Conditional gate operation in superconducting charge qubits

The technologies of Josephson-junction-based qubits have been progressing rapidly, ever since its first demonstration by a superconducting charge qubit1. A variety of systems have been implemented with remarkable progress in coherence time and read-out schemes. Although the current level of this solid-state device is still not as advanced as that of the most advanced microscopic-system-based qubits, these developments, together with the potential scalability, have renewed its position as a strong candidate as a building block for the quantum computer. Recently, coherent oscillation and microwave spectroscopy in capacitively-coupled superconducting qubits have been reported. The next challenging step toward quantum computation is a realization of logic gates. Here we demonstrate a conditional gate operation using a pair of coupled superconducting charge qubits. Using a pulse technique, we prepare different input states and show that they can be transformed by controlled-NOT (C-NOT) gate operation in the amplitude of the states. Although the phase evolution during the gate operation is still to be clarified, the present results are a major step toward the realization of a universal solid-state quantum gate.

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.

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.

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

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.

Increasing coherent interrogation times is central to advancing the precision of optical clocks. Synchronous differential optical clock comparisons have now demonstrated atomic coherence times that far exceed the coherence time of the clock laser. While atom coherence times are then primarily limited by errors induced by lattice Raman scattering, excited clock state radiative decay, and broadening from two-body collisions, many of these errors take the atoms out of the clock transition subspace, and can therefore be converted into “erasure” errors if the appropriate readout scheme is employed. Here we experimentally demonstrate a hyperfine-resolved readout technique for 87 Sr optical lattice clocks that mitigates decoherence from Raman scattering induced by the lattice as well as radiative decay. By employing hyperfine-resolved readout in synchronous differential comparisons between 87 Sr ensembles with both Ramsey and spin-echo spectroscopy sequences, we achieve enhanced atomic coherence times exceeding 100 and 150 s, respectively, enabling longer coherent measurements without a reduction in performance. We anticipate that this hyperfine-resolved readout technique will benefit applications of state-of-the-art optical lattice clock comparisons in which the coherence times are constrained by Raman scattering or radiative decay.

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.

It has recently been realized that use of the properties of quantum mechanics might speed up certain computations dramatically. Interest in quantum computation has since been growing. One of the main difficulties in realizing quantum computation is that decoherence tends to destroy the information in a superposition of states in a quantum computer making long computations impossible. A further difficulty is that inaccuracies in quantum state transformations throughout the computation accumulate, rendering long computations unreliable. However, these obstacles may not be as formidable as originally believed. For any quantum computation with t gates, we show how to build a polynomial size quantum circuit that tolerates O(1/log/sup c/t) amounts of inaccuracy and decoherence per gate, for some constant c; the previous bound was O(1/t). We do this by showing that operations can be performed on quantum data encoded by quantum error-correcting codes without decoding this data.

Quantum computing enhanced distance-minimizing data-driven computational mechanics

The concept of quantum computing was first developed in the early 1980’s. The attraction of quantum computers is their potential capacity to solve extremely complex problems, such as factorization, on a timescale far faster than that of classical computers. However, realization of quantum computation is currently in its infancy, and recent implementations possess serious drawbacks that reduce their appeal. Some challenges of current designs include the necessity to cool the systems using liquid helium to near absolute zero temperatures (15 mK) in order to maintain sufficiently long-lifetimes of the Qbits (i.e., unit of quantum information), difficulty with scaling up the processing systems, and prohibitively high manufacturing costs. Fundamentally, the key physical effect that enables high processing speeds in quantum computers is quantum superposition, which allows a single qbit to have two (or more) definite states (e.g., 0 and 1) simultaneously. Maintaining a superposition of states at room temperature, however, has proven difficult with silicon-based technology. Coherent exciton delocalization, which involves the superposition of excitonic states characterized by the delocalization of excitons (i.e., electron-hole pairs) across spatially proximate but separated molecules, has been observed in biological photosynthetic systems at ambient temperatures (295 K). Natural photosynthetic systems are composed of protein scaffolds that encompass and elegantly arrange an aggregate of optically active dye molecules (i.e., cluster of chromophores) with nanometer-scale precision in a manner that promotes coherence despite the inherently warm and “noisy” (i.e., rapidly fluctuating) environment inside a plant. As a result, light energy absorbed from the sun is quickly and efficiently transferred through the dye aggregate in a wavelike manner that both optimizes the transfer pathway and minimizes energy loss. Thus, exploiting excitonic delocalization, as inspired by biology, offers a potential path forward towards realizing quantum computing at room temperature. Here, we demonstrate coherent exciton delocalization in systems that utilize DNA, a biological material that affords atomically precise arrangement of dyes (e.g., Cy5) with nanometer proximity, as a scaffold. Leveraging the inherent programmability and functionality of DNA, which undergoes Watson-Crick base-pairing to enable simple structural control than the complex folding mechanisms involved with proteins, we have designed two dye-DNA complexes that are described in two journal manuscripts contained within this dissertation (Chapters 2 and 3). The first manuscript, which described the behavior and spectral properties of a relatively simple linear dye-DNA complex, achieved two milestones towards quantum information processing: (i) the identification of Cy5 dyes as promising candidates for the

