arXiv subjects

Qianfan Zhang

Publications and source records attributed to Qianfan Zhang.

At least 19 recordsLinked to original sources

arXiv2026

Single-Item Auctions with a Monopolist Intermediary

Classical optimal auction theory assumes that bids reach the seller directly. We study how this picture changes when a revenue-maximizing intermediary controls access to the seller's auction. Motivated by blockchain auctions, online platforms, and other intermediated markets, we consider a single-item auction with independent private values and a monopolist intermediary who can decide which bidder messages are forwarded to the seller. We establish approximation guarantees and impossibility results across three timing models: seller-first, intermediary-first, and simultaneous. In the seller-first model, arbitrary deterministic seller mechanisms collapse to posted-price mechanisms, and the intermediary's best response is a shifted Myerson auction. This yields a sharp separation: for regular distributions, the seller's revenue can be arbitrarily small relative to the no-intermediary optimum, while for $α$-strongly regular distributions, posted prices recover a constant fraction of the optimum with a tight dependence on $α$. We further show that timing matters: neither Stackelberg order uniformly dominates, and simultaneous play can leave both parties unboundedly worse off than in either sequential model.

cs.GT↗

arXiv2026

Scaling Reasoning Tokens via RL and Parallel Thinking: Evidence From Competitive Programming

We study how to scale reasoning token budgets for competitive programming through two complementary approaches: training-time reinforcement learning (RL) and test-time parallel thinking. During RL training, we observe an approximately log-linear relationship between validation accuracy and the average number of generated reasoning tokens over successive checkpoints, and show two ways to shift this training trajectory: verification RL warmup raises the starting point, while randomized clipping produces a steeper trend in the observed regime. As scaling single-generation reasoning during RL quickly becomes expensive under full attention, we introduce a multi-round parallel thinking pipeline that distributes the token budget across threads and rounds of generation, verification, and refinement. We train the model end-to-end on this pipeline to match the training objective to the test-time structure. Starting from Seed-OSS-36B, the full system with 16 threads and 16 rounds per thread matches the underlying RL model's oracle pass@16 at pass@1 using 7.6 million tokens per problem on average, and surpasses GPT-5-high on 456 hard competitive programming problems from AetherCode.

cs.CL↗

arXiv2026

Bulk OsO2 Single Crystals: Superior Catalysts for Water Oxidation

Although rutile RuO2 has been a well-known and almost the best oxygen evolution reaction (OER) catalyst, the OER properties for the similar rutile oxide OsO2 with the same group element with Ru have been unknown, mainly due to long-standing synthesis difficulties. In this work, we report the successful synthesis of high-quality OsO2 single crystals, and the ground micrometer-size single crystals are chemically stable in alkaline solutions and exhibit robust OER performance. In sharp contrast, OsO2 nanopowder reacts quickly with KOH solutions and cannot work for OER. Compared with commercial RuO2 nanopowder, the OsO2 single crystals show comparable catalytic current densities, remarkably lower overpotentials at high current densities and better stability. These findings question the universal applicability of nanoscaling and highlight crystal integrity as a key descriptor for achieving stable and efficient OER electrocatalysis.

cond-mat.mtrl-sci↗

arXiv2025

The Communication Complexity of Combinatorial Auctions with Additional Succinct Bidders

We study the communication complexity of welfare maximization in combinatorial auctions with bidders from either a standard valuation class (which require exponential communication to explicitly state, such as subadditive or XOS), or arbitrary succinct valuations (which can be fully described in polynomial communication, such as single-minded). Although succinct valuations can be efficiently communicated, we show that additional succinct bidders have a nontrivial impact on communication complexity of classical combinatorial auctions. Specifically, let $n$ be the number of subadditive/XOS bidders. We show that for SA $\cup$ SC (the union of subadditive and succinct valuations): (1) There is a polynomial communication $3$-approximation algorithm; (2) As $n \to \infty$, there is a matching $3$-hardness of approximation, which (a) is larger than the optimal approximation ratio of $2$ for SA, and (b) holds even for SA $\cup$ SM (the union of subadditive and single-minded valuations); and (3) For all $n \geq 3$, there is a constant separation between the optimal approximation ratios for SA $\cup$ SM and SA (and therefore between SA $\cup$ SC and SA as well). Similarly, we show that for XOS $\cup$ SC: (1) There is a polynomial communication $2$-approximation algorithm; (2) As $n \to \infty$, there is a matching $2$-hardness of approximation, which (a) is larger than the optimal approximation ratio of $e/(e-1)$ for XOS, and (b) holds even for XOS $\cup$ SM; and (3) For all $n \geq 2$, there is a constant separation between the optimal approximation ratios for XOS $\cup$ SM and XOS (and therefore between XOS $\cup$ SC and XOS as well).

