Tootfinder

Dot matrix art display on the bottom of the cantilevered section of the Herbert F. Johnson Museum of Art
#photo #photography #cornell

"Unfortunately, in attempting to do so, we erroneously deleted the data directory of the primary"
jfc we have all been there, if you haven't then it doesn't mean you're perfect it probably just means you haven't done ops enough.
This is what hugops are for.
"Post-mortem of the September 2 Matrix.org outage"

I've been tinkering on a Discord-inspired native #Matrix client on and off for the past three years. During this time it has gone back and forth between #Slint and #Dioxus, because Slint is alw…

Well, a little success, a little failure.
The box with a NeoPixel matrix on the back and a USB battery inside (and a microcontroller) works great!
But I did not bungee it to the bike rack so it flew off, hit the road, the lid broke off, and the MIK adapter also broke.
I bungee corded it into place and it's good now... but the box is busted so I'll have to come up with another solution.

RE: https://mastodon.social/@cheeaun/115415146417702654
After looking at this, got curious to know the limits in most servers.
So I did a little data analysis. Servers list from @…

cintestinalis: Tadpole larva brain (C. intestinalis)
Entire connectivity matrix for the complete brain of a larva of Ciona intestinalis. Each directed edge represents a synaptic connection from pre-synaptic cell i to post-synaptic cell j (may not be a neuron). Edge weights represent the cumulative depth of presynaptic contacts in µm.
This network has 205 nodes and 2903 edges.
Tags: Biological, Connectome, Weighted

DeltaChat is a cool idea but should be cranked to the max. Fuck protocols, instant messaging has never been been about the protocol but the network effect.
Not everyone knows how to login to their email outside of the web browser, a chat client should facilitate speech between you and your friend’s favourite app.
These are all open protocols that allow for direct communication but garden off others: activitypub, email, irc, matrix, xmpp, bluesky, nostr, simplex, theema, tox, jam…

I've now seen one of the new high-tech post boxes on the street.
I say new, it's still an EIIR red pillar box from (probably) the 70s - but the door has been augmented with a camera (for scanning matrix codes) and parcel slot - and it has a sort of solar panel hat. Like it's being very slowly morphed into a Dalek.

#NowPlaying - raga pop & soul jams & very airplane-y nuggets from a far corner of lost san francisco, 1968, aspirational hit-making division, with ex-great society guitarist darby slick. with live cuts from the matrix & deep liners by alec palao. more a portal than a forgotten classic. @…

I guess we should probably add #Clankerslop and #FurryPorn to Cypher's list
#ShamelesslyStolenFromSomewhereElseOnTheInternetHonestlyICantKeepTrackOfThisStuffAnymore

The #Matrix protocol is designed to facilitate collaboration and exchange while preserving national sovereignty. Computing Deutschland spoke with Dr Patrick Alberts, product manager and MD for Germany at #Element, the commercial arm of the Open Matrix project.

Matrix: An open standard for sovereignty
The Matrix protocol is designed to facilitate collaboration and exchange while preserving national sovereignty. Computing Deutschland spoke with Dr Patrick Alberts. He is product manager ...

Technologically I would probably appreciate XMPP more, but the Matrix ecosystem I find much more usable and mature.

Welcome to the Discography of American Historical Recordings (DAHR),
a database of master recordings made by American record companies during the 78rpm era.
It is part of the American Discography Project (ADP)
—an initiative of the University of California, Santa Barbara that is edited by a team of researchers based at the UCSB Library.
To begin your research, enter names, titles, places, matrix or catalog numbers below,
or click on the advanced browse or search…

Catte Cinematic Universe

Multi-port programmable silicon photonics using low-loss phase change material Sb$_2$Se$_3$
Thomas W. Radford, Idris A Ajia, Latif Rozaqi, Priya Deoli, Xingzhao Yan, Mehdi Banakar, David J Thomson, Ioannis Zeimpekis, Alberto Politi, Otto L. Muskens
https://arxiv.org/abs/2511.18205 https://arxiv.org/pdf/2511.18205 https://arxiv.org/html/2511.18205
arXiv:2511.18205v1 Announce Type: new
Abstract: Reconfigurable photonic devices are rapidly emerging as a cornerstone of next generation optical technologies, with wide ranging applications in quantum simulation, neuromorphic computing, and large-scale photonic processors. A central challenge in this field is identifying an optimal platform to enable compact, efficient, and scalable reconfigurability. Optical phase-change materials (PCMs) offer a compelling solution by enabling non-volatile, reversible tuning of optical properties, compatible with a wide range of device platforms and current CMOS technologies. In particular, antimony tri-selenide ($\text{Sb}_{2}\text{Se}_{3}$) stands out for its ultra low-loss characteristics at telecommunication wavelengths and its reversible switching. In this work, we present an experimental platform capable of encoding multi-port operations onto the transmission matrix of a compact multimode interferometer architecture on standard 220~nm silicon photonics using \textit{in-silico} designed digital patterns. The multi-port devices are clad with a thin film of $\text{Sb}_{2}\text{Se}_{3}$, which can be optically addressed using direct laser writing to provide local perturbations to the refractive index. A range of multi-port geometries from 2$\times$2 up to 5$\times$5 couplers are demonstrated, achieving simultaneous control of up to 25 matrix elements with programming accuracy of 90% relative to simulated patterns. Patterned devices remain stable with consistent optical performance across the C-band wavelengths. Our work establishes a pathway towards the development of large scale PCM-based reconfigurable multi-port devices which will allow implementing matrix operations on three orders of magnitude smaller areas than interferometer meshes.
toXiv_bot_toot

Close-up view of the audio-responsive LED floor installation I co-created for the KEF Muon launch in 2007 @ Sala del Cenacolo (Museo Nazionale della Scienza e della Tecnologia in Milano). The animation was repurposed from one of my first projects I created with Processing (in 2003)...
The 2 meter tall speakers were designed by Ross Lovegrove and made from milled solid aluminium...
The installation was created by Moving Brands (my old employer), a short video of the project/instal…

Exact bounds for efficient consistent matrices obtained from a reciprocal matrix
Susana Furtado, Charles Johnson
https://arxiv.org/abs/2510.12358 https://a…

Exact bounds for efficient consistent matrices obtained from a reciprocal matrix
For a given reciprocal matrix A, we give a union of matrix intervals in which any consistent matrix obtained from an efficient vector for A lies, and, conversely, any consistent matrix in this union comes from an efficient vector for A. The maximal sets of entries in the lower and upper bound matrices of each interval that are attainable by some consistent matrix in the interval are described. This allows us to understand which subsets of the alternatives lie above which other subsets in all ef…

Baudrillard (the author of Simulation and Simulacra in 1981, the inspiration for The Matrix movies) predicted Internet bubbles and the influence of algorithms and AI 30 years ago.
https://theconversation.com/how-the-fr

How the French philosopher Jean Baudrillard predicted today’s AI 30 years before ChatGPT
Baudrillard’s genius lay in foreseeing what these rudimentary devices like fax machines suggested about likely future uses of technology.

Improved Central Limit Theorem and Bootstrap Approximations for Linear Stochastic Approximation
Bogdan Butyrin, Eric Moulines, Alexey Naumov, Sergey Samsonov, Qi-Man Shao, Zhuo-Song Zhang
https://arxiv.org/abs/2510.12375

Improved Central Limit Theorem and Bootstrap Approximations for Linear Stochastic Approximation
In this paper, we refine the Berry-Esseen bounds for the multivariate normal approximation of Polyak-Ruppert averaged iterates arising from the linear stochastic approximation (LSA) algorithm with decreasing step size. We consider the normal approximation by the Gaussian distribution with covariance matrix predicted by the Polyak-Juditsky central limit theorem and establish the rate up to order $n^{-1/3}$ in convex distance, where $n$ is the number of samples used in the algorithm. We also prov…

The Matrix Reloaded (2003), Oracle and Neo in the park
Neo: “What does he want?”
Oracle: “What do all men with power want? More power.”

