arXiv subjects

Hideaki Takahashi

Publications and source records attributed to Hideaki Takahashi.

At least 19 recordsLinked to original sources

arXiv2026

Efficient Branch-and-Bound Testing and Verification of zkVMs

Zero-knowledge virtual machines (zkVMs) enable verifiable execution of general-purpose programs by translating virtual machine semantics into algebraic constraints over execution traces. The correctness of these constraints is critical: a single incorrect constraint can admit forged proofs (under-constrained) or reject valid executions (over-constrained). Existing approaches do not provide meaningful guarantees at production scale: fuzzers and unit tests often miss bugs, SMT solvers struggle with the size and nonlinearity of constraints, and theorem provers require substantial manual effort. We present ZEBRA, a fully automated verification and bug-detection framework: for a given program and input, the constraint must admit exactly one valid execution trace - no more and no fewer. This reduces zkVM verification to a solution-set cardinality problem over a canonical trace space, where redundancies such as null-row padding and non-deterministic permutations are eliminated prior to counting. To compute cardinality tractably, ZEBRA lifts analysis from finite-field witnesses to an integer interval lattice, exploiting a structural sparsity property of zkVM constraints: across 5 real-world zkVMs, constraints utilize only 14.0% of their theoretical connectivity capacity on average. This sparsity enables tight interval propagation with limited approximation error. ZEBRA performs a parallel branch-and-bound search that either produces a concrete counter-example or certifies the absence of violations within a bounded region. We evaluate ZEBRA on five real-world zkVMs. ZEBRA discovers 11 zero-day bugs; 6 have already been independently confirmed and 3 have been fixed by developers. Compared to SMT-based verification, ZEBRA is 51.5x faster, verifies 16.5 percentage point more instances, and its range verification provides up to 63x efficiency gain over repeated single-input verification.

cs.CR↗

arXiv2026

zkFuzz: Foundation and Framework for Effective Fuzzing of Zero-Knowledge Circuits

Zero-knowledge (ZK) circuits enable privacy-preserving computations and are central to many cryptographic protocols. Systems like Circom simplify ZK development by combining witness computation and circuit constraints in one program. However, even small errors can compromise security of ZK programs -- under-constrained circuits may accept invalid witnesses, while over-constrained ones may reject valid ones. Static analyzers are often imprecise with high false positives, and formal tools struggle with real-world circuit scale. Additionally, existing tools overlook several critical behaviors, such as intermediate computations and program aborts, and thus miss many vulnerabilities. Our theoretical contribution is the Trace-Constraint Consistency Test (TCCT), a foundational, language-independent formulation of ZK circuit bugs. TCCT provides a unified semantics that subsumes prior definitions and captures both under- and over-constrained vulnerabilities, exposing the full space of ZK bugs that elude prior tools. Our systems contribution is zkFuzz, a novel program mutation-based fuzzing framework for detecting TCCT violations. zkFuzz systematically mutates the computational logic of Zk programs guided by a novel fitness function, and injects carefully crafted inputs using tailored heuristics to expose bugs. We evaluated zkFuzz on 452 real-world ZK circuits written in Circom, a leading programming system for ZK development. zkFuzz successfully identified 85 bugs, including 59 zero-days-39 of which were confirmed by developers and \nfixed fixed, including bugs undetectable by prior works due to their fundamentally limited formulations, earning thousands of bug bounties. Our preliminary research on Noir, another emerging DSL for ZK circuit, also demonstrates the feasibility of zkFuzz to support multiple DSLs.

cs.CR↗

arXiv2026

Reduced Dynamical Maps in Finite Temperature Vibronic Coupling Models via Choi Matrices: Numerical Methods and Applications

