Quantum Architectures Research Articles

A Two-Dimensional Architecture for Fast Large-Scale Trapped-Ion Quantum Computing

Building blocks of quantum computers have been demonstrated in small to intermediate-scale systems. As one of the leading platforms, the trapped ion system has attracted wide attention. A significant challenge in this system is to combine fast high-fidelity gates with scalability and convenience in ion trap fabrication. Here we propose an architecture for large-scale quantum computing with a two-dimensional array of atomic ions trapped at such large distance which is convenient for ion-trap fabrication but usually believed to be unsuitable for quantum computing as the conventional gates would be too slow. Using gate operations far outside of the Lamb–Dicke region, we show that fast and robust entangling gates can be realized in any large ion arrays. The gate operations are intrinsically parallel and robust to thermal noise, which, together with their high speed and scalability of the proposed architecture, makes this approach an attractive one for large-scale quantum computing.

Discrete-time quantum walk algorithm for ranking nodes on a network

We present a quantum algorithm for ranking the nodes on a network in their order of importance. The algorithm is based on a directed discrete-time quantum walk, and works on all directed networks. This algorithm can theoretically be applied to the entire internet, and thus can function as a quantum PageRank algorithm. Our analysis shows that the hierarchy of quantum rank matches well with the hierarchy of classical rank for directed tree network and for non-trivial cyclic networks, the hierarchy of quantum ranks do not exactly match to the hierarchy of the classical rank. This highlights the role of quantum interference and fluctuations in networks and the importance of using quantum algorithms to rank nodes in quantum networks. Another application this algorithm can envision is to model the dynamics on networks mimicking the chemical complexes and rank active centers in order of reactivities. Since discrete-time quantum walks are implementable on current quantum processing systems, this algorithm will also be of practical relevance in analysis of quantum architecture.

Entanglement bounds on the performance of quantum computing architectures.

There are many possible architectures of qubit connectivity that designers of future quantum computers will need to choose between. However, the process of evaluating a particular connectivity graph’s performance as a quantum architecture can be difficult. In this paper, we show that a quantity known as the isoperimetric number establishes a lower bound on the time required to create highly entangled states. This metric we propose counts resources based on the use of two-qubit unitary operations, while allowing for arbitrarily fast measurements and classical feedback. We use this metric to evaluate the hierarchical architecture proposed by A. Bapat et al. [Phys. Rev. A 98, 062328 (2018)] and find it to be a promising alternative to the conventional grid architecture. We also show that the lower bound that this metric places on the creation time of highly entangled states can be saturated with a constructive protocol, up to a factor logarithmic in the number of qubits.

Techniques for fault-tolerant decomposition of a multicontrolled Toffoli gate

Physical implementation of scalable quantum architectures faces an immense challenge in the form of fragile quantum states. To overcome it, quantum architectures with fault tolerance are desirable. These are achieved currently by using a surface code along with a transversal gate set. This indicates the need for decomposition of universal $n$-qubit multicontrolled Toffoli ($n$-MCT) gates using a transversal gate set. Additionally, the transversal non-Clifford phase gate incurs high latency, which makes it an important factor to consider during decomposition. Additionally, the decomposition of a large MCT gate without ancillas presents an additional hurdle. In this paper, we address both of these issues by introducing the $\mathrm{Clifford}+{Z}_{N}$ gate library. We present an ancilla-free decomposition of MCT gates with linear phase depth and quadratic phase count. Furthermore, we provide a technique for decomposition of MCT gates in unit phase depth using the $\mathrm{Clifford}+{Z}_{N}$ library, albeit at the cost of ancillary lines and exponential phase count.

Quantum Computers as Universal Quantum Simulators: State‐of‐the‐Art and Perspectives

AbstractThe past few years have witnessed the concrete and fast spreading of quantum technologies for practical computation and simulation. In particular, quantum computing platforms based on either trapped ions or superconducting qubits have become available for simulations and benchmarking, with up to few tens of qubits that can be reliably initialized, controlled, and measured. The present Review aims at giving a comprehensive outlook on the state‐of‐the‐art capabilities offered from these near‐term noisy devices as universal quantum simulators, that is, programmable quantum computers potentially able to calculate the time evolution of many physical models. First, a pedagogic overview on the basic theoretical background pertaining digital quantum simulations is given, with a focus on hardware‐dependent mapping of spin‐type Hamiltonians into the corresponding quantum circuit as a key initial step toward simulating more complex models. Then, the main experimental achievements obtained in the last decade are reviewed, focusing on the digital quantum simulation of such spin models by employing two leading quantum architectures. Their performances are compared, and future challenges are outlined, also in view of prospective hybrid technologies, towards the ultimate goal of reaching the long‐sought quantum advantage for the simulation of complex many‐body models in the physical sciences.