cs.GT↗

arXiv2025

From Best Responses to Learning: Investment Efficiency in Dynamic Environment

We study the welfare of a mechanism in a dynamic environment where a learning investor can make a costly investment to change her value. In many real-world problems, the common assumption that the investor always makes the best responses, i.e., choosing her utility-maximizing investment option, is unrealistic due to incomplete information in a dynamically evolving environment. To address this, we consider an investor who uses a no-regret online learning algorithm to adaptively select investments through repeated interactions with the environment. We analyze how the welfare guarantees of approximation allocation algorithms extend from static to dynamic settings when the investor learns rather than best-responds, by studying the approximation ratio for optimal welfare as a measurement of an algorithm's performance against different benchmarks in the dynamic learning environment. First, we show that the approximation ratio in the static environment remains unchanged in the dynamic environment against the best-in-hindsight benchmark. Second, we provide tight characterizations of the approximation upper and lower bounds relative to a stronger time-varying benchmark. Bridging mechanism design with online learning theory, our work shows how robust welfare guarantees can be maintained even when an agent cannot make best responses but learns their investment strategies in complex, uncertain environments.

cs.GT↗

arXiv2025

Truthful, Credible, and Optimal Auctions for Matroids via Blockchains and Commitments

We consider a revenue-optimizing auctioneer in single-dimensional environments with matroid feasibility constraints. Akbarpour and Li (2020) argue that any revenue-optimal, truthful, and credible mechanism requires unbounded communication. Recent works (Ferreira and Weinberg, 2020; Essaidi et al., 2022; Chitra et al., 2024) circumvent their impossibility for the single-item setting through the use of cryptographic commitments and blockchains. We extend their results to matroid feasibility constraints. At a high level, the two-round Deferred-Revelation Auction (DRA) discussed by Ferreira and Weinberg (2020) and Chitra et al., (2024) requires each bidder to submit a deposit, which is slashed upon presenting verifiable evidence indicating a deviation from the behaviour prescribed by the mechanism. We prove that the DRA satisfies truthfulness, credibility and revenue-optimality for all matroid environments when bidders' values are drawn from $α$-strongly regular distributions for $α> 0$. Further, we argue that the DRA is not credible for any feasibility constraint beyond matroids and for any smaller deposits than suggested by previous literature even in single-item environments. Finally, we modify the Ascending Deferred-Revelation Auction (ADRA) for single-item settings proposed by Essaidi et al., (2022) for arbitrary bidder value distributions. We implement a deferred-revelation variant of the deferred-acceptance auction for matroids due to Bikhchandani et al., (2011), which requires the same bounded communication as the ADRA.

cs.GT↗

arXiv2024

A Bicriterion Concentration Inequality and Prophet Inequalities for $k$-Fold Matroid Unions

We investigate prophet inequalities with competitive ratios approaching $1$, seeking to generalize $k$-uniform matroids. We first show that large girth does not suffice: for all $k$, there exists a matroid of girth $\geq k$ and a prophet inequality instance on that matroid whose optimal competitive ratio is $\frac{1}{2}$. Next, we show $k$-fold matroid unions do suffice: we provide a prophet inequality with competitive ratio $1-O(\sqrt{\frac{\log k}{k}})$ for any $k$-fold matroid union. Our prophet inequality follows from an online contention resolution scheme. The key technical ingredient in our online contention resolution scheme is a novel bicriterion concentration inequality for arbitrary monotone $1$-Lipschitz functions over independent items which may be of independent interest. Applied to our particular setting, our bicriterion concentration inequality yields "Chernoff-strength" concentration for a $1$-Lipschitz function that is not (approximately) self-bounding.

