arXiv subjects

Yuki Sato

Publications and source records attributed to Yuki Sato.

At least 37 records · Page 2Linked to original sources

arXiv2025

Criticality at absolute zero from Ising model on two-dimensional dynamical triangulations

We reconsider the criticality of the Ising model on two-dimensional dynamical triangulations based on the $N \times N$ hermitian two-matrix model with the introduction of a loop-counting parameter and linear terms in the potential. We show that in the large-N limit even though the Ising model is classical, the critical temperature can reach absolute zero by tuning the loop-counting parameter, and the corresponding continuum theory turns out to be the quantised theory of neither pure gravity nor gravity coupled to conformal matter with central charge being 1/2.

hep-th↗

arXiv2025

Control of nonreciprocal charge transport in topological insulator/superconductor heterostructures with Fermi level tuning and superconducting-layer thickness

Nonreciprocal charge transport (NCT) is defined as a phenomenon where electrical resistance depends on the current direction. It has been drawing much attention because it sensitively reflects the symmetry breaking of material systems. A topological insulator (TI)/superconductor (SC) heterostructure where the topological surface state (TSS) of the TI layer is proximitized with the SC layer is one such system that presents a sizable NCT due to a large spin-orbit coupling and superconductivity. Here, we report a control of the magnitude and sign of NCT: reversal of the direction of NCT by tuning the Fermi energy of TSS of the TI layer with respect to the charge neutral point by systematic regulation of Sb composition $x$ in a TI/SC heterostructures of (Bi$_{1-x}$Sb$_x$)$_2$Te$_3$/FeSe$_{0.1}$Te$_{0.9}$. The result is consistent with the model of a TSS proximitized with superconductivity. Furthermore, we find a significant enhancement of the magnitude of NCT in the TI/SC heterostructures by reducing the thickness of the SC layer. The enhancement can be ascribed to the inversion-symmetry breaking of the FeSe$_{0.1}$Te$_{0.9}$ SC-layer itself adjacent to the TI layer. Our results highlight the essential role of the TSS for exhibiting NCT and offer new knobs to control the direction and magnitude of NCT.

cond-mat.supr-con↗

arXiv2025

Broadband and high-precision two-level system loss measurement using superconducting multi-wave resonators

Two-level systems (TLS) are known to be a dominant source of dissipation and decoherence in superconducting qubits. Superconducting resonators provide a convenient way to study TLS-induced loss due to easier design and fabrication in comparison to devices that include non-linear elements. However, accurately measuring TLS-induced loss in a resonator in the quantum regime is challenging due to low signal-to-noise ratio (SNR) and the temporal fluctuations of the TLS, leading to uncertainties of 30% or more. To address these limitations, we develop a multi-wave resonator device that extends the resonator length from a standard quarter-wave $λ/4$ to $Nλ/4$ where $N = 37$ at 6GHz. This design provides two key advantages: the TLS-induced fluctuations are reduced by a factor of $\sqrt{N}$ due to spatial averaging over an increased number of independent TLS, and the measurement SNR for a given intra-resonator energy density improves by a factor of $\sqrt{N}$. The multi-wave resonator also has fundamental and harmonic resonances that allow one to study the frequency dependence of TLS-induced loss. In this work we fabricate both multi-wave and quarter-wave coplanar waveguide resonators formed from thin-film aluminum on a silicon substrate, and characterize their TLS properties at both 10mK and 200mK. Our results show that the power-dependent TLS-induced loss measured from both types of resonators agree well, with the multi-wave resonators achieving a five-fold reduction in measurement uncertainty due to TLS fluctuations, down to 5%. The $Nλ/4$ resonator also provides a measure of the fully unsaturated TLS-induced loss due to the improved measurement SNR at low intra-resonator energy densities. Finally, measurements across seven harmonic resonances of the $Nλ/4$ resonator between 4GHz - 6.5GHz reveals no frequency dependence in the TLS-induced loss over this range.

