Large-scale Quantum Computers Research Articles

Microwave Superconductivity

We give a broad overview of the history of microwave superconductivity and explore the technological developments that have followed from the unique electrodynamic properties of superconductors. Their low loss properties enable resonators with high quality factors that can nevertheless handle extremely high current densities. This in turn enables superconducting particle accelerators, high-performance filters and analog electronics, including metamaterials, with extreme performance. The macroscopic quantum properties have enabled new generations of ultra-high-speed digital computing and extraordinarily sensitive detectors. The microscopic quantum properties have enabled large-scale quantum computers, which at their heart are essentially microwave-fueled quantum engines. We celebrate the rich history of microwave superconductivity and look to the promising future of this exciting branch of microwave technology.

A proposal for preparation of cluster states with linear optics* *Project supported by the National Natural Science Foundation of China (Grant Nos. 12025401 and U1930402).

Measurement-based quantum computation in an optical setup shows great promise towards the implementation of large-scale quantum computation. The difficulty of measurement-based quantum computation lies in the preparation of cluster state. In this paper, we propose the method of generating the large-scale cluster state, which is a platform for measurement-based quantum computation. In order to achieve more complex quantum circuits, the preparation protocol of N-photon cluster state will be proposed as a generalization of the preparation of four- and five-photon cluster states. Furthermore, our proposal is experimentally feasible.

Reinforcement learning decoders for fault-tolerant quantum computation

Topological error correcting codes, and particularly the surface code, currently provide the most feasible road-map towards large-scale fault-tolerant quantum computation. As such, obtaining fast and flexible decoding algorithms for these codes, within the experimentally realistic and challenging context of faulty syndrome measurements, without requiring any final read-out of the physical qubits, is of critical importance. In this work, we show that the problem of decoding such codes can be naturally reformulated as a process of repeated interactions between a decoding agent and a code environment, to which the machinery of reinforcement learning can be applied to obtain decoding agents. While in principle this framework can be instantiated with environments modelling circuit level noise, we take a first step towards this goal by using deepQ learning to obtain decoding agents for a variety of simplified phenomenological noise models, which yield faulty syndrome measurements without including the propagation of errors which arise in full circuit level noise models.

Gauss’s law, duality, and the Hamiltonian formulation of U(1) lattice gauge theory

Quantum computers have the potential to explore the vast Hilbert space of entangled states that play an important role in the behavior of strongly interacting matter. This opportunity motivates reconsidering the Hamiltonian formulation of gauge theories, with a suitable truncation scheme to render the Hilbert space finite-dimensional. Conventional formulations lead to a Hilbert space largely spanned by unphysical states; given the current inability to perform large scale quantum computations, we examine here how one might restrict wave function evolution entirely or mostly to the physical subspace. We consider such constructions for the simplest of these theories containing dynamical gauge bosons -- U(1) lattice gauge theory without matter in $d=2,3$ spatial dimensions -- and find that electric-magnetic duality naturally plays an important role. We conclude that this approach is likely to significantly reduce computational overhead in $d=2$ by a reduction of variables and by allowing one to regulate magnetic fluctuations instead of electric. The former advantage does not exist in $d=3$, but the latter might be important for asymptotically-free gauge theories.

Effective Compression of Quantum Braided Circuits Aided by ZX-Calculus

Mapping a quantum algorithm to any practical large-scale quantum computer will require a sequence of compilations and optimizations. At the level of fault-tolerant encoding, one likely requirement of this process is the translation into a topological circuit, for which braided circuits represent one candidate model. Given the large overhead associated with encoded circuits, it is paramount to reduce their size in terms of computation time and qubit number through circuit compression. While these optimizations have typically been performed in the language of three-dimensional diagrams, such a representation does not allow an efficient, general, and scalable approach to reduction or verification. We propose the use of the ZX-calculus as an intermediate language for braided circuit compression, demonstrating advantage by comparing results using this approach with those previously obtained for the compression of A- and Y-state distillation circuits. We then provide a benchmark of our method against a small set of Clifford+T circuits, yielding compression percentages of 77%. Our results suggest that the overheads of braided, defect-based circuits are comparable to those of their lattice-surgery counterparts, restoring the potential of this model for surface-code quantum computation.

