Make use of time, let not advantage slip

Posted on December 14, 2025 by Nicole Yunger Halpern

During the spring of 2022, I felt as though I kept dashing backward and forward in time.

At the beginning of the season, hay fever plagued me in Maryland. Then, I left to present talks in southern California. There—closer to the equator—rose season had peaked, and wisteria petals covered the ground near Caltech’s physics building. From California, I flew to Canada to present a colloquium. Time rewound as I traveled northward; allergies struck again. After I returned to Maryland, the spring ripened almost into summer. But the calendar backtracked when I flew to Sweden: tulips and lilacs surrounded me again.

Caltech wisteria in April 2022: Thou art lovely and temperate.

The zigzagging through horticultural time disoriented my nose, but I couldn’t complain: it echoed the quantum information processing that collaborators and I would propose that summer. We showed how to improve quantum metrology—our ability to measure things, using quantum detectors—by simulating closed timelike curves.

A closed timelike curve is a trajectory that loops back on itself in spacetime. If on such a trajectory, you’ll advance forward in time, reverse chronological direction to advance backward, and then reverse again. Author Jasper Fforde illustrates closed timelike curves in his novel The Eyre Affair. A character named Colonel Next buys an edition of Shakespeare’s works, travels to the Elizabethan era, bestows them on a Brit called Will, and then returns to his family. Will copies out the plays and stages them. His colleagues publish the plays after his death, and other editions ensue. Centuries later, Colonel Next purchases one of those editions to take to the Elizabethan era.¹

Closed timelike curves can exist according to Einstein’s general theory of relativity. But do they exist? Nobody knows. Many physicists expect not. But a quantum system can simulate a closed timelike curve, undergoing a process modeled by the same mathematics.

How can one formulate closed timelike curves in quantum theory? Oxford physicist David Deutsch proposed one formulation; a team led by MIT’s Seth Lloyd proposed another. Correlations distinguish the proposals.

Two entities share correlations if a change in one entity tracks a change in the other. Two classical systems can correlate; for example, your brain is correlated with mine, now that you’ve read writing I’ve produced. Quantum systems can correlate more strongly than classical systems can, as by entangling.

Suppose Colonel Next correlates two nuclei and gives one to his daughter before embarking on his closed timelike curve. Once he completes the loop, what relationship does Colonel Next’s nucleus share with his daughter’s? The nuclei retain the correlations they shared before Colonel Next entered the loop, according to Seth and collaborators. When referring to closed timelike curves from now on, I’ll mean ones of Seth’s sort.

We can simulate closed timelike curves by subjecting a quantum system to a circuit of the type illustrated below. We read the diagram from bottom to top. Along this direction, time—as measured by a clock at rest with respect to the laboratory—progresses. Each vertical wire represents a qubit—a basic unit of quantum information, encoded in an atom or a photon or the like. Each horizontal slice of the diagram represents one instant.

At the bottom of the diagram, the two vertical wires sprout from one curved wire. This feature signifies that the experimentalist prepares the qubits in an entangled state, represented by the symbol $| \Psi_- \rangle$ . Farther up, the left-hand wire runs through a box. The box signifies that the corresponding qubit undergoes a transformation (for experts: a unitary evolution).

At the top of the diagram, the vertical wires fuse again: the experimentalist measures whether the qubits are in the state they began in. The measurement is probabilistic; we (typically) can’t predict the outcome in advance, due to the uncertainty inherent in quantum physics. If the measurement yields the yes outcome, the experimentalist has simulated a closed timelike curve. If the no outcome results, the experimentalist should scrap the trial and try again.

So much for interpreting the diagram above as a quantum circuit. We can reinterpret the illustration as a closed timelike curve. You’ve probably guessed as much, comparing the circuit diagram to the depiction, farther above, of Colonel Next’s journey. According to the second interpretation, the loop represents one particle’s trajectory through spacetime. The bottom and top show the particle reversing chronological direction—resembling me as I flew to or from southern California.

Me in southern California in spring 2022. Photo courtesy of Justin Dressel.

How can we apply closed timelike curves in quantum metrology? In Fforde’s books, Colonel Next has a brother, named Mycroft, who’s an inventor.² Suppose that Mycroft is studying how two particles interact (e.g., by an electric force). He wants to measure the interaction’s strength. Mycroft should prepare one particle—a sensor—and expose it to the second particle. He should wait for some time, then measure how much the interaction has altered the sensor’s configuration. The degree of alteration implies the interaction’s strength. The particles can be quantum, if Mycroft lives not merely in Sherlock Holmes’s world, but in a quantum-steampunk one.

But how should Mycroft prepare the sensor—in which quantum state? Certain initial states will enable the sensor to acquire ample information about the interaction; and others, no information. Mycroft can’t know which preparation will work best: the optimal preparation depends on the interaction, which he hasn’t measured yet.

Mycroft, as drawn by Sydney Paget in the 1890s

Mycroft can overcome this dilemma via a strategy published by my collaborator David Arvidsson-Shukur, his recent student Aidan McConnell, and me. According to our protocol, Mycroft entangles the sensor with a third particle. He subjects the sensor to the interaction (coupling the sensor to particle #2) and measures the sensor.

Then, Mycroft learns about the interaction—learns which state he should have prepared the sensor in earlier. He effectively teleports this state backward in time to the beginning-of-protocol sensor, using particle #3 (which began entangled with the sensor).³ Quantum teleportation is a decades-old information-processing task that relies on entanglement manipulation. The protocol can transmit quantum states over arbitrary distances—or, effectively, across time.

We can view Mycroft’s experiment in two ways. Using several particles, he manipulates entanglement to measure the interaction strength optimally (with the best possible precision). This process is mathematically equivalent to another. In the latter process, Mycroft uses only one sensor. It comes forward in time, reverses chronological direction (after Mycroft learns the optimal initial state’s form), backtracks to an earlier time (to when the sensing protocol began), and returns to progressing forward in time (informing Mycroft about the interaction).

Where I stayed in Stockholm. I swear, I’m not making this up.

In Sweden, I regarded my work with David and Aidan as a lark. But it’s led to an experiment, another experiment, and two papers set to debut this winter. I even pass as a quantum metrologist nowadays. Perhaps I should have anticipated the metamorphosis, as I should have anticipated the extra springtimes that erupted as I traveled between north and south. As the bard says, there’s a time for all things.

¹In the sequel, Fforde adds a twist to Next’s closed timelike curve. I can’t speak for the twist’s plausibility or logic, but it makes for delightful reading, so I commend the novel to you.

²You might recall that Sherlock Holmes has a brother, named Mycroft, who’s an inventor. Why? In Fforde’s novel, an evil corporation pursues Mycroft, who’s built a device that can transport him into the world of a book. Mycroft uses the device to hide from the corporation in Sherlock Holmes’s backstory.

