arXiv subjects

Sangjin Lee

Publications and source records attributed to Sangjin Lee.

At least 19 recordsLinked to original sources

arXiv2026

MIFA: An MILP-based Framework for Improving Differential Fault Attacks

At ASIACRYPT 2021, Baksi et al. introduced DEFAULT, a block cipher designed to algorithmically resist Differential Fault Attack (DFA), claiming 64-bit DFA security regardless of the number of injected faults. At EUROCRYPT 2022, Nageler et al. demonstrated that DEFAULT's claimed DFA resistance can be broken by applying an information-combining technique. More recently, at ASIACRYPT 2024, Jana et al. improved DFA by searching for differential trails with a single solution. They showed that, for DEFAULT with a simple key schedule, injecting five faults at the fifth-to-last round reduces the key space to one, and for BAKSHEESH, injecting twelve faults at the third-to-last round achieves the same result. In this paper, we propose a new DFA framework that utilizes a Mixed-Integer Linear Programming (MILP) solver. This framework makes it possible to attack deeper rounds than previously achieved, reducing the number of fault injections required for key recovery. Furthermore, we present a method to determine the most efficient fault injection bit positions by systematically analyzing the input differences from all possible single bit-flip faults, thereby further reducing the required number of faults. This systematic analysis has the significant advantage of allowing us to theoretically calculate the required number of faults. Applying our framework, for DEFAULT, injecting three faults at the sixth-to-last round and two faults at the seventh- and eighth-to-last rounds reduces the key space to one.

cs.CR↗

arXiv2026

Constant-Depth Multi-Product Formula for Trotter Error Mitigation in Near-Term Digital Quantum Simulation

Digital quantum simulation of many-body dynamics faces a tension between algorithmic Trotter error and physical noise that accumulates with circuit depth. Typical higher-order product formulas mitigate the algorithmic error at the cost of deeper circuits. Our benchmark shows that, within the limited physical error budget, the feasible advantage is confined to absolute errors well below the $10^{-2}$ scale, which vanishes under noise levels of current quantum hardware. In sharp contrast to the previous Trotter error mitigation methods, we introduce a constant-depth multi-product formula (cd-MPF) that suppresses the Trotter error by combining multiple circuits at fixed circuit depth. We identify an auxiliary parameter $\alpha$, which reshapes the Trotter error terms while leaving the target evolution invariant. The classical linear combination of the measured expectation values cancels the leading $(\Delta t)^{2}$ algorithmic contribution and steepens the Trotter-error scaling with the two-qubit circuit depth $d$ from $d^{-2}$ to $d^{-4}$. Combined with physical-noise mitigation, our method can serve as a key ingredient for realizing long-time quantum dynamics simulation on near-term hardware.

quant-ph↗

arXiv2026

Mitigating Trotter Errors via Post-Processed Symmetry Restoration

Quantum simulation is a powerful tool for exploring complex quantum many-body systems such as condensed matter physics and gauge theories. Trotterization, which approximates the ideal time evolution operator by decomposing it into a sequence of local gate operations, is one of the most widely used quantum simulation algorithms. However, such Trotterized implementations generally fail to preserve the symmetries of the target Hamiltonian during compilation. As a result, they can drive quantum states out of symmetrically allowed subspaces, leading to unphysical dynamics and symmetry-violating algorithmic errors. In this work, we propose a symmetry-based Trotter error mitigation protocol using classical post-processing. By applying symmetry transformations to the initial state or interleaving them between discrete Trotter layers, and then averaging an ensemble of the resulting measurement outcomes via classical post-processing, our method systematically projects out the symmetry-violating components of the Trotter error while leaving the ideal dynamics unchanged. Importantly, this framework naturally accommodates non-local spatial symmetries and anti-unitary operations such as time reversal, which are difficult or impossible to implement directly with hardware-native quantum gates. We benchmark our protocol on the one-dimensional XY model and the one-dimensional Schwinger model. In the XY model, enforcing reflection symmetry suppresses the leading-order Trotter error, whereas in the Schwinger model, interleaving gauge transformations between Trotter layers enables gauge-twirling effectively to reduce unphysical violations of local Gauss's law. These results demonstrate that symmetry-based post-processing provides a depth-preserving route to substantially improving the fidelity of Trotterized quantum simulations on near-term devices.

