Performance Optimization for Drift-Robust Fidelity Improvement of Two-Qubit Gates

<sec>Spin qubits in silicon-based semiconductor quantum dots have become one of the prominent candidates for realizing fault-tolerant quantum computing due to their long coherence time, good controllability, and compatibility with modern advanced integrated circuit manufacturing processes. In recent years, due to the remarkable advances in silicon-based materials, the structure of quantum dot and its fabrication process, and qubit manipulation technology, the great progress of high-fidelity state preparation and readout, single- and two-qubit gates of spin qubits for silicon based semiconductor quantum computation has been achieved. The control fidelities for single- and two-qubit gates all exceed 99%—fault tolerance threshold required by the surface code known for its exceptionally high tolerance to errors. In this paper, we briefly introduce the basic concepts of silicon-based semiconductor quantum dots, discuss the state-of-art technologies used to improve the fidelities of single- and two-qubit gates, and finally highlight the research directions that should be focused on.</sec><sec>This paper is organized as follows. Firstly, we introduce three major types of quantum dot (QD) devices fabricated on different silicon-based substrates, including Si/SiGe heterojunction and Si/SiO<sub>2</sub>. The spin degree of electron or nucleus hosted in QD can be encoded into spin qubits. Electron spin qubits can be thermally initialized to ground state by using an electron reservoirs, and can be read out by spin-charge conversion mechanism: energy-selective readout (Elzerman readout) with reservoirs or Pauli spin blockade (PSB) without reservoirs. Additionally, high fidelity single-shot readout has been demonstrated by using radio-frequency gate reflectometry combined with the PSB, which has unique advantages in large-scale qubit array. To coherently control the spin qubits, electron dipole resonance (ESR) or electron dipole spin resonance (EDSR) for electron and nuclear magnetic resonance (NMR) for nucleus are introduced. With the help of isotope purification greatly improving the dephasing time of qubit and fast single-qubit manipulation based on EDSR, fidelity above 99.9% can be reached. For the two-qubit gates based on exchange interaction between electron spins, the strength of interaction <inline-formula><tex-math id="M1">\begin{document}$ J $\end{document}</tex-math><alternatives><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="23-20221900_M1.jpg"/><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="23-20221900_M1.png"/></alternatives></inline-formula> combined with Zeeman energy difference <inline-formula><tex-math id="M2">\begin{document}$ \Delta {E}_{z} $\end{document}</tex-math><alternatives><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="23-20221900_M2.jpg"/><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="23-20221900_M2.png"/></alternatives></inline-formula> determines the energy levels of system, which lead to the different two-qubit gates, such as controlled-Z (CZ), controlled-Rotation (CROT), and the square root of the SWAP gate (<inline-formula><tex-math id="M3">\begin{document}$ \sqrt{\rm{S}\rm{W}\rm{A}\rm{P}} $\end{document}</tex-math><alternatives><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="23-20221900_M3.jpg"/><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="23-20221900_M3.png"/></alternatives></inline-formula>) gates. In order to improve the fidelity of two-qubit gates, a series of key technologies is used experimentally, they being isotope purification, symmetry operation, careful Hamiltonian engineering, and gate set tomography. Fidelity of two-qubit gates exceeding 99% has been demonstrated for electron spin qubits in Si/SiGe quantum dots and nuclear spin qubits in donors. These advances have pushed the silicon-based spin qubit platform to become a major stepping stone towards fault-tolerant quantum computation. Finally, we discuss the future study of spin qubits, that is, how to effectively expand the number of qubits, and many other problems to be explored and solved.</sec>

Two-qubit entangling gates for superconducting quantum computers

Quantum computing is an extremely promising research combining theoretical and experimental quantum physics, mathematics, quantum information theory and computer science. Classical simulation of quantum computations will cover part of the gap between the theoretical mathematical formulation of quantum mechanics and the realization of quantum computers. One of the most important problems in “quantum computer science” is the development of new symbolic languages for quantum computing and the adaptation of existing symbolic languages for classical computing to quantum algorithms. The present paper is devoted to the adaptation of the Mathematica symbolic language to known quantum algorithms and corresponding simulation on the classical computer. Concretely we shall represent in the Mathematica symbolic language Simon’s algorithm, the Deutsch-Josza algorithm, Grover’s algorithm, Shor’s algorithm and quantum error-correcting codes. We shall see that the same framework can be used for all these algorithms. This framework will contain the characteristic property of the symbolic language representation of quantum computing and it will be a straightforward matter to include this framework in future algorithms.KeywordsDeutsch-Josza algorithmGrover’s algorithmQuantum computingQuantum error-correctingShor’s algorithmSimon’s algorithmSimulation of quantum algorithms