cs.DS↗

arXiv2024

Modeling and theoretical design of next-generation lithium metal batteries

Rechargeable lithium metal batteries (LMBs) with an ultrahigh theoretical energy density have attracted more and more attentions for their crucial applications of portable electronic devices, electric vehicles, and smart grids. However, the implementation of LMBs in practice is still facing numerous challenges, such as low Coulombic e ciency, poor cycling performance, and complicated interfacial reactions. First-principles calculations have become a powerful technique in lithium battery research eld, in terms of modeling the structures and properties of speci c electrode materials, understanding the charge/discharge mechanisms at the atomic scale, and delivering rational design strategies for electrode materials as well as electrolytes. In this review, theoretical studies on sulfur cathodes, oxygen cathodes, lithium metal anodes, and solid-state electrolytes (SSEs) of LMBs are summarized. A brief introduction of simulation methods is o ered at rst. The next two chapters mainly focus on issues concerning cathodes of LMBs. Then the theoretical researches on the Li metal anode and SSEs are particularly reviewed. The current challenges and potential research directions in each field of LMBs are prospected from a theoretical viewpoint.

cond-mat.mtrl-sci↗

arXiv2024

Communication Separations for Truthful Auctions: Breaking the Two-Player Barrier

We study the communication complexity of truthful combinatorial auctions, and in particular the case where valuations are either subadditive or single-minded, which we denote with $\mathsf{SubAdd}\cup\mathsf{SingleM}$. We show that for three bidders with valuations in $\mathsf{SubAdd}\cup\mathsf{SingleM}$, any deterministic truthful mechanism that achieves at least a $0.366$-approximation requires $\exp(m)$ communication. In contrast, a natural extension of [Fei09] yields a non-truthful $\mathrm{poly}(m)$-communication protocol that achieves a $\frac{1}{2}$-approximation, demonstrating a gap between the power of truthful mechanisms and non-truthful protocols for this problem. Our approach follows the taxation complexity framework laid out in [Dob16b], but applies this framework in a setting not encompassed by the techniques used in past work. In particular, the only successful prior application of this framework uses a reduction to simultaneous protocols which only applies for two bidders [AKSW20], whereas our three-player lower bounds are stronger than what can possibly arise from a two-player construction (since a trivial truthful auction guarantees a $\frac{1}{2}$-approximation for two players).

cs.GT↗

arXiv2024

Sample-Based Matroid Prophet Inequalities

We study matroid prophet inequalities when distributions are unknown and accessible only through samples. While single-sample prophet inequalities for special matroids are known, no constant-factor competitive algorithm with even a sublinear number of samples was known for general matroids. Adding more to the stake, the single-sample version of the question for general matroids has close (two-way) connections with the long-standing matroid secretary conjecture. In this work, we give a $(\frac14 - \varepsilon)$-competitive matroid prophet inequality with only $O_\varepsilon(\mathrm{poly} \log n)$ samples. Our algorithm consists of two parts: (i) a novel quantile-based reduction from matroid prophet inequalities to online contention resolution schemes (OCRSs) with $O_\varepsilon(\log n)$ samples, and (ii) a $(\frac14 - \varepsilon)$-selectable matroid OCRS with $O_\varepsilon(\mathrm{poly} \log n)$ samples which carefully addresses an adaptivity challenge.

cs.DS↗

arXiv2023

Practical algorithms and experimentally validated incentives for equilibrium-based fair division (A-CEEI)

Approximate Competitive Equilibrium from Equal Incomes (A-CEEI) is an equilibrium-based solution concept for fair division of discrete items to agents with combinatorial demands. In theory, it is known that in asymptotically large markets: 1. For incentives, the A-CEEI mechanism is Envy-Free-but-for-Tie-Breaking (EF-TB), which implies that it is Strategyproof-in-the-Large (SP-L). 2. From a computational perspective, computing the equilibrium solution is unfortunately a computationally intractable problem (in the worst-case, assuming $\textsf{PPAD}\ne \textsf{FP}$). We develop a new heuristic algorithm that outperforms the previous state-of-the-art by multiple orders of magnitude. This new, faster algorithm lets us perform experiments on real-world inputs for the first time. We discover that with real-world preferences, even in a realistic implementation that satisfies the EF-TB and SP-L properties, agents may have surprisingly simple and plausible deviations from truthful reporting of preferences. To this end, we propose a novel strengthening of EF-TB, which dramatically reduces the potential for strategic deviations from truthful reporting in our experiments. A (variant of) our algorithm is now in production: on real course allocation problems it is much faster, has zero clearing error, and has stronger incentive properties than the prior state-of-the-art implementation.

