papers

Publications (23)

quant-ph2026

AI Agents for Variational Quantum Circuit Design

Marco Knipfer, Alexander Roman, Konstantin T. Matchev +2

Variational quantum circuits (VQCs) constitute a central building block of near-term quantum machine learning (QML), yet the principled design of expressive and trainable architect…

cs.AI2026

Orchestral AI: A Framework for Agent Orchestration

Alexander Roman, Jacob Roman

The rapid proliferation of LLM agent frameworks has forced developers to choose between vendor lock-in through provider-specific SDKs and complex multi-package ecosystems that obsc…

hep-ph2022

Uncertainties associated with GAN-generated datasets in high energy physics

Konstantin T. Matchev, Alexander Roman, Prasanth Shyamsundar

Recently, Generative Adversarial Networks (GANs) trained on samples of traditionally simulated collider events have been proposed as a way of generating larger simulated datasets a…

hep-ph2026

Agentic Diagrammatica: Towards Autonomous Symbolic Computation in High Energy Physics

Tony Menzo, Alexander Roman, George T. Fleming +3

We present Diagrammatica, a symbolic computation extension to the HEPTAPOD agentic framework, which enables LLM agents to plan and execute multi-step theoretical calculations. Symb…

hep-th2023

Accelerated Discovery of Machine-Learned Symmetries: Deriving the Exceptional Lie Groups G2, F4 and E6

Roy T. Forestano, Konstantin T. Matchev, Katia Matcheva +3

Recent work has applied supervised deep learning to derive continuous symmetry transformations that preserve the data labels and to obtain the corresponding algebras of symmetry ge…

hep-ph2023

Discovering Sparse Representations of Lie Groups with Machine Learning

Roy T. Forestano, Konstantin T. Matchev, Katia Matcheva +3

Recent work has used deep learning to derive symmetry transformations, which preserve conserved quantities, and to obtain the corresponding algebras of generators. In this letter,…

quant-ph2026

Analytical Landscape of Maximal Magic for Two-Qutrit States and Beyond

Marco Knipfer, Alexander Roman, Katia Matcheva +1

Achieving a genuine quantum advantage relies on two distinct non-classical resources that restrict efficient classical simulation: entanglement and magic (nonstabilizerness). We in…

hep-ph2023

Deep Learning Symmetries and Their Lie Groups, Algebras, and Subalgebras from First Principles

Roy T. Forestano, Konstantin T. Matchev, Katia Matcheva +3

We design a deep-learning algorithm for the discovery and identification of the continuous group of symmetries present in a labeled dataset. We use fully connected neural networks…

astro-ph.EP2022

Transverse Vector Decomposition Method for Analytical Inversion of Exoplanet Transit Spectra

Konstantin T. Matchev, Katia Matcheva, Alexander Roman

We develop a new method for analytical inversion of binned exoplanet transit spectra and for retrieval of planet parameters. The method has a geometrical interpretation and treats…

astro-ph.EP2021

Analytical Modelling of Exoplanet Transit Specroscopy with Dimensional Analysis and Symbolic Regression

Konstantin T. Matchev, Katia Matcheva, Alexander Roman

The physical characteristics and atmospheric chemical composition of newly discovered exoplanets are often inferred from their transit spectra which are obtained from complex numer…

cs.AI2026

Towards Shutdownable Agents via Stochastic Choice

Elliott Thornley, Alexander Roman, Christos Ziakas +2

The POST-Agents Proposal (PAP) is an idea for ensuring that advanced artificial agents never resist shutdown. A key part of the PAP is using a novel `Discounted Reward for Same-Len…

cs.LG2023

Oracle-Preserving Latent Flows

Alexander Roman, Roy T. Forestano, Konstantin T. Matchev +2

We develop a deep learning methodology for the simultaneous discovery of multiple nontrivial continuous symmetries across an entire labelled dataset. The symmetry transformations a…

astro-ph.EP2026

Hunting for "Oddballs" with Machine Learning: Detecting Anomalous Exoplanets Using a Deep-Learned Low-Dimensional Representation of Transit Spectra with Autoencoders

Alexander Roman, Emilie Panek, Roy T. Forestano +3

This study explores the application of autoencoder-based machine learning techniques for anomaly detection to identify exoplanet atmospheres with unconventional chemical signatures…

hep-ph2021

Finding Wombling Boundaries in LHC Data with Voronoi and Delaunay Tessellations

Konstantin T. Matchev, Alexander Roman, Prasanth Shyamsundar

We address the problem of finding a wombling boundary in point data generated by a general Poisson point process, a specific example of which is an LHC event sample distributed in…

astro-ph.EP2026

Balancing Variety and Sample Size: Optimal Parameter Sampling for Ariel Target Selection

Emilie Panek, Alexander Roman, Katia Matcheva +2

Targeted astrophysical surveys are limited by the amount of telescope time available, which makes it impossible to observe every single object of interest. In order to maximize the…

hep-ph2023

Identifying the Group-Theoretic Structure of Machine-Learned Symmetries

Roy T. Forestano, Konstantin T. Matchev, Katia Matcheva +3

Deep learning was recently successfully used in deriving symmetry transformations that preserve important physics quantities. Being completely agnostic, these techniques postpone t…

astro-ph.HE2016

Constraints on the FRB rate at 700-900 MHz

Liam Connor, Hsiu-Hsien Lin, Kiyoshi Masui +5

Estimating the all-sky rate of fast radio bursts (FRBs) has been difficult due to small-number statistics and the fact that they are seen by disparate surveys in different regions…

hep-ph2025

HEPTAPOD: Orchestrating High Energy Physics Workflows Towards Autonomous Agency

Tony Menzo, Alexander Roman, Sergei Gleyzer +5

Many theoretical and experimental workflows in high-energy-physics (HEP) stand to benefit from recent advances in transformer-based large language models (LLMs). While early applic…

quant-ph2026

The Pareto Frontiers of Magic and Entanglement: The Case of Two Qubits

Alexander Roman, Marco Knipfer, Jogi Suda Neto +3

Magic and entanglement are two measures that are widely used to characterize quantum resources. We study the interplay between magic and entanglement in two-qubit systems, focusing…

astro-ph.EP2022

Unsupervised Machine Learning for Exploratory Data Analysis of Exoplanet Transmission Spectra

Konstantin T. Matchev, Katia Matcheva, Alexander Roman

Transit spectroscopy is a powerful tool to decode the chemical composition of the atmospheres of extrasolar planets. In this paper we focus on unsupervised techniques for analyzing…

astro-ph.EP2026

ASTER -- Agentic Science Toolkit for Exoplanet Research

Emilie Panek, Alexander Roman, Gaurav Shukla +3

The expansion of exoplanet observations has created a need for flexible, accessible, and user-friendly workflows. Transmission spectroscopy has become a key technique for probing a…

astro-ph.HE2015

Dense magnetized plasma associated with a fast radio burst

Kiyoshi Masui, Hsiu-Hsien Lin, Jonathan Sievers +15

Fast Radio Bursts are bright, unresolved, non-repeating, broadband, millisecond flashes, found primarily at high Galactic latitudes, with dispersion measures much larger than expec…

cs.AI2026

Towards Shutdownable Agents: Generalizing Stochastic Choice in RL Agents and LLMs

Carissa Cullen, Harry Garland, Alexander Roman +3

Misaligned artificial agents might resist shutdown. One proposed solution is to train agents to lack preferences between different-length trajectories. The Discounted Reward for Sa…