Crosslisted article(s) found for math.SG. https://arxiv.org/list/math.SG/new
[1/1]:
- Weak supermajorization between symplectic spectra of positive definite matrix and its pinching
Temjensangba, Hemant Kumar Mishra
https://arxiv.org/abs/2603.27634 https://mastoxiv.page/@arXiv_mathFA_bot/116322760324341903
- Log-concavity from enumerative geometry of planar curve singularities
Tao Su, Baiting Xie, Chenglong Yu
https://arxiv.org/abs/2603.27888 https://mastoxiv.page/@arXiv_mathAG_bot/116323004749425212
- The $\chi_y$-genus, Chern number inequalities and signature
Ping Li, Yibo Ren
https://arxiv.org/abs/2603.27964 https://mastoxiv.page/@arXiv_mathDG_bot/116322841561405646
- The Hodograph Transform Between Thermodynamics and Relativity
Leonid Polterovich
https://arxiv.org/abs/2603.28039 https://mastoxiv.page/@arXiv_grqc_bot/116323121733734684
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Cryptanalysis of a Lightweight RFID Authentication Protocol Based on a Variable Matrix Encryption Algorithm
Hongjun Wu
https://arxiv.org/abs/2603.28313 https://
Compressing Transformer Language Models via Matrix Product Operator Decomposition: A Case Study on PicoGPT
Younes Javanmard, Tanmoy Pandit, Masoud Mardani
https://arxiv.org/abs/2603.28534 https://arxiv.org/pdf/2603.28534 https://arxiv.org/html/2603.28534
arXiv:2603.28534v1 Announce Type: new
Abstract: Transformer-based language models achieve strong performance across NLP tasks, but their quadratic parameter scaling with hidden dimension makes deployment on resource-constrained hardware expensive. We study Matrix Product Operator (MPO) decomposition as a principled compression method for transformers. MPO factorises weight matrices into chains of low-rank cores, with approximation quality controlled by the bond dimension chi. We replace every nn.Linear layer in PicoGPT, a GPT-2-style character-level language model with about 1M parameters, with an MPOLinear module parameterised as an MPO chain. Cores are initialised either by TT-SVD from pretrained dense weights or from random initialisation, and trained using standard PyTorch autograd without a custom backward pass. We derive balanced factorisation schemes for the five distinct weight shapes in PicoGPT and evaluate bond dimensions chi in {4, 8, 16, 32} on Tiny Shakespeare. MPO compression achieves up to 13x compression per transformer block at chi = 4. At chi = 16, the model uses 191,872 parameters instead of 1,020,224 while retaining 97.7% of baseline token accuracy (51.6% vs 52.8%). Reconstruction error follows the expected trend and is lower for three-site than two-site factorisations at the same bond dimension. The chi = 8 model gives the best accuracy per parameter, exceeding the dense baseline by 2.7x on this metric. These results show that MPO parameterisation is a practical and theoretically grounded alternative to low-rank methods and unstructured pruning for transformer compression.
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The Cone of J-Hermitian Matrices and a Geometric Mean
Jose Franco, Allan Merino
https://arxiv.org/abs/2602.21258 https://arxiv.org/pdf/2602.21258 https://arxiv.org/html/2602.21258
arXiv:2602.21258v1 Announce Type: new
Abstract: We study the cone $\mathscr{P}_{\text{J}}$ of positive J-Hermitian matrices associated with an indefinite signature matrix J = $\text{Id}_{p,q}$. We show that the J-exponential map is bijective and use it to analyze the algebraic and geometric structure of $\mathscr{P}_{\text{J}}$. Through a canonical identification with the cone of positive definite matrices, we endow $\mathscr{P}_{\text{J}}$ with a natural Riemannian structure. In this setting, we define a J-geometric mean as the midpoint of geodesics and prove that it is uniquely characterized as the solution of a Riccati-type equation.