quant-ph↗

arXiv2025

Properties of the wormhole-dominant phase in two-dimensional quantum gravity

We study the $N \times N$ Hermitian one-matrix model modified by the double-trace interaction. It is known that the coupling for the double-trace interaction can control the weight for the microscopic wormholes if interpreting the matrix model as the lattice model of random surface; tuning the coupling to its critical value, the effect of wormholes become substantial to change the critical behavior of the pure $2$D quantum gravity, which is characterized by a certain positive value of the string susceptibility. In the large-$N$ limit, we calculate the continuum limit of the disk amplitude in which the wormhole effects are important. The resulting continuum disk amplitude is the same as that of the pure $2$D quantum gravity. We also introduce the renormalized coupling for the double-trace interaction, and show that the newly introduced renormalized coupling can alter the renormalized bulk cosmological constant effectively.

hep-th↗

arXiv2025

CDT and Horava-Lifshitz QG in Two Dimensions

The two-dimensional causal dynamical triangulations ($2$d CDT) is a lattice model of quantum geometry. In $2$d CDT, one can deal with the quantum effects analytically and explore the physics through the continuum limit. The continuum theory is known to be two-dimensional projectable Horava-Lifshitz quantum gravity ($2$d projectable HL QG). In this chapter, we wish to review the very relation between $2$d CDT and $2$d projectable HL QG in detail.

hep-th↗

arXiv2025

Why do financial prices exhibit Brownian motion despite predictable order flow?

In financial market microstructure, there are two enigmatic empirical laws: (i) the market-order flow has predictable persistence due to metaorder splitters by institutional investors, well formulated as the Lillo-Mike-Farmer model. However, this phenomenon seems paradoxical given the diffusive and unpredictable price dynamics; (ii) the price impact $I(Q)$ of a large metaorder $Q$ follows the square-root law, $I(Q)\propto \sqrt{Q}$. Here we theoretically reveal why price dynamics follows Brownian motion despite predictable order flow by unifying these enigmas. We generalize the Lillo-Mike-Farmer model to nonlinear price-impact dynamics, which is mapped to an exactly solvable Lévy-walk model. Our exact solution shows that the price dynamics remains diffusive under the square-root law, even under persistent order flow. This work illustrates the crucial role of the square-root law in mitigating large price movements by large metaorders, thereby leading to the Brownian price dynamics, consistently with the efficient market hypothesis over long timescales.

q-fin.TR↗

arXiv2025

Multilevel Circuit Optimization in Quantum Compilers: A Case Study

In this paper, we explore multilevel circuit optimization (MLCO), where we deploy multiple gate sets and progressively lower the source circuit through the gate sets to the target circuit. At each level, we first perform an appropriate set of circuit simplifications and then lower the simplified circuit into the next level, decomposing the gates not supported there. We demonstrate its effectiveness, using as a case study the source circuit for Hamiltonian simulation to solve a partial differential equation, which is densely populated with multi-controlled gates and is transformed by the state-of-the-art circuit compiler to the target circuit with the quadratic number of CX gates in the number of qubits. MLCO makes visible higher-level circuit structures, providing us with insights about how to simplify the circuits and how to decompose the gates. By putting the right circuit structure in place and selecting the right decomposition algorithm, we could cause massive cancellation of entangling gates, thereby having achieved the quadratic reduction in the number of CX gates.

quant-ph↗

arXiv2025

Inverse design of dual-band valley-Hall topological photonic crystals with arbitrary pseudospin states

Valley photonic crystals (VPCs) offer topological kink states that ensure robust, unidirectional, and backscattering-immune light propagation. The design of VPCs is typically based on analogies with condensed-matter topological insulators that exhibit the quantum valley Hall effect; trial-and-error approaches are often used to tailor the photonic band structures and their topological properties, which are characterized by the local Berry curvatures. In this paper, we present an inverse design framework based on frequency-domain analysis for VPCs with arbitrary pseudospin states. Specifically, we utilize the transverse spin angular momentum (TSAM) at the band edge to formulate the objective function for engineering the desired topological properties. Numerical experiments demonstrate that our proposed design approach can successfully produce photonic crystal waveguides exhibiting dual-band operation, enabling frequency-dependent light routing. Our pseudospin-engineering method thus provides a cost-effective alternative for designing topological photonic waveguides, offering novel functionalities.

