Array Of Qubits Research Articles

Growth and structure of alpha-Ta films for quantum circuit integration

Tantalum films incorporated into superconducting circuits have exhibited low surface losses, resulting in long-lived qubit states. The remaining loss pathways originate in microscopic defects that manifest as two level systems (TLSs) at low temperatures. These defects limit performance, so careful attention to tantalum film structures is critical for optimal use in quantum devices. In this work, we investigate the growth of tantalum using magnetron sputtering on sapphire, Si, and photoresist substrates. In the case of sapphire, we present procedures for the growth of fully-oriented films with α-Ta [1 1 1]//Al2O3 [0 0 0 1] and α-Ta [1 −1 0]//Al2O3 [1 0 −1 0] orientational relationships and having residual resistivity ratio (RRR) ∼ 60 for 220 nm thick films. On Si, we find a complex grain texturing with Ta [1 1 0] normal to the substrate and RRR ∼ 30. We further demonstrate airbridge fabrication using Nb to nucleate α-Ta on photoresist surfaces. For the films on sapphire, resonators show TLS-limited quality factors of 1.3 ± 0.3 × 106 at 10 mK (for a waveguide gap and conductor width of 3 and 6 μm, respectively). Structural characterization using scanning electron microscopy, x-ray diffraction, low temperature transport, secondary ion mass spectrometry, and transmission electron microscopy reveal the dependence of residual impurities and screw dislocation density on processing conditions. The results provide practical insights into the fabrication of advanced superconducting devices including qubit arrays and guide future works on crystallographically deterministic qubit fabrication.

Modeling Short-Range Microwave Networks to Scale Superconducting Quantum Computation

A core challenge for superconducting quantum computers is to scale up the number of qubits in each processor without increasing noise or cross-talk. Distributed quantum computing across small qubit arrays, known as chiplets, can address these challenges in a scalable manner. We propose a chiplet architecture over microwave links with potential to exceed monolithic performance on near-term hardware. Our methods of modeling and evaluating the chiplet architecture bridge the physical and network layers in these processors. We find evidence that distributing computation across chiplets may reduce the overall error rates associated with moving data across the device, despite higher error figures for transfers across links. Preliminary analyses suggest that latency is not substantially impacted, and that at least some applications and architectures may avoid bottlenecks around chiplet boundaries. In the long-term, short-range networks may underlie quantum computers just as local area networks underlie classical datacenters and supercomputers today.

Long-range data transmission in a fault-tolerant quantum bus architecture

We propose a fault-tolerant scheme for generating long-range entanglement at the ends of a rectangular array of qubits of length R with a square cross-section of m=O(log2R) qubits. It is realized by a constant-depth circuit producing a constant-fidelity Bell-pair (independent of R) for local stochastic noise of strength below an experimentally realistic threshold. The scheme can be viewed as a quantum bus in a quantum computing architecture where qubits are arranged on a rectangular 3D grid, and all operations are between neighboring qubits. Alternatively, it can be seen as a quantum repeater protocol along a line, with neighboring repeaters placed at a short distance to allow constant-fidelity nearest-neighbor operations. To show our protocol uses a number of qubits close to optimal, we show that any noise-resilient distance-R entanglement generation scheme realized by a constant-depth circuit needs at least m=Ω(logR) qubits per repeater.

12-Spin-Qubit Arrays Fabricated on a 300 mm Semiconductor Manufacturing Line.

Intel's efforts to build a practical quantum computer are focused on developing a scalable spin-qubit platform leveraging industrial high-volume semiconductor manufacturing expertise and 300 mm fabrication infrastructure. Here, we provide an overview of the design, fabrication, and demonstration of a new customized quantum test chip, which contains 12-quantum-dot spin-qubit linear arrays, code named Tunnel Falls. These devices are fabricated using immersion and extreme ultraviolet lithography (EUV), along with other standard high-volume manufacturing (HVM) processes as well as production-level process control. We present key device features and fabrication details as well as qubit characterization results confirming device functionality. These results corroborate our fabrication methods and are a crucial step toward scaling of extensible 2D qubit array schemes.

