computing. Alibaba’s Quantum Laboratory is a full-stack R&D service offering an 11-qubit quantum cloud platform. According to some reports, Alibaba invested about $15 billion into emerging technologies such as quantum.
What’s not immediately clear is the scope of the closure. Industry experts wonder whether this is a sign that the move could portend a larger, if note global, quantum tech downturn. However, at least initial indicators suggest Alibaba’s move might be a necessary, but practical tactic to stem Alibaba’s shaky business position. Yahoo Finance reported that Alibaba’s stock crashed last week, losing $26 billion in valuation in just two days. The news may also be a sign of underlying weakness in China’s once bustling tech leadership.
What’s next for Alibaba’s once world-leading quantum ambition is unknown.
The media sources repot: “Although it is currently unclear whether Alibaba will continue to choose other teams to attempt quantum R&D in the future, this change still inevitably causes a sense of regret.”
The UK and the Republic of Korea have signed a series of science and tech deals, including commitments on AI, semiconductors, and space. The agreements were signed by UK Secretary of State Michelle Donelan, Korean Minister of Trade, Industry and Energy Bang Moon-kyu, and Minister of Science and ICT Lee Jong Ho. The deals include a £4.5 million fund for joint research and innovation partnerships. The two countries will co-host the next AI Safety Summit. The agreements also include a new Framework for Semiconductor Cooperation, a Digital Partnership, a Memorandum of Understanding on space cooperation, and a dialogue on quantum.
The Chicago Quantum Exchange (CQE), through its Open Quantum Initiative (OQI) Fellowship Program, in collaboration with the Argonne National Laboratory, recently facilitated a unique opportunity for undergraduate students. This summer, eight out of 18 OQI fellows participated in the program, contributing significantly to the Q-NEXT research and development, a project under the U.S. Department of Energy’s National Quantum Information Science Research Center led by Argonne.
These fellows, immersed in quantum science laboratories and research groups, experienced first-hand the dynamic world of quantum information science and engineering (QISE). For many, it was their inaugural foray into the realm of QISE, offering them a comprehensive understanding of the life and responsibilities of a scientist in a laboratory setting. They learned to actively participate in research groups and effectively communicate complex experimental results.
A highlight of the program was a visit to HRL Laboratories in California, coupled with a symposium where the fellows presented their research findings.
In a recent Q&A, these eight fellows shared their experiences and insights gained from investigating various aspects of quantum information science and engineering during their summer with the Q-NEXT program. This fellowship has been a crucial step in driving the advancement of technology using the properties of nature’s smallest particles.
Atlas Sébastien Bailly
Atlas Sébastien Bailly.
Home institution: Cornell University Major: Physics, mathematics OQI institution: Argonne National Laboratory Faculty mentor: Paul Kairys, postdoctoral appointee
Q: What was the focus of your OQI research this summer?
A: Autonomous characterization of nitrogen-vacancy centers in diamond. Initially, I worked on a computer model of the nitrogen-vacancy center, then used the model to explore optimal Bayesian experimentation.
Q: What was your role?
A: I was given a lot of freedom to explore my own ideas while working with my mentor on an existing project.
Q: What have you gained from the OQI experience?
A: By working with scientists and constantly being engaged with researchers or new startups through the OQI, I gained a lot of soft knowledge about QISE and science at large. Through my work, I built many practical skills and a foundational image of how science is done.
Q: What new perspectives do you have about QISE?
A: “Quantum stuff” has taken on an almost mythical/sci-fi aura in the public eye. This summer I learned that QISE is not composed of a top-secret Google basement but of a wide range of people with different technical goals and interests.
Q: What’s next for you?
A: I greatly enjoyed my work in QISE but feel that it would be premature to commit myself to any field. I want to explore more science and math and discover what else people are working on.
Q: What do you enjoy doing outside of research?
A: I’m an avid rock climber and outdoorsman, I love reading of all sorts, and in the past year I’ve rediscovered my passion for football (soccer).