physics.optics↗

arXiv2025

Quantum algorithm for partial differential equations of non-conservative systems with spatially varying parameters

Partial differential equations (PDEs) are crucial for modeling various physical phenomena such as heat transfer, fluid flow, and electromagnetic waves. In computer-aided engineering (CAE), the ability to handle fine resolutions and large computational models is essential for improving product performance and reducing development costs. However, solving large-scale PDEs, particularly for systems with spatially varying material properties, poses significant computational challenges. In this paper, we propose a quantum algorithm for solving second-order linear PDEs of non-conservative systems with spatially varying parameters, using the linear combination of Hamiltonian simulation (LCHS) method. Our approach transforms those PDEs into ordinary differential equations represented by qubit operators, through spatial discretization using the finite difference method. Then, we provide an algorithm that efficiently constructs the operator corresponding to the spatially varying parameters of PDEs via a logic minimization technique, which reduces the number of terms and subsequently the circuit depth. We also develop a scalable method for realizing a quantum circuit for LCHS, using a tensor-network-based technique, specifically a matrix product state (MPS). We validate our method with applications to the acoustic equation with spatially varying parameters and the dissipative heat equation. Our approach includes a detailed recipe for constructing quantum circuits for PDEs, leveraging efficient encoding of spatially varying parameters of PDEs and scalable implementation of LCHS, which we believe marks a significant step towards advancing quantum computing's role in solving practical engineering problems.

quant-ph↗

arXiv2025

Non-Fermi liquid transport and strong mass enhancement near the nematic quantum critical point in FeSe$_x$Te$_{1-x}$ thin films

Unconventional superconductivity is often accompanied by non-Fermi liquid (NFL) behavior, which emerges near a quantum critical point (QCP) - a point where an electronic ordered phase is terminated at absolute zero under non-thermal parameters. While nematic orders, characterized by broken rotational symmetry, are sometimes found in unconventional superconductors, the role of nematic fluctuations in driving NFL transport behavior remains unclear. Here, we investigated electrical and thermoelectric transport properties in FeSe$_x$Te$_{1-x}$ thin films and observed hallmark NFL behavior: temperature-linear resistivity and logarithmic divergence of thermoelectricity at low temperatures. Notably, the thermoelectricity peaks sharply at the nematic QCP ($x$ = 0.45), highlighting the dominant role of nematic fluctuations in the NFL transport. Furthermore, we found that the pair-breaking mechanisms in the superconducting phase crosses over from orbital- to Pauli-limited effects, indicating the mass enhancement near the nematic critical regime. These findings reveal the profound impact of nematic fluctuations on both normal-state transport and superconducting properties.

cond-mat.str-el↗

arXiv2025

Recursive Quantum Relaxation for Combinatorial Optimization Problems

Quantum optimization methods use a continuous degree-of-freedom of quantum states to heuristically solve combinatorial problems, such as the MAX-CUT problem, which can be attributed to various NP-hard combinatorial problems. This paper shows that some existing quantum optimization methods can be unified into a solver to find the binary solution which is most likely measured from the optimal quantum state. Combining this finding with the concept of quantum random access codes (QRACs) for encoding bits into quantum states on fewer qubits, we propose an efficient recursive quantum relaxation method called recursive quantum random access optimization (RQRAO) for MAX-CUT. Experiments on standard benchmark graphs with several hundred nodes in the MAX-CUT problem, conducted in a fully classical manner using a tensor network technique, show that RQRAO not only outperforms the Goemans-Williamson and recursive QAOA methods, but also is comparable to state-of-the-art classical solvers. The code is available at \url{https://github.com/ToyotaCRDL/rqrao}.

quant-ph↗

arXiv2024

This took us a Weyl: synthesis of a semimetallic Weyl ferromagnet with point Fermi surface