Polyharmonic Cascade
Yuriy N. Bakhvalov
https://arxiv.org/abs/2512.17671 https://arxiv.org/pdf/2512.17671 https://arxiv.org/html/2512.17671
arXiv:2512.17671v1 Announce Type: new
Abstract: This paper presents a deep machine learning architecture, the "polyharmonic cascade" -- a sequence of packages of polyharmonic splines, where each layer is rigorously derived from the theory of random functions and the principles of indifference. This makes it possible to approximate nonlinear functions of arbitrary complexity while preserving global smoothness and a probabilistic interpretation. For the polyharmonic cascade, a training method alternative to gradient descent is proposed: instead of directly optimizing the coefficients, one solves a single global linear system on each batch with respect to the function values at fixed "constellations" of nodes. This yields synchronized updates of all layers, preserves the probabilistic interpretation of individual layers and theoretical consistency with the original model, and scales well: all computations reduce to 2D matrix operations efficiently executed on a GPU. Fast learning without overfitting on MNIST is demonstrated.
toXiv_bot_toot

If you haven't re-watched your 720p pirated copy from 2016 of The Matrix lately, do it now, if only for the showy dialogue at the beginning. So full of hope and righteousness, pure 90s bullet-time fuck-the-establishment attitude.
#Movies #SciFi

Exploring the Spectral Edge in SYK Models
Bowen Ouyang, Pratik Rath
https://arxiv.org/abs/2510.07804 https://arxiv.org/pdf/2510.07804

Exploring the Spectral Edge in SYK Models
Previous work on Jackiw-Teitelboim (JT) gravity has shown that, at low temperatures, the annealed entropy becomes negative and departs from the quenched entropy. From the perspective of the random-matrix theory (RMT) dual of JT gravity, this effect is encoded in the level spacing statistics of the spectral edge that is universally described by the Airy model. At low temperature, the quenched entropy exhibits a power law dependence determined by the symmetry class of the RMT ensemble. Here we st…

The Matrix was supposed to be green-ish, but it's been made when the film industry was switching from analog to digital, so all the (re)released versions look different.
Noodle made a charming documentary about losing sanity trying to find the "correct" green:
https://youtu.be/lPU-kXEhSgk

Reciprocal relations for orthogonal quantum matrices
Pavel Pyatov, Oleg Ogievetsky
https://arxiv.org/abs/2510.09811 https://arxiv.org/pdf/2510.09811…

Reciprocal relations for orthogonal quantum matrices
For the family of the orthogonal quantum matrix algebras we investigate the structure of their characteristic subalgebras -- special commutative subalgebras, which for the subfamily of the reflection equation algebras appear to be central. In [OP1] we described three generating sets of the characteristic subalgebras of the symplectic and orthogonal quantum matrix algebras. One of these -- the set of the elementary sums -- is finite. In the symplectic case the elementary sums are in general alge…

cintestinalis: Tadpole larva brain (C. intestinalis)
Entire connectivity matrix for the complete brain of a larva of Ciona intestinalis. Each directed edge represents a synaptic connection from pre-synaptic cell i to post-synaptic cell j (may not be a neuron). Edge weights represent the cumulative depth of presynaptic contacts in µm.
This network has 205 nodes and 2903 edges.
Tags: Biological, Connectome, Weighted

A Wigner Matrix Based Convolution Algorithm For Matrix Elements in the LCAO Method
Tyler C. Sterling
https://arxiv.org/abs/2510.06285 https://arxiv.org/pdf…

A Wigner Matrix Based Convolution Algorithm For Matrix Elements in the LCAO Method
The linear combination of atomic orbitals (LCAO) method uses a small basis set in exchange for expensive matrix element calculations. The most efficient approximation for the matrix element calculations is the two-center approximation (2CA) in tight binding (TB). In the 2CA, a variety of matrix elements are neglected with only "two-center integrals" (2CI) remaining. The 2CI are calculated efficiently by rotating to symmetrical coordinates where the integral is parameterized. This makes TB fast …

> The upshot is that, whereas it used to take upwards of 12 minutes to join Matrix HQ […] now down to about 30 seconds
In #matrix , room joins occur after you start to enjoy the loading spinner.
https://

A possibility of describing a sequential gauge symmetry as a part of the dihedral flavor symmetry and its implications
Jae Jun Kim
https://arxiv.org/abs/2510.06155 https://

A possibility of describing a sequential gauge symmetry as a part of the dihedral flavor symmetry and its implications
We present a method in which the dimension-five and -six terms in a sequential gauge symmetry can coexist with that of the dihedral flavor symmetry. We start with the contents in the model proposed in a sequential gauge symmetry, meeting the conditions for the contents to be described in the flavor symmetry, build up the mass matrices and discuss its implications. Given that the breaking of the symmetry only takes place in the dimension-five and -six terms in the mass matrix of the charged ferm…

Matrix Random Walks and the Lima Bean Law
Bruce K. Driver, Brian C. Hall, Ching Wei Ho, Todd Kemp, Yuriy Nemish, Evangelos A. Nikitopoulos, Felix Parraud
https://arxiv.org/abs/2510.10712

Matrix Random Walks and the Lima Bean Law
A matrix random walk is a stochastic process of the form $B_k = (I+A_1)\cdots(I+A_k)$ where $A_j$ are independent ``step'' matrices in $\mathrm{M}_N(\mathbb{C})$. With the right entry-covariance, a rescaled matrix random walk converges to Brownian motion $B(t)$ on a matrix Lie group. In this paper, we study the eigenvalues of such rescaled matrix random walks, as $N\to\infty$ and $k\to\infty$. The standard Brownian motion $W(t)$ on $\mathrm{M}_N(\mathbb{C})$ has independent Gaussian entries a…

Just booked the train ticket to #Strasbourg for the #matrix conference 15-18 Oct. Check out the schedule:
https://2025.matrix.org/s…

Due to long inactivity in #Matrix, I managed to get in that dreaded state where *all* my sessions were zombies (logged in, but considered inactive, and unable to send events or decrypt new events). I know the drill, so it was easy to get back to a functioning state, but I can't say I was happy about it. (I "lost" a few months of group messages sent while I was inactive, as none of my sessi…

Semiclassical analytical solutions of the eigenstate thermalization hypothesis in a quantum billiard
Yaoqi Ye, Chengkai Lin, Xiao Wang
https://arxiv.org/abs/2510.12517 https://

Semiclassical analytical solutions of the eigenstate thermalization hypothesis in a quantum billiard
We derive semiclassical analytical solutions for both the diagonal and off-diagonal functions in the eigenstate thermalization hypothesis (ETH) in a quarter-stadium quantum billiard. For a representative observable, we obtain an explicit expression and an asymptotic closed-form solution that naturally separate into a local contribution and a phase-space correlation term. These analytical results predict the band structure of the observable matrix, including its bandwidth and scaling behavior. W…

But what *IS* the Matrix?
Oh. okay. nevermind.

