Holographic Invariant Storage uses vector architectures to ensure LLM safety at design time.
problem Mitigating context drift in large language models (LLMs) during deployment.
method Introduces Holographic Invariant Storage (HIS) protocol that combines known properties of bipolar Vector Symbolic Architectures into a design-time safety contract.
result Closed-form guarantees for single-signal recovery fidelity, continuous-noise robustness, and multi-signal capacity degradation are provided and validated.
Holographic energy equals Hamiltonian energy.
problem Equating holographic and Hamiltonian energies.
method Relative holographic and Hamiltonian energy comparison.
result Holographic energy is identical to Hamiltonian energy.
Holographic principle matches deformed Liouville theory action.
problem Matching deformed Liouville theory action in holography.
method Developed a holographic scheme involving bending energy.
result Perfect match between deformed theory actions on field and gravity sides.
Study improves pollen detection in optical and holographic images using deep learning.
problem Improving pollen detection accuracy in holographic microscopy images.
method Used YOLOv8s for detection and MobileNetV3L for classification, addressing performance gaps through dataset expansion and automated labeling.
result Significant improvement in detection and classification performance on holographic images.
Study uses holography to analyze entanglement entropy in deformed CFTs.
problem Analyzing entanglement entropy in $Tar{T}$-deformed CFTs.
method Holographic methods and direct bulk gravitational action evaluation.
result Agreement with known results for entanglement entropy.
We extend the holographic formula for the critical Q-curvature to all Q-curvatures.
This paper derives an explicit formula for Branson's Q-curvature in even-dimensional conformal geometry. The ingredients in the formula come from the Poincare metric in one higher dimension; hence the formula is called holographic. When specialized to the conformally flat case, the holographic formula expresses Q-curva…
In the presence of boundaries the integrated conformal anomaly is modified by the boundary terms so that the anomaly is non-vanishing in any (even or odd) dimension. The boundary terms are due to extrinsic curvature whose exact structure in d=3 and d=4 has recently been identified. In this note we present a hologra…
New framework constructs holographic tensor networks using hyperbolic buildings.
problem Building holographic tensor networks for non-integer dimensions and fractal spaces.
method Introducing a unifying framework based on hyperbolic buildings and dualities.
result Constructs a family of bulk regions satisfying complementary recovery and Ryu-Takayanagi formula.
Any traversally generic vector flow on a compact manifold X with boundary leaves some residual structure on its boundary $\d X$. A part of this structure is the flow-generated causality map Cv, which takes a region of $\d X$ to the complementary region. By the Holography Theorem from \cite{K4}, the map Cv allow…
Bit threads provide an alternative description of holographic entanglement, replacing the Ryu-Takayanagi minimal surface with bulk curves connecting pairs of boundary points. We use bit threads to prove the monogamy of mutual information (MMI) property of holographic entanglement entropies. This is accomplished using t…
Learning embeddings of entities and relations is an efficient and versatile method to perform machine learning on relational data such as knowledge graphs. In this work, we propose holographic embeddings (HolE) to learn compositional vector space representations of entire knowledge graphs. The proposed method is relate…
HGConv uses HRR to efficiently detect malware, outperforming existing methods.
problem Efficiently detecting malware with long sequences.
method Holographic Global Convolutional Networks (HGConv) utilizing Holographic Reduced Representations (HRR).
result Achieved state-of-the-art results on malware benchmarks.
Researchers create holographic super-embeddings for M5 and M2 branes.
problem No concrete examples of super-embeddings for M5 and M2 branes existed.
method Constructed explicit holographic super-embeddings of probe M5 and M2 branes into their super-AdS backgrounds.
result Explicit holographic super-embeddings of M5 and M2 branes were successfully constructed.
Representation learning is at the heart of what makes deep learning effective. In this work, we introduce a new framework for representation learning that we call "Holographic Neural Architectures" (HNAs). In the same way that an observer can experience the 3D structure of a holographed object by looking at its hologra…
Secure neural network inference on untrusted platforms using holographic reduced representations.
problem Secure neural network inference on untrusted platforms.
method Connectionist Symbolic Pseudo Secrets using Holographic Reduced Representations (HRR).
result Empirical robustness to attack under various threat models.
