Qubit Circuit Research Articles

Efficient realization of quantum algorithms with qudits

The development of a universal fault-tolerant quantum computer that can solve efficiently various difficult computational problems is an outstanding challenge for science and technology. In this work, we propose a technique for an efficient implementation of quantum algorithms with multilevel quantum systems (qudits). Our method uses a transpilation of a circuit in the standard qubit form, which depends on the characteristics of a qudit-based processor, such as the number of available qudits and the number of accessible levels. This approach provides a qubit-to-qudit mapping and comparison to a standard realization of quantum algorithms highlighting potential advantages of qudits. We provide an explicit scheme of transpiling qubit circuits into sequences of single-qudit and two-qudit gates taken from a particular universal set. We then illustrate our method by considering an example of an efficient implementation of a 6-qubit quantum algorithm with qudits. In this particular example, we demonstrate how using qudits allows a decreasing amount of two-body interactions in the qubit circuit implementation. We expect that our findings are of relevance for ongoing experiments with noisy intermediate-scale quantum devices that operate with information carriers allowing qudit encodings, such as trapped ions and neutral atoms, as well as optical and solid-state systems.

Solving the vehicle routing problem via quantum support vector machines

The vehicle routing problem (VRP) is an example of a combinatorial optimization problem that has attracted academic attention due to its potential use in various contexts. VRP aims to arrange vehicle deliveries to several sites in the most efficient and economical manner possible. Quantum machine learning offers a new way to obtain solutions by harnessing the natural speedups of quantum effects, although many solutions and methodologies are modified using classical tools to provide excellent approximations of the VRP. In this paper, we employ 6 and 12 qubit circuits, respectively, to build and evaluate a hybrid quantum machine learning approach for solving VRP of 3- and 4-city scenarios. The approach employs quantum support vector machines (QSVMs) trained using a variational quantum eigensolver on a static or dynamic ansatz. Different encoding strategies are used in the experiment to transform the VRP formulation into a QSVM and solve it. Multiple optimizers from the IBM Qiskit framework are also evaluated and compared

A complexity efficient penta-diagonal quantum smoothing filter for bio-medical signal denoising: a study on ECG

Extracting information-bearing signal from a noisy environment has been a practical challenge in both classical and quantum computing formalism, especially in critical signal processing applications. To filter out the effect of noise, we propose a quantum smoothing filter built upon quantum formalism-based circuits applied for electrocardiogram signal denoising. The proposed quantum filter is a conceptually novel framework with an advantage in computational complexity as compared to the existing classical filters, such as discrete wavelet transform and empirical mode decomposition, whereas it achieves similar performance metrics for the accuracy of the filter. Further, we exploit the penta-diagonal Toeplitz structure of the smoothing filter, which gives approximately 48%\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$48\\%$$\\end{document} gate cost reduction for 10 qubit circuit compared to the standard Hamiltonian simulation without structure. The run-time complexity using the quantum matrix inversion technique for the structured matrix is given by O~κ2poly(logN)εP\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ ilde{{\\mathscr {O}}}\\left( \\frac{\\kappa ^2 \ ext {poly}(\\log {N})}{\\varepsilon _P}\\right)$$\\end{document} for condition number κ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\kappa$$\\end{document} of the N×N\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$N\ imes N$$\\end{document} filter matrix within precision εP\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\varepsilon _P$$\\end{document}. Embedding fixed sparsity of the banded matrix, the quantum filter shows potentially better run-time complexity than classical filtering techniques. For the quantifiable research results of our work, we have shown several performance metrics, such as mean-square error and peak signal-to-noise ratio analysis, with a bound of error due to observation noise, simulation error and quantum measurement uncertainty.

Rotationally Invariant Circuits: Universality with the Exchange Interaction and Two Ancilla Qubits.

Universality of local unitary transformations is one of the cornerstones of quantum computing with many applications and implications that go beyond this field. However, it has recently been shown that this universality does not hold in the presence of continuous symmetries: generic symmetric unitaries on a composite system cannot be implemented, even approximately, using local symmetric unitaries on the subsystems. In this Letter, we show that, despite these constraints, any SU(2) rotationally invariant unitary can be realized with the Heisenberg exchange interaction, which is 2-local and rotationally invariant, provided that the system interacts with a pair of ancilla qubits. We also show that a single ancilla is not enough to achieve universality. Furthermore, we study qubit circuits formed from k-local rotationally invariant unitaries and fully characterize the constraints imposed by locality on the realizable unitaries. We also find an interpretation of these constraints in terms of the average energy of states with a fixed angular momentum.