Experimental pairwise entanglement estimation for an N-qubit system

Designing and implementing algorithms for medium- and large-scale quantum computers is not easy. In the previous work, we have suggested, and developed, the idea of using machine learning techniques to train a quantum system such that the desired process is “learned,” thus obviating the algorithm design difficulty. This works quite well for small systems. But the goal is macroscopic physical computation. Here, we implement our learned pairwise entanglement witness on Microsoft’s Q#, one of the commercially available gate model quantum computer simulators; we perform statistical analysis to determine reliability and reproducibility; and we show that after training the system in stages for an incrementing number of qubits (2, 3, 4, ...) we can infer the pattern for mesoscopic N from simulation results for three-, four-, five-, six-, and seven-qubit systems. Our results suggest a fruitful pathway for general quantum computer algorithm design and for practical computation on noisy intermediate-scale quantum devices.

Decoherence dynamics of entangled quantum states in the XXX central spin model

Maintaining coherence of a qubit is of vital importance for realizing a large-scale quantum computer in practice. In this work, we study the central spin decoherence problem in the XXX central spin model (CSM) and focus on the quantum states with different initial entanglement, namely intra-bath entanglement or system–bath entanglement. We analytically obtain their evolutions of fidelity, entanglement, and quantum coherence. When the initial bath spins constitute an N-particle entangled state (the Greenberger–Horne–Zeilinger-bath or the W-bath), the leading amplitudes of their fidelity evolutions both scale as $$\mathscr {O}(1/N)$$ , which is the same as the case of a fully polarized bath. However, when the central spin is maximally entangled with one of the bath spins, the amplitude scaling of its fidelity evolution declines from $$\mathscr {O}(1/N)$$ to $$\mathscr {O}(1/N^2)$$ . That implies appropriate initial system–bath entanglement is contributive to suppress central spin decoherence. In addition, with the help of system–bath entanglement, we realize quantum coherence-enhanced dynamics for the central spin where the consumption of bath entanglement is shown to play a central role.

Architecture and noise analysis of continuous-variable quantum gates using two-dimensional cluster states

Due to its unique scalability potential, continuous variable quantum optics is a promising platform for large scale quantum computing. In particular, very large cluster states with a two-dimensional topology that are suitable for universal quantum computing and quantum simulation can be readily generated in a deterministic manner, and routes towards fault-tolerance via bosonic quantum error-correction are known. In this article we propose a complete measurement-based quantum computing architecture for the implementation of a universal set of gates on the recently generated two-dimensional cluster states [1,2]. We analyze the performance of the various quantum gates that are executed in these cluster states as well as in other two-dimensional cluster states (the bilayer-square lattice and quad-rail lattice cluster states [3,4]) by estimating and minimizing the associated stochastic noise addition as well as the resulting gate error probability. We compare the four different states and find that, although they all allow for universal computation, the quad-rail lattice cluster state performs better than the other three states which all exhibit similar performance.

Efficient-sideband-cooling protocol for long trapped-ion chains

Trapped ions are a promising candidate for large scale quantum computation. Several systems have been built in both academic and industrial settings to implement modestly-sized quantum algorithms. Efficient cooling of the motional degrees of freedom is a key requirement for high-fidelity quantum operations using trapped ions. Here, we present a technique whereby individual ions are used to cool individual motional modes in parallel, reducing the time required to bring an ion chain to its motional ground state. We demonstrate this technique experimentally and develop a model to understand the efficiency of our parallel sideband cooling technique compared to more traditional methods. This technique is applicable to any system using resolved sideband cooling of co-trapped atomic species and only requires individual addressing of the trapped particles.