Inverse Continuous-Time Linear Quadratic Regulator: From Control Cost Matrix to Entire Cost Reconstruction
Yuexin Cao, Yibei Li, Zhuo Zou, Xiaoming Hu
https://arxiv.org/abs/2510.04083

Inverse Continuous-Time Linear Quadratic Regulator: From Control Cost Matrix to Entire Cost Reconstruction
This paper studies the inverse optimal control problem for continuous-time linear quadratic regulators over finite-time horizon, aiming to reconstruct the control, state, and terminal cost matrices in the objective function from observed optimal inputs. Previous studies have mainly explored the recovery of state cost matrices under the assumptions that the system is controllable and the control cost matrix is given. Motivated by various applications in which the control cost matrix is unknown a…

Even Faster Kernel Matrix Linear Algebra via Density Estimation
Rikhav Shah, Sandeep Silwal, Haike Xu
https://arxiv.org/abs/2510.02540 https://arxiv.org/pd…

Even Faster Kernel Matrix Linear Algebra via Density Estimation
This paper studies the use of kernel density estimation (KDE) for linear algebraic tasks involving the kernel matrix of a collection of $n$ data points in $\mathbb R^d$. In particular, we improve upon existing algorithms for computing the following up to $(1+\varepsilon)$ relative error: matrix-vector products, matrix-matrix products, the spectral norm, and sum of all entries. The runtimes of our algorithms depend on the dimension $d$, the number of points $n$, and the target error $\varepsilon…

On the Noise Robustness of Affine Frequency Division Multiplexing: Analysis and Applications
Vincent Savaux, Steve Sawadogo, Hyeon Seok Rou, Giuseppe Thadeu Freitas de Abreu
https://arxiv.org/abs/2510.03901

On the Noise Robustness of Affine Frequency Division Multiplexing: Analysis and Applications
This paper investigates the robustness of affine frequency division multiplexing (AFDM) and orthogonal time frequency space (OTFS) modulation schemes against non-white Gaussian noise, which can model various sources of additive disturbances to the received signal. The proposed approach demonstrates that the performance of these waveforms depends on the ability of the demodulation matrix to whiten the noise-a property that is, in turn, related to the sparsity of the matrix. AFDM is shown to outp…

Fisher Matrix for Beginners
David Wittman (UC Davis)
https://arxiv.org/abs/2510.09683 https://arxiv.org/pdf/2510.09683

Fisher Matrix for Beginners
The Fisher information matrix is used widely in astronomy (and presumably other fields) to forecast the precision of future experiments while they are still in the design phase. Although many sources describe the mathematics of the formalism, few sources offer simple examples to help the beginner. This pedagogical document works through a few simple examples to develop conceptual understanding of the applications.

Construction of Basis Functions for the Geometry Conforming Immersed Finite Element Method
Slimane Adjerid, Tao Lin, Haroun Meghaichi
https://arxiv.org/abs/2510.12018 https://…

Construction of Basis Functions for the Geometry Conforming Immersed Finite Element Method
The Frenet apparatus is a new framework for constructing high order geometry-conforming immersed finite element functions for interface problems. In this report, we present a procedure for constructing the local IFE bases in some detail as well as a new approach for constructing orthonormal bases using the singular value decomposition of the local generalized Vandermonde matrix. A sample implementation in MATLAB is provided to showcase the simplicity and extensionability of the framework.

I am not all that knowledgeable of Matrix servers but I have one that is unfederated and somehow we're getting spam sent from one of the users who only use a iPhone.
Seems to me this should just be impossible given their security?

1. Be unhappy that #Element doesn't support multiple accounts.
2. Be unhappy that they've made a new #ElementX that doesn't work with your main account.
3. Realize that you can use both programs to support your main and backup accounts simultaneously.
4. Realize you don't have your backup account password in KeepassDX.
5. Try to figure out which email address you used.
6. It finally works.
7. Realize that you can't get the room address from Element when the server is down.
#Matrix

Ah. Now there's the motion picture studio ligitiousness & just-desserts I know so well.
Warner vs Alcon. Y'all deserve each other.
✅ Matrix, Practical Magic, Ocean's Sequels: Warner Bros. Forced Into Deal
https://www.…

Warner Bros. Forced Into Shotgun Wedding for ‘Matrix,’ ‘Practical Magic’ and ‘Ocean’s 11’ Sequels
A bankruptcy court awarded Alcon the derivative rights to Village Roadshow's film library after Warners' higher bid was rebuffed. The studio is considering an appeal.

The distorted Fourier transform for the linearized Gross-Pitaevskii equation in the Hyperbolic plane
Oussama Landoulsi, Sohrab Shahshahani
https://arxiv.org/abs/2509.26590 https…

The distorted Fourier transform for the linearized Gross-Pitaevskii equation in the Hyperbolic plane
Motivated by the stability problem for Ginzburg-Landau vortices on the hyperbolic plane, we develop the distorted Fourier transform for a general class of radial non-self-adjoint matrix Schrödinger operators on the hyperbolic plane. This applies in particular to the operator obtained by linearizing the equivariant Ginzburg-Landau equation on the hyperbolic plane around the degree one vortex. We systematically construct the distorted Fourier transform by writing the Stone formula for complex …

Reduced Density Matrix Functional Theory And A Reduced Formulation Of Density Functional Theory
H{\aa}kon Richard Fredheim, Simen Kvaal
https://arxiv.org/abs/2510.12242 https://…

Reduced Density Matrix Functional Theory And A Reduced Formulation Of Density Functional Theory
A mathematical framework for reduced density matrix functional theory (RDMFT) is proposed. The work is inspired by and generalizes the work by E.H.~Lieb [E.H. Lieb, Int. J. Quant. Chem. 24(1983), pp.243--277] on density-functional theory (DFT). We introduce a Banach space for density matrices with finite kinetic energy. The dual space is a rich class of single-particle potentials, i.e., Hermitian forms. The ground state energy of an $N$-fermion system with external forces given by any such Herm…

After months of not using it, I dusted off my Matrix account thanks to the room created by @… and I encountered a problem due to a loop that prevented me from completing the verification of some devices. Although I solved it, it is certainly not an app suitable for non-techies.
I guess Matrix isn't designed for them, to begin with. However, maybe there…

Privacy-Preserving Distributed Estimation with Limited Data Rate
Jieming Ke, Jimin Wang, Ji-Feng Zhang
https://arxiv.org/abs/2510.12549 https://arxiv.org/p…

Privacy-Preserving Distributed Estimation with Limited Data Rate
This paper focuses on the privacy-preserving distributed estimation problem with a limited data rate, where the observations are the sensitive information. Specifically, a binary-valued quantizer-based privacy-preserving distributed estimation algorithm is developed, which improves the algorithm's privacy-preserving capability and simultaneously reduces the communication costs. The algorithm's privacy-preserving capability, measured by the Fisher information matrix, is dynamically enhanced over…

Near-optimal Rank Adaptive Inference of High Dimensional Matrices
Fr\'ed\'eric Zheng, Yassir Jedra, Alexandre Proutiere
https://arxiv.org/abs/2510.08117 https://

Near-optimal Rank Adaptive Inference of High Dimensional Matrices
We address the problem of estimating a high-dimensional matrix from linear measurements, with a focus on designing optimal rank-adaptive algorithms. These algorithms infer the matrix by estimating its singular values and the corresponding singular vectors up to an effective rank, adaptively determined based on the data. We establish instance-specific lower bounds for the sample complexity of such algorithms, uncovering fundamental trade-offs in selecting the effective rank: balancing the precis…

Roots in the substitution group and in the group of Riordan matrices with ones in the main diagonal
Jorge Calero-Sanz, Luis Felipe Prieto-Mart\'inez
https://arxiv.org/abs/2509.25972

Roots in the substitution group and in the group of Riordan matrices with ones in the main diagonal
We investigate the existence and uniqueness of iterative roots of order $n$ within the substitution group of formal power series $\mathcal J(Z)$ -with coefficients in a commutative ring with unity $Z$- employing a matrix-based framework grounded in the Riordan group. We analyse the relationship between the substitution group and the Lagrange subgroup - a group of Riordan matrices - and explore some classic questions concerning algebraic completeness and uniqueness of root extractions. This appr…

Complexity of the Zero Set of a Matrix Schubert Ideal
Laura Escobar, Cesar Meza
https://arxiv.org/abs/2510.00131 https://arxiv.org/pdf/2510.00131