We present a streamlined implementation of a computational framework for constructing and analyzing reduced dynamical maps for complex system--bath models at finite temperature. The methodology is based on three established ingredients of quantum dynamics: the Choi--Jamiołkowski isomorphism for the representation of quantum channels, thermofield (TFD) purification of thermal environments, and tensor-train (TT) propagation of the resulting enlarged pure state. The reduced map is obtained from a single unitary propagation in a thermofield-doubled Hilbert space and represented in matrix form through the Choi--Jamiołkowski isomorphism. The TFD evolution is implemented in the TT representation, enabling efficient propagation of high-dimensional purified thermal states. We illustrate the methodology for exciton transfer in the Fenna--Matthews--Olson complex with site-dependent structured spectral densities represented by discretized bosonic environments. The resulting maps are used to analyze decoherence, relaxation, and finite-memory effects, and to assess the crossover to an effectively time-local description. The proposed approach provides a route to compute reduced propagators and to post-process them into memory kernels, transfer tensors, and effective kinetic rate descriptions for complex molecular systems.

quant-ph↗

arXiv2025

Kinetic energy density functional based on electron distribution on the energy coordinate to describe covalent bond

The development of kinetic energy functional (KEF) is known as one of the most difficult subjects in the electronic density functional theory (DFT). In particular, the sound description of chemical bonds using a KEF is a matter of great significance in the field of theoretical physics and chemistry. It can be readily confirmed that the famous Thomas-Fermi (TF) model or the TF model corrected with a generalized gradient approximation (GGA) fails to realize the bound state of a covalent bond in general. In this work, a new kinetic energy functional is developed on the basis of the novel density functional theory (J. Phys. B: At. Mol. Opt. Phys. 51, 055102, 2018) that utilizes the electron distribution on the energy coordinate as the fundamental variable. It is demonstrated for an H$_2$ molecule that the bound state can be realized by the KEF by virtue of the property of the electron density on the energy coordinate. The mechanism underlying the formation of the bound state is the same as that for the realization of the static correlation in the exchange energy described with the new DFT. We also developed a method termed potential gradient method to make a correction to the TF model instead of the GGA approach.

physics.chem-ph↗

arXiv2024

Discretization of Structured Bosonic Environments at Finite Temperature by Interpolative Decomposition: Theory and Application

We present a comprehensive theory for a novel method to discretize the spectral density of a bosonic heat bath, as introduced in [H. Takahashi and R. Borrelli, J. Chem. Phys. \textbf{161}, 151101 (2024)]. The approach leverages a low-rank decomposition of the Fourier-transform relation connecting the bath correlation function to its spectral density. By capturing the time, frequency, and temperature dependencies encoded in the spectral density-autocorrelation function relation, our method significantly reduces the degrees of freedom required for simulating open quantum system dynamics. We benchmark our approach against existing methods and demonstrate its efficacy through applications to both simple models and a realistic electron transfer process in biological systems. Additionally, we show that this new approach can be effectively combined with the tensor-train formalism to investigate the quantum dynamics of systems interacting with complex non-Markovian environments. Finally, we provide a perspective on the selection and application of various spectral density discretization techniques.

quant-ph↗

arXiv2024

Effective Modeling of Open Quantum Systems by Low-rank Discretization of Structured Environments

The accurate description of the interaction of a quantum system with a its environment is a challenging problem ubiquitous across all areas of physics, and lies at the foundation of quantum mechanics theory. Here we pioneer a new strategy to create discrete low-rank models of the system-environment interaction, by exploiting the frequency and time domain information encoded in the fluctuation-dissipation relation connecting the system-bath correlation function and the spectral density. We demonstrate the effectiveness of our methodology by combining it with tensor-network methodologies and simulating the quantum dynamics of a complex excitonic systems in a highly structured bosonic environment. The new modeling framework sets the basis for a leap in the analysis of open quantum systems providing controlled accuracy at significantly reduced computational costs, with benefits in all connected research areas.

