A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.
Derives exact gradients for linear optics with single photons.
The paper extends IPC framework to stationary physical systems and validates it with a photonic system.
Photonic chip speeds up option pricing with GAN for financial efficiency.
We show a uniqueness result for the n-dimensional spatial Reissner-Nordström manifold: a static, electrovacuum, asymptotically flat system which is asymptotically Reissner-Nordström is a subextremal Reissner-Nordström manifold with positive mass, provided that its inner boundary is a (possibly disconnected) photon sphe…
Study on black holes and photon surfaces in 4D spacetimes, proving uniqueness theorems.
Photonic co-processor speeds up training of large neural networks.
The paper analyzes the performance of delay-based reservoir computing using eigenvalue analysis.
Active learning method for neural population dynamics using optogenetics.
Characterizes photon surfaces in static spacetimes, proving uniqueness.
Optical co-processor speeds up neural network training.
The paper develops methods for monitoring TPL machine health.
Paper proves uniqueness of black holes and photon surfaces in higher dimensions.
In a recent paper the first author established the uniqueness of photon spheres, suitably defined, in static vacuum asymptotically flat spacetimes by adapting Israel's proof of static black hole uniqueness. In this note we establish uniqueness of photon spheres by adapting the argument of Bunting and Masood-ul-Alam, wh…
The paper simplifies FLRW photon propagators using geometric embeddings.
Predicts coherence from quantum heat engine noise using machine learning.
Photon surfaces are timelike, totally umbilic hypersurfaces of Lorentzian spacetimes. In the first part of this paper, we locally characterize all possible photon surfaces in a class of static, spherically symmetric spacetimes that includes Schwarzschild, Reissner--Nordström, Schwarzschild-anti de Sitter, etc., in $n+1…
Photonic quantum reinforcement learning for control problems.
Machine learning classifies topological phases in leaky photonic lattices.
Enhances quantum machine learning models using Fock states.
Study improves chiral photonic metasurface design using neural networks and genetic algorithms.
Performance of nuclear threat detection systems based on gamma-ray spectrometry often strongly depends on the ability to identify the part of measured signal that can be attributed to background radiation. We have successfully applied a method based on Principal Component Analysis (PCA) to obtain a compact null-space m…
New proofs of unique photon surfaces in 4D spacetimes, extending previous work.
We study the set of trapped photons of a subcritical (a<M) Kerr spacetime as a subset of the phase space. First, we present an explicit proof that the photons of constant Boyer--Lindquist coordinate radius are the only photons in the Kerr exterior region that are trapped in the sense that they stay away both from the h…
Adapting Israel's proof of static black hole uniqueness, we show that the Schwarzschild spacetime is the only static vacuum asymptotically flat spacetime that possesses a suitably defined photon sphere.
In a recent paper, the authors established the uniqueness of photon spheres in static vacuum asymptotically flat spacetimes by adapting Bunting and Masood-ul-Alam's proof of static vacuum black hole uniqueness. Here, we establish uniqueness of suitably defined sub-extremal photon spheres in static electro-vacuum asympt…
Unified framework for photon and massive particle hypersurfaces in stationary spacetimes.
Most cryptocurrencies rely on Proof-of-Work (PoW) "mining" for resistance to Sybil and double-spending attacks, as well as a mechanism for currency issuance. Hashcash PoW has successfully secured the Bitcoin network since its inception, however, as the network has expanded to take on additional value storage and transa…
Designs chiral photonic structures using machine learning for efficient optical properties.
We propose a method to build quantum memristors in quantum photonic platforms. We firstly design an effective beam splitter, which is tunable in real-time, by means of a Mach-Zehnder-type array with two equal 50:50 beam splitters and a tunable retarder, which allows us to control its reflectivity. Then, we show that th…
Diffuse optical tomography (DOT) has been investigated as an alternative imaging modality for breast cancer detection thanks to its excellent contrast to hemoglobin oxidization level. However, due to the complicated non-linear photon scattering physics and ill-posedness, the conventional reconstruction algorithms are s…
New approach confirms Kruskal-Szekeres extension for Schwarzschild spacetime.
Quantum computing at room temperature achieves high accuracy in image classification.
The implementation of artificial neural networks in hardware substrates is a major interdisciplinary enterprise. Well suited candidates for physical implementations must combine nonlinear neurons with dedicated and efficient hardware solutions for both connectivity and training. Reservoir computing addresses the proble…
Proves a Minkowski inequality for static Einstein-Maxwell space-time.
We propose a conceptual design for a quantum blockchain. Our method involves encoding the blockchain into a temporal GHZ (Greenberger-Horne-Zeilinger) state of photons that do not simultaneously coexist. It is shown that the entanglement in time, as opposed to an entanglement in space, provides the crucial quantum adva…
We study the Bondi-Sachs rockets with nonzero cosmological constant. We observe that the acceleration of the systems arises naturally in the asymptotic symmetries of (anti-) de Sitter spacetimes. Assuming the validity of the concepts of energy and mass previously introduced in asymptotically flat spacetimes, we find th…
Detecting a change point is a crucial task in statistics that has been recently extended to the quantum realm. A source state generator that emits a series of single photons in a default state suffers an alteration at some point and starts to emit photons in a mutated state. The problem consists in identifying the poin…
Paper proves rigidity of static manifolds and applies to metric extensions.
Calcium imaging has revolutionized systems neuroscience, providing the ability to image large neural populations with single-cell resolution. The resulting datasets are quite large, which has presented a barrier to routine open sharing of this data, slowing progress in reproducible research. State of the art methods fo…
New model enhances SPIM for solving low-rank combinatorial optimization and statistical learning problems.
This thesis discusses the Newtonian limit of General Relativity for static isolated systems with compactly supported matter. We call these systems "geometrostatic" to underline their geometric nature. We introduce new quasi-local notions of mass and center of mass that can be read off locally in the vicinity of the mat…
Study maximal representations of surface groups via pleated surfaces in pseudo-Riemannian space.
Study null energy condition impacts on special hypersurfaces in static spacetimes.
We apply numerical methods in combination with finite-difference-time-domain (FDTD) simulations to optimize transmission properties of plasmonic mirror color filters using a multi-objective figure of merit over a five-dimensional parameter space by utilizing novel multi-fidelity Gaussian processes approach. We compare …
This paper is devoted to the study of the Reissner-Nordstrøm-de Sitter black holes and their maximal analytic extensions. In particular, we study some of their properties that lays the groundwork for separate papers where we obtain decay results and construct conformal scattering theories for test fields on such spacet…
How useful can machine learning be in a quantum laboratory? Here we raise the question of the potential of intelligent machines in the context of scientific research. A major motivation for the present work is the unknown reachability of various entanglement classes in quantum experiments. We investigate this question …
Paper tackles Bayesian image restoration in low-photon Poisson imaging problems.
This article is written for the online newspaper "The Photon" published by the Department of Physics, University of Maryland. The article describes econophysics research done in the group of Victor Yakovenko. It briefly surveys the subjects "Statistical Mechanics of Money, Income, and Wealth" and "Probability Distribut…