Complexity of the Zero Set of a Matrix Schubert Ideal
$T$-varieties are normal varieties equipped with an action of an algebraic torus $T$. When the action is effective, the complexity of a $T$-variety $X$ is $\dim(X)-\dim(T)$. Matrix Schubert varieties, introduced by Fulton in 1992, are $T$-varieties consisting of $n \times n$ matrices satisfying certain constraints on the ranks of their submatrices. In this paper, we focus on the complexity of certain torus-fixed affine subvarieties of matrix Schubert varieties. Concretely, given a matrix Schube…

The Log-Rank Conjecture: New Equivalent Formulations
Lianna Hambardzumyan, Shachar Lovett, Morgan Shirley
https://arxiv.org/abs/2510.02583 https://arxiv.or…

The Log-Rank Conjecture: New Equivalent Formulations
The log-rank conjecture is a longstanding open problem with multiple equivalent formulations in complexity theory and mathematics. In its linear-algebraic form, it asserts that the rank and partitioning number of a Boolean matrix are quasi-polynomially related. We propose a relaxed but still equivalent version of the conjecture based on a new matrix parameter, signed rectangle rank: the minimum number of all-1 rectangles needed to express the Boolean matrix as a $\pm 1$-sum. Signed rectangle …

Intelligent backpropagated neural networks application on Couette-Poiseuille flow of variable viscosity in a composite porous channel filled with an anisotropic porous layer
Timir Karmakar, Amrita Mandal
https://arxiv.org/abs/2510.08745

Intelligent backpropagated neural networks application on Couette-Poiseuille flow of variable viscosity in a composite porous channel filled with an anisotropic porous layer
This study examines Couette-Poiseuille flow of variable viscosity within a channel that is partially filled with a porous medium. To enhance its practical relevance, we assume that the porous medium is anisotropic with permeability varying in all directions, making it a positive semidefinite matrix in the momentum equation. We assume the Navier-Stokes equations govern the flow in the free flow region, while the Brinkman-Forchheimer-extended Darcy's equation governs the flow inside the porous me…

Einstein and Debye temperatures, electron-phonon coupling constant and a probable mechanism for ambient-pressure room-temperature superconductivity in intercalated graphite
E. F. Talantsev
https://arxiv.org/abs/2511.07460 https://arxiv.org/pdf/2511.07460 https://arxiv.org/html/2511.07460
arXiv:2511.07460v1 Announce Type: new
Abstract: Recently, Ksenofontov et al (arXiv:2510.03256) observed ambient pressure room-temperature superconductivity in graphite intercalated with lithium-based alloys with transition temperature (according to magnetization measurements) $T_c=330$ $K$. Here, I analyzed the reported temperature dependent resistivity data $\rho(T)$ in these graphite-intercalated samples and found that $\rho(T)$ is well described by the model of two series resistors, where each resistor is described as either an Einstein conductor or a Bloch-Gr\"uneisen conductor. Deduced Einstein and Debye temperatures are $\Theta_{E,1} \approx 250$ $K$ and $\Theta_{E,2} \approx 1,600$ $K$, and $\Theta_{D,1} \approx 300$ $K$ and $\Theta_{D,2} \approx 2,200$ $K$, respectively. Following the McMillan formalism, from the deduced $\Theta_{E,2}$ and $\Theta_{D,2}$, the electron-phonon coupling constant $\lambda_{e-ph} = 2.2 - 2.6$ was obtained. This value of $\lambda_{e-ph}$ is approximately equal to the value of $\lambda_{e-ph}$ in highly compressed superconducting hydrides. Based on this, I can propose that the observed room-temperature superconductivity in intercalated graphite is localized in nanoscale Sr-Ca-Li metallic flakes/particles, which adopt the phonon spectrum from the surrounding bulk graphite matrix, and as a result, conventional electron-phonon superconductivity arises in these nano-flakes/particles at room temperature. Experimental data reported by Ksenofontov et al (arXiv:2510.03256) on trapped magnetic flux decay in intercalated graphite samples supports the proposition.
toXiv_bot_toot

anyone else seeing matrix 429 errors today on matrix.org? The element web app is ok, but all clients I've tried on debian are giving it.

Investigating Matrix Repartitioning to Address the Over- and Undersubscription Challenge for a GPU-based CFD Solver
Gregor Olenik, Marcel Koch, Hartwig Anzt
https://arxiv.org/abs/2510.08536

Investigating Matrix Repartitioning to Address the Over- and Undersubscription Challenge for a GPU-based CFD Solver
Modern high-performance computing (HPC) increasingly relies on GPUs, but integrating GPU acceleration into complex scientific frameworks like OpenFOAM remains a challenge. Existing approaches either fully refactor the codebase or use plugin-based GPU solvers, each facing trade-offs between performance and development effort. In this work, we address the limitations of plugin-based GPU acceleration in OpenFOAM by proposing a repartitioning strategy that better balances CPU matrix assembly and GP…

The Matrix Reloaded (2003), Oracle and Neo in the park
Neo: “What does he want?”
Oracle: “What do all men with power want? More power.”

Generalized Bishop frames of regular time-like curves in 4-dimensional Lorentz space $\mathbb{L}^{4}$
Subaru Nomoto
https://arxiv.org/abs/2510.09345 https://

Generalized Bishop frames of regular time-like curves in 4-dimensional Lorentz space $\mathbb{L}^{4}$
We introduced generalized Bishop frames on curves in 4-dimensional Euclidean space $\mathbb{E}^{4}$, which are orthonormal frames such that the derivatives of the vectors of the frames along the curve can be expressed, via a certain matrix, as a linear combination of the vectors of the frame. In relation to that, we study generalized Bishop frames of regular time-like curves. In a previous work, we showed that there is a hierarchy among different types of generalized Bishop frames for regular…

Regularized Random Fourier Features and Finite Element Reconstruction for Operator Learning in Sobolev Space
Xinyue Yu, Hayden Schaeffer
https://arxiv.org/abs/2512.17884 https://arxiv.org/pdf/2512.17884 https://arxiv.org/html/2512.17884
arXiv:2512.17884v1 Announce Type: new
Abstract: Operator learning is a data-driven approximation of mappings between infinite-dimensional function spaces, such as the solution operators of partial differential equations. Kernel-based operator learning can offer accurate, theoretically justified approximations that require less training than standard methods. However, they can become computationally prohibitive for large training sets and can be sensitive to noise. We propose a regularized random Fourier feature (RRFF) approach, coupled with a finite element reconstruction map (RRFF-FEM), for learning operators from noisy data. The method uses random features drawn from multivariate Student's $t$ distributions, together with frequency-weighted Tikhonov regularization that suppresses high-frequency noise. We establish high-probability bounds on the extreme singular values of the associated random feature matrix and show that when the number of features $N$ scales like $m \log m$ with the number of training samples $m$, the system is well-conditioned, which yields estimation and generalization guarantees. Detailed numerical experiments on benchmark PDE problems, including advection, Burgers', Darcy flow, Helmholtz, Navier-Stokes, and structural mechanics, demonstrate that RRFF and RRFF-FEM are robust to noise and achieve improved performance with reduced training time compared to the unregularized random feature model, while maintaining competitive accuracy relative to kernel and neural operator tests.
toXiv_bot_toot

I spit on the popular opinion and declare #TheMatrixResurrections essential to the original trilogy 🙂 It's not a good Matrix movie. It's a painfully stand-alone movie commenting on society expecting a repeat of a Matrix movie - despite the obvious warnings of The Matrix. Try re-watching it after the first three from today's point view and judge by yourself. F…

cintestinalis: Tadpole larva brain (C. intestinalis)
Entire connectivity matrix for the complete brain of a larva of Ciona intestinalis. Each directed edge represents a synaptic connection from pre-synaptic cell i to post-synaptic cell j (may not be a neuron). Edge weights represent the cumulative depth of presynaptic contacts in µm.
This network has 205 nodes and 2903 edges.
Tags: Biological, Connectome, Weighted