Methods for classically simulating noisy networked quantum architectures

As research on building scalable quantum computers advances, it is important to be able to certify their correctness. Due to the exponential hardness of classically simulating quantum computation, straight-forward verification through classical simulation fails. However, we can classically simulate small scale quantum computations and hence we are able to test that devices behave as expected in this domain. This constitutes the first step towards obtaining confidence in the anticipated quantum-advantage when we extend to scales that can no longer be simulated. Realistic devices have restrictions due to their architecture and limitations due to physical imperfections and noise. Here we extend the usual ideal simulations by considering those effects. We provide a general methodology for constructing realistic simulations emulating the physical system which will both provide a benchmark for realistic devices, and guide experimental research in the quest for quantum-advantage. We exemplify our methodology by simulating a networked architecture and corresponding noise-model; in particular that of the device developed in the Networked Quantum Information Technologies Hub (NQIT) (Networked Quantum Information Technologies Hub 2018 https://nqit.ox.ac.uk/; 2016 private communication. The error model was based on communication with Chris Balance and Tom Harty, mediated through Niel de Beaudrap, early on the NQIT project. Continued collaboration and communication with experimentalists could lead in refinement of the error model, which could be subject for future work.). For our simulations we use, with suitable modification, the classical simulator of Bravyi and Gosset 2016 (Phys. Rev. Lett. 116 250501). The specific problems considered belong to the class of instantaneous quantum polynomial-time (IQP) problems (Shepherd and Bremner 2009 Proc. R. Soc. A 465 141339), a class believed to be hard for classical computing devices, and to be a promising candidate for the first demonstration of quantum-advantage. We first consider a subclass of IQP, defined in Bermejo-Vega et al 2018 (Phys. Rev. X 8 021010), involving two-dimensional dynamical quantum simulators, before moving to more general instances of IQP, but which are still restricted to the architecture of NQIT.

Two-axis quantum control of a fast valley qubit in silicon

Quantum dots in silicon are a promising architecture for semiconductor quantum computing due to a high degree of electric control and compatibility with existing silicon fabrication processes. Although electron charge and spin are prominent methods for encoding the qubit state, valley states in silicon can also store quantum information via valley-orbit coupling with protection against charge noise. By observing coherent oscillations between valley states in a Si/SiGe double quantum dot device tuned to the two-electron charge configuration, we measure the valley energy splitting in both quantum dots individually. We further demonstrate two-axis quantum control of the valley qubit using gated pulse sequences with X and Z rotations occurring within a fast operation time of 300 ps. This control is used to completely map out the surface of the Bloch sphere in a single phase-space plot that is subsequently used for state and process tomography.

Hybrid spin-superconducting quantum circuit mediated by deterministically prepared entangled photonic states

In hybrid quantum systems, a controllable coupling can be obtained by mediating the interactions with dynamically introduced photons. We propose a hybrid quantum architecture consisting of two nitrogen vacancy center ensembles coupled to a tunable flux qubit, which is contained on the transmission line of a multimode nonlinear superconducting coplanar waveguide resonator with an appended Josephson mixing device. We discuss the use of entangled propagating microwaves photons, which through our nonlinear wave-mixing procedure are made into macroscopically distinct quantum states. We use these states to steer the system and show that, with further amplification, we can create a similar photonic state, which has a more distinct reduction of its uncertainty. Furthermore, we show that all of this leads to a lengthened coherence time, a reasonable fidelity that decays to 0.94 and then later increases upward to stabilize at 0.6, as well as a strengthened entanglement.

Qubit allocation as a combination of subgraph isomorphism and token swapping

In 2016, the first quantum processors have been made available to the general public. The possibility of programming an actual quantum device has elicited much enthusiasm. Yet, such possibility also brought challenges. One challenge is the so called Qubit Allocation problem: the mapping of a virtual quantum circuit into an actual quantum architecture. There exist solutions to this problem; however, in our opinion, they fail to capitalize on decades of improvements on graph theory. In contrast, this paper shows how to model qubit allocation as the combination of Subgraph Isomorphism and Token Swapping. This idea has been made possible by the publication of an approximative solution to the latter problem in 2016. We have compared our algorithm against five other qubit allocators, all independently designed in the last two years, including the winner of the IBM Challenge. When evaluated in "Tokyo", a quantum architecture with 20 qubits, our technique outperforms these state-of-the-art approaches in terms of the quality of the solutions that it finds and the amount of memory that it uses, while showing practical runtime.