Quantum materials governed by emergent topological fermions have become a cornerstone of physics. Dirac fermions in graphene form the basis for moiré quantum matter, and Dirac fermions in magnetic topological insulators enabled the discovery of the quantum anomalous Hall effect. In contrast, there are few materials whose electromagnetic response is dominated by emergent Weyl fermions. Nearly all known Weyl materials are overwhelmingly metallic, and are largely governed by irrelevant, conventional electrons. Here we theoretically predict and experimentally observe a semimetallic Weyl ferromagnet in van der Waals (Cr,Bi)$_2$Te$_3$. In transport, we find a record bulk anomalous Hall angle $> 0.5$ along with non-metallic conductivity, a regime sharply distinct from conventional ferromagnets. Together with symmetry analysis, our data suggest a semimetallic Fermi surface composed of two Weyl points, with a giant separation $> 75\%$ of the linear dimension of the bulk Brillouin zone, and no other electronic states. Using state-of-the-art crystal synthesis techniques, we widely tune the electronic structure, allowing us to annihilate the Weyl state and visualize a unique topological phase diagram exhibiting broad Chern insulating, Weyl semimetallic and magnetic semiconducting regions. Our observation of a semimetallic Weyl ferromagnet offers an avenue toward novel correlated states and non-linear phenomena, as well as zero-magnetic-field Weyl spintronic and optical devices.

cond-mat.mes-hall↗

arXiv2024

Hamiltonian simulation for hyperbolic partial differential equations by scalable quantum circuits

Solving partial differential equations for extremely large-scale systems within a feasible computation time serves in accelerating engineering developments. Quantum computing algorithms, particularly the Hamiltonian simulations, present a potential and promising approach to achieve this purpose. Actually, there are several oracle-based Hamiltonian simulations with potential quantum speedup, but their detailed implementations and accordingly the detailed computational complexities are all unclear. This paper presents a method that enables us to explicitly implement the quantum circuit for Hamiltonian simulation; the key technique is the explicit gate construction of differential operators contained in the target partial differential equation discretized by the finite difference method. Moreover, we show that the space and time complexities of the constructed circuit are exponentially smaller than those of conventional classical algorithms. We also provide numerical experiments and an experiment on a real device for the wave equation to demonstrate the validity of our proposed method.

quant-ph↗

arXiv2024

Efficient computational homogenization via tensor train format

Real-world physical systems, like composite materials and porous media, exhibit complex heterogeneities and multiscale nature, posing significant computational challenges. Computational homogenization is useful for predicting macroscopic properties from the microscopic material constitution. It involves defining a representative volume element (RVE), solving governing equations, and evaluating its properties such as conductivity and elasticity. Despite its effectiveness, the approach can be computationally expensive. This study proposes a tensor-train (TT)-based asymptotic homogenization method to address these challenges. By deriving boundary value problems at the microscale and expressing them in the TT format, the proposed method estimates material properties efficiently. We demonstrate its validity and effectiveness through numerical experiments applying the proposed method for homogenization of thermal conductivity and elasticity in two- and three-dimensional materials, offering a promising solution for handling the multiscale nature of heterogeneous systems.

cs.CE↗

arXiv2024

Computational synthesis of locomotive soft robots by topology optimization

Locomotive soft robots (SoRos) have gained prominence due to their adaptability. Traditional locomotive SoRo design is based on limb structures inspired by biological organisms and requires human intervention. Evolutionary robotics, designed using evolutionary algorithms (EAs), have shown potential for automatic design. However, EA-based methods face the challenge of high computational cost when considering multiphysics in locomotion, including materials, actuations, and interactions with environments. Here, we present a design approach for pneumatic SoRos that integrates gradient-based topology optimization with multiphysics material point method (MPM) simulations. This approach starts with a simple initial shape (a cube with a central cavity). The topology optimization with MPM then automatically and iteratively designs the SoRo shape. We design two SoRos, one for walking and one for climbing. These SoRos are 3D printed and exhibit the same locomotion features as in the simulations. This study presents an efficient strategy for designing SoRos, demonstrating that a purely mathematical process can produce limb-like structures seen in biological organisms.