quant-ph↗

arXiv2026

Technical Report for ICRA 2026 GOOSE 2D Fine-Grained Semantic Segmentation Challenge: Leveraging DINOv3 for Robust Outdoor Scene Understanding in Field Robotics

The GOOSE 2D Fine-Grained Semantic Segmentation Challenge at the ICRA 2026 Workshop on Field Robotics evaluates dense semantic segmentation of off-road imagery over a fine-grained taxonomy of 64 classes and 11 evaluated non-void coarse categories. We present the first-place solution to this challenge. Our solution comprises two complementary improvements: (a) a network-level design that combines a self-supervised DINOv3 ViT-L/16 backbone, a ViT-Adapter, and a Mask2Former mask-classification decoder, together with a coarse-category auxiliary loss on the global [CLS] token; and (b) an inference-time aggregation strategy based on multi-scale and horizontal-flip test-time augmentation and an ensemble of the top three checkpoints selected using Codabench scores. Our method achieves an official composite score of 76.57%, consisting of 69.32% fine-class mIoU and 83.81% category-level mIoU, and ranks first on the final phase leaderboard: www.codabench.org/competitions/14257/#/results-tab.

cs.CV↗

arXiv2026

Proper modules over Ginzburg dg algebras and compact Fukaya categories of plumbings

We study Ginzburg dg algebras which appear at the intersection of representation theory and symplectic topology. First, we provide a collection of proper modules that generates all proper modules over a Ginzburg dg algebra, without assuming the Jacobi-finite condition. Using this generation result, we study the immersed compact Fukaya category of a general plumbing space. In particular, we prove a generation result for the compact Fukaya category and show that it is equivalent to the category of proper modules over the wrapped Fukaya category, and hence to the category of microlocal sheaves on the Lagrangian skeleton.

math.SG↗

arXiv2026

Generation of immersed Lagrangians by cocores

We extend the generation theorem of Chantraine--Dimitroglou Rizell--Ghiggini--Golovko to exact Lagrangian immersions in Weinstein manifolds. We prove that an exact Lagrangian immersion equipped with an augmentation of the Chekanov--Eliashberg algebra of its Legendrian lift, or equivalently, equipped with a corresponding bounding cochain, is generated by the Lagrangian cocores.

math.SG↗

arXiv2026

qSHIFT: An Adaptive Sampling Protocol for Higher-Order Quantum Simulation

Early fault-tolerant quantum computers are expected to support reliable but depth-limited quantum circuits, while classical computational resources remain available. These conditions have motivated hybrid coherent algorithms which use quantum simulation as a central algorithmic primitive. This trend calls for quantum-simulation methods that operate with shallow circuits and admit systematic improvements in gate-complexity scaling. Here, we introduce qSHIFT, an adaptive sampling protocol for simulating a Hamiltonian $H=\sum_{i=1}^{L}h_iH_i$. qSHIFT achieves gate complexity $\mathcal{O}_r\left((\lambda t)^{1+1/r}/\varepsilon^{1/r}\right)$, where $r$ is an algorithmic parameter, $\lambda=\sum_i |h_i|$ and $\varepsilon$ denotes the target precision. Relative to qDRIFT, increasing $r$ systematically improves the gate complexity for a given target precision without incurring extra quantum cost. Unlike Trotterization, the number of sampled gates is nominally independent of $L$. qSHIFT retains the elementary gate set of qDRIFT and, unlike qSWIFT, requires neither ancillary qubits nor controlled operations. The improved gate complexity scaling is obtained at the cost of a classical calculation involving $L^r$ coefficients at each adaptive sampling round.