cs.GT↗

arXiv2021

Oblivious Online Contention Resolution Schemes

Contention resolution schemes (CRSs) are powerful tools for obtaining "ex post feasible" solutions from candidates that are drawn from "ex ante feasible" distributions. Online contention resolution schemes (OCRSs), the online version, have found myriad applications in Bayesian and stochastic problems, such as prophet inequalities and stochastic probing. When the ex ante distribution is unknown, it was unknown whether good CRSs/OCRSs exist with no sample (in which case the scheme is oblivious) or few samples from the distribution. In this work, we give a simple $\frac{1}{e}$-selectable oblivious single item OCRS by mixing two simple schemes evenly, and show, via a Ramsey theory argument, that it is optimal. On the negative side, we show that no CRS or OCRS with $O(1)$ samples can be $Ω(1)$-balanced/selectable (i.e., preserve every active candidate with a constant probability) for graphic or transversal matroids.

cs.DS↗

arXiv2021

Ordered $k$-Median with Outliers and Fault-Tolerance

In this paper, we study two natural generalizations of ordered $k$-median, named robust ordered $k$-median and fault-tolerant ordered $k$-median. In ordered $k$-median, given a finite metric space $(X,d)$, we seek to open $k$ facilities $S\subseteq X$ which induce a service cost vector $\vec{c}=\{d(j,S):j\in X\}$, and minimize the ordered objective $w^\top\vec{c}^\downarrow$. Here $d(j,S)=\min_{i\in S}d(j,i)$ is the minimum distance between $j$ and facilities in $S$, $w\in\mathbb{R}^{|X|}$ is a given non-increasing non-negative vector, and $\vec{c}^\downarrow$ is the non-increasingly sorted version of $\vec{c}$. The current best result is a $(5+ε)$-approximation [CS19]. We first consider robust ordered $k$-median, a.k.a. ordered $k$-median with outliers, where the input consists of an ordered $k$-median instance and parameter $m\in\mathbb{Z}_+$. The goal is to open $k$ facilities $S$, select $m$ clients $T\subseteq X$ and assign the nearest open facility to each $j\in T$. The service cost vector is $\vec{c}=\{d(j,S):j\in T\}$ and $w$ is in $\mathbb{R}^m$. We introduce a novel yet simple objective function that enables linear analysis of the non-linear ordered objective, apply an iterative rounding framework [KLS18] and obtain a constant-factor approximation. We devise the first constant-approximations for ordered matroid median and ordered knapsack median using the same method. We also consider fault-tolerant ordered $k$-median, where besides the same input as ordered $k$-median, we are also given additional client requirements $\{r_j\in\mathbb{Z}_+:j\in X\}$ and need to assign $r_j$ distinct open facilities to each client $j\in X$. The service cost of $j$ is the sum of distances to its assigned facilities, and the objective is the same. We obtain a constant-factor approximation using a novel LP relaxation with constraints created via a new sparsification technique.

cs.DS↗

arXiv2019

Anisotropic Bi2O2Se(Te) Monolayer: Realizing Ultra-High Carrier Mobility and Giant Electric Polarization in Two-Dimension

Here, we have identified the monolayer phase of Bi2O2Se as a promising two-dimensional semiconductor with ultra-high carrier mobility and giant electric polarization. Due to the strong reconstruction originated from the interlayer electrostatic force, we have applied structure prediction algorithms to explore the crystalline geometry of Bi2O2Se monolayer with the lowest total energy. Considering Se and Te belong to the same group, Bi2O2Te monolayer is also investigated based on a similar scheme. Further calculations suggest that the high carrier mobility is maintained in the monolayer phase and the moderate band gap will lead to the strong optical absorption in the visible light region. In particular, the electron mobility in Bi2O2Te can reach as high as 3610 cm2V-1s-1 at room temperature, which is almost ten times of conventional transition metal dichalcogenides (TMD) family. Because of the strong structural anisotropy, a remarkable spontaneous in-plane and out-of-plane electric polarization is additionally revealed along with significant piezoelectric properties, endowing them as promising candidates in the area of photovoltaic solar cells, optoelectronic materials and field effect transistors.

cond-mat.mtrl-sci↗

arXiv2019

Modulating Super-Exchange Strength to Achieve Robust Ferromagnetic Couplings in Two-Dimensional Semiconductors