³Experts, Mycroft implements the effective teleportation as follows: He prepares a fourth particle in the ideal initial sensor state. Then, he performs a two-outcome entangling measurement on particles 3 and 4: he asks “Are particles 3 and 4 in the state in which particles 1 and 3 began?” If the measurement yields the yes outcome, Mycroft has effectively teleported the ideal sensor state backward in time. He’s also simulated a closed timelike curve. If the measurement yields the no outcome, Mycroft fails to measure the interaction optimally. Figure 1 in our paper synopsizes the protocol.

Can AI Predict the Quantum Universe?

Posted on December 11, 2025 by robbieking1000

AI promises to revolutionize the way we do science, which raises a central technological question of our time: Can classical AI understand all natural phenomena, or are some fundamentally beyond its reach? Many proponents of artificial intelligence argue that any pattern that can be generated or found in nature can be efficiently discovered and modeled by a classical learning algorithm, implying that AI is a universal and sufficient tool for science.

The word “classical” is important here to contrast with quantum computation. Nature is quantum mechanical, and the insights of Shor’s algorithm [1] along with quantum error correction [2,3,4] teach us that there are quantum systems, at least ones that have been heavily engineered, that can have trajectories that are fundamentally unpredictable¹ by any classical algorithm, including AI. This opens the possibility that there are complex quantum phenomena occurring naturally in our universe where classical AI is insufficient, and we need a quantum computer in order to model them.

This essay uses the perspective of computational complexity to unpack this nuanced question. We begin with quantum sampling, arguing that despite clear quantum supremacy, it does not represent a real hurdle for AI to predict quantum phenomena. We then shift to the major unsolved problems in quantum physics and quantum chemistry, examining how quantum computers could empower AI in these domains. Finally, we’ll consider the possibility of truly complex quantum signals in nature, where quantum computers might prove essential for prediction itself.

Quantum Sampling

In 2019 Google demonstrated quantum supremacy on a digital quantum device [5], and in 2024 their latest chip performed a task in minutes where our best classical computers would take 10^25 years [6]. The task they performed is to prepare a highly entangled many-body quantum state and to sample from the corresponding distribution over classical configurations. Quantum supremacy on such sampling problems is on firm ground, with results in complexity theory backing up the experimental claims [7].² Moreover, the classical hardness of quantum sampling appears to be generic in quantum physics. A wide range of quantum systems will generate highly entangled many-body states where sampling becomes classically hard.

However, quantum sampling alone does not refute the universality of classical AI. The output of quantum sampling often appears completely featureless, which cannot be verified by any classical or quantum algorithm, or by any process in our universe for that matter. For example, running the exact same sampling task a second time will produce a list of configurations that will appear unrelated to the original. In order for a phenomenon to be subject to scientific prediction, there must be an experiment that can confirm or deny the prediction. So if quantum sampling has no features that can be experimentally verified, there is nothing to predict, and no pattern for the AI to discover and model.

Quantum Chemistry and Condensed Matter Physics

There are many unsolved problems in quantum chemistry and condensed matter physics that are inaccessible using our best classical simulation algorithms and supercomputers. For example, these occur in the strongly correlated regime of electronic structure in quantum chemistry, and around low-temperature phase transitions of condensed matter systems. We do not understand the electronic structure of FeMoco, the molecule responsible for nitrogen fixation in the nitrogenase enzyme, nor do we understand the phase diagram of the 2D Fermi-Hubbard lattice and whether or not it exhibits superconductivity.

It is possible there are no fundamental barriers for a sufficiently advanced AI to solve these problems. Researchers in the field have achieved major breakthroughs using neural networks to predict complex biological structures like protein folding. One could imagine similar specialized AI models that predict the electronic structure of molecules, or that predict quantum phases of matter. Perhaps the main reason it is currently out of reach is a lack of sufficient training data. Here lies a compelling opportunity for quantum computing: The only feasible way to generate an abundance of accurate training data may be to use a quantum computer, since physical experiments are too difficult, too unreliable, and too slow.

How should we view these problems in physics and chemistry from the perspective of computational complexity? Physicists and chemists often consider systems with a fixed number of parameters, or even single instances. Although computing physical quantities may be extremely challenging, single instances cannot form computationally hard problems, since ultimately only a constant amount of resources is required to solve it. Systems with a fixed number of parameters often behave similarly, since physical quantities tend to depend smoothly on the parameters which allows for extrapolation and learning [8]. Here we can recognize a familiar motif from machine learning: Ab initio prediction is challenging, but prediction becomes efficient after learning from data. Quantum computers are useful for generating training data, but then AI is able to learn from this data and perform efficient inference.

Truly Complex Quantum Signals

While AI might be able to learn much of the patterns of physics and chemistry from quantum-generated data, there remains a deeper possibility: The quantum universe may produce patterns that AI cannot compress and understand. If there are quantum systems that display signals that are truly classically complex, then predicting the pattern will require a quantum computer at inference time, not only in training.

We’ll now envision how such a signal could arise. Imagine a family of quantum systems of arbitrary size N, and at each size N there is a number of independent parameters that is polynomial in N, for example the coefficients of a Hamiltonian or the rotation angles of a quantum circuit. Suppose the system has some physical feature whose signal we would like to compute as a function of the parameters, and this signal has the following properties:

(Signal) There is a quantum algorithm that efficiently computes the signal. For example, the signal cannot be exponentially small in N.
(Verifiable) The signal is verifiable, at least by an ideal quantum computer. For example, the task could be to compute an expectation value.
(Typically complex) When the parameters are chosen randomly, the signal is computationally hard to classically compute in the average case.

If these properties hold, then it’s possible that no machine learning model using a polynomial amount of classical compute can perform the task, even with the help of training data.

The requirement of verifiability by a quantum process ensures that the signal being computed is a robust phenomenon where there is some “fact of the matter”, and a prediction can be confirmed or denied by nature. For example, this holds for any task where the output is the expectation value of some observable. The average-case hardness ensures that hard instances really exist and can be easily generated, rather than only existing in some abstract worst-case that cannot be instantiated.

There is a connection between the verifiability of a computation and its utility to us. Suppose we use a computer to help us design a high-temperature superconductor. If our designed material indeed works as a high-temperature superconductor when fabricated, this forms a verification of the predictions made by our computer. Utility implies verifiability, and likewise, unverifiable computations cannot be useful. However, since nature is quantum, a computation need not be classically verifiable in order to be useful, but only quantumly verifiable. In our high-temperature superconductor example, nature has verified our computer by performing a quantum process.

Making progress

John Preskill’s “entanglement frontier” seeks to understand the collective behavior of many interacting quantum particles [10]. In order to shed light on the fundamental limits of classical AI and the utility of quantum computers in this regime, we must understand if the exponential Hilbert space of quantum theory remains mostly hidden, or if it reveals itself in observable phenomena. The search for classically complex signals forms an exciting research program for making progress. Google recently performed the first demonstration of a classically complex signal on a quantum device: The out-of-time-order correlators³ of random quantum circuits [9]. We can seek to find more such examples, first in abstract models, and then in the real world, to understand how abundant they are in nature.