Quantum Implementation of AIM: Aiming for Low-Depth

Security vulnerabilities in the symmetric-key primitives of a cipher can undermine the overall security claims of the cipher. With the rapid advancement of quantum computing in recent years, there is an increasing effort to evaluate the security of symmetric-key cryptography against potential quantum attacks. This paper focuses on analyzing the quantum attack resistance of AIM, a symmetric-key primitive used in the AIMer digital signature scheme. We present the first quantum circuit implementation of AIM and estimate its complexity (such as qubit count, gate count, and circuit depth) with respect to Grover’s search algorithm. For Grover’s key search, the most important optimization metric is depth, especially when considering parallel search. Our implementation gathers multiple methods for a low-depth quantum circuit of AIM in order to reduce the Toffoli depth and full depth (such as the Karatsuba multiplication and optimization of inner modules; Mer, LinearLayer).

Reducing two-level systems dissipations in 3D superconducting niobium resonators by atomic layer deposition and high temperature heat treatment

Superconducting qubits have arisen as a leading technology platform for quantum computing, which is on the verge of revolutionizing the world's calculation capacities. Nonetheless, the fabrication of computationally reliable qubit circuits requires increasing the quantum coherence lifetimes, which are predominantly limited by the dissipations of two-level system defects present in the thin superconducting film and the adjacent dielectric regions. In this paper, we demonstrate the reduction of two-level system losses in three-dimensional superconducting radio frequency niobium resonators by atomic layer deposition of a 10 nm aluminum oxide Al2O3 thin films, followed by a high vacuum heat treatment at 650 °C for few hours. By probing the effect of several heat treatments on Al2O3-coated niobium samples by x-ray photoelectron spectroscopy plus scanning and conventional high resolution transmission electron microscopy coupled with electron energy loss spectroscopy and energy dispersive spectroscopy, we witness a dissolution of niobium native oxides and the modification of the Al2O3-Nb interface, which correlates with the enhancement of the quality factor at low fields of two 1.3 GHz niobium cavities coated with 10 nm of Al2O3.

Quasiparticle Poisoning of Superconducting Qubits from Resonant Absorption of Pair-Breaking Photons.

The ideal superconductor provides a pristine environment for the delicate states of a quantum computer: because there is an energy gap to excitations, there are no spurious modes with which the qubits can interact, causing irreversible decay of the quantum state. As a practical matter, however, there exists a high density of excitations out of the superconducting ground state even at ultralow temperature; these are known as quasiparticles. Observed quasiparticle densities are of order 1 μm^{-3}, tens of orders of magnitude greater than the equilibrium density expected from theory. Nonequilibrium quasiparticles extract energy from the qubit mode and can induce dephasing. Here we show that a dominant mechanism for quasiparticle poisoning is direct absorption of high-energy photons at the qubit junction. We use a Josephson junction-based photon source to controllably dose qubit circuits with millimeter-wave radiation, and we use an interferometric quantum gate sequence to reconstruct the charge parity of the qubit. We find that the structure of the qubit itself acts as a resonant antenna for millimeter-wave radiation, providing an efficient path for photons to generate quasiparticles. A deep understanding of this physics will pave the way to realization of next-generation superconducting qubits that are robust against quasiparticle poisoning.

Deep Neural Network Assisted Quantum Chemistry Calculations on Quantum Computers.

The variational quantum eigensolver (VQE) is a widely employed method to solve electronic structure problems in the current noisy intermediate-scale quantum (NISQ) devices. However, due to inherent noise in the NISQ devices, VQE results on NISQ devices often deviate significantly from the results obtained on noiseless statevector simulators or traditional classical computers. The iterative nature of VQE further amplifies the errors in each loop. Recent works have explored ways to integrate deep neural networks (DNN) with VQE to mitigate iterative errors, albeit primarily limited to the noiseless statevector simulators. In this work, we trained DNN models across various quantum circuits and examined the potential of two DNN-VQE approaches, DNN1 and DNNF, for predicting the ground state energies of small molecules in the presence of device noise. We carefully examined the accuracy of the DNN1, DNNF, and VQE methods on both noisy simulators and real quantum devices by considering different ansatzes of varying qubit counts and circuit depths. Our results illustrate the advantages and limitations of both VQE and DNN-VQE approaches. Notably, both DNN1 and DNNF methods consistently outperform the standard VQE method in providing more accurate ground state energies in noisy environments. However, despite being more accurate than VQE, the energies predicted using these methods on real quantum hardware remain meaningful only at reasonable circuit depths (depth = 15, gates = 21). At higher depths (depth = 83, gates = 112), they deviate significantly from the exact results. Additionally, we find that DNNF does not offer any notable advantage over VQE in terms of speed. Consequently, our study recommends DNN1 as the preferred method for obtaining quick and accurate ground state energies of molecules on current quantum hardware, particularly for quantum circuits with lower depth and fewer qubits.

