arXiv subjects

Shuhan Yang

Publications and source records attributed to Shuhan Yang.

8 recordsLinked to original sources

arXiv2026

Bio-resorbable magnetic tunnel junctions

Magnetic tunnel junctions (MTJs) play a crucial role in spintronic applications, particularly data storage and sensors. Especially as a non-volatile memory, MTJs have received substantial attention due to its CMOS compatibility, low power consumption, fast switching speed, and high endurance. In parallel, bio-resorbable electronics have emerged as a promising solution for systems requiring temporary operation and secure data disposal, especially in military, intelligence, and biomedical systems where devices must safely disintegrate under physiological conditions. In this study, we investigate the bio-resorbability of MTJ by analyzing the dissolution behavior of its nanometer-thick constituent layers in phosphate-buffered saline (PBS) solution at pH 7.4, simulating physiological environments. The MTJ structures, composed of bio-resorbable materials, exhibit well-controlled degradation behaviors. Critically, as one of the ferromagnetic layers dissolves, binary information is irreversibly lost, within 10 hours of immersion. These findings highlight the potential of MTJs not only as high-performance memory elements but also as secure, transient data storage platforms. The ability to modify the dissolution lifetime by materials and thickness selection offers unique advantages for short-lived implantable devices, paving the way for integrating spintronic functionality into next-generation bioresorbable electronics.

cond-mat.mtrl-sci↗

arXiv2025

Stability of Minkowski inequality for nearly spherical sets

In this paper, we study the stability of Minkowski inequality for nearly spherical domains that are $C^1$ close to the ball. We show the stability inequalities between the positive part of the $\sigma_k$ curvature integrals for $C^1$ perturbations of a ball; we also establish the stability inequalities for axially symmetric $C^1$ perturbations of a ball. Finally, we construct a counterexample, illustrating that the inequalities become invalid if we do not compensate the integral with the negative part of the curvature. Our work generalizes Glaudo's results on the mean curvature integral to the fully nonlinear cases.

math.DG↗

arXiv2025

Securing generative artificial intelligence with parallel magnetic tunnel junction true randomness

Deterministic pseudo random number generators (PRNGs) used in generative artificial intelligence (GAI) models produce predictable patterns vulnerable to exploitation by attackers. Conventional defences against the vulnerabilities often come with significant energy and latency overhead. Here, we embed hardware-generated true random bits from spin-transfer torque magnetic tunnel junctions (STT-MTJs) to address the challenges. A highly parallel, FPGA-assisted prototype computing system delivers megabit-per-second true random numbers, passing NIST randomness tests after in-situ operations with minimal overhead. Integrating the hardware random bits into a generative adversarial network (GAN) trained on CIFAR-10 reduces insecure outputs by up to 18.6 times compared to the low-quality random number generators (RNG) baseline. With nanosecond switching speed, high energy efficiency, and established scalability, our STT-MTJ-based system holds the potential to scale beyond 106 parallel cells, achieving gigabit-per-second throughput suitable for large language model sampling. This advancement highlights spintronic RNGs as practical security components for next-generation GAI systems.

cs.LG↗

arXiv2025

250 Magnetic Tunnel Junctions-Based Probabilistic Ising Machine

In combinatorial optimization, probabilistic Ising machines (PIMs) have gained significant attention for their acceleration of Monte Carlo sampling with the potential to reduce time-to-solution in finding approximate ground states. However, to be viable in real applications, further improvements in scalability and energy efficiency are necessary. One of the promising paths toward achieving this objective is the development of a co-design approach combining different technology layers including device, circuits and algorithms. Here, we experimentally demonstrate a fully connected PIM architecture based on 250 spin-transfer torque magnetic tunnel junctions (STT-MTJs), interfaced with an FPGA. Our computing approach integrates STT-MTJ-based tunable true random number generators with advanced annealing techniques, enabling the solution of problems with any topology and size. For sparsely connected graphs, the massive parallel architecture of our PIM enables a cluster parallel update method that overcomes the serial limitations of Gibbs sampling, leading to a 10 times acceleration without hardware changes. Furthermore, we prove experimentally that the simulated quantum annealing boosts solution quality 20 times over conventional simulated annealing while also increasing robustness to MTJ variability. Short pulse switching measurements indicate that STT-MTJ-based PIMs can potentially be 10 times faster and 10 times more energy-efficient than graphic processing units, which paves the way for future large-scale, high-performance, and energy-efficient unconventional computing hardware implementations.