Under widely accepted cryptographic assumptions. ↩︎
Classical computers cannot perform quantum sampling unless the polynomial hierarchy collapses. ↩︎
More precisely, the higher moments of the out-of-time-order correlator. ↩︎

References

[1] Shor, Peter W. “Algorithms for quantum computation: discrete logarithms and factoring.” Proceedings 35th annual symposium on foundations of computer science. Ieee, 1994.

[2] Shor, Peter W. “Scheme for reducing decoherence in quantum computer memory.” Physical review A 52.4 (1995): R2493.

[3] Shor, Peter W. “Fault-tolerant quantum computation.” Proceedings of 37th conference on foundations of computer science. IEEE, 1996.

[4] Kitaev, A. Yu. “Fault-tolerant quantum computation by anyons.” Annals of physics 303.1 (2003): 2-30.

[5] Arute, Frank, et al. “Quantum supremacy using a programmable superconducting processor.” Nature 574.7779 (2019): 505-510.

[6] Morvan, Alexis, et al. “Phase transitions in random circuit sampling.” Nature 634.8033 (2024): 328-333.

[7] Aaronson, Scott, and Alex Arkhipov. “The computational complexity of linear optics.” Proceedings of the forty-third annual ACM symposium on Theory of computing. 2011.

[8] Huang, Hsin-Yuan, et al. “Provably efficient machine learning for quantum many-body problems.” Science 377.6613 (2022): eabk3333.

[9] Abanin, Dmitry A., et al. “Constructive interference at the edge of quantum ergodic dynamics.” arXiv preprint arXiv:2506.10191 (2025).

[10] Preskill, John. “Quantum computing and the entanglement frontier.” arXiv preprint arXiv:1203.5813 (2012).

What distinguishes quantum from classical thermodynamics?

Posted on November 26, 2025 by Nicole Yunger Halpern

Should you require a model for an Oxford don in a play or novel, look no farther than Andrew Briggs. The emeritus professor of nanomaterials speaks with a southern-English accent as crisp as shortbread, exhibits manners to which etiquette influencer William Hanson could aspire, and can discourse about anything from Bantu to biblical Hebrew. I joined Andrew for lunch at St. Anne’s College, Oxford, this month.¹ Over vegetable frittata, he asked me what unifying principle distinguishes quantum from classical thermodynamics.

With a thermodynamic colleague at the Oxford University Museum of Natural History

I’d approached quantum thermodynamics from nearly every angle I could think of. I’d marched through the thickets of derivations and plots; I’d journeyed from subfield to subfield; I’d gazed down upon the discipline as upon a landscape from a hot-air balloon. I’d even prepared a list of thermodynamic tasks enhanced by quantum phenomena: we can charge certain batteries at greater powers if we entangle them than if we don’t, entanglement can raise the amount of heat pumped out of a system by a refrigerator, etc. But Andrew’s question flummoxed me.

I bungled the answer. I toted out the aforementioned list, but it contained examples, not a unifying principle. The next day, I was sitting in an office borrowed from experimentalist Natalia Ares in New College, a Gothic confection founded during the late 1300s (as one should expect of a British college called “New”). Admiring the view of ancient stone walls, I realized how I should have responded the previous day.

View from a window near the office I borrowed in New College. If I could pack that office in a suitcase and carry it home, I would.

My answer begins with a blog post written in response to a quantum-thermodynamics question from a don at another venerable university: Yoram Alhassid. He asked, “What distinguishes quantum thermodynamics to quantum statistical mechanics?” You can read the full response here. Takeaways include thermodynamics’s operational flavor. When using an operational theory, we imagine agents who perform tasks, using given resources. For example, a thermodynamic agent may power a steamboat, given a hot gas and a cold gas. We calculate how effectively the agents can perform those tasks. For example, we compute heat engines’ efficiencies. If a thermodynamic agent can access quantum resources, I’ll call them “quantum thermodynamic.” If the agent can access only everyday resources, I’ll call them “classical thermodynamic.”

A quantum thermodynamic agent may access more resources than a classical thermodynamic agent can. The latter can leverage work (well-organized energy), free energy (the capacity to perform work), information, and more. A quantum agent may access not only those resources, but also entanglement (strong correlations between quantum particles), coherence (wavelike properties of quantum systems), squeezing (the ability to toy with quantum uncertainty as quantified by Heisenberg and others), and more. The quantum-thermodynamic agent may apply these resources as described in the list I rattled off at Andrew.

With Oxford experimentalist Natalia Ares in her lab

Yet quantum phenomena can impede a quantum agent in certain scenarios, despite assisting the agent in others. For example, coherence can reduce a quantum engine’s power. So can noncommutation. Everyday numbers commute under multiplication: 11 times 12 equals 12 times 11. Yet quantum physics features numbers that don’t commute so. This noncommutation underlies quantum uncertainty, quantum error correction, and much quantum thermodynamics blogged about ad nauseam on Quantum Frontiers. A quantum engine’s dynamics may involve noncommutation (technically, the Hamiltonian may contain terms that fail to commute with each other). This noncommutation—a fairly quantum phenomenon—can impede the engine similarly to friction. Furthermore, some quantum thermodynamic agents must fight decoherence, the leaking of quantum information from a quantum system into its environment. Decoherence needn’t worry any classical thermodynamic agent.

In short, quantum thermodynamic agents can benefit from more resources than classical thermodynamic agents can, but the quantum agents also face more threats. This principle might not encapsulate how all of quantum thermodynamics differs from its classical counterpart, but I think the principle summarizes much of the distinction. And at least I can posit such a principle. I didn’t have enough experience when I first authored a blog post about Oxford, in 2013. People say that Oxford never changes, but this quantum thermodynamic agent does.

In the University of Oxford Natural History Museum in 2013, 2017, and 2025. I’ve published nearly 150 Quantum Frontiers posts since taking the first photo!

¹Oxford consists of colleges similarly to how neighborhoods form a suburb. Residents of multiple neighborhoods may work in the same dental office. Analogously, faculty from multiple colleges may work, and undergraduates from multiple colleges may major, in the same department.

The sequel

Posted on October 26, 2025 by Nicole Yunger Halpern

This October, fantasy readers are devouring a sequel: the final installment in Philip Pullman’s trilogy The Book of Dust. The series follows student Lyra Silvertongue as she journeys from Oxford to the far east. Her story features alternate worlds, souls that materialize as talking animals, and a whiff of steampunk. We first met Lyra in the His Dark Materials trilogy, which Pullman began publishing in 1995. So some readers have been awaiting the final Book of Dust volume for 30 years.