Simulating two-dimensional topological quantum phase transitions on a digital quantum computer

Efficient preparation of many-body ground states is key to harnessing the power of quantum computers in studying quantum many-body systems. In this work, we propose a simple method to design exact linear-depth parameterized quantum circuits which prepare a family of ground states across topological quantum phase transitions in 2D. We achieve this by constructing ground states represented by isometric tensor networks (isoTNS), which form a subclass of tensor network states that are efficiently preparable. By continuously tuning a parameter in the wavefunction, the many-body ground state undergoes quantum phase transitions, exhibiting distinct 2D quantum phases. We illustrate this by constructing an isoTNS path with bond dimension D=2 interpolating between distinct symmetry-enriched topological (SET) phases. At the transition point, the wavefunction is related to a gapless point in the classical six-vertex model. Furthermore, the critical wavefunction supports a power-law correlation along one spatial direction while remaining long-range ordered in the other spatial direction. We provide an explicit parametrized local quantum circuit for the path and show that the 2D isoTNS can also be efficiently simulated by a holographic quantum algorithm requiring only an 1D array of qubits. Published by the American Physical Society 2024

Hybrid Atom Tweezer Array of Nuclear Spin and Optical Clock Qubits

While data qubits with a long coherence time are essential for the storage of quantum information, ancilla qubits are pivotal in quantum error correction (QEC) for fault-tolerant quantum computing. The recent development of optical tweezer arrays, such as the preparation of large-scale qubit arrays and high-fidelity gate operations, offers the potential for realizing QEC protocols, and one of the important next challenges is to control and detect ancilla qubits while minimizing atom loss and crosstalk. Here, we present the realization of a hybrid system consisting of a dual-isotope ytterbium (Yb) atom array, in which we can utilize a nuclear spin qubit of fermionic Yb171 as a data qubit and an optical clock qubit of bosonic Yb174 as an ancilla qubit with a capacity of nondestructive qubit readout. We evaluate the crosstalk between qubits regarding the impact on the coherence of the nuclear spin qubits from the imaging light for Yb174. For the Hahn-echo sequence with a 399 nm probe and 556 nm cooling beams for Yb174, we observe 99.1(1.8)% coherence retained under 20 ms exposure, yielding a discrimination fidelity of 0.9992 and a survival probability of 0.988. The Ramsey sequence with a 556 nm probe beam shows negligible influence on the coherence, suggesting the potential future improvement of low crosstalk measurements. This result highlights the potential of the hybrid-Yb atom array for midcircuit measurements for ancilla-qubit-based QEC protocols. Published by the American Physical Society 2024

Resisting High-Energy Impact Events through Gap Engineering in Superconducting Qubit Arrays

Quantum error correction (QEC) provides a practical path to fault-tolerant quantum computing through scaling to large qubit numbers, assuming that physical errors are sufficiently uncorrelated in time and space. In superconducting qubit arrays, high-energy impact events can produce correlated errors, violating this key assumption. Following such an event, phonons with energy above the superconducting gap propagate throughout the device substrate, which in turn generate a temporary surge in quasiparticle (QP) density throughout the array. When these QPs tunnel across the qubits’ Josephson junctions, they induce correlated errors. Engineering different superconducting gaps across the qubit’s Josephson junctions provides a method to resist this form of QP tunneling. By fabricating all-aluminum transmon qubits with both strong and weak gap engineering on the same substrate, we observe starkly different responses during high-energy impact events. Strongly gap engineered qubits do not show any degradation in T1 during impact events, while weakly gap engineered qubits show events of correlated degradation in T1. We also show that strongly gap engineered qubits are robust to QP poisoning from increasing optical illumination intensity, whereas weakly gap engineered qubits display rapid degradation in coherence. Based on these results, gap engineering mitigates the threat of high-energy impacts to QEC in superconducting qubit arrays. Published by the American Physical Society 2024

Towards Early Fault Tolerance on a 2×N Array of Qubits Equipped with Shuttling

It is well understood that a two-dimensional grid of locally interacting qubits is a promising platform for achieving fault-tolerant quantum computing. However in the near future, it may prove less challenging to develop lower-dimensional structures. In this paper, we show that such constrained architectures can also support fault tolerance; specifically we explore a 2×N array of qubits where the interactions between non-neighboring qubits are enabled by shuttling the logical information along the rows of the array. Despite the apparent constraints of this setup, we demonstrate that error correction is possible and identify the classes of codes that are naturally suited to this platform. Focusing on silicon spin qubits as a practical example of qubits believed to meet our requirements, we provide a protocol for achieving full universal quantum computation with the surface code, while also addressing the additional constraints that are specific to a silicon spin-qubit device. Through numerical simulations, we evaluate the performance of this architecture using a realistic noise model, demonstrating that both surface code and more complex quantum low-density parity-check codes efficiently suppress gate and shuttling noise to a level that allows for the execution of quantum algorithms within the classically intractable regime. This work thus brings us one step closer to the execution of quantum algorithms that outperform classical machines. Published by the American Physical Society 2024