Scattering in the dual regime of Yang-Baxter deformed O(2N) sigma models
Alexey Bychkov, Boris Nekrasov
https://arxiv.org/abs/2510.11429 https://arxiv.org/…

Scattering in the dual regime of Yang-Baxter deformed O(2N) sigma models
We continue to explore the previously suggested dual regime of Yang-Baxter (YB) deformed $\mathrm{O}(2N)$ sigma models, which is a new one-parametric deformation of the $\mathrm{O}(2N)$ model. It can be obtained from the conventional YB deformed $\mathrm{O}(2N+2)$ sigma model by freezing two isometries. The scattering matrix in the non-deformed $\mathrm{O}(n)$ model is known coincide with the rational $\mathfrak{so}_n$-invariant $R-$matrix. For $n = 2N$ this rational solution allows for two tri…

Rotation of crystal seed during early stages of growth reveals the anisotropy of glass matrix
R. Thapa, E. Mustermann, H. Jain, V. Dierolf, M. E. McKenzie
https://arxiv.org/abs/2510.09807

Rotation of crystal seed during early stages of growth reveals the anisotropy of glass matrix
Rotation of crystal seed during the early stages of growth in a glass matrix has been observed due to some torque, contradicting the expectations from the isotropic, uniform structure of the surrounding amorphous matrix. We establish an atomistic origin of this new phenomenon from molecular dynamics simulations using LiNbO3 and LiNbO3-SiO2 glasses as model systems. Effectively, it arises due to non-uniform forces on the seed from the surrounding glass, which appears inhomogeneous and anisotropi…

Dimension-Free Minimax Rates for Learning Pairwise Interactions in Attention-Style Models
Shai Zucker, Xiong Wang, Fei Lu, Inbar Seroussi
https://arxiv.org/abs/2510.11789 https:…

Dimension-Free Minimax Rates for Learning Pairwise Interactions in Attention-Style Models
We study the convergence rate of learning pairwise interactions in single-layer attention-style models, where tokens interact through a weight matrix and a non-linear activation function. We prove that the minimax rate is $M^{-\frac{2β}{2β+1}}$ with $M$ being the sample size, depending only on the smoothness $β$ of the activation, and crucially independent of token count, ambient dimension, or rank of the weight matrix. These results highlight a fundamental dimension-free statistical efficie…

A Limit on the Total Lepton Number in the Universe from BBN and the CMB
Valerie Domcke, Miguel Escudero, Mario Fernandez Navarro, Stefan Sandner
https://arxiv.org/abs/2510.02438

A Limit on the Total Lepton Number in the Universe from BBN and the CMB
At temperatures below the QCD phase transition, any substantial lepton number in the Universe can only be present within the neutrino sector. In this work, we systematically explore the impact of a non-vanishing lepton number on Big Bang Nucleosynthesis (BBN) and the Cosmic Microwave Background (CMB). Relying on our recently developed framework based on momentum averaged quantum kinetic equations for the neutrino density matrix, we solve the full BBN reaction network to obtain the abundances of…

The distance spectrum of the bipartite double cover of strongly regular graphs
S. Morteza Mirafzal
https://arxiv.org/abs/2510.02400 https://arxiv.org/pdf/2…

The distance spectrum of the bipartite double cover of strongly regular graphs
A strongly regular graph with parameters $(n,d,a,c)$ is a $d$-regular graph of order $n$, in which every pair of adjacent vertices has exactly $a$ common neighbor(s) and every pair of nonadjacent vertices has exactly $c$ common neighbor(s). Let $n$ be the number of vertices of the graph $G=(V,E)$. The distance matrix $D=D(G)$ of $G$ is an $n \times n $ matrix with the rows and columns indexed by $V$ such that $D_{uv} = d_{G}(u, v)=d(u,v)$, where $d_{G}(u, v)$ is the distance between the verti…

Emergence and localization of exceptional points in an exactly solvable toy model
Miloslav Znojil
https://arxiv.org/abs/2510.01756 https://arxiv.org/pdf/25…

Emergence and localization of exceptional points in an exactly solvable toy model
The most elementary non-Hermitian quantum square-well problem with real spectrum is considered. The Schroedinger equation is required discrete and endowed with PT-symmetric Robin (i.e., two-parametric) boundary conditions. Some of the rather enigmatic aspects of impact of the variability of the parameters on the emergence of the Kato's exceptional-point (EP) singularities is clarified. In particular, the current puzzle of the apparent absence of the EP degeneracies at the odd-matrix dimensions …

Reddit is switching off their Matrix server after two years of operation.
(Most of the reactions to the announcement was that they had no idea Reddit ran a Matrix server.)
https://support.reddithelp.com/hc/en-us/articles/249629456…

Dispersion-Aware Modeling Framework for Parallel Optical Computing
Ziqi Wei, Yuanjian Wan, Yuhu Cheng, Xiao Yu, Peng Xie
https://arxiv.org/abs/2511.18897 https://arxiv.org/pdf/2511.18897 https://arxiv.org/html/2511.18897
arXiv:2511.18897v1 Announce Type: new
Abstract: Optical computing represents a groundbreaking technology that leverages the unique properties of photons, with innate parallelism standing as its most compelling advantage. Parallel optical computing like cascaded Mach-Zehnder interferometers (MZIs) based offers powerful computational capabilities but also introduces new challenges, particularly concerning dispersion due to the introduction of new frequencies. In this work, we extend existing theories of cascaded MZI systems to develop a generalized model tailored for wavelength-multiplexed parallel optical computing. Our comprehensive model incorporates component dispersion characteristics into a wavelength-dependent transfer matrix framework and is experimentally validated. We propose a computationally efficient compensation strategy that reduces global dispersion error within a 40 nm range from 0.22 to 0.039 using edge-spectrum calibration. This work establishes a fundamental framework for dispersion-aware model and error correction in MZI-based parallel optical computing chips, advancing the reliability of multi-wavelength photonic processors.
toXiv_bot_toot

Great insights and many new contacts at the #matrixconf2025 . The @… team will present tomorrow Sat Oct 18th at 10 am CEST SchulchatRLP, a #matrix service for half a mill…

Forward and backward error bounds for a mixed precision preconditioned conjugate gradient algorithm
Thomas Bake, Erin Carson, Yuxin Ma
https://arxiv.org/abs/2510.11379 https://

Forward and backward error bounds for a mixed precision preconditioned conjugate gradient algorithm
The preconditioned conjugate gradient (PCG) algorithm is one of the most popular algorithms for solving large-scale linear systems Ax = b, where A is a symmetric positive definite matrix. Rather than computing residuals directly, it updates the residual vectors recursively. Current analyses of the conjugate gradient (CG) algorithm in finite precision typically assume that the norm of the recursively updated residual goes orders of magnitude below the machine precision, focusing mainly on boundi…

In Matrix, the server has your consent, If you like it or not
```
sender cannot leave as they are not already knocking on, invited to, or joined to the room
```
#matrix

Global Convergence of Four-Layer Matrix Factorization under Random Initialization
Minrui Luo, Weihang Xu, Xiang Gao, Maryam Fazel, Simon Shaolei Du
https://arxiv.org/abs/2511.09925 https://arxiv.org/pdf/2511.09925 https://arxiv.org/html/2511.09925
arXiv:2511.09925v1 Announce Type: new
Abstract: Gradient descent dynamics on the deep matrix factorization problem is extensively studied as a simplified theoretical model for deep neural networks. Although the convergence theory for two-layer matrix factorization is well-established, no global convergence guarantee for general deep matrix factorization under random initialization has been established to date. To address this gap, we provide a polynomial-time global convergence guarantee for randomly initialized gradient descent on four-layer matrix factorization, given certain conditions on the target matrix and a standard balanced regularization term. Our analysis employs new techniques to show saddle-avoidance properties of gradient decent dynamics, and extends previous theories to characterize the change in eigenvalues of layer weights.
toXiv_bot_toot