quant-ph↗

arXiv2026

Dual channel multi-product formulas

Product-formula (PF) based quantum simulation is a promising approach for simulating quantum systems on near-term quantum computers. Achieving a desired simulation precision typically requires a polynomially increasing number of Trotter steps, which remains challenging due to the limited performance of current quantum hardware. To alleviate this issue, post-processing techniques such as the multi-product formula (MPF) have been introduced to suppress algorithmic errors within restricted hardware resources. In this work, we propose a dual-channel multi-product formula that achieves a two-fold improvement in Trotter error scaling. As a result, our method enables the target simulation precision to be reached with approximately half the circuit depth compared to conventional MPF schemes. Importantly, the reduced circuit depth directly translates into lower physical error mitigation overhead when implemented on real quantum hardware. We demonstrate that, for a fixed CNOT count as a measure of quantum circuit, our proposal yields significantly smaller algorithmic errors, while the sampling error remains essentially unchanged.

quant-ph↗

arXiv2025

A4: Microarchitecture-Aware LLC Management for Datacenter Servers with Emerging I/O Devices

In modern server CPUs, the Last-Level Cache (LLC) serves not only as a victim cache for higher-level private caches but also as a buffer for low-latency DMA transfers between CPU cores and I/O devices through Direct Cache Access (DCA). However, prior work has shown that high-bandwidth network-I/O devices can rapidly flood the LLC with packets, often causing significant contention with co-running workloads. One step further, this work explores hidden microarchitectural properties of the Intel Xeon CPUs, uncovering two previously unrecognized LLC contentions triggered by emerging high-bandwidth I/O devices. Specifically, (C1) DMA-written cache lines in LLC ways designated for DCA (referred to as DCA ways) are migrated to certain LLC ways (denoted as inclusive ways) when accessed by CPU cores, unexpectedly contending with non-I/O cache lines within the inclusive ways. In addition, (C2) high-bandwidth storage-I/O devices, which are increasingly common in datacenter servers, benefit little from DCA while contending with (latency-sensitive) network-I/O devices within DCA ways. To this end, we present \design, a runtime LLC management framework designed to alleviate both (C1) and (C2) among diverse co-running workloads, using a hidden knob and other hardware features implemented in those CPUs. Additionally, we demonstrate that \design can also alleviate other previously known network-I/O-driven LLC contentions. Overall, it improves the performance of latency-sensitive, high-priority workloads by 51\% without notably compromising that of low-priority workloads.

cs.AR↗

arXiv2025

Trotter error mitigation by error profiling with shallow quantum circuit

Understanding the dynamics of quantum systems is crucial in many areas of physics, but simulating many-body systems presents significant challenges due to the large Hilbert space to navigate and the exponential growth of computational overhead. Quantum computers offer a promising platform to overcome these challenges, particularly for simulating the time evolution with Hamiltonians. Trotterization is a widely used approach among available algorithms in this regard, and well suited for near-term quantum devices. However, it introduces algorithmic Trotter errors due to the non-commutativity of Hamiltonian components. Several techniques such as multi-product formulas have been developed to mitigate Trotter errors, but often require deep quantum circuits, which can introduce additional physical errors. In this work, we propose a resource-efficient scheme to reduce the algorithmic Trotter error with relatively shallow circuit depth. We develop a profiling method by introducing an auxiliary parameter to estimate the error effects in expectation values, enabling significant error suppression with a fixed number of Trotter steps. Our approach offers an efficient way of quantum simulation on near-term quantum processors with shallow circuits.