Another sequel debuts this fall. It won’t spur tens of thousands of sales; nor will Michael Sheen narrate an audiobook version of it. Nevertheless, the sequel should provoke as much thought as Pullman’s: the sequel to the Maryland Quantum-Thermodynamics Hub’s first three years.

More deserving of a Carnegie Medal than our hub, but the hub deserves no less enthusiasm!

The Maryland Quantum-Thermodynamics Hub debuted in 2022, courtesy of a grant from the John F. Templeton Foundation. Six theorists, three based in Maryland, have formed the hub’s core. Our mission has included three prongs: research, community building, and outreach. During the preceding decade, quantum thermodynamics had exploded, but mostly outside North America. We aimed to provide a lodestone for the continent’s quantum-thermodynamics researchers and visitors.

Also, we aimed to identify the thermodynamics of how everyday, classical physics emerges from quantum physics. Quantum physics is reversible (doesn’t distinguish the past from the future), is delicate (measuring a quantum system can disturb it), and features counterintuitive phenomena such as entanglement. In contrast, our everyday experiences include irreversibility (time has an arrow), objectivity (if you and I read this article, we should agree about its contents), and no entanglement. How does quantum physics give rise to classical physics at large energy and length scales? Thermodynamics has traditionally described macroscopic, emergent properties. So quantum thermodynamics should inform our understanding of classical reality’s emergence from quantum mechanics.

Our team has approached this opportunity from three perspectives. One perspective centers on quantum Darwinism, a framework for quantifying how interactions spread information about an observed quantum system. Another perspective highlights decoherence, the contamination of a quantum system by its environment. The third perspective features incompatible exchanged quantities, described in an earlier blog post. Or two. Or at least seven.

Each perspective led us to discover a tension, or apparent contradiction, that needs resolving. One might complain that we failed to clinch a quantum-thermodynamic theory of the emergence of classical reality. But physicists adore apparent contradictions as publishers love splashing “New York Times bestseller” on their book covers. So we aim to resolve the tensions over the next three years.

Physicists savor paradoxes and their ilk.

I’ll illustrate the tensions with incompatible exchanged quantities, of course. Physicists often imagine a small system, such as a quantum computer, interacting with a large environment, such as the surrounding air and the table on which the quantum computer sits. The system and environment may exchange energy, particles, electric charge, etc. Typically, the small system thermalizes, or reaches a state mostly independent of its initial conditions. For example, after exchanging enough energy with its environment, the system ends up at the environment’s temperature, mostly regardless of the system’s initial temperature.

For decades, physicists implicitly assumed that the exchanged quantities are compatible: one can measure them simultaneously. But one can’t measure all of a quantum system’s properties simultaneously. Position and momentum form the most famous examples. Incompatibility epitomizes quantum physics, underlying Heisenberg’s uncertainty relation, quantum error correction, and more. So collaborators and I ask how exchanged quantities’ incompatibility alters thermalization, which helps account for time’s arrow.

Our community has discovered that such incompatibility can hinder certain facets of thermalization—in a sense, stave off certain aspects of certain quantum systems’ experience of time. But incompatible exchanged quantities enhance other features of thermalization. How shall we reconcile the hindrances with the enhancements? Does one of the two effects win out? I hope to report back in three years. For now, I’m rooting for Team Hindrance.

In addition to resolving apparent conflicts, we’re adding a fourth perspective to our quiver—a gravitational one. In our everyday experiences, space-time appears smooth; unlike Lyra’s companion Will in The Subtle Knife, we don’t find windows onto other worlds. But quantum physics, combined with general relativity, suggests that you’d find spikes and dips upon probing space-time over extremely short length scales. How does smooth space-time emerge from its quantum underpinnings? Again, quantum thermodynamics should help us understand.

To address these challenges, we’re expanding the hub’s cast of characters. The initial cast included six theorists. Two more are joining the crew, together with the hub’s first two experimentalists. So is our first creative-writing instructor, who works at the University of Maryland (UMD) Jiménez-Porter Writers’ House.

As the hub has grown, so has the continent’s quantum-thermodynamics community. We aim to continue expanding that community and strengthening its ties to counterparts abroad. As Lyra learned in Pullman’s previous novel, partnering with Welsh miners and Czech book sellers and Smyrnan princesses can further one’s quest. I don’t expect the Maryland Quantum-Thermodynamics Hub to attract Smyrnan princesses, but a girl can dream. The hub is already partnering with the John F. Templeton Foundation, Normal Computing, the Fidelity Center for Applied Technology, the National Quantum Laboratory, Maryland’s Capital of Quantum team, and more. We aim to integrate quantum thermodynamics into North America’s scientific infrastructure, so that the field thrives here even after our new grant terminates. Reach out if you’d like to partner with us.

To unite our community, the hub will host a gathering—a symposium or conference—each year. One conference will feature quantum thermodynamics and quantum-steampunk creative writing. Scientists and authors will present. We hope that both groups will inspire each other, as physicist David Deutsch’s work on the many-worlds formulation of quantum theory inspired Pullman.

That conference will follow a quantum-steampunk creative-writing course to take place at UMD during spring 2026. I’ll co-teach the course with creative-writing instructor Edward Daschle. Students will study quantum thermodynamics, read published science-fiction stories, write quantum-steampunk stories, and critique each other’s writing. Five departments have cross-listed the course: physics, arts and humanities, computer science, chemistry, and mechanical engineering. If you’re a UMD student, you can sign up in a few weeks. Do so early; seats are limited! We welcome graduate students and undergrads, the latter of whom can earn a GSSP general-education credit.¹ Through the course, the hub will spread quantum thermodynamics into Pullman’s world—into literature.

Pullman has entitled his latest novel The Rose Field. The final word refers to an object studied by physicists. A field, such as an electric or gravitational field, is a physical influence spread across space. Hence fiction is mirroring physics—and physics can take its cue from literature. As ardently as Lyra pursues the mysterious particle called Dust, the Maryland Quantum-Thermodynamics Hub is pursuing a thermodynamic understanding of the classical world’s emergence from quantum physics. And I think our mission sounds as enthralling as Lyra’s. So keep an eye on the hub for physics, community activities, and stories. The telling of Lyra’s tale may end this month, but the telling of the hub’s doesn’t.

¹Just don’t ask me what GSSP stands for.

Blending science with fiction in Baltimore

Posted on September 21, 2025 by Nicole Yunger Halpern

I judge a bookstore by the number of Diana Wynne Jones novels it stocks. The late British author wrote some of the twentieth century’s most widely lauded science-fiction and fantasy (SFF). She clinched more honors than I should list, including two World Fantasy Awards. Neil Gaiman, author of American Gods, called her “the best children’s writer of the last forty years” in 2010—and her books suit children of all ages.¹ But Wynne Jones passed away as I was finishing college, and her books have been disappearing from American bookshops. The typical shop stocks, at best, a book in the series she began with Howl’s Moving Castle, which Hayao Miyazaki adapted into an animated film.