Optimal qubit circuits for quantum-enhanced telescopes

Optimal qubit circuits for quantum-enhanced telescopes

Quantum simulation of preferred tautomeric state prediction

Prediction of tautomers plays an essential role in computer-aided drug discovery. However, it remains a challenging task nowadays to accurately predict the canonical tautomeric form of a given drug-like molecule. Lack of extensive tautomer databases, most likely due to the difficulty in experimental studies, hampers the development of effective empirical methods for tautomer predictions. A more accurate estimation of the stable tautomeric form can be achieved by quantum chemistry calculations. Yet, the computational cost required prevents quantum chemistry calculation as a standard tool for tautomer prediction in computer-aided drug discovery. In this paper we propose a hybrid quantum chemistry-quantum computation workflow to efficiently predict the dominant tautomeric form. Specifically, we select active-space molecular orbitals based on quantum chemistry methods. Then we utilize efficient encoding methods to map the Hamiltonian onto quantum devices to reduce the qubit resources and circuit depth. Finally, variational quantum eigensolver (VQE) algorithms are employed for ground state estimation where hardware-efficient ansatz circuits are used. To demonstrate the applicability of our methodology, we perform experiments on two tautomeric systems: acetone and Edaravone, each having 52 and 150 spin-orbitals in the Slater Type Orbital - 3 Gaussian (STO-3G) basis set, respectively. Our numerical results show that their tautomeric state prediction agrees with the Coupled Cluster Singles and Doubles (CCSD) benchmarks. Moreover, the required quantum resources are efficient: in the example of Edaravone, we could achieve chemical accuracy with only eight qubits and 80 two-qubit gates.

Compact superconducting transmon qubit circuits made of ultrathin NbN

We design and fabricate a compact superconducting qubit circuit made of nano-thick NbN film on a high-resistivity silicon substrate, carrying seven transmon qubits. By comparing with the conventional superconducting qubit circuits made of superconducting films with hundred-nanometer thickness, our superconducting qubit circuit has much smaller size in the readout circuit, whose resonator length is only about 1/20 of that in a conventional superconducting circuit. Transmons are measured and characterized in the frequency and time domains with different flux bias. The transition frequency f01 can be adjusted in the range of several GHz. The qubit circuits made of such nano-thick material with high kinetic inductance are promising in the integration of quantum circuits.

A co-simulation of superconducting qubit and control electronics for quantum computing.

As the number of qubits in quantum computing increases, the scalability of existing qubit circuit structures and control systems may become insufficient for large-scale expansion and high-fidelity control. To address this challenge, we propose a behavioral-level model of a superconducting qubit and its control electronics, followed by a co-simulation to evaluate their performance. In this paper, we present the modeling process, simulation procedure, and resulting design specifications for the qubit control system. Our co-simulation approach utilizes MATLAB and Simulink, enabling us to derive critical circuit design specifications, such as the required Digital-to-Analog Converter (DAC) resolution, which should be 8 bits or higher, to achieve high-fidelity control. By taking into account factors such as DAC sampling rates, integral and differential nonlinearities, and filter characteristics, we optimize the control system for efficient and accurate qubit manipulation. Our model and simulation approach offer a promising solution to the scalability challenges in quantum computing, providing valuable insights for the design of large-scale superconducting quantum computing systems.

Cryogenic Analog Microwave Variable Attenuator Using rf-SQUIDs for Quantum Systems

We present the design, fabrication and testing of a low-temperature superconducting (LTS) analog microwave variable attenuator. The two-port circuit includes two <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$90^{\circ }$</tex-math></inline-formula> hybrid couplers and a phase shifter to realize a variable attenuation at the output port. The wideband analog phase shifter is implemented using LTS microstrip transmission line (TL) coupled to an array of radio frequency superconducting quantum interference devices (rf-SQUIDs). The phase shift is achieved by passing a dc current through a TL adjacent to the SQUID-loaded microstrip line which controls the flux through the rf-SQUIDs. The proposed variable attenuator shows more than 30 dB of precise analog flat attenuation tuning range over 8 GHz to 12 GHz with a dc control current ranging from 0 mA to 4.5 mA. The device exhibits a wideband operation with variable attenuation seen not only in the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">X-</i> band but also in <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Ku-</i> band. The device is fabricated using a multilayer niobium-based superconducting process SFQ5ee by MIT Lincoln Laboratory, and has a compact footprint of 1.3 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\mathrm{mm}^{2}$</tex-math></inline-formula> . To the best of our knowledge, this is the first implementation of a variable attenuator using distributed rf-SQUIDs. This device has implications in a variety of applications such as cryogenic receivers and qubit circuit measurements.