The variational quantum eigensolver (VQE) is a promising algorithm to demonstrate quantum advantage on near-term noisy-intermediate-scale quantum (NISQ) computers. One central problem of VQE is the effect of noise, especially physical noise, on realistic quantum computers. We systematically study the effect of noise for the VQE algorithm by performing numerical simulations with various local noise models, including amplitude damping, dephasing, and depolarizing noise. We show that the ground state energy will deviate from the exact value as the noise probability increase, and typically, the noise will accumulate as the circuit depth increase. The results suggest that the noisy quantum system can remain entanglement at the noise level of NISQ devices by comparing the VQE solution with the mean-field solution for the many-body ground state problem. We build a noise model to capture the noise in a real quantum computer, and the corresponding numerical simulation is consistent with experimental results on IBM Quantum computers through cloud. Our work sheds new light on the practical research of noisy VQE, and the deep understanding of the noise effect of VQE will also help develop error mitigation techniques on near-term quantum computers.

As quantum devices make steady progress towards intermediate scale and fault-tolerant quantum computing, it is essential to develop rigorous and efficient measurement protocols that account for known sources of noise. Most existing quantum characterization protocols such as gate-set tomography and randomized benchmarking assume the noise acting on the qubits is Markovian. However, this assumption is often not valid, as for the case of 1/f charge noise or hyperfine nuclear spin noise. Here, we present a general framework for quantum process tomography (QPT) in the presence of time-correlated noise. We further introduce fidelity benchmarks that quantify the relative strength of different sources of Markovian and non-Markovian noise. As an application of our method, we perform a comparative theoretical and experimental analysis of silicon spin qubits. We first develop a detailed noise model that accounts for the dominant sources of noise and validate the model against experimental data. Applying our framework for time-correlated QPT, we find that the number of independent parameters needed to characterize one- and two-qubit gates can be compressed by 10× and 100×, respectively, when compared to the fully generic case. These compressions reduce the amount of tomographic measurements needed in experiment, while also significantly speeding up numerical simulations of noisy quantum circuit dynamics compared to time-dependent Hamiltonian simulation. Using this compressed noise model, we find good agreement between our theoretically predicted process fidelities and two-qubit interleaved randomized benchmarking fidelities of 99.8% measured in recent experiments on silicon spin qubits. More broadly, our formalism can be directly extended to develop efficient and scalable tuning protocols for high-fidelity control of large arrays of quantum devices with non-Markovian noise. Published by the American Physical Society 2024

Quantum computers have been attractive because they could realize large-scale and highly complicated calculations that conventional computers cannot solve within a finite time. The large-scale integration of qubits, which are the building block of quantum computers, is required to realize their practical application. Indeed, fault-tolerant quantum computers require the integration of one million qubits. Therefore, silicon qubits is a high-profile candidate because they have advanced process and miniaturization technologies developed with VLSI. In addition, silicon qubits are advantageous in operation temperature. Superconductor qubits operate at the cryogenic temperature at around a few tens mK; in contrast, the operation principle of silicon qubits can operate at a much higher temperature over 1 K. The high-temperature operation can realize quantum computers with small and high-power refrigerators; therefore, we can expect desktop quantum computers instead of ongoing supercomputer-size ones. We must promote integration technology development for silicon qubits; however, the silicon qubit research was mainly in the physics field. Then, nowadays, the integration technology development is accelerated in the world.The challenges are in all conventional research fields: devices, integration, and circuits. We must re-develop the silicon technologies for quantum. For example, on the device design, now we do not have a good tool to design the qubits like TCAD; therefore, we must re-develop the TCAD technologies for quantum [1]. Actually, this is the starting point of our recent research activities; we are going to develop a quantum device simulator, clarify the requirements on the fabrication process of silicon qubits, and propose new technologies to reduce the variability to realize large-scale integration [2]. As for the integration, the quantum calculation circuits require several integrated items: qubits, qubit couplers, micro-magnets, and readout systems. The situation is quite different from the conventional VLSI case for which only the transistors should be integrated. Therefore, we must go re-developing new technologies to integrate all these items. Regarding the circuits, we must use CMOS circuits to generate input signals for qubits and readout the results of quantum calculation, which should be operated at cryogenic temperature. This is so-called “cryo-CMOS.” We must explore a new side of the transistor technologies, which is not investigated so far, because the physics of the MOSFET operation is quite different from the conventional room-temperature operation, hampering the circuit design due to the lack of the device operation model. In this situation, despite the long history of MOSFETs, new phenomena of transistor operation are discovered. For example, the low-frequency current noise increases at a low temperature. The origin of the noise is on the interface traps, instead of the fixed charges in the gate oxides as is the case for room temperature operation [3]. Therefore, we must re-developing CMOS circuit technologies from the bottom of the technologies, device physics.In this presentation, I’m going to overview the status of silicon technology developments for quantum from the viewpoints of devices, integration, and circuits. Also, we introduce some of our recent results to contribute to the developments.Acknowledgment: Our work is supported by MEXT Quantum Leap Flagship Program (Q-LEAP) JPMXS0118069228.[1] H. Asai et al., IEEE Electron Devices Technology and Manufacturing Conference 2021.[2] S. Iizuka et al., Tech. Dig. Symp. VLSI Technology 2021.[3] H. Oka et al., Tech. Dig. Symp. VLSI Technology 2020.