quant-ph↗

arXiv2024

VFLAIR: A Research Library and Benchmark for Vertical Federated Learning

Vertical Federated Learning (VFL) has emerged as a collaborative training paradigm that allows participants with different features of the same group of users to accomplish cooperative training without exposing their raw data or model parameters. VFL has gained significant attention for its research potential and real-world applications in recent years, but still faces substantial challenges, such as in defending various kinds of data inference and backdoor attacks. Moreover, most of existing VFL projects are industry-facing and not easily used for keeping track of the current research progress. To address this need, we present an extensible and lightweight VFL framework VFLAIR (available at https://github.com/FLAIR-THU/VFLAIR), which supports VFL training with a variety of models, datasets and protocols, along with standardized modules for comprehensive evaluations of attacks and defense strategies. We also benchmark 11 attacks and 8 defenses performance under different communication and model partition settings and draw concrete insights and recommendations on the choice of defense strategies for different practical VFL deployment scenarios.

cs.LG↗

arXiv2024

AIJack: Let's Hijack AI! Security and Privacy Risk Simulator for Machine Learning

This paper introduces AIJack, an open-source library designed to assess security and privacy risks associated with the training and deployment of machine learning models. Amid the growing interest in big data and AI, advancements in machine learning research and business are accelerating. However, recent studies reveal potential threats, such as the theft of training data and the manipulation of models by malicious attackers. Therefore, a comprehensive understanding of machine learning's security and privacy vulnerabilities is crucial for the safe integration of machine learning into real-world products. AIJack aims to address this need by providing a library with various attack and defense methods through a unified API. The library is publicly available on GitHub (https://github.com/Koukyosyumei/AIJack).

cs.LG↗

arXiv2024

A Simple and Accurate Method for Computing Optimized Effective Potentials for Exact Exchange Energy

The inverse Kohn-Sham density-functional theory (inv-KS) for the electron density of the Hartree-Fock (HF) wave function was revisited within the context of the optimized effective potential (HF- OEP). First, it is proved that the exchange potential created by the inv-KS is equivalent to the potential obtained by the HF-OEP when the HF-OEP realizes the HF energy of the system under consideration. Next the real-space grid (RSG) implementations of the inv-KS and the HF-OEP are addressed. The total HF energies EHF for the wave functions on the effective potentials optimized by the inv-KS are computed for a set of small molecules. It is found that the mean absolute deviation (MAD) of EHF from the HF energy is clearly smaller than the MAD of EHF, demonstrating that the inv-KS is advantageous in constructing the detailed structure of the exchange potential vx as compared with the HF-OEP. The inv-KS method is also applied to an ortho-benzyne radical known as a strongly correlated polyatomic molecule. It is revealed that the spin populations on the atomic sites computed by the UHF calculation can be faithfully reproduced by the wave functions on the inv-KS potential.

physics.chem-ph↗

arXiv2024

On the Transit Obfuscation Problem

Concealing an intermediate point on a route or visible from a route is an important goal in some transportation and surveillance scenarios. This paper studies the Transit Obfuscation Problem, the problem of traveling from some start location to an end location while "covering" a specific transit point that needs to be concealed from adversaries. We propose the notion of transit anonymity, a quantitative guarantee of the anonymity of a specific transit point, even with a powerful adversary with full knowledge of the path planning algorithm. We propose and evaluate planning/search algorithms that satisfy this anonymity criterion.

cs.AI↗

arXiv2024

Finite temperature dynamics in a polarized sub-Ohmic heat bath: a hierarchical equations of motion-tensor train study

Dynamics of the sub-Ohmic spin-boson model under polarized initial conditions at finite temperature is investigated by employing both analytical tools and the numerically accurate hierarchical equations of motion-tensor train method. By analyzing the features of nonequilibrium dynamics, we discovered a bifurcation phenomenon which separates two regimes of the dynamics. It is found that before the bifurcation time, increasing temperature slows down the population dynamics, while the opposite effect occurs after the bifurcation time. The dynamics is highly sensitive to both initial preparation of the bath and thermal effects.

