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2026-121 Real-Time Battery Health Diagnostics Without Additional Hardware

Background Current battery management systems, such as those in electric vehicles, grid storage and consumer electronics, can only estimate bulk metrics like capacity and resistance, which miss key degradation mechanisms. While electrochemical impedance spectroscopy (EIS) provides detailed insight into battery health, it requires specialized hardware...

2025-150 - Quantum Transduction via Generalized Continuous-Variable Teleportation: Boosting Performance of Low-Efficiency Transducers

Background Quantum transduction technologies are essential for linking quantum systems that operate at different frequencies and physical platforms. Leading quantum processors such as superconducting and spin qubits function in the microwave domain, while long-distance quantum communication relies on low-loss optical photons. Efficient conversion between...

2026-004: A Method for Quantifying Similarity Between Population Spiking Activities

Variance-weighted neural similarity analytics delivering noise-corrected, reproducible population spike comparisons. Abstract As neural recording systems have expanded in channel density and data complexity, reliably comparing population-level spike activity across trials, sessions, and subjects has remained a significant challenge. Traditional...

2024-170 - Deterministic Benchmarking: fast and scalable calibration of qubit logic gates to minimize downtime

Background To enable fault-tolerant quantum computing and reliable quantum simulations for drug development and materials science, quantum hardware must move beyond "noisy" prototypes to commercial-grade stability. Current benchmarking standards often miss systematic coherent errors that accumulate quadratically, creating a hidden bottleneck...

2016-094 - Detecting and Correcting Radiation Effects in Electronics

Market Opportunity All electronic devices are susceptible to computational errors due to radiation effects. As electronics get smaller, they are more vulnerable to computational errors due to radiation effects. In mission-critical environments such as military, finance and healthcare, these computational errors are not tolerable. The best solution...

2016-249 - Improved High-Resolution Sensing Technology for Autonomous Vehicles

Market Opportunity Demand for autonomous vehicles is expected to reach 29 million units by 2035. High-resolution detection and ranging technologies, such as LiDAR, are used in autonomous vehicles for remote sensing. Using LiDAR to create, steer, and detect high-resolution optical beams in free-space allows capturing real time 3D data for a diverse...

2021-227 - Quantum Chip Optoelectronic Interposer

Quantum computing Cryogenic quantum chip to classical world quantum interconnect for heterogeneous quantum devices (memory, sensors, detectors, circulators, qubit sources) Abstract USC inventors have designed a heterogeneously integrated quantum chip optoelectronics interposer (QuIP). QuIP enhances qubit performance, offers controlled coupling between...

2021-229 - Secure Aggregation in Federated Learning

Federated learning Healthcare data Financial data Abstract USC researchers have developed LightSecAgg, a novel approach for secure aggregation that guarantees privacy and dropout-resiliency while significantly cutting the overhead for resiliency against dropped users. Utilizing a “one-shot aggregate-mask reconstruction of the active users...

2022-037 - Parity-Time Symmetric Optical Neural Networks

Optical computing Neural networks Abstract USC inventors propose PT-symmetric ONN, a novel architecture based on parity-time (PT) symmetric couplers. The architecture uses optical gain-loss in III-V semiconductors or other gain materials, providing a performance comparable to passive optical systems with phase shifters even at low/moderate levels...

2022-051 - Multiwavelet-Based Operator Learning for Differential Equations

Physical modeling, including aerospace and complex fluid flow Biological modeling, including bacterial dynamics and neuron potential Epidemiology Abstract USC researchers introduce a novel method to solve partial differential equations (PDEs) using a multiwavelet-based neural operator learning scheme. By compressing the operator's kernel using...

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