Quantum machine learning recently gained prominence due to the computational ability of quantum computers in solving machine learning problems that are intractable on a classical computer. However, achieving a quantum advantage on present-day quantum computers remains an open challenge. In this work, we primarily focus on solving machine learning problems using a hybrid model based on both quantum and classical computers together for the classification task. We propose the quantum multi-class classifier (QMCC) as a variational circuit with a hybrid classical-quantum approach using quantum mechanical properties such as superposition and entanglement. A unitary operation on a single qubit for the state preparation is designed and also demonstrated using a real quantum computer on the IBMQX platform. The entire variational circuit for the classification task is implemented on a quantum simulator. We performed our quantum simulations on three benchmark datasets: Iris dataset, Banknote Authentication (BNA) dataset, and Wireless Indoor Localization (WIL) dataset for machine learning algorithms. Our simulation results show that the proposed QMCC model classified Iris dataset with an accuracy of 92.10%, BNA dataset with an accuracy of 89.50%, and WIL dataset with an accuracy of 91.73%. The proposed model can also be extended to multiple class classifiers.

Achieving high-fidelity and robust qubit manipulations is a crucial requirement for realizing fault-tolerant quantum computation. Here, we demonstrate a single-hole spin qubit in a germanium quantum dot and characterize its control fidelity using gate set tomography. The maximum control fidelities reach 97.48%, 99.81%, 99.88% for the I, X/2 and Y/2 gate, respectively. These results reveal that off-resonance noise during consecutive I gates in gate set tomography sequences severely limits qubit performance. Therefore, we introduce geometric quantum computation to realize noise-resilient qubit manipulation. The geometric gate control fidelities remain above 99% across a wide range of Rabi frequencies. The maximum fidelity surpasses 99.9%. Furthermore, the fidelities of geometric X/2 and Y/2 (I) gates exceed 99% even when detuning the microwave frequency by ± 2.5 MHz (± 1.2 MHz), highlighting the noise-resilient feature. These results demonstrate that geometric quantum computation is a potential method for achieving high-fidelity qubit manipulation reproducibly in semiconductor quantum computation.

This paper presents a hybrid quantum-classical approach to prime factorization. The proposed algorithm is based on the variational quantum eigensolver (VQE), which employs a classical optimizer to find the ground state of a given Hamiltonian. A numerical study is presented, evaluating the performance of the proposed method across various instances on both IBM's real quantum computer and its classical simulator. The results demonstrate that the method is capable of successfully factorizing numbers up to 253 on a real quantum computer and up to 1 048 561 on a classical simulator. These findings show the potential of the approach for practical applications on near-term quantum computers. Published by the American Physical Society 2025

We present and experimentally implement a real-time protocol for calibrating the frequency of a resonantly driven qubit, achieving exponential scaling in calibration precision with the number of measurements, up to the limit imposed by decoherence. The real-time processing capabilities of a classical controller dynamically generate adaptive probing sequences for qubit-frequency estimation. Each probing evolution time and drive frequency are calculated to divide the prior probability distribution into two branches, following a locally optimal strategy that mimics a conventional binary search. The scheme does not require repeated measurements at the same setting, as it accounts for state preparation and measurement errors. Its use of a parametrized probability distribution favors numerical accuracy and computational speed. We show the efficacy of the algorithm by stabilizing a flux-tunable transmon qubit, leading to improved coherence and gate fidelity. As benchmarked by gate-set tomography, the field-programmable gate array (FPGA) powered control electronics partially mitigates non-Markovian noise, which is detrimental to quantum error correction. The mitigation is achieved by dynamically updating and feeding forward the qubit frequency. Our protocol highlights the importance of feedback in improving the calibration and stability of qubits subject to drift and can be readily applied to other qubit platforms.

