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Kouki Yamamoto

Publications and source records attributed to Kouki Yamamoto.

4 recordsLinked to original sources

Charge discreteness and the energy efficiency of information erasure in dynamic random-access memory cells

A dynamic random-access memory (DRAM) cell stores information as an integer number of electrons on a capacitor, and whether this discreteness is thermodynamically relevant depends on the competition between the charging energy and thermal fluctuations. This competition is quantified by the ratio $κ$ of the single-electron charging energy to the thermal energy, and here we investigate how $κ$ affects the energy efficiency of information erasure in a DRAM cell. Using a stochastic-thermodynamic model of a DRAM cell, we show that the nonquasistatic heat released during the discharge step is suppressed as $κ$ increases, whereas the quasistatic heat of the charge step approaches the Landauer cost. As a result, the energy efficiency increases monotonically with $κ$ and approaches the Landauer limit where the effect of charge discreteness is maximal and the cell is effectively reduced to two charge states. The parameter $κ$ thus connects two thermodynamic regimes: a multilevel single-well memory, whose nonequilibrium initial state prevents quasistatic erasure, and an effective two-level memory that can attain the Landauer limit. These results identify $κ$ as the parameter that controls the fundamental efficiency ceiling of transistor--capacitor memory circuits.

cond-mat.stat-mech

High-pressure magnetic transition in iron observed via diamond quantum sensing

Diamond quantum sensors offer high precision and spatial resolution as magnetic probes, making them promising for a wide range of applications. While diamond anvil cells (DACs) can generate extremely high pressures, techniques for magnetometry under such conditions remain limited. By fabricating an ensemble of NV centers directly on the anvil diamond surface, we enable precise magnetic measurements under high pressure. In this work, we employ this NV ensemble to image the stray magnetic field of iron up to 30 GPa, enabling the observation of the magnetic transition ($α$-$\varepsilon$ transition) in iron.

physics.app-ph

GPa Pressure Imaging Using Nanodiamond Quantum Sensors

We demonstrate wide-field optical microscopy of the pressure distribution at approximately 20 GPa in a diamond anvil cell (DAC), using nitrogen-vacancy (NV) centers in nanodiamonds (NDs) as quantum sensors. Pressure and non-hydrostaticity maps are obtained by fitting optically detected magnetic resonance (ODMR) spectra with models incorporating hydrostatic and uniaxial stress conditions. Two methods for introducing NDs with a pressure-transmitting medium are compared, revealing that the embedding approach affects the degree of non-hydrostaticity. This ND-based technique offers a powerful imaging platform for probing pressure-induced phenomena and is extendable to other physical quantities such as magnetic fields.

cond-mat.mtrl-sci

Nanodiamond quantum thermometry assisted with machine learning

Nanodiamonds (NDs) are quantum sensors that enable local temperature measurements, taking advantage of their small size. Though the model based analysis methods have been used for ND quantum thermometry, their accuracy has yet to be thoroughly investigated. Here, we apply model-free machine learning with the Gaussian process regression (GPR) to ND quantum thermometry and compare its capabilities with the existing methods. We prove that GPR provides more robust results than them, even for a small number of data points and regardless of the data acquisition methods. This study extends the range of applications of ND quantum thermometry with machine learning.

quant-ph