A quantum computation algorithm is demonstrated using single photons and linear optics. Quantum registers are realized by modes and polarization of photons, and the unitary transformations for them are implemented with linear optics. For each quantum computation, the answer to the Deutsch Jozsa problem for any 4 bit digit is given by a single-photon detection signal with a small error rate. The origin of the error is also studied and categorized according to the sources: systematic errors of quantum gates, phase relaxation, amplitude dumping, and misreadout. It is suspected that a demonstration of 11 qubits using linear optics anda single photon with less than a 20 % error rate is achievable by the technique used in the experiment. As a further objective, an idea to construct controlled-NOT gate using quantum phase gate (QPG) given by Chuang et. al., is introduced and experiments on the QPGs are also reviewed.

We propose a scheme for generating squeezed states of a nanomechanical resonator. The scheme is based on a hybrid system consisting of two NAMRs and a superconducting charge qubit (SCCQ). The nonlinear interaction between the two nanomechanical resonators (NAMRs) can be implemented by setting the external biased flux of the SCCQ at some certain values, which plays the role of “nonlinear media”. The noise in the SCCQ does not need to be considered, since we can adiabatically keep the SCCQ at the ground state. In addition, the squeezing parameters can also be adjusted by changing the external driving voltage.

Quantum system characterization techniques represent the front line in the identification and mitigation of noise in quantum computing, but can be expensive in terms of quantum resources and time to repeatedly employ. Another challenging aspect is that parameters governing the performance of various operations tend to drift over time, and monitoring these is hence a difficult task. One of the most promising characterization techniques, gate set tomography (GST), provides a self-consistent estimate of the completely positive, trace-preserving (CPTP) maps for a complete set of gates, as well as preparation and measurement operators. We develop a method for performance optimization seeded by tomography (POST), which couples the power of GST with a classical optimization routine to achieve a consistent gate improvement in just a short number of steps within a given calibration cycle. By construction, the POST procedure finds the best available gate operation given the hardware, and is therefore robust to the effects of drift. Further, in comparison to other quantum error mitigation techniques, it builds upon a one-time application of GST. To demonstrate the performance of this method on a real quantum computer, we map out the operations of six qubit pairs on the superconducting \emph{ibmq\_poughkeepsie} quantum device. Under the restriction of logical-only control, we monitor the performance of the POST approach on a chosen CNOT gate over a period of six weeks. In this time, we achieve a consistent improvement in gate fidelity, averaging a fidelity increase of 21.1\% as measured by randomized benchmarking. The POST approach should find wide applicability as it is hardware agnostic, and can be applied at the upper logical level or at a deeper pulse control level.

Calculations of nuclear properties and nuclear models are performed using quantum computing algorithms on simulated and real quantum computers. The models are a realistic calculation of deuteron binding based on effective field theory, and a simplified two-level version of the nuclear shell model. A method of reducing the number of qubits needed for practical calculation is presented, the reduction being with respect to that used when the standard Jordan-Wigner encoding is used. Its efficacy is shown in the case of the deuteron binding and shell model. A version of the variational quantum eigensolver in which all eigenstates in a spectrum are targeted on an equal basis is shown. The method involves finding the minima of the variance of the Hamiltonian, and its ability to find the full spectrum of small version of the simplified shell model is presented.