cs.CE↗

arXiv2024

Computational co-design of structure and feedback controller for locomoting soft robots

Soft robots have gained significant attention due to their flexibility and safety, particularly in human-centric applications. The co-design of structure and controller in soft robotics has presented a longstanding challenge owing to the complexity of the dynamics involved. Despite some pioneering work dealing with the co-design of soft robot structures and actuation, design freedom has been limited by stochastic design search approaches. This study proposes the simultaneous optimization of structure and controller for soft robots in locomotion tasks, integrating topology optimization-based structural design with neural network-based feedback controller design. Here, the feedback controller receives information about the surrounding terrain and outputs actuation signals that induce the expansion and contraction of the material. We formulate the simultaneous optimization problem under uncertainty in terrains and construct an optimization algorithm that utilizes automatic differentiation within topology optimization and neural networks. We present numerical experiments to demonstrate the validity and effectiveness of our proposed method.

cs.CE↗

arXiv2024

Molecular beam epitaxy of superconducting FeSe$_{x}$Te$_{1-x}$ thin films interfaced with magnetic topological insulators

Engineering heterostructures with various types of quantum materials can provide an intriguing playground for studying exotic physics induced by the proximity effect. Here, we report the successful synthesis of iron-based superconductor FeSe$_{x}$Te$_{1-x}$ (FST) thin films across the entire composition range of $0 \leq x \leq 1$ and its heterostructure with a magnetic topological insulator by using molecular beam epitaxy. Superconductivity is observed in the FST films with an optimal superconducting transition temperature $T_c$ $\sim$ 12 K at around x = 0.1. We found that superconductivity survives in the very Te-rich films ($x \leq 0.05$), showing stark contrast to bulk crystals with suppression of superconductivity due to an appearance of bicollinear antiferromagnetism accompanied by a monoclinic structural transition. By examining thickness $t$ dependence of magnetic susceptibility and electrical transport properties, we observed a trend where anomalies associated with the first order structural transition broaden in films with below $t \sim$ 100 nm. We infer this observation suggests a suppression of the structural instability near substrates. Furthermore, we fabricated an all chalcogenide-based heterointerface between FST and a magnetic topological insulator (Cr,Bi,Sb)$_{2}$Te$_{3}$ for the first time, observing both superconductivity and a large anomalous Hall conductivity. The anomalous Hall conductivity increases with decreasing temperature, approaching the quantized value of $e^2/h$ down to the measurable minimum temperature at $T_c$. The result suggests coexistence of magnetic and superconducting gaps at low temperatures opening at the top and bottom surfaces, respectively. Our novel magnetic topological insulator/superconductor heterostructure could be an ideal platform to explore chiral Majorana edge mode.

cond-mat.supr-con↗

arXiv2024

Noise Robustness of Quantum Relaxation for Combinatorial Optimization

QRAO (Quantum Random Access Optimization) is a relaxation algorithm that reduces the number of qubits required to solve a problem by encoding multiple variables per qubit using QRAC (Quantum Random Access Code). Reducing the number of qubits is a common way of dealing with the impact of noise on a quantum algorithm. Our interest lies in the impact of noise on the quality of the binary solution of QRAO, which is unknown. We demonstrate that the mean approximation ratio of the (3, 1)-QRAC Hamiltonian, i.e., the Hamiltonian utilizing the encoding of 3 bits into 1 qubit by QRAC, is less affected by noise compared to the Ising Hamiltonian used in quantum annealer and QAOA (Quantum Approximate Optimization Algorithm). Based on this observation, we discuss a plausible mechanism behind the robustness of QRAO under depolarizing noise. Finally, we assess the number of shots required to estimate the values of binary variables correctly under depolarizing noise and show that the (3, 1)-QRAC Hamiltonian requires less shots to achieve the same accuracy compared to the Ising Hamiltonian.

quant-ph↗