4,166 research outputs found

### Two Structural Results for Low Degree Polynomials and Applications

In this paper, two structural results concerning low degree polynomials over
finite fields are given. The first states that over any finite field
$\mathbb{F}$, for any polynomial $f$ on $n$ variables with degree $d \le
\log(n)/10$, there exists a subspace of $\mathbb{F}^n$ with dimension $\Omega(d
\cdot n^{1/(d-1)})$ on which $f$ is constant. This result is shown to be tight.
Stated differently, a degree $d$ polynomial cannot compute an affine disperser
for dimension smaller than $\Omega(d \cdot n^{1/(d-1)})$. Using a recursive
argument, we obtain our second structural result, showing that any degree $d$
polynomial $f$ induces a partition of $F^n$ to affine subspaces of dimension
$\Omega(n^{1/(d-1)!})$, such that $f$ is constant on each part.
We extend both structural results to more than one polynomial. We further
prove an analog of the first structural result to sparse polynomials (with no
restriction on the degree) and to functions that are close to low degree
polynomials. We also consider the algorithmic aspect of the two structural
results.
Our structural results have various applications, two of which are:
* Dvir [CC 2012] introduced the notion of extractors for varieties, and gave
explicit constructions of such extractors over large fields. We show that over
any finite field, any affine extractor is also an extractor for varieties with
related parameters. Our reduction also holds for dispersers, and we conclude
that Shaltiel's affine disperser [FOCS 2011] is a disperser for varieties over
$F_2$.
* Ben-Sasson and Kopparty [SIAM J. C 2012] proved that any degree 3 affine
disperser over a prime field is also an affine extractor with related
parameters. Using our structural results, and based on the work of Kaufman and
Lovett [FOCS 2008] and Haramaty and Shpilka [STOC 2010], we generalize this
result to any constant degree

### Bi-Lipschitz Bijection between the Boolean Cube and the Hamming Ball

We construct a bi-Lipschitz bijection from the Boolean cube to the Hamming
ball of equal volume. More precisely, we show that for all even n there exists
an explicit bijection f from the n-dimensional Boolean cube to the Hamming ball
of equal volume embedded in (n+1)-dimensional Boolean cube, such that for all x
and y it holds that distance(x,y) / 5 <= distance(f(x),f(y)) <= 4 distance(x,y)
where distance(,) denotes the Hamming distance. In particular, this implies
that the Hamming ball is bi-Lipschitz transitive.
This result gives a strong negative answer to an open problem of Lovett and
Viola [CC 2012], who raised the question in the context of sampling
distributions in low-level complexity classes. The conceptual implication is
that the problem of proving lower bounds in the context of sampling
distributions will require some new ideas beyond the sensitivity-based
structural results of Boppana [IPL 97].
We study the mapping f further and show that it (and its inverse) are
computable in DLOGTIME-uniform TC0, but not in AC0. Moreover, we prove that f
is "approximately local" in the sense that all but the last output bit of f are
essentially determined by a single input bit

### Network Formations among Immigrants and Natives

In this paper we examine possible network formations among immigrants and natives with endogenous investment. We consider a model of a network formation where the initiator of the link bears its cost while both agents benefit from it. We present the model by considering possible interactions between immigrants and the new society in the host country: assimilation, separation, integration and marginalization. The paper highlights different aspects of immigrantsâ behavior and their interaction with the members of the host country (society) and their source country (society). We found that when the stock of the immigrants in the host country increases, the immigrants' investment in the middlemen increases and the natives may bear the cost of link formation with the middlemen.assimilation and separation, social networks, network formations

### Non-Malleable Extractors - New Tools and Improved Constructions

A non-malleable extractor is a seeded extractor with a very strong guarantee - the output of a non-malleable extractor obtained using a typical seed is close to uniform even conditioned on the output obtained using any other seed. The first contribution of this paper consists of two new and improved constructions of non-malleable extractors:
- We construct a non-malleable extractor with seed-length O(log(n) * log(log(n))) that works for entropy Omega(log(n)). This improves upon a recent exciting construction by Chattopadhyay, Goyal, and Li (STOC\u2716) that has seed length O(log^{2}(n)) and requires entropy Omega(log^{2}(n)).
- Secondly, we construct a non-malleable extractor with optimal seed length O(log(n)) for entropy n/log^{O(1)}(n). Prior to this construction, non-malleable extractors with a logarithmic seed length, due to Li (FOCS\u2712), required entropy 0.49*n. Even non-malleable condensers with seed length O(log(n)), by Li (STOC\u2712), could only support linear entropy.
We further devise several tools for enhancing a given non-malleable extractor in a black-box manner. One such tool is an algorithm that reduces the entropy requirement of a non-malleable extractor at the expense of a slightly longer seed. A second algorithm increases the output length of a non-malleable extractor from constant to linear in the entropy of the source. We also devise an algorithm that transforms a non-malleable extractor to the so-called t-non-malleable extractor for any desired t. Besides being useful building blocks for our constructions, we consider these modular tools to be of independent interest

