Reaction: Can We Grow a Quantum Processor?

Alexei Marchenkov is an experimental physicist who has devoted most of his research career to studying quantum phenomena in materials and structures at cryogenic temperatures, including graphene, atomic-sized wires and contacts, and superconducting quantum bits and circuits. He is a former associate professor at the Georgia Institute of Technology and founder and chief executive officer of the Bleximo Corp., a startup developing application-specific superconducting quantum computers. Alexei Marchenkov is an experimental physicist who has devoted most of his research career to studying quantum phenomena in materials and structures at cryogenic temperatures, including graphene, atomic-sized wires and contacts, and superconducting quantum bits and circuits. He is a former associate professor at the Georgia Institute of Technology and founder and chief executive officer of the Bleximo Corp., a startup developing application-specific superconducting quantum computers. Quantum information science (QIS) is a surprisingly mature field: the use of quantum-mechanical phenomena such as superposition and entanglement for computation purposes was proposed in the early 1980s, around the same time that the first personal computers appeared. The following decades saw the development of a large number of special quantum algorithms that demonstrate quantum computers’ potential to outperform conventional digital supercomputers in a large spectrum of simulation, optimization, and machine-learning problems. They can even tackle problems that cannot be solved on digital computers of any conceivable size.1Montanaro A. Quantum algorithms: an overview.npj Quantum Inf. 2016; 2: 15023Crossref Scopus (333) Google Scholar In theoretical QIS, quantum processors are constructed from “ideal” quantum bits (“qubits”), which are just two-level noise-resistant quantum systems that can be controlled and measured with very high accuracy. In 2000, theoretical physicist David DiVincenzo established the seven criteria necessary for building a practical quantum computing or communication system.2DiVincenzo D.P. The physical implementation of quantum computation.Fortschr. Phys. 2000; 48: 771-783Crossref Scopus (1456) Google Scholar The first five are essential for computing. Paraphrased from his article, they are as follows:1.A scalable physical system with well-characterized qubits. A single working qubit is not enough; the ability to reproducibly manufacture a large number of them is needed. Practical algorithms require thousands or even millions of qubits.2.The ability to initialize the state of the qubits to a simple fiducial state. This is the equivalent of a reset button for a quantum processor given that running any algorithm requires the ability to initialize the system into a well-defined and determinate initial state.3.Long relevant decoherence times. If qubits in a processor are not sufficiently stable, a computation with them cannot be completed.4.A “universal” set of quantum gates. One must be able to rotate a single qubit to anywhere on the Bloch sphere (i.e., perform single-qubit gates) and perform some two-qubit gates that entangle qubits. With these capabilities, it is possible to execute any quantum algorithm.5.A qubit-specific measurement capability. If results cannot be read, a computer is useless. In practice, it is very difficult to read out the qubit state with high accuracy. The remaining two are known as DiVincenzo’s quantum communication criteria and are related to the ability to faithfully transfer quantum data over long distances. Today’s superconducting and trapped-ion quantum processors, the two leading qubit modalities, have a few tens of qubits, but they are beset by coherence-destroying noise. This noise comes not only from the environment but also from parasitic cross-talk between qubits, as well as other numerous sources stemming from how qubits are made, connected together, controlled, and measured. This level of technology is referred to as noisy intermediate-scale quantum (NISQ),3Preskill J. Quantum computing in the NISQ era and beyond.Quantum. 2018; 2: 79Crossref Scopus (2217) Google Scholar and assessing the state of the art of existing modalities is an exercise in hitting a fast-moving target. Academic groups and commercial enterprises are trying to find ways for these imperfect computers with several tens or potentially hundreds of qubits to perform tasks that surpass the capabilities of today’s digital supercomputers4Arute F. Arya K. Babbush R. Bacon D. Bardin J.C. Barends R. Biswas R. Boixo S. Brandao F.G.S.L. Buell D.A. et al.Quantum supremacy using a programmable superconducting processor.Nature. 