Q: What advice do you have for other young people who are interested in pursuing a career in QISE?
A: Explore your interests before anything! The world is broad and QISE itself is unimaginably diverse.
Anais El Akkad
Anais El Akkad.
Home institution: Georgia Institute of Technology Major: Physics OQI institution: University of Illinois Urbana-Champaign Faculty mentor: Elizabeth Goldschmidt, assistant professor of atomic, molecular and optical physics
Q: What was the focus of your OQI research this summer?
A: My OQI research this summer focused on studying the phenomenon of superradiance in a rare-earth doped crystal, which has potential applications to the development of quantum memories.
Q: What was your role?
A: I mainly worked on the experimental set-up, gaining lots of hands-on experience with arranging and aligning optics, as well as learning how to operate the laser.
Q: What have you gained from the OQI experience?
A: So much! I think I learned more this past summer than I have in any class. Being able to do hands-on work and see how science is done has truly reaffirmed my passion for physics. I also think the community is phenomenal — everybody involved in OQI, including my labmates, my peer OQI fellows and everybody who worked tirelessly to ensure we had a good experience were incredibly supportive and friendly and really made me feel like I belong in QISE.
Q: What new perspectives do you have about QISE?
A: I’ve learned how diverse and interdisciplinary QISE is. There are so many people from all sorts of different backgrounds working on various problems in quantum information. It’s such a vast field — there are so many ways to be involved in quantum.
Q: What’s next for you?
A: After my undergrad, I hope to pursue graduate studies and further immerse myself in the exciting research within QISE.
Q: What do you enjoy doing outside of research?
A: I love reading, hiking, baking and playing piano.
Q: What advice do you have for other young people who are interested in pursuing a career in QISE?
A: Don’t be afraid to seek new opportunities! Even if you don’t feel qualified, take every chance you get to meet professionals in the field, gain some hands-on experience and just put yourself out there. I never would have expected to find myself working in a quantum optics lab, and I’m so grateful to the OQI program for this amazing opportunity.
Gabriel Gaeta
Gabriel Gaeta.
Home institution: San Jose State University Major: Physics OQI institution: Argonne National Laboratory Faculty mentor: Jiefei Zhang, applied physicist, assistant staff scientist
Q: What was the focus of your OQI research this summer?
A: My research was focused on the growth of single-crystal thin films doped with rare-earth spin qubits and characterizing those qubits in the crystals through optical measurements in order to find optimal coherence times for quantum memory applications. I was primarily focused on growing erbium in cerium dioxide that would be used as a memory qubit for a quantum network.
Q: What was your role?
A: My role was that of a student researcher — I was given a lot of freedom within the constraints of working within a group, and I was also offered the guidance needed to achieve my goals. My work consisted of material growth in which I formed thin-layer depositions of single-crystal cerium dioxide on a substrate surface. I also gathered data through optical measurements by shooting a laser at the grown film and looked at emission as a way of characterizing the quality of grown film.
Q: What have you gained from the OQI experience?
A: I have gained numerous skills from simply working in the lab through this summer. But something I gained that was invaluable was experiencing the dynamic of working in a research group. It gave me insight into what goes on behind the research as well as into the different types of roles you can have as a researcher.
Q: What new perspectives do you have about QISE?
A: It’s a field of science that is still young and has immense potential and implications in the future. Quantum computers, quantum sensing and quantum communication were all things that I had no idea were possible prior to my opportunity with OQI and the CQE.
Q: What’s next for you?
A: Continuing my undergraduate program at San Jose State and pursuing other research opportunities in the future. I always want to have a plan as to what I will do once I am done with my main goal, and after my bachelor’s degree, I would love to pursue graduate school.
Q: What do you enjoy doing outside of research?
A: I am an avid film and TV lover. I love being immersed in entire other worlds and storylines, especially films that simply explore the human experience and the difficulties that go along with that. My favorite genres consist of dramas, science fiction, thrillers and biopics.