physics.chem-ph↗

arXiv2023

Eliminating Label Leakage in Tree-Based Vertical Federated Learning

Vertical federated learning (VFL) enables multiple parties with disjoint features of a common user set to train a machine learning model without sharing their private data. Tree-based models have become prevalent in VFL due to their interpretability and efficiency. However, the vulnerability of tree-based VFL has not been sufficiently investigated. In this study, we first introduce a novel label inference attack, ID2Graph, which utilizes the sets of record IDs assigned to each node (i.e., instance space)to deduce private training labels. ID2Graph attack generates a graph structure from training samples, extracts communities from the graph, and clusters the local dataset using community information. To counteract label leakage from the instance space, we propose two effective defense mechanisms, Grafting-LDP, which improves the utility of label differential privacy with post-processing, and andID-LMID, which focuses on mutual information regularization. Comprehensive experiments on various datasets reveal that ID2Graph presents significant risks to tree-based models such as RandomForest and XGBoost. Further evaluations of these benchmarks demonstrate that our defense methods effectively mitigate label leakage in such instances

cs.LG↗

arXiv2023

Breaching FedMD: Image Recovery via Paired-Logits Inversion Attack

Federated Learning with Model Distillation (FedMD) is a nascent collaborative learning paradigm, where only output logits of public datasets are transmitted as distilled knowledge, instead of passing on private model parameters that are susceptible to gradient inversion attacks, a known privacy risk in federated learning. In this paper, we found that even though sharing output logits of public datasets is safer than directly sharing gradients, there still exists a substantial risk of data exposure caused by carefully designed malicious attacks. Our study shows that a malicious server can inject a PLI (Paired-Logits Inversion) attack against FedMD and its variants by training an inversion neural network that exploits the confidence gap between the server and client models. Experiments on multiple facial recognition datasets validate that under FedMD-like schemes, by using paired server-client logits of public datasets only, the malicious server is able to reconstruct private images on all tested benchmarks with a high success rate.

cs.CR↗

arXiv2023

Discretized hierarchical equations of motion in mixed Liouville--Wigner space for two-dimensional vibrational spectroscopies of liquid water

A model of a bulk water system describing the vibrational motion of intramolecular and intermolecular modes is constructed, enabling analysis of its linear and nonlinear vibrational spectra, as well as the energy transfer processes between the vibrational modes. The model is described as a system of four interacting anharmonic oscillators nonlinearly coupled to their respective heat baths. To perform a rigorous numerical investigation of the non-Markovian and nonperturbative quantum dissipative dynamics of the model, we derive discretized hierarchical equations of motion in mixed Liouville-Wigner space (DHEOM-MLWS), with Lagrange-Hermite mesh discretization being employed in the Liouville space of the intramolecular modes and Lagrange-Hermite mesh discretization and Hermite discretization in the Wigner space of the intermolecular modes. One-dimensional infrared and Raman spectra and two-dimensional terahertz-infrared-visible and infrared-infrared-Raman spectra are computed as demonstrations of the quantum dissipative description provided by our model.

physics.comp-ph↗

arXiv2023

Simulating two-dimensional correlation spectroscopies with third-order infrared and fifth-order infrared--Raman processes of liquid water

To investigate the possibility of measuring the intermolecular and intramolecular anharmonic coupling of balk water, we calculate third-order two-dimensional (2D) infrared (IR) spectra and fifth-order 2D IR-IR-Raman-Raman spectra expressed in terms of four-body correlation functions of optical observables. For this purpose, a multimode Brownian oscillator model of four interacting anharmonic oscillators strongly coupled to their respective heat baths is employed. The nonlinearity of the system-bath interactions is considered to describe thermal relaxation and vibrational dephasing. The linear and nonlinear spectra are then computed in a non-Markovian and nonperturbative regime in a rigorous manner using the discretized hierarchical equations of motion in mixed Liouville-Wigner space (DHEOM-MLWS). The calculated 2D spectra for stretching-bending, bending-librational, stretching-librational, and stretching-translational modes consist of various positive and negative peaks exhibiting essential details of the intermolecular and intramolecular mode-mode interactions under thermal relaxation and dephasing at finite temperature.