I don’t recall the last time I glimpsed Deep Secret in a bookshop, but it ranks amongst my favorite Wynne Jones books—and favorite books, full-stop. So I relished living part of that book this spring.

Deep Secret centers on video-game programmer Rupert Venables. Outside of his day job, he works as a Magid, a magic user who helps secure peace and progress across the multiple worlds. Another Magid has passed away, and Rupert must find a replacement for him. How does Rupert track down and interview his candidates? By consolidating their fate lines so that the candidates converge on an SFF convention. Of course.

My fate line drew me to an SFF convention this May. Balticon takes place annually in Baltimore, Maryland. It features not only authors, agents, and publishers, but also science lecturers. I received an invitation to lecture about quantum steampunk—not video-game content,² but technology-oriented like Rupert’s work. I’d never attended an SFF convention,³ so I reread Deep Secret as though studying for an exam.

Rupert, too, is attending his first SFF convention. A man as starched as his name sounds, Rupert packs suits, slacks, and a polo-neck sweater for the weekend—to the horror of a denim-wearing participant. I didn’t bring suits, in my defense. But I did dress business-casual, despite having anticipated that jeans, T-shirts, and capes would surround me.

I checked into a Renaissance Hotel for Memorial Day weekend, just as Rupert checks into the Hotel Babylon for Easter weekend. Like him, I had to walk an inordinately long distance from the elevators to my room. But Rupert owes his trek to whoever’s disrupted the magical node centered on his hotel. My hotel’s architects simply should have installed more elevator banks.

Balticon shared much of its anatomy with Rupert’s con, despite taking place in a different century and country (not to mention world). Participants congregated downstairs at breakfast (continental at Balticon, waitered at Rupert’s hotel). Lectures and panels filled most of each day. A masquerade took place one night. (I slept through Balticon’s; impromptu veterinary surgery occupies Rupert during his con’s.) Participants vied for artwork at an auction. Booksellers and craftspeople hawked their wares in a dealer’s room. (None of Balticon’s craftspeople knew their otherworldly subject matter as intimately as Rupert’s Magid colleague Zinka Fearon does, I trust. Zinka paints her off-world experiences when in need of cash.)

In our hotel room, I read out bits of Deep Secret to my husband, who confirmed the uncanniness with which they echoed our experiences. Both cons featured floor-length robes, Batman costumes, and the occasional slinky dress. Some men sported long-enough locks, and some enough facial hair, to do a Merovingian king proud. Rupert registers “a towering papier-mâché and plastic alien” one night; on Sunday morning, a colossal blow-up unicorn startled my husband and me. We were riding the elevator downstairs to breakfast, pausing at floor after floor. Hotel guests packed the elevator like Star Wars fans at a Lucasfilm debut. Then, the elevator halted again. The doors opened on a bespectacled man, 40-something years old by my estimate, dressed as a blue-and-white unicorn. The costume billowed out around him; the golden horn towered multiple feet above his head. He gazed at our sardine can, and we gazed at him, without speaking. The elevator doors shut, and we continued toward breakfast.

Despite having read Deep Secret multiple times, I savored it again. I even laughed out loud. Wynne Jones paints the SFF community with the humor, exasperation, and affection one might expect of a middle-school teacher contemplating her students. I empathize, belonging to a community—the physics world—nearly as idiosyncratic as the SFF community.⁴ Wynne Jones’s warmth for her people suffuses Deep Secret; introvert Rupert surprises himself by enjoying a dinner with con-goers and wishing to spend more time with them. The con-goers at my talk exhibited as much warmth as any audience I’ve spoken to, laughing, applauding, and asking questions. I appreciated sojourning in their community for a weekend.⁵

This year, my community is fêting the physicists who founded quantum theory a century ago. Wynne Jones sparked imaginations two decades ago. Let’s not let her memory slip from our fingertips like a paperback over which we’re falling asleep. After all, we aren’t forgetting Louis de Broglie, Paul Dirac, and their colleagues. So check out a Wynne Jones novel the next time you visit a library, or order a novel of hers to your neighborhood bookstore. Deep Secret shouldn’t be an actual secret.

With thanks to Balticon’s organizers, especially Miriam Winder Kelly, for inviting me and for fussing over their speakers’ comfort like hens over chicks.

¹Wynne Jones dedicated her novel Hexwood to Gaiman, who expressed his delight in a poem. I fancy the comparison of Gaiman, a master of phantasmagoria and darkness, to a kitten.

²Yet?

³I’d attended a steampunk convention, and spoken at a Boston SFF convention, virtually. But as far as such conventions go, attending virtually is to attending in person as my drawings are to a Hayao Miyazaki film.

⁴But sporting fewer wizard hats.

⁵And I wonder what the Diana Wynne Jones Conference–Festival is like.

John Preskill receives 2025 Quantum Leadership Award

Posted on September 18, 2025 by preskill

The 2025 Quantum Leadership Awards were announced at the Quantum World Congress on 18 September 2025. Upon receiving the Academic Pioneer in Quantum Award, John Preskill made these remarks.

I’m enormously excited and honored to receive this Quantum Leadership Award, and especially thrilled to receive it during this, the International Year of Quantum. The 100^th anniversary of the discovery of quantum mechanics is a cause for celebration because that theory provides our deepest and most accurate description of how the universe works, and because that deeper understanding has incalculable value to humanity. What we have learned about electrons, photons, atoms, and molecules in the past century has already transformed our lives in many ways, but what lies ahead, as we learn to build and precisely control more and more complex quantum systems, will be even more astonishing.

As a professor at a great university, I have been lucky in many ways. Lucky to have the freedom to pursue the scientific challenges that I find most compelling and promising. Lucky to be surrounded by remarkable, supportive colleagues. Lucky to have had many collaborators who enabled me to do things I could never have done on my own. And lucky to have the opportunity to teach and mentor young scientists who have a passion for advancing the frontiers of science. What I’m most proud of is the quantum community we’ve built at Caltech, and the many dozens of young people who imbibed the interdisciplinary spirit of Caltech and then moved onward to become leaders in quantum science at universities, labs, and companies all over the world.

Right now is a thrilling time for quantum science and technology, a time of rapid progress, but these are still the early days in a nascent second quantum revolution. In quantum computing, we face two fundamental questions: How can we scale up to quantum machines that can solve very hard computational problems? And once we do so, what will be the most important applications for science and for industry? We don’t have fully satisfying answers yet to either question and we won’t find the answers all at once – they will unfold gradually as our knowledge and technology advance. But 10 years from now we’ll have much better answers than we have today.

Companies are now pursuing ambitious plans to build the world’s most powerful quantum computers. Let’s not forget how we got to this point. It was by allowing some of the world’s most brilliant people to follow their curiosity and dream about what the future could bring. To fulfill the potential of quantum technology, we need that spirit of bold adventure now more than ever before. This award honors one scientist, and I’m profoundly grateful for this recognition. But more importantly it serves as a reminder of the vital ongoing need to support the fundamental research that will build foundations for the science and technology of the future. Thank you very much!