Low-dimensional semiconducting ferromagnets have attracted considerable attention due to their promising applications as nano-size spintronics. However, realizing robust ferromagnetic couplings that can survive at high temperature is restrained by two decisive factors: super-exchange couplings and anisotropy. Despite widely explored low-dimensional anisotropy, strengthening super-exchange couplings has rarely been investigated. Here, we found that ligands with lower electronegativity can strengthen ferromagnetic super-exchange couplings and further proposed the ligand modulation strategy to enhance the Curie temperature of low-dimensional ferromagnets. Based on the metallic CrX2 (X = S, Se, Te) family, substituting ligand atoms by halides can form stable semiconducting phase as CrSeCl, CrSeBr and CrTeBr. It is interesting to discover that, the nearest ferromagnetic super-exchange couplings can be strengthened when substituting ligands from S to Se and Te. Such evolution originates from the enhanced electron hopping integral and reduced energy intervals between d and p orbits. While the second nearest anti-ferromagnetic couplings are also benefitted due to delocalized p-p interactions. Finally, ligand modulation strategy is applied in other ferromagnetic monolayers, further verifying our theory and providing a fundamental understanding on controlling super-exchange couplings in low-dimension.

cond-mat.mtrl-sci↗

arXiv2017

Origin of interfacial perpendicular magnetic anisotropy in MgO/CoFe/metallic capping layer structures

Spin-transfer-torque magnetic random access memory (STT-MRAM) attracts extensive attentions due to its non-volatility, high density and low power consumption. The core device in STT-MRAM is CoFeB/MgO-based magnetic tunnel junction (MTJ), which possesses a high tunnel magnetoresistance ratio as well as a large value of perpendicular magnetic anisotropy (PMA). It has been experimentally proven that a capping layer coating on CoFeB layer is essential to obtain a strong PMA. However, the physical mechanism of such effect remains unclear. In this paper, we investigate the origin of the PMA in MgO/CoFe/metallic capping layer structures by using a first-principles computation scheme. The trend of PMA variation with different capping materials agrees well with experimental results. We find that interfacial PMA in the three-layer structures comes from both the MgO/CoFe and CoFe/capping layer interfaces, which can be analyzed separately. Furthermore, the PMAs in the CoFe/capping layer interfaces are analyzed through resolving the magnetic anisotropy energy by layer and orbital. The variation of PMA with different capping materials is attributed to the different hybridizations of both d and p orbitals via spin-orbital coupling. This work can significantly benefit the research and development of nanoscale STT-MRAM.

cond-mat.mtrl-sci↗

arXiv2016

Giant interfacial perpendicular magnetic anisotropy in MgO/CoFe/capping layer structures

Magnetic tunnel junction (MTJ) based on CoFeB/MgO/CoFeB structures is of great interest due to its application in the spin-transfer-torque magnetic random access memory (STT-MRAM). Large interfacial perpendicular magnetic anisotropy (PMA) is required to achieve high thermal stability. Here we use first-principles calculations to investigate the magnetic anisotropy energy (MAE) of MgO/CoFe/capping layer structures, where the capping materials include 5d metals Hf, Ta, Re, Os, Ir, Pt, Au and 6p metals Tl, Pb, Bi. We demonstrate that it is feasible to enhance PMA by using proper capping materials. Relatively large PMA is found in the structures with capping materials of Hf, Ta, Os, Ir and Pb. More importantly, the MgO/CoFe/Bi structure gives rise to giant PMA (6.09 mJ/m2), which is about three times larger than that of the MgO/CoFe/Ta structure. The origin of the MAE is elucidated by examining the contributions to MAE from each atomic layer and orbital. These findings provide a comprehensive understanding of the PMA and point towards the possibility to achieve advanced-node STT-MRAM with high thermal stability.

cond-mat.mtrl-sci↗

arXiv2014

Nature of proton transport in a water-filled carbon nanotube and in liquid water

Proton transport (PT) in bulk liquid water and within a thin water-filled carbon nanotube has been examined with ab initio pathintegral molecular dynamics (PIMD). Barrierless proton transfer is observed in each case when quantum nuclear effects (QNEs) are accounted for. The key difference between the two systems is that in the nanotube facile PT is facilitated by a favorable prealignment of water molecules, whereas in bulk liquid water solvent reorganization is required prior to PT. Configurations where the quantum excess proton is delocalized over several adjacent water molecules along with continuous interconversion between different hydration states reveals that, as in liquid water, the hydrated proton under confinement is best described as a fluxional defect, rather than any individual idealized hydration state such as Zundel, Eigen, or the so-called linear H7O3+ complex along the water chain. These findings highlight the importance of QNEs in intermediate strength hydrogen bonds (HBs) and explain why H+ diffusion through nanochannels is impeded much less than other cations.

cond-mat.mtrl-sci↗