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In recent years, achieving verifiable quantum advantage on a NISQ device has emerged as an important open problem in quantum information. The sampling-based quantum advantages are not known to have efficient verification methods. This article investigates the verification of quantum advantage from a cryptographic perspective. We establish a strong connection between the verifiability of quantum advantage and cryptographic and complexity primitives, including efficiently samplable, statistically far but computationally indistinguishable pairs of (mixed) quantum states (EFI), pseudorandom states (PRS), and variants of minimum circuit size problems (MCSP). Specifically, we prove that a) a sampling-based quantum advantage is either verifiable or can be used to buildEFIand evenPRSand b) polynomial-time algorithms for a variant ofMCSPwould imply efficient verification of quantum advantages. Our work shows that the quest for verifiable quantum advantages may lead to applications of quantum cryptography, and the construction of quantum primitives can provide new insights into the verifiability of quantum advantages. 

The NadABC pathway is involved in the biosynthesis of nicotinamide adenine dinucleotide (NAD) and is a dominant pathway in bacteria. The conversion of l-aspartate to quinolinic acid is initiated by the l-aspartate oxidase NadB, which catalyzes the formation of iminoaspartate that is used by quinolinate synthase NadA in a condensation reaction with dihydroxyacetone phosphate to produce quinolinic acid. NadA is a [4Fesingle bond4S] cluster-containing enzyme that is indispensable in the production of NAD. In B. subtilis, the cysteine sulfurtransferase nifS gene is located in genomic proximity to the nad genes, and its expression is regulated by NadR based on the availability of nicotinic acid. Inactivation of nifS leads to inactivation of the NAD pathway and, consequently, nicotinic acid auxotrophy. In this study, we explored the hypothesis that NifS’ involvement in NAD biosynthesis is associated with its role in the maturation of NadA [4Fesingle bond4S] cluster. We showed through in vitro reconstitution experiments that NifS is catalytically competent in promoting cluster assembly onto apo-NadA and that the rate of reactivation depends on the rate of sulfur mobilization. Furthermore, the activity of NifS in sulfur mobilization is modulated by Apo-NadA. Under conditions of cluster synthesis, apo-NadA enhances the turnover rate of NifS. This phenomenon is not observed for YrvO, NifZ, and SufSU, the other three cysteine sulfurtransferases in B. subtilis. This work provides biochemical evidence for the requirement of a dedicated cysteine desulfurase in the maturation of specialized Fesingle bondS enzymes. 

Learning the Hamiltonian underlying a quantum many-body system in thermal equilibrium is a fundamental task in quantum learning theory and experimental sciences. To learn the Gibbs state of local Hamiltonians at any inverse temperature β, the state-of-the-art provable algorithms fall short of the optimal sample and computational complexity, in sharp contrast with the locality and simplicity in the classical cases. In this work, we present a learning algorithm that learns each local term of a n-qubit D-dimensional Hamiltonian to an additive error ϵ with sample complexity $$\tilde{O}\left(\frac{e^{\mathrm{poly}(\beta)}}{\beta^2\epsilon^2}\right)\log(n)$$. The protocol uses parallelizable local quantum measurements that act within bounded regions of the lattice and near-linear-time classical post-processing. Thus, our complexity is near optimal with respect to n, ϵ and is polynomially tight with respect to β. We also give a learning algorithm for Hamiltonians with bounded interaction degree with sample and time complexities of similar scaling on n but worse on β, ϵ. At the heart of our algorithm is the interplay between locality, the Kubo-Martin-Schwinger condition, and the operator Fourier transform at arbitrary temperatures. 

Abstract This study examines burst laser-induced pitting (BLIP), an understudied surface modification phenomenon driven by ultrafast laser bursts with sub-picosecond to picosecond inter-pulse delays. Through SEM and AFM analysis, we characterize BLIP as sub-micron pits with polarizationdependent oval shapes, alongside high-fluence melting zones and localized ripple-like structures. Unlike conventional LIPSS, BLIP demonstrates exceptional energy coupling efficiency, evidenced by 10× greater damage areas and a steeper fluence-scaling expansion rate than LIPSS, attributed to transient carrier-mediated processes. Pit density decays exponentially with delay (τ ≈ 6.6-8.9 ps), matching the timescale of self-trapped exciton (STE) relaxation, while spatial statistics reveal a delay-driven transition from field-guided ordering (1-5 ps) to randomized distributions (>10 ps). The resonant-like angular distributions and delay-dependent ellipticity reduction indicate competing mechanisms: optical field enhancement dominates at short delays, while energy dissipation and structure disordering prevail at longer delays. Simulation of nanoplasma excitation reveals near-field optical field enhancements responsible for the ellipticity and ripple-like structures. Beyond their fundamental significance, these BLIP nanostructures offer practical functionalities, including use as anti-reflection coatings and hydrophobic surfaces. These findings establish BLIP as a new paradigm in ultrafast laser-material interactions, where burst parameters selectively activate defect-mediated or field-driven modification pathways in dielectrics. 

Cloud computing has become crucial for the commercial world due to its computational capacity, storage capabilities, scalability, software integration, and billing convenience. Initially, clouds were relatively homogeneous, but now diverse machine configurations in heterogeneous clouds are recognized for their improved application performance and energy efficiency. This shift is driven by the integration of various hardware to accommodate diverse user applications. However, alongside these advancements, security threats like micro-architectural attacks are increasing concerns for cloud providers and users. Studies like Repttack and Cloak & Co-locate highlight the vulnerability of heterogeneous clouds to co-location attacks, where attacker and victim instances are placed together. The ease of these attacks isn’t solely linked to heterogeneity but also correlates with how heterogeneous the target systems are. Despite this, no numerical metrics exist to quantify cloud heterogeneity. This article introduces the Heterogeneity Score (HeteroScore) to evaluate server setups and instances. HeteroScore significantly correlates with co-location attack security. The article also proposes strategies to balance diversity and security. This study pioneers the quantitative analysis connecting cloud heterogeneity and infrastructure security.