paper / benbloom / 11d ago
This paper extends the construction of Day convolution to a broader range of structures within ∞-categorical algebra. It provides a necessary and sufficient criterion for exponentiable objects in diverse structures like (equivariant) ∞-operads and virtual double ∞-categories. The work leverages the framework of algebraic patterns (Chu-Haugseng) and introduces a new description of weak Segal fibrations using generalized Segal spaces.
category-theoryalgebraic-topologyinfinity-categoriesoperadssegal-fibrationsday-convolution
“The paper characterizes exponentiable objects for various structures in ∞-categorical algebra.”
paper / benbloom / 22d ago
Traditional runtime verification with privacy is hampered by computationally expensive cryptographic primitives. This work proposes a distributed monitoring architecture utilizing efficient secret-sharing schemes. This approach significantly reduces overhead, enabling practical real-time privacy-preserving monitoring.
distributed-systemsprivacy-preservingsecret-sharingruntime-verificationcryptographyscalable-monitoring
“Traditional privacy-preserving runtime verification is computationally expensive due to heavy cryptographic primitives.”
paper / benbloom / Feb 28
This paper presents a data-driven approach using the Discrete Laplacian Cell Mechanics (DLCM) framework to model fibroblast-driven wound closure. By integrating in vitro time-lapse microscopy data, the model demonstrates proficient replication of experimental trends. The core insight is that G1 phase arrest and initial spatial arrangement of cell cycle states significantly impact wound healing, providing a quantitative link between single-cell dynamics and emergent tissue behavior.
cell-mechanicscomputational-biologywound-healingdata-driven-modelingtissue-engineering
“The Discrete Laplacian Cell Mechanics (DLCM) framework, when driven by time-lapse microscopy data, can reproduce essential experimental trends in fibroblast-driven wound closure.”
paper / benbloom / Feb 19
This paper outlines a strategic vision for integrating Artificial Intelligence (AI) into experimental particle physics. It identifies key challenges and proposes a roadmap for current and future facilities, such as HL-LHC, DUNE, EIC, FCC-ee, and IceCube-Gen2, to leverage AI for accelerating discovery. The authors advocate for a national-scale collaboration between DOE laboratories and universities to realize an "AI-native" research ecosystem.
ai-in-scienceparticle-physicsresearch-ecosystemexperimental-physicsai-native-experimentsscientific-collaboration
“AI can accelerate discovery in experimental particle physics.”
paper / benbloom / Feb 18
This paper investigates the structural properties of finite integer sets $A$ when the $L_1$ norm of the Fourier transform of its characteristic function, $||\widehat{1_A}||_1$, is bounded by $K\log N$. It demonstrates that such sets must contain a large subset with small sumset, and consequently, an arithmetic progression of significant length. The work also refines the constant in the original Littlewood conjecture.
number-theoryclassical-analysisodescombinatoricsmathematical-conjecturesarithmetic-progressions
“If $A \subset \mathbb{Z}$ is a finite set with $|A|=N$ and $||\widehat{1_A}||_1 \leq K\log N$, then $A$ contains a subset $A'\subseteq A$ with $|A'| \geq N^{0.99}$ such that $|A'+A'| \ll K^{O(1)}|A'|$.”