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Documents authored by Ghasemi, Fatemeh

Document
DOI: 10.4230/LIPIcs.CSL.2026.41
Weakly-Sparse and Strongly Flip-Flat Classes of Graphs Are Uniformly Almost-Wide

Authors: Fatemeh Ghasemi, Julien Grange, Mamadou Moustapha Kanté, and Florent Madelaine

Published in: LIPIcs, Volume 363, 34th EACSL Annual Conference on Computer Science Logic (CSL 2026)

Abstract
In this work we take a step towards characterising strongly flip-flat classes of graphs. Strong flip-flatness appears to be the analogue of uniform almost-wideness in the setting of dense classes of graphs. We prove that strongly flip-flat classes of graphs that are weakly sparse are indeed uniformly almost-wide.
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Fatemeh Ghasemi, Julien Grange, Mamadou Moustapha Kanté, and Florent Madelaine. Weakly-Sparse and Strongly Flip-Flat Classes of Graphs Are Uniformly Almost-Wide. In 34th EACSL Annual Conference on Computer Science Logic (CSL 2026). Leibniz International Proceedings in Informatics (LIPIcs), Volume 363, pp. 41:1-41:14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)

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@InProceedings{ghasemi_et_al:LIPIcs.CSL.2026.41,
  author =	{Ghasemi, Fatemeh and Grange, Julien and Kant\'{e}, Mamadou Moustapha and Madelaine, Florent},
  title =	{{Weakly-Sparse and Strongly Flip-Flat Classes of Graphs Are Uniformly Almost-Wide}},
  booktitle =	{34th EACSL Annual Conference on Computer Science Logic (CSL 2026)},
  pages =	{41:1--41:14},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-411-6},
  ISSN =	{1868-8969},
  year =	{2026},
  volume =	{363},
  editor =	{Guerrini, Stefano and K\"{o}nig, Barbara},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CSL.2026.41},
  URN =		{urn:nbn:de:0030-drops-254668},
  doi =		{10.4230/LIPIcs.CSL.2026.41},
  annote =	{Keywords: Almost-wide, Flip-flatness}
}
Document
DOI: 10.4230/LIPIcs.ITCS.2026.68
Fourier Sparsity of Delta Functions and Matching Vector PIRs

Authors: Fatemeh Ghasemi and Swastik Kopparty

Published in: LIPIcs, Volume 362, 17th Innovations in Theoretical Computer Science Conference (ITCS 2026)

Abstract
In this paper we study a basic and natural question about Fourier analysis of Boolean functions, which has applications to the study of Matching Vector based Private Information Retrieval (PIR) schemes. For integers m,r, define a delta function on {0,1}^r ⊆ ℤ_m^r to be a function f: ℤ_m^r → C if f(0) = 1 and f(x) = 0 for all nonzero Boolean x. The basic question that we study is how small can the Fourier sparsity of a delta function be; namely, how sparse can such an f be in the Fourier basis? In addition to being intrinsically interesting and natural, such questions arise naturally while studying "S-decoding polynomials" for the known matching vector families. Finding S-decoding polynomials of reduced sparsity - which corresponds to finding delta functions with low Fourier sparsity - would improve the current best PIR schemes. We show nontrivial upper and lower bounds on the Fourier sparsity of delta functions. Our proofs are elementary and clean. These results imply limitations on improvements to the Matching Vector PIR schemes simply by finding better S-decoding polynomials. In particular, there are no S-decoding polynomials which can make Matching Vector PIRs based on the known matching vector families achieve polylogarithmic communication for constantly many servers. Many interesting questions remain open.
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Fatemeh Ghasemi and Swastik Kopparty. Fourier Sparsity of Delta Functions and Matching Vector PIRs. In 17th Innovations in Theoretical Computer Science Conference (ITCS 2026). Leibniz International Proceedings in Informatics (LIPIcs), Volume 362, pp. 68:1-68:22, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)

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@InProceedings{ghasemi_et_al:LIPIcs.ITCS.2026.68,
  author =	{Ghasemi, Fatemeh and Kopparty, Swastik},
  title =	{{Fourier Sparsity of Delta Functions and Matching Vector PIRs}},
  booktitle =	{17th Innovations in Theoretical Computer Science Conference (ITCS 2026)},
  pages =	{68:1--68:22},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-410-9},
  ISSN =	{1868-8969},
  year =	{2026},
  volume =	{362},
  editor =	{Saraf, Shubhangi},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ITCS.2026.68},
  URN =		{urn:nbn:de:0030-drops-253556},
  doi =		{10.4230/LIPIcs.ITCS.2026.68},
  annote =	{Keywords: Fourier Sparsity, Matching Vectors, Private Information Retrieval}
}
Document
RANDOM
DOI: 10.4230/LIPIcs.APPROX/RANDOM.2025.37
Permanental Rank vs Determinantal Rank of Random Matrices over Finite Fields

Authors: Fatemeh Ghasemi, Gal Gross, and Swastik Kopparty

Published in: LIPIcs, Volume 353, Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2025)

Abstract
This paper is motivated by basic complexity and probability questions about permanents of random matrices over small finite fields, and in particular, about properties separating the permanent and the determinant. Let q be a fixed odd prime, and let k ≤ n both be growing. For a uniformly random n × k matrix A over 𝔽_q, we study the probability that all k × k submatrices of A have zero permanent; namely that A does not have full permanental rank. When k = n, this is simply the probability that a random square matrix over 𝔽_q has zero permanent, which we do not understand. We believe that the probability in this case is 1/q + o(1), which would be in contrast to the case of the determinant, where the answer is 1/q + Ω_q(1). Our main result is that when k is O(√n), the probability that a random n × k matrix does not have full permanental rank is essentially the same as the probability that the matrix has a 0 column, namely (1 +o(1)) k/qⁿ. In contrast, for determinantal (standard) rank the analogous probability is Θ(q^k/q^n). At the core of our result are some basic linear algebraic properties of the permanent that distinguish it from the determinant.
Cite as

Fatemeh Ghasemi, Gal Gross, and Swastik Kopparty. Permanental Rank vs Determinantal Rank of Random Matrices over Finite Fields. In Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 353, pp. 37:1-37:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{ghasemi_et_al:LIPIcs.APPROX/RANDOM.2025.37,
  author =	{Ghasemi, Fatemeh and Gross, Gal and Kopparty, Swastik},
  title =	{{Permanental Rank vs Determinantal Rank of Random Matrices over Finite Fields}},
  booktitle =	{Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2025)},
  pages =	{37:1--37:15},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-397-3},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{353},
  editor =	{Ene, Alina and Chattopadhyay, Eshan},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.APPROX/RANDOM.2025.37},
  URN =		{urn:nbn:de:0030-drops-244037},
  doi =		{10.4230/LIPIcs.APPROX/RANDOM.2025.37},
  annote =	{Keywords: Permanent, random matrices over a finite field}
}
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