Nicole’s guide to writing research statements

Posted on August 10, 2025 by Nicole Yunger Halpern

Sunflowers are blooming, stores are trumpeting back-to-school sales, and professors are scrambling to chart out the courses they planned to develop in July. If you’re applying for an academic job this fall, now is the time to get your application ducks in a row. Seeking a postdoctoral or faculty position? Your applications will center on research statements. Often, a research statement describes your accomplishments and sketches your research plans. What do evaluators look for in such documents? Here’s my advice, which targets postdoctoral fellowships and faculty positions, especially for theoretical physicists.

Keep your audience in mind. Will a quantum information theorist, a quantum scientist, a general physicist, a general scientist, or a general academic evaluate your statement? What do they care about? What technical language do and don’t they understand?

What thread unites all the projects you’ve undertaken? Don’t walk through your research history chronologically, stepping from project to project. Cast the key projects in the form of a story—a research program. What vision underlies the program?

Here’s what I want to see when I read a description of a completed project.
- The motivation for the project: This point ensures that the reader will care enough to read the rest of the description.
- Crucial background information
- The physical setup
- A statement of the problem
- Why the problem is difficult or, if relevant, how long the problem has remained open
- Which mathematical toolkit you used to solve the problem or which conceptual insight unlocked the solution
- Which technical or conceptual contribution you provided
- Whom you collaborated with: Wide collaboration can signal a researcher’s maturity. If you collaborated with researchers at other institutions, name the institutions and, if relevant, their home countries. If you led the project, tell me that, too. If you collaborated with a well-known researcher, mentioning their name might help the reader situate your work within the research landscape they know. But avoid name-dropping, which lacks such a pedagogical purpose and which can come across as crude.
- Your result’s significance/upshot/applications/impact: Has a lab based an experiment on your theoretical proposal? Does your simulation method outperform its competitors by X% in runtime? Has your mathematical toolkit found applications in three subfields of quantum physics? Consider mentioning whether a competitive conference or journal has accepted your results: QIP, STOC, Physical Review Letters, Nature Physics, etc. But such references shouldn’t serve as a crutch in conveying your results’ significance. You’ll impress me most by dazzling me with your physics; name-dropping venues instead can convey arrogance.

Not all past projects deserve the same amount of space. Tell a cohesive story. For example, you might detail one project, then synopsize two follow-up projects in two sentences.

A research statement must be high-level, because you don’t have space to provide details. Use mostly prose; and communicate intuition, including with simple examples. But sprinkle in math, such as notation that encapsulates a phrase in one concise symbol.
Be concrete, and illustrate with examples. Many physicists—especially theorists—lean toward general, abstract statements. The more general a statement is, we reason, the more systems it describes, so the more powerful it is. But humans can’t visualize and intuit about abstractions easily. Imagine a reader who has four minutes to digest your research statement before proceeding to the next 50 applications. As that reader flys through your writing, vague statements won’t leave much of an impression. So draw, in words, a picture that readers can visualize. For instance, don’t describe only systems, subsystems, and control; invoke atoms, cavities, and lasers. After hooking your reader with an image, you can generalize from it.

A research statement not only describes past projects, but also sketches research plans. Since research covers terra incognita, though, plans might sound impossible. How can you predict the unknown—especially the next five years of the unknown (as required if you’re applying for a faculty position), especially if you’re a theorist? Show that you’ve developed a map and a compass. Sketch the large-scale steps that you anticipate taking. Which mathematical toolkits will you leverage? What major challenge do you anticipate, and how do you hope to overcome it? Let me know if you’ve undertaken preliminary studies. Do numerical experiments support a theorem you conjecture?

When I was applying for faculty positions, a mentor told me the following: many a faculty member can identify a result (or constellation of results) that secured them an offer, as well as a result that earned them tenure. Help faculty-hiring committees identify the offer result and the tenure result.

Introduce notation before using it. If you use notation and introduce it afterward, the reader will encounter the notation; stop to puzzle over it; tentatively continue; read the introduction of the notation; return to the earlier use of the notation, to understand it; and then continue forward, including by rereading the introduction of the notation. This back-and-forth breaks up the reading process, which should flow smoothly.

Begin every paragraph with a topic sentence.

Avoid verbs that fail to relate that you accomplished anything: “studied,” “investigated,” “worked on,” etc. What did you prove, show, demonstrate, solve, calculate, compute, etc.?
Tailor a version of your research statement to every position. Is Fellowship Committee X seeking biophysicists, statistical physicists, mathematical physicists, or interdisciplinary scientists? Also, respect every application’s guidelines about length.

If you have room, end the statement with a recap and a statement of significance. Yes, you’ll be repeating ideas mentioned earlier. But your reader’s takeaway hinges on the last text they read. End on a strong note, presenting a coherent vision.
Read examples. Which friends and colleagues, when applying for positions, have achieved success that you’d like to emulate? Ask if those individuals would share their research statements. Don’t take offense if they refuse; research statements are personal.
Writing is rewriting, a saying goes. Draft your research statement early, solicit feedback from a couple of mentors, edit the draft, and solicit more feedback.

Little ray of sunshine

Posted on July 27, 2025 by Nicole Yunger Halpern

A common saying goes, you should never meet your heroes, because they’ll disappoint you. But you shouldn’t trust every common saying; some heroes impress you more, the better you know them. Ray Laflamme was such a hero.

I first heard of Ray in my undergraduate quantum-computation course. The instructor assigned two textbooks: the physics-centric “Schumacher and Westmoreland” and “Kaye, Laflamme, and Mosca,” suited to computer scientists. Back then—in 2011—experimentalists were toiling over single quantum logic gates, implemented on pairs and trios of qubits. Some of today’s most advanced quantum-computing platforms, such as ultracold atoms, resembled the scrawnier of the horses at a racetrack. My class studied a stepping stone to those contenders: linear quantum optics (quantum light). Laflamme, as I knew him then, had helped design the implementation.

Imagine my awe upon meeting Ray the following year, as a master’s student at the Perimeter Institute for Theoretical Physics. He belonged to Perimeter’s faculty and served as a co-director of the nearby Institute for Quantum Computing (IQC). Ray was slim, had thinning hair of a color similar to mine, and wore rectangular glasses frames. He often wore a smile, too. I can hear his French-Canadian accent in my memory, but not without hearing him smile at the ends of most sentences.

My master’s program entailed a research project, which I wanted to center on quantum information theory, one of Ray’s specialties. He met with me and suggested a project, and I began reading relevant papers. I then decided to pursue research with another faculty member and a postdoc, eliminating my academic claim on Ray’s time. But he agreed to keep meeting with me. Heaven knows how he managed; institute directorships devour one’s schedule like ravens dining on a battlefield. Still, we talked approximately every other week.