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Replaced article(s) found for cs.DS. https://arxiv.org/list/cs.DS/new
[1/1]:
- Fully Dynamic Adversarially Robust Correlation Clustering in Polylogarithmic Update Time
Vladimir Braverman, Prathamesh Dharangutte, Shreyas Pai, Vihan Shah, Chen Wang
https://arxiv.org/abs/2411.09979 https://mastoxiv.page/@arXiv_csDS_bot/113502653187863544
- A Simple and Combinatorial Approach to Proving Chernoff Bounds and Their Generalizations
William Kuszmaul
https://arxiv.org/abs/2501.03488 https://mastoxiv.page/@arXiv_csDS_bot/113791396712128907
- The Structural Complexity of Matrix-Vector Multiplication
Emile Anand, Jan van den Brand, Rose McCarty
https://arxiv.org/abs/2502.21240 https://mastoxiv.page/@arXiv_csDS_bot/114097340825270885
- Clustering under Constraints: Efficient Parameterized Approximation Schemes
Sujoy Bhore, Ameet Gadekar, Tanmay Inamdar
https://arxiv.org/abs/2504.06980 https://mastoxiv.page/@arXiv_csDS_bot/114312444050875805
- Minimizing Envy and Maximizing Happiness in Graphical House Allocation
Anubhav Dhar, Ashlesha Hota, Palash Dey, Sudeshna Kolay
https://arxiv.org/abs/2505.00296 https://mastoxiv.page/@arXiv_csDS_bot/114437013364446063
- Fast and Simple Densest Subgraph with Predictions
Thai Bui, Luan Nguyen, Hoa T. Vu
https://arxiv.org/abs/2505.12600 https://mastoxiv.page/@arXiv_csDS_bot/114538936921930134
- Compressing Suffix Trees by Path Decompositions
Becker, Cenzato, Gagie, Kim, Koerkamp, Manzini, Prezza
https://arxiv.org/abs/2506.14734 https://mastoxiv.page/@arXiv_csDS_bot/114703384646892523
- Improved sampling algorithms and functional inequalities for non-log-concave distributions
Yuchen He, Zhehan Lei, Jianan Shao, Chihao Zhang
https://arxiv.org/abs/2507.11236 https://mastoxiv.page/@arXiv_csDS_bot/114862112197588124
- Deterministic Lower Bounds for $k$-Edge Connectivity in the Distributed Sketching Model
Peter Robinson, Ming Ming Tan
https://arxiv.org/abs/2507.11257 https://mastoxiv.page/@arXiv_csDS_bot/114862223634372292
- Optimally detecting uniformly-distributed $\ell_2$ heavy hitters in data streams
Santhoshini Velusamy, Huacheng Yu
https://arxiv.org/abs/2509.07286 https://mastoxiv.page/@arXiv_csDS_bot/115178875220889588
- Uncrossed Multiflows and Applications to Disjoint Paths
Chandra Chekuri, Guyslain Naves, Joseph Poremba, F. Bruce Shepherd
https://arxiv.org/abs/2511.00254 https://mastoxiv.page/@arXiv_csDS_bot/115490402963680492
- Dynamic Matroids: Base Packing and Covering
Tijn de Vos, Mara Grilnberger
https://arxiv.org/abs/2511.15460 https://mastoxiv.page/@arXiv_csDS_bot/115580946319285096
- Branch-width of connectivity functions is fixed-parameter tractable
Tuukka Korhonen, Sang-il Oum
https://arxiv.org/abs/2601.04756 https://mastoxiv.page/@arXiv_csDS_bot/115864074799755995
- CoinPress: Practical Private Mean and Covariance Estimation
Sourav Biswas, Yihe Dong, Gautam Kamath, Jonathan Ullman
https://arxiv.org/abs/2006.06618
- The Ideal Membership Problem and Abelian Groups
Andrei A. Bulatov, Akbar Rafiey
https://arxiv.org/abs/2201.05218
