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View article: Bayesian inference of general noise-model parameters from the syndrome statistics of surface codes
Bayesian inference of general noise-model parameters from the syndrome statistics of surface codes Open
The performance of error correction in the surface code can be enhanced by leveraging the knowledge of the noise model for physical qubits. To provide accurate noise information to the decoder in parallel with quantum computation, an adapt…
View article: Universal scaling laws of absorbing phase transitions in artificial deep neural networks
Universal scaling laws of absorbing phase transitions in artificial deep neural networks Open
We demonstrate that conventional artificial deep neural networks operating near the phase boundary of the signal propagation dynamics—also known as the edge of chaos—exhibit universal scaling laws of absorbing phase transitions in nonequil…
View article: Accelerated spin-adapted ground state preparation with non-variational quantum algorithms
Accelerated spin-adapted ground state preparation with non-variational quantum algorithms Open
Various methods have been explored to prepare the spin-adapted ground state, the lowest energy state within the Hilbert space constrained by externally specified values of the total spin magnitude and the spin-$z$ component. In such proble…
View article: Grassmann tensor renormalization group approach to (1+1)-dimensional two-color lattice QCD at finite density
Grassmann tensor renormalization group approach to (1+1)-dimensional two-color lattice QCD at finite density Open
A bstract We construct a Grassmann tensor network representing the partition function of (1+1)-dimensional two-color QCD with staggered fermions. The Grassmann path integral is rewritten as the trace of a Grassmann tensor network by introd…
View article: Embedding of Tree Tensor Networks into Shallow Quantum Circuits
Embedding of Tree Tensor Networks into Shallow Quantum Circuits Open
Variational Quantum Algorithms (VQAs) are being highlighted as key quantum algorithms for demonstrating quantum advantage on Noisy Intermediate-Scale Quantum (NISQ) devices, which are limited to executing shallow quantum circuits because o…
View article: Two-color lattice QCD in $(1+1)$ dimensions with Grassmann tensor renormalization group
Two-color lattice QCD in $(1+1)$ dimensions with Grassmann tensor renormalization group Open
The $(1+1)$-dimensional two-color lattice QCD is studied with the Grassmann tensor renormalization group. We construct tensor network representations of theories with the staggered fermion and the Wilson fermion and show that Grassmann ten…
View article: Local Basis Transformation to Mitigate Negative Sign Problems
Local Basis Transformation to Mitigate Negative Sign Problems Open
Quantum Monte Carlo (QMC) methods for the frustrated quantum spin systems occasionally suffer from the negative sign problem, which makes simulations exponentially harder for larger systems at lower temperatures and severely limits QMC's a…
View article: LSQCA: Resource-Efficient Load/Store Architecture for Limited-Scale Fault-Tolerant Quantum Computing
LSQCA: Resource-Efficient Load/Store Architecture for Limited-Scale Fault-Tolerant Quantum Computing Open
Current fault-tolerant quantum computer (FTQC) architectures utilize several encoding techniques to enable reliable logical operations with restricted qubit connectivity. However, such logical operations demand additional memory overhead t…
View article: Markov Chain Monte Carlo in Tensor Network Representation
Markov Chain Monte Carlo in Tensor Network Representation Open
Markov chain Monte Carlo (MCMC) is a powerful tool for sampling from complex probability distributions. Despite its versatility, MCMC often suffers from strong autocorrelation and the negative sign problem, leading to slowing down the conv…
View article: Grassmann tensor renormalization group approach to $(1+1)$-dimensional two-color lattice QCD at finite density
Grassmann tensor renormalization group approach to $(1+1)$-dimensional two-color lattice QCD at finite density Open
We construct a Grassmann tensor network representing the partition function of (1+1)-dimensional two-color QCD with staggered fermions. The Grassmann path integral is rewritten as the trace of a Grassmann tensor network by introducing two-…
View article: Systematic construction of multi-controlled Pauli gate decompositions with optimal $T$-count
Systematic construction of multi-controlled Pauli gate decompositions with optimal $T$-count Open
Multi-controlled Pauli gates are typical high-level qubit operations that appear in the quantum circuits of various quantum algorithms. We find multi-controlled Pauli gate decompositions with smaller CNOT-count or $T$-depth while keeping t…
View article: Bayesian inference of general noise-model parameters from the syndrome statistics of surface codes
Bayesian inference of general noise-model parameters from the syndrome statistics of surface codes Open
The performance of error correction in the surface code can be enhanced by leveraging the knowledge of the noise model for physical qubits. To provide accurate noise information to the decoder in parallel with quantum computation, an adapt…
View article: Update of <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si1.svg"> <mml:mi mathvariant="script">H</mml:mi> <mml:mi mathvariant="normal">Φ</mml:mi> </mml:math> : Newly added functions and methods in versions 2 and 3
