Tootfinder

BenchRL-QAS: Benchmarking reinforcement learning algorithms for quantum architecture search
Azhar Ikhtiarudin, Aditi Das, Param Thakkar, Akash Kundu
https://arxiv.org/abs/2507.12189

BenchRL-QAS: Benchmarking reinforcement learning algorithms for quantum architecture search
We introduce BenchRL-QAS, a unified benchmarking framework for systematically evaluating reinforcement learning (RL) algorithms in quantum architecture search (QAS) across diverse variational quantum algorithm tasks and system sizes ranging from 2- to 8-qubit. Our study benchmarks nine RL agents including both value-based and policy-gradient methods on representative quantum problems such as variational quantum eigensolver, variational quantum state diagonalization, quantum classification, and …

Mallows Model with Learned Distance Metrics: Sampling and Maximum Likelihood Estimation
Yeganeh Alimohammadi, Kiana Asgari
https://arxiv.org/abs/2507.08108

Mallows Model with Learned Distance Metrics: Sampling and Maximum Likelihood Estimation
\textit{Mallows model} is a widely-used probabilistic framework for learning from ranking data, with applications ranging from recommendation systems and voting to aligning language models with human preferences~\cite{chen2024mallows, kleinberg2021algorithmic, rafailov2024direct}. Under this model, observed rankings are noisy perturbations of a central ranking $σ$, with likelihood decaying exponentially in distance from $σ$, i.e, $P (π) \propto \exp\big(-β\cdot d(π, σ)\big),$ where $β> 0…

LeanExplore: A search engine for Lean 4 declarations
Justin Asher (Independent Researcher)
https://arxiv.org/abs/2506.11085 https://a…

LeanExplore: A search engine for Lean 4 declarations
The expanding Lean 4 ecosystem poses challenges for navigating its vast libraries. This paper introduces LeanExplore, a search engine for Lean 4 declarations. LeanExplore enables users to semantically search for statements, both formally and informally, across select Lean 4 packages (including Batteries, Init, Lean, Mathlib, PhysLean, and Std). This search capability is powered by a hybrid ranking strategy, integrating scores from a multi-source semantic embedding model (capturing conceptual me…

Welcome to "rowhome"!
As usual, you can count on real estate marketers to signal status shifts.
"Townhome," invented because "rowhouse" felt low-class, now feels low-class itself.
I think they would have done better to just say "rowhouse" and invoke the prestige of historic preservation.

Check out some renderings for Woodley Park’s Wardman Park!! (the former Marriott Wardman) - PoPville
Renderings are courtesy Wardman Park From a press release: "Carmel Partners announced today the start of pre-leasing for Aerie, the first residential tower to open at Wardman Park, a reimagined, 9.5-acre landmark property now home to a resort-style residential oasis. Set atop one of the city’s highest elevations in Woodley Park, Wardman Park is defined

3D forest semantic segmentation using multispectral LiDAR and 3D deep learning
Narges Takhtkeshha, Lauris Bocaux, Lassi Ruoppa, Fabio Remondino, Gottfried Mandlburger, Antero Kukko, Juha Hyypp\"a
https://arxiv.org/abs/2507.08025

3D forest semantic segmentation using multispectral LiDAR and 3D deep learning
Conservation and decision-making regarding forest resources necessitate regular forest inventory. Light detection and ranging (LiDAR) in laser scanning systems has gained significant attention over the past two decades as a remote and non-destructive solution to streamline the labor-intensive and time-consuming procedure of forest inventory. Advanced multispectral (MS) LiDAR systems simultaneously acquire three-dimensional (3D) spatial and spectral information across multiple wavelengths of the…

Cowboys new backup QB outranks 10 drafted higher, including 2 first-round picks https://cowboyswire.usatoday.com/story/sports/nfl/cowboys/2025/06/04/cowboys-milton-backup-qb-rankings-2025/84029638007/

Never Trust the Manufacturer, Never Trust the Client: A Novel Method for Streaming STL Files for Secure Additive
Seyed Ali Ghazi Asgar, Narasimha Reddy, Satish T. S. Bukkapatnam
https://arxiv.org/abs/2507.06421

Never Trust the Manufacturer, Never Trust the Client: A Novel Method for Streaming STL Files for Secure Additive
While additive manufacturing has opened interesting avenues to reimagine manufacturing as a service (MaaS) platform, transmission of design files from client to manufacturer over networks opens up many cybersecurity challenges. Securing client's intellectual property (IP) especially from cyber-attacks emerges as a major challenge. Earlier works introduced streaming, instead of sharing process plan (G-code) files, as a possible solution. However, executing client's G-codes on manufacturer's mach…

#ndwgoecountdown Jupiter: Gasriese im Sonnensystem
Jupiter ist der größte Planet im Sonnensystem; seine Wolkenwirbel und -bänder geben uns Rätsel auf. Unter Eisschichten verbergen seine Monde Europa und Ganymed Ozeane, in denen sich Leben entwickelt haben könnte. Das MPS stellt Weltrauminstrumente vor, die an Bord der Raumsonde JUICE auf dem Weg zum Jupiter sind. Mit Wolkenwir…

Exploring Year-timescale Gamma-ray Quasi-Periodic Oscillations in Blazars: Evidence for Supermassive Binary Black Holes Scenario
Ajay Sharma, Sakshi Chaudhary, Aishwarya Sarath, Debanjan Bose
https://arxiv.org/abs/2505.23697

Exploring Year-timescale Gamma-ray Quasi-Periodic Oscillations in Blazars: Evidence for Supermassive Binary Black Holes Scenario
A comprehensive analysis of quasi-periodic oscillations (QPOs) in the gamma-ray emissions of blazars. Utilizing 15 years of Fermi-LAT observations of seven blazars in our sample, we identify both long-term and transient quasi-periodic oscillations in the gamma-ray light curves, with timescales ranging from a few months to years. These periodicities were detected using the Lomb-Scargle periodogram and REDFIT techniques. To robustly evaluate the statistical significance of the quasi-periodic sign…