Spin Quintet in a Silicon Double Quantum Dot: Spin Blockade and Relaxation

Spins in gate-defined silicon quantum dots are promising candidates for implementing large-scale quantum computing. To read the spin state of these qubits, the mechanism that has provided the highest fidelity is spin-to-charge conversion via singlet-triplet spin blockade, which can be detected in-situ using gate-based dispersive sensing. In systems with a complex energy spectrum, like silicon quantum dots, accurately identifying when singlet-triplet blockade occurs is hence of major importance for scalable qubit readout. In this work, we present a description of spin blockade physics in a tunnel-coupled silicon double quantum dot defined in the corners of a split-gate transistor. Using gate-based magnetospectroscopy, we report successive steps of spin blockade and spin blockade lifting involving spin states with total spin angular momentum up to $S=3$. More particularly, we report the formation of a hybridized spin quintet state and show triplet-quintet and quintet-septet spin blockade. This enables studies of the quintet relaxation dynamics from which we find $T_1 \sim 4 ~\mu s$. Finally, we develop a quantum capacitance model that can be applied generally to reconstruct the energy spectrum of a double quantum dot including the spin-dependent tunnel couplings and the energy splitting between different spin manifolds. Our results open for the possibility of using Si CMOS quantum dots as a tuneable platform for studying high-spin systems.

A Scalable Cryo-CMOS Controller for the Wideband Frequency-Multiplexed Control of Spin Qubits and Transmons

Building a large-scale quantum computer requires the co-optimization of both the quantum bits (qubits) and their control electronics. By operating the CMOS control circuits at cryogenic temperatures (cryo-CMOS), and hence in close proximity to the cryogenic solid-state qubits, a compact quantum-computing system can be achieved, thus promising scalability to the large number of qubits required in a practical application. This work presents a cryo-CMOS microwave signal generator for frequency-multiplexed control of 4 × 32 qubits (32 qubits per RF output). A digitally intensive architecture offering full programmability of phase, amplitude, and frequency of the output microwave pulses and a wideband RF front end operating from 2 to 20 GHz allow targeting both spin qubits and transmons. The controller comprises a qubit-phase-tracking direct digital synthesis (DDS) back end for coherent qubit control and a single-sideband (SSB) RF front end optimized for minimum leakage between the qubit channels. Fabricated in Intel 22-nm FinFET technology, it achieves a 48-dB SNR and 45-dB spurious-free dynamic range (SFDR) in a 1-GHz data bandwidth when operating at 3 K, thus enabling high-fidelity qubit control. By exploiting the on-chip 4096-instruction memory, the capability to translate quantum algorithms to microwave signals has been demonstrated by coherently controlling a spin qubit at both 14 and 18 GHz.

A dynamic programming approach for distributing quantum circuits by bipartite graphs

There are many challenges involved in building near-term large-scale quantum computers. Some of these challenges can be overcome by partitioning a quantum circuit into smaller parts and allowing each part to be executed on a smaller quantum unit. This approach is known as distributed quantum computation. In this study, a dynamic programming algorithm is proposed to minimize the number of communications in a distributed quantum circuit. This algorithm consists of two steps: first, the quantum circuit is converted into a bipartite graph model, and then a dynamic programming approach is proposed to partition the model into low-capacity quantum circuits. The proposed approach is evaluated on some benchmark quantum circuits, and a remarkable reduction in the number of required teleportations is obtained.

Speedup of Grover’s search algorithm and closed timelike curves

The quadratic reduction of query complexity of Grover’s search algorithm (GA), while significant, would not be enough to enjoy exponentially fast data searching in large-scale quantum computation. One of the ways to enhance the speedup in the framework of Grover’s algorithm is to employ a novel quantum operation, i.e., inversion against an unknown state; however, this is not possible at least in quantum theory. We thus extend the Grover algorithm assisted by closed timelike curves (CTCs), in which the unknown-state inversion is achievable by combining the superposition of two unknown states with cloning. We dubbed this refined algorithm CTC-assisted Grover algorithm (CTC-GA). We show that the CTC-GA can vastly reduce the query complexity compared to the original algorithm; remarkably, from polynomial to poly-logarithmic. These results will provide a broader intuition for exponential quantum speedup of data searching problems.