Observation Matrix Design for Densifying MIMO Channel Estimation via 2D Ice Filling
Zijian Zhang, Mingyao Cui
https://arxiv.org/abs/2510.08887 https://arxi…

Observation Matrix Design for Densifying MIMO Channel Estimation via 2D Ice Filling
In recent years, densifying multiple-input multiple-output (MIMO) has attracted much attention from the communication community. Thanks to the subwavelength antenna spacing, the strong correlations among densifying antennas provide sufficient prior knowledge about channel state information (CSI). This inspires the careful design of observation matrices (e.g., transmit precoders and receive combiners), that exploits the CSI prior knowledge, to boost channel estimation performance. Aligned with t…

cintestinalis: Tadpole larva brain (C. intestinalis)
Entire connectivity matrix for the complete brain of a larva of Ciona intestinalis. Each directed edge represents a synaptic connection from pre-synaptic cell i to post-synaptic cell j (may not be a neuron). Edge weights represent the cumulative depth of presynaptic contacts in µm.
This network has 205 nodes and 2903 edges.
Tags: Biological, Connectome, Weighted

A simpler kernel for stratified Mukai flops
Ed Segal, Wei Tseu
https://arxiv.org/abs/2510.08250 https://arxiv.org/pdf/2510.08250

A simpler kernel for stratified Mukai flops
We reinvestigate the problem of describing the Fourier-Mukai kernel for the derived equivalence associated to a stratified Mukai flop. For the case of Grassmannians of planes we give a very simple geometric construction of the kernel, using the framework of matrix factorizations.

A New Method of Constructing Hadamard Matrices, Circulant Hadamard Matrices, CZCS, GCS, CCC, and CZCSS
Piyush Priyanshu, Sudhan Majhi, Subhabrata Paul
https://arxiv.org/abs/2510.12315

A New Method of Constructing Hadamard Matrices, Circulant Hadamard Matrices, CZCS, GCS, CCC, and CZCSS
A Hadamard matrix $H$ is a square matrix of order $n$ with entries $\pm 1$, such that $HH^\top=nI_{n}$, where $I_n$ is an identity matrix of order $n$. A circulant Hadamard matrix $H$ is a Hadamard matrix that has rows of entries in cyclic order. There exist only $8$ circulant Hadamard matrices of order 4, and here, we provide a novel construction of all such $8$ circulant Hadamard matrices using a linear operator and generalized Boolean function (GBF). The constructed circulant Hadamard matric…

Gaussian Equivalence for Self-Attention: Asymptotic Spectral Analysis of Attention Matrix
Tomohiro Hayase, Beno\^it Collins, Ryo Karakida
https://arxiv.org/abs/2510.06685 https:…

Gaussian Equivalence for Self-Attention: Asymptotic Spectral Analysis of Attention Matrix
Self-attention layers have become fundamental building blocks of modern deep neural networks, yet their theoretical understanding remains limited, particularly from the perspective of random matrix theory. In this work, we provide a rigorous analysis of the singular value spectrum of the attention matrix and establish the first Gaussian equivalence result for attention. In a natural regime where the inverse temperature remains of constant order, we show that the singular value distribution of t…

Replaced article(s) found for cs.LG. https://arxiv.org/list/cs.LG/new
[4/5]:
- Sample, Don't Search: Rethinking Test-Time Alignment for Language Models
Gon\c{c}alo Faria, Noah A. Smith
https://arxiv.org/abs/2504.03790 https://mastoxiv.page/@arXiv_csCL_bot/114301112970577326
- A Survey on Archetypal Analysis
Aleix Alcacer, Irene Epifanio, Sebastian Mair, Morten M{\o}rup
https://arxiv.org/abs/2504.12392 https://mastoxiv.page/@arXiv_statME_bot/114357826909813483
- The Stochastic Occupation Kernel (SOCK) Method for Learning Stochastic Differential Equations
Michael L. Wells, Kamel Lahouel, Bruno Jedynak
https://arxiv.org/abs/2505.11622 https://mastoxiv.page/@arXiv_statML_bot/114539065460187982
- BOLT: Block-Orthonormal Lanczos for Trace estimation of matrix functions
Kingsley Yeon, Promit Ghosal, Mihai Anitescu
https://arxiv.org/abs/2505.12289 https://mastoxiv.page/@arXiv_mathNA_bot/114539035462135281
- Clustering and Pruning in Causal Data Fusion
Otto Tabell, Santtu Tikka, Juha Karvanen
https://arxiv.org/abs/2505.15215 https://mastoxiv.page/@arXiv_statML_bot/114550346291754635
- On the performance of multi-fidelity and reduced-dimensional neural emulators for inference of ph...
Chloe H. Choi, Andrea Zanoni, Daniele E. Schiavazzi, Alison L. Marsden
https://arxiv.org/abs/2506.11683 https://mastoxiv.page/@arXiv_statML_bot/114692410563481289
- Beyond Force Metrics: Pre-Training MLFFs for Stable MD Simulations
Maheshwari, Tang, Ock, Kolluru, Farimani, Kitchin
https://arxiv.org/abs/2506.14850 https://mastoxiv.page/@arXiv_physicschemph_bot/114709402590755731
- Quantifying Uncertainty in the Presence of Distribution Shifts
Yuli Slavutsky, David M. Blei
https://arxiv.org/abs/2506.18283 https://mastoxiv.page/@arXiv_statML_bot/114738165218533987
- ZKPROV: A Zero-Knowledge Approach to Dataset Provenance for Large Language Models
Mina Namazi, Alexander Nemecek, Erman Ayday
https://arxiv.org/abs/2506.20915 https://mastoxiv.page/@arXiv_csCR_bot/114754394485208892
- SpecCLIP: Aligning and Translating Spectroscopic Measurements for Stars
Zhao, Huang, Xue, Kong, Liu, Tang, Beers, Ting, Luo
https://arxiv.org/abs/2507.01939 https://mastoxiv.page/@arXiv_astrophIM_bot/114788369702591337
- Towards Facilitated Fairness Assessment of AI-based Skin Lesion Classifiers Through GenAI-based I...
Ko Watanabe, Stanislav Frolov, Aya Hassan, David Dembinsky, Adriano Lucieri, Andreas Dengel
https://arxiv.org/abs/2507.17860 https://mastoxiv.page/@arXiv_csCV_bot/114912976717523345
- PASS: Probabilistic Agentic Supernet Sampling for Interpretable and Adaptive Chest X-Ray Reasoning
Yushi Feng, Junye Du, Yingying Hong, Qifan Wang, Lequan Yu
https://arxiv.org/abs/2508.10501 https://mastoxiv.page/@arXiv_csAI_bot/115032101532614110
- Unified Acoustic Representations for Screening Neurological and Respiratory Pathologies from Voice
Ran Piao, Yuan Lu, Hareld Kemps, Tong Xia, Aaqib Saeed
https://arxiv.org/abs/2508.20717 https://mastoxiv.page/@arXiv_csSD_bot/115111255835875066
- Machine Learning-Driven Predictive Resource Management in Complex Science Workflows
Tasnuva Chowdhury, et al.
https://arxiv.org/abs/2509.11512 https://mastoxiv.page/@arXiv_csDC_bot/115213444524490263
- MatchFixAgent: Language-Agnostic Autonomous Repository-Level Code Translation Validation and Repair
Ali Reza Ibrahimzada, Brandon Paulsen, Reyhaneh Jabbarvand, Joey Dodds, Daniel Kroening
https://arxiv.org/abs/2509.16187 https://mastoxiv.page/@arXiv_csSE_bot/115247172280557686
- Automated Machine Learning Pipeline: Large Language Models-Assisted Automated Dataset Generation ...
Adam Lahouari, Jutta Rogal, Mark E. Tuckerman
https://arxiv.org/abs/2509.21647 https://mastoxiv.page/@arXiv_condmatmtrlsci_bot/115286737423175311
- Quantifying the Impact of Structured Output Format on Large Language Models through Causal Inference
Han Yuan, Yue Zhao, Li Zhang, Wuqiong Luo, Zheng Ma
https://arxiv.org/abs/2509.21791 https://mastoxiv.page/@arXiv_csCL_bot/115287166674809413
- The Generation Phases of Flow Matching: a Denoising Perspective
Anne Gagneux, S\'egol\`ene Martin, R\'emi Gribonval, Mathurin Massias
https://arxiv.org/abs/2510.24830 https://mastoxiv.page/@arXiv_csCV_bot/115462527449411627
- Data-driven uncertainty-aware seakeeping prediction of the Delft 372 catamaran using ensemble Han...
Giorgio Palma, Andrea Serani, Matteo Diez
https://arxiv.org/abs/2511.04461 https://mastoxiv.page/@arXiv_eessSY_bot/115507785247809767
- Generalized infinite dimensional Alpha-Procrustes based geometries
Salvish Goomanee, Andi Han, Pratik Jawanpuria, Bamdev Mishra
https://arxiv.org/abs/2511.09801 https://mastoxiv.page/@arXiv_statML_bot/115547135711272091
toXiv_bot_toot