(Invited) Faster ALD for Emerging Quantum Applications

Plasma Atomic Layer Deposition (ALD) enables the deposition of a wide variety of materials, with nanometre-scale resolution and precision. Self-limiting growth is a keystone characteristic of ALD processes but limits deposition rate. Long cycle times and low growth per cycle (GPC) impose practical limits on how thick ALD films can be grown. In the field of Quantum Technology (QT), superconducting nanolayers are required for use in Single-Photon Detectors (SPDs), superconducting qubits and interconnects for quantum computing.1 Some superconducting interconnects benefit from non-planar connectivity to control qubits,2 and 3D architectures are key for scaling larger arrays of qubits.3 The deposition of high-quality materials on high aspect ratio Through-Silicon Via (TSV) interconnects is essential but difficult to achieve by conventional sputter techniques. Superconducting nitrides in some QT applications demand relatively thick films (>50 nm), and this poses a new challenge for ALD: to maintain desirable film characteristics and grow thick layers much faster. Here we present recent developments from our new R&D ALD platform: PlasmaPro ASP.The design of the remote, RF-driven plasma source has been optimised to deliver quick, repeatable plasma doses to the substrate with minimal plasma damage. The chamber size, pumping and precursor delivery have been carefully considered to enable efficient ALD of many materials. For multiple materials, we have demonstrated a reduction of cycle times. For example, rates of >25 nm/h for NbN and TiN which is about 3x faster than previously reported. Importantly, these materials retain excellent film properties. NbN showed excellent electrical resistivity (four-point probe), conformality (100% on 8:1 trench), and superconducting transition temperature (Tc) >11 K for <10 nm thick films – a key regime for SPDs. NbN and TiN crystallinity, film stress and film composition will be discussed. Furthermore, many other applications will benefit from this fast plasma ALD. We will also present plasma Al2O3 for power electronics which has been deposited on substrates of up to 200 mm in diameter with a less than one second ALD cycle time. As the needs of emerging quantum technologies and other applications change and continue to push process and film performance, production and research will benefit from high-quality, low damage, conformal films by fast, remote plasma ALD.

Monolithically Integrated Quantum Dots in a 22‐nm Fully Depleted Silicon‐on‐Insulator Process Operating at 3 K

ABSTRACTQuantum computers comprising large‐scale arrays of qubits will enable complex algorithms to be executed to provide a quantum advantage for practical applications. A prerequisite for this milestone is a power‐efficient qubit control and detection system operating at cryogenic temperatures. Implementing such systems in complementary metal‐oxide‐semiconductor (CMOS) technology offers clear advantages in terms of scalability. Here, we present a fully integrated quantum dot array in which silicon quantum wells are co‐located with control and detection circuitry on the same die in a commercial 22‐nm fully depleted silicon‐on‐insulator (FDSOI) process. Our system comprises a two‐dimensional quantum dot array, integrated with 8 detectors and 32 injectors, operating at 3 K inside a cryo‐cooler. The power consumption of the control and detection circuitry is 2.5 mW per qubit without body biasing. The design utilizes 0.8‐V nominal devices. The setup allows us to verify discrete charge injection control and detection at the quantum dot array and demonstrate the feasibility of this architecture for scaling up the existing quantum core to hundreds and thousands of physical qubits.

A synthetic magnetic vector potential in a 2D superconducting qubit array

A synthetic magnetic vector potential in a 2D superconducting qubit array

Coupling and characterization of a Si/SiGe triple quantum dot array with a microwave resonator

Abstract Scaling up spin qubits in silicon-based quantum dots is one of the pivotal challenges in achieving large-scale semiconductor quantum computation. To satisfy the connectivity requirements and reduce the lithographic complexity, utilizing the qubit array structure and the circuit quantum electrodynamics (cQED) architecture together is expected to be a feasible scaling scheme. A triple-quantum dot (TQD) coupled with a superconducting resonator is regarded as a basic cell to demonstrate this extension scheme. In this article, we investigate a system consisting of a silicon TQD and a high-impedance TiN coplanar waveguide (CPW) resonator. The TQD can couple to the resonator via the right double-quantum dot (RDQD), which reaches the strong coupling regime with a charge–photon coupling strength of g 0/(2π) = 175 MHz. Moreover, we illustrate the high tunability of the TQD through the characterization of stability diagrams, quadruple points (QPs), and the quantum cellular automata (QCA) process. Our results contribute to fostering the exploration of silicon-based qubit integration.