Q: What advice do you have for other young people who are interested in pursuing a career in QISE?
A: Have an open mind and go for it! I love being receptive to new ideas, and quantum was one of those. I had no idea that I was going to enjoy quantum research as much as I did, but I tried it and got to experience a wonderful time with so many like-minded people. Don’t let your doubts hold you back!
Kenneth Muhammad
Kenneth Muhammad.
Home institution: Massachusetts Institute of Technology Major: Electrical science and engineering OQI institution: University of Illinois Urbana-Champaign Faculty mentor: Paul Kwiat, Sony Bardeen chair in physics and electrical and computer engineering
Q: What was the focus of your OQI research this summer?
A: Our goal was to implement an active stabilization scheme for a tabletop interferometer setup and photonic integrated chip setup for use in time-bin encoding of quantum information.
Q: What was your role?
A: I built a tabletop Michelson interferometer setup and programmed a microcontroller to actively control the position of a translation stage using a piezoelectric actuator. I wrote some accompanying code to easily modify the control parameters and calculate the optimal set point using Python. I spent time learning theory as well and used this knowledge to inform my design.
Q: What have you gained from the OQI experience?
A: I have gained practical experience building optical setups, programming microcontrollers and designing a system that is user-friendly. Perhaps the most useful experience I have received is working with other researchers in the lab and both communicating my ideas clearly and asking them the right questions so as to learn as much as possible. Working in the lab allowed me the unique opportunity to learn things like quantum information science alongside building a project that uses the same theory, and I don’t think I could have gotten that anywhere else.
Q: What new perspectives do you have about QISE?
A: I used to not think much of the quantum technologies of today due to their lack of tangible applications and my lack of knowledge on the subject. Now, I believe that QISE is a rapidly growing field and there are likely many applications that we haven’t thought of yet. I’m excited to see what new branches of technology emerge as this whole thing unfolds.
Q: What’s next for you?
A: I am interested in learning more about applications of quantum information science, so I will likely find myself working in a lab continuing research in something that combines electronics and quantum mechanics. I’m also hoping to use my math background to dive deeper into the potential of this field.
Q: What do you enjoy doing outside of research?
A: I mainly enjoy playing video games, reading books and going for walks in places I’ve never been.
Q: What advice do you have for other young people who are interested in pursuing a career in QISE?
A: Pursue what you enjoy and play to your strengths.
Natasha Ninan
Natasha Ninan.
Home institution: University of Akron Major: Electrical engineering OQI institution: University of Wisconsin–Madison Faculty mentor: Mikhail Kats, associate professor of electrical and computer engineering
Q: What was the focus of your OQI research this summer?
A: Our group is working on the design and fabrication of an optical bottle beam trap using a metasurface. Optical bottle beam traps are used to create optical tweezers for quantum devices such as atomic clocks or quantum computers. I worked on designing of the metasurface structure using the finite difference time domain (FDTD) method, which models the electrodynamics using Maxwell’s equations. Other group members are working on fabricating the resulting devices.
Q: What was your role?
A: The challenges in using scanning electron microscope imaging to assess the fabricated structure performance to the design necessitated the development of a simpler method to evaluate overall metasurface performance. I designed the witness sample metasurface that will be fabricated to easily evaluate the fabrication quality.
Q: What have you gained from the OQI experience?
A: Working in the Kats Research Group enabled me to learn more about optical trapping of atoms. In addition, I was able to learn how to design metasurfaces using FDTD and simulate possible fabrication error scenarios.
Q: What new perspectives do you have about QISE?
A: Being a part of Kats Research Group and the US Quantum Information Science School this summer has given me insight into different qubit creation methods. The various methods such as superconducting, trapped ions and photonic qubits present unique advantages. While these approaches have room for improvement, I expect the various qubit creation methods to become more application-specific.
Q: What’s next for you?