cond-mat.mtrl-sci↗

arXiv2025

CEE: An Inference-Time Jailbreak Defense for Embodied Intelligence via Subspace Concept Rotation

Large language models (LLMs) are widely used for task understanding and action planning in embodied intelligence (EI) systems, but their adoption substantially increases vulnerability to jailbreak attacks. While recent work explores inference-time defenses, existing methods rely on static interventions on intermediate representations, which often degrade generation quality and impair adherence to task instructions, reducing system usability in EI settings. We propose a dynamic defense framework. For each EI inference request, we dynamically construct a task-specific safety-semantic subspace, project its hidden state to the most relevant direction, and apply SLERP rotation for adaptive safety control. At comparable defense success rates, our method preserves generation quality, improves usability, reduces tuning cost, and strengthens robustness in EI scenarios.

cs.CR↗

arXiv2024

Chiral damping of magnons

Chiral magnets have garnered significant interest due to the emergence of unique phenomena prohibited in inversion-symmetric magnets. While the equilibrium characteristics of chiral magnets have been extensively explored through the Dzyaloshinskii-Moriya interaction (DMI), non-equilibrium properties like magnetic damping have received comparatively less attention. We present the inaugural direct observation of chiral damping through Brillouin light scattering (BLS) spectroscopy. Employing BLS spectrum analysis, we independently deduce the Dzyaloshinskii-Moriya interaction (DMI) and chiral damping, extracting them from the frequency shift and linewidth of the spectrum peak, respectively. The resulting linewidths exhibit clear odd symmetry with respect to the magnon wave vector, unambiguously confirming the presence of chiral damping. Our study introduces a novel methodology for quantifying chiral damping, with potential ramifications on diverse nonequilibrium phenomena within chiral magnets.

cond-mat.mtrl-sci↗

arXiv2023

Energy-efficient superparamagnetic Ising machine and its application to traveling salesman problems

The growth of artificial intelligence and IoT has created a significant computational load for solving non-deterministic polynomial-time (NP)-hard problems, which are difficult to solve using conventional computers. The Ising computer, based on the Ising model and annealing process, has been highly sought for finding approximate solutions to NP-hard problems by observing the convergence of dynamic spin states. However, it faces several challenges, including high power consumption due to artificial spins and randomness emulated by complex circuits, as well as low scalability caused by the rapidly growing connectivity when considering large-scale problems. Here, we present an experimental Ising annealing computer based on superparamagnetic tunnel junctions (SMTJs) with all-to-all connections, which successfully solves a 70-city travelling salesman problem (4761-node Ising problem). By taking advantage of the intrinsic randomness of SMTJs, implementing a proper global annealing scheme, and using an efficient algorithm, our SMTJ-based Ising annealer shows superior performance in terms of power consumption and energy efficiency compared to other Ising schemes. Additionally, our approach provides a promising way to solve complex problems with limited hardware resources. Moreover, we propose a crossbar array architecture for scalable integration using conventional magnetic random access memories. Our results demonstrate that the SMTJ-based Ising annealing computer with high energy efficiency, speed, and scalability is a strong candidate for future unconventional computing schemes.

cs.ET↗

arXiv2022

Provably-secure randomness generation from switching probability of magnetic tunnel junctions

In recent years, true random number generators (TRNGs) based on magnetic tunnelling junction (MTJ) have become increasingly attractive. This is because MTJ-based TRNGs offer some advantages over traditional CMOS-based TRNGs, such as smaller area and simpler structure. However, there has been no work thus far that quantified the quality of the raw output of an MTJ-based TRNG and performed suitable randomness extraction to produce provably-secure random bits, unlike their CMOS-based counterparts. In this work, we implement an MTJ-based TRNG and characterise the entropy of the raw output. Using this information, we perform post-processing to extract a set of random bits which are provably-secure.

quant-ph↗