Monogamy of Entanglement Bounds and Improved Approximation Algorithms for Qudit Hamiltonians
- URL: http://arxiv.org/abs/2410.15544v2
- Date: Mon, 11 Nov 2024 06:47:25 GMT
- Title: Monogamy of Entanglement Bounds and Improved Approximation Algorithms for Qudit Hamiltonians
- Authors: Zackary Jorquera, Alexandra Kolla, Steven Kordonowy, Juspreet Singh Sandhu, Stuart Wayland,
- Abstract summary: We prove new monogamy of entanglement bounds for 2-local qudit Hamiltonian of rank-one projectors without local terms.
We certify the ground state energy in terms of the maximum matching of the underlying interaction graph via low-degree sum-of-squares proofs.
- Score: 37.96754147111215
- License:
- Abstract: We prove new monogamy of entanglement bounds for 2-local qudit Hamiltonian of rank-one projectors without local terms. In particular, we certify the ground state energy in terms of the maximum matching of the underlying interaction graph via low-degree sum-of-squares proofs. Algorithmically, we show that a simple matching-based algorithm approximates the ground state energy to at least $1/d$ for general graphs and to at least $1/d + \Theta(1/D)$ for graphs with bounded degree, $D$. This outperforms random assignment, which, in expectation, achieves energy of only $1/d^2$ of the ground state energy for general graphs. Notably, on $D$-regular graphs with degree, $D \leq 5$, and for any local dimension, $d$, we show that this simple matching-based algorithm has an approximation guarantee of $1/2$. Lastly, when $d=2$, we present an algorithm achieving an approximation guarantee of $0.595$, beating that of [PT22, arXiv:2206.08342] (which gave a tight approximation guarantee of $1/2$).
Related papers
- A Scalable Algorithm for Individually Fair K-means Clustering [77.93955971520549]
We present a scalable algorithm for the individually fair ($p$, $k$)-clustering problem introduced by Jung et al. and Mahabadi et al.
A clustering is then called individually fair if it has centers within distance $delta(x)$ of $x$ for each $xin P$.
We show empirically that not only is our algorithm much faster than prior work, but it also produces lower-cost solutions.
arXiv Detail & Related papers (2024-02-09T19:01:48Z) - Moments, Random Walks, and Limits for Spectrum Approximation [40.43008834125277]
We show that there are distributions on $[-1,1]$ that cannot be approximated to accuracy $epsilon$ in Wasserstein-1 distance.
No algorithm can compute an $epsilon$-accurate approximation to the spectrum of a normalized graph adjacency matrix with constant probability.
arXiv Detail & Related papers (2023-07-02T05:03:38Z) - Detection of Dense Subhypergraphs by Low-Degree Polynomials [72.4451045270967]
Detection of a planted dense subgraph in a random graph is a fundamental statistical and computational problem.
We consider detecting the presence of a planted $Gr(ngamma, n-alpha)$ subhypergraph in a $Gr(n, n-beta) hypergraph.
Our results are already new in the graph case $r=2$, as we consider the subtle log-density regime where hardness based on average-case reductions is not known.
arXiv Detail & Related papers (2023-04-17T10:38:08Z) - Finding the KT partition of a weighted graph in near-linear time [1.572727650614088]
Kawarabayashi and Thorup gave a near-trivial time deterministic algorithm for minimum cut in a simple graph $G = (V,E)$.
We give a near-linear time randomized algorithm to find the $(1+varepsilon)$-KT partition of a weighted graph.
arXiv Detail & Related papers (2021-11-02T05:26:10Z) - Fast Graph Sampling for Short Video Summarization using Gershgorin Disc
Alignment [52.577757919003844]
We study the problem of efficiently summarizing a short video into several paragraphs, leveraging recent progress in fast graph sampling.
Experimental results show that our algorithm achieves comparable video summarization as state-of-the-art methods, at a substantially reduced complexity.
arXiv Detail & Related papers (2021-10-21T18:43:00Z) - Improved approximation algorithms for bounded-degree local Hamiltonians [12.961180148172197]
We describe a family of shallow quantum circuits that can be used to improve the approximation ratio achieved by a given product state.
We extend our results to $k$-local Hamiltonians and entangled initial states.
arXiv Detail & Related papers (2021-05-03T22:23:47Z) - Local classical MAX-CUT algorithm outperforms $p=2$ QAOA on high-girth
regular graphs [0.0]
We show that for all degrees $D ge 2$ of girth $> 5$, QAOA$ has a larger expected cut fraction than QAOA$$ on $G$.
We conjecture that for every constant $p$, there exists a local classical MAX-CUT algorithm that performs as well as QAOA$_p$ on all graphs.
arXiv Detail & Related papers (2021-01-14T09:17:20Z) - A Randomized Algorithm to Reduce the Support of Discrete Measures [79.55586575988292]
Given a discrete probability measure supported on $N$ atoms and a set of $n$ real-valued functions, there exists a probability measure that is supported on a subset of $n+1$ of the original $N$ atoms.
We give a simple geometric characterization of barycenters via negative cones and derive a randomized algorithm that computes this new measure by "greedy geometric sampling"
We then study its properties, and benchmark it on synthetic and real-world data to show that it can be very beneficial in the $Ngg n$ regime.
arXiv Detail & Related papers (2020-06-02T16:38:36Z) - Curse of Dimensionality on Randomized Smoothing for Certifiable
Robustness [151.67113334248464]
We show that extending the smoothing technique to defend against other attack models can be challenging.
We present experimental results on CIFAR to validate our theory.
arXiv Detail & Related papers (2020-02-08T22:02:14Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.