A: As a rising senior, I am working on applying for graduate school. This internship has given me the opportunity to explore my research interests. As I navigate the application process, I will be actively seeking projects in the fields of optical engineering, photonics and quantum sensing.
Q: What do you enjoy doing outside of research?
A: Traveling and hiking. When I’m not working on my coursework and research, I’m usually diving into researching new travel destinations and hiking adventures.
Q: What advice do you have for other young people who are interested in pursuing a career in QISE?
A: QISE is a multidisciplinary field. Having multiple opportunities in academia, industry and the national labs is very important to understand where you would like to contribute in QISE. In addition, it is equally as important to network and be open to hearing about the career paths of researchers in the field. This can provide valuable insights into your own path.
Peter Mugaba Noertoft
Peter Mugaba Noertoft.
Home institution: Stanford University Major: Electrical engineering OQI institution: University of Chicago Faculty mentor: David Awschalom, Liew Family professor of molecular engineering, UChicago; senior scientist, Argonne; director of the Chicago Quantum Exchange
Q: What was the focus of your OQI research this summer?
A: This summer I joined the quantum sensing efforts in the Awschalom group working on magnetometry with the nitrogen-vacancy center in diamond.
Q: What was your role?
A: My role was to establish scanning probe magnetic field sensing capabilities to be used for characterization of various quantum devices. The goal is to use information about distributions of magnetic fields to learn about relevant device physics. This involved building an optical setup for confocal microscopy and creating instrument control code to network the necessary lab equipment.
Q: What have you gained from the OQI experience?
A: Through the OQI experience, I’m excited to have gained a deeper insight into what it means to be a scientist working in a lab. I’ve also enjoyed getting to know all the other fellows, who share a strong interest in quantum science and engineering.
Q: What new perspectives do you have about QISE?
A: This summer I’ve learned about the sheer breadth of opportunities related to quantum science and engineering. It has been very inspiring to hear how the problems people choose to work on are often related to their unique backgrounds and interests.
Q: What’s next for you?
A: I’ve really enjoyed spending my summer in a research lab, gaining hands-on experience as a scientist and engineer. During the upcoming academic year, I’m excited to continue working on my research project at my home institution and thinking about what role I can play in the world of science long term.
Q: What do you enjoy doing outside of research?
A: I am an avid cyclist and love outdoor bike rides. I also enjoy playing recreational soccer and basketball.
Q: What advice do you have for other young people who are interested in pursuing a career in QISE?
A: I would encourage anyone with an interest in quantum science and engineering to consider a wide range of ways to get involved. Doing is an excellent way of learning!
Rachelle Rosiles
Rachelle Rosiles.
Home Institution: Illinois Institute of Technology Major: Physics OQI Institution: Argonne National Laboratory Faculty Mentor: Nazar Delegan, assistant scientist
Q: What was the focus of your OQI research this summer?
A: The group I worked with this summer conducted experiments on the growth and characterization of nitrogen-vacancy centers in diamonds for quantum sensing on the diamond surface. I was particularly involved in the process of optically addressing and manipulating the qubit.
Q: What was your role?
A: For my role, I adapted the control software, nspyre, to integrate new optical devices and create more self-driven experiments.
Q: What have you gained from the OQI experience?
A: I gained perspective on different opportunities in quantum science in both industry and academia. The connections I made have been extremely rewarding by exposing me to new fields and opening up opportunities for me.
Q: What new perspectives do you have about QISE?
A: I see now that industry and academia are not mutually exclusive. Plenty of startups have spawned from research groups and have backgrounds in academia, while industries in quantum science rely heavily on people who can conduct research on the product they’re developing. I’ve also come to realize that there is a lot of investment and momentum in this field, so I know it is a great time to be getting in.
Q: What’s next for you?
A: I’m looking to continue my work in research as I figure out if graduate school is the path for me. There are some researchers I’m interested in working with next summer in quantum computing.
Q: What do you enjoy doing outside of research?