Automated distribution of quantum circuits via hypergraph partitioning

Quantum algorithms are usually described as monolithic circuits, becoming large at modest input size. Near-term quantum architectures can only manage a small number of qubits. We develop an automated method to distribute quantum circuits over multiple agents, minimising quantum communication between them. We reduce the problem to hypergraph partitioning and then solve it with state-of-the-art optimisers. This makes our approach useful in practice, unlike previous methods. Our implementation is evaluated on five quantum circuits of practical relevance.

Transmon qubit in a magnetic field: Evolution of coherence and transition frequency

We report on spectroscopic and time-domain measurements on a fixed-frequency concentric transmon qubit in an applied in-plane magnetic field to explore its limits of magnetic field compatibility. We demonstrate quantum coherence of the qubit up to field values of $B={40}\,\mathrm{mT}$, even without an optimized chip design or material combination of the qubit. The dephasing rate $\Gamma_\varphi$ is shown to be not affected by the magnetic field in a broad range of the qubit transition frequency. For the evolution of the qubit transition frequency, we find the unintended second junction created in the shadow angle evaporation process to be non-negligible and deduce an analytic formula for the field-dependent qubit energies. We discuss the relevant field-dependent loss channels, which can not be distinguished by our measurements, inviting further theoretical and experimental investigation. Using well-known and well-studied standard components of the superconducting quantum architecture, we are able to reach a field regime relevant for quantum sensing and hybrid applications of magnetic spins and spin systems.

Adiabatic Hamming Code Generator-Checker using 4-Dot-2-Electron Quantum Dot Cellular Automata

Technological advancements have witnessed rapid regression of Moore’s Law within the past few years. With rising demand for higher clocking speeds, CMOS has already started exhibiting threshold limitations. Reversible Logic has emerged as a suitable alternative with near zero heat dissipation attribute. Quantum Dot Cellular Automata (QCA) has adopted the concept of reversibility and emerged as a primitive tool for quantum architecture deigns with clocking near Terra-Hertz range. A plethora of quantum architectures based on QCA cells have been proposed till date. With rise of research on digital designs based on QCA, multiple literary proposals exist which realize digital designs incorporating QCA cells. This communication proposes a Hamming Code Generator-Checker architecture design using 4-dot-2-electron QCA cells. We employ an existing QCA based XOR gate literary proposal for designing the proposed architecture. Peer comparison with literary counterparts has proven our design to fare better with a gain of 60.6% in area.

Quantum annealing learning search for solving QUBO problems

In this paper we present a novel strategy to solve optimization problems within a hybrid quantum-classical scheme based on quantum annealing, with a particular focus on QUBO problems. The proposed algorithm is based on an iterative structure where the representation of an objective function into the annealer architecture is learned and already visited solutions are penalized by a tabu-inspired search. The result is a heuristic search equipped with a learning mechanism to improve the encoding of the problem into the quantum architecture. We prove the convergence of the algorithm to a global optimum in the case of general QUBO problems. Our technique is an alternative to the direct reduction of a given optimization problem into the sparse annealer graph.

Quantized Single-Ion-Channel Hodgkin-Huxley Model for Quantum Neurons

The Hodgkin-Huxley model describes the behavior of the cell membrane in neurons, treating each part of it as an electric circuit element, namely capacitors, memristors, and voltage sources. We focus on the activation channel of potassium ions, due to its simplicity, while keeping most of the features displayed by the original model. This reduced version is essentially a classical memristor, a resistor whose resistance depends on the history of electric signals that have crossed it, coupled to a voltage source and a capacitor. Here, we will consider a quantized Hodgkin-Huxley model based on a quantum memristor formalism. We compare the behavior of the membrane voltage and the potassium channel conductance, when the circuit is subjected to AC sources, in both classical and quantum realms. Numerical simulations show an expected adaptation of the considered channel conductance depending on the signal history in all regimes. Remarkably, the computation of higher moments of the voltage manifest purely quantum features related to the circuit zero-point energy. Finally, we study the implementation of the Hodgkin-Huxley quantum memristor as an asymmetric rf SQUID in superconducting circuits. This study may allow the construction of quantum neuron networks inspired in the brain function, as well as the design of neuromorphic quantum architectures for quantum machine learning.