Boundaries of quantum supremacy via random circuit sampling

Google’s quantum supremacy experiment heralded a transition point where quantum computers can evaluate a computational task, random circuit sampling, faster than classical supercomputers. We examine the constraints on the region of quantum advantage for quantum circuits with a larger number of qubits and gates than experimentally implemented. At near-term gate fidelities, we demonstrate that quantum supremacy is limited to circuits with a qubit count and circuit depth of a few hundred. Larger circuits encounter two distinct boundaries: a return of a classical advantage and practically infeasible quantum runtimes. Decreasing error rates cause the region of a quantum advantage to grow rapidly. At error rates required for early implementations of the surface code, the largest circuit size within the quantum supremacy regime coincides approximately with the smallest circuit size needed to implement error correction. Thus, the boundaries of quantum supremacy may fortuitously coincide with the advent of scalable, error-corrected quantum computing.

Quantum Binary Field Multiplication with Optimized Toffoli Depth and Extension to Quantum Inversion

The Shor's algorithm can find solutions to the discrete logarithm problem on binary elliptic curves in polynomial time. A major challenge in implementing Shor's algorithm is the overhead of representing and performing arithmetic on binary elliptic curves using quantum circuits. Multiplication of binary fields is one of the critical operations in the context of elliptic curve arithmetic, and it is especially costly in the quantum setting. Our goal in this paper is to optimize quantum multiplication in the binary field. In the past, efforts to optimize quantum multiplication have centred on reducing the Toffoli gate count or qubits required. However, despite the fact that circuit depth is an important metric for indicating the performance of a quantum circuit, previous studies have lacked sufficient consideration for reducing circuit depth. Our approach to optimizing quantum multiplication differs from previous work in that we aim at reducing the Toffoli depth and full depth. To optimize quantum multiplication, we adopt the Karatsuba multiplication method which is based on the divide-and-conquer approach. In summary, we present an optimized quantum multiplication that has a Toffoli depth of one. Additionally, the full depth of the quantum circuit is also reduced thanks to our Toffoli depth optimization strategy. To demonstrate the effectiveness of our proposed method, we evaluate its performance using various metrics such as the qubit count, quantum gates, and circuit depth, as well as the qubits-depth product. These metrics provide insight into the resource requirements and complexity of the method. Our work achieves the lowest Toffoli depth, full depth, and the best trade-off performance for quantum multiplication. Further, our multiplication is more effective when not used in stand-alone cases. We show this effectiveness by using our multiplication to the Itoh-Tsujii algorithm-based inversion of F(x8+x4+x3+x+1).

Optimization of shadow evaporation and oxidation for reproducible quantum Josephson junction circuits

The most commonly used physical realization of superconducting qubits for quantum circuits is a transmon. There are a number of superconducting quantum circuits applications, where Josephson junction critical current reproducibility over a chip is crucial. Here, we report on a robust chip scale Al/AlOx/Al junctions fabrication method due to comprehensive study of shadow evaporation and oxidation steps. We experimentally demonstrate the evidence of optimal Josephson junction electrodes thickness, deposition rate and deposition angle, which ensure minimal electrode surface and line edge roughness. The influence of oxidation method, pressure and time on critical current reproducibility is determined. With the proposed method we demonstrate Al/AlOx/Al junction fabrication with the critical current variation (sigma /langle {I_{c} } rangle ) less than 3.9% (from 150 × 200 to 150 × 600 nm2 area) and 7.7% (for 100 × 100 nm2 area) over 20 × 20 mm2 chip. Finally, we fabricate separately three 5 × 10 mm2 chips with 18 transmon qubits (near 4.3 GHz frequency) showing less than 1.9% frequency variation between qubits on different chips. The proposed approach and optimization criteria can be utilized for a robust wafer-scale superconducting qubit circuits fabrication.