My master’s program intimidated me, I confessed. It crammed graduate-level courses, which deserved a semester each, into weeks. My class raced through Quantum Field Theory I and Quantum Field Theory II—a year’s worth of material—in part of an autumn. General relativity, condensed matter, and statistical physics swept over us during the same season. I preferred to learn thoroughly, deeply, and using strategies I’d honed over two decades. But I didn’t have time, despite arriving at Perimeter’s library at 8:40 every morning and leaving around 9:30 PM.

In response, Ray confessed that his master’s program had intimidated him. Upon completing his undergraduate degree, Ray viewed himself as a nobody from nowhere. He chafed in the legendary, if idiosyncratically named, program he attended afterward: Part III of the Mathematical Tripos at the University of Cambridge. A Cambridge undergraduate can earn a master’s degree in three steps (tripos) at the Department of Applied Mathematics and Theoretical Physics. Other students, upon completing bachelor’s degrees elsewhere, undertake the third step to earn their master’s. Ray tackled this step, Part III.

He worked his rear off, delving more deeply into course material than lecturers did. Ray would labor over every premise in a theorem’s proof, including when nobody could explain the trickiest step to him.¹ A friend and classmate helped him survive. The two studied together, as I studied with a few fellow Perimeter students; and Ray took walks with his friend on Sundays, as I planned lunches with other students on weekends.

Yet the program’s competitiveness appalled Ray. All students’ exam scores appeared on the same piece of paper, posted where everyone could read it. The department would retain the highest scorers in its PhD program; the other students would have to continue their studies elsewhere. Hearing about Ray’s program, I appreciated more than ever the collaboration characteristic of mine.

Ray addressed that trickiest proof step better than he’d feared, come springtime: his name appeared near the top of the exam list. Once he saw the grades, a faculty member notified him that his PhD advisor was waiting upstairs. Ray didn’t recall climbing those stairs, but he found Stephen Hawking at the top.

As one should expect of a Hawking student, Ray studied quantum gravity during his PhD. But by the time I met him, Ray had helped co-found quantum computation. He’d also extended his physics expertise as far from 1980s quantum gravity as one can, by becoming an experimentalist. The nobody from nowhere had earned his wings—then invented novel wings that nobody had dreamed of. But he descended from the heights every other week, to tell stories to a nobody of a master’s student.

The author’s copy of “Kaye, Laflamme, and Mosca”…

Seven and a half years later, I advertised openings in the research group I was establishing in Maryland. A student emailed from the IQC, whose co-directorship Ray had relinquished in 2017. The student had seen me present a talk, it had inspired him to switch fields into quantum thermodynamics, and he asked me to co-supervise his PhD. His IQC supervisor had blessed the request: Ray Laflamme.

The student was Shayan Majidy, now a postdoc at Harvard. Co-supervising him with Ray Laflamme reminded me of cooking in the same kitchen as Julia Child. I still wonder how I, green behind the ears, landed such a gig. Shayan delighted in describing the difference between his supervisors’ advising styles. An energetic young researcher,² I’d respond to emails as early as 6:00 AM. I’d press Shayan about literature he’d read, walk him through what he hadn’t grasped, and toss a paper draft back and forth with him multiple times per day. Ray, who’d mellowed during his career, mostly poured out support and warmth like hollandaise sauce.

Once, Shayan emailed Ray and me to ask if he could take a vacation. I responded first, as laconically as my PhD advisor would have: “Have fun!” Ray replied a few days later. He elaborated on his pleasure at Shayan’s plans and on how much Shayan deserved the break.

When I visited Perimeter in 2022, Shayan insisted on a selfie with both his PhD advisors.

This June, an illness took Ray earlier than expected. We physicists lost an intellectual explorer, a co-founder of the quantum-computing community, and a scientist of my favorite type: a wonderful physicist who was a wonderful human being. Days after he passed, I was holed up in a New York hotel room, wincing over a web search. I was checking whether a quantum system satisfies certain tenets of quantum error correction, and we call those tenets the Knill–Laflamme conditions. Our community will keep checking the Knill–Laflamme conditions, keep studying quantum gates implementable with linear optics, and more. Part of Ray won’t leave us anytime soon—the way he wouldn’t leave a nobody of a master’s student who needed a conversation.

¹For the record, some of the most rigorous researchers I know work in Cambridge’s Department of Applied Mathematics and Theoretical Physics today. I’ve even blogged about some.

²As I still am, thank you very much.

A (quantum) complex legacy: Part trois

Posted on June 22, 2025 by Nicole Yunger Halpern

When I worked in Cambridge, Massachusetts, a friend reported that MIT’s postdoc association had asked its members how it could improve their lives. The friend confided his suggestion to me: throw more parties.¹ This year grants his wish on a scale grander than any postdoc association could. The United Nations has designated 2025 as the International Year of Quantum Science and Technology (IYQ), as you’ve heard unless you live under a rock (or without media access—which, come to think of it, sounds not unappealing).

A metaphorical party cracker has been cracking since January. Governments, companies, and universities are trumpeting investments in quantum efforts. Institutions pulled out all the stops for World Quantum Day, which happens every April 14 but which scored a Google doodle this year. The American Physical Society (APS) suffused its Global Physics Summit in March with quantum science like a Bath & Body Works shop with the scent of Pink Pineapple Sunrise. At the summit, special symposia showcased quantum research, fellow blogger John Preskill dished about quantum-science history in a dinnertime speech, and a “quantum block party” took place one evening. I still couldn’t tell you what a quantum block party is, but this one involved glow sticks.

Attending the summit, I felt a satisfaction—an exultation, even—redolent of twelfth grade, when American teenagers summit the Mont Blanc of high school. It was the feeling that this year is our year. Pardon me while I hum “Time of your life.”²

Speakers and organizer of a Kavli Symposium, a special session dedicated to interdisciplinary quantum science, at the APS Global Physics Summit

Just before the summit, editors of the journal PRX Quantum released a special collection in honor of the IYQ.³ The collection showcases a range of advances, from chemistry to quantum error correction and from atoms to attosecond-length laser pulses. Collaborators and I contributed a paper about quantum complexity, a term that has as many meanings as companies have broadcast quantum news items within the past six months. But I’ve already published two Quantum Frontiers posts about complexity, and you surely study this blog as though it were the Bible, so we’re on the same page, right?

Just joshing.

Imagine you have a quantum computer that’s running a circuit. The computer consists of qubits, such as atoms or ions. They begin in a simple, “fresh” state, like a blank notebook. Post-circuit, they store quantum information, such as entanglement, as a notebook stores information post-semester. We say that the qubits are in some quantum state. The state’s quantum complexity is the least number of basic operations, such as quantum logic gates, needed to create that state—via the just-completed circuit or any other circuit.

