arXiv subjects

Masato Fukushima

Publications and source records attributed to Masato Fukushima.

3 recordsLinked to original sources

arXiv2026

Mid-infrared photothermal imaging flow cytometry

Imaging flow cytometry (IFC) enables high-throughput single-cell analysis but largely relies on fluorescence labeling to obtain molecular specificity. Label-free vibrational imaging can provide intrinsic chemical contrast, yet coherent Raman-based methods interrogate only a limited axial volume, which restricts quantitative whole-cell analysis under flow. Mid-infrared photothermal (MIP) microscopy offers a promising route to overcome this limitation by combining linear mid-infrared (MIR) absorption-based chemical contrast with visible-light detection, allowing chemical imaging of a broader axial volume of each cell in a wide-field configuration. However, applying MIP microscopy to rapidly flowing cells has been difficult because conventional frame-sequential acquisition of MIR-ON and MIR-OFF images is highly susceptible to motion-induced subtraction artifacts. Here we demonstrate MIP-IFC, a label-free imaging flow cytometry platform based on single-shot nanosecond-dual-pulse MIP (SNAP-MIP) microscopy. SNAP-MIP encodes the MIR-ON and MIR-OFF states into separate holographic channels within a single camera exposure, reducing their temporal separation to 20 ns. This single-shot acquisition suppresses motion artifacts and increases the allowable sample velocity for artifact-free MIP imaging by five orders of magnitude compared with conventional frame-sequential MIP imaging. Leveraging this capability, MIP-IFC acquired chemical images at 500 frames per second and achieved a cellular event rate up to ~70 events s^-1. We demonstrate quantitative chemical discrimination of flowing microbeads and apply MIP-IFC to single-cell profiling of oleic-acid-induced lipid accumulation, adipocyte differentiation, and confluence-dependent cellular heterogeneity. These results establish MIP-IFC as a high-throughput, quantitative, label-free chemical imaging platform for single-cell phenotyping under flow.

physics.optics↗

arXiv2026

Video-rate volumetric chemical imaging via mid-infrared photothermal optical diffraction tomography

Label-free vibrational microscopy provides chemically specific access to cellular structure, yet quantitative volumetric chemical dynamics in living cells remain largely inaccessible, particularly on subsecond timescales relevant to intracellular transport and structural reorganization. This limitation arises because most high-speed vibrational techniques rely on raster scanning, which constrains volumetric throughput to approximately one volume per second (vps). Although mid-infrared photothermal (MIP) imaging offers a pathway toward spatially parallel chemical detection, existing implementations have remained far below video-rate volumetric operation, reflecting a fundamental trade-off between imaging speed and signal-to-noise ratio. Here, we overcome this trade-off in MIP tomography and realize video-rate volumetric chemical imaging using mid-infrared photothermal optical diffraction tomography (MIP-ODT), achieving high photothermal sensitivity while maintaining quantitative measurement fidelity. High per-angle detectability supports volumetric reconstruction without temporal averaging, yielding a signal-to-noise ratio exceeding 70 under video-rate acquisition conditions. Consequently, volumetric imaging at 19.2 vps is achieved, representing a nearly 400-fold improvement over prior implementations. Using this capability, we performed video-rate three-dimensional tracking of lipid droplets in living cells and quantified anomalous diffusion from full volumetric trajectories, revealing heterogeneous intracellular transport behaviors that are obscured in two-dimensional measurements. We further demonstrate high-speed hyperspectral volumetric chemical imaging across a 300 cm-1 spectral window within 1 s through rapid MIR wavenumber sweeping, paving the way for real-time three-dimensional organelle-specific chemical phenotyping.

physics.optics↗

arXiv2022

Graphix: optimizing and simulating measurement-based quantum computation on local-Clifford decorated graph

We introduce an open-source software library Graphix, which optimizes and simulates measurement-based quantum computation (MBQC). By combining the measurement calculus with an efficient graph state simulator, Graphix allows the classical preprocessing of Pauli measurements in the measurement patterns, significantly reducing the number of operations required to perform the quantum computation while maintaining determinism. For a measurement pattern translated from a quantum circuit, this corresponds to the preprocessing of all Clifford gates, and this improvement in the one-way model is important for efficient operations in quantum hardware with limited qubit numbers. In addition to the direct translation from gate networks, we provide a pattern generation method based on flow-finding algorithms, which automatically generates byproduct correction sequences to ensure determinism. We further implement optimization strategies for measurement patterns beyond the standardization procedure and provide tensor-network backend for classically simulating the MBQC.

quant-ph↗