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Finance is not the only industry looking for a way to profit from even the small, unstable quantum computers that mark the current state of the art; sectors from aerospace to pharmaceuticals are also hunting for a "quantum advantage". But there are reasons to think finance may be among the first to find it. Mike Biercuk of Q-CTRL, a startup that makes control software for quantum computers, points out that a new financial algorithm can be deployed faster than a new industrial process. The size of financial markets means that even a small advance would be worth a lot of money.
当前最先进的量子计算机规模小且不稳定，即便如此，试图利用它获利的行业并不局限在金融业，从航空航天到制药等众多行业都在寻求“量子优势”，只不过我们有理由认为金融业是会捷足先登的行业之一。Q-CTRL是一家为量子计算机开发控制软件的创业公司，其创始人迈克比埃库克指出，部署一种新的金融算法可能比部署新的工业流程要快。金融市场的规模如此庞大，就算小小的进步也会价值千金。
Banks are also buying in expertise. Firms including BBVA, Citigroup, JPMorgan and Standard Chartered have set up research teams and signed deals with computing firms. The Boston Consulting Group reckons that, as of June, banks and insurers in America and Europe had hired more than 115 experts—a big number for what remains, even in academia, a small specialism. "We have more physics and maths PhDs than some big universities," jokes Alexei Kondratyev, head of data analytics at Standard Chartered.
银行也在为专业技术掏腰包。包括西班牙对外银行、花旗集团、摩根大通和渣打银行在内的许多公司已经成立了研究团队，并和计算公司签署了协议。据波士顿咨询集团估计，欧美的银行和保险公司截至6月已经聘请了超过115名专家——鉴于量子研究即使在学术界也仍属小众，这个数字可谓相当惊人了。渣打银行的数据分析负责人阿列克谢康德拉特耶夫打趣道：“我们这里的物理博士和数学博士比一些大型大学还要多。
Startups are exploring possibilities too. Enrique Lizaso of Multiverse Computing reckons his firm's quantum-enhanced algorithms can spot fraud more effectively, and around a hundred times faster, than existing ones. The firm has also experimented with portfolio optimisation, in which analysts seek well-performing investment strategies. Multiverse re-ran decisions made by real traders at a bank. The job was to choose, over the course of a year, the most profitable mix from a group of 50 assets, subject to restrictions, such as how often trades could be made.
创业公司也在试水。平行宇宙计算公司的恩里克·利萨索认为其公司利用经量子增强的算法可以更有效地甄别欺诈，速度比现有算法快了约100倍。该公司还测试了投资组合优化，即让分析师寻求表现优异的投资策略。它重演了由一家银行的真实交易员所做的决策。这项工作要求在交易频率等限制条件下，于一年时间内从50项资产中选择盈利能力最强的组合。
The result was a problem with around 101,300 possible solutions, a number that far outstrips the number of atoms in the visible universe. In reality, the bank's traders, assisted by models running on classical computers, managed an annual return of 19%. Depending on the amount of volatility investors were prepared to put up with, Multiverse's algorithm generated returns of 20-80%—though it stops short of claiming a definitive quantum advantage.
这样就产生了一个约有10^1300个可能解的问题，这个数字远远超过了可见宇宙中的原子数量。现实中该银行交易员在经典计算机上运行的模型的辅助下实现了19％的年回报率，而平行宇宙公司的算法在还没有发挥绝对的量子优势的前提下，根据投资者愿意承受的波动程度的不同产生了20％到80％的不等回报。
Not all potential uses are so glamorous. Monte Carlo simulations are often used in regulatory stress tests. Christopher Savoie of Zapata, a quantum-computing firm based in Boston, recalls one bank executive telling him: "Don't bring me trading algorithms, bring me a solution to CCAR (an American stress-test regulation). That stuff eats up half my computing budget."
并非所有的潜在应用都令人如此着迷。蒙特卡罗模拟常用于监管压力测试。克里斯多夫·萨瓦来自一家总部位于波士顿的量子计算公司Zapata，他记得一位银行高管曾对他说：“不用给我交易算法，能想办法让我通过CCAR（美国一项压力测试法规）就行。这玩意儿吃掉了我一半的计算预算。”
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