Designing a DDS-Based SoC for High-Fidelity Multi-Qubit Control

The design of a large-scale quantum computer requires co-optimization of both the quantum bits (qubits) and their control electronics. This work presents the first systematic design of such a controller to simultaneously and accurately manipulate the states of multiple spin qubits or transmons. By employing both analytical and simulation techniques, the detailed electrical specifications of the controller have been derived for a single-qubit gate fidelity of 99.99% and validated using a qubit Hamiltonian simulator. Trade-offs between several architectures with different levels of digitization are discussed, resulting in the selection of a highly digital DDS-based solution. Initiating from the system specifications, a complete error budget for the various analog and digital circuit blocks is drafted and their detailed electrical specifications, such as signal power, linearity, spurs and noise, are derived to obtain a digital-intensive power-optimized multi-qubit controller. A power consumption estimate demonstrates the feasibility of such a system in a nanometer CMOS technology node. Finally, application examples, including qubit calibration and multi-qubit excitation, are simulated with the proposed controller to demonstrate its efficacy. The proposed methodology, and more specifically, the proposed error budget lay the foundations for the design of a scalable electronic controller enabling large-scale quantum computers with practical applications.

Compositional resource theories of coherence

Quantum coherence is one of the most important resources in quantum information theory. Indeed, preventing the loss of coherence is one of the most important technical challenges obstructing the development of large-scale quantum computers. Recently, there has been substantial progress in developing mathematical resource theories of coherence, paving the way towards its quantification and control. To date however, these resource theories have only been mathematically formalised within the realms of convex-geometry, information theory, and linear algebra. This approach is limited in scope, and makes it difficult to generalise beyond resource theories of coherence for single system quantum states. In this paper we take a complementary perspective, showing that resource theories of coherence can instead be defined purely compositionally, that is, working with the mathematics of process theories, string diagrams and category theory. This new perspective offers several advantages: i) it unifies various existing approaches to the study of coherence, for example, subsuming both speakable and unspeakable coherence; ii) it provides a general treatment of the compositional multi-system setting; iii) it generalises immediately to the case of quantum channels, measurements, instruments, and beyond rather than just states; iv) it can easily be generalised to the setting where there are multiple distinct sources of decoherence; and, iv) it directly extends to arbitrary process theories, for example, generalised probabilistic theories and Spekkens toy model---providing the ability to operationally characterise coherence rather than relying on specific mathematical features of quantum theory for its description. More importantly, by providing a new, complementary, perspective on the resource of coherence, this work opens the door to the development of novel tools which would not be accessible from the linear algebraic mind set.

Temporal-mode continuous-variable three-dimensional cluster state for topologically protected measurement-based quantum computation

Measurement-based quantum computation with continuous variables in an optical setup shows the great promise towards implementation of large-scale quantum computation, where the time-domain multiplexing approach enables us to generate the large-scale cluster state used to perform measurement-based quantum computation. To make effective use of the advantage of the time-domain multiplexing approach, in this paper, we propose the method to generate the large-scale 3-dimensional cluster state which is a platform for topologically protected measurement-based quantum computation. Our method combines a time-domain multiplexing approach with a divide-and-conquer approach, and has the two advantages for implementing large-scale quantum computation. First, the squeezing level for verification of the entanglement of the 3-dimensional cluster states is experimentally feasible. The second advantage is the robustness against analog errors derived from the finite squeezing of continuous variables during topologically-protected measurement-based quantum computation. Therefore, our method is a promising approach to implement large-scale quantum computation with continuous variables.