Update of : Newly added functions and methods in versions 2 and 3 Open
HΦ [aitch-phi] is an open-source software package of numerically exact and stochastic calculations for a wide range of quantum many-body systems. In this paper, we present the newly added functions and the implemented methods in vers. 2 an…
View article: Update of $\mathcal{H}Φ$: Newly added functions and methods in versions 2 and 3
Update of $\mathcal{H}Φ$: Newly added functions and methods in versions 2 and 3 Open
$\mathcal{H}Φ$ [$aitch$-$phi$] is an open-source software package of numerically exact and stochastic calculations for a wide range of quantum many-body systems. In this paper, we present the newly added functions and the implemented metho…
View article: Universal Scaling Laws of Absorbing Phase Transitions in Artificial Deep Neural Networks
Universal Scaling Laws of Absorbing Phase Transitions in Artificial Deep Neural Networks Open
We demonstrate that conventional artificial deep neural networks operating near the phase boundary of the signal propagation dynamics, also known as the edge of chaos, exhibit universal scaling laws of absorbing phase transitions in non-eq…
View article: Stochastic parameter optimization analysis of dynamical quantum critical phenomena in long-range transverse-field Ising chain
Stochastic parameter optimization analysis of dynamical quantum critical phenomena in long-range transverse-field Ising chain Open
The quantum phase transition of the one-dimensional long-range transverse-field Ising model is explored by combining the quantum Monte Carlo method and stochastic parameter optimization, specifically achieved by tuning correlation ratios s…
View article: A Noise-Robust Data Assimilation Method for Crystal Structure Prediction Using Powder Diffraction Intensity
A Noise-Robust Data Assimilation Method for Crystal Structure Prediction Using Powder Diffraction Intensity Open
Crystal structure prediction for a given chemical composition has long been a challenge in condensed-matter science. We have recently shown that experimental powder X-ray diffraction (XRD) data are helpful in a crystal structure search usi…
View article: MateriApps LIVE! and MateriApps Installer: Environment for starting and scaling up materials science simulations
MateriApps LIVE! and MateriApps Installer: Environment for starting and scaling up materials science simulations Open
In our current era, numerical simulations have become indispensable theoretical and experimental tools for use in daily research activities, particularly in the materials science fields. However, the installation processes for such simulat…
View article: Nested Iterative Shift-invert Diagonalization for Many-body Localization in the Random-field Heisenberg Chain
Nested Iterative Shift-invert Diagonalization for Many-body Localization in the Random-field Heisenberg Chain Open
We study the many-body localization of the random-field Heisenberg chain using the nested shift-invert Lanczos method with an iterative linear solver. We use the minimum residual method (MINRES) inside each Lanczos iteration. The memory co…
View article: Randomized-Gauge Test for Machine Learning of Ising Model Order Parameter
Randomized-Gauge Test for Machine Learning of Ising Model Order Parameter Open
Recently, machine learning has been applied successfully for identifying\nphases and phase transitions of the Ising models. The continuous phase\ntransition is characterized by spontaneous symmetry breaking, which can not be\ndetected in g…
View article: Bond-weighted tensor renormalization group
Bond-weighted tensor renormalization group Open
We propose an improved tensor renormalization-group (TRG) algorithm, the bond-weighted TRG (BTRG). In BTRG, we generalize the conventional TRG by introducing bond weights on the edges of the tensor network. We show that BTRG outperforms th…
View article: Quantum-gate decomposer
Quantum-gate decomposer Open
Efficient decompositions of multi-qubit gates are essential in NISQ applications, where the number of gates or the circuit depth is limited. This paper presents efficient decompositions of CCZ and CCCZ gates, typical multi-qubit gates, und…
View article: Fast-update in self-learning algorithm for continuous-time quantum Monte Carlo
Fast-update in self-learning algorithm for continuous-time quantum Monte Carlo Open
We propose a novel technique for speeding up the self-learning Monte Carlo method applied to the single-site impurity model. For the case where the effective Hamiltonian is expressed by polynomial functions of differences of imaginary-time…
View article: Anisotropic tensor renormalization group
Anisotropic tensor renormalization group Open
We propose a new tensor renormalization group algorithm, Anisotropic Tensor Renormalization Group (ATRG), for lattice models in arbitrary dimensions. The proposed method shares the same versatility with the Higher-Order Tensor Renormalizat…
View article: Crystal Structure Analysis by Data Assimilation of X-ray Diffraction Experiment and Simulation
Crystal Structure Analysis by Data Assimilation of X-ray Diffraction Experiment and Simulation Open
Prediction of crystal structure from the chemical composition has been a long-standing challenge in natural science. Although various numerical methods have been developed over the last decades, it remains still tricky to numerically predi…