We formulate the holographic principle for knots and links. For the "space" of all knots and links, torus knots T(2m+1,2) and torus links L(2m,2) play the role of the "boundary" of this space. Using the holographic principle, we find the skein relation of knots and links with the help of the recurrence relation for pol…
AI enhances pollen recognition in veterinary imaging using holographic microscopy.
problem Challenges in recognizing pollen in holographic images due to speckle noise and artifacts.
method Training YOLOv8s and MobileNetV3L on dual-modality dataset, employing WGAN-SN for synthetic data augmentation.
result GAN-based augmentation improves object detection and classification in holographic images, closing the performance gap.
New method makes neural networks transparent, revealing learning modes.
problem Lack of interpretability in neural networks.
method Weight pathway analysis (WPA) to decompose neural networks into subnetworks.
result Neural networks store and utilize information holographically, with linear and nonlinear learning modes.
Generalizes holographic method to higher codimension submanifolds.
problem Extract higher-order local invariants of embeddings.
method Natural generalization of holographic method to higher codimension submanifolds.
result New invariants obstructing the order-by-order construction of unit defining maps.
We prove that the boundary of the future of a surface K consists precisely of the points p that lie on a null geodesic orthogonal to K such that between K and p there are no points conjugate to K nor intersections with another such geodesic. Our theorem has applications to holographic screens and their asso…
Deep learning tackles low-photon nanoscale holographic phase retrieval.
problem Low-photon imaging challenges at nanoscale.
method Dataset-free deep learning framework with physical model integration.
result Significantly improves signal recovery from higher noise levels.
Minkowski space is a physically important space-time for which the finding an adequate holographic description is an urgent problem. In this paper we develop further the proposal made in hep-th/0303006 for the description as a duality between Minkowski space-time and a Conformal Field Theory defined on the boundary of …
The holographic duality can be extended to include quantum theories with broken coordinate invariance leading to the appearance of the gravitational anomalies. On the gravity side one adds the gravitational Chern-Simons term to the bulk action which gauge invariance is only up to the boundary terms. We analyze in detai…
We develop a systematic method for renormalizing the AdS/CFT prescription for computing correlation functions. This involves regularizing the bulk on-shell supergravity action in a covariant way, computing all divergences, adding counterterms to cancel them and then removing the regulator. We explicitly work out the ca…
We argue that Horava-Lifshitz (HL) gravity provides the minimal holographic dual for Lifshitz-type field theories with anisotropic scaling and dynamical exponent z. First we show that Lifshitz spacetimes are vacuum solutions of HL gravity, without need for additional matter. Then we perform holographic renormalization …
A learning algorithm optimizes beamforming for holographic transceivers in far-field communication.
problem Optimal phase-shifts for beamforming in holographic transceivers are challenging due to unknown receiver locations and large phase-shifts.
method Developed a learning algorithm using a fixed-budget multi-armed bandit framework to learn optimal phase-shifts.
result The algorithm, HoloBeam, outperforms state-of-the-art methods in beamforming optimization.
We show that holographic renormalization of relativistic gravity in asymptotically Lifshitz spacetimes naturally reproduces the structure of gravity with anisotropic scaling: The holographic counterterms induced near anisotropic infinity take the form of the action for gravity at a Lifshitz point, with the appropriate …
Game theory models storage investment to balance market competition and profits.
problem Strategic storage investment impacts electricity market prices and revenues.
method Formulated a non-cooperative game between investors to model strategic storage decisions.
result Increasing storage capacity reduces individual profits but increases total investment.
We prove the conjecture that a monopole in three-dimensional anti-de Sitter space can be completely determined by its ``holographic'' image on the conformal boundary two-sphere.
We prove universal recursive formulas for Branson's Q-curvatures in terms of respective lower-order Q-curvatures, lower-order GJMS-operators and holographic coefficients.
Study on bit threads and their locking properties in holographic spacetimes.
problem Understanding the conditions under which regions can be locked in holographic spacetimes.
method Investigation of different density bounds and their implications on the locking of regions.
result Non-crossing regions can be locked under the most stringent bound, but crossing regions cannot.
New method assesses energy storage value beyond cost reduction.
problem Improving energy storage value beyond cost reduction.
method Market potential method to evaluate and compare energy storage technologies.
result High-cost hydrogen storage can be more valuable than low-cost hydrogen storage.