CNOT Gate Optimizations via Qubit Permutations for IBM's Quantum Architectures

CNOT Gate Optimizations via Qubit Permutations for IBM's Quantum Architectures

EUV Microscopy: A Unique Approach for Materials Characterization

AbstractUnderstanding of fundamental processes as well as nanostructure performance of nano‐engineered systems, novel materials, and quantum architectures, often requires advanced imaging and spectroscopic tools. This is particularly critical as dimensions shrink below 100 nm as visible light cannot directly probe function at these lengthscales. Ultrafast extreme ultraviolet (EUV) techniques offer a pathway to both functional characterization and imaging at sub‐50 nm lengthscales, and a host of use cases in materials and nano science have been demonstrated. Progress in terms of source and instrumentation development are assisting the rapid increase in the availability of these approaches in the laboratory.

Quantum computing for energy systems optimization: Challenges and opportunities

The purpose of this paper is to explore the applications of quantum computing to energy systems optimization problems and discuss some of the challenges faced by quantum computers with techniques to overcome them. The basic concepts underlying quantum computation and their distinctive characteristics in comparison to their classical counterparts are also discussed. Along with different hardware architecture description of two commercially available quantum systems, an example making use of open-source software tools is provided as a first step for diving into the new realm of programming quantum computers for solving systems optimization problems. The trade-off between qualities of these two quantum architectures is also discussed. Complex nature of energy systems due to their structure and large number of design and operational constraints make energy systems optimization a hard problem for most available algorithms. Problems like facility location allocation for energy systems infrastructure development, unit commitment of electric power systems operations, and heat exchanger network synthesis which fall under the category of energy systems optimization are solved using both classical algorithms implemented on conventional CPU based computer and quantum algorithm realized on quantum computing hardware. Their designs, implementation and results are stated. Additionally, this paper describes the limitations of state-of-the-art quantum computers and their great potential to impact the field of energy systems optimization.

An exercise in spin control

Quantum Optics Semiconductor quantum dots offer the highest rate and quality of single photons among all other solid-state quantum light sources. However, they lack access to a long-lived quantum memory, such as a proximal nuclear spin, that would make them competitive for large-scale quantum architectures. Gangloff et al. used the spin of a single electron and light to cool an ensemble of about 30,000 nuclei within semiconductor quantum dots (see the Perspective by Bayer). They then extended this approach to manipulate individual nuclear spins. The ability to manipulate the ensemble of nuclei coherently, down to the single nuclear spin, could lead to the realization of a quantum dot network where each node has its own dedicated quantum memory. Science , this issue p. [62][1]; see also p. [30][2] [1]: /lookup/volpage/364/62?iss=6435 [2]: /lookup/volpage/364/30?iss=6435

Loss-tolerant teleportation on large stabilizer states

We present a general method for finding loss-tolerant teleportation on large, entangled stabilizer states using only single-qubit measurements, known as stabilizer pathfinding (SPF). For heralded loss, SPF is shown to generate optimally loss-tolerant measurement patterns on any given stabilizer state. Furthermore, SPF also provides highly loss-tolerant teleportation strategies when qubit loss is unheralded. We provide a fast algorithm for SPF that updates continuously as a state is generated and measured, which is therefore suitable for real-time implementation on a quantum-computing device. When compared to simulations of previous heuristics for loss-tolerant teleportation on graph states, SPF provides considerable gains in tolerance to both heralded and unheralded loss, achieving a near-perfect teleportation rate (>95%) in the regime of low qubit loss (<10%) on various graph state lattices. Using these results we also present evidence that points towards the existence of loss-tolerant thresholds on such states, which in turn indicates that the loss-tolerant behaviour we have found also applies as the number of qubits tends to infinity. Our results represent a significant advance towards the realistic implementation of teleportation in both large-scale and near-future quantum architectures that are susceptible to qubit loss, such as linear optical quantum computation and quantum communication networks.

Quantum repeater architecture with hierarchically optimized memory buffer times

We propose a quantum repeater protocol and architecture that mitigates decoherence of the entangled states by optimizing the quantum memory buffer time. The protocol maximizes the rate of distillable entanglement in the average accessed state at all nesting levels. The achievable rate is higher by orders of magnitude in comparison to a canonical protocol that does not optimize the buffer time. The advantage of the proposed design is observed for all nesting levels of the repeater for technologically feasible memory quality, entanglement generation and swapping success probabilities.