Optimisation of diamond quantum processors

Diamond quantum processors consisting of a nitrogen-vacancy centre and surrounding nuclear spins have been the key to significant advancements in room-temperature quantum computing, quantum sensing and microscopy. The optimisation of these processors is crucial for the development of large-scale diamond quantum computers and the next generation of enhanced quantum sensors and microscopes. Here, we present a full model of multi-qubit diamond quantum processors and develop a semi-analytical method for designing gate pulses. This method optimises gate speed and fidelity in the presence of random control errors and is readily compatible with feedback optimisation routines. We theoretically demonstrate infidelities approaching ∼10−5 for single-qubit gates and established evidence that this can also be achieved for a two-qubit CZ gate. Consequently, our method reduces the effects of control errors below the errors introduced by hyperfine field misalignment and the unavoidable decoherence that is intrinsic to the processors. Having developed this optimal control, we simulated the performance of a diamond quantum processor by computing quantum Fourier transforms. We find that the simulated diamond quantum processor is able to achieve fast operations with low error probability.

Privacy-Preserving Location-Based Services Query Scheme Against Quantum Attacks

Location-based service (LBS) provides more and more conveniences to people. However, it also brings potential threats of offending users’ privacy. How to protect users’ privacy in LBS schemes has aroused increasing research interests in recent years. Most of the existing privacy-preserving LBS schemes are based on the hardness of traditional number-theoretic problems such as the integer factorization or the discrete logarithm problems. However, with the development of large scale quantum computers, these traditional problems can be easily solved by Shor's algorithms, hence the security of these LBS schemes is greatly threatened. In this paper, we solve this problem by constructing a privacy-preserving LBS scheme against quantum attacks from an LWE-based key-homomorphic pseudorandom functions (PRF). In our scheme, due to the key-homomorphic property of the PRF, an LBS user only has to compute one PRF value of the target location and the remaining computation is outsourced to a cloud server, which releases the user from heavy computation burden. In addition, by dividing the key encrypting LBS data into two parts and assigning the two parts to the cloud sever and each user respectively, our scheme avoids the threats of key abuse and information leaking of LBS data. Moreover, we use this PRF to realize an authenticated protocol, which protects the communications between the LBS users and the cloud server. We stress that the security of our scheme is based only on the security of the LWE-based key-homomorphic PRF, hence our scheme is the first LBS scheme secure against quantum attacks.

Generation of distributed steady entangled state between two solid-state spins

The generation of distributed entangled states among solid-state spins is key to the development of large-scale quantum networks and quantum computation. We propose a dissipative scheme for generating stable entanglement between the electron-spin states of two separated nitrogen-vacancy centers, each coupled to a microtoroidal resonator and separated in space. An optical fiber-taper waveguide links the two microtoroidal resonators. Numerical simulations show that spontaneous emission from the NV centers and the collective decay of delocalized field modes can act as effective resources to generate stationary singlet-like states without the need for initialization and precise control of the evolution of the system over time. Results indicate that the proposed scheme can reach high-fidelity and purity of states, and is resilient against small parameter fluctuations. We also discuss how the pure spin dephasing that arises from longitudinal magnetic-near-field noise affects the fidelity of the target state.

Advanced exact synthesis of Clifford+T circuits

Quantum systems provide a new way of conducting computations based on the so-called qubits. Due to the potential for significant speed-ups, this field received significant research attention in recent years. The Clifford+T library is a very promising and popular gate library for these kinds of computations. Unlike other libraries considered so far, it consists of only a small number of gates for all of which robust, fault-tolerant realizations are known for many technologies that seem to be promising for large-scale quantum computing. As a consequence, (logic) synthesis of Clifford+T quantum circuits became an important research problem. However, previous work in this area has several drawbacks: Corresponding approaches are either only applicable to very small quantum systems or lead to circuits that are far from being optimal. The latter is mainly caused by the fact that current synthesis realizes the desired circuit by a local, i.e., column-wise, consideration of the underlying unitary transformation matrix to be synthesized. In this paper, we analyze the conceptual drawbacks of this approach and propose to overcome them by taking a global view of the matrices and perform a separation of concerns regarding individual synthesis steps. We precisely describe a corresponding algorithm as well as its efficient implementation on top of decision diagrams. Experimental results confirm the resulting benefits and show improvements of up to several orders of magnitudes in costs compared to previous work.