Suppose that Σ=∂Ω is the n-dimensional boundary, with positive (inward) mean curvature H, of a connected compact (n+1)-dimensional Riemannian spin manifold (Ωn+1,g) whose scalar curvature R≥−n(n+1)k2, for some $k\textgreater{}0$. If Σ admits an isometric and isospin immersion F into the hy…
Study on energy storage's impact on electricity prices and profitability.
problem Analyzing the profitability of energy storage in electricity markets.
method Characterized optimal operating strategy for storage systems, determined equilibrium price in a market with storage, renewables, and conventional producers, and characterized price process using stochastic differential equations.
result Increased average revenues and interquantile ranges for storage assets in energy transition scenarios.
The Ryu-Takayanagi (RT) formula relates the entanglement entropy of a region in a holographic theory to the area of a corresponding bulk minimal surface. Using the max flow-min cut principle, a theorem from network theory, we rewrite the RT formula in a way that does not make reference to the minimal surface. Instead, …
We define a holographic dual to the Donaldson-Witten topological twist of N=2 gauge theories on a Riemannian four-manifold. This is described by a class of asymptotically locally hyperbolic solutions to N=4 gauged supergravity in five dimensions, with the four-manifold as conformal boundary. Und…
In this paper, we initiate the study of holographic renormalization group flows acting on the metric of four-manifolds. In particular, we derive a set of equations which govern the evolution of a generic Kähler four-manifold along the renormalization group flow in seven-dimensional gauged supergravity. The physical ele…
Using holographic renormalization coupled with the Caffarelli/Silvestre\cite{caffarelli} extension theorem, we calculate the precise form of the boundary operator dual to a bulk scalar field rather than just its average value. We show that even in the presence of interactions in the bulk, the boundary operator dual to …
In the first part of this paper we provide a short introduction to the AdS/CFT correspondence and to holographic renormalization. We discuss how QFT correlation functions, Ward identities and anomalies are encoded in the bulk geometry. In the second part we develop a Hamiltonian approach to the method of holographic re…
Paper provides a method to price electricity storage contracts using COS technique.
problem Valuation of electricity storage contracts considering physical and operational constraints.
method Uses Fourier-based COS method to price contracts based on stochastic polynomial process.
result The COS method accurately and efficiently prices electricity storage contracts.
Generative models improve carbon storage site prediction using Bayesian inversion.
problem Predicting suitable geologic sites for long-term carbon dioxide storage.
method Generative adversarial networks and Bayesian inversion to condition models on physical measurements and historic data.
result Improved resolution of carbon dioxide storage capacity forecasts.
Hrrformer uses HRR to speed up self-attention for long sequences.
problem Infeasibility of using transformers with very long sequence lengths.
method Re-cast self-attention using Holographic Reduced Representations (HRR).
result Achieves near state-of-the-art accuracy with O(THlogH) time complexity and O(TH) space complexity. Paper proposes a risk-averse approach to energy storage price arbitrage using conformal uncertainty quantification.
problem Inherent volatility and uncertainty of real-time electricity prices create financial risks for storage arbitrage.
method Two-layer prediction model with conformal uncertainty quantification for high coverage of real-time price uncertainty.
result The framework achieves good profit margins with minimal losses, demonstrating effectiveness in real-time market.
A 'holographic formula' expressing the functional determinant of the scattering operator in an asymptotically locally anti-de Sitter(ALAdS) space has been proposed in terms of a relative functional determinant of the scalar Laplacian in the bulk. It stems from considerations in AdS/CFT correspondence of a quantum corre…
It has been known for a long time that the classical spherical perceptrons can be used as storage memories. Seminal work of Gardner, \cite{Gar88}, started an analytical study of perceptrons storage abilities. Many of the Gardner's predictions obtained through statistical mechanics tools have been rigorously justified. …
Active learning method for neural population dynamics using optogenetics.
problem Efficiently selecting neurons to stimulate for identifying neural population dynamics.
method Developed active learning procedure for low-rank regression to determine informative photostimulation patterns.
result Demonstrated a two-fold reduction in data required for predictive power using low-rank linear dynamical systems model.
Framework uses RL and simulation for optimal microgrid energy storage planning.
problem Optimal investment in diverse energy storage technologies for microgrids.
method Combines reinforcement learning with simulation-based optimization for long-term planning.
result Derives better engineering solutions for future microgrid applications.