quant-ph↗

arXiv2024

A Randomization-Based Method for Evaluating Time-Varying Treatment Effects

Tests for paired censored outcomes have been extensively studied, with some justified in the context of randomization-based inference. These tests are primarily designed to detect an overall treatment effect across the entire follow-up period, providing limited insight into when the effect manifests and how it changes over time. In this article, we introduce new randomization-based tests for paired censored outcomes that enable both time-specific and long-term analysis of a treatment effect. The tests utilize time-specific scores, quantifying each individual's impact on sample survival at a fixed time, obtained via pseudo-observations. Moreover, we develop corresponding sensitivity analysis methods to address potential unmeasured confounding in observational studies where randomization often lacks support. To illustrate how our methods can provide a fuller analysis of a time-varying treatment effect, we apply them to a matched cohort study using data from the Korean Longitudinal Study of Aging (KLoSA), focusing on the effect of social engagement on survival.

stat.ME↗

arXiv2024

Multi-Scale Feature Prediction with Auxiliary-Info for Neural Image Compression

Recently, significant improvements in rate-distortion performance of image compression have been achieved with deep-learning techniques. A key factor in this success is the use of additional bits to predict an approximation of the latent vector, which is the output of the encoder, through another neural network. Then, only the difference between the prediction and the latent vector is coded into the bitstream, along with its estimated probability distribution. We introduce a new predictive structure consisting of the auxiliary coarse network and the main network, inspired by neural video compression. The auxiliary coarse network encodes the auxiliary information and predicts the approximation of the original image as multi-scale features. The main network encodes the residual between the predicted feature from the auxiliary coarse network and the feature of the original image. To further leverage our new structure, we propose Auxiliary info-guided Feature Prediction (AFP) module that uses global correlation to predict more accurate predicted features. Moreover, we present Context Junction module that refines the auxiliary feature from AFP module and produces the residuals between the refined features and the original image features. Finally, we introduce Auxiliary info-guided Parameter Estimation (APE) module, which predicts the approximation of the latent vector and estimates the probability distribution of these residuals. We demonstrate the effectiveness of the proposed modules by various ablation studies. Under extensive experiments, our model outperforms other neural image compression models and achieves a 19.49\% higher rate-distortion performance than VVC on Tecnick dataset.

eess.IV↗

arXiv2024

The wrapped Fukaya category of plumbings

Plumbing spaces have drawn significant attention among symplectic topologists due to their natural occurrence as examples of Weinstein manifolds. In our paper, we provide a general formula for the wrapped Fukaya category of plumbings (with arbitrary grading structure) of cotangent bundles along any quiver. Our approach relies on "local-to-global" computations. Specifically, we compute the wrapped Fukaya category of "plumbing sectors" that serve as local models for the singularities of Lagrangian skeletons of plumbing spaces. As corollaries, we fully describe the wrapped Fukaya category of plumbing spaces in dimension $4$ and plumbings of $T^*S^n$ for $n \geq 3$. We show that any Ginzburg dg algebra/category of a graded quiver without potential is equivalent to the wrapped Fukaya category of a plumbing of $T^*S^n$ (with the corresponding grading structure).

math.SG↗

arXiv2024

A Computational Approach to the Homotopy Theory of DG categories

We give a specific cylinder functor for semifree dg categories. This allows us to construct a homotopy colimit functor explicitly. These two functors are "computable", specifically, the constructed cylinder functor sends a dg category of finite type, i.e., a semifree dg category having finitely many generating morphisms, to a dg category of finite type. The homotopy colimit functor has a similar property. Moreover, using the cylinder functor, we give a cofibration category of semifree dg categories and that of dg categories of finite type, independently from the work of Tabuada. All the results similarly work for semifree dg algebras. We also describe an application to symplectic topology and provide a toy example.

