QUANT-PHMar 13Code
A Note on Publicly Verifiable Quantum Money with Low Quantum Computational ResourcesFabrizio Genovese, Lev Stambler
In this work we present a publicly verifiable quantum money protocol which assumes close to no quantum computational capabilities. We rely on one-time memories which in turn can be built from quantum conjugate coding and hardware-based assumptions. Specifically, our scheme allows for a limited number of verifications and also allows for quantum tokens for digital signatures. Double spending is prevented by the no-cloning principle of conjugate coding states. An implementation of the concepts presented in this work can be found at https://github.com/neverlocal/otm_billz.
QUANT-PHMar 13
Towards Simple and Useful One-Time Programs in the Quantum Random Oracle ModelLev Stambler
We construct simulation-secure one-time memories (OTM) in the random oracle model, and present a plausible argument for their security against quantum adversaries with bounded and adaptive depth. Our contributions include: (1) A simple scheme where we use only single-qubit Wiesner states and conjunction obfuscation (constructible from LPN): no complex entanglement or quantum cryptography is required. (2) A new POVM bound where e prove that any measurement achieving $(1 - ε)$ success on one basis has conjugate-basis guessing probability at most $\frac{1}{2m} + O(ε^\frac{1}{4})$. (3) Simultation-secure OTMs in the quantum random oracle model where an adversary can only query the random oracle classically. (4) Adaptive depth security where, via an informal application of a lifting theorem from Arora et al., we conjecture security against adversaries with polynomial quantum circuit depth between random oracle queries. Security against adaptive, depth-bounded, quantum adversaries captures many realistic attacks on OTMs built from single-qubit states; our work thus paves the way for practical and truly secure one-time programs. Moreover, depth bounded adaptive adversarial models may allow for encoding one-time memories into error corrected memory states, opening the door to implementations of one-time programs which persist for long periods of time.
QUANT-PHMar 13
New Quantum Internet Applications via Verifiable One-Time ProgramsLev Stambler
We introduce Verifiable One-Time Programs (Ver-OTPs) and use them to construct single-round Open Secure Computation (OSC), a novel primitive enabling applications like (1) single-round sealed-bid auctions, (2) single-round and honest-majority atomic proposes -- a building block of consensus protocols, and (3) single-round differentially private statistical aggregation without pre-registration. First, we construct Ver-OTPs from single-qubit states and classical cryptographic primitives. Then, assuming a multi-key homomorphic scheme (MHE) with certain properties, we use Ver-OTPs with MHE to construct OSC. The underlying quantum requirement is minimal: only single-qubit states are needed alongside a hardware assumption on the receiver's quantum resources. Our work therefore provides a new framework for quantum-assisted cryptography that may be implementable with near-term quantum technology.
LGFeb 9, 2025
Provably Overwhelming Transformer Models with Designed InputsLev Stambler, Seyed Sajjad Nezhadi, Matthew Coudron
We develop an algorithm which, given a trained transformer model $\mathcal{M}$ as input, as well as a string of tokens $s$ of length $n_{fix}$ and an integer $n_{free}$, can generate a mathematical proof that $\mathcal{M}$ is ``overwhelmed'' by $s$, in time and space $\widetilde{O}(n_{fix}^2 + n_{free}^3)$. We say that $\mathcal{M}$ is ``overwhelmed'' by $s$ when the output of the model evaluated on this string plus any additional string $t$, $\mathcal{M}(s + t)$, is completely insensitive to the value of the string $t$ whenever length($t$) $\leq n_{free}$. Along the way, we prove a particularly strong worst-case form of ``over-squashing'', which we use to bound the model's behavior. Our technique uses computer-aided proofs to establish this type of operationally relevant guarantee about transformer models. We empirically test our algorithm on a single layer transformer complete with an attention head, layer-norm, MLP/ReLU layers, and RoPE positional encoding. We believe that this work is a stepping stone towards the difficult task of obtaining useful guarantees for trained transformer models.