2019; 574: 505-510Crossref PubMed Scopus (2792) Google Scholar while simultaneously improving qubits, trying different processor architectures, and honing the ability to precisely control and measure a large number of qubits. The Catalysis article by Liu and Toma5Liu Y. Toma F.M. Catalyst: qubits from the bottom up.Chem. 2020; 6: 795-798Abstract Full Text Full Text PDF Scopus (8) Google Scholar first reviews the state of the art for an emergent qubit modality called molecular electron-spin qubits. An apparent advantage of molecules is that molecular electron-spin qubits can potentially be assembled with great control into 2D and 3D arrays through the flexibility of supramolecular chemistry. The qubits’ individual properties and qubit-qubit couplings can also be tuned, thus promising great flexibility in building processors with various architectures and high direct qubit-qubit connectivity. The latter is important for efficiently running many quantum algorithms. The authors then outline the key research directions, in which they particularly emphasize engineering longer coherence times through structural tuning and studying structure-coherence relationships while extending the research to solid-state qubit arrays and developing methods for their precision manufacturing and characterization. Cited experimental demonstrations give evidence that all five of DiVincenzo’s criteria can potentially be satisfied. However, it is important to note that these criteria are necessary, but not sufficient, for building a useful quantum computer in the NISQ era and beyond. First, it must be emphasized that qubits’ coherence times by themselves are not the most important parameters for a useful quantum computer because these times can be vastly different for different modalities (e.g., ~100 microseconds in superconducting qubits versus tens of seconds in trapped ions). An equally important characteristic is how fast single- and two-qubit gates can be executed given that the number of computational operations achievable in a coherence-limited NISQ processor depends on the ratios of the coherence time and the gate execution times. In particular, coherence times must be much longer than the gate times for a processor to be able to complete a useful calculation. From this writer’s perspective, efforts to implement fast gates are as important as efforts to prolong coherence times. Second, the ability to control and read out individual qubits without affecting other qubits in arrays must be addressed very early on. Parasitic cross-talk can kill the overall performance of quantum processors because it becomes impossible to execute gates on different qubits in parallel. Third, limits on scalability of a full-stack quantum computer should be assessed as soon as possible. A scalable quantum computer is one where the number of qubits can be increased on demand without a loss in performance (i.e., the computer retains coherence times and high-fidelity gates while maintaining full control of the processor) and without an incommensurate increase in cost, energy usage, or size. QIS is in rapid growth mode and has an even more exciting time ahead. Today, one can already access cloud-deployed NISQ computers with tens of qubits for hands-on experimentation. Whether more advanced versions of these computers can beat supercomputers in efficiently solving high-value research and business problems remains to be seen. The winning qubit modality, if there is a single one, is still far from certain. It is quite possible that different modalities could be more suitable for different types of computation. Only experiments can show whether molecular electron-spin qubits will be one of the best elementary blocks for building practical quantum computers. There is no obvious reason why they cannot be. Reaction: Molecular Spins as QubitsFloriana TunaChemApril 09, 2020In BriefQuantum computation operates with qubits rather than bits to assure ultra-fast calculations that are otherwise unreachable. Chemistry in particular offers immense opportunities for qubit design and scalability. Examples of molecular qubits with long memory times have already been demonstrated, and their properties can be further improved with chemical tools. These qubits are versatile, easily replicated, and capable of forming multiqubit gates that execute calculation tasks. Pulse EPR experiments have also been developed to enable coherent qubit manipulations and measurement of qubit-qubit interactions. Full-Text PDF Open ArchiveCatalyst: Qubits from the Bottom UpLiu et al.ChemApril 09, 2020In BriefThe need for long coherence and quantum entanglement in quantum information science requires a cross-disciplinary taskforce with physicists, engineers, materials scientists, and chemists for the discovery of novel quantum materials. In this space, molecular electron-spin qubits and multielectron-spin systems offer an unprecedented opportunity to precisely build qubit arrays from the bottom up. Full-Text PDF Open Archive