Modeling phonon-mediated quasiparticle poisoning in superconducting qubit arrays

Modeling phonon-mediated quasiparticle poisoning in superconducting qubit arrays

Detrimental Increase of Spin-Phonon Coupling in Molecular Qubits on Substrates.

Molecular qubits are a promising platform for quantum information systems. Although single molecule and ensemble studies have assessed the performance of S = 1/2 molecules, it is understood that to function in devices, regular arrays of addressable qubits supported by a substrate are needed. The substrate imposes mechanical and electronic boundary conditions on the molecule; however, the impact of these effects on spin-lattice relaxation times is not well understood. Here we perform electronic structure calculations to assess the effects of a graphene (Cgr) substrate on the molecular qubit copper phthalocyanine (CuPc). We use a progressive Hessian approach to efficiently calculate and separate the substrate contributions. We also use a simple thermal model to predict the impact of these changes on the spin-phonon coupling from 0 to 200 K. Further analysis of the individual vibrational modes with and without Cgr shows that an overall increase in SPC between the vibrations modes of CuPc with the surface reduces the spin-lattice relaxation time T1. We explain these changes by examining how the substrate lifts symmetries of CuPc in the absorbed configuration. Our work shows that a surface can have a large unintentional impact on SPC and that ways to reduce this coupling need to be found to fully exploit arrays of molecular qubits in device architectures.

Integration of buried nanomagnet and silicon spin qubits in a one-dimensional fin structure

We adopt a buried nanomagnet (BNM) technology on a one-dimensional (1D) array of silicon spin qubits, and its availability was investigated using numerical simulations. The qubit array is formed in the center of the Si fin and the nanomagnet is buried in the lower lateral part of the qubits. The nanomagnet placed near the qubit generates a strong slanting magnetic field in the qubit, enabling X-gate operation approximately 15 times faster than in conventional cases. Furthermore, the formation of a BNM using a self-aligned process suppresses the dimensional variation of the nanomagnet caused by process variation, thereby mitigating the slanting field fluctuation and fidelity degradation. In addition, even for multiple qubits formed in the Si fin, the BNM with excess length generated a uniform slanting field, mitigating fidelity degradation and enabling all qubits to operate using a single-frequency microwave. Therefore, the proposed structure is useful for 1D integrated structures.

Lieb-Robinson correlation function for the quantum transverse-field Ising model

The Lieb-Robinson correlation function is the norm of a commutator between local operators acting on separate subsystems at different times. This provides a useful state-independent measure for characterizing the specifically quantum interaction between spatially separated qubits. The finite propagation velocity for this correlator defines a “light cone” of quantum influence. We calculate the Lieb-Robinson correlation function for one-dimensional qubit arrays described by the transverse-field Ising model. Direct calculations of this correlation function have been limited by the exponential increase in the size of the state space with the number of qubits. We introduce a technique that avoids this barrier by transforming the calculation to a sum over Pauli walks which results in linear scaling with system size. We can then explore propagation in arrays of hundreds of qubits and observe the effects of the quantum phase transition in the system. We observe the emergence of two distinct velocities of propagation: a correlation front velocity, which is affected by the phase transition, and the Lieb-Robinson velocity which is not. The correlation front velocity is equal to the maximum group velocity of single quasiparticle excitations. The Lieb-Robinson velocity describes the extreme leading edge of correlations when the value of the correlation function itself is still very small. For the semi-infinite chain of qubits at the quantum critical point, we derive an analytical result for the correlation function. Published by the American Physical Society 2024

Wave-Function Network Description and Kolmogorov Complexity of Quantum Many-Body Systems