cond-mat.soft↗

arXiv2022

Development of Nonlocal Kinetic-Energy Density Functional for the Hybrid QM/MM Interaction

Development of the electronic kinetic-energy density functional is a subject of major interest in theoretical physics and chemistry. In this work, the nonlocal kinetic-energy functional is developed in terms of the response function for the molecular system to realize the orbital free density-functional theory(OF-DFT) to be utilized in the hybrid QM/MM(quantum mechanical/molecular mechanical) method. The present approach shows a clear contrast to the previous functionals where the homogeneous electron gas serves as a reference to build the response function. As a benchmark test we apply the method to a QM water molecule in a dimer system and that embedded in a condensed environment to make comparisons with the results given by the QM/MM calculations employing the Kohn-Sham DFT. It was found that the energetics and the polarization density of the QM solute under the influence of the MM environment can be adequately reproduced with our approach. This work suggests the potential ability of the kinetic-energy functional based on the response functions for the molecular reference systems.

physics.chem-ph↗

arXiv2021

Development of Kinetic Energy Density Functional Using Response Function Defined on the Energy Coordinate

A kinetic energy functional Ee was developed within the framework of the density-functional theory (DFT) based on the energy electron density for the purpose of realizing the orbital-free DFT. The functional includes the nonlocal term described with the linear-response function (LRF) of a reference system. As a notable feature of the present approach, the LRF is represented on the energy coordinate ε defined for each system of interest. In addition, an atomic system is taken as a reference system for the construction of the LRF, which shows a clear difference from the conventional approach based on the homogeneous electron gas. The explicit form of the functional Ee was formulated by means of the coupling-parameter integration scheme. The functional Ee kin kin was applied to the calculations of the kinetic energies of the pseudo atoms that mimics H, He, Ne, and Ar. Explicitly, the kinetic energy of each atom was computed using the functional Ee with respect to the variation of the valence charge Zv of each atom. In these calculations, the electron density n optimized by the Kohn-Sham DFT was adopted as an argument of the functional. It was found that the results are in excellent agreements with those given by the Kohn-Sham DFT. We also devised a method to perform the self-consistent field calculation utilizing the functional Ee . kin The method was applied to the computation of the radial distribution functions of the electrons in the pseudo Ne and Ar atoms. It was demonstrated that the results reasonably agree with those yielded by the Kohn-Sham DFT.

physics.comp-ph↗

arXiv2020

A Paradigm for Density Functional Theory Using Electron Distribution on the Energy Coordinate

Static correlation error(SCE) inevitably emerges when a dissociation of a covalent bond is described with a conventional denstiy-functional theory (DFT) for electrons. SCE gives rise to a serious overshoot in the potential energy at the dissociation limit even in the simplest molecules. The error is attributed to the basic framework of the approximate functional for the exchange correlation energy Exc which refers only to local properties at coordinate r, namely, the electron density n(r) and its derivatives. To solve the problem we developed a functional Ee which uses xc the energy electron distribution ne(e) as a fundamental variable in DFT. ne(e) is obtained by the projection of the density n(r) onto an energy coordinate e defined with the external potential of interest. The functional was applied to the dissociations of single, double, and triple bonds in small molecules showing reasonable agreements with the results given by a high level molecular orbitals theory. We also applied the functional to the computation of the energy change associated with spin depolarization and symmetrization in Carbon atom, which made an improvement over the conventional functional. This work opens the way for development of tougher functional that necessitates non-local properties of electrons such as kinetic energy functional.

physics.comp-ph↗