Gradient-flowed operator product expansion without IR renormalons
Martin Beneke (TU Munich), Hiromasa Takaura (Kyoto University)
https://arxiv.org/abs/2510.12193 https://…

Gradient-flowed operator product expansion without IR renormalons
A long-standing problem concerns the question how to consistently combine perturbative expansions in QCD with power corrections in the context of the operator product expansion (OPE), since the former exhibit ambiguities due to infrared renormalons, which are of the same order as the power corrections. We propose to use the gradient flow time $1/\sqrt{t}$ as a factorization scale and to express the OPE in terms of IR renormalon-free subtracted perturbative expansions and unambiguous matrix elem…

Approximating quantum states by states of low rank
Nathaniel Johnston, Chi-Kwong Li
https://arxiv.org/abs/2510.08463 https://arxiv.org/pdf/2510.08463

Approximating quantum states by states of low rank
Given a positive integer k, it is natural to ask for a formula for the distance between a given density matrix (i.e., mixed quantum state) and the set of density matrices of rank at most k. This problem has already been solved when "distance" is measured in the trace or Frobenius norm. We solve it for all other unitary similarity invariant norms. We also present some consequences of our formula. For example, in the trace and Frobenius norms, the density matrix that is farthest from the set of l…

Spectral gap of $G(n, \alpha n, \alpha^2 n)$ graphs and the giant component theorem
M. Koshelev, A. Raigorodskii
https://arxiv.org/abs/2510.06722 https://a…

Spectral gap of $G(n, αn, α^2 n)$ graphs and the giant component theorem
The spectrum of a graph $G$ is the set of the eigenvalues of its adjacency matrix. It turns out that one can say a lot about a graph with the only knowledge being the spectrum of this graph. In this paper we obtain new results about the spectrum of $G(n, αn, α^2 n)$ graphs. We then apply these results to get a giant component theorem for them.

The true #matrix experience, it spins then errors out.
@… I honestly gave matrix a try (self hosting) but this is ridiculous, I’m unable to enter an unencrypted chat room. This is now before and after the cloudflare downtime

For some reason I've been banned (without ever interacting or having been in the room)
```
conduwuit_core::matrix::state_res::event_auth:sender cannot join as they are banned from the room
```
#matrix

Bootstrapping Yang-Mills matrix integrals
Wenliang Li, Xinran Su
https://arxiv.org/abs/2510.06704 https://arxiv.org/pdf/2510.06704

Bootstrapping Yang-Mills matrix integrals
We revisit the large $N$ limit of bosonic $D$-matrix Yang-Mills integrals using two complementary bootstrap methods. In the positivity bootstrap, we obtain bounds for $\langle \text{tr}\, XX \rangle$ and $\langle \text{tr}\, XXXX \rangle$ at various length cutoff $L_{\max}$. For $D=3$, we do not find an isolated region until $L_{\max}=12$. For larger $D$, the allowed regions become islands at $L_{\max}=8$ and shrink rapidly as $L_{\max}$ increases. The precision of some $L_{\max}=12$ islands is…

Active Subspaces in Infinite Dimension
Poorbita Kundu, Nathan Wycoff
https://arxiv.org/abs/2510.11871 https://arxiv.org/pdf/2510.11871

Active Subspaces in Infinite Dimension
Active subspace analysis uses the leading eigenspace of the gradient's second moment to conduct supervised dimension reduction. In this article, we extend this methodology to real-valued functionals on Hilbert space. We define an operator which coincides with the active subspace matrix when applied to a Euclidean space. We show that many of the desirable properties of Active Subspace analysis extend directly to the infinite dimensional setting. We also propose a Monte Carlo procedure and discus…

Lepton flavor from a horizontal symmetry in a slice of AdS$_5$
Leandro Da Rold, Franco A. Gigena, Jaime S. Guzm\'an Guerrero
https://arxiv.org/abs/2510.06356 https://…

Lepton flavor from a horizontal symmetry in a slice of AdS$_5$
We build a model of lepton flavor in a slice of AdS$_5$. We add to the 5D SM fields a set of neutrino fields, as well as a horizontal U(1) symmetry and a flavon field, all propagating in the bulk. The electroweak and U(1) symmetries are spontaneously broken by a potential localized on the infrared boundary. We show that in a flavor anarchic scenario, by suitable choice of the 5D masses and the U(1) charges, the masses of the SM leptons and the PMNS matrix can be naturally generated. The neutrin…

Fisher Information, Training and Bias in Fourier Regression Models
Lorenzo Pastori, Veronika Eyring, Mierk Schwabe
https://arxiv.org/abs/2510.06945 https://

Fisher Information, Training and Bias in Fourier Regression Models
Motivated by the growing interest in quantum machine learning, in particular quantum neural networks (QNNs), we study how recently introduced evaluation metrics based on the Fisher information matrix (FIM) are effective for predicting their training and prediction performance. We exploit the equivalence between a broad class of QNNs and Fourier models, and study the interplay between the \emph{effective dimension} and the \emph{bias} of a model towards a given task, investigating how these affe…

A New Quantum Linear System Algorithm Beyond the Condition Number and Its Application to Solving Multivariate Polynomial Systems
Jianqiang Li
https://arxiv.org/abs/2510.05588 ht…

A New Quantum Linear System Algorithm Beyond the Condition Number and Its Application to Solving Multivariate Polynomial Systems
Given a matrix $A$ of dimension $M \times N$ and a vector $\vec{b}$, the quantum linear system (QLS) problem asks for the preparation of a quantum state $|\vec{y}\rangle$ proportional to the solution of $A\vec{y} = \vec{b}$. Existing QLS algorithms have runtimes that scale linearly with the condition number $κ(A)$, the sparsity of $A$, and logarithmically with inverse precision, but often overlook structural properties of $\vec{b}$, whose alignment with $A$'s eigenspaces can greatly affec…

A $q$-analogue of distance matrix of bi-block graphs
Joyentanuj Das
https://arxiv.org/abs/2509.26060 https://arxiv.org/pdf/2509.26060