Today’s quantum computers can’t create high-complexity states. The reason is, every quantum computer inhabits an environment that disturbs the qubits. Air molecules can bounce off them, for instance. Such disturbances corrupt the information stored in the qubits. Wait too long, and the environment will degrade too much of the information for the quantum computer to work. We call the threshold time the qubits’ lifetime, among more-obscure-sounding phrases. The lifetime limits the number of gates we can run per quantum circuit.

The ability to perform many quantum gates—to perform high-complexity operations—serves as a resource. Other quantities serve as resources, too, as you’ll know if you’re one of the three diehard Quantum Frontiers fans who’ve been reading this blog since 2014 (hi, Mom). Thermodynamic resources include work: coordinated energy that one can harness directly to perform a useful task, such as lifting a notebook or staying up late enough to find out what a quantum block party is.

My collaborators: Jonas Haferkamp, Philippe Faist, Teja Kothakonda, Jens Eisert, and Anthony Munson (in an order of no significance here)

My collaborators and I showed that work trades off with complexity in information- and energy-processing tasks: the more quantum gates you can perform, the less work you have to spend on a task, and vice versa. Qubit reset exemplifies such tasks. Suppose you’ve filled a notebook with a calculation, you want to begin another calculation, and you have no more paper. You have to erase your notebook. Similarly, suppose you’ve completed a quantum computation and you want to run another quantum circuit. You have to reset your qubits to a fresh, simple state.

Three methods suggest themselves. First, you can “uncompute,” reversing every quantum gate you performed.⁴ This strategy requires a long lifetime: the information imprinted on the qubits by a gate mustn’t leak into the environment before you’ve undone the gate.

Second, you can do the quantum equivalent of wielding a Pink Pearl Paper Mate: you can rub the information out of your qubits, regardless of the circuit you just performed. Thermodynamicists inventively call this strategy erasure. It requires thermodynamic work, just as applying a Paper Mate to a notebook does.

Third, you can

Suppose your qubits have finite lifetimes. You can undo as many gates as you have time to. Then, you can erase the rest of the qubits, spending work. How does complexity—your ability to perform many gates—trade off with work? My collaborators and I quantified the tradeoff in terms of an entropy we invented because the world didn’t have enough types of entropy.⁵

Complexity trades off with work not only in qubit reset, but also in data compression and likely other tasks. Quantum complexity, my collaborators and I showed, deserves a seat at the great soda fountain of quantum thermodynamics.

The great soda fountain of quantum thermodynamics

…as quantum information science deserves a seat at the great soda fountain of physics. When I embarked upon my PhD, faculty members advised me to undertake not only quantum-information research, but also some “real physics,” such as condensed matter. The latter would help convince physics departments that I was worth their money when I applied for faculty positions. By today, the tables have turned. A condensed-matter theorist I know has wound up an electrical-engineering professor because he calculates entanglement entropies.

So enjoy our year, fellow quantum scientists. Party like it’s 1925. Burnish those qubits—I hope they achieve the lifetimes of your life.

¹Ten points if you can guess who the friend is.

²Whose official title, I didn’t realize until now, is “Good riddance.” My conception of graduation rituals has just turned a somersault.

³PR stands for Physical Review, the brand of the journals published by the APS. The APS may have intended for the X to evoke exceptional, but I like to think it stands for something more exotic-sounding, like ex vita discedo, tanquam ex hospitio, non tanquam ex domo.

⁴Don’t ask me about the notebook analogue of uncomputing a quantum state. Explaining it would require another blog post.

⁵For more entropies inspired by quantum complexity, see this preprint. You might recognize two of the authors from earlier Quantum Frontiers posts if you’re one of the three…no, not even the three diehard Quantum Frontiers readers will recall; but trust me, two of the authors have received nods on this blog before.

Congratulations, class of 2025! Words from a new graduate

Posted on June 9, 2025 by jleschack

Editor’s note (Nicole Yunger Halpern): Jade LeSchack, the Quantum Steampunk Laboratory’s first undergraduate, received her bachelor’s degree from the University of Maryland this spring. Kermit the Frog presented the valedictory address, but Jade gave the following speech at the commencement ceremony for the university’s College of Mathematical and Natural Sciences. Jade heads to the University of Southern California for a PhD in physics this fall.

Good afternoon, everyone. My name is Jade, and it is my honor and pleasure to speak before you.

Today, I’m graduating with my Bachelor of Science, but when I entered UMD, I had no idea what it meant to be a professional scientist or where my passion for quantum science would take me. I want you to picture where you were four years ago. Maybe you were following a long-held passion into college, or maybe you were excited to explore a new technical field. Since then, you’ve spent hours titrating solutions, debugging code, peering through microscopes, working out proofs, and all the other things our disciplines require of us. Now, we’re entering a world of uncertainty, infinite possibility, and lifelong connections. Let me elaborate on each of these.

First, there is uncertainty. Unlike simplified projectile motion, you can never predict the exact trajectory of your life or career. Plans will change, and unexpected opportunities will arise. Sometimes, the best path forward isn’t the one you first imagined. Our experiences at Maryland have prepared us to respond to the challenges and curveballs that life will throw at us. And, we’re going to get through the rough patches.

Second, let’s embrace the infinite possibilities ahead of us. While the concept of the multiverse is best left to the movies, it’s exciting to think about all the paths before us. We’ve each found our own special interests over the past four years here, but there’s always more to explore. Don’t put yourself in a box. You can be an artist and a scientist, an entrepreneur and a humanitarian, an athlete and a scholar. Continue to redefine yourself and be open to your infinite potential.

Third, as we move forward, we are equipped not only with knowledge but with connections. We’ve made lasting relationships with incredible people here. As we go from place to place, the people who we’re close to will change. But we’re lucky that, these days, people are only an email or phone call away. We’ll always have our UMD communities rooting for us.

Now, the people we met here are certainly not the only important ones. We’ve each had supporters along the various stages of our journeys. These are the people who championed us, made sacrifices for us, and gave us a shoulder to cry on. I’d like to take a moment to thank all my mentors, teachers, and friends for believing in me. To my mom, dad, and sister sitting up there, I couldn’t have done this without you. Thank you for your endless love and support.

To close, I’d like to consider this age-old question that has always fascinated me: Is mathematics discovered or invented? People have made a strong case for each side. If we think about science in general, and our future contributions to our fields, we might ask ourselves: Are we discoverers or inventors? My answer is both! Everyone here with a cap on their head is going to contribute to both. We’re going to unearth new truths about nature and innovate scientific technologies that better society. This uncertain, multitudinous, and interconnected world is waiting for us, the next generation of scientific thinkers! So let’s be bold and stay fearless.

Congratulations to the class of 2024 and the class of 2025! We did it!

Author’s note: I was deeply grateful for the opportunity to serve as the student speaker at my commencement ceremony. I hope that the science-y references tickle the layman and SME alike. You can view a recording of the speech here. I can’t wait for my next adventures in quantum physics!