A: I enjoy caring for my plants, watching them grow and shaping the bonsai I have.
Q: What advice do you have for other young people who are interested in pursuing a career in QISE?
A: I would say that now is the perfect time to do so, whether your interest lies in the science, organization or the business side. There’s plenty of work to do, and many people are willing to talk and advise on how to get into the field, whether through the OQI fellowship or other means. Don’t let the word “quantum” intimidate because it is really not that inaccessible.
Rain Wang
Rain Wang.
Home institution: Harvard University Major: Physics OQI institution: Argonne National Laboratory Faculty mentor: F. Joseph Heremans, staff scientist, Argonne; affiliated scientist at the Pritzker School of Molecular Engineering at the University of Chicago
Q: What was the focus of your OQI research this summer?
A: Both projects that I worked on aimed toward realizing real-world quantum networking. In quantum networking, like any network, you have nodes, and you have connections that are essential to the network’s function. This summer, my main project optimized the connections in the Chicago Quantum Network, while my second project delved into characterizing a potential node for quantum communication.
Q: What was your role?
A: For my main project, I performed various analysis techniques to characterize the polarization drift in the fibers and eventually implement a protocol that would correct this drift (later phase as well). This was important for retaining information and clear communication. In my second project, I designed, optimized and built an optical/modulator setup that would enable the characterization of vanadium spin-defects in silicon carbide so that we can further understand its properties and potential for quantum communication.
Q: What have you gained from the OQI experience?
A: I am extremely grateful for the wealth of knowledge, relationships and resources that I have gained from the OQI experience. I had never been able to explore quantum this deeply prior to OQI, and this time has invigorated my curiosity and motivation to pursue such a new and exciting field through different avenues.
Q: What new perspectives do you have about QISE?
A: There is so much more opportunity in this field than I think I previously understood. There are research, entrepreneurial and communications opportunities — and more. Further, while current industry eyes are mostly on quantum computing, this experience has led to my developing interest in quantum sensing and communication. I’m excited to explore.
Q: What’s next for you?
A: I’m curious to explore the different sides of quantum beyond research. Quantum is such an interdisciplinary field — I want to see all its potential. While I love science, I am curious about industry-side roles and how to facilitate this science becoming accessible to the public. In summary: I’m not sure, but I am looking forward to finding out!
Q: What do you enjoy doing outside of research?
A: On campus, I am involved in activities from our Asian American Dance Troupe to Tech for Social Good club. I am very passionate about accessible education and empowering underrepresented people in STEM. I involve myself in mentorship programs and affinity groups that realize those goals. I also love to cook, bake, exercise and paint with friends and family.
Q: What advice do you have for other young people who are interested in pursuing a career in QISE?
A: It’s never too early to discover your passions! There are so many available opportunities and resources to start investigating quantum at any age, you just have to look (OQI is an amazing example). It can be extremely daunting, but you can take that first step. Don’t be afraid to reach out to people; people are always happy to help.
The experience of participating in the Open Quantum Initiative (OQI) Fellowship Program reaffirmed the above students’ passion for physics and science, broadening their perspectives and opening up new academic and career possibilities in QISE. Many expressed a desire to continue exploring this field through further studies and research, demonstrating the program’s success in inspiring the next generation of quantum scientists and engineers.
Funding was provided by the University of Chicago, The U.S. Department of Energy Office of Technology Transitions and Q-NEXT, the Illinois Quantum Information Science and Technology Center at the University of Illinois Urbana-Champaign, HQAN at the University of Wisconsin–Madison, the Ohio State University, Gordon and Betty Moore Foundation, and UChicago’s Inclusive Innovation in the Sciences Fund.