- Bridging Classical and Quantum: Group-Theoretic Approach to Quantum Circuit Simulation
Daksh Shami
https://arxiv.org/abs/2407.19575 https://mastoxiv.page/@arXiv_quantph_bot/112874282709517475
- Young domination on Hamming rectangles
Janko Gravner, Matja\v{z} Krnc, Martin Milani\v{c}, Jean-Florent Raymond
https://arxiv.org/abs/2501.03788 https://mastoxiv.page/@arXiv_mathCO_bot/113791421814248215
- On the Space Complexity of Online Convolution
Joel Daniel Andersson, Amir Yehudayoff
https://arxiv.org/abs/2505.00181 https://mastoxiv.page/@arXiv_csCC_bot/114437005955255553
- Universal Solvability for Robot Motion Planning on Graphs
Anubhav Dhar, Pranav Nyati, Tanishq Prasad, Ashlesha Hota, Sudeshna Kolay
https://arxiv.org/abs/2506.18755 https://mastoxiv.page/@arXiv_csCC_bot/114737342714568702
- Colorful Minors
Evangelos Protopapas, Dimitrios M. Thilikos, Sebastian Wiederrecht
https://arxiv.org/abs/2507.10467
- Learning fermionic linear optics with Heisenberg scaling and physical operations
Aria Christensen, Andrew Zhao
https://arxiv.org/abs/2602.05058
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Crosslisted article(s) found for math.OA. https://arxiv.org/list/math.OA/new
[1/1]:
- On matrix valued (asymmetric) truncated Toeplitz operators
Nihat Gokhan Gogus, Rewayat Khan
https://arxiv.org/abs/2603.23579 https://mastoxiv.page/@arXiv_mathFA_bot/116294346151902644
- Class number zeta function of imaginary quadratic fields
Igor V. Nikolaev
https://arxiv.org/abs/2603.24313 https://mastoxiv.page/@arXiv_mathNT_bot/116294463792701405
- A new source of purely finite matricial fields
David Gao, Srivatsav Kunnawalkam Elayavalli, Aareyan Manzoor, Gregory Patchell
https://arxiv.org/abs/2603.24502 https://mastoxiv.page/@arXiv_mathGR_bot/116294455301063850
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R-Matrix Theory for Electron-Ion Collisions in Plasmas
Chao Wu, Wen Hao Xia, Yong Wu, Jun Yan, Ming Li, Jian Guo Wang, Xiang Gao
https://arxiv.org/abs/2601.19538 https://…
Replaced article(s) found for math.OA. https://arxiv.org/list/math.OA/new
[1/1]:
- Invariant $C^*$-subalgebras of the reduced group $C^*$-algebra
Tattwamasi Amrutam, Yongle Jiang
https://arxiv.org/abs/2503.09548 https://mastoxiv.page/@arXiv_mathOA_bot/114153932488469168
- Uniqueness of the zeta transformation in operator K-theory
Mikkel Munkholm
https://arxiv.org/abs/2512.16035 https://mastoxiv.page/@arXiv_mathOA_bot/115745354413545840
- Kernel Radon-Nikodym Derivatives for Random Matrix Products
James Tian
https://arxiv.org/abs/2509.20496 https://mastoxiv.page/@arXiv_mathFA_bot/115269543643186260
toXiv_bot_toot
Crosslisted article(s) found for nlin.PS. https://arxiv.org/list/nlin.PS/new
[1/1]:
- Turing patterns in Matrix-Weighted Networks
Anna Gallo, Wilfried Segnou, Timoteo Carletti
https://arxiv.org/abs/2602.13080 https://mastoxiv.page/@arXiv_condmatstatmech_bot/116079407955524567
toXiv_bot_toot
Crosslisted article(s) found for math.OA. https://arxiv.org/list/math.OA/new
[1/1]:
- Time-Scaled Intertwining Cocycles and Identifiability of Multi-Semigroup Mixtures on Hilbert Oper...