Fault-tolerant quantum computers that can solve hard problems rely on quantum error correction1. One of the most promising error correction codes is the surface code2, which requires universal gate fidelities exceeding an error correction threshold of 99 per cent3. Among the many qubit platforms, only superconducting circuits4, trapped ions5 and nitrogen-vacancy centres in diamond6 have delivered this requirement. Electron spin qubits in silicon7-15 are particularly promising for a large-scale quantum computer owing to their nanofabrication capability, but the two-qubit gate fidelity has been limited to 98 per cent owing to the slow operation16. Here we demonstrate a two-qubit gate fidelity of 99.5 per cent, along with single-qubit gate fidelities of 99.8 per cent, in silicon spin qubits by fast electrical control using a micromagnet-induced gradient field and a tunable two-qubit coupling. We identify the qubit rotation speed and coupling strength where we robustly achieve high-fidelity gates. We realize Deutsch-Jozsa and Grover search algorithms with high success rates using our universal gate set. Our results demonstrate universal gate fidelity beyond the fault-tolerance threshold and may enable scalable silicon quantum computers.

Quantum computers are set to revolutionize multiple application domains, including financial portfolio optimization, drug discovery, supply chain optimization, and cryptography, by offering algorithmic speed-up over the best-known classical algorithms. This large-scale adoption will also make quantum computers a lucrative target for cyber-criminals. However, to date, there has been minimal experimental study on the possible attack surfaces and the severity of attacks on a real quantum computer. In this work, we introduce MalaQ, a malware specifically developed for quantum computers. MalaQ exploits the classical-computer frontend of a quantum system and causes extensive damages like performance degradation and even complete failure of the quantum circuits. In this paper, we discuss the design, implementation, and experiments using MalaQ in great detail, including drawing parallels with prior works on both classical and quantum cyber-attacks.

Recent advances in computing have led to a further miniaturization of integrated systems. In addition, these new devices would be faster than current ones and capable to share a very high quantity of information. Unfortunately, electronics is physically limited due to impedance and size constraints. To overcome these challenges, researchers are being developed new devices based on other physical principles as optics and quantum mechanics.This special session is devoted to the study and analysis of the last quantum and optical devices and their applications on computing. Several aspects will be treated, ranging from theoretical studies and their application to designs of new devices for futuristic computers. Important subjects as new ways to process information or storing it will be discussed through the four invited talks.From a theoretical point of view, Dr. Romero-Isart from Max-Plank Institute for Quantum Optics will discuss the ways to manipulate the quantum states of nanodielectrics and their applications. Quantum states are the base of quantum computing and how to use them as a processor. This item will be explained by Dr. Kaltenbaek from the Institute for Quantum Computing. On the other way, and with a more applicable point of view, the two other speakers will talk about certain optical and quantum devices. In particular, Dr de Riedmatten from the Institute of Photonic Sciences will dissert about quantum memories as an alternative to the actual magnetic memories, while Dr. Assefa will expose his last research in IBM Thomas J. Watson Research Center about nanophotonic devices for next generation of supercomputers.

Finding ground states and low-lying excitations of a given Hamiltonian is one of the most important problems in many fields of physics. As a novel approach, quantum computing on Noisy Intermediate-Scale Quantum (NISQ) devices offers the prospect to efficiently perform such computations and may eventually outperform classical computers. However, current quantum devices still suffer from inherent quantum noise. In this work, we propose an error mitigation scheme suitable for parametric quantum circuits. This scheme is based on projecting a general quantum noise channel onto depolarization errors. Our method can efficiently reduce errors in quantum computations, which we demonstrate by carrying out simulations both on classical and IBM's quantum devices. In particular, we test the performance of the method by computing the mass gap of the transverse-field Ising model using the variational quantum eigensolver algorithm.

A variety of Josephson-junction-based qubits have recently been implemented with remarkable progress in coherence time and read-out scheme. These developments, together with its potential scalability, have renewed the position of this solid-state device as a strong candidate as a building block for the quantum computer. On the other hand, coupling multiple qubits to construct a logic gate is another important step toward the realization of quantum computer. In this paper, we present our experiments on conditional gate operations using coupled superconducting charge qubits.