Programmable quantum devices are now able to probe wave functions at unprecedented levels. This is based on the ability to project the many-body state of atom and qubit arrays onto a measurement basis which produces snapshots of the system wave function. Extracting and processing information from such observations remains, however, an open quest. One often resorts to analyzing low-order correlation functions—that is, discarding most of the available information content. Here, we introduce wave-function networks—a mathematical framework to describe wave-function snapshots based on network theory. For many-body systems, these networks can become scale-free—a mathematical structure that has found tremendous success and applications in a broad set of fields, ranging from biology to epidemics to Internet science. We demonstrate the potential of applying these techniques to quantum science by introducing protocols to extract the Kolmogorov complexity corresponding to the output of a quantum simulator and implementing tools for fully scalable cross-platform certification based on similarity tests between networks. We demonstrate the emergence of scale-free networks analyzing experimental data obtained with a Rydberg quantum simulator manipulating up to 100 atoms. Our approach illustrates how, upon crossing a phase transition, the simulator complexity decreases while correlation length increases—a direct signature of buildup of universal behavior in data space. Comparing experiments with numerical simulations, we achieve cross-certification at the wave-function level up to timescales of 4 μs with a confidence level of 90% and determine experimental calibration intervals with unprecedented accuracy. Our framework is generically applicable to the output of quantum computers and simulators with access to the system wave function and requires probing accuracy and repetition rates accessible to most currently available platforms. Published by the American Physical Society 2024

Sweet-spot operation of a germanium hole spin qubit with highly anisotropic noise sensitivity

Spin qubits defined by valence band hole states are attractive for quantum information processing due to their inherent coupling to electric fields, enabling fast and scalable qubit control. Heavy holes in germanium are particularly promising, with recent demonstrations of fast and high-fidelity qubit operations. However, the mechanisms and anisotropies that underlie qubit driving and decoherence remain mostly unclear. Here we report the highly anisotropic heavy-hole g-tensor and its dependence on electric fields, revealing how qubit driving and decoherence originate from electric modulations of the g-tensor. Furthermore, we confirm the predicted Ising-type hyperfine interaction and show that qubit coherence is ultimately limited by 1/f charge noise, where f is the frequency. Finally, operating the qubit at low magnetic field, we measure a dephasing time of T2*\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${T}_{2}^{* }$$\\end{document} = 17.6 μs, maintaining single-qubit gate fidelities well above 99% even at elevated temperatures of T > 1 K. This understanding of qubit driving and decoherence mechanisms is key towards realizing scalable and highly coherent hole qubit arrays.

Single-Atom Control of Arsenic Incorporation in Silicon for High-Yield Artificial Lattice Fabrication.

Artificial lattices constructed from individual dopant atoms within a semiconductor crystal hold promise to provide novel materials with tailored electronic, magnetic, and optical properties. These custom-engineered lattices are anticipated to enable new, fundamental discoveries in condensed matter physics and lead to the creation of new semiconductor technologies including analog quantum simulators and universal solid-state quantum computers. This work reports precise and repeatable, substitutional incorporation of single arsenic atoms into a silicon lattice. A combination of scanning tunneling microscopy hydrogen resist lithography and a detailed statistical exploration of the chemistry of arsine on the hydrogen-terminated silicon (001) surface are employed to show that single arsenic dopants can be deterministically placed within four silicon lattice sites and incorporated with 97 ± 2% yield. These findings bring closer to the ultimate frontier in semiconductor technology: the deterministic assembly of atomically precise dopant and qubit arrays at arbitrarily large scales.

Compiling Quantum Circuits for Dynamically Field-Programmable Neutral Atoms Array Processors

Dynamically field-programmable qubit arrays (DPQA) have recently emerged as a promising platform for quantum information processing. In DPQA, atomic qubits are selectively loaded into arrays of optical traps that can be reconfigured during the computation itself. Leveraging qubit transport and parallel, entangling quantum operations, different pairs of qubits, even those initially far away, can be entangled at different stages of the quantum program execution. Such reconfigurability and non-local connectivity present new challenges for compilation, especially in the layout synthesis step which places and routes the qubits and schedules the gates. In this paper, we consider a DPQA architecture that contains multiple arrays and supports 2D array movements, representing cutting-edge experimental platforms. Within this architecture, we discretize the state space and formulate layout synthesis as a satisfiability modulo theories problem, which can be solved by existing solvers optimally in terms of circuit depth. For a set of benchmark circuits generated by random graphs with complex connectivities, our compiler OLSQ-DPQA reduces the number of two-qubit entangling gates on small problem instances by 1.7x compared to optimal compilation results on a fixed planar architecture. To further improve scalability and practicality of the method, we introduce a greedy heuristic inspired by the iterative peeling approach in classical integrated circuit routing. Using a hybrid approach that combined the greedy and optimal methods, we demonstrate that our DPQA-based compiled circuits feature reduced scaling overhead compared to a grid fixed architecture, resulting in 5.1X less two-qubit gates for 90 qubit quantum circuits. These methods enable programmable, complex quantum circuits with neutral atom quantum computers, as well as informing both future compilers and future hardware choices.