The University of Tokyo · Computer Science
Professor Nobuyuki Yoshioka's research lab specializes in the intersection of quantum many-body physics, machine learning, and quantum computing. The lab focuses on developing advanced theoretical and computational methods to simulate strongly correlated quantum systems, particularly through the use of artificial neural networks and variational principles. Key research directions include quantum error mitigation for near-term quantum devices, topological phase recognition using data-driven machine learning, and ab initio simulations of quantum materials using neural network wave functions. The lab also explores exact mappings between complex spin models and machine learning architectures to enhance numerical simulations and quantum algorithm design.
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A theoretical exploration of exotic properties in open quantum many-body systems requires an efficient search of the nonequillibrum stationary states. Aiming to accelerate the process, the authors develop here a variational method, in which the ansatz for the mixed states is based on the restricted Boltzmann machine, motivated by its high expressive power shown in various recent works. It is demonstrated that the ansatz successfully simulates dissipative spin systems both in one and two dimensio
One of the major challenges for erroneous quantum computers is undoubtedly the control over the effect of noise. Considering the rapid growth of available quantum resources that are not fully fault tolerant, it is crucial to develop practical hardware-friendly quantum error mitigation (QEM) techniques to suppress unwanted errors. Here, we propose a novel generalized quantum subspace expansion method which can handle stochastic, coherent, and algorithmic errors in quantum computers. By fully expl
Understanding the phases of a model usually requires knowledge of their characteristic features, which are nonlocal in topologically ordered systems. Here, the authors reframe the phase classification problem in disordered topological superconductors as a data-driven task, motivated by the recent surge of interest in the application of machine-learning techniques including deep learning. It is demonstrated that an artificial neural network learns to extract the essence of the clean system and su
Abstract Establishing a predictive ab initio method for solid systems is one of the fundamental goals in condensed matter physics and computational materials science. The central challenge is how to encode a highly-complex quantum-many-body wave function compactly. Here, we demonstrate that artificial neural networks, known for their overwhelming expressibility in the context of machine learning, are excellent tool for first-principles calculations of extended periodic materials. We show that th
Abstract The intensive pursuit for quantum advantage in terms of computational complexity has further led to a modernized crucial question of when and how will quantum computers outperform classical computers. The next milestone is undoubtedly the realization of quantum acceleration in practical problems. Here we provide a clear evidence and arguments that the primary target is likely to be condensed matter physics. Our primary contributions are summarized as follows: 1) Proposal of systematic e
We find an exact mapping from the generalized Ising models with many-spin interactions to equivalent Boltzmann machines, i.e., the models with only two-spin interactions between physical and auxiliary binary variables accompanied by local external fields. More precisely, the appropriate combination of the algebraic transformations, namely the star-triangle and decoration-iteration transformations, allows one to express the model in terms of fewer-spin interactions at the expense of the degrees o
Surface acoustic wave (SAW) devices with 0.6 ∼ 1.7 μm pattern size (fo=287.5∼812.5 MHz) designed as band-pass filters (BPF) were fabricated by using x-ray lithography. An x-ray stepper SX-5 with a conventional source (Pd terget), high sensitive x-ray resist chlorinated polymethylstyrene (CPMS) (negative) and EBR-9 HS (positive), and a low-distortion x-ray mask with W–Ti alloy absorber were used. The SAW BPF devices were fabricated by forming Al transducer patterns on an LiNbO3 substrate. The Al
We present a quantum-classical hybrid algorithm that simulates electronic structures of periodic systems such as ground states and quasiparticle band structures. By extending the unitary coupled cluster (UCC) theory to describe crystals in arbitrary dimensions, for a hydrogen chain, we numerically demonstrate that the UCC ansatz implemented on a quantum circuit can be successfully optimized with a small deviation from the exact diagonalization over the entire range of the potential energy curves
Functional 1-Mbit DRAM devices were fabricated by using x-ray lithography. An x-ray stepper ( Nikon SX-5) which has a high brightness x-ray tube (10 kW) with a Pd rotating target was used for the fabrication of the devices. The alignment system is based upon the use of a linear diffraction grating as an alignment target. The mask-to-wafer alignment is performed by detecting the first-order diffraction beam of incident laser beams from the grating alignment target. The wafer diameter is 150 mm, t
The estimation of low energies of many-body systems is a cornerstone of the computational quantum sciences. Variational quantum algorithms can be used to prepare ground states on pre-fault-tolerant quantum processors, but their lack of convergence guarantees and impractical number of cost function estimations prevent systematic scaling of experiments to large systems. Alternatives to variational approaches are needed for large-scale experiments on pre-fault-tolerant devices. Here, we use a super
Generic chiral superconductors with three-dimensional electronic structure have nodal gaps and are not strictly topological. Nevertheless, they exhibit a spontaneous thermal Hall effect (THE), i.e. a transverse temperature gradient in response to a heat current even in the absence of an external magnetic field. While in some cases this THE can be quantized analogous to the Quantum Hall effect, this is not the case for nodal superconductors in general. In this study we determine the spontaneous T
Attenuated phase-shifting mask with a single-layer absorptive shifter with MoSiO or MoSiON films has been developed. These films satisfies the condition both the 180-degree phase shift and the transmittance between 5 and 20%. Conventional mask processes, such as etching, cleaning, defect inspection and defect repair, can be used for the fabrication. Defect-free masks for hole layers of 64 M-bit DRAM have been obtained. Using this mask, the focus depth of 0.35-/spl mu/m hole is improved from 0.6
The performance of W-Ti alloy as an x-ray mask absorber material was investigated in order to obtain a low distortion x-ray mask. The W-Ti films were deposited by sputtering the W-Ti (1wt% Ti content) target using Ar + N2 gas with a DC magnetron sputtering system. It was found that the internal stress and the density in the W-Ti films strongly depend on the gas pressure and N2 content of the Ar + N2 sputtering gas. The internal stress of W-Ti films deposited using Ar + N2 of 30% N2 content decre
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