A $q$-analogue of distance matrix of bi-block graphs
A $q$-analogue of the distance matrix, referred to as the \emph{$q$-distance matrix}, is obtained from the distance matrix by replacing each nonzero entry $α$ with the sum $1+q+\cdots+q^{α-1}$. This notion was introduced independently by Bapat, Lal, and Pati~\cite{Ba-Lal-Pati}, and by Yan and Yeh~\cite{Yan}. A connected graph is called a \emph{bi-block graph} if each of its blocks is a complete bipartite graph. In this paper, we derive explicit formulas for the determinant and the inverse of …

Sharpness of Minima in Deep Matrix Factorization: Exact Expressions
Anil Kamber, Rahul Parhi
https://arxiv.org/abs/2509.25783 https://arxiv.org/pdf/2509.25…

Sharpness of Minima in Deep Matrix Factorization: Exact Expressions
Understanding the geometry of the loss landscape near a minimum is key to explaining the implicit bias of gradient-based methods in non-convex optimization problems such as deep neural network training and deep matrix factorization. A central quantity to characterize this geometry is the maximum eigenvalue of the Hessian of the loss, which measures the sharpness of the landscape. Currently, its precise role has been obfuscated because no exact expressions for this sharpness measure were known i…

Coherence restoring in communication line via controlled interaction with environment
E. B. Fel'dman, I. D. Lazarev, A. N. Pechen, A. I. Zenchuk
https://arxiv.org/abs/2509.25861

Coherence restoring in communication line via controlled interaction with environment
We consider the state-restoring protocol based on the controlled interaction of a linear chain with environment through the specially adjusted step-wise time dependent Lindblad operators. We show that the best restoring result (maximal scale factors in the restored state) corresponds to the symmetrical Lindblad equation. (0,1)-excitation dynamics is considered numerically, and restoring protocol for the 1-order coherence matrix is proposed for the case of the two-qubit sender (receiver). The st…

Qubit entanglement from forward scattering
Kamila Kowalska, Enrico Maria Sessolo
https://arxiv.org/abs/2510.04200 https://arxiv.org/pdf/2510.04200

Qubit entanglement from forward scattering
In the context of entanglement in relativistic $2\to 2$ scattering described by a perturbative $S$-matrix, we derive analytically the concurrence for a mixed final state of two qubits corresponding to a discrete quantum number of the scattered particles. Given an initial product state, the derived concurrence depends at the leading order on the real part of the inelastic forward amplitude and the initial state only. We also point out that the real part of the forward amplitude provides a sublea…

On the Benefits of Weight Normalization for Overparameterized Matrix Sensing
Yudong Wei, Liang Zhang, Bingcong Li, Niao He
https://arxiv.org/abs/2510.01175 https://

On the Benefits of Weight Normalization for Overparameterized Matrix Sensing
While normalization techniques are widely used in deep learning, their theoretical understanding remains relatively limited. In this work, we establish the benefits of (generalized) weight normalization (WN) applied to the overparameterized matrix sensing problem. We prove that WN with Riemannian optimization achieves linear convergence, yielding an exponential speedup over standard methods that do not use WN. Our analysis further demonstrates that both iteration and sample complexity improve p…

cintestinalis: Tadpole larva brain (C. intestinalis)
Entire connectivity matrix for the complete brain of a larva of Ciona intestinalis. Each directed edge represents a synaptic connection from pre-synaptic cell i to post-synaptic cell j (may not be a neuron). Edge weights represent the cumulative depth of presynaptic contacts in µm.
This network has 205 nodes and 2903 edges.
Tags: Biological, Connectome, Weighted

CP-conserving SO(3) parameterization of the neutrino mixing matrix
Jaros{\l}aw Duda, Janusz Gluza, Biswajit Karmakar
https://arxiv.org/abs/2509.25328 https://

CP-conserving SO(3) parameterization of the neutrino mixing matrix
The pattern of neutrino mixing, usually parameterized by the Pontecorvo-Maki-Nakagawa-Sakata $U_{\rm PMNS}$ matrix, still remains a striking puzzle in particle physics. $U_{\rm PMNS}$ is one of six possible products of multiplying three Euler matrices. Here we discuss the neutrino mixing matrix parameterization for three known flavours of neutrinos based on the SO(3) group represented by one three-dimensional rotation matrix $U_{\rm SO3}$. The mixing matrix $U_{\rm SO3}$ with cyclic order of th…

I thought matrix chat was slow, but it's the element client that's slow, laggy, bad cache prone.
Thankfully there are alternatives not built by element, client and server
#matrix

The Loss Kernel: A Geometric Probe for Deep Learning Interpretability
Maxwell Adam, Zach Furman, Jesse Hoogland
https://arxiv.org/abs/2509.26537 https://ar…

The Loss Kernel: A Geometric Probe for Deep Learning Interpretability
We introduce the loss kernel, an interpretability method for measuring similarity between data points according to a trained neural network. The kernel is the covariance matrix of per-sample losses computed under a distribution of low-loss-preserving parameter perturbations. We first validate our method on a synthetic multitask problem, showing it separates inputs by task as predicted by theory. We then apply this kernel to Inception-v1 to visualize the structure of ImageNet, and we show that t…

Texture-zeros in minimal seesaw from non-invertible symmetry fusion rules
Zheng Jiang, Bu-Yao Qu, Gui-Jun Ding
https://arxiv.org/abs/2510.07236 https://arx…

Texture-zeros in minimal seesaw from non-invertible symmetry fusion rules
The $Z_2$ gauging of $Z_N$ symmetry can enforce certain elements of the fermion Yukawa couplings to vanish. We have performed a systematical study of texture zero patterns of lepton mass matrices in the minimal seesaw model, and we present all the possible patterns of the charged lepton Yukawa coupling $Y_E$, neutrino Yukawa coupling $Y_ν$, right-handed neutrino mass matrix $M_R$ and the light neutrino mass matrix $M_ν$ which can be derived from the $Z_2$ gauging of $Z_N$ symmetry. The realiz…

Visualizing Quantum Circuits: State Vector Difference Highlighting and the Half-Matrix
Michael J. McGuffin, Jean-Marc Robert
https://arxiv.org/abs/2510.00895 https://

Visualizing Quantum Circuits: State Vector Difference Highlighting and the Half-Matrix
Existing graphical user interfaces for circuit simulators often show small visual summaries of the reduced state of each qubit, showing the probability, phase, purity, and/or Bloch sphere coordinates associated with each qubit. These necessarily provide an incomplete picture of the quantum state of the qubits, and can sometimes be confusing for students or newcomers to quantum computing. We contribute two novel visual approaches to provide more complete information about small circuits. First, …

Sample-Efficient Differentially Private Fine-Tuning via Gradient Matrix Denoising
Ali Dadsetan, Frank Rudzicz
https://arxiv.org/abs/2510.01137 https://arxi…

Sample-Efficient Differentially Private Fine-Tuning via Gradient Matrix Denoising
We address the challenge of sample efficiency in differentially private fine-tuning of large language models (LLMs) using DP-SGD. While DP-SGD provides strong privacy guarantees, the added noise significantly increases the entropy of gradient matrices, disrupting their low-rank structure and slowing optimization. We propose a post-processing algorithm that leverages random matrix theory to denoise gradients, restore low-rank structure, and improve alignment with the original signal. Applied to …

MSHT Approximate N3LO PDFs: Updates and Consequences for Phenomenology
T. Cridge, L. A. Harland-Lang, R. S. Thorne
https://arxiv.org/abs/2510.09321 https://

MSHT Approximate N3LO PDFs: Updates and Consequences for Phenomenology
We present updates to the MSHT approximate N3LO PDFs focusing upon recent developments, examining the impacts of newly determined splitting function and transition matrix element calculations, performed since the public MSHT20aN3LO PDF set was released. We observe only small changes to the output PDFs, at most of similar size to their quoted uncertainties and typically notably less. Finally, we also present the impacts on the PDF luminosities, where changes are generally further reduced.