Scientists at the University of Bristol, led by Professor Nigel Hussey, have discovered a rare phenomenon in purple bronze, a unique one-dimensional metal, that could be key to creating a 'perfect switch' in quantum devices. The material can flip between being an insulator and a superconductor, a versatility known as 'emergent symmetry'. This could offer an ideal On/Off switch in future quantum technology. The research, which began 13 years ago, was published in Science. The team included Dr Piotr Chudzinski, now a Research Fellow at Queen’s University Belfast, and PhD students Xiaofeng Xu, Nick Wakeham, and Maarten Berben.
A universal quantum computer, capable of executing any quantum operation, has vast potential applications in the real world, extending beyond specific uses like solving optimization problems.
In 2022, Fellner and Messinger — along with physicists Kilian Ender and Wolfgang Lechner — unveiled a new universal gate set for quantum computers. This development, rooted in the ParityQC Architecture, boasts all-to-all connectivity and inherent error correction capabilities. Their research, titled “Universal Parity Quantum Computing,” was published in the journal Physical Review Letters.
In the short video, Fellner and Messinger describe how the essence of their work revolves around the Parity Code, which doubles as a stabilizer code defined by specific parity constraints. They explain how the product of the eigenvalues of two qubits correlates with the eigenvalue of a third qubit, illustrating a fundamental aspect of their approach. This relationship is central to their definition of ‘parity qubits,’ where one qubit represents the parity of others.
In terms of quantum operations, their methodology facilitates the implementation of certain multi-qubit interactions. For example, they can easily execute operations like the RS ad set gate through simple local operations on parity qubits. However, they acknowledge the complexity of implementing other interactions within this framework.
To address these challenges, they’ve devised a strategy that combines direct single qubit interactions with more complex ones enabled by the Parity encoding. This innovative approach involves alternating between blocks of gates within the Parity encoding and others applied directly to the qubits. Remarkably, they’ve developed a method that allows this interchange with only a constant time overhead, leveraging measurements and classical information processing akin to quantum teleportation.
Their approach is reminiscent of quantum repeaters, where a sequence of local entangling gates and measurements can generate long-range entanglement. They’ve applied this method to execute the quantum approximate optimization algorithm (QAOA) in constant time, independent of system size, a significant step towards realizing quantum advantage with imminent quantum devices.
This development by Keller, Messinger, and the team at ParityQC represents a pivotal advancement in quantum computing. The potential of this technology is immense, and its future applications are eagerly anticipated.
Researchers at Texas A&M University utilized quantum computing to map gene regulatory networks (GRNs), revealing new gene relationships previously undetectable with traditional computing methods, which could significantly impact both animal and human medicine.
Quantum computing allowed for more complex analysis of gene interactions, overcoming limitations of older technologies that could only compare two genes at a time, thus providing a more complete picture of how genes influence each other.
The study, part of a new and rapidly developing field, involved both biomedical scientists and engineers, and future plans include comparing healthy cells with those affected by diseases or mutations to understand the impact of these changes on gene states and expressions.
UNIVERSITY RESEARCH NEWS — Colleg Station, Texas/November 20, 2023 — In a new multidisciplinary study, researchers at Texas A&M University showed how quantum computing — a new kind of computing that can process additional types of data — can assist with genetic research and used it to discover new links between genes that scientists were previously unable to detect.
Their project used the new computing technology to map gene regulatory networks (GRNs), which provide information about how genes can cause each other to activate or deactivate.
As the team published in npj Quantum Information, quantum computing will help scientists more accurately predict relationships between genes, which could have huge implications for both animal and human medicine.
“The GRN is like a map that tells us how genes affect each other,” Cai said. “For example, if one gene switches on or off, then it may change another gene that could change three, or five, or 20 more genes down the line.
“Because our quantum computing GRNs are constructed in ways that allow us to capture more complex relationships between genes than traditional computing, we found some links between genes that people hadn’t known about previously,” he said. “Some researchers who specialize in the type of cells we studied read our paper and realized that our predictions using quantum computing fit their expectations better than the traditional model.”
The ability to know which genes will affect other genes is crucial for scientists looking for ways to stop harmful cellular processes or promote helpful ones.