LEAP: Scaling Numerical Optimization Based Synthesis Using an Incremental Approach

While showing great promise, circuit synthesis techniques that combine numerical optimization with search over circuit structures face scalability challenges due to a large number of parameters, exponential search spaces, and complex objective functions. The LEAP algorithm improves scaling across these dimensions using iterative circuit synthesis, incremental reoptimization, dimensionality reduction, and improved numerical optimization. LEAP draws on the design of the optimal synthesis algorithm QSearch by extending it with an incremental approach to determine constant prefix solutions for a circuit. By narrowing the search space, LEAP improves scalability from four to six qubit circuits. LEAP was evaluated with known quantum circuits such as QFT and physical simulation circuits like the VQE, TFIM, and QITE. LEAP can compile four qubit unitaries up to 59× faster than QSearch and five and six qubit unitaries with up to 1.2× fewer CNOTs compared to the QFAST package. LEAP can reduce the CNOT count by up to 36×, or 7× on average, compared to the CQC Tket compiler. Despite its heuristics, LEAP has generated optimal circuits for many test cases with a priori known solutions. The techniques introduced by LEAP are applicable to other numerical optimization based synthesis approaches.

Tuning Superinductors by Quantum Coherence Effects for Enhancing Quantum Computing.

Research on spatially inhomogeneous weakly coupled superconductors has recently received a boost of interest because of the experimental observation of a dramatic enhancement of the kinetic inductance with relatively low losses. Here, we study the kinetic inductance and the quality factor of a strongly disordered, weakly coupled superconducting thin film. We employ a gauge-invariant random-phase approximation capable of describing collective excitations and other fluctuations. In line with the experimental findings, we have found that in the range of frequencies of interest, and for sufficiently low temperatures, an exponential increase of the kinetic inductance with disorder coexists with a still large quality factor of ∼10^{4}. More interestingly, on the metallic side of the superconductor-insulator transition, we have identified a range of frequencies and temperatures, T∼0.1T_{c}, where quantum coherence effects induce a broad statistical distribution of the quality factor with an average value that increases with disorder. We expect these findings to further stimulate experimental research on the design and optimization of superinductors for a better performance and miniaturization of quantum devices such as qubit circuits and microwave detectors.

A Stabilizer Framework for the Contextual Subspace Variational Quantum Eigensolver and the Noncontextual Projection Ansatz.

Quantum chemistry is a promising application for noisy intermediate-scale quantum (NISQ) devices. However, quantum computers have thus far not succeeded in providing solutions to problems of real scientific significance, with algorithmic advances being necessary to fully utilize even the modest NISQ machines available today. We discuss a method of ground state energy estimation predicated on a partitioning of the molecular Hamiltonian into two parts: one that is noncontextual and can be solved classically, supplemented by a contextual component that yields quantum corrections obtained via a Variational Quantum Eigensolver (VQE) routine. This approach has been termed Contextual Subspace VQE (CS-VQE); however, there are obstacles to overcome before it can be deployed on NISQ devices. The problem we address here is that of the ansatz, a parametrized quantum state over which we optimize during VQE; it is not initially clear how a splitting of the Hamiltonian should be reflected in the CS-VQE ansätze. We propose a "noncontextual projection" approach that is illuminated by a reformulation of CS-VQE in the stabilizer formalism. This defines an ansatz restriction from the full electronic structure problem to the contextual subspace and facilitates an implementation of CS-VQE that may be deployed on NISQ devices. We validate the noncontextual projection ansatz using a quantum simulator and demonstrate chemically precise ground state energy calculations for a suite of small molecules at a significant reduction in the required qubit count and circuit depth.

Tunable spectral narrowing enabling the functionality of graphene qubit circuits at room temperature

Electrically controllable quantum coherence in quantum dot clusters and arrays based on graphene stripes with zigzag atomic edges (ZZ-stripes) is studied using the Dirac equation and S-matrix technique. We find that respective multiqubit circuits promise stable operation up to room temperatures when the coherence time is prolonged up by a few orders of magnitude through the intrinsic spectral narrowing owing to electron transport between at bands in adjacent sections. Respectively, the coupling of qubits to a noisy environment is diminished, while the inelastic electron-phonon scattering is suppressed. The Stark splitting technique enables a broad range of operations such as all{electrical tuning of the energy level positions and width, level splitting, controlling of the inter-qubit coupling, and the coherence time. At the resonant energies, the phase coherence spreads over thousands of periods. Such phenomena potentially can be utilized in quantum computing and communication applications at room temperature.