### Spectral Expanding Expanders

Dinitz, Schapira, and Valadarsky [Dinitz et al., 2017] introduced the intriguing notion of expanding expanders - a family of expander graphs with the property that every two consecutive graphs in the family differ only on a small number of edges. Such a family allows one to add and remove vertices with only few edge updates, making them useful in dynamic settings such as for datacenter network topologies and for the design of distributed algorithms for self-healing expanders. [Dinitz et al., 2017] constructed explicit expanding-expanders based on the Bilu-Linial construction of spectral expanders [Bilu and Linial, 2006]. The construction of expanding expanders, however, ends up being of edge expanders, thus, an open problem raised by [Dinitz et al., 2017] is to construct spectral expanding expanders (SEE).
In this work, we resolve this question by constructing SEE with spectral expansion which, like [Bilu and Linial, 2006], is optimal up to a poly-logarithmic factor, and the number of edge updates is optimal up to a constant. We further give a simple proof for the existence of SEE that are close to Ramanujan up to a small additive term. As in [Dinitz et al., 2017], our construction is based on interpolating between a graph and its lift. However, to establish spectral expansion, we carefully weigh the interpolated graphs, dubbed partial lifts, in a way that enables us to conduct a delicate analysis of their spectrum. In particular, at a crucial point in the analysis, we consider the eigenvectors structure of the partial lifts

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### Sucrose Concentration and Fermentation Temperature Impact the Sensory Characteristics and Liking of Kombucha

Kombucha is a fermented tea beverage consumed for its probiotics and functional properties and has a unique sensory profile driven by the properties of tea polyphenols and fermentation products, including organic acids. Fermentation temperature and sucrose content affect the fermentation process and the production of organic acids, yet less is known about the impact on the sensory profile and consumer acceptance. Thus, we aim to examine the impact of sucrose concentration and fermentation temperature on sensory attributes and liking. For this study, kombucha tea was fermented at three different concentrations of sucrose and fermented at two temperatures for 11 days. Fermentation was monitored by pH, brix, and titratable acidity, and consumers (n=104) evaluated the kombucha for sensory attributes and overall liking. Fermentation temperature resulted in significant differences in titratable acidity, with higher temperatures producing more organic acids, resulting in higher astringency, and suppressed sweetness. The lower fermentation was reported as significantly more liked, with no difference in liking between the 7.5% and 10% sucrose kombucha samples. Overall, sucrose concentration had less of an impact on overall liking, and the sensory profile and fermentation temperature, which drives the fermentation rate and production of organic acids, strongly influenced the sensory profile

### Professional vs. Non-Professional Investors: A Comparative study into the usage of Investment Tools

Investors use varies tools in the investment process.Some use technical or fundamental analysis, or both inthat process. The difference between those investmentstools have been well documented in the financialliterature. However, little have been written about thedifference investment behaviour between professionaland non-professional investors. The aim of thefollowing survey research is to examine differencesbetween professional portfolio managers to nonprofessionalinvestors in their approach towardstechnical and fundamental analysis. We used onlinesurvey in one of the leading business portals in additionto asking professional investors in a leading investmenthouse in Israel. The results show no significantdifference between professional and non-professionalinvestors in terms of how frequently they usefundamental and technical investment tools. Bothgroups of investors use more frequently fundamentaltools than technical when they make buy/sell decisions.Non- professional investors use more fundamental toolssuch as "analysts' recommendations" when they buystocks and more technical tools such as "support andresistance lines" when they sell stocks. Moreover, whileolder investors prefer fundamental tools when they buyand sell stocks, younger investors prefer to usetechnical tools over fundamentals. This importantresult might indicate that younger investor less believein a long time consuming fundamentals analysis thantheir older colleagues and they rather use a more quickmethod that does not demand an extensive effort andknowledge

### Two-Source Condensers with Low Error and Small Entropy Gap via Entropy-Resilient Functions

In their seminal work, Chattopadhyay and Zuckerman (STOC\u2716) constructed a two-source extractor with error epsilon for n-bit sources having min-entropy {polylog}(n/epsilon). Unfortunately, the construction\u27s running-time is {poly}(n/epsilon), which means that with polynomial-time constructions, only polynomially-small errors are possible. Our main result is a {poly}(n,log(1/epsilon))-time computable two-source condenser. For any k >= {polylog}(n/epsilon), our condenser transforms two independent (n,k)-sources to a distribution over m = k-O(log(1/epsilon)) bits that is epsilon-close to having min-entropy m - o(log(1/epsilon)). Hence, achieving entropy gap of o(log(1/epsilon)).
The bottleneck for obtaining low error in recent constructions of two-source extractors lies in the use of resilient functions. Informally, this is a function that receives input bits from r players with the property that the function\u27s output has small bias even if a bounded number of corrupted players feed adversarial inputs after seeing the inputs of the other players. The drawback of using resilient functions is that the error cannot be smaller than ln r/r. This, in return, forces the running time of the construction to be polynomial in 1/epsilon.
A key component in our construction is a variant of resilient functions which we call entropy-resilient functions. This variant can be seen as playing the above game for several rounds, each round outputting one bit. The goal of the corrupted players is to reduce, with as high probability as they can, the min-entropy accumulated throughout the rounds. We show that while the bias decreases only polynomially with the number of players in a one-round game, their success probability decreases exponentially in the entropy gap they are attempting to incur in a repeated game

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