“If you can predict gene expression through the GRN and understand how those changes translate to the state of the cells, you might be able to control certain outcomes,” Cai said. “For example, changing how one gene is expressed could end up inhibiting the growth of cancer cells.”
Members of the Cai Lab (l-r): master’s student Victoria Gatlin, doctoral student Shreyan Gupta, doctoral student Cristhian Roman Vicharra, postdoctoral researcher Dr. Selim Romero Gonzalez, Dr. James Cai, doctoral student Qian Xu, and master’s student Amy Barrett.
Texas A&M University School of Veterinary Medicine and Biomedical Sciences
Making The Most Of A New Technology
With quantum computing, Cai and his team are overcoming the limitations of older computing technologies used to map GRNs.
“Prior to using quantum computing, the algorithms could only handle comparing two genes at a time,” Cai said.
Cai explained that only comparing genes in pairs could result in misleading conclusions, since genes may operate in more complex relationships. For example, if gene A activates and so does gene B, it doesn’t always mean that gene A is responsible for gene B’s change. In fact, it could be gene C changing both genes.
“With traditional computing, data is processed in bits, which only have two states — on and off, or 1 and 0,” Cai said. “But with quantum computing, you can have a state called the superposition that’s both on and off simultaneously. That gives us a new kind of bit — the quantum bit, or qubit.
“Because of superposition, I can simulate both the active and inactive states for a gene in the GRN, as well as this single gene’s impact on other genes,” he said. “You end up with a more complete picture of how genes influence each other.”
Taking The Next Step
While Cai and his team have worked hard to show that quantum computing is helpful to the biomedical field, there’s still a lot of work to be done.
“It’s a very new field,” Cai said. “Most people working in quantum computing have a physics background. And people on the biology side don’t usually understand how quantum computing works. You really have to be able to understand both sides.”
That’s why the research team includes both biomedical scientists and engineers like Cai’s Ph.D. student Cristhian Roman Vicharra, who is a key member of the research team and spearheaded the study behind the recent publication.
“In the future, we plan to compare the healthy cells to ones with diseases or mutations,” Cai said. “We hope to see how a mutation might affect genes’ states, expression, frequencies, etc.”
For now, it’s important to get as clear an understanding as possible of how healthy cells work before comparing them to mutated or diseased cells.
“The first step was to predict this baseline model and see whether the network we mapped made sense,” Cai said. “Now, we can keep going from there.”
Written by Courtney Price, Texas A&M University School of Veterinary Medicine and Biomedical Sciences
Featured image: (l-r) Professor James Cai and Ph.D. student Cristhian Roman Vicharra. Credit: Texas A&M University School of Veterinary Medicine and Biomedical Sciences
IBM Quantum and UC Berkeley researchers have published a paper in Nature demonstrating the utility of quantum computing. Quantum utility refers to a quantum computer's ability to perform reliable computations beyond the capabilities of classical computing methods. This marks a significant milestone in the field, as quantum computers were previously small, experimental devices used primarily for studying quantum computing. IBM's Quantum Theory and Computational Science director, Katie Pizzolato, and Quantum Theory and Capabilities senior manager, Sarah Sheldon, emphasise the potential of quantum computers as tools for scientific exploration.
Quantum software company Classiq, in collaboration with NVIDIA and the Tel Aviv Sourasky Medical Center, has launched the Quantum Computing for Life Sciences & Healthcare Center. The initiative aims to develop quantum algorithms and applications to revolutionise life sciences and healthcare, including drug discovery, molecular analysis, and personalised medical treatments. The centre will also address challenges in supply chain and treatment coordination. Classiq CEO Nir Minerbi believes the software driving quantum computing is growing rapidly. The centre will utilise NVIDIAH100 Tensor Core GPU capabilities and NVIDIA CUDA Quantum programming platform. The Tel Aviv Sourasky Medical Center will initiate the centre's collaborative approach.
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