math.CT↗

arXiv2024

STT: Stateful Tracking with Transformers for Autonomous Driving

Tracking objects in three-dimensional space is critical for autonomous driving. To ensure safety while driving, the tracker must be able to reliably track objects across frames and accurately estimate their states such as velocity and acceleration in the present. Existing works frequently focus on the association task while either neglecting the model performance on state estimation or deploying complex heuristics to predict the states. In this paper, we propose STT, a Stateful Tracking model built with Transformers, that can consistently track objects in the scenes while also predicting their states accurately. STT consumes rich appearance, geometry, and motion signals through long term history of detections and is jointly optimized for both data association and state estimation tasks. Since the standard tracking metrics like MOTA and MOTP do not capture the combined performance of the two tasks in the wider spectrum of object states, we extend them with new metrics called S-MOTA and MOTPS that address this limitation. STT achieves competitive real-time performance on the Waymo Open Dataset.

cs.RO↗

arXiv2023

On Categorical Entropy from the viewpoint of Symplectic Topology

In this paper, motivated by symplectic topology, we explore categorical entropy and present two main results. The first result establishes a relation between categorical entropies of functors on a category and its localization. Additionally, it demonstrates analogies between the notions of topological and categorical entropy. This result is then applied to symplectic topology, where we provide a method for calculating the categorical entropy of a functor on a (partially) wrapped Fukaya category, assuming that the functor is induced by a compactly supported symplectic automorphism. For the second main result of the paper, we observe the existence of natural examples of symplectic manifolds whose Fukaya categories satisfy a type of Floer-theoretic duality. Motivated by this observation, we prove that categorical entropy can be computed from the morphism spaces under the assumption of duality. The formula is similar to the result of [DHKK14], which is proven for the case of smooth and proper categories.

math.SG↗

arXiv2023

Pseudo-Anosov autoquivalances arising from Symplectic topology and their hyperbolic actions on stability conditions

Within $N$-Calabi-Yau categories associated with quivers whose base graphs form trees, we delve into the study of the asymptotic behaviors of autoequivalences of a specific type. These autoequivalences, which we call "Penner type," exhibit straightforward asymptotic characteristics, making them noteworthy exemplars of "pseudo-Anosov" autoequivalences in the sense of \cite{Fan-Filip-Haiden-Katzarkov-Liu21}, and also in a stronger sense that we define in the present paper. In addition, we provide a practical methodology for calculating the stretching factors of Penner type autoequivalences. We expect that this computational approach can have applications. As an example, we establish a positive lower bound on the translation length of the induced action these autoequivalences have on the space of stability conditions. Our anticipation is that this lower bound is, in fact, exact. Notably, we have observed instances of Penner type $Φ$ where the induced actions align precisely with this lower bound. In other words, these examples induce hyperbolic actions on the space of stability conditions.

math.SG↗

arXiv2023

Atom-level design strategy for hydrogen evolution reaction of transition metal dichalcogenides catalysts

Two-dimensional transition metal dichalcogenides are among the most promising materials for water-splitting catalysts. While a variety of methods have been applied to promote the hydrogen evolution reaction on the transition metal dichalcogenides, doping of transition metal heteroatoms have attracted much attention since it provides effective ways to optimize the hydrogen adsorption and H2 generation reactions. Herein, we provide in-depth and systematic analyses on the trends of the free energy of hydrogen adsorption (ΔGH*), the most well-known descriptor for evaluating hydrogen evolution reaction performance, in the doped transition metal dichalcogenides. Using the total 150 doped transition metal dichalcogenides, we carried out the atom-level analysis on the origin of ΔGH* changes upon the transition metal heteroatom doping, and suggest two key factors that govern the hydrogen adsorption process on the doped transition metal dichalcogenides: 1) the changes in the charge of chalcogen atoms where hydrogen atoms adsorbed for the early transition metal doped structures, and 2) the structural deformation energies accompanying in introduced dopants for the late transition metal doped structures. Based on our findings, we interpret from a new perspective how vacancies in the TM-doped TMDs can provide optimal ΔGH* in HER. We suggest electrostatic control for early TM doped systems and structural control for late TM doped systems as the effective strategies for the thermoneutral ΔGH* in TMD.

cond-mat.mtrl-sci↗