Anton Alexa
https://arxiv.org/abs/2603.20322 https://mastoxiv.page/@arXiv_mathFA_bot/116283090397448396
- Universal Coefficients and Mayer-Vietoris for Moore Homology of Ample Groupoids
Luciano Melodia
https://arxiv.org/abs/2603.20861 https://mastoxiv.page/@arXiv_mathAT_bot/116283018602632921
- Cocycles and positive functionals in higher cohomology
Antonio L\'opez Neumann, Piotr W. Nowak
https://arxiv.org/abs/2603.21431 https://mastoxiv.page/@arXiv_mathAT_bot/116283163474031677
- Maximality Levels of the classical permutation group in the quantum permutation group
J. P. McCarthy
https://arxiv.org/abs/2603.21759 https://mastoxiv.page/@arXiv_mathQA_bot/116283160850717727
- Triangular Decomposition of the Crystal Lattice of Quantized Function Algebras: Revisited
Ayan Dey
https://arxiv.org/abs/2603.21868 https://mastoxiv.page/@arXiv_mathQA_bot/116283166064403090
- Cyclicity of stable matrix free polynomials over non-commutative operator unit balls
Jeet Sampat, Maximilian Tornes
https://arxiv.org/abs/2603.22129 https://mastoxiv.page/@arXiv_mathFA_bot/116283334169858979
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Fast Sparse Matrix Permutation for Mesh-Based Direct Solvers
Behrooz Zarebavami, Ahmed H. Mahmoud, Ana Dodik, Changcheng Yuan, Serban D. Porumbescu, John D. Owens, Maryam Mehri Dehnavi, Justin Solomon
https://arxiv.org/abs/2602.00898 https://arxiv.org/pdf/2602.00898 https://arxiv.org/html/2602.00898
arXiv:2602.00898v1 Announce Type: new
Abstract: We present a fast sparse matrix permutation algorithm tailored to linear systems arising from triangle meshes. Our approach produces nested-dissection-style permutations while significantly reducing permutation runtime overhead. Rather than enforcing strict balance and separator optimality, the algorithm deliberately relaxes these design decisions to favor fast partitioning and efficient elimination-tree construction. Our method decomposes permutation into patch-level local orderings and a compact quotient-graph ordering of separators, preserving the essential structure required by sparse Cholesky factorization while avoiding its most expensive components. We integrate our algorithm into vendor-maintained sparse Cholesky solvers on both CPUs and GPUs. Across a range of graphics applications, including single factorizations, repeated factorizations, our method reduces permutation time and improves the sparse Cholesky solve performance by up to 6.27x.
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RE: https://beep.town/@zion/116025223395990218
Sometimes I wonder if Matrix Bot is like a horoscope. Is it predicting my future, or am I just reading too much into the messaging?
Either way... It works 🤣
Quantum Graph Theory by Example
Gian Luca Spitzer, Ion Nechita
https://arxiv.org/abs/2603.23651 https://arxiv.org/pdf/2603.23651 https://arxiv.org/html/2603.23651
arXiv:2603.23651v1 Announce Type: new
Abstract: Quantum graphs have been introduced by Duan, Severini, and Winter to describe the zero-error behaviour of quantum channels. Since then, quantum graph theory has become a field of study in its own right. A substantial source of difficulty in working with quantum graphs compared to classical graphs stems from the fact that they are no longer discrete objects. This makes it generally difficult to construct insightful, non-trivial examples. We present a collection of non-trivial quantum graphs that can be thought of in discrete terms, and that can be expressed in the diagrammatic formalism introduced by Musto, Reutter, and Verdon. The examples arise as the quantum graphs acted on by increasingly smaller classical matrix groups, and are parametrised by triples of matrices $(A, B, C)$. The parametrisation reveals a clean decomposition of quantum graph structure into classical and genuinely quantum components: $A$ and $C$ are described by a classical weighted graph called the strange graph, while $B$ provides a purely quantum contribution with no classical analogue. Based on this model, we give exact formulas or establish bounds for quantum graph parameters, such as the number of connected components, the chromatic number, the independence number, and the clique number. Our results provide the first large, parametric families of quantum graphs for which standard graph parameters can be computed analytically.
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Replaced article(s) found for math.CA. https://arxiv.org/list/math.CA/new
[1/1]:
- On the equivalence between moderate growth-type conditions in the weight matrix setting II
Gerhard Schindl
Light propagation in atomic stratified media: breakdown of the transfer-matrix method at high density
Igor M. Sokolov, William Guerin
https://arxiv.org/abs/2601.14715 https://
Crosslisted article(s) found for math.CV. https://arxiv.org/list/math.CV/new
[1/1]:
- Perturbation of monic matrix polynomials
Cong Trinh Le, Gue Myung Lee, Yongdo Lim, Tien Son Pham
@arXiv_mathSG_bot@mastoxiv.page
